WO2025137134A1

WO2025137134A1 - Biomarkers for predicting due date and time to birth

Info

Publication number: WO2025137134A1
Application number: PCT/US2024/060815
Authority: WO
Inventors: Paul Edward Kearney; John Jay BONIFACE; Tracey Cristine FLEISCHER; Andrew Dennis GASSMAN; Mai CORPUZ; Charles Cox; Ashoka Dharmapriya POLPITIYA; Max Taylor Williams DUFFORD
Original assignee: Sera Prognostics Inc
Current assignee: Sera Prognostics Inc
Priority date: 2023-12-18
Filing date: 2024-12-18
Publication date: 2025-06-26
Anticipated expiration: 2026-06-18

Abstract

The present disclosure provides compositions and methods for determing predicted delivery date and time to birth for a pregnancy with significantly higher accuracy than current clinical methods. The compositions and methods for predicted delivery date and time to birth for a pregnancy can also identifiy those pregnancies that will deliver earlier than the due date derived from last menstrual period and/or ultrasound dating.

Description

BIOMARKERS FOR PREDICTING DUE DATE AND TIME TO BIRTH

CROSS REFERENCE TO RELATED APPLICATIONS

[001] This application claims the benefit of priority of U.S. Provisional Application No. 63/611,698, filed December 18, 2023, the entire contents of which is incorporated herein by reference.

INCORPORATION BY REFERENCE OF SEQUENCE LISTING

[002] The instant application contains a Sequence Listing, which has been submitted via Patent Center. The Sequence Listing titled 203123-029002_PCT_SL.xml, which was created on December 17, 2024, and is 109,301 bytes in size, is hereby incorporated by reference in its entirety.

FIELD

[003] The present disclosure relates generally to the field of dating when a pregnant female will deliver her baby and, more specifically, to biomarkers, methods, compositions, and kits for predicting the due date and time to birth in a pregnant female. The present disclosure also relates to biomarkers, methods, compositions, and kits for more accurately dating a pregnancy for a pregnant female.

BACKGROUND

[004] Accurately assigning Estimated Due Date (EDD) and/or Time To Birth (TTB) early in prenatal care can be vital for timing of appropriate obstetric care; scheduling and interpretation of certain antepartum tests; determining the appropriateness of fetal growth; diagnosis of pregnancy complications/outcomes that are dependent on, or defined by gestational age; and designing interventions to prevent preterm births, postterm births, and related morbidities. A consistent and exacting approach to accurate dating can also be useful for a pregnant mother’s personal planning, e.g., travel, maternity leave, and family visits.

[005] Traditionally, determining the first day of the Last Menstrual Period (LMP) is the first step in establishing the EDD. By convention, the EDD is 280 days after the first day of the LMP. Because this practice assumes a regular menstrual cycle of 28 days, with ovulation occurring on the 14th day after the beginning of the menstrual cycle, its accuracy is affected by factors that include inaccurate recall of the LMP, irregularities in cycle length, or variability in the timing of ovulation. The accuracy of delivery prediction may also be influenced by the timing of fertilization, implantation and the rate of fetal development. Obstetric ultrasonography (US) is recommended and frequently used to determine fetal gestational age and aid in assigning EDD. Specifically, it has been found that the accuracy of the EDD can be improved by a few days if fetal crown-rump length is measured by ultrasound between 8 and 12 weeks of gestation (see, e.g., Mongelli, M., M. Wilcox, and J. Gardosi, Estimating the date of confinement: ultrasonographic biometry versus certain menstrual dates. Am J Obstet Gynecol, 1996. 174(1 Pt 1): p. 278-81; Taipale, P. and V. Hiilesmaa, Predicting delivery date by ultrasound and last menstrual period in early gestation. Obstet Gynecol, 2001. 97(2): p. 189-94; and Committee Opinion No 700: Methods for Estimating the Due Date. Obstet Gynecol, 2017. 129(5): p. el50-el54). However, even in developed countries, for instance, many women either lack access to ultrasound in the first trimester or miss this crucial timing window when ultrasound can inform gestational age (see, e.g., Osterman, M.J.K., et al., Births: Final Data for 2022. Natl Vital Stat Rep, 2024. 73(2): p. 1-56), showing that clinical tools other than ultrasound are needed to improve the accuracy of term delivery date prediction.

[006] Moreover, if the individual is unsure of her LMP, dating of EDD based on first trimester US is considered more reliable than second trimester or third semester US. Both LMP and/or US are population-based estimates for a normal pregnancy and the accuracy of these methods varies significantly. Current clinical practice utilizing these methods is accurate in making a prediction that falls within plus or minus five days of the actual delivery date for term deliveries only about 35% of the time. In addition, 15% of predictions made under current clinical practice fall on or outside of 14 days before or after the actual delivery date for term deliveries. More accurate dating of pregnancy is needed to improve clinical outcomes and to help in personal planning. The present disclosure addresses this need and provides related advantages.

SUMMARY

[007] The present disclosure provides compositions and methods useful in predicting delivery date and time to birth for a pregnancy with significantly higher accuracy than current compositions and methods by providing a Predicted Delivery Date (PDD) molecular predictor (PDDmp) and/or a Time To Birth (TTB) molecular predictor (TTBmp) that incorporates molecular information from proteins listed in Table 2 into the prediction of pregnancy delivery date and/or TTB with much higher accuracy than methods utilized as part of current practice. The compositions and methods can also identifiy those pregnancies, with high accuracy, that will deliver earlier than the clinical EDD as derived from LMP and/or US dating. Accordingly, the present disclosure provides an improved process that applies the discoveries described herein to enable, inter alia, new and useful methods for estimating the due date of a pregnant female, subsequently referred to as the PDD and/or estimating TTB with higher accuracy than current compositions and methods.

[008] Each of the proteins or fragments thereof disclosed herein can serve as components of pairs, ratios, and/or reversal pairs that serve as biomarkers for determining PDD, predicting gestational age at birth (GAB), predicting TTB, either individually, in ratios, or in reversal pairs, each of which can be incorporated into a model (e.g., regression formula with or without clinical variables).

[009] The utility of the biomarker pairs, ratios and/or reversal pairs described herein as biomarkers to more accurately date a pregnancy, e.g., accurately estimate gestational age (GA), extends to prognostic, diagnostic, or other clinical assessments of the pregnant female and fetus that relies on accurately estimating GA for its own accuracy. The biomarker compositions and methods using them are also useful for a pregnant mother’s personal planning, e.g., travel, maternity leave, and family visits.

[0010] In some embodiments, the present disclosure provides a method of determining the predicted delivery date (PDD) or time to birth (TTB) for a pregnant female. In some embodiments, the method comprises obtaining a biological sample obtained from said pregnant female, detecting the presence or amount of a pair of isolated biomarkers in said biological sample obtained from said pregnant female, and measuring in said biological sample a reversal value for said pair of isolated biomarkers. In some embodiments, the pair of isolated biomarkers exhibits a change in reversal value between pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days, and Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In yet further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days, Y is no more than 1, 2, 3, or 4 days, and Z is no more than 1, 2, 3, or 4 days. In some embodiments, the pair of isolated biomarkers comprises two isolated biomarkers selected from Table 2.

[0011] In some embodiments, detecting the presence or amount of a pair of isolated biomarkers in the biological sample obtained from the pregnant female comprises subjecting said biological sample to an assay that utilizes a capture agent that binds to at least one biomarker of said pair of isolated biomarkers. In some embodiments, the assay is selected from the group consisting of an enzyme immunoassay (EIA), an enzyme-linked immunosorbent assay (ELISA), and a radioimmunoassay (RIA). In some embodiments, the capture agent is selected from the group consisting of an antibody, antibody fragment, nucleic acid-based protein binding reagent, small molecule or variant thereof. In some embodiments, the capture agent binds to a region of ADA12 comprising the amino acid sequence FGFGGSTDSGPIR (SEQ ID NO: 1) the capture agent binds to a region of KIT comprising the amino acid sequence YVSELHLTR (SEQ ID NO: 2), the capture agent binds to a region of KIT comprising the amino acid sequence LCLHCSVDQEGK (SEQ ID NO: 3), the capture agent binds to a region of FETUA comprising the amino acid sequence FSVVYAK (SEQ ID NO: 4), the capture agent binds to a region of ENPP2 comprising the amino acid sequence TEFLSNYLTNVDDITLVPGTLGR (SEQ ID NO: 5), the capture agent binds to a region of ENPP2 comprising the amino acid sequence TYLHTYESEI (SEQ ID NO: 6), the capture agent binds to a region of A2GL comprising the amino acid sequence DLLLPQPDLR (SEQ ID NO: 7), or the capture agent binds to a region of IGF 1 comprising the amino acid sequence GFYFNKPTGYGSSSR (SEQ ID NO: 8). In some embodiments, the capture agent binds to a region of any of the isolated biomarkers of Table 2 comprising any of the respective amino acid sequences.

[0012] In some embodiments, the method of determining the PDD or TTB for a pregnant female comprises detecting the presence or amount of a pair of isolated biomarkers in said biological sample, wherein said pair of isolated biomarkers comprises two isolated biomarkers selected from Table 2. In some embodiments, the method of determining the PDD or TTB for a pregnant female comprises detecting the presence or amount of a pair of isolated biomarkers in said biological sample, wherein said pair of isolated biomarkers comprises ADA12 and an isolated biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1. In further embodiments, the pair of isolated biomarkers comprises ADA12 and KIT. [0013] In some embodiments, the biological sample of the methods herein is collected, stored and shipped using an at-home or in-clinic handheld bodily fluid collection device, a volumetric absorptive microsampling device, or a dried blood spot card. In some embodiments, the biological sample is selected from the group consisting of venous whole blood, capillary whole blood, serum, or plasma. In some embodiments, the biological sample is selected from the group consisting of dried capillary whole blood, dried serum, or dried plasma. In further embodiments, the biological sample is dried capillary whole blood. In some embodiments, the biological sample is obtained at a gestational age at blood draw (GABD) from 126 through 202 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 160 days. In other embodiments, biological sample is obtained at a GABD from 161 through 202 days. In some embodiments, the biological sample is stable up to 50°C for up to 48 hours. In some embodiments, the biological sample is stable at 50°C for 48 hours.

[0014] In some embodiments, the amount of the pair of isolated biomarkers in the methods herein is further combined with one or more clinical components into a model that can be trained on a dataset to determine the PDD or TTB. In some embodiments, the model comprises the amount of said pair of isolated biomarkers and one or more clinical components selected from the group consisting of GABD, gravidity, and maternal age (MAGE).

[0015] In some embodiments, the present disclosure also provides a method of determining the PDD or TTB for a pregnant female, the method comprising obtaining a biological sample obtained from said pregnant female, detecting the presence or amount of a pair of isolated biomarkers in said biological sample obtained from said pregnant female; and measuring in said biological sample a reversal value for said pair of isolated biomarkers to determine the PDD or TTB, wherein the reversal value gives a PDD or TTB that falls within +/-X days of the pregnant female’s actual delivery date (ADD) or actual TTB at least Y% of the time. In some embodiments, X is 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1, and Y is 50%, 51%, 52%, 53%, 54%, 55%, 56%, 57%, 58%, 59%, 60%, 61%, 62%, 63%, 64%, 65%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or 100%. In further embodiments, X is 3, 2, or 1, and Y is 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or 100%. In some embodiments, said pair of isolated biomarkers comprises two isolated biomarkers selected from Table 2. In some embodiments, said pair of isolated biomarkers comprises ADA12 and an isolated biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1. In some embodiments, the pair of isolated biomarkers comprises ADA12 and KIT. In some embodiments, the reversal value gives a PDD or TTB that falls within 3 days of the pregnant female’s ADD or actual TTB, and a PDD or TTB that is within 5 days of an estimated due date (EDD) of the pregnant female.

[0016] The present disclosure also provides a method of detecting a pair of isolated biomarkers. In some embodiments, the method comprises obtaining a biological sample obtained from a pregnant female, detecting the presence and/or amount of the pair of isolated biomarkers in the biological sample by contacting the biological sample with a first capture agent that specifically binds a first member of said pair and a second capture agent that specifically binds a second member of said pair; and detecting binding between the first biomarker of said pair and the first capture agent and between the second member of said pair and the second capture agent. In some embodiments, the biological sample obtained from the pregnant female is collected, stored, or shipped using an at-home or in-clinic handheld bodily fluid collection device, a volumetric absorptive microsampling device, or a dried blood spot card. In some embodiments, said pair of isolated biomarkers comprises two isolated biomarkers selected from Table 2. In some embodiments, the pair of isolated biomarkers comprises ADA12 and an isolated biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1. In further embodiments, the pair of isolated biomarkers comprises ADA12 and KIT. In some embodiments, the first capture agent specifically binds ADA12 and the second capture agent specifically binds KIT. In some embodiments, the first capture agent and second capture agent is selected from the group consisting of an antibody, antibody fragment, nucleic acid-based protein binding reagent, small molecule or variant thereof. In some embodiments, the method is performed by an assay selected from the group consisting of enzyme immunoassay (EIA), enzyme-linked immunosorbent assay (ELISA), and radioimmunoassay (RIA).

[0017] Also provided herein is a method of detecting a pair of isolated biomarkers in a pregnant female, wherein the method comprises obtaining a biological sample obtained from the pregnant female, and detecting the level of the pair of isolated biomarkers in the biological sample comprising subjecting the sample to a proteomics workflow comprised of mass spectrometry quantification. In some embodiments, the biological sample obtained from the pregnant female is collected, stored, and shipped using an at-home or in-clinic handheld bodily fluid collection device, a volumetric absorptive microsampling device, or a dried blood spot card. In some embodiments, said pair of isolated biomarkers comprises two isolated biomarkers selected from Table 2. In some embodiments, said pair of isolated biomarkers comprises ADA12 and an isolated biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1. In further embodiments, said pair of isolated biomarkers comprises ADA12 and KIT.

[0018] In some embodiments, the proteomics workflow herein comprises thawing and depleting the biological sample of high abundance proteins (e.g., the 5, 8, 10, 12 or 14 highest abundance proteins) by immunity-affinity chromatography, digesting the depleted biological sample with a protease to yield peptides, fortifying the digest with a mixture of stable isotope labeled standard (SIS) peptides, and desalting and subjecting the digest to LC-MS/MS with a triple quadrapole instrument operated in MRM mode. In some embodiments, the protease is trypsin. In some embodiments, the high abundance proteins are selected from the group consisting of Albumin, IgG, Antitrypsin, IgA, Transferrin, Haptoglobin, Fibrinogen, Alpha2- macroglobulin, Alphal-acid glycoprotein, IgM, Apolipoprotein Al, Apolipoprotein All, Complement C3, and Transthyretin.

[0019] In some embodiments, the present disclosure provides a kit for determining the PDD or TTB for a pregnant female. In some embodiments, the kit comprises one or more agents for the detection of a pair of isolated biomarkers; a container for holding a biological sample isolated from a pregnant female, and printed instructions for reacting agents with the biological sample or a portion or derivative of the biological sample to detect the presence or amount of the isolated biomarkers in the biological sample. In some embodiments, said pair of isolated biomarkers comprises two isolated biomarkers selected from Table 2. In some embodiments, the pair of isolated biomarkers comprises ADA12 and a biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1. In further embodiments, the pair of isolated biomarkers comprises ADA12 and KIT. In some embodiments, the kit further comprises one or more control reference samples and reagents for performing an immunoassay. In other embodiments, the kit further comprises a package insert containing written instructions for methods for separating a pregnancy that delivers X or more days before the EDD or Y or more days after the EDD, from a pregnancy that delivers within Z days of the EDD, wherein X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, wherein Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 days, and wherein Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days.

[0020] The present disclosure also provides a composition comprising a pair of isolated biomarkers. In some embodiments, said pair of isolated biomarkers exhibits change in reversal value between pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD, wherein X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, wherein Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, and wherein Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, said pair of isolated biomarkers comprises two isolated biomarkers selected from Table 2. In some embodiments, the pair of isolated biomarkers comprises ADA12 and an isolated biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1. In further embodiments, the pair of isolated biomarkers comprises ADA12 and KIT.

[0021] Also provided herein is a use of a composition comprising a pair of isolated biomarkers in a method of determining the PDD or TTB for a pregnant female. In some embodiments, the pair of isolated biomarkers exhibits a change in reversal value between pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD, wherein X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, wherein Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, and wherein Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, said pair of isolated biomarkers comprises two isolated biomarkers selected from Table 2. In some embodiments, the pair of isolated biomarkers comprises ADA12 and an isolated biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1. In further embodiments, the pair of isolated biomarkers comprises ADA12 and KIT.

[0022] The present disclosure also provides a method of determining the PDD or TTB for a pregnant female, wherein the method comprises (a) obtaining a biological sample obtained from said pregnant female; (b) detecting the presence or amount of one or more isolated biomarkers in said biological sample, and (c) integrating one or more clinical or demographic variables with the detected presence or amount of said one or more isolated biomarkers into a predictive model for determining the PDD or TTB. In some embodiments, said detecting comprises subjecting said biological sample to (i) mass spectrometry (MS) quantification, or (ii) an assay that utilizes a capture agent that binds to each of the one or more isolated biomarkers. In some embodiments, said one or more isolated biomarkers is selected from Table 2.

[0023] In some embodiments, the method further comprises measuring in said biological sample the amount of each of said one or more isolated biomarkers to determine the PDD or TTB. In some embodiments, each of said one or more isolated biomarkers exhibits a change in the amount between pregnant females who deliver X or more days before the estimated due date (EDD) or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days, and Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days, Y is no more than 1, 2, 3, or 4 days, and Z is no more than 1, 2, 3, or 4 days.

[0024] In some embodiments, the method of determining the PDD or TTB further comprises measuring in said biological sample the amount of each of said one or more biomarkers to determine the PDD or TTB, wherein the amount is integrated into said predictive model and gives a PDD or TTB that falls within +/-X days of the pregnant female’s actual delivery date (ADD) or actual TTB at least Y% of the time. In some embodiments, X is 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1, and Y is 50%, 51%, 52%, 53%, 54%, 55%, 56%, 57%, 58%, 59%, 60%, 61%, 62%, 63%, 64%, 65%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 80%, 81%, 82%,

83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%,

99% or 100%. In further embodiments, X is 3, 2, or 1, and Y is 90%, 91%, 92%, 93%, 94%,

95%, 96%, 97%, 98%, 99% or 100%. In some embodiments, the amount of each of said one or more biomarkers is integrated into said predictive model and gives a PDD or TTB that falls within 3 days of the pregnant female’s ADD or actual TTB, and a PDD or TTB that is within 5 days of an estimated due date (EDD) of the pregnant female.

[0025] In some embodiments of the method of determining the PDD or TTB, the biological sample obtained from the pregnant female is collected using an at-home or in-clinic handheld bodily fluid collection device, a volumetric absorptive microsampling device, or a dried blood spot card. In some embodiments, the biological sample is selected from the group consisting of dried capillary whole blood, dried serum, or dried plasma. In further embodiments, the biological sample is dried capillary whole blood. In some embodiments, the biological sample is stable at 50°C for 48 hours. In some embodiments, heparin is used in the detection of said one or more isolated biomarkers in said biological sample obtained from said pregnant female. [0026] In some embodiments, the biological sample is obtained at a gestational age at blood draw (GABD) from 126 through 202 days. In further embodiments, the biological sample is obtained at a GABD from 126 through 160 days. In other embodiments, the biological sample is obtained at a GABD from 161 through 202 days.

[0027] In some embodiments, said one or more clinical or demographic variables is selected from the group consisting of age, body mass index (BMI), race, hypertiension/preeclampsia in a prior pregnancy, preterm birth in a prior pregnancy, cesarean section (c-section) delivery in a prior pregnancy, education level, being a first time mother, chronic diabetes, gestational diabetes in the current pregnancy, hypertension or preeclampsia in the current pregnancy, previous low birth weight or preterm delivery, multiple 2nd trimester spontaneous abortions, prior first trimester induced abortion, familial and intergenerational factors, history of infertility, parity, nulliparity, placental abnormalities, cervical and uterine anomalies, short cervical length measurements, results of anomaly scans (including fetal (e.g., crown-rump length), placental and maternal pelvic organ measures), gestational bleeding, intrauterine growth restriction, in utero diethylstilbestrol exposure, multiple gestations, infant sex, short stature, low prepregnancy weight, chronic hypertension, urogenital infections (z.e., urinary tract infection), asthma, anxiety and depression, asthma, hypothyroidism, high BMI, low BMI, maternal age (MAGE), ethnicity, single marital status, low socioeconomic status, employment-related physical activity, occupational exposures, environment exposures, stress, inadequate prenatal care, cigarette smoking, use of marijuana and other illicit drugs, cocaine use, alcohol consumption, caffeine intake, maternal weight gain, dietary intake, sexual activity during late pregnancy, and leisure-time physical activities. In further embodiments, said one or more clinical or demographic variables is selected from the group consisting of age, BMI, race, hypertiension/preeclampsia in a prior pregnancy, preterm birth in a prior pregnancy, c-section delivery in a prior pregnancy, education level, being a first-time mother, chronic diabetes, gestational diabetes in the current pregnancy, hypertension or preeclampsia in the current pregnancy.

[0028] In some embodiments, said detecting comprises said assay that utilizes a capture agent that binds to the at least one or more isolated biomarkers, wherein the at least one or more isolated biomarkers comprises an amino acid sequence selected from Table 2. In some embodiments, said capture agent is selected from the group consisting of an antibody, antibody fragment, nucleic acid-based protein binding reagent, small molecule or variant thereof. In some embodiments, said assay is selected from the group consisting of enzyme immunoassay (EIA), enzyme-linked immunosorbent assay (ELISA), and radioimmunoassay (RIA). In other embodiments, said detecting comprises said MS quantification. In some embodiments, said MS is selected from the group consisting of matrix-assisted laser desorption/ionisation time- of-flight (MALDI-TOF) MS; MALDI-TOF post-source-decay (PSD); MALDL TOF/TOF; surface-enhanced laser desorption/ionization time-of-fhght mass spectrometry (SELDLTOF) MS; electrospray ionization mass spectrometry (ESLMS); ESLMS/MS; ESI-MS/(MS)n (n is an integer greater than zero); ESI 3D or linear (2D) ion trap MS; ESI triple quadrupole MS; ESI quadrupole orthogonal TOF (Q-TOF); ESI Fourier transform MS systems; desorption/ionization on silicon (DIOS); secondary ion mass spectrometry (SIMS); atmospheric pressure chemical ionization mass spectrometry (APCLMS); APCL MS/MS; APCL (MS)n (n is an integer greater than zero); ion mobility spectrometry (IMS); inductively coupled plasma mass spectrometry (ICP-MS); atmospheric pressure photoionization mass spectrometry (APPI- MS); APPLMS/MS; and APPI- (MS)n (n is an integer greater than zero). In some embodiments, said MS comprises affinity-capture MS (AC -MS), coimmunoprecipitation-mass spectrometry (co-IP MS), liquid chromatography-mass spectrometry (LC-MS), multiple reaction monitoring (MRM) or selected reaction monitoring (SRM).

[0029] Also provided herein is a method of detecting one or more isolated biomarkers. In some embodiments, the method comprises (a) obtaining a biological sample obtained from a pregnant female; (b) detecting the presence or amount of each of the one or more isolated biomarkers in the biological sample by contacting the biological sample with a capture agent that specifically binds a member of each of said one or more isolated biomarkers; and (c) detecting binding between the one or more isolated biomarkers and the capture agent. In some embedments, the biological sample obtained from the pregnant female is collected using an at- home or in-clinic handheld bodily fluid collection device, a volumetric absorptive microsampling device, or a dried blood spot card. In some embodiments, the one or more isolated biomarkers is selected from Table 2.

[0030] In some embodiments, the capture agent is selected from the group consisting of an antibody, antibody fragment, nucleic acid-based protein binding reagent, small molecule or variant thereof. In some embodiments, the method is performed by an assay selected from the group consisting of enzyme immunoassay (EIA), enzyme-linked immunosorbent assay (ELISA), and radioimmunoassay (RIA).

[0031] The present disclosure also provides a method of detecting one or more isolated biomarkers in a pregnant female. In some embodiments, the method comprises (a) obtaining a biological sample obtained from the pregnant female; and (b) detecting the level of each of the one or more isolated biomarkers in the biological sample including subjecting the sample to a proteomics workflow which includes mass spectrometry quantification. In some embodiments, the biological sample obtained from the pregnant female is collected using an at-home or inclinic handheld bodily fluid collection device, a volumetric absorptive microsampling device, or a dried blood spot card. In some embodiments, the one or more isolated biomarkers is selected from Table 2. In some embodiments, the proteomics workflow comprises (i) thawing and depleting the biological sample of high abundance proteins (e.g., the 5, 8, 10, 12 or 14 highest abundance proteins) by immunity-affinity chromatography; (ii) digesting the depleted biological sample with a protease to yield peptides; (iii) fortifying the digest with a mixture of stable isotope labeled standard (SIS) peptides; and (iv) desalting and subjecting the digest to LC-MS/MS with a triple quadrapole instrument operated in MRM mode. In some embodiments, the protease is trypsin. In some embodiments, the high abundance proteins are selected from the group consisting of Albumin, IgG, Antitrypsin, IgA, Transferrin, Haptoglobin, Fibrinogen, Alpha2-macroglobulin, Alphal-acid glycoprotein, IgM, Apolipoprotein Al, Apolipoprotein All, Complement C3, and Transthyretin.

[0032] Also provided herein is a kit for determining the predicted delivery date (PDD) or time to birth (TTB) for a pregnant female, wherein the kit comprises: (a) one or more agents for the detection of one or more isolated biomarkers; (b) a container for holding a biological sample isolated from a pregnant female; and (c) printed instructions for reacting agents with the biological sample or a portion or derivative of the biological sample to detect the presence or amount of each of the one or more isolated biomarkers in the biological sample. In some embodiments, the one or more isolated biomarkers is selected from Table 2. In some embodiments, the kit further comprises one or more control reference samples and reagents for performing an immunoassay. In some embodiments, the kit further comprises a package insert containing written instructions (e.g., a link or QR code to a website with instructions or downloadable software with instructions) for methods for separating a pregnancy that delivers X or more days before the Estimated due date (EDD) or Y or more days after the EDD, from a pregnancy that delivers within Z days of the EDD. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 days, and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days.

[0033] The present disclosure also provides a composition comprising one or more isolated biomarkers. In some embodiments, said one or more isolated biomarkers exhibits a change in an amount between pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, said one or more isolated biomarkers is selected from Table 2.

[0034] Also provided herein is a use of a composition comprising one or more isolated biomarkers in a method of determining the predicted delivery date (PDD) or time to birth (TTB) for a pregnant female. In some embodiments, said one or more isolated biomarkers exhibits a change in an amount between pregnant females who deliver X or more days before the estimated due date (EDD) or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, said one or more isolated biomarkers is selected from Table 2.

[0035] Also provided herein is a method of predicting the week of gestation in which a pregnant female is most likely to deliver. In some embodiments, the method comprises (a) obtaining a biological sample obtained from said pregnant female; (b) detecting the presence or amount of one or more isolated biomarkers in said biological sample; (c) comparing clinical factors for said pregnant female to the same clinical factors in a cohort of reference pregnant females; and (d) deriving from (b) and (c) the probability said pregnant female will deliver in each of certain specific weeks of gestation. In some embodiments, said one or more isolated biomarkers in said biological sample is selected from Table 2. In some embodiments, said one or more isolated biomarkers in said biological sample is selected from Table 16. In some embodiments, said one or more isolated biomarkers in said biological sample comprises at least two isolated biomarkers selected from Table 2. In some embodiments, said one or more isolated biomarkers in said biological sample comprises at least two isolated biomarkers selected from Table 16. In some embodiments, said one or more isolated biomarkers in said biological sample comprises ADA12 and an isolated biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1. In further embodiments, said one or more isolated biomarkers in said biological sample comprises ADA12 and KIT.

[0036] In some embodiments, the cohort of reference pregnant females is derived from a proprietary database or a public database. In some embodiments, the cohort of reference pregnant females is derived from a CDC database. In some embodiments, the clinical factors in (c) are selected from the group consisting of age, BMI, race, hypertension/preeclampsia in a prior pregnancy, preterm birth in a prior pregnancy, c-section delivery in a prior pregnancy, education level, being a first-time mother, chronic diabetes, gestational diabetes in the current pregnancy, and hypertension or preeclampsia in the current pregnancy. In some embodiments, the probability in (d) is derived by : (1) deriving the probability said pregnant female will deliver in each of certain specific weeks of pregnancy based at least in part on the comparison in (c) and (2) adjusting the probability in (1) by the probability derived from comparing the amount of biomarker(s) detected in (b) with the amount of said biomarkers detected in a reference cohort of pregnant females. In some embodiments, said certain specific weeks of gestation comprise weeks 37 through 41 of gestation.

[0037] Other features and advantages will be apparent from the detailed description, and from the claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] FIG. 1 shows an exemplary scatterplot of actual TTB vs predicted TTB (top) and the histograms for due date differences for Model 1 in Table 6 (bottom).

[0039] FIG. 2 shows an exemplary scatterplot of actual TTB vs predicted TTB (top) and the histograms for due date differences for Model 2 in Table 6 (bottom).

[0040] FIG. 3 shows an exemplary scatterplot of actual TTB vs predicted TTB (top) and the histograms for due date differences for Model 3 in Table 6 (bottom).

[0041] FIG. 4 shows an exemplary scatterplot of actual TTB vs predicted TTB (top) and the histograms for due date differences for Model 4 in Table 6 (bottom).

[0042] FIG. 5 shows an examplary scatterplot of actual TTB vs predicted TTB (top) and the histograms for due date differences for Model 5 in Table 6 (bottom).

[0043] FIG. 6 shows an exemplary scatterplot of actual TTB vs predicted TTB (top) and the histograms for due date differences for Model 6 in Table 6 (bottom).

[0044] FIG. 7 shows an exemplary linear regession plot of TTB ratios of the analytes ADA12 over KIT (ADA12/KIT), establishing the correlation between ELISA and mass spectrometry (MS) immunoassays of liquid serum that had been previously frozen.

[0045] FIG. 8 shows an exemplary linear regession plot of TTB ratios of the analytes ADA12 over KIT (ADA12/KIT), establishing the correlation between ELISA and MS immunoassays of dried serum samples.

[0046] FIG. 9 shows an exemplary linear regession plot of TTB ratios of the analytes ADA12 over KIT (ADA12/KIT), establishing the correlation between frozen serum (assayed via depletion-MS) and capillary whole blood (assayed via AC -MS).

[0047] FIG. 10 shows an exemplary linear regession plot of TTB ratios of the analytes ADA12 over KIT (ADA12/KIT), establishing the correlation between frozen serum (assayed via depletion-MS) and venous whole blood (assayed via AC -MS).

[0048] FIG. 11 shows an exemplary linear regession plot of TTB ratios of the analytes ADA12 over KIT (ADA12/KIT), establishing the correlation between dried whole blood samples assayed by ELISA and MS.

[0049] FIG. 12 shows an exemplary linear regession plot of TTB ratios of the analytes ADA12 over KIT (ADA12/KIT), establishing the correlation between ELISA-assayed dried serum and dried whole blood samples.

[0050] FIG. 13 shows an exemplary linear regession plot of TTB ratios of the analytes ADA12 over KIT (ADA12/KIT), establishing the correlation between the ELISA-assayed dried plasma and dried whole blood samples. [0051] FIG. 14 shows a scatter plot of ELISA-assayed analyte ratios of the analytes AD Al 2 over KIT (ADA12/KIT) at different temperatures and time points.

[0052] FIG. 15 shows an exemplary linear regession plot of the concentration of ADA12 (ng/mL), establishing a correlation between an automated ELISA immunoassay and a manual immunoassay for an ADA12 liquid serum sample.

[0053] FIG. 16 shows an exemplary linear regession plot of TTB ratios establishing a correlation between an automated ELISA immunoassay and an MS assay for an ADA12 liquid serum sample.

[0054] FIG. 17 shows a scatterplot of ADA12 signal from various capillary blood and venous blood samples collected without the use of EDTA.

[0055] FIG. 18 shows an exemplary linear regression plot of TTB ratios establishing a correlation between a venipuncture ADA12 serum sample dried on a Mitra® tip and a finger prick ADA12 sample dried on a blood spot card. Both samples were collected without the use of EDTA.

[0056] FIG. 19 shows an exemplary regression plot of TTB ratios of the analytes ADA12 over KIT (ADA12/KIT), establishing the correlation between serum samples collected via venipuncture, and finger prick samples collected on a dried blood spot card. Both samples were collected without the use of EDTA.

[0057] FIGS. 20A-20B show changes in exemplary protein expression between 18 to 20 weeks’ gestation and 26-28 weeks’ gestation. FIG. 20A shows a Volcano plot showing significantly upregulated (proteins to the right of the dashed section) and downregulated (proteins to the left of the dashed section) proteins. Significance is represented on the y-axis as the -logio P-value, while the magnitude of change is shown on the x-axis as the log2 foldchange. When a protein is depicted more than once (denoted by _1 and _2), it was measured using two distinct peptides. FIG. 20B depicts smoothing plots for representative proteins PAEP, KIT, CNTN1, FGFR1, ADA12 and PSG1, showing expression changes that were significantly upregulated, downregulated, or demonstrated no significant change. The 95% confidence interval (CI) expression (response ratio; “RR”) and GABD is represented by the width of the gray-shaded area.

[0058] FIG. 21 shows results of an MRPC analysis, depicting statistical directional relationships between proteins and TTB. The clusters (groups 1-6) represent groups of proteins that clustered based on statistical association. Single direction arrowheads indicate statistically causal relationships where the protein or outcome being touched by the arrowhead is statistically dependent on the protein being touched by the blunt end of the arrow. Bidirectional arrows indicate indeterminant statistical causality. When a protein is depicted more than once (denoted by _1 and _2), it was measured on two distinct peptides.

[0059] FIG. 22 shows 3 bar graphs depicting the association between GAB and ADA12 expression in 3 different groups. The top graph shows the distribution of GAB in mothers who expressed the lowest levels of ADA12 (10^th percentile). The middle graph shows the distribution of GAB in mothers who expressed the highest levels of ADA12 (90^th percentile). The combined number of births in both groups (bottom graph), shows how many more births from each group occurred in each week relative to the other. The dashed lines indicate the mean GABs for each group: black = 90^th percentile, white = 10^th percentile.

[0060] FIGS. 23A-23F show linear plots of 6 exemplary biomarker candidates, z.e., the biomarkers and the corresponding peptides (denoted as “biomarker_peptide”) that demonstrated linear correlations with GABD: (A) ADA12 FGFGGSTDSGPIR (SEQ ID NO: 1); (B) GRN EVVSAQPATFLAR (SEQ ID NO: 83); (C) SEM7A ATIVHQDQAYDDK (SEQ ID NO: 78); (D) SPIT1 YTSGFDELQR (SEQ ID NO: 86); (E) LYPD3 GCGSGLPGK (SEQ ID NO: 74); and (F) CSH ISLLLIESWLEPVR (SEQ ID NO: 18).

[0061] FIG. 24 provides a bar graph from an exemplary test report, showing the birth week probability distribution for each week (weeks 36 to 43) for a pregnant subject with the following 11 clinical and demographic factors: 1. 32 (age), 2. 23.3 (BMI), 3. White (race), 4. No (hypertension/preeclampsia in a prior pregnancy), 5. No (preterm birth in a prior pregnancy), 6. Yes (c-section delivery in a prior pregnancy), 7. High School (education level), 8. No (first time mother), 9. No (chronic diabetes), 10. No (gestational diabetes in the current pregnancy), and 11. No (hypertension or preeclampsia in the current pregnancy).

[0062] FIG. 25 shows a line graph of the distribution of “neutral”, “positive”, and “negative” groups of pregnant subjects and their probability to deliver for each week (weeks 37 to 42). “Neutral” represents the average weekly probability whereas the “positive group” is skewed to the right of the “neutral” group, and the “negative” group is skewed to the left.

DETAILED DESCRIPTION

[0063] The present disclosure is based, generally, on the unexpected discovery that certain proteins and peptides in biological samples obtained from a pregnant female disclosed herein can be utilized in methods of determining the predicted delivery date of a pregnant female (referred to herein as the Predicted Delivery Date (PDD)) and/or determining the time to birth (TTB) of a pregnant female. The present disclosure is also based, generally, on the discovery that the PDD may be used to more accurately estimate the actual delivery date (ADD) of a pregnant female compared to the EDD, based on a pregnant female’s own demographics and blood analytes. In particular, the present disclosure provides a new and useful process for estimating the PDD and/or TTB with higher accuracy than currently practiced clinical methods. Each of the proteins or fragments thereof disclosed herein, for instance, serve as components of pairs, ratios and/or reversal pairs that serve as biomarkers for determining the PDD, predicting gestational age at birth (GAB), predicting TTB, estimating gestational age (GA) either individually, in ratios, or reversal pairs. Furthemore, the compositions and methods described herein can comprise each of the proteins corresponding to the peptide biomarkers disclosed herein, and can likewise serve as a component of pairs, ratios and/or reversal pairs for determining the PDD, predicting GAB, predicting TTB, estimating GA either individually, in ratios, or reversal pairs. Additionally, each of the ratios or reversal pairs of the biomarkers disclosed herein can be incorporated into a model (e.g., regression formula) for determining the PDD, predicting TAB, predicting TTB, and/or estimating GA.

[0064] The present disclosure is also based, generally, on the discovery that certain proteins and peptides in biological samples obtained from a pregnant female are differentially expressed in pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD, wherein X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days; Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days; and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days.

[0065] Definitions

[0066] It must be noted that, as used in this specification and the appended claims, the singular forms “a”, “an” and “the” include plural referents unless the content clearly dictates otherwise, and are used interchangeably with “at least one” and “one or more.” Thus, for example, reference to “a biomarker” includes a mixture of two or more biomarkers, and the like.

[0067] The term “about,” particularly in reference to a given quantity, is meant in some instances to encompass deviations of, e.g., plus or minus 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45%.

[0068] As used herein, the terms “comprises,” “comprising,” “includes,” “including,” “contains,” “containing,” and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, product-by-process, or composition of matter that comprises, includes, or contains an element or list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, product-by-process, or composition of matter.

[0069] As used herein, and unless otherwise specified, the terms “isolated” and “purified” generally describes a composition of matter that has been removed from its native environment (e.g., the natural environment if it is naturally occurring), and thus is altered by the hand of man from its natural state so as to possess markedly different characteristics with regard to at least one of structure, function or properties. An isolated protein (including peptide) or nucleic acid is distinct from the way it exists in nature and includes synthetic proteins (including peptides) or synthetic nucleic acids.

[0070] The term “biomarker” refers to a biological molecule or a fragment of a biological molecule, the state, structure, sequence, amount, level, change and/or the detection of which can be correlated with a particular physical condition or state. Except where context clearly indicates otherwise, the terms “marker” and “biomarker” are used interchangeably throughout the disclosure. For example, the biomarkers of the present disclosure are associated with a discrimination power between pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD; where X is 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, 35 or more days; Y is 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or more days; and Z is 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some instances, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In further instances, X is no more than 1, 2, 3, 4, 5, 6, or 7 days. In some instances, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further instances, Y is no more than 1, 2, 3, or 4 days. In some instances, Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further instances, Z is no more than 1, 2, 3, or 4 days. Such biomarkers include any suitable analyte, but are not limited to, biological molecules comprising nucleotides, nucleic acids, nucleosides, amino acids, sugars, fatty acids, steroids, metabolites, peptides, polypeptides, proteins, carbohydrates, lipids, hormones, antibodies, regions of interest that serve as surrogates for biological macromolecules and combinations thereof (e.g., glycoproteins, ribonucleoproteins, lipoproteins). The term also encompasses portions or fragments of a biological molecule, for example, peptide fragment of a protein or polypeptide that comprises at least 5 consecutive amino acid residues, at least 5 consecutive amino acid residues, at least 6 consecutive amino acid residues, at least 7 consecutive amino acid residues, at least 8 consecutive amino acid residues, at least 9 consecutive amino acid residues, at least 10 consecutive amino acid residues, at least 11 consecutive amino acid residues, at least 12 consecutive amino acid residues, at least 13 consecutive amino acid residues, at least 14 consecutive amino acid residues, at least 15 consecutive amino acid residues, at least 16 consecutive amino acid residues, at least 17consecutive amino acid residues, at least 18 consecutive amino acid residues, at least 19 consecutive amino acid residues, at least 20 consecutive amino acid residues, at least 21 consecutive amino acid residues, at least 22 consecutive amino acid residues, at least 23 consecutive amino acid residues, at least 24 consecutive amino acid residues, at least 25 consecutive amino acid residues, or more consecutive amino acid residues.

[0071] In the context of the present disclosure, the term “biological sample,” encompasses any sample that is taken from pregnant female and contains one or more of the biomarkers disclosed herein. Suitable samples in the context of the present disclosure include, for example, blood, plasma, serum, amniotic fluid, vaginal secretions, saliva, and urine. In some instances, the biological sample is selected from the group consisting of whole blood, plasma, and serum. In a particular instance, the biological sample is serum. In some instances, the biological sample is a dry sample. In particular instances, the biological sample is dried whole blood, dried serum, or dried plasma. In some instances, the biological sample is dried capillary whole blood. As will be appreciated by those skilled in the art, a biological sample can include any fraction or component of blood, without limitation, T cells, monocytes, neutrophils, erythrocytes, platelets and microvesicles such as exosomes and exosome-like vesicles.

[0072] As used herein, the term “estimated gestational age” or “estimated GA” refers to the GA determined based on the date of the last normal menses and additional obstetric measures, ultrasound estimates or other clinical parameters including, without limitation, those described in the preceding paragraph. In contrast, the term “predicted gestational age at birth” or “predicted GAB” refers to the GAB determined based on the methods of the disclosure as dislosed herein. In the art, “early term” generally means delivery at 37 0/7 weeks of gestation through 38 6/7 weeks of gestation, “full term” generally means delivery at 39 0/7 weeks of gestation through 40 6/7 weeks of gestation, “late term” generally means delivery at 41 0/7 weeks of gestation through 41 6/7 weeks of gestation, and “post-term” generally means delivery at 42 0/7 weeks of gestation and beyond. As used herein, “term” delivery and “term” birth refer to any delivery occurring at or after 37 0/7 weeks.

[0073] The term “amount” or “level” as used herein refers to a quantity of a biomarker that is detectable or measurable in a biological sample and/or control. The quantity of a biomarker can be, for example, the quantity of polypeptide, the quantity of nucleic acid, or the quantity of a fragment of each. The term can alternatively include combinations thereof. The term “amount” or “level” of a biomarker is a measurable feature of that biomarker. [0074] As used herein, the term “mass spectrometer” refers to a device able to volatilize/ionize analytes to form gas-phase ions and determine their absolute or relative molecular masses. Suitable methods of volatilization/ionization are matrix-assisted laser desorption ionization (MALDI), electrospray, laser/light, thermal, electrical, atomized/sprayed and the like, or combinations thereof. Suitable forms of mass spectrometry include, but are not limited to, ion trap instruments, quadrupole instruments, electrostatic and magnetic sector instruments, time of flight instruments, time of flight tandem mass spectrometer (TOF MS/MS), Fourier-transform mass spectrometers, Orbitraps and hybrid instruments composed of various combinations of these types of mass analyzers. These instruments can, in turn, be interfaced with a variety of other instruments that fractionate the samples (for example, liquid chromatography or solid-phase adsorption techniques based on chemical, or biological properties) and that ionize the samples for introduction into the mass spectrometer, including matrix-assisted laser desorption (MALDI), electrospray, or nanospray ionization (ESI) or combinations thereof.

[0075] As used herein, the terms “multiple reaction monitoring (MRM)” or “selected reaction monitoring (SRM)” refer to an MS-based quantification method that is particularly useful for quantifying analytes that are in low abundance. In an SRM experiment, a predefined precursor ion and one or more of its fragments are selected by the two mass filters of a triple quadrupole instrument and monitored over time for precise quantification. Multiple SRM precursor and fragment ion pairs can be measured within the same experiment on the chromatographic time scale by rapidly toggling between the different precursor/fragment pairs to perform an MRM experiment. A series of transitions (precursor/fragment ion pairs) in combination with the retention time of the targeted analyte (e.g., peptide or small molecule such as chemical entity, steroid, hormone) can constitute a definitive assay. A large number of analytes can be quantified during a single LC-MS experiment. The term “scheduled,” or “dynamic” in reference to MRM or SRM, refers to a variation of the assay wherein the transitions for a particular analyte are only acquired in a time window around the expected retention time, significantly increasing the number of analytes that can be detected and quantified in a single LC-MS experiment and contributing to the selectivity of the test, as retention time is a property dependent on the physical nature of the analyte. A single analyte can also be monitored with more than one transition. Finally, included in the assay can be standards that correspond to the analytes of interest (e.g., same amino acid sequence), but differ by the inclusion of stable isotopes. Stable isotopic standards (SIS) can be incorporated into the assay at precise levels and used to quantify the corresponding unknown analyte. An additional level of specificity is contributed by the co-elution of the unknown analyte and its corresponding SIS and properties of their transitions (e.g., the similarity in the ratio of the level of two transitions of the unknown and the ratio of the two transitions of its corresponding SIS). [0076] In the context of the disclosure, the term “capture agent” refers to a compound that can specifically bind to a target, in particular a biomarker. The term includes antibodies, antibody fragments, nucleic acid-based protein binding reagents (e.g., aptamers, Slow Off-rate Modified Aptamers (SOMAmer™)), protein-capture agents, natural ligands (z.e., a hormone for its receptor or vice versa), small molecules or variants thereof.

[0077] As used herein, the term “surrogate peptide” refers to a peptide that is selected to serve as a surrogate for quantification of a biomarker of interest in an assay described in the disclosure, including but not limited to in a multiple reaction monitoring (MRM, also known as Selective Reaction Monitoring - SRM) assay configuration. In the MRM detection technique, quantification of surrogate peptides is achieved by measuring the peak area of the endogenous surrogate peptide in the sample. Moreover, synthetic stable isotope labeled standard surrogate peptides (“SIS surrogate peptides” or “SIS peptides”) can be introduced into the sample and used to establish a “response ratio” (RR). A surrogate peptide can be derived from the biomarker or synthetic peptide standard. An SIS surrogate peptide can be synthesized with heavy labeled for example, with an Arginine or Lysine, or any other amino acid of the peptide to serve as an internal standard in the MRM assay. An SIS surrogate peptide is not a naturally occurring peptide and has markedly different characteristics compared to its naturally occurring counterpart, such as having a markedly different mass, which can be distinguished by mass spectrometry allowing the SIS and endogenous surrogate peptides to be quantified independently. For any of the instances described herein, the biomarkers can be quantified by measuring surrogate peptides.

[0078] In some instances, an SIS peptide can derive from an SIS protein standard. (Phillip et al., Production and application of high-quality stable isotope-labeled human immunoglobulin G1 for mass spectrometry analysis, J. Labelled Comp. Radi opharm. (2017) 60: 160-167.) For example, the full-length protein biomarker, or fragments thereof, can be expressed recombinantly in a suitable in vitro or cell (prokaryotic or eukaryotic) expression system in the presence of stable isotope labelled amino acids. The SIS protein biomarker can then be purified from the recombinant system and introduced into samples as an internal protein standard. The SIS protein will typically have the same biological properties, track with the endogenous protein biomarker during laboratory analysis, but differ in molecular mass. Peptides derived from proteolytic digestion of the sample will yield both the SIS peptide derived from the SIS protein and the corresponding endogenous peptide. The use of an SIS protein may have several advantages over the synthetic SIS peptide, in that it mimics the protein biomarker in early steps in a proteomic process (e.g., immunoaffinity depletion and tryptic digestion) and therefore controls for variability in those steps. It would also bind to antibodies in an affinity-capture, mass spectrometry (ACMS) workflow and control for variability in affinity capture. Because SIS proteins generate SIS peptides, this can also serve to normalize the same variability later in proteomic workflows associated with synthetic SIS peptide, such as desalting, lyophilization, liquid chromatographic and mass spectrometry. In a related instance, a ratiometric calibration curve can be constructed varying the concentration of an unlabeled protein biomarker standard and a fixed amount of the SIS protein. (Wang et al., Targeted absolute quantitative proteomics with SILAC internal standards and unlabeled full- length protein calibrators (TAQSI), Rapid Commun. Mass. Spectrom. (2016) 30:553-561.) The concentration of endogenous biomarker in a sample containing (spiked with) the presence of the same fixed amount of SIS protein can then be compared to the calibration curve to calculate an absolute concentration of the unknown.

[0079] As disclosed herein, ADA12, (or ADAM12), refers to Disintegrin and metalloproteinase domain-containing protein 12 (Gene ID: 8038, UniProt ID: 043184), which is a secreted and membrane protein (different isoforms) highly expressed in placental trophoblasts. Maternal serum ADAM 12 has been used as a marker of prenatal development. The protein is implicated in processes related to cell-cell and cell-matrix interactions, such as fertilization, skeletal muscle regeneration, and neurogenesis. Alternative splicing results in different isoforms, with shorter forms being secreted and longer forms being membrane-bound. ADA12 has been found to play a key role in regulating trophoblast migration and invasion suring early pregnancy and helps anchor trophoblast columns in the placenta during the first trimester (Christians, J.K. and A.G. Beristain, ADA12 and PAPP-A: Candidate regulators of trophoblast invasion and first trimester markers of healthy trophoblasts. Cell Adh Migr, 2016. 10(1-2): p. 147-53). It also cleaves insulin-like growth factor (IGF)-binding proteins that regulate the concentration of IGF, which is important for fetal growth (see, e.g., Myers, J.E., et al., Mid-trimester maternal ADA 12 levels differ according to fetal gender in pregnancies complicated by preeclampsia. Reprod Sci, 2015. 22(2): p. 235-41). Based on aberrant expression at various times during pregnancy, ADA12 has been linked to pre-term birth, fetal growth restriction, preeclampsia, Down Syndrome, and likelihood of the fetus being small for gestational age at birth (see, e.g., Andres, F., et al., A disintegrin and metalloproteinase 12 (ADA12) is reduced at 36 weeks' gestation in pregnancies destined to deliver small for gestational age infants. Placenta, 2022. 117: p. 1-4; Goetzinger, K.R., et al., First-trimester prediction of preterm birth using ADA12, PAPP -A, uterine artery Doppler, and maternal characteristics. Prenat Diagn, 2012. 32(10): p. 1002-7; Laigaard, J., et al., ADAM 12 as a first- trimester maternal serum marker in screening for Down syndrome. PrenatDiagn, 2006. 26(10): p. 973-9.; and Kasimis, C., et al., Predictive value of biochemical marker ADAM- 12 at first trimester of pregnancy for hypertension and intrauterine growth restriction. Clin Exp Obstet Gynecol, 2016. 43(1): p. 43-7). As detailed in the Examples herein, a statistical association between ADA12 and TTB is reported, and shows that the week in which delivery occurred was significantly different between the reported cohort’s highest and lowest expressors of ADA12, which, altogether, support the use of this protein as a predictor of derlivery date in term pregnancies.

[0080] As disclosed herein, KIT refers to Mast/stem cell growth factor receptor Kit (Gene ID: 3815, UniProt ID:P10721), which is a proto-oncogene and receptor tyrosine kinase that upon binding of its ligand, stem cell factor (SCF), phosphorylates intracellular targets that regulate cell proliferation, differentiation, migration and apoptosis. Alternative splicing leads to multiple isoforms, two that are single-pass type I membrane proeins and a third that is cytoplasmic. Variants in the gene are associated with the piebald trait, a pigmentation abnormality, and somatic mutations can lead to constitutive activation of the kinase, and subsequently, abnormal cell proliferation and cancer.

[0081] As disclosed herein, FETUA refers to Alpha-2-HS-glycoprotein (Gene ID: 197, UniProtID: P02765), which is a serum glyprotein with roles in bone and brain development and endocytosis. FETUA functions as a carrier protein for calcium phosphate, and thus FETUA deficiencies can lead to abnormal calcification of soft tissues. High levels of FETUA are implicated in insulin resistance by enhancing the binding of free fatty acids to TLR4 and also by downregulating adiponectin.

[0082] As disclosed herein, ENPP2 refers to Ectonucleotide pyrophosphatase/ phosphodiesterase family member 2, also known as autotaxin, (Gene ID: 5168, UniProtID: Q13822), which is a secreted protein with broad tissue distribution, including placental expression. ENPP2 activity is highest in the third trimester and also in patients with threatened preterm birth; thus, it is thought to have roles in induction of parturition (Tokumura A, Majima E, Kariya Y, Tominaga K, Kogure K, Yasuda K, Fukuzawa K. Identification of human plasma lysophospholipase D, a lysophosphatidic acid-producing enzyme, as autotaxin, a multifunctional phosphodiesterase. J Biol Chem. 2002 Oct 18;277(42):39436-42). As a phospholipase, it catalyzes formation of lysophosphatidic acid (LPA), which in turn induces cell proliferation and chemotaxis. ENPP2 stimulates angiogenesis and cell motility.

[0083] As disclosed herein, A2GL refers to Leucine-rich alpha-2-glycoprotein (Gene ID: 116844, UniProtID: P02750), which is a secreted protein implicated in many disease conditions such as cancer, cardiovascular, neurological, and inflammatory disorders. High levels of A2GL activate pro-angiogenic pathways via the modification of TGFP signaling (Camilli, C., Hoeh, A.E., De Rossi, G. et al. LRG1 : an emerging player in disease pathogenesis. J Biomed Sci 29, 6 (2022)).

[0084] As disclosed herein, IGF1 refers to Insulin-like growth factor I (Gene ID: 3479, UniProtID: P05019), which is a plasma peptide growth factor related to insulin that is a major driver of growth and development, including placental and fetal growth during pregnancy. IGF1 promotes implantation and placental growth and circulating maternal IGR1 levels increase markedly in the third trimester. Mutations in IGF1 are associated with severe fetal growth restriction (see, e.g., Kaur, H., Muhlhausler, B. S., Roberts, C. T., & Gatford, K. L. (2021). The growth hormone-insulin-like growth factor axis in pregnancy. Journal of Endocrinology, 251(3), R23-R39).

[0085] As disclosed herein, CSH refers to chorionic somatomammotropin (UniProtID: P0DML2 for CSH1; P0DML3 for CSH2), and is a reported marker of gestational age. The circulating levels of CSH, which increase with pregnancy progression, correlate with activation of STAT-5 signaling activity in CD4 T cells. This signaling event is a strong predictor of gestational age (Aghaeepour, N., et al., A proteomic clock of human pregnancy. Am J Obstet Gynecol, 2018. 218(3): p. 347 el-347 el4).

[0086] As disclosed herein, SOM2 refers to growth hormone 2 (UniProt ID: P01242), and is a placentally derived hormone and a key driver of fetal growth and placental development. It steadily increases through pregnancy, peaking around week 37 of gestation. The gestational age at peak placental SOM2 levels has been associated with pregnancy length and thus, is considered to be an indicator of deliver date (Badsha, M.B., E.A. Martin, and A.Q. Fu, MRPC: An R Package for Inference of Causal Graphs. Front Genet, 2021. 12: p. 651812).

[0087] As disclosed herein, CGB1 refers to chorionic gonadotropin subunit pi (UniProtID: A6NKQ9). CGB1 is the subunit that gives human chorionic gonadotropin (hCG) its functional specificity. hCG is critical for fetal viability as it plays a central role in thickening the uterine lining, stimulating progesterone production, stopping menstruation, and enhancing embryo implantation and survival (Montagnana, M., et al., Human chorionic gonadotropin in pregnancy diagnostics. Clin Chim Acta, 2011. 412(17-18): p. 1515-20). Quantitative measurements of hCG are currently used in clinical practice to calculate gestational age (Korevaar, T.I., et al., Reference ranges and determinants of total hCG levels during pregnancy: the Generation R Study. Eur J Epidemiol, 2015. 30(9): p. 1057-66). In normal pregnancies, hCG levels are highest at the end of the first trimester, then gradually decrease over the rest of pregnancy. In addition, one study showed that when the CGB transcript was included in a model that contained measurements of eight cell-free RNAs (cfRNAs), it was predictive of delivery within 14 days of the actual date with an accuracy ranging from 23-45% depending on trimester, roughly comparable to ultrasound with an accuracy of 48% (see, e.g., Ngo, T.T.M., et al., Noninvasive blood tests for fetal development predict gestational age and preterm delivery. Science, 2018. 360(6393): p. 1133-1136).

[0088] As disclosed herein, SVEP1 refers to Sushi, von Willebrand Factor type A, EGF, and pentraxin domain-containing protein (UniProtID: Q4LDE5). SVEP1 has been shown to be upregulated in pregnancy, as well as correlate with gestational age of chorionic villi (Hannibal, R.L., et al., Investigating human placentation and pregnancy using first trimester chorionic villi. Placenta, 2018. 65: p. 65-75).

[0089] As disclosed herein, PSG1 refers to pregnancy-specific pi Glycoprotein 1 (UniProtID: Q9UQ72). PSG1 is a placentally expressed protein that binds to heparin sulfate proteoglycans, the latency-associated peptide of TGF-pi, and the platelet integrin alip3 (see, e.g., Blois, S.M., et al., Pregnancy-specific glycoprotein 1 (PSG1) activates TGF-beta and prevents dextran sodium sulfate (DSS)-induced colitis in mice. Mucosal Immunol, 2014. 7(2): p. 348-58; Lisboa, F.A., et al., Pregnancy-specific glycoprotein 1 induces endothelial tubulogenesis through interaction with cell surface proteoglycans. J Biol Chem, 2011. 286(9): p. 7577-86; and Shanley, D.K., et al., Pregnancy-specific glycoproteins bind integrin alphallbbeta3 and inhibit the platelet-fibrinogen interaction. PLoS One, 2013. 8(2): p. e57491). Through interactions with these ligands, PSG1 helps mediate the immune shift away from innate immunity in pregnancy and dampens platelet aggregation and thrombosis to counterbalance the prothrombotic maternal environment of pregnancy (see, e.g., Martinez, F.F., et al., The role of pregnancy-specific glycoprotein la (PSGla) in regulating the innate and adaptive immune response. Am J Reprod Immunol, 2013. 69(4): p. 383-94; Martinez, F.F., et al., Pregnancy-specific glycoprotein la activates dendritic cells to provide signals for Thl 7- , Th2-, and Treg-cell polarization. Eur J Immunol, 2012. 42(6): p. 1573-84; and Shanley, D.K., et al., Pregnancy-specific glycoproteins bind integrin alphallbbeta3 and inhibit the platelet- fibrinogen interaction. PLoS One, 2013. 8(2): p. e57491). PSG1 expression gradually increases throughout pregnancy, reaching its peak around 36 weeks of gestation (see, e.g., Zhou, G.Q., et al., Highly specific monoclonal antibody demonstrates that pregnancy-specific glycoprotein (PSG) is limited to syncytiotr ophoblast in human early and term placenta. Placenta, 1997. 18(7): p. 491-501; and Pluta, M., et al., Radioimmunoassay of serum SP 1 andHPL in normal and abnormal pregnancies. Arch Gynecol, 1979. 227(4): p. 327-36).

[0090] As disclosed herein, PSG2 refers to Pregnancy-Specific pi Glycoprotein 2 (UniProtID: Pl 1465). Similarly, as disclosed herein, PSG11 refers to Pregnancy-Specific pi Glycoprotein 11 (UniProtID: Q9UQ72). Both proteins are placental glycoproteins that play a role in immune cell and angiogenesis modulation. Both proteins are also placentally expressed (see, e.g., Atlas, T.H.P. 2024).

[0091] As disclosed herein, DPEP2 refers to dipeptidase 2 (UniProtID: Q9H4A9). DPEP2 is a hydrolase enzyme that plays a role in cell differentiation in pregnancy, and is also placentally expressed (see, e.g., Atlas, T.H.P. 2024).

[0092] As disclosed herein, APOC3 refers to apolipoprotein C-III (UniProtID: P02656). APOC3 is a lipid binding protein that serves as a modulator of lipid metabolism in pregnancy. APOC3 has also been reported to have associations with pregnancy complications such as gestational diabetes mellitus (GDM) (see, e.g., Ramanjaneya, M., et al., apoA2 correlates to gestational age with decreased apolipoproteins A2, Cl, C3 and E in gestational diabetes. BMJ Open Diabetes Res Care, 2021. 9(1)).

[0093] As disclosed herein, PGRP2 refers to peptidoglycan recognition protein 2 (UniProtID: Q96PD5). PGRP2 is a pattern recognition molecule expressed mainly in gut epithelial cells that recognizes and hydrolyzes bacterial peptidoglycan (PGN) (see, e.g., Wang, Z.M., et al., Human peptidoglycan recognition protein-L is an N-acetylmuramoyl-L-alanine amidase. J Biol Chem, 2003. 278(49): p. 49044-52; Gelius, E., et al., A mammalian peptidoglycan recognition protein with N-acetylmuramoyl-L-alanine amidase activity. Biochem Biophys Res Commun, 2003. 306(4): p. 988-94; and Lo, D., et al., Peptidoglycan recognition protein expression in mouse Peyer's Patch follicle associated epithelium suggests functional specialization. Cell Immunol, 2003. 224(1): p. 8-16). Bacterial PGN derived from the gut microbiota has been shown to influence brain development (see, e.g., Tosoni, G., M. Conti, and R. Diaz Heijtz, Bacterial peptidoglycans as novel signaling molecules from microbiota to brain. Curr Opin Pharmacol, 2019. 48: p. 107-113), and PGRP2 has been implicated as a mediator of this phenomenon owing to its influence on expression of brain- derived neurotropic factor and the autism risk gene c-Met (Arentsen, T., et al., The bacterial peptidoglycan-sensing molecule Pglyrp2 modulates brain development and behavior. Mol Psychiatry, 2017. 22(2): p. 257-266). [0094] As disclosed herein, PAEP refers to progestagen-associated endometrial protein (UniProtID: P09466). PAEP helps modulate the immune system in pregnancy. During the second trimester of pregnancy, a tightly regulated suppression of the immune system occurs to prevent the mother’ s immune system from rej ecting the fetus. This suppression is characterized by a shift towards a Th2 immune response, which decreases the number of several types of innate immune cells including natural killer (NK) cells (see, e.g., Borzychowski, A.M., et al., Changes in systemic type 1 and type 2 immunity in normal pregnancy and pre-eclampsia may be mediated by natural killer cells. Eur J Immunol, 2005. 35(10): p. 3054-63; and Sargent, I.L., A.M. Borzychowski, and C.W. Redman, NK cells and human pregnancy— an inflammatory view. Trends Immunol, 2006. 27(9): p. 399-404). PAEP has been shown to facilitate this natural immune shift by mediating apoptosis of NK cells (see, e.g., Okamoto, N., et al., Suppression by human placental protein 14 of natural killer cell activity. Am J Reprod Immunol, 1991. 26(4): p. 137-42; and Mukhopadhyay, D., et al., Placental protein 14 induces apoptosis in T cells but not in monocytes. J Biol Chem, 2001. 276(30): p. 28268-73).

[0095] As disclosed herein, NCHL1 refers to Cell Adhesion Molecule LI Like Protein (UniProtID: 000533). NCHL1 is an adhesion molecule that is expressed on the surface of neurons and plays a role in their migration and organization. Mutations in the NCHL1 gene result in brain malformation and neurodevel opmental delay (see, e.g., Li, Y.T., et al., L1CAM mutations in three fetuses diagnosed by medical exome sequencing. Taiwan J Obstet Gynecol, 2020. 59(3): p. 451-455), and neurological phenotypes attributed to fetal alcohol syndrome have been partially attributed to disruption of functions mediated by NCHL1 (see, e.g., Arevalo, E., et al., An alcohol binding site on the neural cell adhesion molecule LI. Proc Natl Acad Sci U S A, 2008. 105(1): p. 371-5; and Bearer, C.F., Mechanisms of brain injury: LI cell adhesion molecule as a target for ethanol-induced prenatal brain injury. Semin Pediatr Neurol, 2001. 8(2): p. 100-7). NCHL1 is highly expressed in the developing fetal spinal cord and in extracellular vesicles, suggesting that during pregnancy it serves as an extracellular signaling molecule to support axon outgrowth (see, c.g, Cau, F., et al., Expression of LI Cell Adhesion Molecule (L1CAM) in extracellular vesicles in the human spinal cord during development. Eur Rev Med Pharmacol Sci, 2022. 26(17): p. 6273-6282).

[0096] As disclosed herein, LYAM1 refers to L-selectin (UniProtID: P14151). LYAM1 is an adhesion molecule expressed on the surface of leukocytes, and blastocysts and in cytotrophoblast aggregates. This protein facilitates blastocyst adhesion to the endometrium during pregnancy to enable embryo implantation and is essential for proper anchoring of the fetus to the decidua (see, c.g, Prakobphol, A., et al., A role for the L-selectin adhesion system in mediating cytotrophoblast emigration from the placenta. Dev Biol, 2006. 298(1): p. 107- 17). LYAM1 is highly expressed at the beginning of pregnancy, then tapers during the second trimester (see, e.g., Genbacev, O.D., et al., Trophoblast L-selectin-mediated adhesion at the maternal-fetal interface. Science, 2003. 299(5605): p. 405-8). Its levels may remain elevated in preeclampsia, likely because of increased leukocyte activation stemming from inflammatory signaling (see, e.g., Acar, A., et al., Selectins in normal pregnancy, pre-eclampsia and missed abortus. Haematologia (Budap), 2001. 31(1): p. 33-8).

[0097] As used herein, the term “reversal” refers to the ratio of the measured level or value of one analyte over that of another analyte. For example, in some instances, the “upregulated” analyte is the numerator, and the “downregulated” analyte is the denominator in a ratio or pairing, whereas in some instances this may be reversed (i.e., downregulated analyte over upregulated analyte). In some instances, the analyte level or value is itself a ratio of the level of the endogenous analyte over that of the level of a corresponding standard or reference (e.g., stable isotopic standard analyte). This is sometimes referred to herein as response ratio or relative ratio.

[0098] As used herein, the term “reversal pair” refers to biomarkers in pairs that exhibit a change in value between the classes being compared. The detection of reversals in protein levels or gene expression levels can in some instances eliminate the need for data normalization or the establishment of population- wide thresholds. Encompassed within the definition of any reversal pair is the corresponding reversal pair wherein individual biomarkers are switched between the numerator and denominator. One skilled in the art will appreciate that such a corresponding reversal pair is equally informative with regard to its predictive power.

[0099] The term “reversal value” refers to the ratio of the relative levels corresponding to the abundance of two analytes and, in some instances, can serve to both normalize variability and amplify diagnostic signal. In some instances, a reversal value refers to the ratio of the relative peak area of an an up-regulated (interchangeably referred to as “over-abundant,” upregulation as used herein simply refers to an observation of relative abundance) analyte over the relative peak area of a down-regulated analyte (interchangeably referred to as “under- abundant;” down- regulation as used herein simply refers to an observation of relative abundance). In some instances, a reversal value refers to the ratio of the relative peak area of an up-regulated analyte over the relative peak area of an up-regulated analyte, where one analyte differs in the degree of up-regulation relative the other analyte. In some instances, a reversal value refers to the ratio of the relative peak area of a down-regulated analyte over the relative peak area of a down-regulated analyte, where one analyte differs in the degree of down- regulation relative the other analyte. Thus, in some instances, as set forth above, the “upregulated” analyte is the numerator, and the “downregulated” analyte is the denominator in a ratio or pairing of such a reversal value, whereas in some instances, this may be reversed (z.e., a “downgulated” analyte is the numerator and an “upregulated analyte” is the denominator). [00100] As used herein, the term “gravidity” refers to the number of pregnancies, including current pregnancy, of a pregnant female.

[00101] As used herein, the phrase “term” refers to birth at or after 37^0/7 weeks of gestation. [00102] For methods directed to predicting TTB, it is understood that the term “birth” encompasses birth following spontaneous or non-spontaneous onset of labor, by induction, via C-section, with or without rupture of membranes.

[00103] Abbreviations

[00104] Table 1 below summarizes a list of abbreviations for terms commonly disclosed herein and their respective definitions.

Table 1

[00105] Biological Samples and Biomarkers for Determining the PDD and/or TBB

[00106] The disclosure provides biomarkers, reversal pairs, methods, compositions, and kits for determining the PDD and/or TTB in a pregnant female. In particular, the proteins and peptides disclosed herein as components of pairs, ratios and/or reversal pairs serve as biomarkers for determining the PDD, predicting GAB, predicting TTB, either individually, in ratios, or reversal pairs, each of which can be incorporated into a model (e.g., regression formula with or without clinical variables). In some embodiments, certain biomarkers or peptides can be excluded (or not used or included) from the biomarkers, reversal pairs, methods, compositins, and kits herein. For example, in some embodiments, when a single biomarker is measured, assayed, detected, quantified, etc., one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 can be excluded from such a measurement, assay, detection, quantification, etc. Similarly, in some embodiments, when one or more pairs of biomarkers are being measured, assayed, detected, quantified, etc., at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 can be excluded from said one or more pairs being measured, assayed, detected, quantified, etc. Additional biomarkers that can be excluded include, but are not limited to, any one or more of such listed in Table 2.

[00107] In addition, the compositions, kits, and methods described herein may comprise surrogate peptides for each of the proteins corresponding to the peptide biomarkers disclosed herein, and can serve as a component of pairs, ratios and/or reversal pairs for determining the PDD, predicting GAB, predicting TTB, estimating GA, either individually, in ratios, reversal pairs or in panels of biomarkers/reversal pairs, each of which can be incorporated into a model. [00108] In addition to the specific biomarkers identified in this disclosure — e.g., by name, sequence, or reference — the present disclosure also provides use of biomarker variants that are at least 90% or at least 95% or at least 97% identical to the exemplified sequences and that are now known or later discovered and that have utility for the methods of the disclosure. These variants may represent polymorphisms, splice variants, mutations, and the like. In this regard, the instant specification discloses multiple art-known proteins in the context of the described embodiments and provides exemplary peptide sequences that can be used to identify, detect or measure the level of these proteins. However, those skilled in the art appreciate that additional sequences or other information can easily be identified that can provide additional characteristics of the disclosed biomarkers and that the exemplified references are in no way limiting with regard to the disclosed biomarkers. Such variants can be surrogates for each biomarker in an assay of the disclosure.

[00109] As described herein, various techniques and reagents find use in the methods of the present disclosure. Suitable samples in the context of the present disclosure include, for example, blood, plasma, serum, amniotic fluid, vaginal secretions, saliva, and urine. In some embodiments, the biological sample is selected from the group consisting of whole blood, plasma, and serum. In a particular embodiment, the biological sample is whole blood. In a particular embodiment, the biological sample is serum. In other embodiments, the biological sample is a dried sample. In further embodiments, the biological sample is selected from the group consisting of dried whole blood, dried serum, or dried plasma. In some embodiments, the biological sample is dried capillary whole blood. In some embodiments, the biological sample is collected, stored and shipped using an at-home or in-clinic handheld bodily fluid collection device or a shoulder-mounting device, e.g., the Tasso-M20 device by Tasso Inc., a volumetric absorptive microsampling device, e.g., a Mitra® device, or a dried blood spot (DBS) collection card, e.g., a filter paper from which a biological sample from a subject’s finger prick is collected and dried on. In some embodiments, the biological sample is collected, stored, and shipped using an at-home or in-clinic handheld bodily fluid collection device. In other embodiments, the biological sample is collected, stored, and shipped using an at-home or inclinic volumetric absorptive microsampling device. In some embodiments, systems, methods and fixating agents (e.g., absorbent filter paper) that do not use or have metal chelators, such as ethylenediaminetetraacetic acid (EDTA) or citrate, with the exception of heparin, are used to detect, capture and/or store such samples. As described herein, biomarkers can be detected through a variety of assays and techniques known in the art. As further described herein, such assays include, without limitation, enzyme-linked immunosorbent assays (ELISAs), mass spectrometry (MS)-based assays, antibody -based assays as well as assays that combine aspects of the three.

[00110] In some embodiments, the disclosure provides methods of obtaining and collecting biological samples. In some embodiments, the biological sample is selected from the group consisting of whole blood, plasma, and serum. In some embodiments, the biological sample is whole blood. In some embodiments, the biological sample is serum. In some embodiments, the biological samples are dry samples. In some embodiments, the embodiments, the biological samples are selected from the group consisting of dried whole blood, dried plasma, and dried serum. In particular embodiments, the biological samples are dried capillary whole blood samples.

[00111] A variety of sample collection and drying of the samples can be used for preparing the samples used in the compositions and methods described herein. Typically, dried blood samples have been collected and tested using conventional blood spot testing, where patients (e.g., pregnant females) place blood drops on a filter card after a finger prick with a lancet. This is followed by drying, which then may be used for storange and analysis. Such typical methods of sample preparation can be used in the compositions and methods described herein. However, newer approaches have been developed. One such approach that can be used in the compositions and methods described herein involves a microsampling device which utilizes volumetric absorptive microsampling (VAMS), such as a Mitra® device (see, e.g., Rudge, J., Why consider two volumetric blood microsampling devices? 2023, Neoteryx.) This device allows a precise volume of, e.g., blood, to be collected to account for variations in hematocrit levels. In some embodiments, the biological sample obtained from a pregnant female is a dried sample collected, stored, and shipped using an at-home or in-clinic volumetric absorptive microsampling device. In some embodiments, the biological sample collected, stored and shipped using an at-home or in-clinic volumetric absorptive microsampling device is a biological sample selected from the group consisting of dried capillary whole blood, dried serum, or dried plasma.

[00112] In some embodiments, the biological sample obtained from a pregnant female is collected, stored and shipped using an at-home or in-clinic handheld bodily fluid collection device. The Tasso-M20 device by Tasso, Inc., for instance, is a device used to collect, store, and transport capillary blood for testing in a centralized laboratory (see, e.g., Tasso, Inc. (n.d.). Tasso-M202) In some embodiments, the biological sample collected, stored, and shipped using an at-home or in-clinic handheld bodily fluid collection device is a dried sample. In some embodiments, the dried sample is selected from the group consisting of dried capillary whole blood, dried serum, or dried plasma. Other sample types are also contemplated, such that GABD, as used herein unless otherwise indicated, is meant to encompass the gestational age at sample collection irrespective of the sample type or the means of collection. In some embodiments, the biological sample is refrigerated or frozen after collection from the pregnant female. In some embodiments, the biological sample is dried before analysis. In some embodiments, the biological sample is collected by venous blood draw (e.g., venipuncture) or by capillary blood extraction (e.g., micro-lancets).

[00113] In some embodiments, protein biomarkers described herein include, for example, the proteins and example peptides listed in Table 2:

Table 2

[00114] In some embodiments, the methods, compositions, uses, and kits herein exclude, or do not use or include, certain biomarkers, including, but not limited to, those listed in Table 2. For example, in some embodiments of the methods, compositions, uses, and kits herein, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included.

[00115] In some embodiments, protein biomarkers pairs described herein include, for example, the protein pairs (Protein 1 paired with Protein 2) and example peptides listed in Table 3:

Table 3

[00116] In some embodiments, the capture agents herein bind to a region of any of the biomarkers of Table 2, or biomarker pairs of Table 3, comprising the respective amino acid sequences of the biomarkers.

[00117] The stability of the various compounds in the biomarker products/ analytes disclosed herein are known to vary. Serum ADA12 samples, for instance, have previously been shown to be unstable under many routine laboratory conditions, with stability times of around 15 hours or less at 30°C, around 20 hours or less at room temperature, and around 51 hours at refrigerator temperature (see, e.g., Crowans et al. (2010) Prenatal Diagnosis, 30(6): 555-560). However, as detailed in the Examples herein, it was found that a dried serum sample comprising ADA12, assayed via ELISA, was stable for about 48 hours at 50°C. It is believed that the other samples for the biomarkers described herein, such as dried whole blood samples, exhibit the same or similar stability. In some embodiments, the biological sample is stable at 50°C for 48 hours. In some embodiments, the biological samples herein are detected, captured, and/or stored using systems, methods, and fixating agents (e.g. , absorbant filter paper) that do not use or have metal chelators, such as ethylenediaminetetraacetic acid (EDTA) or citrate. It is believed that ADA12 detection, for instance, is negatively impacted by the presence of such compounds. Heparin, however, is contemplated to be acceptable as an anti -coagulant due to its siginificantly different mechanism for anti-coagulation.

[00118] Reversal Values

[00119] As defined above, a reversal value is the ratio of the relative levels corresponding to the abundance of two analytes and, in some instances, can serve to both normalize variability and amplify diagnostic signal. In some embodiments, the two analytes comprise an upregulated analyte and/or a downregulated analyte. For example, in some embodiment, the “upregulated” analyte is the numerator, and the “downregulated” analyte is the denominator in a ratio or pairing of such a reversal value, whereas in some embodiments, this may be reversed (z.e., a “downgulated” analyte is the numerator and an “upregulated analyte” is the denominator). In some embodiments, the two analytes can be two upregulated analytes. In some embodiments, the two analytes can be two downregulated analytes. Examples of “upregulated” and “downregulated” biomarkers are shown, for instance, in Table 16. The advancements described herein lie, at least in part, in the selection of particular biomarkers that, when paired together, can accurately determine the PDD and/or TTB based on pairs of biomarkers. Accordingly, it is human ingenuity in selecting the specific biomarkers that are informative upon being paired — e.g., in novel reversals — that underlies some embodiments of the present disclosure.

[00120] One advantageous aspect of a reversal is the presence of complementary information in the two analytes, so that the combination of the two is more diagnostic of the condition of interest than either one alone. In some embodiments, the combination of the two analytes increases signal-to-noise ratio by compensating for biomedical conditions not of interest, pre-analytic variability and/or analytic variability. Out of all the possible reversals within a narrow window, a subset can be selected based on individual univariate performance. Additionally, a subset can be selected based on bivariate or multivariate performance in a training set, with testing on held-out data or on bootstrap iterations. For example, logistic or linear regression models can be trained, optionally with parameter shrinkage by LI or L2 or other penalties, and tested in leave-one-out, leave-pair-out or leave-fold-out cross-validation, or in bootstrap sampling with replacement, or in a held-out data set. In some embodiments, the analyte level or value is itself a ratio of the level or value of the endogenous analyte over that of the level or value of the corresponding standard or reference (e.g., stable isotopic standard analyte). This is sometimes referred to herein as response ratio or relative ratio. As disclosed herein, the ratio of the relative levels or values corresponding to the abundance of two analytes, for example, the ratio of the relative level or value of an up-regulated biomarker over the relative level or value) of a down-regulated biomarker, can be used to identify robust and accurate classifiers to determine PDD and/or predict GAB and/or TTB. Use of a ratio of biomarkers in the methods disclosed herein corrects for variability that is the result of human manipulation after the removal of the biological sample from the pregnant female. Such variability can be introduced, for example, during sample collection, processing, depletion, digestion or any other step of the methods used to measure the biomarkers present in a sample and is independent of how the biomarkers behave in nature. Accordingly, the disclosure generally encompasses the use of a reversal pair in a method of the disclosure to reduce variability and/or amplify, normalize or clarify diagnostic or predictive signal.

[00121] While the term reversal value includes the ratio of the relative level or value of an up regulated analyte over the relative level or value of a down regulated analyte and can serve to both normalize variability and amplify diagnostic signal, it is also contemplated that a pair of biomarkers described herein could be measured by any other means, for example, by substraction, addition or multiplication of relative levels or values. The methods disclosed herein encompass the measurement of biomarker pairs by such other means.

[00122] The methods of the disclosure are advantageous, inter alia, because they can provide a simpler classifier that is independent of additional data normalization, helps to avoid overfitting, and results in a simple assay that is easy to implement in a clinic or laboratory. The use of marker pairs based on changes in reversal values that are independent of additional data normalization was used in the development of the predictive biomarkers disclosed herein. Because quantification of any single protein can be subject to uncertainties caused by measurement variability, normal fluctuations, and individual-related variation in baseline expression, identification of pairs of markers that may be under coordinated, systematic regulation enables robust methods for individualized diagnosis and prognosis.

[00123] Compositions and Methods

[00124] The present disclosure provides an improved process that applies the aforementioned discoveries to enable a new and useful process for estimating the PDD and/or estimating TTB with higher accuracy than currently practiced clinical methods. [00125] The concepts of PDD and TTB are directly related, and a skilled person can adjust the methods for determining PDD to be used to determine TTB and vice versa. Accordingly, the PDD can be used to predict TTB and vice versa. Specifically, if the estimated gestational age (GA) of a pregnancy is X at the time of blood draw (GABD), then TTB can be estimated from PDD as follows: TTB = PDD - X. And PDD can be estimated from a TTB predictor as follows: PDD = X + TTB, where the units used are days.

[00126] In some embodiments, the disclosure provides a method of determining the PDD for a pregnant female, the method comprising measuring in a biological sample obtained from the pregnant female a reversal value for the biomarkers ADA12/KIT. In some embodiments, the method comprises measuring in a biological sample obtained from the pregnant female a reversal value for the biomarkers ADA12/FETUA. In some embodiments, the method comprises measuring in a biological sample obtained from the pregnant female a reversal value for the biomarkers ADA12/ENPP2. In some embodiments, the method comprises measuring in a biological sample obtained from the pregnant female a reversal value for the biomarkers ADA12/A2GL. In some embodiments, the method comprises measuring in a biological sample obtained from the pregnant female a reversal value for the biomarkers ADA12/IGF1. In some embodiments, the method comprises measuring in a biological sample obtained from the pregnant female a reversal value for a pair of isolated biomarkers comprising two isolated biomarkers selected from Table 2. In some embodiments, the pair of isolated biomarkers comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers are shown, for instance, in Table 16. In some embodiments, the pair of isolated biomarkers comprises two upregulated biomarkers. In some embodiments, the pair of isolated biomarkers comprises two downregulated biomarkers. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included.

[00127] In some embodiments, the disclosure provides a method of determining the PDD for a pregnant female, the method comprising measuring in a biological sample obtained from the pregnant female an amount of one or more isolated biomarkers. In some embodiments, the one or more isolated biomarkers is selected from Table 2. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included. [00128] In some embodiments, the disclosure provides a method of determining the PDD for a pregnant female, the method comprising measuring in a biological sample obtained from the pregnant female a reversal value for a pair (or two or more pairs) of biomarkers consisting of ADA12/KIT to determine the PDD for said pregnant female. In some embodiments, the disclosure provides a method of determining the PDD for a pregnant female, the method comprising measuring in a biological sample obtained from the pregnant female a reversal value for a pair (or two or more pairs) of biomarkers consisting of ADA12/FETUA to determine the PDD for said pregnant female. In some embodiments, the disclosure provides a method of determining the PDD for a pregnant female, the method comprising measuring in a biological sample obtained from the pregnant female a reversal value for a pair (or two or more pairs) of biomarkers consisting of ADA12/ENPP2 to determine the PDD for said pregnant female. In some embodiments, the disclosure provides a method of determining the PDD for a pregnant female, the method comprising measuring in a biological sample obtained from the pregnant female a reversal value for a pair (or two or more pairs) of biomarkers consisting of ADA12/A2GL to determine the PDD for said pregnant female. In some embodiments, the disclosure provides a method of determining the PDD for a pregnant female, the method comprising measuring in a biological sample obtained from the pregnant female a reversal value for a pair (or two or more pairs) of biomarkers consisting of ADA12/IGF1 to determine the PDD for said pregnant female. In some embodiments, the disclosure provides a method of determining the PDD for a pregnant female, the method comprising measuring in a biological sample obtained from the pregnant female a reversal value for a pair (or two or more pairs) of biomarkers selected from Table 2 to determine the PDD for said pregnant female. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 16. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two upregulated biomarkers. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two downregulated biomarkers. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included.

[00129] In some embodiments, the disclosure provides a pair (or two or more pairs) of isolated biomarkers selected from Table 2 (e.g., ADA12 and KIT, ADA12 and FETUA, ADA12 and ENPP2, ADA12 and A2GL, or ADA12 and IGF1), wherein the pair of biomarkers exhibits a higher ratio in pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD, in some embodiments of which X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days; Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days; and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Y is no more than 1, 2, 3, or 4 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Z is no more than 1, 2, 3, or 4 days. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 16. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two upregulated biomarkers. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two downregulated biomarkers. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included.

[00130] In some embodiments, the disclosure provides one or more isolated biomarkers selected from Table 2 to be used in any of the methods, compositions, kits, and uses described herein. In some embodiments, the methods, compositions, kits, and uses herein exclude, or do not use, certain biomarkers, including, but not limited to, those listed in Table 2. For example, in some embodiments of the methods, compositions, kits, and uses herein, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included.

[00131] In some embodiments, the present disclosure provides a composition comprising one or more isolated biomarkers selected from Table 2, wherein each of the one or more biomarkers exhibits a change in the amount pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, the present disclosure provides a composition comprising a pair (or two or more pairs) of isolated biomarkers selected from Table 2, wherein said pair of biomarkers exhibits a change in reversal value between pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, the pair of isolated biomarkers is selected from the pairs listed in Table 3. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 17. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two upregulated biomarkers. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two downregulated biomarkers. In some embodiments, at least one of S0M2, CSH, CGB1, SVEP1, CHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of S0M2, CSH, CGB1, and SVEP1 are not used or included. In some embodiments, the pair of isolated biomarkers consists of ADA12/KIT (e.g, FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g, YVSELHLTR peptide (SEQ ID NO: 2) or LCLHCSVDQEGK peptide (SEQ ID NO: 3) for KIT). In some embodiments, the pair of isolated biomarkers consists of ADA12/FETUA (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g, FSVVYAK peptide (SEQ ID NO: 4) for FETUA). In some embodiments, the pair of isolated biomarkers consists of ADA12/ENPP2 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., TEFLSNYLTNVDDITLVPGTLGR peptide (SEQ ID NO: 5) or TYLHTYESEI peptide (SEQ ID NO: 6) for ENPP2). In some embodiments, the pair of isolated biomarkers consists of ADA12/A2GL (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., DLLLPQPDLR peptide (SEQ ID NO: 7) for A2GL). In some embodiments, the pair of isolated biomarkers consists of ADA12/IGF1 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., GFYFNKPTGYGSSSR peptide (SEQ ID NO: 8) for IGF1). In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Y is no more than 1, 2, 3, or 4 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Z is no more than 1, 2, 3, or 4 days. In some embodiments, the pregnant females are nulliparous.

[00132] In some embodiments, the present disclosure provides a use of a composition comprising one or more isolated biomarkers in a method of determining the PDD or TTB for a pregnant female. In some embodiments, the one or more isolated biomarkers are selected from Table 2. In some embodiments, each of the one or more isolated biomarkers exhibits a change in an amount between pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, the present disclosure provides a use of a composition comprising a pair of isolated biomarkers in a method of determining the PDD or TTB for a pregnant female. In some embodiments, said pair of isolated biomarkers exhibits a change in reversal value between pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, and Z is no more than 1, 2,

3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, X is no more than 1, 2, 3,

4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In further embodiments, X is no more than 1, 2, 3, 4,

5, 6, or 7 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Y is no more than 1, 2, 3, or 4 days. In some embodiments, Z is no more than 1,

2, 3, 4, 5, 6, or 7 days. In further embodiments, Z is no more than 1, 2, 3, or 4 days. In some embodiments, said pair of isolated biomarkers comprises ADA12 and an isolated biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1. In further embodiments, said pair of isolated biomarkers comprises ADA12 and KIT. In other embodiments, said pair of isolated biomarkers comprises ADA12 and FETUA. In some embodiments, said pair of isolated biomarkers comprises ADA12 and ENPP2. In some embodiments, said pair of isolated biomarkers comprises ADA12 and A2GL. In some embodiments, said pair of isolated biomarkers comprises ADA12 and IGF1. In some embodiments, said pair of isolated biomarkers comprises two isolated biomarkers selected from Table 2.

[00133] In some embodiments, the present disclosure provides a method of determining the PDD for a pregnant female, the method comprising measuring in a biological sample obtained from said pregnant female an amount of one or more isolated biomarkers selected from Table 2 to determine the PDD for said pregnant female. In some embodiments, each of the one or more isolated biomarkers exhibits a change in an amount between pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, X is no more than 1, 2,

3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Y is no more than 1, 2, 3, or 4 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Z is no more than 1, 2, 3, or 4 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 202 days, 126 through 160 days, or 161 through 202 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 150 days. In some embodiments, the biological sample is obtained at a GABD from 161 through 180 days. In some embodiments, the biological sample is obtained at a GABD from 181 days through 200 days. In some embodiments, the biological sample is obtained at a GABD of 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, or 150 days. In some embodiments, the biological sample is obtained at a GABD of 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, or 180 days. In some embodiments, the biological sample is obtained at a GABD of 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, or 202 days. In some embodiments, the pregnant female is nulliparous.

[00134] In some embodiments, the present disclosure provides a method of determining the PDD for a pregnant female, the method comprising measuring in a biological sample obtained from said pregnant female a reversal value for a pair (or two or more pairs) of isolated biomarkers selected from Table 2 to determine the PDD for said pregnant female. In some embodiments, the pair of isolated biomarkers is selected from the pairs listed in Table 3. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 17. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two upregulated biomarkers. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two downregulated biomarkers. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, CHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included. In some embodiments, the pair of isolated biomarkers consists of ADA12/KIT (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., YVSELHLTR peptide (SEQ ID NO: 2) or LCLHCSVDQEGK peptide (SEQ ID NO: 3) for KIT). In some embodiments, the pair of isolated biomarkers consists of ADA12/FETUA (e.g, FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g, FSVVYAK peptide (SEQ ID NO: 4) for FETUA). In some embodiments, the pair of isolated biomarkers consists of ADA12/ENPP2 e.g, FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g, TEFLSNYLTNVDDITLVPGTLGR peptide (SEQ ID NO: 5) or TYLHTYESEI peptide (SEQ ID NO: 6) for ENPP2). In some embodiments, the pair of isolated biomarkers consists of ADA12/A2GL (e.g, FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g, DLLLPQPDLR peptide (SEQ ID NO: 7) for A2GL). In some embodiments, the pair of isolated biomarkers consists of ADA12/IGF1 e.g, FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., GFYFNKPTGYGSSSR peptide (SEQ ID NO: 8) for IGF1). In some embodiments, said pair of isolated biomarkers exhibits a change in reversal value between pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Y is no more than 1, 2, 3, or 4 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Z is no more than 1, 2, 3, or 4 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 202 days, 126 through 160 days, or 161 through 202 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 150 days. In some embodiments, the biological sample is obtained at a GABD from 161 through 180 days. In some embodiments, the biological sample is obtained at a GABD from 181 days through 200 days. In some embodiments, the biological sample is obtained at a GABD of 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, or 150 days. In some embodiments, the biological sample is obtained at a GABD of 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, or 180 days. In some embodiments, the biological sample is obtained at a GABD of 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, or 202 days. In some embodiments, the pregnant female is nulliparous.

[00135] In some embodiments, the present disclosure provides a method of determining the TTB for a pregnant female, the method comprising measuring in a biological sample obtained from said pregnant female an amount of each of one or more isolated biomarkers selected from Table 2 to determine the TTB for said pregnant female. In some embodiments, each of said one or more isolated biomarkers exhibits a change in the amount between pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Y is no more than 1, 2, 3, or 4 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Z is no more than 1, 2, 3, or 4 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 202 days, 126 through 160 days, or 161 through 202 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 150 days. In some embodiments, the biological sample is obtained at a GABD from 161 through 180 days. In some embodiments, the biological sample is obtained at a GABD from 181 days through 200 days. In some embodiments, the biological sample is obtained at a GABD of 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, or 150 days. In some embodiments, the biological sample is obtained at a GABD of 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, or 180 days. In some embodiments, the biological sample is obtained at a GABD of 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, or 202 days. In some embodiments, the pregnant female is nulliparous. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included.

[00136] In some embodiments, the present disclosure provides a method of determining the TTB for a pregnant female, the method comprising measuring in a biological sample obtained from said pregnant female a reversal value for a pair (or two or more pairs) of isolated biomarkers selected from Table 2 to determine the TTB for said pregnant female. In some embodiments, the pair of isolated biomarkers is selected from the pairs listed in Table 3. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 17. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two upregulated biomarkers. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two downregulated biomarkers. In some embodiments, the pair of isolated biomarkers consists of ADA12/KIT (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, (e.g., YVSELHLTR peptide (SEQ ID NO: 2) or LCLHCSVDQEGK peptide (SEQ ID NO: 3) for KIT). In some embodiments, the pair of isolated biomarkers consists of ADA12/FETUA (e.g, FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., FSVVYAK peptide (SEQ ID NO: 4) for FETUA). In some embodiments, the pair of isolated biomarkers consists of ADA12/ENPP2 (e.g, FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., TEFLSNYLTNVDDITLVPGTLGR peptide (SEQ ID NO: 5) or TYLHTYESEI peptide (SEQ ID NO: 6) for ENPP2). In some embodiments, the pair of isolated biomarkers consists of ADA12/A2GL (e.g, FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., DLLLPQPDLR peptide (SEQ ID NO: 7) for A2GL). In some embodiments, the pair of isolated biomarkers consists of ADA12/IGF1 (e.g, FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., GFYFNKPTGYGSSSR peptide (SEQ ID NO: 8) for IGF1). In some embodiments, said pair of isolated biomarkers exhibits a change in reversal value between pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Y is no more than 1, 2, 3, or 4 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Z is no more than 1, 2, 3, or 4 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 202 days, 126 through 160 days, or 161 through 202 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 150 days. In some embodiments, the biological sample is obtained at a GABD from 161 through 180 days. In some embodiments, the biological sample is obtained at a GABD from 181 days through 200 days. In some embodiments, the biological sample is obtained at a GABD of 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, or 150 days. In some embodiments, the biological sample is obtained at a GABD of 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, or 180 days. In some embodiments, the biological sample is obtained at a GABD of 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, or 202 days. In some embodiments, the pregnant female is nulliparous. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, CHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included.

[00137] In some embodiments, the present disclosure provides a method of determining the PDD or TTB for a pregnant female, wherein the method comprises (a) obtaining a biological sample obtained from said pregnant female; (b) detecting the presence or amount of one or more isolated biomarkers in said biological sample, and (c) integrating one or more clinical or demographic variables with the detected presence or amount of said one or more isolated biomarkers into a predictive model for determining the PDD or TTB. In some embodiments, said detecting comprises subjecting said biological sample to (i) mass spectrometry (MS) quantification, or (ii) an assay that utilizes a capture agent that binds to each of the one or more isolated biomarkers. In some embodiments, said one or more isolated biomarkers is selected from Table 2. In some embodiments, the method further comprises measuring in said biological sample the amount of each of said one or more isolated biomarkers to determine the PDD or TTB. In some embodiments, each of said one or more isolated biomarkers exhibits a change in the amount between pregnant females who deliver X or more days before the estimated due date (EDD) or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days, and Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days, Y is no more than 1, 2, 3, or 4 days, and Z is no more than 1, 2, 3, or 4 days. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSGl are not used or included in the method. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included in the method.

[00138] In some embodiments, the present disclosure provides a method of determining the PDD or TTB for a pregnant female, wherein the method comprises (a) obtaining a biological sample obtained from said pregnant female, (b) detecting the presence or amount of a pair (or two or more pairs) of isolated biomarkers selected from Table 2 in said biological sample obtained from said pregnant female, and (c) measuring in said biological sample a reversal value for said pair of isolated biomarkers. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 16. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two upregulated biomarkers. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two downregulated biomarkers. In some embodiments, the pair of isolated biomarkers exhibits a change in reversal value between pregnant females who deliver X or more days before the estimated due date (EDD) or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days, and Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days, Y is no more than 1, 2, 3, or 4 days, and Z is no more than 1, 2, 3, or 4 days. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included in the method. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included in the method.

[00139] In some embodiments, the method of determining the PDD or TTB further comprises measuring in said biological sample the amount of each of said one or more biomarkers to determine the PDD or TTB, wherein the amount is integrated into said predictive model and gives a PDD or TTB that falls within +/-X days of the pregnant female’s actual delivery date (ADD) or actual TTB at least Y% of the time. In some embodiments, X is 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1, and Y is 50%, 51%, 52%, 53%, 54%, 55%, 56%, 57%, 58%, 59%, 60%, 61%, 62%, 63%, 64%, 65%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 80%, 81%, 82%,

83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%,

95%, 96%, 97%, 98%, 99% or 100%. In some embodiments, the amount of each of said one or more biomarkers is integrated into said predictive model and gives a PDD or TTB that falls within 3 days of the pregnant female’s ADD or actual TTB, and a PDD or TTB that is within 5 days of an estimated due date (EDD) of the pregnant female. [00140] In some embodiments of the methods of determining the PDD or TTB described herein, the detecting step comprises subjecting said biological sample to an assay that utilizes a capture agent that binds to at least one biomarker of said one or more isolated biomarkers, or said pair of isolated biomarkers. In some embodiments, said capture agent is selected from the group consisting of an antibody, antibody fragment, nucleic acid-based protein binding reagent, small molecule or variant thereof. In some embodiments, the capture agent binds to a region of ADA12 comprising the amino acid sequence FGFGGSTDSGPIR (SEQ ID NO: 1); the capture agent binds to a region of KIT comprising the amino acid sequence YVSELHLTR (SEQ ID NO: 2); the capture agent binds to a region of KIT comprising the amino acid sequence LCLHCSVDQEGK (SEQ ID NO: 3); the capture agent binds to a region of FETUA comprising the amino acid sequence FSVVYAK (SEQ ID NO: 4); the capture agent binds to a region of ENPP2 comprising the amino acid sequence TEFLSNYLTNVDDITLVPGTLGR (SEQ ID NO: 5); the capture agent binds to a region of ENPP2 comprising the amino acid sequence TYLHTYESEI (SEQ ID NO: 6); the capture agent binds to a region of A2GL comprising the amino acid sequence DLLLPQPDLR (SEQ ID NO: 7); or the capture agent binds to a region of IGF 1 comprising the amino acid sequence GFYFNKPTGYGSSSR (SEQ ID NO: 8). In some embodiments, the capture agent binds to a region of any one of the isolated biomarkers in Table 2 comprising any of the respective amino acid sequences. In some embodiments, said assay is selected from the group consisting of an enzyme immunoassay (EIA), an enzyme-linked immunosorbent assay (ELISA), and a radioimmunoassay (RIA). In some embodiments, said pair of isolated biomarkers comprises ADA12 and an isolated biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1. In further embodiments, said pair of isolated biomarkers comprises ADA12 and KIT. In other embodiments, said pair of isolated biomarkers comprises ADA12 and FETUA. In other embodiments, said pair of isolated biomarkers comprises ADA12 and ENPP2. In other embodiments, said pair of isolated biomarkers comprises ADA12 and A2GL. In other embodiments, said pair of isolated biomarkers comprises ADA12 and IGF1. In some embodiments, said pair of isolated biomarkers comprises two isolated biomarkers selected from Table 2. In some embodiments, each said pair of isolated biomarkers comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 16. In some embodiments, said pair of isolated biomarkers comprises two upregulated biomarkers. In some embodiments, said pair of isolated biomarkers comprises two downregulated biomarkers. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, AP0C3, and PSGl are not used or included in the method. In some embodiments, at least one of S0M2, CSH, CGB1, and SVEP1 are not used or included in the method.

[00141] In some embodiments of the methods of determining the PDD or TTB described herein, the biological sample obtained from the pregnant female is collected, stored, and shipped using an at-home or in-clinic handheld bodily fluid collection device, a volumetric absorptive microsampling device, or a dried blood spot card. In particular embodiments, the biogical sample obtained from the pregnant female is collected, stored, and shipped using an at-home or in-clinic handheld bodily fluid collection device. In other embodiments, the biological sample obtained from the pregnant female is collected, stored, and shipped using an at-home or in-clinic volumetric absorptive microsampling device. In some embodiments, the biological sample is selected from the group consisting of dried capillary whole blood, dried serum, or dried plasma. In particular embodiments, the biological sample is dried capillary whole blood. In some embodiments, the biological sample is obtained at a GABD from 126 through 202 days, 126 through 160 days, or 161 through 202 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 150 days. In some embodiments, the biological sample is obtained at a GABD from 161 through 180 days. In some embodiments, the biological sample is obtained at a GABD from 181 days through 200 days. In some embodiments, the biological sample is obtained at a GABD of 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, or 150 days. In some embodiments, the biological sample is obtained at a GABD of 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, or 180 days. In some embodiments, the biological sample is obtained at a GABD of 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, or 202 days. In some embodiments, the biological sample is stable at 50°C for 48 hours. In some embodiments, heparin is used in the detection of the pair of isolated biomarkers in the biological sample obtained from the pregnant female.

[00142] In some embodiments of the methods of dermining the PDD or TTB herein, the amount of the one or more isolated biomarkers (or the detected presence or amount of the one or more isolated biomarkers), or the pair of isolated biomarkers, is further combined with one or more clinical components or demographic variables into a model that can be trained on a dataset to determine the PDD or TTB. In some embodiments, the model is a predictive model. In some embodiments, the methods comprise integrating one or more clinical or demographic variables with the detected presence or amount of said one or more isolated biomarkers, or said pair of isolated biomarkers, into a predictive model for determining the PDD or TTB. In particular embodiments, the model comprises the detected presence or amount of said one or more isolated biomarkers, or the amount of said pair of isolated biomarkers, and one or more clinical components or demographic variables selected from the group consisting of GABD, gravidity, maternal age (MAGE), age, BMI, race, hypertiension/preeclampsia in a prior pregnancy, preterm birth in a prior pregnancy, cesarean section (c-section) delivery in a prior pregnancy, education level, being a first time mother, chronic diabetes, gestational diabetes in the current pregnancy, hypertension or preeclampsia in the current pregnancy, previous low birth weight or preterm delivery, multiple 2nd trimester spontaneous abortions, prior first trimester induced abortion, familial and intergenerational factors, history of infertility, parity, nulliparity, placental abnormalities, cervical and uterine anomalies, short cervical length measurements, results of anomaly scans (including fetal (e.g., crown-rump length), placental and maternal pelvic organ measures), gestational bleeding, intrauterine growth restriction, in utero diethylstilbestrol exposure, multiple gestations, infant sex, short stature, low prepregnancy weight, chronic hypertension, urogenital infections (z.e., urinary tract infection), asthma, anxiety and depression, asthma, hypothyroidism, high BMI, low BMI, ethnicity, single marital status, low socioeconomic status, employment-related physical activity, occupational exposures, environment exposures, stress, inadequate prenatal care, cigarette smoking, use of marijuana and other illicit drugs, cocaine use, alcohol consumption, caffeine intake, maternal weight gain, dietary intake, sexual activity during late pregnancy, and leisure-time physical activities. In some embodiments, the one or more clinical or demographic variables is selected from the group consisting of age, BMI, race, hypertiension/preeclampsia in a prior pregnancy, preterm birth in a prior pregnancy, c-section delivery in a prior pregnancy, education level, being a first-time mother, chronic diabetes, gestational diabetes in the current pregnancy, hypertension or preeclampsia in the current pregnancy. In some embodiments, at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, or at least eleven clinical components or demographic variables can be used in the methods herein to determine the PDD or TTB.

[00143] In some embodiments, the present disclosure provides a method of predicting the PDD or TTB for a pregnant female, the method comprising: (a) obtaining a biological sample obtained from said pregnant female; (b) detecting the presence or amount of one or more isolated biomarkers in said biological sample, and (c) integrating one or more clinical or demographic variables with the detected presence or amount of said one or more isolated biomarkers into a predictive model for determining the PDD or TTB. In further embodiments, said detecting comprises subjecting said biological sample to (i) mass spectrometry (MS) quantification, or (ii) an assay that utilizes a capture agent that binds to each of the one or more isolated biomarker. In some embodiments, the one or more isolated biomarkers is selected from Table 2. In some embodiments, at least one of S0M2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included in the method. In some embodiments, at least one of S0M2, CSH, CGB1, and SVEP1 are not used or included in the method. In some embodiments, the method further comprises measuring in said biological sample the amount of each of said one or more isolated biomarkers to determine the PDD or TTB. In some embodiments, each of said one or more isolated biomarkers exhibits a change in the amount between pregnant females who deliver X or more days before the estimated due date (EDD) or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days, and Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days, Y is no more than 1, 2, 3, or 4 days, and Z is no more than 1, 2, 3, or 4 days. In other embodiments, the method further comprises measuring in said biological sample the amount of each of said one or more biomarkers to determine the PDD or TTB, wherein the amount is integrated into said predictive model and gives a PDD or TTB that falls within +/-X days of the pregnant female’s actual delivery date (ADD) or actual TTB at least Y% of the time. In some embodiments, X is 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1, and Y is 50%, 51%, 52%, 53%, 54%, 55%, 56%, 57%, 58%, 59%, 60%, 61%, 62%, 63%, 64%, 65%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or 100%. In further embodiments, X is 3, 2, or 1, and Y is 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or 100%. In some embodiments, the amount of each of said one or more biomarkers is integrated into said predictive model and gives a PDD or TTB that falls within 3 days of the pregnant female’s ADD or actual TTB, and a PDD or TTB that is within 5 days of an estimated due date (EDD) of the pregnant female.

[00144] In some embodiments, the present disclosure provides a method of determining the PDD or TTB for a pregnant female, the method comprising the steps of (a) obtaining a biological sample obtained from said pregnant female; (b) detecting the presence or amount of a pair (or two or more pairs) of isolated biomarkers selected from Table 2 in said biological sample obtained from said pregnant female; and (c) measuring in said biological sample a reversal value for said pair of isolated biomarkers to determine the PDD or TTB, wherein the reversal value gives a PDD or TTB that falls within +/-X days of the pregnant female’s ADD or actual TTB at least Y% of the time. In some embodiments, X is 10, 9, 8, 7, 6, 5, 4, 3, 2, or

1, and Y is 50%, 51%, 52%, 53%, 54%, 55%, 56%, 57%, 58%, 59%, 60%, 61%, 62%, 63%,

64%, 65%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 80%, 81%, 82%, 83%, 84%, 85%,

86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or 100%. In further embodiments, X is 3, 2, or 1, and Y is 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%,

98%, 99% or 100%. In some embodiments, the pair of isolated biomarkers comprises ADA12 and an isolated biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1. In further embodiments, the pair of isolated biomarkers comprises ADA12/KIT. In other embodiments, the pair of isolated biomarkers comprises ADA12/FETUA. In some embodiments, the pair of isolated biomarkers comprises ADA12/ENPP2. In some embodiments, the pair of isolated biomarkers comprises ADA12/A2GL. In some embodiments, the pair of isolated biomarkers comprises ADA12/IGF1. In some embodiments, the pair of isolated biomarkers comprises two isolated biomarkers selected from Table 2. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 16. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two upregulated biomarkers. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two downregulated biomarkers. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included in the method. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included in the method. In some embodiments, the reversal value gives a PDD or TTB that falls within 3 days of the pregnant female’s ADD or actual TTB, and a PDD or TTB that is within 5 days of the EDD of the pregnant female.

[00145] In some embodiments, the present disclosure provides a method for separating a pregnancy that delivers X or more days before the EDD or Y or more days after the EDD, from a pregnancy that delivers within Z days of the EDD, the method comprising measuring a change in a reversal value of a pair of biomarkers (or two or more biomarker pairs) selected from Table

2, wherein said pair of biomarkers exhibits a change in reversal value between pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, the pair of isolated biomarkers is selected from the pairs listed in Table 3. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 16. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two upregulated biomarkers. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two downregulated biomarkers. In some embodiments, the pair of isolated biomarkers consists of ADA12/KIT (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g, YVSELHLTR peptide (SEQ ID NO: 2) orLCLHCSVDQEGK peptide (SEQ ID NO: 3) for KIT). In some embodiments, the pair of isolated biomarkers consists of ADA12/FETUA (e.g, FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g, FSVVYAK peptide (SEQ ID NO: 4) for FETUA). In some embodiments, the pair of isolated biomarkers consists of ADA12/ENPP2 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., TEFLSNYLTNVDDITLVPGTLGR peptide (SEQ ID NO: 5) or TYLHTYESEI peptide (SEQ ID NO: 6) for ENPP2). In some embodiments, the pair of isolated biomarkers consists of ADA12/A2GL (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., DLLLPQPDLR peptide (SEQ ID NO: 7) for A2GL). In some embodiments, the pair of isolated biomarkers consists of ADA12/IGF1 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., GFYFNKPTGYGSSSR peptide (SEQ ID NO: 8) for IGF1). In some embodiments, the pair of isolated biomarkers comprises two isolated biomarkers selected from Table 2. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days. In some embodiments, X is no more than 1, 2, 3, 4,

5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In further embodiments, X is no more than 1, 2, 3, 4, 5,

6, or 7 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Y is no more than 1, 2, 3, or 4 days. In some embodiments, Z is no more than 1,

2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, Z is no more than 1, 2,

3, 4, 5, 6, or 7 days. In further embodiments, Z is no more than 1, 2, 3, or 4 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 202 days, 126 through 160 days, or 161 through 202 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 150 days. In some embodiments, the biological sample is obtained at a GABD from 161 through 180 days. In some embodiments, the biological sample is obtained at a GABD from 181 days through 200 days. In some embodiments, the biological sample is obtained at a GABD of 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, or 150 days. In some embodiments, the biological sample is obtained at a GABD of 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, or 180 days. In some embodiments, the biological sample is obtained at a GABD of 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, or 202 days. In some embodiments, the pregnant female is nulliparous. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included in the method. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included in the method.

[00146] In some embodiments, the sample is obtained at a GABD between X and Y days (inclusive), where X is 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126,

127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145,

146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164,

165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183,

184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202,

203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221,

222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240,

241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259,

260, 261, 262, 263, or 264; and Y is greater than X and is 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125,

126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144,

145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163,

164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182,

183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201,

202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220,

221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239,

240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258,

259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, or 273. In some embodiments, X is between 42 and 100 days (inclusive), and Y is between 49 and 100 days (inclusive). In further embodiments, X is between between 60 and 80 days (inclusive), and Y is between 70 and 90 days (inclusive). In some embodiments, the sample is obtained at a GABD between 126 and 202 days (inclusive), between 126 and 160 days (inclusive), or between 161 and 202 days (inclusive). In some embodiments, the biological sample is obtained at a GABD from 126 through 150 days (inclusive). In some embodiments, the biological sample is obtained at a GABD from 161 through 180 days (inclusive). In some embodiments, the biological sample is obtained at a GABD from 181 days through 200 days (inclusive). In some embodiments, the biological sample is obtained at a GABD of 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, or 150 days. In some embodiments, the biological sample is obtained at a GABD of 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, or 180 days. In some embodiments, the biological sample is obtained at a GABD of 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, or 202 days.

[00147] While the specification discloses embodiments directed to measuring the particular biomarkers selected from Table 2 or pairs listed in Table 3 (e.g., ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and KIT (e.g., YVSELHLTR peptide (SEQ ID NO: 2) or LCLHCSVDQEGK peptide (SEQ ID NO: 3)); ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and FETUA (e.g., FSVVYAK peptide (SEQ ID NO: 4)); ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and ENPP2 (e.g., TEFLSNYLTNVDDITLVPGTLGR peptide (SEQ ID NO: 5) or TYLHTYESEI peptide (SEQ ID NO: 6)); ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and A2GL (e.g., DLLLPQPDLR peptide (SEQ ID NO: 7)); or ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and IGF1 (e.g., GFYFNKPTGYGSSSR peptide (SEQ ID NO: 8))), the disclosure is not restricted to the particular pairs recited in Table 3. Individual biomarkers in Table 2 as well as any pair of the individual biomarkers in Table 2 are also encompassed by the present disclosure, as are methods comprising one or more pairs of biomarkers. Moreover, while the specification discloses embodiments directed to measuring the particular biomarkers from Table 2 or pairs listed in Table 3, the disclosure can also include the exclusion of certain biomarkers, including, but not limited to, those listed in Table 2. For instance, in some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are excluded, or not used or included, when an individual biomarker is being assayed, measured, quantified, detected, etc. Similarly, when two or more isolated biomarkers are being assayed, measured, quantified, detected, etc., at least one of S0M2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, AP0C3, and PSG1 can be excluded.

[00148] In some embodiments, the present disclosure provides a composition comprising one or more isolated biomarkers selected from Table 2. In some embodiments, each of the one or more isolated biomarkers exhibits a change in an amount between pregnant females who deliver X or more days before the estimated due date (EDD) or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD; where X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days, and Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days, Y is no more than 1, 2, 3, or 4 days, and Z is no more than 1, 2, 3, or 4 days.

[00149] In some embodiments, the present disclosure also provides a composition comprising a pair of isolated biomarkers consisting of ADA12/KIT (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., YVSELHLTR peptide (SEQ ID NO: 2) or LCLHCSVDQEGK peptide (SEQ ID NO: 3) for KIT), wherein said pair of biomarkers exhibits a change in reversal value between pregnant females that deliver X or more days before the EDD or Y or more days after the EDD, relative to a pregnancy that delivers within Z days of the EDD; where X is nore more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days; Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days; and Z is no more than

1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, X is no more than 1,

2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days, and Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days, Y is no more than 1, 2, 3, or 4 days, and Z is no more than 1, 2, 3, or 4 days. [00150] In some embodiments, the present disclosure provides a composition comprising a pair of isolated biomarkers consisting of ADA12/FETUA (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., FSVVYAK peptide (SEQ ID NO: 4) for FETUA), wherein said pair of biomarkers exhibits a change in reversal value between pregnant females that deliver X or more days before the EDD or Y or more days after the EDD, relative to a pregnancy that delivers within Z days of the EDD; where X is nore more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days; Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days; and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days, and Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days, Y is no more than 1, 2, 3, or 4 days, and Z is no more than 1, 2, 3, or 4 days.

[00151] In some embodiments, the present disclosure provides a composition comprising a pair of isolated biomarkers consisting of ADA12/ENPP2 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., TEFLSNYLTNVDDITLVPGTLGR peptide (SEQ ID NO: 5) or TYLHTYESEI peptide (SEQ ID NO: 6) for ENPP2), wherein said pair of biomarkers exhibits a change in reversal value between pregnant females that deliver X or more days before the EDD or Y or more days after the EDD, relative to a pregnancy that delivers within Z days of the EDD; where X is nore more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days; Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days; and Z is no more than

2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days, and Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days, Y is no more than 1, 2, 3, or 4 days, and Z is no more than 1, 2, 3, or 4 days. [00152] In some embodiments, the present disclosure provides a composition comprising a pair of isolated biomarkers consisting of ADA12/A2GL (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., DLLLPQPDLR peptide (SEQ ID NO: 7) for A2GL), wherein said pair of biomarkers exhibits a change in reversal value between pregnant females that deliver X or more days before the EDD or Y or more days after the EDD, relative to a pregnancy that delivers within Z days of the EDD; where X is nore more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days; Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days; and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days, and Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days, Y is no more than 1, 2, 3, or 4 days, and Z is no more than 1, 2, 3, or 4 days.

[00153] In some embodiments, the present disclosure provides a composition comprising a pair of isolated biomarkers consisting of ADA12/IGF1 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., GFYFNKPTGYGSSSR peptide (SEQ ID NO: 8) for IGF1), wherein said pair of biomarkers exhibits a change in reversal value between pregnant females that deliver X or more days before the EDD or Y or more days after the EDD, relative to a pregnancy that delivers within Z days of the EDD; where X is nore more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days; Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days; and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days, and Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days, Y is no more than 1, 2, 3, or 4 days, and Z is no more than 1, 2, 3, or 4 days.

[00154] In some embodiments, the present disclosure provides a method of determining the PDD for a pregnant female, the method comprising measuring in a biological sample obtained from said pregnant female a reversal value for a pair (or two or more pairs) of biomarkers consisting of ADA12/KIT to determine the PDD for said pregnant female. In some embodiments, the present disclosure provides a method of determining the PDD for a pregnant female, the method comprising measuring in a biological sample obtained from said pregnant female a reversal value for a pair (or two or more pairs) of biomarkers consisting of ADA12/FETUA to determine the PDD for said pregnant female. In some embodiments, the present disclosure provides a method of determining the PDD for a pregnant female, the method comprising measuring in a biological sample obtained from said pregnant female a reversal value for a pair (or two or more pairs) of biomarkers consisting of ADA12/ENPP2 to determine the PDD for said pregnant female. In some embodiments, the present disclosure provides a method of determining the PDD for a pregnant female, the method comprising measuring in a biological sample obtained from said pregnant female a reversal value for a pair (or two or more pairs) of biomarkers consisting of ADA12/A2GL to determine the PDD for said pregnant female. In some embodiments, the present disclosure provides a method of determining the PDD for a pregnant female, the method comprising measuring in a biological sample obtained from said pregnant female a reversal value for a pair (or two or more pairs) of biomarkers consisting of ADA12/IGF1 to determine the PDD for said pregnant female.

[00155] In some embodiments, the present disclosure provides a method for separating a pregnancy that delivers X or more days before the EDD or Y or more days after the EDD, from a pregnancy that delivers within Z days of the EDD; where X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days; Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days; and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days, and Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days, Y is no more than 1, 2, 3, or 4 days, and Z is no more than 1, 2, 3, or 4 days. In some embodiments, the method comprises measuring a change in reversal value of a pair (or two or more pairs) of biomarkers consisting of ADA12/KIT, wherein said pair of biomarkers exhibits a change in reversal value between pregnant females that deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD; where X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days; Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days; and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, the method comprises measuring a change in reversal value of a pair (or two or more pairs) of biomarkers consisting of ADA12/FETUA, wherein said pair of biomarkers exhibits a change in reversal value between pregnant females that deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD; where X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days; Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days; and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, the method comprises measuring a change in reversal value of a pair (or two or more pairs) of biomarkers consisting of ADA12ZENPP2, wherein said pair of biomarkers exhibits a change in reversal value between pregnant females that deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD; where X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days; Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days; and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 16. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two upregulated biomarkers. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two downregulated biomarkers. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included. In some embodiments, the method comprises measuring a change in reversal value of a pair (or two or more pairs) of biomarkers consisting of ADA12/A2GL, wherein said pair of biomarkers exhibits a change in reversal value between pregnant females that deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD; where X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days; Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days; and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, the method comprises measuring a change in reversal value of a pair (or two or more pairs) of biomarkers consisting of AD A 12/IGF1, wherein said pair of biomarkers exhibits a change in reversal value between pregnant females that deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD; where X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days; Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days; and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,

11, 12, 13, or 14 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,

12, 13, or 14 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Y is no more than 1, 2, 3, or 4 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Z is no more than 1, 2, 3, or 4 days.

[00156] In some embodiments, the present disclosure further provides a method for prediction of GAB. In one embodiment, the present disclosure further provides a method for prediction of TTB.

[00157] In some embodiments, the present disclosure provides a composition comprising a pair (or two or more pairs) of isolated biomarkers selected from Table 2, wherein said pair of biomarkers exhibits a change in reversal value between pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, the pair of isolated biomarkers is selected from the pairs listed in Table 3. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 16. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two upregulated biomarkers. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two downregulated biomarkers. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included. In some embodiments, the pair of isolated biomarkers comprises ADA12 and an isolated biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1. In some embodiments, the pair of isolated biomarkers consists of ADA12/KIT (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., YVSELHLTR peptide (SEQ ID NO: 2) or LCLHCSVDQEGK peptide (SEQ ID NO: 3) for KIT). In some embodiments, the pair of isolated biomarkers consists of ADA12/FETUA (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g, FSVVYAK peptide (SEQ ID NO: 4) for FETUA). In some embodiments, the pair of isolated biomarkers consists of ADA12/ENPP2 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., TEFLSNYLTNVDDITLVPGTLGR peptide (SEQ ID NO: 5) or TYLHTYESEI peptide (SEQ ID NO: 6) for ENPP2). In some embodiments, the pair of isolated biomarkers consists of ADA12/A2GL (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., DLLLPQPDLR peptide (SEQ ID NO: 7) for A2GL). In some embodiments, the pair of isolated biomarkers consists of ADA12/IGF1 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., GFYFNKPTGYGSSSR peptide (SEQ ID NO: 8) for IGF1). In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Y is no more than 1, 2, 3, or 4 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Z is no more than 1, 2, 3, or 4 days. In some embodiments, the pregnant females are nulliparous. [00158] In some embodiments, the present disclosure provides a method of determining the PDD for a pregnant female, the method comprising measuring in a biological sample obtained from said pregnant female a reversal value for a pair (or two or more pairs) of isolated biomarkers selected from Table 2 to determine the PDD for said pregnant female. In some embodiments, the pair of isolated biomarkers is selected from the pairs listed in Table 3. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 16. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two upregulated biomarkers. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two downregulated biomarkers. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included. In some embodiments, the pair of isolated biomarkers consists of ADA12/KIT (e.g., FGFGGSTDSGPIR peptide for ADA12 and e.g., YVSELHLTR peptide or LCLHCSVDQEGK peptide for KIT). . In some embodiments, the pair of isolated biomarkers consists of ADA12/KIT (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and e.g, YVSELHLTR peptide (SEQ ID NO: 2) or LCLHCSVDQEGK peptide (SEQ ID NO: 3) for KIT). In some embodiments, the pair of isolated biomarkers consists of ADA12/FETUA (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., FSVVYAK peptide (SEQ ID NO: 4) for FETUA). In some embodiments, the pair of isolated biomarkers consists of ADA12/ENPP2 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., TEFLSNYLTNVDDITLVPGTLGR peptide (SEQ ID NO: 5) or TYLHTYESEI peptide (SEQ ID NO: 6) for ENPP2). In some embodiments, the pair of isolated biomarkers consists of ADA12/A2GL (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., DLLLPQPDLR peptide (SEQ ID NO: 7) for A2GL). In some embodiments, the pair of isolated biomarkers consists of ADA12/IGF1 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., GFYFNKPTGYGSSSR peptide (SEQ ID NO: 8) for IGF1). In some embodiments, said pair of isolated biomarkers exhibits a change in reversal value between pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Y is no more than 1, 2, 3, or 4 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Z is no more than 1, 2, 3, or 4 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 202 days, 126 through 160 days, or 161 through 202 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 150 days. In some embodiments, the biological sample is obtained at a GABD from 161 through 180 days. In some embodiments, the biological sample is obtained at a GABD from 181 days through 200 days. In some embodiments, the biological sample is obtained at a GABD of 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, or 150 days. In some embodiments, the biological sample is obtained at a GABD of 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, or 180 days. In some embodiments, the biological sample is obtained at a GABD of 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, or 202 days. In some embodiments, the pregnant female is nulliparous. [00159] In some embodiments, the present disclosure provides a method of determining the likelihood the ADD for a pregnant female differs by at least X days from the EDD. In some embodiments, the method comprises measuring in a biological sample obtained from said pregnant female an amount of each of one or more isolated biomarkers selected from Table 2 to determine the PDD for said pregnant female. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included. In some embodiments, the method comprises measuring in a biological sample obtained from said pregnant female a reversal value for a pair (or two or more pairs) of isolated biomarkers selected from Table 2 to determine the PDD for said pregnant female. In some embodiments, the pair of isolated biomarkers is selected from the pairs listed in Table 3. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 16. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two upregulated biomarkers. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two downregulated biomarkers. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included. In some embodiments, the pair of isolated biomarkers consists of ADA12/KIT (e.g, FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g, YVSELHLTR peptide (SEQ ID NO: 2) or LCLHCSVDQEGK peptide (SEQ ID NO: 3) for KIT). In some embodiments, the pair of isolated biomarkers consists of ADA12/FETUA (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g, FSVVYAK peptide (SEQ ID NO: 4) for FETUA). In some embodiments, the pair of isolated biomarkers consists of ADA12/ENPP2 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., TEFLSNYLTNVDDITLVPGTLGR peptide (SEQ ID NO: 5) or TYLHTYESEI peptide (SEQ ID NO: 6) for ENPP2). In some embodiments, the pair of isolated biomarkers consists of ADA12/A2GL (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., DLLLPQPDLR peptide (SEQ ID NO: 7) for A2GL). In some embodiments, the pair of isolated biomarkers consists of ADA12/IGF1 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., GFYFNKPTGYGSSSR peptide (SEQ ID NO: 8) for IGF1). In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 202 days, 126 through 160 days, or 161 through 202 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 150 days. In some embodiments, the biological sample is obtained at a GABD from 161 through 180 days. In some embodiments, the biological sample is obtained at a GABD from 181 days through 200 days. In some embodiments, the biological sample is obtained at a GABD of 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, or 150 days. In some embodiments, the biological sample is obtained at a GABD of 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, or 180 days. In some embodiments, the biological sample is obtained at a GABD of 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, or 202 days. In some embodiments, the pregnant female is nulliparous.

[00160] In some embodiments, the present disclosure provides a method of determining the TTB for a pregnant female, the method comprising measuring in a biological sample obtained from said pregnant female an amount of each of one or more isolated biomarkers selected from Table 2 to determine the TTB for said pregnant female. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included. In some embodiments, the present disclosure provides a method of determining the TTB for a pregnant female, the method comprising measuring in a biological sample obtained from said pregnant female a reversal value for a pair (or two or more pairs) of isolated biomarkers selected from Table 2 to determine the TTB for said pregnant female. In some embodiments, the pair of isolated biomarkers is selected from the pairs listed in Table 3. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 16. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two upregulated biomarkers. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two downregulated biomarkers. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included. . In some embodiments, the pair of isolated biomarkers consists of ADA12/KIT (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g, YVSELHLTR peptide (SEQ ID NO: 2) or LCLHCSVDQEGK peptide (SEQ ID NO: 3) for KIT). In some embodiments, the pair of isolated biomarkers consists of ADA12/FETUA (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., FSVVYAK peptide (SEQ ID NO: 4) for FETUA). In some embodiments, the pair of isolated biomarkers consists of ADA12/ENPP2 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., TEFLSNYLTNVDDITLVPGTLGR peptide (SEQ ID NO: 5) or TYLHTYESEI peptide (SEQ ID NO: 6) for ENPP2). In some embodiments, the pair of isolated biomarkers consists of ADA12/A2GL (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., DLLLPQPDLR peptide (SEQ ID NO: 7) for A2GL). In some embodiments, the pair of isolated biomarkers consists of ADA12/IGF1 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., GFYFNKPTGYGSSSR peptide (SEQ ID NO: 8) for IGF1). In some embodiments, said pair of isolated biomarkers exhibits a change in reversal value between pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, each of said one or more isolated biomarkers exhibits a change in the amount between pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Y is no more than 1, 2, 3, or 4 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Z is no more than 1, 2, 3, or 4 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 202 days, 126 through 160 days, or 161 through 202 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 150 days. In some embodiments, the biological sample is obtained at a GABD from 161 through 180 days. In some embodiments, the biological sample is obtained at a GABD from 181 days through 200 days. In some embodiments, the biological sample is obtained at a GABD of 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, or 150 days. In some embodiments, the biological sample is obtained at a GABD of 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, or 180 days. In some embodiments, the biological sample is obtained at a GABD of 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, or 202 days. In some embodiments, the pregnant female is nulliparous.

[00161] In some embodiments, the present disclosure provides a method for separating a pregnancy that delivers X or more days before the EDD or Y or more days after the EDD, from a pregnancy that delivers within Z days of the EDD, the method comprising measuring a change in an amount each of one or more isolated biomarkers selected from Table 2, wherein each of said one or more isolated biomarkers exhibits a change in the amount between pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included. In some embodiments, the present disclosure provides a method for separating a pregnancy that delivers X or more days before the EDD or Y or more days after the EDD, from a pregnancy that delivers within Z days of the EDD, the method comprising measuring a change in a reversal value of a pair (or two or more pairs) of isolated biomarkers selected from Table 2, wherein said pair of biomarkers exhibits a change in reversal value between pregnant females who deliver X or more days before the EDD or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD. In some embodiments, the pair of isolated biomarkers is selected from the pairs listed in Table 3. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 16. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two upregulated biomarkers. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two downregulated biomarkers. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included. In some embodiments, the pair of isolated biomarkers consists of ADA12/KIT (e.g, FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g, YVSELHLTR peptide (SEQ ID NO: 2) or LCLHCSVDQEGK peptide (SEQ ID NO: 3) for KIT). In some embodiments, the pair of isolated biomarkers consists of ADA12/FETUA (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g, FSVVYAK peptide (SEQ ID NO: 4) for FETUA). In some embodiments, the pair of isolated biomarkers consists of ADA12/ENPP2 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., TEFLSNYLTNVDDITLVPGTLGR peptide (SEQ ID NO: 5) or TYLHTYESEI peptide (SEQ ID NO: 6) for ENPP2). In some embodiments, the pair of isolated biomarkers consists of ADA12/A2GL e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g, DLLLPQPDLR peptide (SEQ ID NO: 7) for A2GL). In some embodiments, the pair of isolated biomarkers consists of ADA12/IGF1 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., GFYFNKPTGYGSSSR peptide (SEQ ID NO: 8) for IGF1). In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Y is no more than 1, 2, 3, or 4 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Z is no more than 1, 2, 3, or 4 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 202 days, 126 through 160 days, or 161 through 202 days. In some embodiments, the biological sample is obtained at a GABD from 126 through 150 days. In some embodiments, the biological sample is obtained at a GABD from 161 through 180 days. In some embodiments, the biological sample is obtained at a GABD from 181 days through 200 days. In some embodiments, the biological sample is obtained at a GABD of 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, or 150 days. In some embodiments, the biological sample is obtained at a GABD of 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, or 180 days. In some embodiments, the biological sample is obtained at a GABD of 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, or 202 days. In some embodiments, the pregnant female is nulliparous.

[00162] The disclosed methods, compositions, and kits herein also contemplate measuring surrogate peptides of the biomarkers. The biomarkers of the disclosure, their surrogate peptides and the corresponding stable isotope labeled standard peptides (SIS peptides) can be used in methods of determining the PDD, predicting the GAB, predicting the TTB, or estimating the GA for a pregnant female. In some embodiments, the SIS peptides correspond to surrogate peptides of the isolated biomarkers selected from the group consisting of ADA12 and KIT. In some embodiments, the SIS peptides correspond to surrogate peptides of the isolated biomarkers selected from the group consisting of ADA12 and FETUA. In some embodiments, the SIS peptides correspond to surrogate peptides of the isolated biomarkers selected from the group consisting of ADA12 and ENPP2. In some embodiments, the SIS peptides correspond to surrogate peptides of the isolated biomarkers selected from the group consisting of ADA12 and A2GL. In some embodiments, the SIS peptides correspond to surrogate peptides of the isolated biomarkers selected from the group consisting of ADA12 and IGF1. In some embodiments, the SIS peptides correspond to surrogate peptides of any of the isolated biomarkers selected from Table 2.

[00163] In some embodiments, the present disclosure provides a method for estimating gestational age (GA) comprising measuring a change in an amount of each of one or more isolated biomarkers selected from Table 2, and correlating said measurement to GA. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included. In some embodiments, the present disclosure provides a method for estimating gestational age (GA) comprising measuring a change in reversal value of a pair (or two or more pairs) of biomarkers selected from Table 2 and correlating said measurement to GA. In some embodiments, the pair of isolated biomarkers is selected from the pairs listed in Table 3. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 16. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two upregulated biomarkers. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two downregulated biomarkers. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included. In some embodiments, the pair of isolated biomarkers consists of ADA12/KIT (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g, YVSELHLTR peptide (SEQ ID NO: 2) or LCLHCSVDQEGK peptide (SEQ ID NO: 3) for KIT). In some embodiments, the pair of isolated biomarkers consists of ADA12/FETUA (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., FSVVYAK peptide (SEQ ID NO: 4) for FETUA). In some embodiments, the pair of isolated biomarkers consists of ADA12/ENPP2 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., TEFLSNYLTNVDDITLVPGTLGR peptide (SEQ ID NO: 5) or TYLHTYESEI peptide (SEQ ID NO: 6) for ENPP2). In some embodiments, the pair of isolated biomarkers consists of ADA12/A2GL (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., DLLLPQPDLR peptide (SEQ ID NO: 7) for A2GL). In some embodiments, the pair of isolated biomarkers consists of ADA12/IGF1 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1) for ADA12 and, e.g., GFYFNKPTGYGSSSR peptide (SEQ ID NO: 8) for IGF1). In some embodiments, the measuring comprises an assay that utilizes a capture agent. In one embodiment, the measuring comprises an assay that utilizes a capture agent selected from the group consisting of an antibody, antibody fragment, nucleic acid-based protein binding reagent, small molecule or variant thereof. In one embodiment, the measuring comprises an assay selected from the group consisting of enzyme immunoassay (EIA), enzyme-linked immunosorbent assay (ELISA), and radioimmunoassay (RIA).

[00164] In some embodiments, the measuring comprises mass spectrometry (MS). In some embodiments, MS is selected from the group consisting of matrix-assisted laser desorption/ionisation time-of-flight (MALDI-TOF) MS; MALDI-TOF post-source-decay (PSD); MALDI- TOF/TOF; surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF) MS; electrospray ionization mass spectrometry (ESLMS); ESI- MS/MS; ESI-MS/(MS)n (n is an integer greater than zero); ESI 3D or linear (2D) ion trap MS; ESI triple quadrupole MS; ESI quadrupole orthogonal TOF (Q-TOF); ESI Fourier transform MS systems; desorption/ionization on silicon (DIOS); secondary ion mass spectrometry (SIMS); atmospheric pressure chemical ionization mass spectrometry (APCI-MS); APCI- MS/MS; APCL (MS)n (n is an integer greater than zero); ion mobility spectrometry (IMS); inductively coupled plasma mass spectrometry (ICP-MS); atmospheric pressure photoionization mass spectrometry (APPL MS); APPLMS/MS; and APPI- (MS)n (n is an integer greater than zero). In some embodiments, MS comprises affinity-capture MS (AC -MS), co-immunoprecipitation-mass spectrometry (co-IP MS), liquid chromatography-mass spectrometry (LC-MS), multiple reaction monitoring (MRM) or selected reaction monitoring (SRM). In one embodiment, the measuring further comprises measuring surrogate peptides of said biomarkers in the biological sample obtained from said pregnant female. In one embodiment, the measuring of surrogate peptides of said biomarkers further comprises measuring stable isotope labeled standard peptides (SIS peptides) for each of the surrogate peptides.

[00165] In some embodiments, the disclosure provides a method of separating a pregnancy that delivers X or more days before the EDD relative to a pregnancy that delivers within Z days of the EDD; where X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days; and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days; the method comprising measuring in a biological sample obtained from the pregnant female a ratio for at least a pair of biomarkers consisting of ADA12/KIT to determine the PDD for said pregnant female, wherein a higher ratio indicates a greater likelihood of a greater value for X. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Z is no more than 1, 2, 3, or 4 days. [00166] In some embodiments, the disclosure provides a method of separating a pregnancy that delivers Y or more days after the EDD, relative to a pregnancy that delivers within Z days of the EDD; where Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days; and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days; the method comprising measuring in a biological sample obtained from the pregnant female a ratio for at least a pair of biomarkers consisting of ADA12/KIT to determine the PDD for said pregnant female, wherein a lower ratio indicates a greater likelihood of a greater value for Y. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Y is no more than 1, 2, 3, or 4 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Z is no more than 1, 2, 3, or 4 days.

[00167] Although described and exemplified with reference to methods of determining PDD in a pregnant female, the present disclosure is similarly applicable to related methods of predicting GAB, related methods for predicting term birth, methods for determining TTB, methods of estimating gestational age (GA), methods of estimating GABD in a pregnant female. GA and GABD are directly related in that estimation of GABD can be used to calculate GA post-sample collection. It will be apparent to one skilled in the art that each of the aforementioned methods has specific and substantial utilities and benefits with regard maternal-fetal health considerations.

[00168] In some embodiments, the present disclosure provides biomarkers, biomarker pairs and/or reversals, e.g., ADA12/KIT, that are strong predictors of TTB. TTB is the difference between GABD and GAB. This discovery enables prediction, either individually or in mathematical combination of such analytes, of TTB or GAB. Analytes that lack a case versus control difference, but demonstrate changes in analyte intensity across pregnancy, are useful according to the methods described herein. These analytes can be used to date a pregnancy in the absence of or in conjunction with other dating methods. Calibration of multiple analytes can be used to date pregnancy, which is of value to correct or confirm dating by another measure (e.g. , date of LMP and/or ultrasound dating), or useful alone to subsequently and more accurately predict GAB or TTB, for example. All of the embodiments described herein can therefore be used to accurately predict GA and GABD based on measurement of biomarkers. [00169] In some embodiments, the methods of the disclosure comprise calculation of body mass index (BMI).

[00170] In some embodiments, the disclosed methods for determining the PDD encompass detecting and/or quantifying one or more biomarkers using mass spectrometry, an immunoassay, a capture agent, or a combination thereof.

[00171] In some embodiments, the disclosed methods for determining the PDD encompass an initial step of providing a biological sample from the pregnant female.

[00172] As stated above, although described and exemplified with reference to determining methods for determining the PDD for a pregnant female, all embodiments described throughout this disclosure are similarly applicable to methods of predicting GAB, methods for predicting term birth, methods for determining the probability of term birth in a pregnant female as well methods of predicting TTB in a pregnant female. Specifically, the biomarkers recited throughout this application with express reference to determining the PDD can also be used in methods for predicting GAB, the methods for predicting term birth, methods for determining the probability of term birth in a pregnant female as well methods of predicting TTB in a pregnant female. It will be apparent to one skilled in the art that each of the aforementioned methods has specific and substantial utilities and benefits with regard to personal pregnancy planning and to maternal-fetal health considerations.

[00173] In some embodiments, the disclosed methods for determining the PDD for a pregnant female encompass communicating the results to the pregnant female and/or to a health care provider. The disclosed methods of predicting GAB, the methods for predicting term birth, methods for determining the probability of term birth in a pregnant female as well methods of predicting TTB in a pregnant female similarly encompass communicating the determination or prediction to the pregnant female and/or to a health care provider.

[00174] In some embodiments, the communication informs a subsequent treatment decision for the pregnant female. In some embodiments, the method of determining the PDD for a pregnant female encompasses the initial or subsequent (or follow-up) step of administering an additional test for predicting the probability of pre-term birth in said pregnant female, for example, the methods described in publication US2017/0022565A1, the entire contents of which are incorporated herein by reference.

[00175] In some embodiments, each of the proteins or fragments there of disclosed herein serve as components of pairs, ratios and/or reversal pairs that can serve to normalize component peptides in signatures to improve predictive performance or to select appropriate biomarkers and/or classifiers. Accordingly, the present disclosure includes methods for estimating GABD comprising measuring one or more proteins in Table 2 or protein pairs in Table 3 and correlating said measurement to GABD.

[00176] The utility of the biomarker pairs, ratios and/or reversal pairs to accurately date a pregnancy, z.e., accurately estimate gestational age (GA), can be an improvement to the quality of personal pregnancy planning, obstetric care and maternal-fetal health. The utility of the compositions and methods described herein to date a pregnancy with significantly higher accuracy than can be achieved with current clinical extends to every personal pregnancy planning decision or to any prognostic, diagnostic or other clinical assessment of the pregnant female and fetus that relies on accurately estimating GA for its own accuracy. For example, acceptable ultrasonographic fetal measurements and algorithms for their use vary by gestational age at ultrasound. As a clinical example, the sensitivity of non-invasive prenatal testing (NIPT), which is available for detection of aneuploidies and other conditions, relies on accurately estimating GA in defining an acceptable window for testing. Similarly, prenatal tests such as the Alpha-fetoprotein (AFP) test and the quadruple marker test (quad screen), which also measures human chorionic gonadotropin (HCG) estriol, and inhibin A in addition to AFP, interpret analyte abundances in view of estimated GA. When a pregnant female’s EDD is changed based on new information, such as a new ultrasound, tests run earlier in pregnancy are often re-assessed and may give medically different results, for example changing an AFP result from normal to abnormal, or vice versa. More generally, biomarkers associated with pregnancy are known to change continuously across pregnancy with individual kinetics. As a result, accurate GA estimation is crucial to the assessment of maternal and fetal health, and to obstetric care decisions. The biomarker pairs, ratios and/or reversal pairs can serve to improve the performance of clinical assessment relating to maternal and fetal health that take into account GA by enabling a new and useful process for estimating GA with higher accuracy than currently practiced clinical methods. In some embodiments, such biomarker pairs, ratios and/or reversal pairs include, but are not limited to, the biomarkers listed in Table 2. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 16. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two upregulated biomarkers. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two downregulated biomarkers. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included in such a pair of isolated biomarkers. In some embodiments, at least one of S0M2, CSH, CGB1, and SVEP1 are not used or included in such a pair of isolated biomarkers. [00177] Methods for assessment of GA with the biomarkers disclosed herein can guide medical decisions related to fetal maturity. For example, a decision to induce labor or perform a c-section based on maternal health takes into account the estimated maturity of the fetus. Inaccurate assessment of GA can result in induction/c-sections that deliver: an early preterm baby when the fetus was thought to be at term; or a stillborn or ill baby and/or a mother with disseminated intravascular coagulation when the baby was thought to be full term. Further, the ARRIVE trial (Grobman, American Journal of Obstetrics & Gynecology , Volume 218 , Issue 1, S601) suggests that most nulliparous women will show benefit to fetal health without increasing risk of c-section if labor is induced in the 39th week of gestation. Reducing the trial findings to practice crucially requires differentiation between 38 and 39 weeks’ GA, and between 39 and 40 weeks’ GA. Further, current guidelines on proper management of late-term (41 0/7 weeks through 41 6/7 weeks) and postterm (42 0/7 weeks and beyond) require GA dating accurate to within a week. The critical importance for accurately dating a pregnancy to proper maternal and fetal health care is well documented in the literature and appreciated by those of skill in the art. (see, for example, Grobman et al., N Engl J Med 2018;379, 6:513-23; Greene, N Engl J Med 2018; 379;6:580-581; Ananth et al., JAMA Pediatr 2018;172: 627-34; McDorman et al., Natl Vital Stat Rep 2015; 64: 1-24; Middleton et al., Cochrane Database Syst Rev 2018; 5: CD004945; Walker et al., N Engl J Med 2016; 374: 813-22; Martin et al., Natl Vital Stat Rep 2018; 67: 1-55). Accordingly, in some embodiments of the disclosure, the clock protein compositions and corresponding methods can be used in tandem with an assessment of maternal and fetal health that depends on accurate GA estimation.

[00178] In some embodiments, determining the PDD for a pregnant female encompasses an initial step that includes formation of a probability/risk index by measuring the ratio of a pair (or two or more pairs) of isolated biomarkers as disclosed herein in a cohort of pregnancies that includes deliveries at a variety of gestational ages, e.g., before 270 days and deliveries on or after 280 days. For an individual pregnancy, determining the PDD for a pregnant female can encompass measuring the ratio of the isolated biomarker, in some embodiments using the same measurement method as used in the initial step of creating the probability/risk index, and comparing the measured ratio to the probability/risk index to derive the personalized PDD for the individual pregnancy. In some embodiments, a probability/risk index is formed by measuring the ratio of ADA12/KIT in a cohort of pregnancies that includes deliveries at a variety of gestational ages, e.g., before 270 days and deliveries on or after 280 days, where the GAB is recorded. Then, the measured ratio of ADA12/KIT in an individual pregnancy can be compared in the index to derive the PDD, in some embodiments using the same isolation and measurement technologies as in the index group.

[00179] Gestational age is useful a proxy for the extent of fetal development and the fetus’s readiness for birth. Gestational age has typically been defined as the length of time from the date of the last normal menses to the date of birth. However, obstetric measures and ultrasound estimates also can aid in estimating gestational age. In some embodiments, the methods disclosed herein are directed to predicting GAB.

[00180] The disclosure also provides a method of detecting a pair of isolated biomarkers selected from Table 2, said method comprising the steps of (a) obtaining a biological sample obtained from a pregnant female; (b) detecting the presence and/or amount of the pair of isolated biomarkers in the biological sample by contacting the biological sample with a first capture agent that specifically binds a first member of said pair and a second capture agent that specifically binds a second member of said pair; and (c) detecting binding between the first biomarker of said pair and the first capture agent and between the second member of said pair and the second capture agent. In some embodiments, the pair of isolated biomarkers is selected from the pairs listed in Table 3. In some embodiments, said pair of isolated biomarkers comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 16. In some embodiments, said pair of isolated biomarkers comprises two upregulated biomarkers. In some embodiments, said pair of isolated biomarkers comprises two downregulated biomarkers. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included. In some embodiments, the pair of isolated biomarkers consists of ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and KIT (e.g., YVSELHLTR peptide (SEQ ID NO: 2) or LCLHCSVDQEGK peptide (SEQ ID NO: 3)). In some embodiments, the first capture agent specifically binds ADA12 and the second capture agent specifically binds KIT. In some embodiments, the pair of isolated biomarkers consists of ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and FETUA (e.g., FSVVYAK peptide (SEQ ID NO: 4)). In some embodiments, the first capture agent specifically binds ADA12 and the second capture agent specifically binds FETUA. In some embodiments, the pair of isolated biomarkers consists of ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and ENPP2 (e.g., TEFLSNYLTNVDDITLVPGTLGR peptide (SEQ ID NO: 5) or TYLHTYESEI peptide (SEQ ID NO: 6)). In some embodiments, the first capture agent specifically binds ADA12 and the second capture agent specifically binds ENPP2. In some embodiments, the pair of isolated biomarkers consists of ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and A2GL (e.g., DLLLPQPDLR peptide (SEQ ID NO: 7)). In some embodiments, the first capture agent specifically binds ADA12 and the second capture agent specifically binds A2GL. In some embodiments, the pair of isolated biomarkers consists of ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and IGF1 (e.g., GFYFNKPTGYGSSSR peptide (SEQ ID NO: 8)). In some embodiments, the first capture agent specifically binds ADA12 and the second capture agent specifically binds IGF1. In some embodiments, the first capture agent and second capture agent is selected from the group consisting of an antibody, antibody fragment, nucleic acidbased protein binding reagent, small molecule or variant thereof. In an additional embodiment, the method is performed by an assay selected from the group consisting of EIA, ELISA, and RIA. In some embodiments, the biological sample obtained from the pregnant female is collected, stored, and shipped using an at-home or in-clinic handheld bodily fluid collection device, a volumetric absorptive microsampling device, or a dried blood spot card.

[00181] The disclosure also provides a method of detecting one or more isolated biomarkers selected from Table 2, said method comprising (a) obtaining a biological sample obtained from a pregnant female; (b) detecting the presence or amount of each of the one or more isolated biomarkers in the biological sample by contacting the biological sample with a capture agent that specifically binds a member of each of said one or more isolated biomarkers; and (c) detecting binding between the one or more isolated biomarkers and the capture agent. In some embodiments, one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, one of SOM2, CSH, CGB1, and SVEP1 are not used or included. In some embodiments, the biological sample obtained from the pregnant female is collected using an at-home or in-clinic handheld bodily fluid collection device, a volumetric absorptive microsampling device, or a dried blood spot card. In some embodiments, the capture agent is selected from the group consisting of an antibody, antibody fragment, nucleic acid-based protein binding reagent, small molecule or variant thereof. In other embodiments, the method is performed by an assay selected from the group consisting of enzyme immunoassay (EIA), enzyme-linked immunosorbent assay (ELISA), and radioimmunoassay (RIA).

[00182] In some embodiments, the disclosure provides a method of detecting one or more isolated biomarkers in a pregnant female, the method comprising (a) obtaining a biological sample obtained from the pregnant female; and (b) detecting the level of each of the one or more isolated biomarkers in the biological sample comprising subjecting the sample to a proteomics workflow comprised of mass spectrometry quantification. In some embodiments, the biological sample obtained from the pregnant female is collected using an at-home or inclinic handheld bodily fluid collection device, a volumetric absorptive microsampling device, or a dried blood spot card. In some embodiments, said one or more isolated biomarkers are selected from Table 2. In some embodiments, one of S0M2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, one of S0M2, CSH, CGB1, and SVEP1 are not used or included. In some embodiments, the proteomics workflow comprises (i) thawing and depleting the biological sample of high abundance proteins (e.g., the 5, 8, 10, 12 or 14 highest abundance proteins) by immunityaffinity chromatography; (ii) digesting the depleted biological sample with a protease to yield peptides; (iii) fortifying the digest with a mixture of stable isotope labeled standard (SIS) peptides; and (iv) desalting and subjecting the digest to LC-MS/MS with a triple quadrapole instrument operated in MRM mode. In further embodiments, the protease is trypsin. In some embodiments, the high abundance proteins are selected from the group consisting of Albumin, IgG, Antitrypsin, IgA, Transferrin, Haptoglobin, Fibrinogen, Alpha2-macroglobulin, Alphal- acid glycoprotein, IgM, Apolipoprotein Al, Apolipoprotein All, Complement C3, and Transthyretin.

[00183] In some embodiments, the disclosure provides a method of detecting ADA12 and KIT in a pregnant female, said method comprising the steps of (a) obtaining a biological sample obtained from the pregnant female; (b) detecting the level of ADA12 and KIT in the biological sample by (1) contacting the biological sample with a capture agent that specifically binds ADA12 and a capture agent that specifically binds KIT and (2) detecting binding between ADA12 and the capture agent and between KIT and the capture agent. In a further embodiment, the capture agent is selected from the group consisting of an antibody, antibody fragment, nucleic acid-based protein binding reagent, small molecule or variant thereof. In an additional embodiment, the method is performed by an assay selected from the group consisting of enzyme immunoassay (EIA), enzyme-linked immunosorbent assay (ELISA), and radioimmunoassay (RIA).

[00184] In some embodiments, the disclosure provides a method of detecting ADA12 and ENPP2 in a pregnant female, said method comprising the steps of (a) obtaining a biological sample obtained from the pregnant female; (b) detecting the level of ADA12 and ENPP2 in the biological sample by (1) contacting the biological sample with a capture agent that specifically binds ADA12 and a capture agent that specifically binds ENPP2 and (2) detecting binding between ADA12 and the capture agent and between ENPP2 and the capture agent. In a further embodiment, the capture agent is selected from the group consisting of an antibody, antibody fragment, nucleic acid-based protein binding reagent, small molecule or variant thereof. In an additional embodiment, the method is performed by an assay selected from the group consisting of EIA, ELISA, and RIA.

[00185] In some embodiments, the disclosure provides a method of detecting ADA12 and FETUA in a pregnant female, said method comprising the steps of (a) obtaining a biological sample obtained from the pregnant female; (b) detecting the level of ADA12 and FETUA in the biological sample by (1) contacting the biological sample with a capture agent that specifically binds ADA12 and a capture agent that specifically binds FETUA and (2) detecting binding between ADA12 and the capture agent and between FETUA and the capture agent. In a further embodiment, the capture agent is selected from the group consisting of an antibody, antibody fragment, nucleic acid-based protein binding reagent, small molecule or variant thereof. In an additional embodiment, the method is performed by an assay selected from the group consisting of EIA, ELISA, and RIA.

[00186] In some embodiments, the disclosure provides a method of detecting ADA12 and A2GL in a pregnant female, said method comprising the steps of (a) obtaining a biological sample obtained from the pregnant female; (b) detecting the level of ADA12 and A2GL in the biological sample by (1) contacting the biological sample with a capture agent that specifically binds ADA12 and a capture agent that specifically binds A2GL and (2) detecting binding between ADA12 and the capture agent and between A2GL and the capture agent. In a further embodiment, the capture agent is selected from the group consisting of an antibody, antibody fragment, nucleic acid-based protein binding reagent, small molecule or variant thereof. In an additional embodiment, the method is performed by an assay selected from the group consisting of EIA, enzyme-linked ELISA, and RIA.

[00187] In some embodiments, the disclosure provides a method of detecting ADA12 and IGF1 in a pregnant female, said method comprising the steps of (a) obtaining a biological sample obtained from the pregnant female; (b) detecting the level of ADA12 and IGF1 in the biological sample by (1) contacting the biological sample with a capture agent that specifically binds ADA12 and a capture agent that specifically binds IGF1 and (2) detecting binding between ADA12 and the capture agent and between IGF1 and the capture agent. In a further embodiment, the capture agent is selected from the group consisting of an antibody, antibody fragment, nucleic acid-based protein binding reagent, small molecule or variant thereof. In an additional embodiment, the method is performed by an assay selected from the group consisting of EIA, ELISA, and RIA.

[00188] The disclosure also provides a method of detecting a pair of isolated biomarkers selected from Table 2 in a pregnant female, said method comprising the steps of (a) obtaining a biological sample obtained from the pregnant female; and (b) detecting the level of the pair of isolated biomarkers in the biological sample comprising subjecting the sample to a proteomics workflow comprised of mass spectrometry quantification. In some embodiments, the pair of isolated biomarkers is selected from the pairs listed in Table 3. In some embodiments, the pair of isolated biomarkers comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 16. In some embodiments, the pair of isolated biomarkers comprises two upregulated biomarkers. In some embodiments, the pair of isolated biomarkers comprises two downregulated biomarkers. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included. In some embodiments, the pair of isolated biomarkers comprises ADA12 and an isolated biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1. In some embodiments, the pair of isolated biomarkers consists of ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and KIT (e.g., YVSELHLTR peptide (SEQ ID NO: 2) or LCLHCSVDQEGK peptide (SEQ ID NO: 3)). In some embodiments, the pair of isolated biomarkers consists of ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and FETUA (e.g., FSVVYAK peptide (SEQ ID NO: 4)). In some embodiments, the pair of isolated biomarkers consists of ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and ENPP2 (e.g., TEFLSNYLTNVDDITLVPGTLGR peptide (SEQ ID NO: 5) or TYLHTYESEI peptide (SEQ ID NO: 6)). In some embodiments, the pair of isolated biomarkers consists of ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and A2GL (e.g., DLLLPQPDLR peptide (SEQ ID NO: 7)). In some embodiments, the pair of isolated biomarkers consists of ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and IGF1 (e.g., GFYFNKPTGYGSSSR peptide (SEQ ID NO: 8)). In some embodiments, the biological sample obtained from the pregnant female is collected, stored, and shipped using an at-home or in-clinic handheld bodily fluid collection device, a volumetric absorptive microsampling device, or a dried blood spot card. In particular embodiments, the biological sample obtained from the pregnant female is collected, stored, and shipped using an at-home or in-clinic handheld bodily fluid collection device. In other embodiments, the biological sample obtained from the pregnant female is collected, stored, and shipped using an at-home or in-clinic volumetric absorptive microsampling device. In some embodiments, the proteomics workflow comprises the steps of (i) thawing and depleting the biological sample of high abundance proteins (e.g., the 5, 8, 10, 12 or 14 highest abundance) proteins by immunity-affinity chromatography; (ii) digesting the depleted biological sample with a protease to yield peptides; (iii) fortifying the digest with a mixture of stable isotope labeled standard (SIS) peptides; and (iv) desalting and subjecting the digest to LC-MS/MS with a triple quadrapole instrument operated in MRM mode. In some embodiments, the protease is trypsin. In one embodiment the disclosure provides a method of detecting ADA12 and KIT in a pregnant female, said method comprising the steps of (a) obtaining a biological sample obtained from the pregnant female; and (b) detecting the level of the pair of isolated biomarkers in the biological sample comprising subjecting the sample to a proteomics workflow comprised of mass spectrometry quantification. In some embodiments, the high abundance proteins are selected from the group consisting of Albumin, IgG, Antitrypsin, IgA, Transferrin, Haptoglobin, Fibrinogen, Alpha2-macroglobulin, Alphal-acid glycoprotein, IgM, Apolipoprotein Al, Apolipoprotein All, Complement C3, and Transthyretin.

[00189] In one embodiment the disclosure provides a method of detecting ADA12 and FETUA in a pregnant female, said method comprising the steps of (a) obtaining a biological sample obtained from the pregnant female; and (b) detecting the level of the pair of isolated biomarkers in the biological sample comprising subjecting the sample to a proteomics workflow comprised of mass spectrometry quantification.

[00190] In one embodiment the disclosure provides a method of detecting ADA12 and ENPP2 in a pregnant female, said method comprising the steps of (a) obtaining a biological sample obtained from the pregnant female; and (b) detecting the level of the pair of isolated biomarkers in the biological sample comprising subjecting the sample to a proteomics workflow comprised of mass spectrometry quantification.

[00191] In one embodiment the disclosure provides a method of detecting ADA12 and A2GL in a pregnant female, said method comprising the steps of (a) obtaining a biological sample obtained from the pregnant female; and (b) detecting the level of the pair of isolated biomarkers in the biological sample comprising subjecting the sample to a proteomics workflow comprised of mass spectrometry quantification.

[00192] In one embodiment the disclosure provides a method of detecting ADA12 and IGF 1 in a pregnant female, said method comprising the steps of (a) obtaining a biological sample obtained from the pregnant female; and (b) detecting the level of the pair of isolated biomarkers in the biological sample comprising subjecting the sample to a proteomics workflow comprised of mass spectrometry quantification.

[00193] In some embodiments, a proteomics workflow encompasses one or more of the following steps: Serum samples are thawed and depleted of high abundance proteins (e.g., the 5, 8, 10, 12 or 14 highest abundance proteins) by immune-affinity chromatography. Depleted serum is digested with a protease, for example, trypsin, to yield peptides. The digest is subsequently fortified with a mixture of stable isotope labeled standard (SIS) peptides and then desalted and subjected to LC-MS/MS with a triple quadrapole instrument operated in MRM mode. Response ratios are formed from the area ratios of endogenous peptide peaks and the corresponding SIS peptide counterpart peaks. Those skilled in the art appreciate that other types of MS such as, for example, MALDI-TOF, ESI-TOF, ESI-ion trap, ESI-Orbitrap, accurate- mass (HRAM) liquid chromatography mass spectrometry (LC-MS), etc., can be used in the methods described herein. In addition, one skilled in the art can modify a proteomics workflow, for example, by selecting particular reagents (such as proteases) or omitting or changing the order of certain steps, for example, it may not be necessary to immunodeplete, the SIS peptide could be added earlier or later and stable isotope labeled proteins could be used as standards instead of peptides. In some embodiments, the high abundance proteins are selected from the group consisting of Albumin, IgG, Antitrypsin, IgA, Transferrin, Haptoglobin, Fibrinogen, Alpha2-macroglobulin, Alphal-acid glycoprotein, IgM, Apolipoprotein Al, Apolipoprotein All, Complement C3, and Transthyretin.

[00194] In some embodiments, the present disclosure provides surrogate peptides corresponding to each of the isolated biomarkers listed in Table 2. In some embodiments, the present disclosure provides a pair of surrogate peptides of a pair of biomarkers selected from the pairs listed in Table 3 (e.g., ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and KIT (e.g., YVSELHLTR peptide (SEQ ID NO: 2) or LCLHCSVDQEGK peptide (SEQ ID NO: 3)); ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and FETUA (e.g., FSVVYAK peptide (SEQ ID NO: 4)); ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and ENPP2 (e.g., TEFLSNYLTNVDDITLVPGTLGR peptide (SEQ ID NO: 5) or TYLHTYESEI peptide (SEQ ID NO: 6)); ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and A2GL (e.g., DLLLPQPDLR peptide (SEQ ID NO: 7)); or ADA12 (e.g., FGFGGSTDSGPIR peptide (SEQ ID NO: 1)) and IGF1 (e.g., GFYFNKPTGYGSSSR peptide (SEQ ID NO: 8)), wherein said pair of biomarkers exhibits a change in reversal value between pregnant females that deliver X or more days before the EDD or Y or more days after the EDD, relative to a pregnancy that delivers within Z days of the EDD; where X is 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, 35 or more days; Y is 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or more days; and Z is 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days, and Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days, Y is no more than 1, 2, 3, or 4 days, and Z is no more than 1, 2, 3, or 4 days. In one embodiment, the present disclosure further provides SIS peptides corresponding to each of the endogenous surrogate peptides.

[00195] Immunoassays and Mass Spectrometry

[00196] As commonly understood and practiced in the art, immunoassays are biochemical tests that quantify and/or measure the presence or concentration of biological molecules of interest in a solution through the use of an antibody or an antigen. In some cases, immunoassays include the the use of antibodies to capture and detect a target. Such detection and quantification methods can be used herein to detect the presence or absence, and/or detect the quantity, of biomarkers, peptides, polypeptides, proteins and/or fragments thereof. Existing, available or conventional separation, detection and quantification methods can also be used herein to detect the presence or absence (e.g., readout being present vs. absent; or detectable amount vs. undetectable amount) and/or detect the quantity (e.g., readout being an absolute or relative quantity, such as, for example, absolute or relative concentration) of biomarkers, peptides, polypeptides, proteins and/or fragments thereof and optionally of the one or more other biomarkers or fragments thereof in samples. In some embodiments, detection and/or quantification of one or more biomarkers comprises an assay that utilizes a capture agent. In further embodiments, the capture agent is an antibody, antibody fragment, nucleic acid-based protein binding reagent, small molecule or variant thereof. In additional embodiments, the assay is an enzyme immunoassay (EIA), enzyme-linked immunosorbent assay (ELISA), and radioimmunoassay (RIA). In some embodiments, detection and/or quantification of one or more biomarkers further comprises mass spectrometry (MS). In yet further embodiments, the mass spectrometry is co-immunoprecitipation-mass spectrometry (co-IP MS), where coimmunoprecipitation, a technique suitable for the isolation of whole protein complexes, is followed by mass spectrometric analysis.

[00197] Generally, any mass spectrometric (MS) technique that can provide precise information on the mass of peptides, and preferably also on fragmentation and/or (partial) amino acid sequence of selected peptides (e.g., in tandem mass spectrometry, MS/MS; or in post source decay, TOF MS), can be used in the methods disclosed herein. Suitable peptide MS and MS/MS techniques and systems are well-known per se (see, e.g., Methods in Molecular Biology, vol. 146: “Mass Spectrometry of Proteins and Peptides”, by Chapman, ed., Humana Press 2000; Biemann 1990. Methods Enzymol 193: 455-79; or Methods in Enzymology, vol. 402: “Biological Mass Spectrometry”, by Burlingame, ed., Academic Press 2005) and can be used in practicing the methods disclosed herein. Accordingly, in some embodiments, the disclosed methods comprise performing quantitative MS to measure one or more biomarkers. Such quantitative methods can be performed in an automated (Villanueva, et al., Nature Protocols (2006) l(2):880-891) or semi-automated format. In particular embodiments, MS can be operably linked to a liquid chromatography device (LC-MS/MS or LC-MS) or gas chromatography device (GC-MS or GC -MS/MS). Other methods useful in this context include isotope-coded affinity tag (ICAT), tandem mass tags (TMT), or stable isotope labeling by amino acids in cell culture (SIL AC), followed by chromatography and MS/MS. [00198] Mass spectrometry assays, instruments and systems suitable for biomarker peptide analysis can include, without limitation, matrix-assisted laser desorption/ionisation time-of- flight (MALDI-TOF) MS; MALDI-TOF post-source-decay (PSD); MALDI-TOF/TOF; surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDLTOF) MS; electrospray ionization mass spectrometry (ESLMS); ESLMS/MS; ESI-MS/(MS)n (n is an integer greater than zero); ESI 3D or linear (2D) ion trap MS; ESI triple quadrupole MS; ESI quadrupole orthogonal TOF (Q-TOF); ESI Fourier transform MS systems; desorption/ionization on silicon (DIOS); secondary ion mass spectrometry (SIMS); atmospheric pressure chemical ionization mass spectrometry (APCLMS); APCLMS/MS; APCL (MS)_n; ion mobility spectrometry (IMS); inductively coupled plasma mass spectrometry (ICP-MS)atmospheric pressure photoionization mass spectrometry (APPLMS); APPI- MS/MS; and APPI- (MS)n. Peptide ion fragmentation in tandem MS (MS/MS) arrangements can be achieved using manners established in the art, such as, e.g., collision induced dissociation (CID). As described herein, detection and quantification of biomarkers by mass spectrometry can involve multiple reaction monitoring (MRM), such as described among others by Kuhn et al. Proteomics 4: 1175-86 (2004). Scheduled multiple-reaction-monitoring (Scheduled MRM) mode acquisition during LC-MS/MS analysis enhances the sensitivity and accuracy of peptide quantitation. Anderson and Hunter, Molecular and Cellular Proteomics 5(4): 573 (2006). As described herein, mass spectrometry -based assays can be advantageously combined with upstream peptide or protein separation or fractionation methods, such as for example with the chromatographic and other methods described herein below. As further described herein, shotgun quantitative proteomics can be combined with SRM/MRM-based assays for high-throughput identification and verification of biomarkers useful for separating a pregnancy that delivers before 270 days from a pregnancy that delivers on or after 280 days.

[00199] A person skilled in the art will appreciate that a number of methods can be used to determine the amount of a biomarker, including mass spectrometry approaches, such as MS/MS, LC-MS/MS, multiple reaction monitoring (MRM) or SRM and product-ion monitoring (PIM) and also including antibody based methods such as immunoassays such as Western blots, enzyme-linked immunosorbant assay (ELISA), immunoprecipitation, immunohistochemistry, immunofluorescence, radioimmunoassay, dot blotting, and FACS. Accordingly, in some embodiments, determining the level of the at least one biomarker comprises using an immunoassay and/or mass spectrometric methods. In additional embodiments, the mass spectrometric methods are selected from MS, MS/MS, LC-MS/MS, SRM, PIM, and other such methods that are known in the art. In other embodiments, LC- MS/MS further comprises ID LC-MS/MS, 2D LC-MS/MS or 3D LC-MS/MS. Immunoassay techniques and protocols are generally known to those skilled in the art (Price and Newman, Principles and Practice of Immunoassay, 2nd Edition, Grove’s Dictionaries, 1997; and Gosling, Immunoassays: A Practical Approach, Oxford University Press, 2000.) A variety of immunoassay techniques, including competitive and non-competitive immunoassays, can be used (Self et ak, Curr. Opin. Biotechnok, 7:60-65 (1996).

[00200] In further embodiments, the immunoassay is selected from Western blot, ELISA, immunoprecipitation, immunohistochemistry, immunofluorescence, radioimmunoassay (RIA), dot blotting, and FACS. In certain embodiments, the immunoassay is an ELISA. In yet a further embodiment, the ELISA is direct ELISA (enzyme-linked immunosorbent assay), indirect ELISA, sandwich ELISA, competitive ELISA, multiplex ELISA, ELISPOT technologies, and other similar techniques known in the art. Principles of these immunoassay methods are known in the art, for example John R. Crowther, The ELISA Guidebook, 1st ed., Humana Press 2000, ISBN 0896037282. Typically ELISAs are performed with antibodies but they can be performed with any capture agents that bind specifically to one or more biomarkers described herein and that can be detected. Multiplex ELISA allows simultaneous detection of two or more analytes within a single compartment (e.g., microplate well) usually at a plurality of array addresses (Nielsen and Geierstanger 2004. J Immunol Methods 290: 107-20 (2004) and Ling et al. 2007. Expert Rev Mol Diagn 7: 87-98 (2007)).

[00201] In some embodiments, RIA can be used to detect one or more biomarkers in the methods of the disclosure. RIA is a competition-based assay that is well known in the art and involves mixing known quantities of radioactively-labelled (e.g.,¹²⁵I or ¹³ ^-labelled) target analyte with antibody specific for the analyte, then adding non-labeled analyte from a sample and measuring the amount of labeled analyte that is displaced (see, e.g., An Introduction to Radioimmunoassay and Related Techniques, by Chard T, ed., Elsevier Science 1995, ISBN 0444821198 for guidance).

[00202] Analogous to SIS in MRM, surrogates can be used in immunoassays. For example, a recombinant protein can be used as a standard for quantification in ELISA/ECLIA. The protein standard may be synthesized as “full length” or a fragment of the protein.

[00203] A detectable label can be used in the assays described herein for direct or indirect detection of the biomarkers in the methods of the disclosure. A wide variety of detectable labels can be used, with the choice of label depending on the sensitivity required, ease of conjugation with the antibody, stability requirements, and available instrumentation and disposal provisions. Those skilled in the art are familiar with selection of a suitable detectable label based on the assay detection of the biomarkers in the methods described herein. Suitable detectable labels include, but are not limited to, fluorescent dyes (e.g., fluorescein, fluorescein isothiocyanate (FITC), Oregon Green™, rhodamine, Texas red, tetrarhodimine isothiocynate (TRITC), Cy3, Cy5, etc.), fluorescent markers (e.g., green fluorescent protein (GFP), phycoerythrin, etc.), enzymes (e.g., luciferase, horseradish peroxidase, alkaline phosphatase, etc.), nanoparticles, biotin, digoxigenin, metals, and the like.

[00204] For mass-spectrometry based analysis, differential tagging with isotopic reagents, e.g., isotope-coded affinity tags (ICAT) or the more recent variation that uses isobaric tagging reagents, iTRAQ (Applied Biosystems, Foster City, Calif.), or tandem mass tags, TMT, (Thermo Scientific, Rockford, IL), followed by multidimensional liquid chromatography (LC) and tandem mass spectrometry (MS/MS) analysis can provide a further methodology in practicing the methods described herein.

[00205] A chemiluminescence assay using a chemiluminescent antibody can be used for sensitive, non-radioactive detection of protein levels. An antibody labeled with fluorochrome also can be suitable. Examples of fluorochromes include, without limitation, DAPI, fluorescein, Hoechst 33258, R-phycocyanin, B -phycoerythrin, R-phycoerythrin, rhodamine, Texas red, and lissamine. Indirect labels include various enzymes well known in the art, such as horseradish peroxidase (HRP), alkaline phosphatase (AP), beta-galactosidase, urease, and the like. Detection systems using suitable substrates for horseradish-peroxidase, alkaline phosphatase, and beta-galactosidase are well known in the art. Moreover, an electrochemiluminescence immunoassay (ECLIA), is a type of chemiluminescence immunoassay used to measure the concentration of various substances in a patient’s blood. As readily appreciated in the art, ECLIA is commonly employed to detect and quantify, e.g., hormones, proteins, drugs, and other analytes that are important for diagnosing and monitoring various diseases and conditions. In some embodiments, the present methods, compositions, and kits herein use ECLIA in determining the PDD, predicting the GAB, predicting the TTB, or estimating the GA for a pregnant female.

[00206] A signal from the direct or indirect label can be analyzed, for example, using a spectrophotometer to detect color from a chromogenic substrate; a radiation counter to detect radiation such as a gamma counter for detection of ¹²⁵I; or a fluorometer to detect fluorescence in the presence of light of a certain wavelength. For detection of enzyme-linked antibodies, a quantitative analysis can be made using a spectrophotometer such as an EMAX Microplate Reader (Molecular Devices; Menlo Park, Calif.) in accordance with the manufacturer’s instructions. If desired, assays used to practice the methods described herein can be automated or performed robotically, and the signal from multiple samples can be detected simultaneously. [00207] In some embodiments, the methods described herein encompass quantification of the biomarkers using mass spectrometry (MS). In further embodiments, the mass spectrometry can be liquid chromatography-mass spectrometry (LC-MS), multiple reaction monitoring (MRM) or selected reaction monitoring (SRM). In additional embodiments, the MRM or SRM can further encompass scheduled MRM or scheduled SRM.

[00208] Chromatography

[00209] As described above, chromatography can also be used in practicing the methods described herein. Chromatography encompasses methods for separating chemical substances and generally involves a process in which a mixture of analytes is carried by a moving stream of liquid or gas (“mobile phase”) and separated into components as a result of differential distribution of the analytes as they flow around or over a stationary liquid or solid phase (“stationary phase”), between the mobile phase and said stationary phase. The stationary phase can be usually a finely divided solid, a sheet of filter material, or a thin film of a liquid on the surface of a solid, or the like. Chromatography is well understood by those skilled in the art as a technique applicable for the separation of chemical compounds of biological origin, such as, e.g., amino acids, proteins, fragments of proteins or peptides, etc.

[00210] Chromatography can be columnar (i.e. , wherein the stationary phase is deposited or packed in a column), preferably liquid chromatography, and yet more preferably high- performance liquid chromatography (HPLC), or ultra high performance/pressure liquid chromatography (UHPLC). Particulars of chromatography are well known in the art (Bidlingmeyer, Practical HPLC Methodology and Applications, John Wiley & Sons Inc., 1993). Exemplary types of chromatography include, without limitation, high-performance liquid chromatography (HPLC), UHPLC, normal phase HPLC (NP-HPLC), reversed phase HPLC (RP-HPLC), ion exchange chromatography (IEC), such as cation or anion exchange chromatography, hydrophilic interaction chromatography (HILIC), hydrophobic interaction chromatography (HIC), size exclusion chromatography (SEC) including gel filtration chromatography or gel permeation chromatography, chromatofocusing, affinity chromatography such as immuno-affinity, immobilized metal affinity chromatography, and the like. Chromatography, including single-, two- or more-dimensional chromatography, can be used as a peptide fractionation method in conjunction with a further peptide analysis method, such as for example, with a downstream mass spectrometry analysis as described elsewhere in this specification.

[00211] Further peptide or polypeptide separation, identification or quantification methods can be used, optionally in conjunction with any of the above-described analysis methods, for measuring biomarkers in the present disclosure. Such methods include, without limitation, chemical extraction partitioning, isoelectric focusing (IEF) including capillary isoelectric focusing (CIEF), capillary isotachophoresis (CITP), capillary electrochromatography (CEC), and the like, one-dimensional polyacrylamide gel electrophoresis (PAGE), two-dimensional polyacrylamide gel electrophoresis (2D-PAGE), capillary gel electrophoresis (CGE), capillary zone electrophoresis (CZE), micellar electrokinetic chromatography (MEKC), free flow electrophoresis (FFE), etc.

[00212] Capture Agents and Detection

[00213] As disclosed herein, capture agents can be configured to specifically bind to a target, in particular a biomarker. Capture agents can include but are not limited to organic molecules, such as polypeptides, polynucleotides and other non polymeric molecules that are identifiable to a skilled person. In the embodiments disclosed herein, capture agents include any agent that can be used to detect, purify, isolate, or enrich a target, in particular a biomarker. Any art- known affinity capture technologies can be used to selectively isolate and enrich/concentrate biomarkers that are components of complex mixtures of biological media for use in the disclosed methods.

[00214] Antibody capture agents that specifically bind to a biomarker can be prepared using any suitable methods known in the art. See, e.g., Coligan, Current Protocols in Immunology (1991); Harlow & Lane, Antibodies: A Laboratory Manual (1988); Goding, Monoclonal Antibodies: Principles and Practice (2d ed. 1986). Antibody capture agents can be any immunoglobulin or derivative thereof, whether natural or wholly or partially synthetically produced. All derivatives thereof which maintain specific binding ability are also included in the term. Antibody capture agents have a binding domain that is homologous or largely homologous to an immunoglobulin binding domain and can be derived from natural sources, or partly or wholly synthetically produced. Antibody capture agents can be monoclonal or polyclonal antibodies. In some embodiments, an antibody is a single chain antibody. Those of ordinary skill in the art will appreciate that antibodies can be provided in any of a variety of forms including, for example, humanized, partially humanized, chimeric, chimeric humanized, etc. Antibody capture agents can be antibody fragments including, but not limited to, Fab, Fab’, F(ab’)2, scFv, Fv, dsFv diabody, and Fd fragments. An antibody capture agent can be produced by any means. For example, an antibody capture agent can be enzymatically or chemically produced by fragmentation of an intact antibody and/or it can be recombinantly produced from a gene encoding the partial antibody sequence. An antibody capture agent can comprise a single chain antibody fragment. Alternatively, or additionally, antibody capture agent can comprise multiple chains which are linked together, for example, by disulfide linkages.; and, any functional fragments obtained from such molecules, wherein such fragments retain specificbinding properties of the parent antibody molecule. Because of their smaller size as functional components of the whole molecule, antibody fragments can offer advantages over intact antibodies for use in certain immunochemical techniques and experimental applications.

[00215] Suitable capture agents useful for practicing the methods described herein also include aptamers. Aptamers are oligonucleotide sequences that can bind to their targets specifically via unique three-dimensional (3-D) structures. An aptamer can include any suitable number of nucleotides and different aptamers can have either the same or different numbers of nucleotides. Aptamers can be DNA or RNA or chemically modified nucleic acids and can be single stranded, double stranded, or contain double stranded regions, and can include higher ordered structures. An aptamer can also be a photoaptamer, where a photoreactive or chemically reactive functional group is included in the aptamer to allow it to be covalently linked to its corresponding target. Use of an aptamer capture agent can include the use of two or more aptamers that specifically bind the same biomarker. An aptamer can include a tag. An aptamer can be identified using any known method, including the SELEX (systematic evolution of ligands by exponential enrichment) process. Once identified, an aptamer can be prepared or synthesized in accordance with any known method, including chemical synthetic methods and enzymatic synthetic methods and used in a variety of applications for biomarker detection. Liu et al.. Curr Med Chem. 18(27):4117-25 (2011). Capture agents useful in practicing the methods described herein also include SOMAmers (Slow Off-Rate Modified Aptamers) known in the art to have improved off-rate characteristics. Brody et al., J Mol Biol. 422(5):595-606 (2012). SOMAmers can be generated using any known method, including the SELEX method.

[00216] In some embodiments, the capture agents herein bind to a region of any of the biomarkers of Table 2 comprising the respective amino acid sequences of the biomarkers. For instance, in some embodiments, any of the capture agents herein can specifically bind to a region of any of the biomarkers of Table 2, such that the capture agents are selective for the desired biomarker when present in the sample. Such a region can include a domain that includes one or more of the amino acid sequences disclosed herein for the desired biomarker or for a different domain comprising an amino acid sequence that is different from those described herein, as long as the domain is selective for the desired biomarker. Accordingly, in some embodiments, any of the capture agents herein bind to a region of ADA12 comprising the amino acid sequence FGFGGSTDSGPIR (SEQ ID NO: 1), the capture agent binds to a region of KIT comprising the amino acid sequence YVSELHLTR (SEQ ID NO: 2), the capture agent binds to a region of KIT comprising the amino acid sequence LCLHCSVDQEGK (SEQ ID NO: 3), the capture agent binds to a region of FETUA comprising the amino acid sequence FSVVYAK (SEQ ID NO: 4), the capture agent binds to a region of ENPP2 comprising the amino acid sequence TEFLSNYLTNVDDITLVPGTLGR (SEQ ID NO: 5), the capture agent binds to a region of ENPP2 comprising the amino acid sequence TYLHTYESEI (SEQ ID NO: 6), the capture agent binds to a region of A2GL comprising the amino acid sequence DLLLPQPDLR (SEQ ID NO: 7), or the capture agent binds to a region of IGF 1 comprising the amino acid sequence GFYFNKPTGYGSSSR (SEQ ID NO: 8). In some embodiments, any of the capture agents herein bind to a region of ADA12 that does not comprise the amino acid sequence FGFGGSTDSGPIR (SEQ ID NO: 1), the capture agent binds to a region of KIT that does not comprise the amino acid sequence YVSELHLTR (SEQ ID NO: 2), the capture agent binds to a region of KIT that does not comprise the amino acid sequence LCLHCSVDQEGK (SEQ ID NO: 3), the capture agent binds to a region of FETUA that does not comprise the amino acid sequence FSVVYAK (SEQ ID NO: 4), the capture agent binds to a region of ENPP2 that does not comprise the amino acid sequence TEFLSNYLTNVDDITLVPGTLGR (SEQ ID NO: 5), the capture agent binds to a region of ENPP2 that does not comprise the amino acid sequence TYLHTYESEI (SEQ ID NO: 6), the capture agent binds to a region of A2GL that does not comprise the amino acid sequence DLLLPQPDLR (SEQ ID NO: 7), or the capture agent binds to a region of IGF1 that does not comprise the amino acid sequence GFYFNKPTGYGSSSR (SEQ ID NO: 8), but does bind to a region of ADA12, KIT, FETUA, ENPP2, A2GL, or IGF1, respectively, that is selective for ADA12, KIT, FETUA, ENPP2, A2GL, or IGF1, respectively.

[00217] It is understood by those skilled in the art that biomarkers can be modified prior to analysis to improve their resolution or to determine their identity. For example, the biomarkers can be subject to proteolytic digestion before analysis. Any protease can be used. Proteases, such as trypsin, that are likely to cleave the biomarkers into a discrete number of fragments are particularly useful. The fragments that result from digestion function as a fingerprint for the biomarkers, thereby enabling their detection indirectly. This is particularly useful where there are biomarkers with similar molecular masses that might be confused for the biomarker in question. Also, proteolytic fragmentation is useful for high molecular weight biomarkers because smaller biomarkers are more easily resolved by mass spectrometry. In another example, biomarkers can be modified to improve detection resolution. For instance, neuraminidase can be used to remove terminal sialic acid residues from glycoproteins to improve binding to an anionic adsorbent and to improve detection resolution. In another example, the biomarkers can be modified by the attachment of a tag of particular molecular weight that specifically binds to molecular biomarkers, further distinguishing them. Optionally, after detecting such modified biomarkers, the identity of the biomarkers can be further determined by matching the physical and chemical characteristics of the modified biomarkers in a protein database (e.g., SwissProt).

[00218] It is further appreciated in the art that biomarkers in a sample can be captured on a substrate for detection. Traditional substrates include antibody-coated 96-well plates or nitrocellulose membranes that are subsequently probed for the presence of the proteins. Alternatively, protein-binding molecules attached to microspheres, microparticles, microbeads, beads, or other particles can be used for capture and detection of biomarkers. The protein-binding molecules can be antibodies, peptides, peptoids, aptamers, small molecule ligands or other protein-binding capture agents attached to the surface of particles. Each protein-binding molecule can include unique detectable label that is coded such that it can be distinguished from other detectable labels attached to other protein-binding molecules to allow detection of biomarkers in multiplex assays. Examples include, but are not limited to, color- coded microspheres with known fluorescent light intensities (see e.g., microspheres with xMAP technology produced by Luminex (Austin, Tex.); microspheres containing quantum dot nanocrystals, for example, having different ratios and combinations of quantum dot colors (e.g., Qdot nanocrystals produced by Life Technologies (Carlsbad, Calif.); glass coated metal nanoparticles (see e.g., SERS nanotags produced by Nanoplex Technologies, Inc. (Mountain View, Calif.); barcode materials (see e.g., sub-micron sized striped metallic rods such as Nanobarcodes produced by Nanoplex Technologies, Inc.), encoded microparticles with colored bar codes (see e.g., CellCard produced by Vitra Bioscience, vitrabio.com), glass microparticles with digital holographic code images (see e.g., CyVera microbeads produced by Illumina (San Diego, Calif.); chemiluminescent dyes, combinations of dye compounds; and beads of detectably different sizes.

[00219] In another aspect, biochips can be used for capture and detection of the biomarkers described herein. Many protein biochips are known in the art. These include, for example, protein biochips produced by Packard BioScience Company (Meriden Conn.), Zyomyx (Hayward, Calif.) and Phylos (Lexington, Mass.). In general, protein biochips comprise a substrate having a surface. A capture reagent or adsorbent is attached to the surface of the substrate. Frequently, the surface comprises a plurality of addressable locations, each of which location has the capture agent bound there. The capture agent can be a biological molecule, such as a polypeptide or a nucleic acid, which captures other biomarkers in a specific manner. Alternatively, the capture agent can be a chromatographic material, such as an anion exchange material or a hydrophilic material. Examples of protein biochips are well known in the art.

[00220] In some embodiments, a biological sample can be contacted with one or more polynucleotide binding agents. The expression of one or more of the biomarkers detected can then be evaluated according to the methods disclosed herein, e.g., with or without the use of nucleic acid amplification methods. Skilled practitioners appreciate that in the methods described herein, a measurement of gene expression can be automated. For example, a system that can carry out multiplexed measurement of gene expression can be used, e.g., providing digital readouts of the relative abundance of hundreds of mRNA species simultaneously.

[00221] In some embodiments, nucleic acid amplification methods can be used to detect a polynucleotide biomarker. For example, the oligonucleotide primers and probes of the present disclosure can be used in amplification and detection methods that use nucleic acid substrates isolated by any of a variety of well-known and established methodologies (e.g., Sambrook et al., Molecular Cloning, A laboratory Manual, pp. 7.37-7.57 (2nd ed., 1989); Lin et al., in Diagnostic Molecular Microbiology, Principles and Applications, pp. 605-16 (Persing et al., eds. (1993); Ausubel et al., Current Protocols in Molecular Biology (2001 and subsequent updates)). Methods for amplifying nucleic acids include, but are not limited to, for example the polymerase chain reaction (PCR) and reverse transcription PCR (RT-PCR) (see e.g., U.S. Pat. Nos. 4,683,195; 4,683,202; 4,800,159; 4,965,188), ligase chain reaction (LCR) (see, e.g., Weiss, Science 254: 1292-93 (1991)), strand displacement amplification (SDA) (see e.g., Walker et al., Proc. Natl. Acad. Sci. USA 89:392-396 (1992); U.S. Pat. Nos. 5,270,184 and 5,455,166), Thermophilic SDA (tSDA) (see e.g., European Pat. No. 0 684 315) and methods described in U.S. Pat. No. 5,130,238; Lizardi et al., BioTechnol. 6: 1197-1202 (1988); Kwoh et al., Proc. Natl. Acad. Sci. USA 86: 1173-77 (1989); Guatelli et al., Proc. Natl. Acad. Sci. USA 87: 1874-78 (1990); U.S. Pat. Nos. 5,480,784; 5,399,491; US Publication No. 2006/46265. [00222] In some embodiments, measuring mRNA in a biological sample can be used as a surrogate for detection of the level of the corresponding protein biomarker in a biological sample. Thus, any of the biomarkers or biomarker pairs described herein can also be detected by detecting the appropriate RNA. Levels of mRNA can be measured by reverse transcription quantitative polymerase chain reaction (RT-PCR followed with qPCR). RT-PCR is used to create a cDNA from the mRNA. The cDNA can be used in a qPCR assay to produce fluorescence as the DNA amplification process progresses. By comparison to a standard curve, qPCR can produce an absolute measurement such as number of copies of mRNA per cell. Northern blots, microarrays, Invader assays, and RT-PCR combined with capillary electrophoresis have all been used to measure expression levels of mRNA in a sample. See Gene Expression Profiling: Methods and Protocols, Richard A. Shimkets, editor, Humana Press, 2004.

[00223] In some embodiments, the biological samples herein are detected, collected, captured, shipped, and/or stored using systems, methods, and fixating agents (e.g., absorbant filter paper) that do not use or have metal chelators, such as ethylenediaminetetraacetic acid (EDTA) or citrate. It is believed that ADA12 detection, for instance, is negatively impacted by the presence of such compounds. Heparin, however, is contemplated to be acceptable as an anti-coagulant due to its siginificantly different mechanism for anti-coagulation.

[00224] Classifiers and Models

[00225] The methods, compositions, and kits of the disclosure can include use of clinical and demographic variables, including but not limited to, maternal characteristics, medical history, past pregnancy history, and obstetrical history. Such additional clinical variables can include, e.g., previous low birth weight or preterm delivery, multiple 2nd trimester spontaneous abortions, prior first trimester induced abortion, familial and intergenerational factors, history of infertility, parity, nulliparity, placental abnormalities, cervical and uterine anomalies, short cervical length measurements, results of anomaly scans (including fetal (e.g., crown-rump length), placental and maternal pelvic organ measures), gestational bleeding, intrauterine growth restriction, in utero diethylstilbestrol exposure, multiple gestations, infant sex, short stature, low prepregnancy weight, chronic diabetes mellitus, chronic hypertension, urogenital infections (z.e., urinary tract infection), asthma, anxiety and depression, asthma, hypothyroidism, high body mass index (BMI), low BMI, BMI. Demographic variables, factors, or risk indicia for preterm birth can include, for example, MAGE, race/ethnicity, single marital status, low socioeconomic status, employment-related physical activity, occupational exposures and environment exposures and stress. Further clinical variables can include, inadequate prenatal care, cigarette smoking, use of marijuana and other illicit drugs, cocaine use, alcohol consumption, caffeine intake, maternal weight gain, dietary intake, sexual activity during late pregnancy and leisure-time physical activities. (Preterm Birth: Causes, Consequences, and Prevention, Institute of Medicine (US) Committee on Understanding Premature Birth and Assuring Healthy Outcomes; Behrman RE, Butler AS, editors. Washington (DC): National Academies Press (US); 2007). Additional clinical variables useful for as markers can be identified using learning algorithms known in the art, such as linear discriminant analysis, support vector machine classification, recursive feature elimination, prediction analysis of microarray, logistic regression, CART, FlexTree, LART, random forest, MART, and/or survival analysis regression, which are known to those of skill in the art and are further described herein. In some embodiments, the clinical or demographic variables that can be used in the methods, uses, and compositions herein include one or more of any of the above listed clinical and/or demographic variables, including one or more of: previous low birth weight or preterm delivery, multiple 2nd trimester spontaneous abortions, prior first trimester induced abortion, familial and intergenerational factors, history of infertility, parity, nulliparity, placental abnormalities, cervical and uterine anomalies, short cervical length measurements, results of anomaly scans (including fetal (e.g., crown-rump length), placental and maternal pelvic organ measures), gestational bleeding, intrauterine growth restriction, in utero diethylstilbestrol exposure, multiple gestations, infant sex, short stature, low prepregnancy weight, chronic diabetes mellitus, chronic hypertension, urogenital infections (/.c., urinary tract infection), asthma, anxiety and depression, asthma, hypertension, hypothyroidism, high body mass index (BMI), low BMI, BMI, MAGE, race/ethnicity, single marital status, low socioeconomic status, employment-related physical activity, occupational exposures and environment exposures and stress, inadequate prenatal care, cigarette smoking, use of marijuana and other illicit drugs, cocaine use, alcohol consumption, caffeine intake, maternal weight gain, dietary intake, sexual activity during late pregnancy and leisure-time physical activities. For example, in some embodiments, the clinical or demographic variables that can be used in the methods, uses, and compositions herein include one or more of age, BMI, race, hypertiension/preeclampsia in a prior pregnancy, preterm birth in a prior pregnancy, c-section delivery in a prior pregnancy, education level, being a first time mother, chronic diabetes, gestational diabetes in the current pregnancy, and hypertension or preeclampsia in the current pregnancy. In some embodiments, two or more clinical or demographic variables are selected. In some embodiments, three or more clinical demographic variables are selected. In some embodiments, four or more clinical or demographic variables are selected. In some embodiments, five or more clinical or demographic variables are selected. In some embodiments, six or more embodimclinical or demographic variables are selected. In some embodiments, seven or more clinical or demographic variables are selected. In some embodiments, eight or more clinical or demographic variables are selected. In some embodiments, nine or more clinical or demographic variables are selected. In some embodiments, ten or more clinical or demographic variables are selected. In some embodiments, eleven or more clinical or demographic variables are selected.

[00226] The present disclosure describes and exemplifies various models and corresponding biomarkers that perform at high levels of accuracy and precision in determining the PDD. It will be understood by those of skill in the art that other models are known in the art that can be used to practice the claimed embodiments of the disclosure and that the performance of a model can be evaluated in a variety of ways, including, but not limited to accuracy, precision, recall/sensitivity, weighted average of precision and recall. Models known in the art include, witout limitation, linear discriminant analysis, support vector machine classification, recursive feature elimination, prediction analysis of microarray, logistic regression, CART, FlexTree, LART, random forest, MART, and/or survival analysis regression.

[00227] The present disclosure is based, in part, on the surprising discovery that the selection of certain biomarkers and/or clinical variables enables determining PDD and/or TTB at a significantly higher level of accuracy and precision compared to current cinical practice of determining EDD, which is accurate in making a due date prediction that falls within +/-5 days of the actual due date only about 35% of the time. In some embodiments, the present disclosure provides and exemplifies compositions, methods and kits that enable a PDD or predicted TTB that falls within +/-X days of the ADD or actual TTB at least Y% of the time, where X = 10, 9, 8, 7, 6, 5, 4, 3, 2 or 1 and Y = 50%, 51%, 52%, 53%, 54%, 55%, 56%, 57%, 58%, 59%, 60%, 61%, 62%, 63%, 64%, 65%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or 100%. In some embodiments, X is 3, 2, or 1. In some embodiments, Y is 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or 100%. Thus, in some embodiments, performance of a model (or a method of the disclosure) can be evaluated based on accuracy, which can be described as the difference between the EDD and the ADD. For example, accuracy can be expressed as the percentage of the time, for example, 50%, 51%, 52%, 53%,

54%, 55%, 56%, 57%, 58%, 59%, 60%, 61%, 62%, 63%, 64%, 65%, 70%, 71%, 72%, 73%,

74%, 75%, 76%, 77%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%,

92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or more, that a model provides a PDD or TTB that falls within a certain range of days, for example, +/-10 days, +/-9 days, +/-8 days, +/-7 days, +/-6 days, +/-5 days, +/-4 days, +/-3 days+/-2 days, +/- 1 day of the ADD. In some embodiments of the present disclosure, the reversal value gives a PDD or TTB that falls within 3 days of the pregnant female’s ADD, and a PDD or TTB that is within 5 days of the pregnant female’s EDD. In some embodiments, accuracy can be described by noting that the PDD or TTB predictor is accurate within +/-X days of the ADD or actual TTB at least Y% of the time, where X = 10, 9, 8, 7, 6, 5, 4, 3, 2 or 1 and Y = 50%, 51%, 52%, 53%, 54%, 55%, 56%, 57%, 58%, 59%, 60%, 61%, 62%, 63%, 64%, 65%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or 100%. In some embodiments, X is 5, 4, 3, 2 or 1. In some embodiments, Y is 50%, 51%, 52%, 53%, 54%, 55%, 56%, 57%, 58%, 59%, 60%, 61%, 62%, 63%, 64%, 65%. In other embodiments, Y is 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, or 89%. In some embodiments, X is 3, 2, or 1, and Y is 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or 100%.

[00228] Some embodiments of the present disclosure relate to using the biomarkers, methods, kits, and compositions herein as predictive models for predicting fetal development or pregnancy progression, independent of a time from fertilization. As an example, using two pregnant women who are each 140 days into their pregnancy and have each been given an equally accurate/precise EDD that is 140 days away, one woman may be given a PDD corresponding to a delivery that is 140 days away (z.e., the EDD is kept), while the other woman may be given a PDD corresponding to delivery that is 133 days away. In this instance, the second woman’s fetus may be 7 days more developed (z.e., the pregnancy is 7 days more advanced), even though the original EDD dating was as equally accurate/precise as the first woman’s, and their pregnancies began on the same day. Thus, the biomarkers, methods, kits, and compositions herein may also be used to provide the rate at which development of pregnancy is advancing, which may then be used to date a pregnancy more accurately.

[00229] Other embodiments of the present disclosure relate to using the biomarkers, methods, kits, and compositions herein, and integrating or combining the same with clinical or demographic variables, to generate test reports or models to estimate the probability of a pregnant female delivering, in each week, e.g., from week 37 to 41 (see, e.g., FIG. 24, Example 5) and/or the most likely week of delivery. In some embodiments, such test reports or predictive models herein use data from a cohort of subjects that have similar term deliveries and factors as the pregnant female such as age, BMI, race, hypertension/preeclampsia in a prior pregnancy, preterm birth in a prior pregnancy, c-section delivery in a prior pregnancy, education level, being a first-time mother, chronic diabetes, gestational diabetes in the current pregnancy, and hypertension or preeclampsia in the current pregnancy.

[00230] Some embodiments utilize a combination of clinical, demographic, and/or biomarker factors, and the method can produce a result that is both qualitative (e.g., the most likely week to deliver) and quantitative (e.g., the probability of each week to deliver). In some embodiments, the method is intended to predict term births (z.e., 37 weeks or later).

[00231] In some embodiments, the method utilizes the pregnant subject’s (denoted as “S”) cohort (denoted as “C(S)”), which can be characterized as women who have similar biomarker results, demographics, and clinical factors as the subject S. The weekly delivery estimates can be derived from their cohort C(S).

[00232] In some embodiments, a database from the Centers for Disease Control and Prevention (CDC) can be used for clinical and demographic factors integrated into the estimation of probability of delivery in each week and prediction of most likely week of delivery. Women similar to S in the CDC database, denoted as “CDC(S)”, can be formed into a cohort defined as those with term deliveries and similarities on the following clinical or demographic factors: Age; BMI; Race; Hypertension/preeclampsia in a prior pregnancy; Preterm birth in a prior pregnancy; C-section delivery in a prior pregnancy; Education level; First time mother; Chronic diabetes; Gestational diabetes in the current pregnancy; Hypertension or preeclampsia in the current pregnancy. For non-categorical factors, such as age, a window can be used, e.g., women whose age is within 2 years of the subject’s age.

[00233] Once the CDC(S) cohort is formed, the probability of delivering for each week, 37 to 41, can be determined by taking the average across subjects in CDC(S) to produce a probability distribution over these weeks.

[00234] Thus, an exemplary method yields a probability distribution across birth weeks 37 to 41, where: Week 41 includes week 41 and 42; the probability distribution sums to 1; and the most likely delivery week will be the week with the highest probability.

[00235] As one example of these embodiments, FIG. 24 provides an exemplary bar graph of the birth week probability distribution where the factors above, in order, are: 1. 32 (age), 2. 23.3 (BMI), 3. White (race), 4. No (hypertension/preeclampsia in a prior pregnancy), 5. No (preterm birth in a prior pregnancy), 6. Yes (c-section delivery in a prior pregnancy), 7. High School (education level), 8. No (first time mother), 9. No (chronic diabetes), 10. No (gestational diabetes in the current pregnancy), and 11. No (hypertension or preeclampsia in the current pregnancy).

[00236] For biomarker factors used in these embodiments, the biomarker assay (TTB) results for subject S, denoted as “TTB(S)”, can be used. The biomarker assay (TTB) can be any of the assay methods described herein. Subjects can be binned using three classifications, denoted “T(S)” using the measurement TTB(S):

If TTB(S) < median(TTB) - std(TTB) then T(S) is positive (‘skewed right’). If TTB(S) > median(TTB) + std(TTB) then T(S) is negative (‘skewed left’). Otherwise, T(S) is neutral (‘no skew’).

[00237] TTB can be the distribution of assay values over the database used for clinical and demographic factors, in which case the database (e.g., CDC(S)) is restricted to those women with the same assay result T(S) as subject S (or assay results within some variance of subject S’s result, e.g., within 20%, 15%, 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, 0.5%, 0.2%, or 0.1%). In some embodiments, the biomarker assay method distribution comes from a different set of subjects from the clinical/demographic factor distribution.

[00238] In some embodiments, pregnancies can be assigned to one of the three groups: “positive”, “neutral”, and “negative”, as shown in FIG. 25. Specifically, FIG. 25 shows a line graph of the distribution of such “neutral”, “positive”, and “negative” groups and their probability to deliver for each week shown (37 to 42). Neutral represents the average weekly probability, whereas the “positive group” is skewed to the right of the “neutral” group, and the “negative” group is skewed to the left. With this classification of pregnancies based on the biomarker assay methods of the present disclosure, each subject S can be assigned to one of three groups T(S).

[00239] In embodiments where the clinical, demographic, and biomarker factors are all derived from the same database of subjects (as in the embodiments described above), there generally is no need to integrate. In some embodiments, disparate databases (or data from them) can be integrated to derive a delivery week probability distribution that incorporates information from each database (e.g., using Bayes Theorem). In some such embodiments, the weekly probability distribution from one database (e.g., CDC databse) can be used as the base distribution (z.e., the prior) and can then be adjusted using the weekly probability distribution from another database. For example, the weekly probability distribution from the CDC database, based on clinical and/or demographic factors (e.g., Age; BMI; Race; Hypertension/preeclampsia in a prior pregnancy; Preterm birth in a prior pregnancy; C-section delivery in a prior pregnancy; Education level; First time mother; Chronic diabetes; Gestational diabetes in the current pregnancy; Hypertension or preeclampsia in the current pregnancy), can be used as the base distribution and can then be adjusted using the weekly probability distribution from a database of biomarker assay results, all to yield a refined estimation of the probability of delivery in each of weeks, e.g., 37-41, and the week with the highest probability of delivery.

[00240] Thus, in some embodiments the disclosure provides a method of predicting the week of gestation in which a pregnant female is most likely to deliver, the method comprising: (a) obtaining a biological sample obtained from said pregnant female; (b) detecting the presence or amount of one or more isolated biomarkers in said biological sample (e.g., an isolated biomarker in Table 2 or a pair of biomarkers in Table 16); (c) comparing clinical factors for said pregnant female (e.g., age, BMI, race, hypertension/preeclampsia in a prior pregnancy, preterm birth in a prior pregnancy, c-section delivery in a prior pregnancy, education level, being a first-time mother, chronic diabetes, gestational diabetes in the current pregnancy, and hypertension or preeclampsia in the current pregnancy) to the same clinical factors in a cohort of reference pregnant females (e.g., in a proprietary or public database, e.g., in a CDC database); and (d) deriving from (b) and (c) the probability said pregnant female will deliver in each of certain specific weeks of gestation (e.g., each of weeks 37 through 41). In some embodiments, (b) comprises detecting the presence or amount of one or more isolated biomarkers selected from Table 2 or Table 16. In some embodiments, (b) comprises detecting the presence or amount of a pair (or one or more pairs) of isolated biomarkers comprising two isolated biomarkers selected from Table 2 or Table 16. In some embodiments, each pair (or one or more pairs) of isolated biomarkers comprises two upregulated biomarkers. In some embodiments, each pair (or one or more pairs) of isolated biomarkers comprises two downregulated biomarkers. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included. In some embodiments, (b) comprises detecting the presence or amount of a pair of isolated biomarkers comprising ADA12 and an isolated biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1 (e.g., ADA12 and KIT). In some such embodiments the probability in (d) is derived by (dl) deriving the probability said pregnant female will deliver in each of certain specific weeks of gestation (e.g., each of weeks 37 through 41) based at least in part on the comparison in (c) and (d2) adjusting the probability in (dl) by the probability derived from comparing the amount of biomarker(s) detected in (b) with the amount of biomarkers detected in a reference cohort of pregnant females. In some embodiments the adjustment is made using Bayes Theorem.

[00241] Some embodiments disclosed herein relate to methods of determining the PDD for a pregnant female. The detection of the amount, presence, or level of expression of one or more biomarkers and/or the determination of a ratio of biomarkers can be used to determine the PDD for a pregnant female. Such detection methods can be used, for example, for early diagnosis of a pregnancy-related condition, to determine whether a subject is predisposed to preterm birth, to monitor the progress of preterm birth or the progress of treatment protocols, to assess the severity of preterm birth, to forecast the outcome of preterm birth and/or prospects of recovery or birth at full term, or to aid in the determination of a suitable treatment for preterm birth.

[00242] The quantitation of biomarkers in a biological sample can be determined, without limitation, by the methods described above as well as any other method known in the art. The quantitative data thus obtained may then be subjected to an analytic classification process. In such a process, the raw data can be manipulated according to an algorithm, where the algorithm has been pre-defined by a training set of data, for example as described in the examples provided herein. An algorithm can utilize the training set of data provided herein, or can utilize the guidelines provided herein to generate an algorithm with a different set of data.

[00243] In some embodiments, determining the PDD for a pregnant female encompasses the use of a predictive model. As those skilled in the art can appreciate, a comparison using such a predictive model can be a direct comparison to a reference feature or an indirect comparison where the reference feature has been incorporated into the predictive model. In further embodiments, determining the PDD for a pregnant female encompasses one or more of a linear discriminant analysis model, a support vector machine classification algorithm, a recursive feature elimination model, a prediction analysis of microarray model, a logistic regression model, a CART algorithm, a flex tree algorithm, a LART algorithm, a random forest algorithm, a MART algorithm, a machine learning algorithm, a penalized regression method, or a combination thereof. In particular embodiments, the analysis comprises logistic regression. [00244] An analytic classification process can use any one of a variety of statistical analytic methods to manipulate the quantitative data and provide for classification of the sample. Examples of useful methods include linear discriminant analysis, recursive feature elimination, a prediction analysis of microarray, a logistic regression, a CART algorithm, a FlexTree algorithm, a LART algorithm, a random forest algorithm, a MART algorithm, machine learning algorithms; etc.

[00245] For creation of a random forest for prediction of GAB one skilled in the art can consider a set of k subjects (pregnant women) for whom the GAB is known, and for whom N analytes (transitions) have been measured in a blood specimen taken several weeks prior to birth. A regression tree begins with a root node that contains all the subjects. The average GAB for all subjects can be calculated in the root node. The variance of the GAB within the root node will be high, because there is a mixture of women with different GAB’s. The root node is then divided (partitioned) into two branches, so that each branch contains women with a similar GAB. The average GAB for subjects in each branch is again calculated. The variance of the GAB within each branch will be lower than in the root node, because the subset of women within each branch has relatively more similar GAB’s than those in the root node. The two branches are created by selecting an analyte and a threshold value for the analyte that creates branches with similar GAB. The analyte and threshold value are chosen from among the set of all analytes and threshold values, usually with a random subset of the analytes at each node. The procedure continues recursively producing branches to create leaves (terminal nodes) in which the subjects have very similar GAB’s. The predicted GAB in each terminal node is the average GAB for subjects in that terminal node. This procedure creates a single regression tree. A random forest can consist of several hundred or several thousand such trees. [00246] Classification can be made according to predictive modeling methods that set a threshold for determining the probability that a sample belongs to a given class. The probability preferably is at least 50%, or at least 55%, or at least 60%, or at least 65%, or at least 70%, or at least 75%, or at least 80%, or at least 85%, or at least 90%, or at least 95% or higher. In some embodiments, the probability is at least 85%, 86%, 87%, 88%, 89%, or 90% or higher. In further embodiments, the probability is at least 95%, 96%, 97%, 98%, or 99% or higher. Classifications also can be made by determining whether a comparison between an obtained dataset and a reference dataset yields a statistically significant difference. If so, then the sample from which the dataset was obtained is classified as not belonging to the reference dataset class. Conversely, if such a comparison is not statistically significantly different from the reference dataset, then the sample from which the dataset was obtained is classified as belonging to the reference dataset class.

[00247] The predictive ability of a model can be evaluated according to its ability to provide a quality metric, e.g., AUROC (area under the ROC curve) or accuracy, of a particular value, or range of values. Area under the curve measures are useful for comparing the accuracy of a classifier across the complete data range. Classifiers with a greater AUC have a greater capacity to classify unknowns correctly between two groups of interest. In some embodiments, a desired quality threshold is a predictive model that will classify a sample with an accuracy of at least about 0.5, at least about 0.55, at least about 0.6, at least about 0.7, at least about 0.75, at least about 0.8, at least about 0.85, at least about 0.9, at least about 0.95, or higher. As an alternative measure, a desired quality threshold can refer to a predictive model that will classify a sample with an AUC of at least about 0.7, at least about 0.75, at least about 0.8, at least about 0.85, at least about 0.9, or higher.

[00248] As is known in the art, the relative sensitivity and specificity of a predictive model can be adjusted to favor either the selectivity metric or the sensitivity metric, where the two metrics have an inverse relationship. The limits in a model as described above can be adjusted to provide a selected sensitivity or specificity level, depending on the particular requirements of the test being performed. One or both of sensitivity and specificity can be at least about 0.7, at least about 0.75, at least about 0.8, at least about 0.85, at least about 0.9, or higher.

[00249] The raw data can be initially analyzed by measuring the values for each biomarker, in some embodiments in triplicate or in multiple triplicates. The data can be manipulated, for example, raw data can be transformed using standard curves, and the average of triplicate measurements used to calculate the average and standard deviation for each patient. These values can be transformed before being used in the models, e.g., log-transformed, Box-Cox transformed (Box and Cox, Royal Stat. Soc., Series B, 26:211-246(1964). The data are then input into a predictive model, which will classify the sample according to the state. The resulting information can be communicated to a patient or health care provider.

[00250] To generate a predictive model for separating a pregnancy that delivers X or more days before the EDD or Y or more days after the EDD, relative to a pregnancy that delivers within Z days of the EDD (where X is e.g., no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days; Y is e.g., no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days; and Z is e.g., no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days), a robust data set, comprising known control samples and samples corresponding to the birth classification of interest can be used in a training set. A sample size can be selected using generally accepted criteria. As discussed above, different statistical methods can be used to obtain a highly accurate predictive model.

[00251] In one embodiment, hierarchical clustering is performed in the derivation of a predictive model, where the Pearson correlation is employed as the clustering metric. One approach is to consider a given birth dataset as a “learning sample” in a problem of “supervised learning.” CART is a standard in applications to medicine (Singer, Recursive Partitioning in the Health Sciences, Springer(1999)) and can be modified by transforming any qualitative features to quantitative features; sorting them by attained significance levels, evaluated by sample reuse methods for Hotelling’s T² statistic; and suitable application of the lasso method. Problems in prediction are turned into problems in regression without losing sight of prediction, indeed by making suitable use of the Gini criterion for classification in evaluating the quality of regressions.

[00252] This approach led to what is termed FlexTree (Huang, Proc. Nat. Acad. Sci. U.S.A 101 : 10529-10534(2004)). FlexTree performs very well in simulations and when applied to multiple forms of data and is useful for practicing the claimed methods. Software automating FlexTree has been developed. Alternatively, LARTree or LART can be used (Turnbull (2005) Classification Trees with Subset Analysis Selection by the Lasso, Stanford University). The name reflects binary trees, as in CART and FlexTree; the lasso, as has been noted; and the implementation of the lasso through what is termed LARS by Efron et ah (2004) Annals of Statistics 32:407-451 (2004). See, also, Huang et al., Proc. Natl. Acad. Sci. USA. 101(29): 10529-34 (2004). Other methods of analysis that can be used include logic regression. One method of logic regression Ruczinski, Journal of Computational and Graphical Statistics 12:475-512 (2003). Logic regression resembles CART in that its classifier can be displayed as a binary tree. It is different in that each node has Boolean statements about features that are more general than the simple “and” statements produced by CART.

[00253] Another approach is that of nearest shrunken centroids (Tibshirani, Proc. Natl. Acad. Sci. U.S.A 99:6567-72(2002)). The technology is k-means-like, but has the advantage that by shrinking cluster centers, one automatically selects features, as is the case in the lasso, to focus attention on small numbers of those that are informative. The approach is available as PAM software and is widely used. Two further sets of algorithms that can be used are random forests (Breiman, Machine Learning 45:5-32 (2001)) and MART (Hastie, The Elements of Statistical Learning, Springer (2001)). These two methods are known in the art as “committee methods,” that involve predictors that “vote” on outcome.

[00254] To provide significance ordering, the false discovery rate (FDR) can be determined. First, a set of null distributions of dissimilarity values is generated. In one embodiment, the values of observed profiles are permuted to create a sequence of distributions of correlation coefficients obtained out of chance, thereby creating an appropriate set of null distributions of correlation coefficients (Tusher et al., Proc. Natl. Acad. Sci. U.S.A 98, 5116-21 (2001)). The set of null distribution is obtained by: permuting the values of each profile for all available profiles; calculating the pair-wise correlation coefficients for all profile; calculating the probability density function of the correlation coefficients for this permutation; and repeating the procedure for N times, where N is a large number, usually 300. Using the N distributions, one calculates an appropriate measure (mean, median, etc.) of the count of correlation coefficient values that their values exceed the value (of similarity) that is obtained from the distribution of experimentally observed similarity values at given significance level.

[00255] The FDR is the ratio of the number of the expected falsely significant correlations (estimated from the correlations greater than this selected Pearson correlation in the set of randomized data) to the number of correlations greater than this selected Pearson correlation in the empirical data (significant correlations). This cut-off correlation value can be applied to the correlations between experimental profiles. Using the aforementioned distribution, a level of confidence is chosen for significance. This is used to determine the lowest value of the correlation coefficient that exceeds the result that would have obtained by chance. Using this method, one obtains thresholds for positive correlation, negative correlation or both. Using this threshold(s), the user can filter the observed values of the pair wise correlation coefficients and eliminate those that do not exceed the threshold(s). Furthermore, an estimate of the false positive rate can be obtained for a given threshold. For each of the individual “random correlation” distributions, one can find how many observations fall outside the threshold range. This procedure provides a sequence of counts. The mean and the standard deviation of the sequence provide the average number of potential false positives and its standard deviation.

[00256] In an alternative analytical approach, variables chosen in the cross-sectional analysis are separately employed as predictors in a time-to-event analysis (survival analysis), where the event is the occurrence of preterm birth, and subjects with no event are considered censored at the time of giving birth. Given the specific pregnancy outcome (preterm birth event or no event), the random lengths of time each patient will be observed, and selection of proteomic and other features, a parametric approach to analyzing survival can be better than the widely applied semi-parametric Cox model. A Weibull parametric fit of survival permits the hazard rate to be monotonically increasing, decreasing, or constant, and also has a proportional hazards representation (as does the Cox model) and an accelerated failure-time representation. All the standard tools available in obtaining approximate maximum likelihood estimators of regression coefficients and corresponding functions are available with this model. [00257] In addition, the Cox models can be used, especially since reductions of numbers of covariates to manageable size with the lasso will significantly simplify the analysis, allowing the possibility of a nonparametric or semi-parametric approach to prediction of time to preterm birth. These statistical tools are known in the art and applicable to all manner of proteomic data. A set of biomarkers, clinical and genetic data that can be easily determined, and that is highly informative regarding the probability for preterm birth and predicted time to a preterm birth event in said pregnant female is provided. Also, algorithms provide information regarding the probability for preterm birth in the pregnant female.

[00258] Survival analyses are commonly used to understand time to occurrence of an event of interest such as birth or death. Commonly, the Kaplan-Meier estimator is used to estimate the survival function, while Cox proportional hazards models are used to estimate the effects of covariates on the hazard of event occurrence. These models conventionally assume that survival time is based on risk of exactly one type of event. However, a competing risk for a different event may be present that either hinders the observation of an event of interest or modifies the chance that this event occurs. Conventional methods may be inappropriate in the presence of competing risks. Alternative methods appropriate for analysis of competing risks either asses competing hazards in sub distribution hazards models or cause-specific modified Cox proportional hazards models; or estimate cumulative incidence over competing events (Jason P. Fine & Robert J. Gray. Journal of the American Statistical Association Vol. 94, Issue 446,1999. A Proportional Hazards Model for the Sub distribution of a Competing Risk).

[00259] In the development of a predictive model, it can be desirable to select a subset of markers, z.e., at least 3, at least 4, at least 5, at least 6, up to the complete set of markers. Usually, a subset of markers will be chosen that provides for the needs of the quantitative sample analysis, e.g., availability of reagents, convenience of quantitation, etc., while maintaining a highly accurate predictive model. The selection of a number of informative markers for building classification models requires the definition of a performance metric and a user- defined threshold for producing a model with useful predictive ability based on this metric. For example, the performance metric can be the AUC, the sensitivity and/or specificity of the prediction as well as the overall accuracy of the prediction model.

[00260] As will be understood by those skilled in the art, an analytic classification process can use any one of a variety of statistical analytic methods to manipulate the quantitative data and provide for classification of the sample. Examples of useful methods include, without limitation, linear discriminant analysis, recursive feature elimination, a prediction analysis of microarray, a logistic regression, a CART algorithm, a FlexTree algorithm, a LART algorithm, a random forest algorithm, a MART algorithm, and machine learning algorithms. Various methods are used in a training model. The selection of a subset of markers can be for a forward selection or a backward selection of a marker subset. The number of markers can be selected that will optimize the performance of a model without the use of all the markers. One way to define the optimum number of terms is to choose the number of terms that produce a model with desired predictive ability (e.g., an AUOO.75, or equivalent measures of sensitivity/specificity) that lies no more than one standard error from the maximum value obtained for this metric using any combination and number of terms used for the given algorithm.

[00261] In some embodiments, one or more isolated biomarkers, reversal pairs, reversal values, and/or reversal triplets of the methods, compositions, and kits herein are combined with clinical and/or demographic variables or components into a numerical combined score (sometimes called a classifier or model herein) that can be trained on a dataset to determine PDD, TTB, etc. In some embodiments, the combined score includes one or more molecular components selected from the group consisting of isolated biomarkers (e.g., measured level of isolated biomarkers in a sample) and/or reversal pairs (either individually or themselves combined into a molecular score) and one or more clinical variables or components selected from the group consisting of GABD; gravidity (number of pregnancies, including current pregnancy); MAGE. In some embodiments, the combined score can be the combination of the molecular score and the clinical score. In some embodiments, the presence or amount of isolated biomarkers detected in a biological sample obtained from a pregnant female is combined with one or more of such clinical components that can be trained on a dataset to determine the PDD or TTB. For instance, in some embodiments, the model comprises a pair of isolated biomarkers herein and one or more clinical components selected from the group consisting of GABD, gravidity, or MAGE. Some components of the combined score (e.g., amount or measured levels of a biomarker, reversal values, GABD, gravidity, MAGE) can be continuous numeric variables. Some components of the combined score can be binary or categorical variables, which can be expressed numerically. For example, the clinical component of gravidity can be included in the combined score as a binary variable, with 0 representing no history of gravidity (nulliparous) and 1 representing a history of gravidity (parous). Any categorical variable can be decomposed into pairwise binary contrasts in which 0 represents one level and 1 represents a second level. As is known in the art, all but one of all possible pairs are so coded for complete representation. Any component of the combined score may be multiplied by a coefficient or otherwise mathematically converted (e.g., logarithm). Some components with continuous possible values can be expressed in a binary fashion. For example, GABD can be expressed as (< 19 weeks or > 20 weeks) = 0 and (19 or 20 weeks) = 1. In some embodiments, the total combined score can be multiplied by a coefficient or otherwise mathematically converted, e.g., to scale the score to run from 0 to 100. Such combined scores can be used as test scores or test values (or correspondingly reference scores or reference values) in any methods or systems described herein.

[00262] In some embodiments of the disclosure, the determination of PDD, TTB, GAB, etc. is based on a regression model. Non-limiting examples of regression models useful as described herein are as follows:

Formula 1 A - B*GABD + C*MAGE - D*GRAVIDITY -

E*log[ADA12] + F*log[KIT]

Formula 2 A - B*GABD + C*MAGE - D*GRAVIDITY - E*log[ADA12]

Formula 3 A - B*GABD - E*log[ADA12] + F*log[KIT]

Formula 4 A - B*GABD - E*log[ADA12]

Each protein biomarker in brackets ([]) above denotes the concentration of the protein in a sample. In some embodiments, the concentration is measured as the ratio of area counts of endogenous fragment over isotopic standard, where the amino acid fragment detected or measured in some embodiments for each protein can be as listed in Table 2 e.g., ADA12 (FGFGGSTDSGPIR (SEQ ID NO:1)) and KIT (YVSELHLTR (SEQ ID NO:2) or LCLHCSVDQEGK (SEQ ID NO:3))).

[00263] The coefficients can be positive or negative. In some embodiments of the disclosure, the coefficients above are as follows:

Modell 263.64 - 0.93*GABD + 0.13*MAGE - 2.06* GRAVIDITY - 3.88*log[ADA12] + 3.88*log[KIT]

Model2 261.43 - 0.91*GABD + 0.12*MAGE - 2.18 *GR AVIDITY - 4.83*log[ADA12] + 2.61*log[KIT]

Model3 262.33 - 0.92*GABD + 0.1*MAGE - 2.21* GRAVIDITY - 4.72*log[ADA12]

Model4 265.49 - 0.93*GABD - 3.63*log[ADA12] + 3.63*log[KIT]

Model5 263.11 - 0.92*GABD - 4.52*log[ADA12] + 2.46*log[KIT]

Model6 263.53 - 0.92*GABD - 4.4*log[ADA12] In some embodiments, A, B, C, D or E is within rounding of these values (e.g., A is between 263.6 and 263.7, etc.). In some embodiments, A is between 263.6 and 263.64, 263.55 and 263.64, 263.5 and 263.64, 263.45 and 263.64, 263.4 and 263.64, 263.35 and 263.64, 263.3 and 263.64, 263.25 and 263.64, 263.2 and 263.64, 263.15 and 263.64, 263.1 and 263.64, 263.05 and 263.64, 263 and 263.64, 262.75 and 263.64, 262.50 and 263.64, 263.64 and 263.7, 263.64 and 263.75, 263.64 and 263.8, 263.64 and 263.85, 263.64 and 263.9, 263.64 and 263.95, 263.64 and 264, 263.64 and 264.25, 263.64 and 264.5, 263.64 and 264.75, 263.64 and 265, 263.64 and

265.25, 263.64 and 265.5, 263.64 and 265.75, or between 263.64 and 266. In some embodiments, B is between 0.90 and 0.92, 0.85 and 0.92, 0.8 and 0.92, 0.75 and 0.92, 0.7 and 0.92, 0.65 and 0.92, 0.6 and 0.92, 0.55 and 0.92, 0.92 and 0.95, 0.92 and 1, 0.92 and 1.05, 0.92 and 1.1, 0.92 and 1.15, 0.92 and 1.2, 0.92 and 1.25, or between 0.92 and 1.3. In some embodiments, C is between 0.10 and 0.12, 0.09 and 0.12, 0.08 and 0.12, 0.07 and 0.12, 0.06 and 0.12, 0.05 and 0.12, 0.04 and 0.12, 0.03 and 0.12, 0.12 and 0.13, 0.12 and 0.14, 0.12 and 0.15, 0.12 and 0.16, 0.12 and 0.17, 0.12 and 0.18, 0.12 and 0.19, or between 0.12 and 0.2. In some embodiments, D is between 2.1 and 2.15, 2.05 and 2.15, 2 and 2.15, 1.95 and 2.15, 1.9 and 2.15, 1.85 and 2.15, 1.8 and 2.15, 1.75 and 2.15, 2.15 and 2.2, 2.15 and 2.25, 2.15 and 2.3, 2.15 and 2.35, 2.15 and 2.4, 2.15 and 2.45, 2.15 and 2.5, or between 2.15 and 2.55. In some embodiments, E is between 3.75 and 4, 3.8 and 4, 3.5 and 4, 3.25 and 4, 3 and 4, 2.75 and 4, 2.5 and 4, 2.25 and 4, 2 and 4, 4 and 4.25, 4 and 4.5, 4 and 4.75, 4 and 5, 4 and 5.25, 4 and 5.5, or between 4 and 5.75. In some embodiments, F is between 2.75 and 3, 2.5 and 3, 2.25 and 3, 2 and 3, 1.75 and 3, 1.5 and 3, 1.25 and 3, 3 and 3.25, 3 and 3.5, 3 and 3.75, 3 and 4, 3 and

4.25, 3 and 4.5, or between 3 and 4.75.

[00264] Kits

[00265] In yet another aspect, the disclosure provides kits for determining the PDD for a pregnant female. The kit can include one or more agents for detection of biomarkers e.g., agents described at length herein); a container for holding a biological sample isolated from a pregnant female; and printed instructions for reacting agents with the biological sample or a portion or derivative of the biological sample to detect the presence or amount of the isolated biomarkers in the biological sample. The agents can be packaged in separate containers. The kit can further comprise one or more control reference samples and reagents for performing an immunoassay.

[00266] In some embodiments, provided herein is a kit for determining the PDD or TTB for a pregnant female, wherein the kit comprises (a) one or more agents for the detection of a pair (or two or more pairs) of isolated biomarkers selected from Table 2; (b) a container for holding a biological sample isolated from a pregnant female; and (c) printed instructions for reacting agents with the biological sample or a portionor derivative of the biological sample to detect the presence or amount of the isolated biomarkers in the biological sample. In some embodiments, the pair of isolated biomarkers is selected from the biomarker pairs listed in Table 3. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 16. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two upregulated biomarkers. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two downregulated biomarkers. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included. In some embodiments, the pair of isolated biomarkers comprises ADA12 and an isolated biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1. In particular embodiments, the pair of isolated biomarkers comprises ADA12 and KIT. In other embodiments, the pair of isolated biomarkers comprises ADA12 and FETUA. In some embodiments, the pair of isolated biomarkers comprises ADA12 and ENPP2. In some embodiments, the pair of isolated biomarkers comprises ADA12 and A2GL. In some embodiments, the pair of isolated biomarkers comprises ADA12 and IGF1. In some embodiments, the pair of isolated biomarkers comprises two isolated biomarkers selected from Table 2. In some embodiments, the kit comprises one or more control reference samples and reagents for performing an immunoassay. [00267] In some embodiments, provided herein is a kit for determining the predicted delivery date (PDD) or time to birth (TTB) for a pregnant female, wherein the kit comprises: (a) one or more agents for the detection of one or more isolated biomarkers; (b) a container for holding a biological sample isolated from a pregnant female; and (c) printed instructions for reacting agents with the biological sample or a portion or derivative of the biological sample to detect the presence or amount of each of the one or more isolated biomarkers in the biological sample. In some embodiments, the one or more isolated biomarkers is selected from Table 2. In some embodiments, the kit further comprises one or more control reference samples and reagents for performing an immunoassay. In some embodiments, the kit further comprises a package insert (e.g., a link or QR code to a website with instructions or downloadable software with instructions) containing written instructions for methods for separating a pregnancy that delivers X or more days before the Estimated due date (EDD) or Y or more days after the EDD, from a pregnancy that delivers within Z days of the EDD. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 days, and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days.

[00268] The kit can comprise one or more containers for compositions or reagents contained in the kit. Compositions can be in liquid form or can be lyophilized. Suitable containers for the compositions include, for example, bottles, vials, syringes, and test tubes. Containers can be formed from a variety of materials, including glass or plastic. The kit can also comprise a package insert (e.g., a link or QR code to a website with instructions or downloadable software with instructions) containing written instructions for methods for separating a pregnancy that delivers X or more days before the EDD or Y or more days after the EDD, relative to a pregnancy that delivers within Z days of the EDD; where X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days; Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days; and Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In further embodiments, X is no more than 1, 2, 3, 4, 5, 6, or 7 days. In some embodiments, Y is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Y is no more than 1, 2, 3, or 4 days. In some embodiments, Z is no more than 1, 2, 3, 4, 5, 6, or 7 days. In further embodiments, Z is no more than 1, 2, 3, or 4 days. In some embodiments, the kit comprises one or more agents for the detection of one or more isolated biomarkers herein. In some embodiments, the one or more isolated biomarkers are selected from Table 2. In other embodiments, the kit comprises one or more agents for the detection of a pair (or two or more pairs) of biomarkers, wherein the pair of biomarkers comprises ADA12 and a biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises an upregulated biomarker and a downregulated biomarker. Examples of such upregulated and downregulated biomarkers that can be used herein include, but are not limited to, those shown in Table 16. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two upregulated biomarkers. In some embodiments, each pair of isolated biomarkers (or two or more pairs) comprises two downregulated biomarkers. In some embodiments, at least one of SOM2, CSH, CGB1, SVEP1, NCHL1, LYAM1, ADA12, ENPP2, APOC3, and PSG1 are not used or included. In some embodiments, at least one of SOM2, CSH, CGB1, and SVEP1 are not used or included. In further embodiments, the pair of biomarkers comprises ADA12 and KIT. In other embodiments, the pair of isolated biomarkers comprises ADA12 and FETUA. In some embodiments, the pair of isolated biomarkers comprises ADA12 and ENPP2. In some embodiments, the pair of isolated biomarkers comprises ADA12 and A2GL. In some embodiments, the pair of isolated biomarkers comprises ADA12 and IGF1. In some embodiments, the pair of isolated biomarkers comprise two isolated biomarkers selected from Table 2.

[00269] The following examples are provided by way of illustration, not limitation.

EXAMPLES

[00270] Example 1

[00271] Introduction

[00272] This Example reports a study using clinical information and blood samples from the PAPR trial (NCT01371019), which enrolled pregnant women with blood draws from weeks 17 to 28 of gestation. Significant clinical information and blood protein levels were collected on these subjects and their blood samples, including gestational age dating information (e.g., clinical EDD, PDD, ADD), complications (e.g., preterm birth), and levels of proteins correlated to the length of gestation.

[00273] This Example describes a method of determing the PDD using molecular biomarkers and in some aspects in addition to clinical variables, regardless of route (vaginal or induction) for term (> 37 weeks) deliveries. Current clinical guideline methodologies utilize the LMP, sometimes in combination with ultrasound dating, along with a population estimate of 280 days of gestation, to provide pregnant women with a clinical EDD.

[00274] However, the EDD, when determined in this way, has been demonstrated to be both inaccurate and imprecise for the purpose of estimating the ADD, especially as the use of induction has increased and also simply due to the variation in length of pregnancies across the population. A PDD as determined according to this Example is an estimate of the ADD based on a pregnant woman’s own clinical variables and molecular biomarkers. This revised PDD can be used to provide clinical management of pregnancies or alter the gestational dating of the fetus, but can also be used to provide the mother with a more accurate PDD for personal pregnancy planning purposes. These purposes may include planning maternity leave, scheduling visits from family, planning childcare, etc.

[00275] Objective

[00276] There are six predictors (see Table 6) used for determining a PDD. The predictors are designed to determine the PDD and the TTB which is the time from the blood draw to the delivery date. Combining the blood draw date with the predicted TTB, PDD can be calculated.

I l l [00277] Methods

[00278] The performance of the PDD as determined according to this Example is assessed by how accurate it is relative to the clinical EDD that the mother has been provided based on LMP, US, etc. The primary measurement of performance is how frequently the PDD date is closer to the ADD than the clinical EDD.

[00279] The clinical validation confirmed that there is a significant correlation between the predicted TTB (pTTB) and the actual TTB (aTTB). Table 4 lists the transformations from predicted TTB (pTTB) to PDD, and Table 5 lists the additional metrics which are calculated to further evaluate the performance of the predictor.

[00280] Discovery work was done on a GABD range spanning 161 days (23^0/7 weeks) to 202 days (28^6/7 weeks) within which there were 675 samples in the validation dataset. This was the GABD range for validation prescribed for this Example. This Example also computed validation metrics for the full available GABD range which includes 807 additional samples from 18^0/7 weeks - 22^6/7 weeks, bringing the total validation dataset to 1,482 samples from 18^0/7 weeks - 28^6/7 weeks. Additional analysis included computing the significance of model accuracy (z.e., is the mean significantly different from zero) and comparisons of model accuracy in the full, early, and original GABD windows (z.e., is the accuracy significantly different between GABD ranges).

Table 4: Transformation from pTTB to PDD.

Table 5: Additional performance metrics described in the validation plan.

[00281] Summaries of the six predictors are provided in Table 6.

Table 6: Six predictors used for validation.

[00282] Results

[00283] Tables 7 through 10 summarize the results of metrics described in Table 5. They include results for the original window, full window, early window.

Table 7: Correlations and significance.

Table 8: Accuracy measures

(mean difference between PDD and ADD, clinical EDD and ADD, and PDD and clinical EDD).

Table 9: Goodness of predictions.

Table 10: Surprise deliveries.

[00284] The significance of the model error was computed and is shown in Table 11. Note that a significant result implies that there is significant error. Insignificant results, marked with asterisks, imply that the model error is not significant and is the desired result. A double asterisk indicates that it was significant for some but not all GABD partitions.

Table 11 : p-values for the significance of PDD - ADD = 0.

[00285] The model error was compared between all combinations of early, original, and full GABD range to determine if there was a significant difference in performance between different GABD windows. The results of that analysis are shown in Table 12.

Table 12: p-values for model performance in GABD range pairs. Results show no significant difference in model performance in different GABD ranges.

[00286] Plots

[00287] Scatterplots and histograms for TTB values, and various due date definitions for the original GABD range (161-202 days) are shown in FIGs. 1-6.

[00288] Conclusion and Discussion

[00289] Passing the hypotheses in validation required a significant correlation between actual TTB and predicted TTB with a p-value < 0.05. As shown in Table 7 and represented graphically in FIGs. 1-6, all models achieved significance with a p-value < 0.001 and correlation coefficient > 0.82 in the original GABD range. Further, the PDD is closer to ADD than clinical EDD on average as shown in Table 8 and represented graphically in FIGs. 1-6 for all models. For the surprise births, on average, PDD is 5-6 days less than the clinical EDD (Table 10).

[00290] In addition, the model performance was computed in the original, early, and full GABD ranges described in Methods. Results showed no significant difference in performance between GABD ranges. Model statistics in Tables 7 through 10 were similar for all models between GABD ranges. Models 4 and 5 showed no statistical difference from zero in PDD - ADD error, whereas models 1, 2, 3, and 6 were significantly different for at least one GABD range, though the difference was small per Table 8.

[00291] In summary, all models passed the validation criteria and provided a PDD that was more accurate than the clinical EDD. The models do not have significantly different performance in the full (18^0/7 weeks - 28^6/7 weeks) GABD range, implying that they are valid for use in the full range with comparable performance.

[00292] Example 2

[00293] The studies demonstrated in this Example investigate the various assays (e.g., ELISA, MS, etc.) and sample types (e.g., dried whole blood, dried plasma, dried serum, etc.) that may be used to determine the PDD and/or TTB of a pregnant female in accordance with any of the methods disclosed herein. Each of the products described herein (also referred to herein as “TTB products”) used two protein biomarkers, or analytes, in a ratio. Any such studies conducted on these biomarkers or biomarker combinations may be applied to any of the biomarkers/biomarker pairs disclosed herein, such as those listed in Table 2 and Table 3.

[00294] The studies herein also demonstrate the potential of an automated immunoassay method for the biomarkers disclosed herein.

[00295] Correlation Between ELISA and MS

[00296] The first study was conducted to determine whether there was any correlation between the ELISA and MS assays on the biomarkers. Specifically, liquid serum samples of a TTB product and dried serum samples of the same TTB product were analyzed by both ELISA and MS. As set forth in Example 1, for instance, liquid samples of the biomarkers disclosed herein have been clinically validated. However, the studies herein investigate whether dried samples of the same biomarkers and products may be assayed by, for instance, ELISAs.

[00297] Methods

[00298] Paired serum samples from pregnant females were collected by venipuncture, and either frozen or Mitra® dipped for dried storage. Frozen serum samples, in particular, were thawed and diluted in a tris-buffered saline buffer (TBST). Mitra® tips were placed in TBST- filled filter plates and eluted for 1 hour at 4°C. Samples were incubated overnight at 4°C and assayed for the TTB biomarkers ADA12 and KIT. Each ELISA kit was proceesed as recommended by the kit manufacturer. Using the calibration curves, quantitative values for ADA12/KIT were determined. The ratio of these values was then used to correlate with MS ratios.

[00299] Serum samples of the TTB product were also prepred and assayed from a dried state in a similar manner. Specifically, the serum sample was dried on a Mitra® tip, which was then assayed via ELISA and MS. In particular, serum samples from pregnant females were collected by venipuncture, and Mitra® dipped for dried storage and assayed for both ADA12 and KIT. Mitra® tips were placed in TBST-filled filter plates and eluted for 1 hours at 4°C. Samples were incubated overnight at 4°C and assayed for the TTB biomarkers ADA12 and KIT. Each ELISA kit was processed as recommended by the kit manufacturer. Using the calibration curves, quantitative values for ADA12/KIT were determined. The ratio of these values was then used to correlate with MS ratios.

[00300] Results

[00301] The biomarker ratios by ELISA were derived from absolute protein measures using calibration curves, while biomarker ratios by MS were derived from relative MS transition response ratios (RRs). Thus, analysis of such ratios is not expected to fall on the same scale. Nevertheless, analysis of the liquid serum sample showed correlation of the product ratio between the ELISA and MS assays, as depicted in FIG. 7, with an R² value of 0.8021. Likewise, analysis of the serum sample dried on a Mitra® device showed strong correlation between the ELISA and MS assays, as depicted in FIG. 8, with an R² value of 0.9724. The results herein indicate a correlation between the ELISA and MS assays, and in particular, a strong correlation between the ELISA and MS assays of the dried serum samples.

[00302] Correlation between Whole Blood and Frozen Serum by MS

[00303] The next study investigated whether there was any correlation between capillary whole blood and frozen serum, as well as and venous whole blood and frozen serum, as assayed by affinity-capture mass spectrometry (AC -MS).

[00304] Methods

[00305] The TTB product comprising serum and whole blood samples from pregnant females was collected by venipuncture and Mitra® dipped for dried storage, and assayed for both ADA12 and KIT. In particular, the TTB product was validated using frozen serum that was depleted of abundant proteins using a MARS 14 (multi-affinity removal column, human- 14) immunoaffinity depletion column, and was analyzed by multiple reaction monitoring MS (MRM-MS). MS to MS correlation between the frozen serum and whole blood was shown by comparing the standard depletion-based workflow for the serum and an affinity capture MS protocol for the whole blood.

[00306] Results

[00307] FIG. 9 shows the correlation between frozen serum (assayed via depletion-MS) and capillary whole blood (assayed via AC -MS), with an R² value of 0.89. FIG. 10 likewise demonstrates correlation between frozen serum (assayed via depletion-MS) and venous whole blood (asayed via AC -MS), with an R² value of 0.92.

[00308] Correlation between Dried Whole Blood assayed via ELISA and Dry Whole Blood assayed via AC -MS

[00309] A study was also conducted to investigate whether a correlation exists between ELISA and MS assays of dried venous whole blood samples. Specifically, paired serum and whole blood samples from pregnant females were collected by venipuncture, and either frozen or Mitra® dipped for dried storage. Frozen serum samples were thawed and diluted in TBST. Mitra® tips were placed in TBST-filled filter plates and eluted for 1 hour at 4°C. Samples were incubated over night at 4°C and assayed for the TTB biomarkers ADA12 and KIT. Each ELISA kit was processed as recommended by the kit manufacturer. Using the calibration curves, quantitative values for ADA12/KIT were determined. The ratio of these values was then used to correlate with MS ratios. The MS measurements were generated by an affinity capture MS protocol.

[00310] Results

[00311] A correlation was identified between dried venous whole blood samples assayed via ELISA and dried venous whole blood samples assayed via MS. Specifically, these ELISA- derived and MS-derived protein ratios demonstrated a correlation in dry venous whole blood, as depicted in FIG. 11, with an R² value of 0.981.

[00312] ELISA Correlation Between Serum, Plasma, and Whole Blood

[00313] Further studies were conducted herein to determine whether there was a correlation between serum, plasma, and whole blood assayed by ELISA. In particular, serum, plasma, and whole blood samples of the TTB product comprising ADA12 and KIT were dried on a Mitra® tip. Specifically, paired serum and whole blood samples from pregnant females were collected by venipuncture, and either frozen or Mitra® dipped for dried storage. Frozen serum samples were thawed and diluted in TBST. Mitra® tips were placed in TBST-filled filter plates and eluted for 1 hour at 4°C. Samples were incubated overnight at 4°C and assayed for the TTB biomarkers ADA12 and KIT. Each ELISA kit was processed as recommended by the kit manufacturer. Using the calibration curves, quantitative values for ADA12/KIT were determined. The ratio of these values was then used to correlate with MS ratios.

[00314] Results

[00315] The ratios from the ELISA demonstrated a correlation between the dried whole blood and dried serum samples, as well as the dried whole blood and dried plasma samples. FIG. 12, for instance, shows the correlation between these ELISA-assayed dried serum and dried whole blood samples, where there was an R² value of 0.8516. FIG. 13 in particular shows a strong correlation between the ELISA-assayed dried plasma and dried whole blood samples, where there was an R² value of 0.9933. Thus, the ELISA analyses on these dried samples demonstrated correlation between serum, plasma, and whole blood samples.

[00316] Stability of Analytes in Product

[00317] The stability of the analytes in the TTB products was also studied.

[00318] Methods

[00319] Pooled pregnant serum samples (PPS) were thawed on ice at the appropriate time. Mitra® tips were dipped into each samples for the indicated conditions. Samples requiring incubation were dried at room temperature for 2 hours before being placed in an incubator at 30°C or 50°C. The samples were incubated at 50°C for 6 hours, then removed and placed at either room temperature or 30°C for the remaining 48 hours. Mitra® tips were placed in TBST- filled filter plates and eluted for 1 hour at 4°C. Samples were incubated overnight at 4°C and assayed for the TTB biomarkers ADA12 and KIT. Each ELISA kit was processed as recommended by the kit manufacturer. Using the calibration curves, quantitative values for ADA12/KIT were determined. The ratio of these values was then used for correlation analysis. [00320] Results

[00321] As noted previously, serum ADA12 samples, for instance, have previously been shown to be unstable under many routine laboratory conditions, with stability times of around

15 hours or less at 30°C, around 20 hours or less at room temperature, and around 51 hours at refrigerator temperature (see, e.g., Crowans et al. (2010) Prenatal Diagnosis, 30(6): 555-560). However, it was found herein that the TTB product ratio assayed via ELISA from a serum sample dried on a Mitra® tip was stable for 48 hours at 50°C. FIG. 14, for instance, shows the ELISA-assayed TTB product ratios at different temperatures and time points, with each data point representing a single subject serum sample. Incubations were 48 hours in duration in some cases, as indicated with a shorter temperature stress. It is believed that the other sample types for the biomarkers described herein, such as dried whole blood samples, exhibit the same or similar stability due to the correlations identified between the immunoassays and analyte sample types described above.

[00322] Automation Development of ADA12 Analyte

[00323] Following the above studies, a Mitra®/serum -based immunoassay method compatible and streamlined for automation was developed, in which the method utilized room temperature incubations only, universal buffers for all steps, and identical dilutions for each analyte to minimize steps, as detailed above.

[00324] Results

[00325] The manual ELISA immunoassay for ADA12, or “bench” ELISA, was found to correlate with the automated version described above across 32 subject samples. In particular, FIG. 15 shows the correlation between such an automated ELISA immunoassay and a manual immunoassay for an ADA12 liquid serum sample, where there was an R² value of 0.9582. FIG.

16 shows the correlation between the automated ELISA immunoassay and an MS assay for an ADA12 liquid serum sample, where there was an R² value of 0.8475.

[00326] Conclusion and Discussion

[00327] The studies and observations described herein demonstrate the various assays and sample types that may be used to determine the PDD and/or TTB of a pregnant female in accordance with any of the methods disclosed herein. Moreover, these studies demonstrate evidence of the potential of automated immunoassays for the biomarkers disclosed herein. In particular, a Mi tra®/serum -based immunoassay method was developed and streamlined for automation utilizing only room temperature incubations, universal buffers for all steps, and identical dilutions for each analyte. Although the automated immunoassay described above utilized a liquid serum sample, the other results described herein demonstrate that such automated immunoassays can also utilize any of the biomarkers and samples described herein, such as dried whole blood, dried serum, or dried plasma.

[00328] Of note, it was found that systems, methods and fixating agents (e.g., absorbent filter paper) that do not use or have anti-coagulant metal chelators, such as ethylenediaminetetraacetic acid (EDTA) or citrate, should be used to detect, capture and/or store samples, at least because ADA12 detection, for instance, is believed to be negatively impacted by the presence of such compounds. For instance, two common sample collection methods that do not employ the use of EDTA are serum processing followed by Mitra® tip collection, and capillary whole blood collection on DBS cards. The data collected from the studies herein suggest that the results of these two methods correlate well with each other and MS. FIG. 17, for instance, displays a graph showing ADA12 signal from various samples collected without the use of EDTA, including finger prick samples collected on DBS cards, venipuncture serum samples dried on a Mitra® tip, venipuncture blood samples collected on DBS cards, and venipuncture blood samples dried on a Mitra® tip. The ADA12 signal from samples collected without the use of EDTA are approximately 10-fold higher than the signal from samples that utilize EDTA. Additionally, FIG. 18 displays a graph showing ADA12 signal correlation between a venipuncture serum sample dried on a Mitra® tip, and a finger prick dried blood spot sample, both samples of which are without the use of EDTA. The graph demonstrates an R² value of 0.7020. Similarly, FIG. 19 displays a graph showing the ADA12/KIT ratios from samples collected without the use of EDTA. The samples collected include a serum sample collected from a venous puncture, and a sample collected from a finger prick dried blood spot. The graph demonstrates an R² value of 0.9787. Moreover, without being bound by theory, heparin is contemplated to be acceptable as an anti -coagulant due to its significantly different mechanism for anti-coagulation.

[00329] Example 3

[00330] Introduction

[00331] This study investigates the hypothesis that exemplary biomarkers and proteins herein, or clock proteins, have statistical associations with the time to birth (TTB) and can have the capability to serve as clinical predictors of term delivery date. [00332] Materials and Methods

[00333] Reagents: Trypsin was purchased from Promega (#V5280), custom stable isotope standards were purchased from Biosynth, and human 14 multiple affinity removal columns (MARS-14) were purchased from Agilent (#5190-7995).

[00334] Study Design and Participants

[00335] 2 ,648 banked serum samples were collected for an institutional review board- approved 10-site study in the United States (NCT01371019) that aimed to characterize proteome differences in women with asymptomatic singleton pregnancies who deliver at term versus those who experience spontaneous preterm birth (see, e.g., Saade, G.R., et al., Development and validation of a spontaneous preterm delivery predictor in asymptomatic women. Am J Obstet Gynecol, 2016. 214(5): p. 633 el-633 e24). Prior to sample collection, enrolled individuals provided written informed consent to participate in the study and for their samples to be used in future studies, including the study herein. The samples used in the current study included term births only and were collected at a single time point from each participant from 18 through 28 weeks of gestation. Table 13 below shows the inclusion and exclusion criteria for the individuals selected for the study.

[00336] Table 13. Study inclusion and exclusion criteria.

[00337] Protomic Analysis

[00338] Maternal serum samples were analyzed in a Clinical Laboratory Improvement Amendments (CLIA)-certified and College of American Pathologist (CAP)-accredited laboratory according to a prespecified laboratory analysis plan and standard operating protocols (see, c.g, Badsha, M.B., E.A. Martin, and A.Q. Fu, MRPC: An R Package for Inference of Causal Graphs. Front Genet, 2021. 12: p. 651812; and Chellakooty, M., et al., A longitudinal study of intrauterine growth and the placental growth hormone (GH) -insulin-like growth factor I axis in maternal circulation: association between placental GH and fetal growth. J Clin Endocrinol Metab, 2004. 89(1): p. 384-91). Briefly, serum samples were randomized and allocated into batches that contained both study samples and quality controls. After thawing samples on ice, high-abundance proteins were depleted on MARS-14 columns. Depleted samples were reduced, alkylated, and digested with trypsin. They were then spiked with SIS peptides corresponding to each measured endogenous peptide, desalted, and anlyzed by coupled liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM- MS). The MRM assay measured 150 peptides from 110 proteins that were either: 1) of placental origin, 2) maternal serum proteins with roles in pregnancy, or 3) used as quality controls. Peptides were quantified as the peak area of the endogenous peptide divided by the peak area of its corresponding SIS peptide counterpart, generating a response ratio (RR).

[00339] Statistical Analyses

[00340] A Wilcoxon test was performed on all subjects in the cohort to identify proteotypic peptides that changed significantly between 18-20 weeks and 26-28 weeks gestation. Results were visualized using a Volcano plot. Significant difference was defined as P < 0.05 and a minimum 10% change (log2Fc=0.25) in relative abundance. A subset of these proteins was smoothed using a generalized additive model and plotted relative to gestational age at blood draw. Confidence intervals (CI) were included to show 95% overall population values across GABD for each model. Separately, a protein association study was performed using Mendelian randomization (MR), a statistical approach to identifying causal genes that has also been applied to proteomic data (see, e.g., Smith, G.D. and S. Ebrahim, 'Mendelian randomization' : can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol, 2003. 32(1): p. 1-22.). An MR-based machine learning algorithm (MRPC) with 50 iterations of bootstrapping was applied to identify proteins having an association with TTB among individuals delivering at term. Lastly, gestational age at birth (GAB) was compared in participants having the highest (90^th percentile) and lowest (10^th percentile) amounts of the placental protein ADA12. This analysis was limited to term pregnancies with vaginal deliveries (n=l,839). C-section deliveries were eliminated because those are often scheduled prior to the natural onset of labor. It is unclear how many of the vaginal deliveries in the analysis were scheduled inductions, as induction data was only captured for preterm deliveries. Prior to comparing the GAB distributions, the levels of ADA12 were normalized for GABD by regressing ADA12 levels against GABD and then removing any trend. The significance of the GAB mean difference was assessed using the Welch two sample t-test. All analyses and visualizations were performed using the statistical program R, version 4.4.2 (see, e.g., Team, R.C., R: A language and envrionment for statistical computing (version 4.4.2). R Foundation for Statistical Computing, Vienna, Austria, 2024).

[00341] Results

[00342] Patient Characteristics [00343] As set forth above, 2,648 banked serum samples from term pregnancies were selected for this study based on inclusion and exclusion criteria for NCT01371019 (see Table 13). The demographics of the study population are shown below in Table 14.

[00344] Table 14. Demographics of study participants.

[00345] The population was characterized by diverse clinical and demographic characteristics, as well as pregnancy histories. While only term pregnancies were analyzed, the diverse population and the presence of pregnancy complications, including gestational diabetes, pre-eclampsia (PE), and pregnancy-induced hypertension (PUT), support the generalizability of these study results.

[00346] Clock Protein Expression

[00347] To identify proteins and biomarkers with levels that change during pregnancy, maternal serum protein expression at 18-20 weeks’ gestation was compared to that at 26-28 weeks’ gestation. Changes were considered significant if protein levels satisfied both a minimum change of log2FC=0.25 and achieved a -value < 0.05. FIGS. 20A-20B show such changes in protein expression between 18-20 weeks gestation and 26-28 weeks gestation. Specifically, FIG. 20A shows a Volcano plot showing significantly upregulated (proteins to the right of the dashed section) and downregulated (proteins to the left of the dashed section) proteins. Significance is represented on the y-axis as the -logio P-value, while the magnitude of change is shown on the x-axis as the log2 fold-change. When a protein is depicted more than once (denoted by _1 and _2), it was measured using two distinct peptides. FIG. 20B depicts smoothing plots for representative proteins PAEP, KIT, CNTN1, FGFR1, ADA12 and PSG1, showing expression changes that were significantly upregulated, downregulated, or demonstrated no significant change. The 95% CI expression (response ratio; “RR”) and GABD is represented by the width of the gray-shaded area.

[00348] Thus, several growth factors, glycoproteins, adhesion proteins, and immune regulators known to play a role in fetal growth and development demonstrated significant changes in expression (FIG. 20A) that largely agree with reported findings. Both linear and non-linear expression changes were seen among samples taken between 18-20 weeks’ and 26- 28 weeks’ gestation. Representative changes are shown in FIG. 20B, and a full listing of proteins shown in FIG. 20A is provided in Table 15 below.

[00349] Table 15 Proteins identified as regulated, or directly or indirectly associated with TTB.

[00350] Statistical Directional Relationship between Proteins and TTB

[00351] The TTB is defined in this Example 3 as TTB = (GAB - GABD), where GAB is gestational age at birth and GABD is gestational age at blood draw. To characterize associations between the proteins analyzed and TTB, a Mendelian Randomization machine learning algorithm (MRPC) was applied to the full protein dataset. Of the proteins analyzed, 15 were shown to have a direct association with TTB, as shown in FIG. 21. Specifically, FIG. 21 shows results of such an MRPC analysis, depicting statistical directional relationships between the proteins therein and TTB. Single direction arrowheads indicate statistically causal relationships where the protein or outcome being touched by the arrowhead is statistically dependent on the protein being touched by the blunt end of the arrow. Bidirectional arrows indicate indeterminant statistical causality. When a protein is depicted more than once (denoted by _1 and _2), it was measured on two distinct peptides. Thus, as shown in FIG. 21, 15 parent proteins were identified to be directly causal to the TTB, and appear to serve as signaling “hubs”. A majority of these proteins are placentally expressed.

[00352] Among the proteins analyzed were growth hormones, adhesion molecules, glycoproteins, enzymes, and lipid-binding proteins that are involved in proliferation, migration, adhesion, fetal and placental growth, immune modulation during pregnancy, pattern recognition, and lipid metabolism (as shown in, e.g., Table 16 below).

Table 16. Summary of proteins shown to have a direct association with TTB. NS = not significant.

[00353] Of these proteins, growth hormone 2 (SOM2), chorionic somatomammotropin (CSH), chorionic gonadotropin subunit pi (CGB1), and sushi, von Willebrand Factor type A, EGF, and pentraxin domain-containing protein (SVEP1), are known markers of gestational age (see, e.g., Aghaeepour, N., et al., A proteomic clock of human pregnancy. Am J Obstet Gynecol, 2018. 218(3): p. 347 el-347 el4). Several others, including cell adhesion molecule LI (NCHL1), lymphocyte adhesion molecule 1 (LYAM1, z.e., L-selectin), a disintegrin and metalloproteinase 12 (ADA12), ectonucleotide pyrophosphatase/phosphodiesterase 2 (ENPP2, z.e., autotaxin), apolipoprotein C-III (APOC3), and pregnancy-specific pi glycoprotein 1 (PSG1), have been proposed as markers of certain fetal abnormalities and/or pregnancy complications, but have not been linked to TTB. The remaining proteins have been been previously associated with either pregnancy complications or TTB. However, PGRP2 is notably not placentally expressed and plays no known role in pregnancy. Thus, overall, these results identify both known and novel biomarkers that can have practical applications in predicting the probability of delivery by week in the term period.

[00354] Biological Association of Biomarkers with TTB

[00355] Next, it was sought to visualize the impact of biomarker levels on the distribution of births. To this end, a proof-of-concept analysis based on expression of ADA12 was performed. ADA12 was chosen because it had one of the largest fold changes of any protein analyzed in this study (as shown in FIG. 20A), and a linear association with GABD, with tight confidence intervals (as shown in FIG. 20B). The GAB distributions of women with the highest ADA12 levels (90^th percentile) and lowest ADA12 levels (10^th percentile) was compared after normalizing for GABD in order to determine if there was a difference in delivery dates. Results are shown in FIG. 22.

[00356] Specifically, FIG. 22 shows 3 bar graphs depicting the association between GAB and ADA12 expression in 3 different groups. The top graph shows the distribution of GAB in mothers who expressed the lowest levels of ADA12 (10^th percentile). The middle graph shows the distribution of GAB in mothers who expressed the highest levels of ADA12 (90^th percentile). The combined number of births in both groups (bottom graph), shows how many more births from each group occurred in each week relative to the other. The dashed lines indicate the mean GABs for each group: black = 90^th percentile, white = 10^th percentile.

[00357] Subjects in the bottom decile of ADA12 levels had a right-skewed GAB distribution (FIG. 22, top panel), while those in the top decile were left-skewed (FIG. 22, middle panels). This skew was further demonstrated by significantly different mean GABs between the two groups. In the 10^th percentile, the mean GAB was 39^3/7 weeks whereas the mean GAB in the 90^th percentile was 39^0/7 weeks, P < 0.001 (FIG. 22, bottom graph).

[00358] Altogether, this suggests that ADA12, and potentially other clock proteins, could aid in the prediction of TTB in term pregnancies.

[00359] Conclusion and Discussion

[00360] In this cross-sectional study, proteins that demonstrated significant changes in expression between two gestational age windows, separated by only five weeks, were analyzed (FIGS. 20A-20B). Using MRPC analysis, 15 proteins that had a direct association to the TTB were identified, 11 of which have not been previously linked to gestational age (FIG. 21). The potential clinical utility of ADA12 as a term delivery date predictor was investigated by comparing the mean and distribution of GAB between the cohort’s highest (90th percentile) and lowest (10th percentile) expressors of ADA12 at blood draw. Results showed the mean GAB to be significantly earlier in the highest ADA12 expressors compared to the lowest expressors (FIG. 22). Thus, ADA12 was one of several proteins shown to have an association with TTB. Mothers who expressed the highest levels of ADA12 (90^th percentile) gave birth earlier than mothers who expressed the lowest levels of ADA12 (10^th percentile) at a statistically significant rate (median gestational age at birth 39^0/7 weeks vs. 39^3/7 weeks, P < 0.001). [00361] The findings on ADA12 suggest that pregnancies characterized by high levels of this protein are farther advanced (shorter TTB) than those with low levels. A pregnancy that is more advanced based on high ADA12 levels and short TTB could reflect more rapid fetal development compared to pregnancies characterized by low ADA12 levels and longer TTB. Alternatively, biomarker differences and their ability to indicate the actual TTB of pregnancy, could be a reflection of pregnancy misdating due to inaccurate recollection of when the last menstrual period occurred, limitations in fetal ultrasound measures, or lack of these measures entirely (see, e.g., Wegienka, G. and D.D. Baird, A comparison of recalled date of last menstrual period with prospectively recorded dates. J Womens Health (Larchmt), 2005. 14(3): p. 248-52; and Barr, W.B. and C.C. Pecci, Last menstrual period versus ultrasound for pregnancy dating. Int J Gynaecol Obstet, 2004. 87(1): p. 38-9). Regardless, based on its functional roles in pregnancy and association between its expression levels and various pregnancy complications, ADA12 can serve as an accurate predictor of term delivery date. These observations suggest that ADA12 expression is carefully regulated in normal pregnancies and that deviation from normal levels at certain points during gestation may reflect aberrant fetal development and pregnancy complications. The direct association that was found between ADA12 and TTB in the study herein, and the difference in the mean GAB between the highest and lowest ADA12 expressors in the reported study cohort, supports a role for this protein as a delivery date predictor in term pregnancies.

[00362] Furthermore, in agreement with previous studies, the findings herein showed a direct association between TTB and CSH, SOM2, CGB1, and SVEP1. Each of these proteins is placentally derived, and placental-fetal signaling plays a crucial role in the pregnancy clock and triggering of parturition. As described herein, the pregnancy clock refers to a biological phenomenon in which harmonized and chronologic signals from the fetus, fetal membrane, placenta, decidua, and myometrium modulate the length of gestation (see, e.g., Menon, R., et al., Novel concepts on pregnancy clocks and alarms: redundancy and synergy in human parturition. Hum Reprod Update, 2016. 22(5): p. 535-60; McLean, M., et al., A placental clock controlling the length of human pregnancy. Nat Med, 1995. 1(5): p. 460-3; Norwitz, E.R., et al., Molecular Regulation of Parturition: The Role of the Decidual Clock. Cold Spring Harb Perspect Med, 2015. 5(11); and Peterson, L.S., et al., Multiomic immune clockworks of pregnancy. Semin Immunopathol, 2020. 42(4): p. 397-412.) In other words, the pregnancy clock is understood to be a series of chronologic and harmonized signals among the mother, fetus, and placenta that regulate the length of gestation. It includes various biomarkers that comprise an immune clock, a proteomic clock, and temporal changes to the transcriptome and metabolome that correlate to gestational age based on ultrasound.

[00363] Additionally, many of the other proteins shown here to have a direct association with TTB have placental expression, including pregnancy-specific pi glycoprotein 1 (PSG1). In the study herein, PSG1 expression increased during the 8-10-week timeframe studied, but not to statistical significance. Since the smoothing plot shows a linear association with GABD and small confidence intervals, this was likely due to the gestational timeframe for blood draw being too narrow to reach significance. Other PSG proteins measured in the study herein had similar linear associations with GABD. Interestingly, the transcript for PSG7 was included in the 8-cfRNA model described herein.

[00364] Another placental protein identified herein, PAEP, helps modulate the immune system in pregnancy. For instance, during the second trimester of pregnancy, a tightly upregulated suppression of the immune system occurs to prevent the mother’s immune system from rejecting the fetus. PAEP has been shown to facilitate the natural immune shift towards a Th2 immune response by, e.g., mediating apoptosis of NK cells, as set forth above. Thus, PAEP and other proteins involved in such an immune system shift can also serve as a type of signaling molecule to indicate the progress of gestation.

[00365] The study herein also suggests that NCHL1 -mediated activity can serve as a clock signal that influences TTB. Moreover, the association between LYAM1 and TTB reported in this study aligns with its role as a mediator of implantation and protector of fetal placement during pregnancy.

[00366] Among others, one protein identified in the study herein, PGRP2, has not been associated with normal pregnancy processes, pregnancy complications, or gestational age. PGRP2, as set forth above, is a pattern recognition molecule, expressed mainly in gut epithelial cells, that recognizes and hydrolyzes bacterial peptideoglycan (PGN). Thus, the findings herein also suggest a novel role for this protein as an indicator of pregnancy timing.

[00367] Altogether, the findings herein demonstrate statistical associations between certain proteins and TTB. The work herein represents an important first step towards characterizing the relationship between clock protein behavior and the duration of pregnancy and determining their clinical utility as predictors of derlivery date in term pregnancies.

[00368] Example 4

[00369] The study herein investigates additional biomarkers and peptides that correlate with GABD.

[00370] Methods [00371] Serum was collected from a cross-sectional cohort of 42 subjects at gestational ages 60-267 days at the time of collection. Serum from each subject was depleted of the most abundant serum proteins (MARS-14, Agilent Technologies), digested with trypsin (Trypsin Gold, Promega), and analyzed by liquid chromatography (LC)-multiple reaction monitoring (MRM)-mass spectrometry(MS) using proprietary assays measuring a total of 273 peptides from 117 proteins, and their corresponding heavy-labeled stable isotope standards (SIS). Proteins in the assay were of placental origin or maternally circulating proteins linked to pregnancy or pregnancy complications, or were included for quality control purposes. Relative quantification was reported as the peak area measured for the endogenous peptide, divided by the peak area of the SIS peptide, generating a response ratio (RR).

[00372] Criteria used to prioritize candidate biomarkers for predicting time to birth from a single blood draw collection were:

Linear Association with gestation; and

Tight confidence intervals (z.e., smaller variation across individuals)

[00373] Results

[00374] To identify candidate univariate biomarkers from this cohort, a Pearson correlation (“SpearmanR”) was calculated for each peptide RR vs. GABD. Top candidates included herein (as shown in Table 17) had a Pearson r > 0.5, with a significant p-value. Examples of 6 candidates are shown in FIGS. 23A-23F.

[00375] Table 17 List of biomarkers and peptides shown to have a linear correlation with

GABD.

[00376] Specifically, FIGS. 23A-23F show examples of 6 candidates, i.e., the biomarkers and their corresponding peptides (denoted as “biomarker_peptide”) that demonstrated linear correlations with GABD: (A) ADA12 FGFGGSTDSGPIR (SEQ ID NO: 1); (B) GRN EVVSAQPATFLAR (SEQ ID NO: 83); (C) SEM7A ATIVHQDQAYDDK (SEQ ID NO: 78); (D) SPIT1 YTSGFDELQR (SEQ ID NO: 86); (E) LYPD3 GCGSGLPGK (SEQ ID NO: 74); and (F) CSH ISLLLIESWLEPVR (SEQ ID NO: 18).

[00377] The study herein identifies exemplary biomarker and peptide candidates that have been demonstrated to have a linear correlation with GABD, which can thus be utilized to predict, e.g., the TTB of a pregnant female in accordance with the methods, uses, kits, and compositions described herein.

[00378] Example 5

[00379] Introduction

[00380] This Example demonstrates the generation of an exemplary “test report” or “model” that can be used to estimate the probability of a pregnant subject delivering in each week from weeks 37 to 41, i.e., term births. Such a test utilizes a combination of clinical, demographic, and/or biomarker factors. The test report is both qualitative (e.g., the most likely week to deliver) and quantitative (e.g., the probability of each week to deliver).

[00381] Methods and Illustrative Results [00382] The test herein consists of a blood test along with demographic and clinical factors that are used to estimate the probability of a mother delivering in each week from weeks 37 to 41. The most likely week of delivery is the one with highest probability. The test is intended to predict term births (z.e., 37 weeks or later).

[00383] The test utilizes the pregnant subject’s (denoted as “S”) cohort. As used herein, the cohort (denoted as “C(S)”) is characterized as women who have similar blood test results, demographics, and clinical factors as the subject, “S”. It is from this cohort (C(S)) that the weekly delivery estimates are derived. It has been demonstrated that probability of delivery in each week for pregnancy cohorts is highly reproducible.

[00384] For clinical and demographic factors, a database from the Centers for Disease Control and Prevention (CDC) is used. Women similar to S in the CDC database, denoted as “CDC(S)”, are defined as those with term deliveries and similarities on the following factors:

1- Age

2. BMI

3. Race

4. Hypertension/preeclampsia in a prior pregnancy

5. Preterm birth in a prior pregnancy

6. C-section delivery in a prior pregnancy

7. Education level

8. First time mother

9. Chronic diabetes

10. Gestational diabetes in the current pregnancy

11. Hypertension or preeclampsia in the current pregnancy

[00385] For non-categorical factors such as age, a window is used, e.g., women whose age is within 2 years of the subject’s age.

[00386] Once CDC(S) is formed, the probability of delivering for each week, 37 to 41, is determined by taking the average across subjects in CDC(S). This produces a probability distribution over these weeks.

[00387] Thus, an exemplary test report, for instance, consists of a probability distribution across birth weeks 37 to 41, where:

Week 41 includes week 41 and 42;

The probability distribution sums to 1; and

The most likely delivery week will be the week with the highest probability. [00388] Such a test report is both qualitative (e.g., most likely week to deliver) and quantitative e.g., probability of each week to deliver).

[00389] To further illustrate, FIG. 24 provides an exemplary bar graph of the birth week probability distribution where the factors above, in order, are: 1. 32 (age), 2. 23.3 (BMI), 3. White (race), 4. No (hypertension/preeclampsia in a prior pregnancy), 5. No (preterm birth in a prior pregnancy), 6. Yes (c-section delivery in a prior pregnancy), 7. High School (education level), 8. No (first time mother), 9. No (chronic diabetes), 10. No (gestational diabetes in the current pregnancy), and 11. No (hypertension or preeclampsia in the current pregnancy).

[00390] Biomarker Factors

[00391] For biomarker factors, the biomarker assay (TTB) results for subject S, denoted as “TTB(S)”, is used. Subjects have three classifications, denoted “T(S)” using the measurement TTB(S):

If TTB(S) < median(TTB) - std(TTB) then T(S) is positive (‘skewed right’).

If TTB(S) > median(TTB) + std(TTB) then T(S) is negative (‘skewed left’). Otherwise, T(S) is neutral (‘no skew’).

[00392] TTB, as used in this Example 5, is the distribution of all assay values over the database used above for clinical and demographic factors in which case CDC(S) is restricted to those women with the same assay result T(S) as subject S. This study illustrates the case where the TTB distribution comes from a different set of subjects such as the PAPR study subjects (NCT01371019).

[00393] Thus, using the PAPR study, restricted to term deliveries, all pregnancies are assigned to one of the three groups: “positive”, “neutral”, and “negative”, as shown in FIG. 25. Specifically, FIG. 25 shows a line graph of the distribution of such “neutral”, “positive”, and “negative” groups and their probability to deliver for each week shown (37 to 42). Neutral represents the average weekly probability whereas the “positive group” is skewed to the right of the “neutral” group, and the “negative” group is skewed to the left. The Wilcoxon Rank- Sum Test demonstrates that there are highly significant shifts (p < 0.001) between positive and non-positive subjects as well as between negative and non-negative subjects.

[00394] In summary, with this classification of pregnancies based on the TTB assay, each subject S is assigned to one of three groups T(S).

[00395] Integrating Clinical, Demographic, and Biomarker Factors

[00396] If the clinical, demographic, and biomarker factors are all derived from the same database of subjects, then there is no need to integrate, as described above. If not, disparate databases (or data from them) can be integrated to derive a delivery week probability distribution that incorporates information from each database using Bayes Theorem.

[00397] The approach is to use the weekly probability distribution from one database as the base distribution (z.e., the prior) and adjust it using the weekly probability distribution from another database.

[00398] Conclusion and Discussion

[00399] In conclusion, the study herein demonstrates the generation of an exemplary “test report” or “model” that can be used to estimate the probability of a pregnant subject delivering in each week from weeks 37 to 41 (z.e., term births) using, e.g., clinical, demographic, and biomarker factors and variables. The test report is both qualitative (e.g., the most likely week to deliver) and quantitative (e.g., the probability of each week to deliver).

EQUIVALENTS AND SCOPE, INCORPORATION BY REFERENCE

[00400] Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific embodiments described herein. It is understood that modifications which do not substantially affect the activity of the various embodiments of this disclosure are also provided within the description of the disclosure provided herein. The scope of the present disclosure is not intended to be limited to the above description, but rather is as set forth in the appended claims.

[00401] In the claims articles such as “a,” “an,” and “the” may mean one or more than one unless indicated to the contrary or otherwise evident from the context. Claims or descriptions that include “or” between one or more members of a group are considered satisfied if one, more than one, or all of the group members are present in, employed in, or otherwise relevant to a given product or process unless indicated to the contrary or otherwise evident from the context. The disclosure includes embodiments in which exactly one member of the group is present in, employed in, or otherwise relevant to a given product or process. The disclosure also includes embodiments in which more than one, or all of the group members, are present in, employed in, or otherwise relevant to a given product or process.

[00402] Furthermore, it is to be understood that the disclosure encompasses all variations, combinations, and permutations in which one or more limitations, elements, clauses, descriptive terms, etc., from one or more of the claims or from relevant portions of the description is introduced into another claim. For example, any claim that is dependent on another claim can be modified to include one or more limitations found in any other claim that is dependent on the same base claim. Furthermore, where the claims recite a composition, it is to be understood that methods of using the composition for any of the purposes disclosed herein are included, and methods of making the composition according to any of the methods of making disclosed herein or other methods known in the art are included, unless otherwise indicated or unless it would be evident to one of ordinary skill in the art that a contradiction or inconsistency would arise.

[00403] Where elements are presented as lists, e.g., in Markush group format, it is to be understood that each subgroup of the elements is also disclosed, and any element(s) can be removed from the group. It should be understood that, in general, where the disclosure, or aspects of the embodiments, is/are referred to as comprising particular elements, features, steps, etc., certain embodiments of the disclosure or aspects of the embodiments consist, or consist essentially of, such elements, features, steps, etc. Thus, for each embodiment of the disclosure that comprises one or more elements, features, steps, etc., the disclosure also provides embodiments that consist or consist essentially of those elements, features, steps, etc.

[00404] Where ranges are given, endpoints are included. Furthermore, it is to be understood that unless otherwise indicated or otherwise evident from the context and/or the understanding of one of ordinary skill in the art, values that are expressed as ranges can assume any specific value within the stated ranges in different embodiments of the disclosure, to the tenth of the unit of the lower limit of the range, unless the context clearly dictates otherwise. It is also to be understood that unless otherwise indicated or otherwise evident from the context and/or the understanding of one of ordinary skill in the art, values expressed as ranges can assume any subrange within the given range, wherein the endpoints of the subrange are expressed to the same degree of accuracy as the tenth of the unit of the lower limit of the range.

[00405] In addition, it is to be understood that any particular embodiment of the present disclosure may be explicitly excluded from any one or more of the claims. Where ranges are given, any value within the range may explicitly be excluded from any one or more of the claims. Any embodiment, element, feature, application, or aspect of the compositions and/or methods of the disclosure, can be excluded from any one or more claims. For purposes of brevity, all of the embodiments in which one or more elements, features, purposes, or aspects is excluded are not set forth explicitly herein.

[00406] Throughout this disclosure various publications, patents, and sequence database entries are mentioned. The disclosures of these publications, patents, and sequence database entries, including those items listed above, are hereby incorporated by reference in their entirety as if each individual publication or patent was specifically and individually indicated to be incorporated by reference. In case of conflict, the present application, including any definitions herein, will control.

[00407] Although the disclosure has been described with reference to the examples provided above, it should be understood that various modifications can be made without departing from the scope of the disclosure. Accordingly, the above examples are intended to illustrate but not limit the present disclosure.

Claims

What is claimed is:

1. A method of determining the predicted delivery date (PDD) or time to birth (TTB) for a pregnant female, the method comprising:

(a) obtaining a biological sample obtained from said pregnant female;

(b) detecting the presence or amount of a pair of isolated biomarkers in said biological sample obtained from said pregnant female; and

(c) measuring in said biological sample a reversal value for said pair of isolated biomarkers, wherein said pair of isolated biomarkers exhibits a change in reversal value between pregnant females who deliver X or more days before the estimated due date (EDD) or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD, wherein X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, wherein Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, wherein Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, wherein said detecting comprises subjecting said biological sample to an assay that utilizes a capture agent that binds to at least one biomarker of said pair of isolated biomarkers, and wherein said pair of isolated biomarkers comprises:

(i) ADA12 and an isolated biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1, or

(ii) two isolated biomarkers selected from Table 2.

2. The method of claim 1, wherein the biological sample obtained from the pregnant female is collected using an at-home or in-clinic handheld bodily fluid collection device, a volumetric absorptive microsampling device, or a dried blood spot card.

3. The method of claim 1 or 2, wherein the biological sample is selected from the group consisting of dried capillary whole blood, dried serum, or dried plasma.

4. The method of claim 3, wherein the biological sample is dried capillary whole blood.

5. The method of any one of claims 1-4, wherein the biological sample is obtained at a gestational age at blood draw (GABD) from 126 through 202 days.

6. The method of any one of claims 1-5, wherein the biological sample is obtained at a GABD from 126 through 160 days.

7. The method of any one of claims 1-5, wherein the biological sample is obtained at a GABD from 161 through 202 days.

8. The method of any one of claims 1-7, wherein the biological sample is stable at 50°C for 48 hours.

9. The method of any one of claims 1-8, wherein said capture agent is selected from the group consisting of an antibody, antibody fragment, nucleic acid-based protein binding reagent, small molecule or variant thereof.

10. The method of any one of claims 1-9, wherein said assay is selected from the group consisting of an enzyme immunoassay (EIA), an enzyme-linked immunosorbent assay (ELISA), and a radioimmunoassay (RIA).

11. The method of any one of claims 1-10, wherein heparin is used in the detection of said pair of isolated biomarkers in said biological sample obtained from said pregnant female.

12. The method of any one of claims 1-11, wherein X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, wherein Y is no more than 1, 2, 3, 4, 5, 6, or 7 days, and wherein Z is no more than 1, 2, 3, 4, 5, 6, or 7 days.

13. The method of claim 12, wherein X is no more than 1, 2, 3, 4, 5, 6, or 7 days, wherein Y is no more than 1, 2, 3, or 4 days, and wherein Z is no more than 1, 2, 3, or 4 days.

14. The method of any one of claims 1-13, wherein said pair of isolated biomarkers comprises AD Al 2 and KIT.

15. The method of any one of claims 1-13, wherein the capture agent binds to a region of any one of the isolated biomarkers of Table 2 comprising any of the respective amino acid sequences.

16. The method of any one of claims 1-14, wherein:

(a) the capture agent binds to a region of ADA12 comprising the amino acid sequence FGFGGSTDSGPIR (SEQ ID NO: 1);

(b) the capture agent binds to a region of KIT comprising the amino acid sequence YVSELHLTR (SEQ ID NO: 2);

(c) the capture agent binds to a region of KIT comprising the amino acid sequence LCLHCSVDQEGK (SEQ ID NO: 3);

(d) the capture agent binds to a region of FETUA comprising the amino acid sequence FSVVYAK (SEQ ID NO: 4);

(e) the capture agent binds to a region of ENPP2 comprising the amino acid sequence TEFLSNYLTNVDDITLVPGTLGR (SEQ ID NO: 5);

(f) the capture agent binds to a region of ENPP2 comprising the amino acid sequence TYLHTYESEI (SEQ ID NO: 6);

(g) the capture agent binds to a region of A2GL comprising the amino acid sequence DLLLPQPDLR (SEQ ID NO: 7); or

(h) the capture agent binds to a region of IGF 1 comprising the amino acid sequence GFYFNKPTGYGSSSR (SEQ ID NO: 8).

17. The method of any one of claims 1-16, wherein the amount of said pair of isolated biomarkers is further combined with one or more clinical components into a model that can be trained on a dataset to determine the PDD or TTB.

18. The method of claim 17, wherein the model comprises the amount of said pair of isolated biomarkers and one or more clinical components selected from the group consisting of GABD, gravidity, and MAGE.

19. A method of determining the predicted delivery date (PDD) or time to birth (TTB) for a pregnant female, the method comprising:

(a) obtaining a biological sample obtained from said pregnant female; (b) detecting the presence or amount of a pair of isolated biomarkers in said biological sample obtained from said pregnant female; and

(c) measuring in said biological sample a reversal value for said pair of isolated biomarkers to determine the PDD or TTB, wherein the reversal value gives a PDD or TTB that falls within +/-X days of the pregnant female’s actual delivery date (ADD) or actual TTB at least Y% of the time, wherein X is 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1, wherein Y is 50%, 51%, 52%, 53%, 54%, 55%, 56%, 57%, 58%, 59%, 60%, 61%, 62%, 63%, 64%, 65%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or 100%, and wherein said pair of isolated biomarkers comprises:

(i) ADA12 and an isolated biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1; or

(ii) two isolated biomarkers selected from Table 2.

20. The method of claim 19, wherein said pair of isolated biomarkers comprises ADA12 and KIT.

21. The method of claim 19 or 20, wherein X is 3, 2, or 1, and wherein Y is 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or 100%.

22. The method of any one of claims 19-21 , wherein the reversal value gives a PDD or TTB that falls within 3 days of the pregnant female’s ADD or actual TTB, and a PDD or TTB that is within 5 days of an estimated due date (EDD) of the pregnant female.

23. A method of detecting a pair of isolated biomarkers, said method comprising:

(a) obtaining a biological sample obtained from a pregnant female;

(b) detecting the presence or amount of the pair of isolated biomarkers in the biological sample by contacting the biological sample with a first capture agent that specifically binds a first member of said pair and a second capture agent that specifically binds a second member of said pair; and

(c) detecting binding between the first biomarker of said pair and the first capture agent and between the second member of said pair and the second capture agent, wherein the biological sample obtained from the pregnant female is collected using an at-home or in-clinic handheld bodily fluid collection device, a volumetric absorptive microsampling device, or a dried blood spot card, and wherein said pair of isolated biomarkers comprises:

(ii) two isolated biomarkers selected from Table 2.

24. The method of claim 23, wherein the pair of isolated biomarkers comprises ADA12 and KIT.

25. The method of claims 23 or 24, wherein the first capture agent specifically binds ADA12 and the second capture agent specifically binds KIT.

26. The method of claim 23, wherein the first capture agent and the second capture agent respectively bind to two isolated biomarkers selected from Table 2.

27. The method of any one of claims 23-26, wherein the first capture agent and second capture agent is selected from the group consisting of an antibody, antibody fragment, nucleic acid-based protein binding reagent, small molecule or variant thereof.

28. The method of any one of claims 23-27, wherein the method is performed by an assay selected from the group consisting of enzyme immunoassay (EIA), enzyme-linked immunosorbent assay (ELISA), and radioimmunoassay (RIA).

29. A method of detecting a pair of isolated biomarkers in a pregnant female, said method comprising:

(a) obtaining a biological sample obtained from the pregnant female; and

(b) detecting the level of the pair of isolated biomarkers in the biological sample comprising subjecting the sample to a proteomics workflow comprised of mass spectrometry quantification, wherein the biological sample obtained from the pregnant female is collected using an at-home or in-clinic handheld bodily fluid collection device, a volumetric absorptive microsampling device, or a dried blood spot card, and wherein said pair of isolated biomarkers comprises:

(ii) two isolated biomarkers selected from Table 2.

30. The method of claim 29, wherein said pair of isolated biomarkers comprises ADA12 and KIT.

31. The method of claim 29, wherein the proteomics workflow comprises:

(i) thawing and depleting the biological sample of the 5, 8, 10, 12 or 14 highest abundance proteins by immunity-affinity chromatography;

(ii) digesting the depleted biological sample with a protease to yield peptides;

(iii) fortifying the digest with a mixture of stable isotope labeled standard (SIS) peptides; and

(iv) desalting and subjecting the digest to LC-MS/MS with a triple quadrapole instrument operated in MRM mode.

32. The method of claim 31, wherein the protease is trypsin.

33. A kit for determining the predicted delivery date (PDD) or time to birth (TTB) for a pregnant female, wherein the kit comprises:

(a) one or more agents for the detection of a pair of isolated biomarkers;

(b) a container for holding a biological sample isolated from a pregnant female; and

(c) printed instructions for reacting agents with the biological sample or a portion or derivative of the biological sample to detect the presence or amount of the isolated biomarkers in the biological sample, wherein the pair of biomarkers comprises:

(i) ADA12 and a biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1; or

(ii) two isolated biomarkers selected from Table 2.

34. The kit of claim 33, wherein the kit further comprises one or more control reference samples and reagents for performing an immunoassay.

35. The kit of claims 33 or 34, wherein the kit further comprises a package insert containing written instructions for methods for separating a pregnancy that delivers X or more days before the EDD or Y or more days after the EDD, from a pregnancy that delivers within Z days of the EDD, wherein X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, wherein Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 days, and wherein Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days.

36. The kit of any one of claims 33-35, wherein the pair of isolated biomarkers comprises ADA12 and KIT.

37. A composition comprising a pair of isolated biomarkers, wherein said pair of isolated biomarkers exhibits change in reversal value between pregnant females who deliver X or more days before the estimated due date (EDD) or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD, wherein X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, wherein Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, wherein Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, and wherein said pair of isolated biomarkers comprises:

(ii) two isolated biomarkers selected from Table 2.

38. The composition of claim 37, wherein the pair of isolated biomarkers comprises ADA12 and KIT.

39. Use of a composition comprising a pair of isolated biomarkers in a method of determining the predicted delivery date (PDD) or time to birth (TTB) for a pregnant female, wherein said pair of isolated biomarkers exhibits a change in reversal value between pregnant females who deliver X or more days before the estimated due date (EDD) or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD, wherein X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, wherein Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, wherein Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, and wherein said pair of isolated biomarkers comprises:

(ii) two isolated biomarkers selected from Table 2.

40. The use of claim 39, wherein the pair of isolated biomarkers comprises ADA12 and KIT.

41. A method of determining the predicted delivery date (PDD) or time to birth (TTB) for a pregnant female, the method comprising:

(a) obtaining a biological sample obtained from said pregnant female;

(b) detecting the presence or amount of one or more isolated biomarkers in said biological sample, and

(c) integrating one or more clinical or demographic variables with the detected presence or amount of said one or more isolated biomarkers into a predictive model for determining the PDD or TTB, wherein said detecting comprises subjecting said biological sample to (i) mass spectrometry (MS) quantification, or (ii) an assay that utilizes a capture agent that binds to each of the one or more isolated biomarkers, and wherein said one or more isolated biomarkers is selected from Table 2.

42. The method of claim 41, further comprising measuring in said biological sample the amount of each of said one or more isolated biomarkers to determine the PDD or TTB, wherein each of said one or more isolated biomarkers exhibits a change in the amount between pregnant females who deliver X or more days before the estimated due date (EDD) or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD, wherein X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, wherein Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, and wherein Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days.

43. The method of claim 42, wherein X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, wherein Y is no more than 1, 2, 3, 4, 5, 6, or 7 days, and wherein Z is no more than 1, 2, 3, 4, 5, 6, or 7 days.

44. The method of claim 43, wherein X is no more than 1, 2, 3, 4, 5, 6, or 7 days, wherein Y is no more than 1, 2, 3, or 4 days, and wherein Z is no more than 1, 2, 3, or 4 days.

45. The method of claim 41, further comprising measuring in said biological sample the amount of each of said one or more biomarkers to determine the PDD or TTB, wherein the amount is integrated into said predictive model and gives a PDD or TTB that falls within +/-X days of the pregnant female’s actual delivery date (ADD) or actual TTB at least Y% of the time, wherein X is 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1, and wherein Y is 50%, 51%, 52%, 53%, 54%, 55%, 56%, 57%, 58%, 59%, 60%, 61%, 62%, 63%, 64%, 65%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or 100%.

46. The method of claim 45, wherein X is 3, 2, or 1, and wherein Y is 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or 100%.

47. The method of any one of claims 45-46, wherein the amount of each of said one or more biomarkers is integrated into said predictive model and gives a PDD or TTB that falls within 3 days of the pregnant female’s ADD or actual TTB, and a PDD or TTB that is within 5 days of an estimated due date (EDD) of the pregnant female.

48. The method of any one of claims 41-47, wherein the biological sample obtained from the pregnant female is collected using an at-home or in-clinic handheld bodily fluid collection device, a volumetric absorptive microsampling device, or a dried blood spot card.

49. The method of any one of claims 41-48, wherein the biological sample is selected from the group consisting of dried capillary whole blood, dried serum, or dried plasma.

50. The method of claim 49, wherein the biological sample is dried capillary whole blood.

51. The method of any one of claims 41-50, wherein the biological sample is obtained at a gestational age at blood draw (GABD) from 126 through 202 days.

52. The method of any one of claims 41-51, wherein the biological sample is obtained at a GABD from 126 through 160 days.

53. The method of any one of claims 41-51, wherein the biological sample is obtained at a GABD from 161 through 202 days.

54. The method of any one of claims 41-53, wherein the biological sample is stable at 50°C for 48 hours.

55. The method of any one of claims 41-54, wherein heparin is used in the detection of said one or more isolated biomarkers in said biological sample obtained from said pregnant female.

56. The method of any one of claims 41-55, wherein said one or more clinical or demographic variables is selected from the group consisting of age, BMI, race, hypertiension/preeclampsia in a prior pregnancy, preterm birth in a prior pregnancy, cesarean section (c-section) delivery in a prior pregnancy, education level, being a first time mother, chronic diabetes, gestational diabetes in the current pregnancy, hypertension or preeclampsia in the current pregnancy, previous low birth weight or preterm delivery, multiple 2nd trimester spontaneous abortions, prior first trimester induced abortion, familial and intergenerational factors, history of infertility, parity, nulliparity, placental abnormalities, cervical and uterine anomalies, short cervical length measurements, results of anomaly scans (including fetal (e.g., crown-rump length), placental and maternal pelvic organ measures), gestational bleeding, intrauterine growth restriction, in utero diethylstilbestrol exposure, multiple gestations, infant sex, short stature, low prepregnancy weight, chronic hypertension, urogenital infections (z.e., urinary tract infection), asthma, anxiety and depression, asthma, hypothyroidism, high BMI, low BMI, maternal age (MAGE), ethnicity, single marital status, low socioeconomic status, employment-related physical activity, occupational exposures, environment exposures, stress, inadequate prenatal care, cigarette smoking, use of marijuana and other illicit drugs, cocaine use, alcohol consumption, caffeine intake, maternal weight gain, dietary intake, sexual activity during late pregnancy, and leisure-time physical activities.

57. The method of claim 56, wherein said one or more clinical or demographic variables is selected from the group consisting of age, BMI, race, hypertiension/preeclampsia in a prior pregnancy, preterm birth in a prior pregnancy, c-section delivery in a prior pregnancy, education level, being a first-time mother, chronic diabetes, gestational diabetes in the current pregnancy, hypertension or preeclampsia in the current pregnancy.

58. The method of claim 41, wherein said detecting comprises said assay that utilizes a capture agent that binds to at least one of said one or more isolated biomarkers, and wherein said one or more isolated biomarkers comprises an amino acid sequence selected from Table 2.

59. The method of claim 58, wherein said capture agent is selected from the group consisting of an antibody, antibody fragment, nucleic acid-based protein binding reagent, small molecule or variant thereof.

60. The method of claim 58, wherein said assay is selected from the group consisting of enzyme immunoassay (EIA), enzyme-linked immunosorbent assay (ELISA), and radioimmunoassay (RIA).

61. The method of claim 41, wherein said detecting comprises said MS quantification.

62. The method of claim 61, wherein said MS is selected from the group consisting of matrix-assisted laser desorption/ionisation time-of-flight (MALDI-TOF) MS; MALDI-TOF post-source-decay (PSD); MALDI- TOF/TOF; surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF) MS; electrospray ionization mass spectrometry (ESLMS); ESLMS/MS; ESI-MS/(MS)n (n is an integer greater than zero); ESI 3D or linear (2D) ion trap MS; ESI triple quadrupole MS; ESI quadrupole orthogonal TOF (Q- TOF); ESI Fourier transform MS systems; desorption/ionization on silicon (DIOS); secondary ion mass spectrometry (SIMS); atmospheric pressure chemical ionization mass spectrometry (APCI-MS); APCL MS/MS; APCL (MS)n (n is an integer greater than zero); ion mobility spectrometry (IMS); inductively coupled plasma mass spectrometry (ICP-MS); atmospheric pressure photoionization mass spectrometry (APPL MS); APPLMS/MS; and APPI- (MS)n (n is an integer greater than zero).

63. The method of claim 61, wherein said MS comprises affinity-capture MS (AC -MS), co-immunoprecipitation-mass spectrometry (co-IP MS), liquid chromatography-mass spectrometry (LC-MS), multiple reaction monitoring (MRM) or selected reaction monitoring (SRM).

64. A method of detecting one or more isolated biomarkers, the method comprising:

(a) obtaining a biological sample obtained from a pregnant female;

(b) detecting the presence or amount of each of the one or more isolated biomarkers in the biological sample by contacting the biological sample with a capture agent that specifically binds a member of each of said one or more isolated biomarkers; and

(c) detecting binding between the one or more isolated biomarkers and the capture agent, wherein the biological sample obtained from the pregnant female is collected using an at-home or in-clinic handheld bodily fluid collection device, a volumetric absorptive microsampling device, or a dried blood spot card, and wherein the one or more isolated biomarkers is selected from Table 2.

65. The method of claim 64, wherein the capture agent is selected from the group consisting of an antibody, antibody fragment, nucleic acid-based protein binding reagent, small molecule or variant thereof.

66. The method of any one of claims 64-65, wherein the method is performed by an assay selected from the group consisting of enzyme immunoassay (EIA), enzyme-linked immunosorbent assay (ELISA), and radioimmunoassay (RIA).

67. A method of detecting one or more isolated biomarkers in a pregnant female, the method comprising:

(a) obtaining a biological sample obtained from the pregnant female; and

(b) detecting the level of each of the one or more isolated biomarkers in the biological sample comprising subjecting the sample to a proteomics workflow comprised of mass spectrometry quantification, wherein the biological sample obtained from the pregnant female is collected using an at-home or in-clinic handheld bodily fluid collection device, a volumetric absorptive microsampling device, or a dried blood spot card, and wherein said one or more isolated biomarkers is selected from Table 2.

68. The method of claim 67, wherein the proteomics workflow comprises:

69. The method of claim 68, wherein the protease is trypsin.

70. A kit for determining the predicted delivery date (PDD) or time to birth (TTB) for a pregnant female, wherein the kit comprises:

(a) one or more agents for the detection of one or more isolated biomarkers;

(c) printed instructions for reacting agents with the biological sample or a portion or derivative of the biological sample to detect the presence or amount of each of the one or more isolated biomarkers in the biological sample, wherein the one or more isolated biomarkers is selected from Table 2.

71. The kit of claim 70, wherein the kit further comprises one or more control reference samples and reagents for performing an immunoassay.

72. The kit of any one of claims 70-71, wherein the kit further comprises a package insert containing written instructions for methods for separating a pregnancy that delivers X or more days before the Estimated due date (EDD) or Y or more days after the EDD, from a pregnancy that delivers within Z days of the EDD, wherein X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, wherein Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 days, and wherein Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days.

73. A composition comprising one or more isolated biomarkers, wherein said one or more isolated biomarkers exhibits a change in an amount between pregnant females who deliver X or more days before the estimated due date (EDD) or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD, wherein X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, wherein Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, wherein Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, and wherein said one or more isolated biomarkers is selected from Table 2.

74. Use of a composition comprising one or more isolated biomarkers in a method of determining the predicted delivery date (PDD) or time to birth (TTB) for a pregnant female, wherein said one or more isolated biomarkers exhibits a change in an amount between pregnant females who deliver X or more days before the estimated due date (EDD) or Y or more days after the EDD, relative to pregnant females who deliver within Z days of the EDD, wherein X is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 28, or 35 days, wherein Y is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, wherein Z is no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, and wherein said one or more isolated biomarkers is selected from Table 2.

75. A method of predicting the week of gestation in which a pregnant female is most likely to deliver, the method comprising:

(a) obtaining a biological sample obtained from said pregnant female;

(b) detecting the presence or amount of one or more isolated biomarkers in said biological sample;

(c) comparing clinical factors for said pregnant female to the same clinical factors in a cohort of reference pregnant females; and

(d) deriving from (b) and (c) the probability said pregnant female will deliver in each of certain specific weeks of gestation.

76. The method of claim 75, wherein said one or more isolated biomarkers in said biological sample is selected from Table 2.

77. The method of claim 75, wherein said one or more isolated biomarkers in said biological sample is selected from Table 16.

78. The method of claim 75, wherein said one or more isolated biomarkers in said biological sample comprises at least two isolated biomarkers selected from Table 2.

79. The method of claim 78, wherein said one or more isolated biomarkers in said biological sample comprises at least two isolated biomarkers selected from Table 16.

80. The method of claim 79, wherein said one or more isolated biomarkers in said biological sample comprises ADA12 and an isolated biomarker selected from the group consisting of KIT, FETUA, ENPP2, A2GL, and IGF1.

81. The method of claim 80, wherein said one or more isolated biomarkers in said biological sample comprises ADA12 and KIT.

82. The method of any one of claims 75 to 81, wherein the cohort of reference pregnant females is derived from a proprietary database or a public database.

83. The method of claim 82, wherein the cohort of reference pregnant females is derived from a CDC database.

84. The method of any one of claims 75 to 83, wherein the clinical factors in (c) are selected from the group consisting of age, BMI, race, hypertension/preeclampsia in a prior pregnancy, preterm birth in a prior pregnancy, c-section delivery in a prior pregnancy, education level, being a first-time mother, chronic diabetes, gestational diabetes in the current pregnancy, and hypertension or preeclampsia in the current pregnancy.

85. The method of any one of claims 75-84, wherein the probability in (d) is derived by:

(1) deriving the probability said pregnant female will deliver in each of certain specific weeks of pregnancy based at least in part on the comparison in (c); and

(2) adjusting the probability in (1) by the probability derived from comparing the amount of biomarker(s) detected in (b) with the amount of said biomarkers detected in a reference cohort of pregnant females.

86. The method of any one of claims 75-85, wherein said certain specific weeks of gestation comprise weeks 37 through 41 of gestation.