WO2020117184A1 - Methods and compositions for providing a preeclampsia assessment by proteomics - Google Patents

Abstract

Preeclampsia markers, preeclampsia (PE) marker panels, and methods for obtaining a preeclampsia marker level representation for a sample are provided. These composition and methods find use in a number of applications, including, for example, diagnosing preeclampsia, prognosing preeclampsia, monitoring a subject with preeclampsia, and determining a treatment for preeclampsia. In addition, systems, devices, and kits thereof that find use in practicing the subject methods are provided.

Description

Methods and compositions for providing a preeclampsia assessment by proteomics

Field of the invention

The present disclosure generally relates to protein biomarkers. In particular, the present disclosure relates to a panel of protein species to diagnose preeclampsia (PE), including methods for identifying such protein biomarkers within biological samples. This invention pertains to providing a PE assessment with proteins. Background of the invention

Preeclampsia is a serious multisystem complication of pregnancy with adverse effects for mothers and babies. The incidence of the disorder is around 5-8% of all pregnancies in the U.S. and worldwide, and the disorder is responsible for 18% of all maternal deaths in the U.S. The causes and pathogenesis of preeclampsia remain uncertain, and the diagnosis relies on nonspecific laboratory and clinical signs and symptoms that occur late in the disease process, sometimes making the diagnosis and clinical management decisions difficult. Earlier and more reliable disease diagnosing, prognosing and monitoring will lead to more timely and personalized preeclampsia treatments and significantly advance our understanding of preeclampsia pathogenesis.

Although the pathophysiology remains largely elusive, PE is a multisystem disorder of pregnancy with the placenta playing a pivotal role. Investigators have used genetic, genomic and proteomic approaches to compare PE and normal placental tissues. Transcriptional profiling of case-control samples has been used to identify

SUBSTITUTE SHEET (RULE 26) disease-specific expression patterns, canonical pathways and gene-gene networks. Proteomics-based biomarker studies have been approved to be powerful to reveal candidate biomarkers. However, an applicable, sensitive and specific proteomic PE test in routine clinical practice is unavailable.

A promising approach is proteomics, a fast-growing area in system biology that uses mass spectrometry (MS) and promises the identification of sensitive proteomic biomarkers associated with disease, drug treatment, toxicity, and environmental effects. Proteomes are the downstream products of genes, transcripts and are playing functioning roles in biological systems. They are especially sensitive to perturbations in a number of functioning pathways and varied pathological conditions. This invention uses LC-MRM/MS to analyze the small molecule metabolites, and uses these proteins for PE assessment.

Summary of the invention

The present disclosure relates to a panel of proteins that is useful for

identification of subjects having PE, including methods of identifying such protein markers within biological samples.

In one aspect, the disclosure includes a method comprising measuring the concentration of 1 to 20 protein species in a sample of a serum from a subject, wherein the protein species is a component of a panel of a plurality of protein species, wherein a change in the concentration of the protein species is useful for the identification of subjects having PE. In certain embodiments the concentration of the proteomic species is normalized. In preferred embodiments, the method includes the step of comparing the

SUBSTITUTE SHEET (RULE 26) measured concentration of the protein species to a predetermined value calculated using a model based on concentrations of a plurality of the protein species that are components of the panel.

In certain embodiments, the panel of proteomic species comprises 1 to 20 proteins selected from the group consisting of Prothrombin, Protein AMBP,

Apolipoprotein E, Apolipoprotein C-lll, Retinol-binding protein 4, Antithrombin-lll, Alpha- 1 -antitrypsin, Alpha-1 -antitrypsin, Apolipoprotein A-ll, Heparin cofactor 2, Alpha-1- antitrypsin, Histidine-rich glycoprotein, Prothrombin, L-selectin, Zinc-alpha-2- glycoprotein, Apolipoprotein A-ll, Alpha-1 -antitrypsin, Hemopexin, Vitronectin, Beta-2- glycoprotein 1.

Brief description of the drawings

The invention will be best understood from the following detailed description when read in conjunction with the accompanying drawings. The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee. It is emphasized that, according to common practice, the various features of the drawings are not to-scale. On the contrary, the dimensions of the various features are arbitrarily expanded or reduced for clarity. Included in the drawings are the following figures.

Figure 1. Outline of the study based on discovery and validation of PE protein biomarkers using 51 proteins method.

SUBSTITUTE SHEET (RULE 26) Figure 2. Scatter plots of selected protein analytes in normal and case for training (Top panel) and cross validation (Bottom panel) prediction. The specific selected proteins analytes are identifiers for PE.

Figure 3. Unsupervised hierarchical clustering analysis with heat map showing the abundance pattern of targeted proteomics profile of PE versus normal control subjects.

Figure 4. Feature importance (weighted score) in PE subset stratification modeling.

Figure 5. ROC curves for models of PE assessment with targeted protein profile evaluated on training prediction (top) and cross validation prediction set consisting of PE patients and normal control subjects.

Detailed description of the invention

Methods, compositions and reagents are provided for diagnosing and prognosing PE. The methods and compositions find use in a number of applications, including, for example, diagnosing PE, and monitoring an individual with PE. A report may be provided to the patient of the assessment. In addition, systems, devices and kits thereof that find use in practicing the subject methods are provided. These and other objects,

advantages, and features of the invention will become apparent to those persons skilled in the art upon reading the details of the compositions and methods as more fully described below.

Before the present methods and compositions are described, it is to be

understood that this invention is not limited to particular method or composition

SUBSTITUTE SHEET (RULE 26) described, as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present invention will be limited only by the appended claims. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, some potential and preferred methods and materials are now described. All publications mentioned herein are incorporated herein by reference to disclose and describe the methods and/or materials in connection with which the publications are cited. It is understood that the present disclosure supersedes any disclosure of an incorporated publication to the extent there is a contradiction.

As will be apparent to those of skill in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has discrete components and features which may be readily separated from or combined with the features of any of the other several embodiments without departing from the scope or spirit of the present invention. Any recited method can be carried out in the order of events recited or in any other order which is logically possible. It must be noted that as used herein and in the appended claims, the singular forms "a", "an", and "the" include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to "a cell" includes a plurality of such cells and

SUBSTITUTE SHEET (RULE 26) reference to "the peptide" includes reference to one or more peptides and equivalents thereof, e.g. polypeptides, known to those skilled in the art, and so forth.

As summarized above, aspects of the subject invention include methods, compositions, systems and kits that find use in providing a preeclampsia assessment, e.g. diagnosing, prognosing, monitoring, and/or treating preeclampsia in a subject. By "preeclampsia" or "pre-eclampsia" it is meant a multisystem complication of pregnancy that may be accompanied by one or more of high blood pressure, proteinuria, swelling of the hands and face/eyes (edema), sudden weight gain, higher-than-normal liver enzymes, and thrombocytopenia. Preeclampsia typically occurs in the third trimester of pregnancy, but in severe cases, the disorder occurs in the second trimester, e.g., after about the 22^nc* week of pregnancy. If unaddressed, preeclampsia can lead to eclampsia, i.e. seizures that are not related to a preexisting brain condition. By "diagnosing" a preeclampsia or "providing a preeclampsia diagnosis," it is generally meant providing a preeclampsia determination, e.g. a determination as to whether a subject (e.g. a subject that has clinical symptoms of preeclampsia, a subject that is asymptomatic for

preeclampsia but has risk factors associated with preeclampsia, a subject that is asymptomatic for preeclampsia and has no risk factors associated with preeclampsia) is presently affected by preeclampsia; a classification of the subject's preeclampsia into a subtype of the disease or disorder; a determination of the severity of preeclampsia; and the like. By“prognosing” a preeclampsia, or "providing a preeclampsia prognosis," it is generally meant providing a preeclampsia prediction, e.g. a prediction of a subject's susceptibility, or risk, of developing preeclampsia; a prediction of the course of disease progression and/or disease outcome, e.g. expected onset of the preeclampsia,

SUBSTITUTE SHEET (RULE 26) expected duration of the preeclampsia, expectations as to whether the preeclampsia will develop into eclampsia, etc.; a prediction of a subject's responsiveness to treatment for the preeclampsia, e.g., positive response, a negative response, no response at all; and the like. By "monitoring" a preeclampsia, it is generally meant monitoring a subject’s condition, e.g. to inform a preeclampsia diagnosis, to inform a preeclampsia prognosis, to provide information as to the effect or efficacy of a preeclampsia treatment, and the like. By "treating" a preeclampsia it is meant prescribing or providing any treatment of a preeclampsia in a mammal, and includes: (a) preventing the preeclampsia from occurring in a subject which may be predisposed to preeclampsia but has not yet been diagnosed as having it; (b) inhibiting the preeclampsia, i.e., arresting its development; or (c) relieving the preeclampsia, i.e., causing regression of the preeclampsia.

In describing the subject invention, compositions useful for providing a

preeclampsia assessment will be described first, followed by methods, systems and kits for their use. PREECLAMPSIA MARKERS AND PANELS

In some aspects of the invention, preeclampsia markers and panels of

preeclampsia markers are provided. By a "preeclampsia marker" it is meant a molecular entity whose representation in a sample is associated with a preeclampsia phenotype. For example, a preeclampsia marker may be differentially represented, i.e. represented at a different level, in a sample from an individual that will develop or has developed preeclampsia as compared to a healthy individual. In some instances, an elevated level of marker is associated with the preeclampsia phenotype. For example, the

SUBSTITUTE SHEET (RULE 26) concentration of marker in a sample may be 1.5- fold, 2-fold, 2.5-fold, 3-fold, 4-fold, 5- fold, 7.5-fold, 10-fold, or greater in a sample associated with the preeclampsia

phenotype than in a sample not associated with the preeclampsia phenotype. In other instances, a reduced level of marker is associated with the preeclampsia phenotype. For example, the concentration of marker in a sample may be 10% less, 20% less, 30% less, 40% less, 50% less or more in a sample associated with the preeclampsia phenotype than in a sample not associated with the preeclampsia phenotype.

As demonstrated in the examples of the present disclosure, the inventors have identified the 20 proteins: Prothrombin, Protein AMBP, Apolipoprotein E, Apolipoprotein C-lll, Retinol-binding protein 4, Antithrombin-Ill, Alpha-1-antitrypsin, Alpha-1 -antitrypsin, Apolipoprotein A-ll, Heparin cofactor 2, Alpha-1 -antitrypsin, Histidine-rich glycoprotein, Prothrombin, L-selectin, Zinc-alpha-2-glycoprotein, Apolipoprotein A-ll, Alpha-1- antitrypsin, Hemopexin, Vitronectin, Beta-2-glycoprotein 1 , that are represented at elevated/lowered levels in blood samples of PE, and thus, that find use as biomarkers in providing a PE assessment, e.g. diagnosing a PE, prognosing a PE, determining a treatment for a subject affected with PE, monitoring a subject with PE, and the like.

Methods

The subject PE biomarkers find use in making a PE assessment for a patient, or "subject". By a "PE assessment", it is generally meant an estimation of a subject's susceptibility to PE, a determination as to whether a subject is presently affected by PE, a prognosis of a subject affected by PE (e.g., identification of PE states, stages of the PE, prediction of responsiveness to a therapy and/or intervention, e.g. sensitivity or

SUBSTITUTE SHEET (RULE 26) resistance a chemotherapy, radiation, or surgery, likelihood that a patient will die from the PE, etc.), and the use of therametrics (e.g., monitoring a subject's condition to provide information as to the effect or efficacy of therapy on the PE). Thus, for example, the subject PE biomarkers and biomarker panels may be used to diagnose PE, to provide a prognosis to a patient having PE, to provide a prediction of the

responsiveness of a patient with PE to a medical therapy, to monitor a patient having PE, to treat a patient having PE, etc. In practicing the subject methods, a PE biomarker signature for a patient is obtained. By a "PE biomarker signature" or more simply, "PE signature", it is meant a representation of the measured level/activity of a PE biomarker or biomarker panel of interest. A biomarker signature typically comprises the

quantitative data on the biomarker levels/activity of these one or more biomarkers of interest.

Examples of biomarker signatures include collections of measured small molecular metabolites levels. As used herein, the term "biomarker signature" means metabolites signature. Examples of biomarker signatures include biomarker profiles and biomarker scores. By a "biomarker profile" it is meant the normalized representation of one or more biomarkers of interest, i.e. a panel of biomarkers of interest, in a patient sample. By a "biomarker score" it is meant a single metric value that represents the sum of the weighted representations of one or more biomarkers of interest, more usually two or more biomarkers of interest, i.e. a panel of biomarkers of interest, in a patient sample. Biomarker profiles and scores are discussed in greater detail below.

For example, in some embodiments, the subject methods may be used to obtain a PE signature. That is, the subject methods may be used to obtain a representation of

SUBSTITUTE SHEET (RULE 26) the metabolite, e.g., Prothrombin, Protein AMBP, Apolipoprotein E, Apolipoprotein C-lll, Retinol-binding protein 4, Antithrombin-Ill, Alpha-1 -antitrypsin, Alpha-1 -antitrypsin, Apolipoprotein A-ll, Heparin cofactor 2, Alpha-1 -antitrypsin, Histidine-rich glycoprotein, Prothrombin, L-selectin, Zinc-alpha-2-glycoprotein, Apolipoprotein A-ll, Alpha-1- antitrypsin, Hemopexin, Vitronectin, Beta-2-glycoprotein 1 , that are up- or down- regulated (i.e. , expressed at a higher or lower level, exhibits a higher or lower level of activity, etc.), in patients with PE.

To obtain a PE signature, the metabolite level of the one or more PE biomarkers of interest is detected in a patient sample. That is, the representation of one or more PE biomarkers, e.g., Prothrombin, Protein AMBP, Apolipoprotein E, Apolipoprotein C-lll, Retinol-binding protein 4, Antithrombin-lll, Alpha-1 -antitrypsin, Alpha-1 -antitrypsin, Apolipoprotein A-ll, Heparin cofactor 2, Alpha-1 -antitrypsin, Histidine-rich glycoprotein, Prothrombin, L-selectin, Zinc-alpha-2-glycoprotein, Apolipoprotein A-ll, Alpha-1 - antitrypsin, Hemopexin, Vitronectin, Beta-2-glyco protein 1 , and in some instances other PE biomarkers in the art, e.g. a panel of biomarkers, is determined for a patient sample.

The term“sample” with respect to a patient encompasses blood and other liquid samples of biological origin, solid tissue samples such as a biopsy specimen or tissue cultures or cells derived or isolated therefrom and the progeny thereof. The definition also includes samples that have been manipulated in any way after their procurement, such as by treatment with reagents; washed; or enrichment for certain cell populations.

The definition also includes samples that have been enriched for particular types of molecules, e.g., nucleic acids, polypeptides, etc. The term "biological sample" encompasses a clinical sample, and also includes tissue obtained by surgical resection,

SUBSTITUTE SHEET (RULE 26) tissue obtained by biopsy, cells in culture, cell supernatants, cell lysates, tissue samples, organs, bone marrow, blood, plasma, serum, and the like. The term "blood sample" encompasses a blood sample (e.g., peripheral blood sample) and any derivative thereof (e.g., fractionated blood, plasma, serum, etc.).

In performing the subject methods, the biomarker level is typically assessed in a body fluid sample (e.g., a sample of blood, e.g., whole blood, fractionated blood, plasma, serum, etc.) that is obtained from an individual. The sample that is collected may be freshly assayed or it may be stored and assayed at a later time. If the latter, the sample may be stored by any convenient means that will preserve the sample so that gene expression may be assayed at a later date. For example, the sample may freshly cryopreserved, that is, cryopreserved without impregnation with fixative, e.g. at 4°C, at - 20°C, at -60°C, at -80°C, or under liquid nitrogen. Alternatively, the sample may be fixed and preserved, e.g. at room temperature, at 4°C, at -20°C, at -60°C, at -80°C, or under liquid nitrogen, using any of a number of fixatives known in the art, e.g. alcohol, methanol, acetone, formalin, paraformaldehyde, etc.

The resultant data provides information regarding activity for each of the PE biomarkers that have been measured, wherein the information is in terms of whether or not the biomarker is present (e.g. expressed and/or active) and, typically, at what level, and wherein the data may be both qualitative and quantitative.

Once the representation of the one or more biomarkers has been determined, the measurement(s) may be analyzed in any of a number of ways to obtain a biomarker signature.

SUBSTITUTE SHEET (RULE 26) For example, the representation of the one or more PE biomarkers may be analyzed individually to develop a biomarker profile. As used herein, a "biomarker profile" is the normalized representation of one or more biomarkers in a patient sample, for example, the normalized level of serological metabolite concentrations in a patient sample, the normalized activity of a biomarker in the sample, etc. A profile may be generated by any of a number of methods known in the art. Other methods of

calculating a biomarker signature will be readily known to the ordinarily skilled artisan.

As another example, the measurement of a PE biomarker or biomarker panel may be analyzed collectively to arrive at a PE biomarker score, and the PE biomarker signature is therefore a single score. By "biomarker assessment score" it is meant a single metric value that represents the sum of the weighted representations of each of the biomarkers of interest, more usually two or more biomarkers of interest, in a biomarker panel. As such, in some embodiments, the subject method comprises detecting the amount of markers of a PE biomarker panel in the sample, and calculating a PE biomarker score based on the weighted levels of the biomarkers. In certain embodiments, the biomarker score is based on the weighted levels of the biomarkers. In certain embodiments, the biomarker score may be a“metabolite biomarker score”, or simply "metabolite score”, i.e. it comprises the weighted expression level(s) of the one or more biomarkers, e.g. each biomarker in a panel of biomarkers.

A PE biomarker score for a patient sample may be calculated by any of a number of methods and algorithms known in the art for calculating biomarker scores. For example, weighted marker levels, e.g. log2 transformed and normalized marker levels that have been weighted by, e.g., multiplying each normalized marker level to a

SUBSTITUTE SHEET (RULE 26) weighting factor, may be totaled and in some cases averaged to arrive at a single value representative of the panel of biomarkers analyzed.

In some instances, the weighting factor, or simply "weight" for each marker in a panel may be a reflection of the change in analyte level in the sample. For example, the analyte level of each biomarker may be log2 transformed and weighted either as 1 (for those markers that are increased in level in a subgroup of PE of interest, etc.) or -1 (for those markers that are decreased in level in a subgroup of PE of interest, etc.), and the ratio between the sum of increased markers as compared to decreased markers determined to arrive at a PE biomarker signature. In other instances, the weights may be reflective of the importance of each marker to the specificity, sensitivity and/or accuracy of the marker panel in making the diagnostic, prognostic, or monitoring assessment. Such weights may be determined by any convenient statistical machine learning methodology, e.g. Principle Component Analysis (PCA), linear regression, support vector machines (SVMs), and/or random forests of the dataset from which the sample was obtained may be used. In some instances, weights for each marker are defined by the dataset from which the patient sample was obtained. In other instances, weights for each marker may be defined based on a reference dataset, or“training dataset”. Methods of analysis may be readily performed by one of ordinary skill in the art by employing a computer-based system, e.g. using any hardware, software and data storage medium as is known in the art, and employing any algorithms convenient for such analysis. For example, data mining algorithms can be applied through“cloud computing”, smartphone based or client-server based platforms, and the like.

SUBSTITUTE SHEET (RULE 26) Thus, in some instances, a PE biomarker signature may be expressed as a series of values that are each reflective of the level of a different biomarker (e.g., as a biomarker profile, i.e. the normalized expression values for multiple biomarkers), while in other instances, the PE biomarker signature may be expressed as a single value (e.g., a PE biomarker score).

In some instances, the subject methods of obtaining or providing a PE biomarker signature for a subject further comprise providing the PE biomarker signature as a report. Thus, in some instances, the subject methods may further include a step of generating or outputting a report providing the results of a PE biomarker evaluation in the sample, which report can be provided in the form of an electronic medium (e.g., an electronic display on a computer monitor), or in the form of a tangible medium (e.g., a report printed on paper or other tangible medium). Any form of report may be provided, e.g. as known in the art or as described in greater detail below.

The PE signature that is so obtained may be employed to make an

PE assessment. Typically, in making the subject PE assessment, the PE signature is employed by comparing it to a reference or control, and using the results of that comparison (a“comparison result”) to make the PE assessment, e.g. diagnosis, prognosis, prediction of responsiveness to treatment, etc. The terms“reference" or “control”, e.t.“reference signature” or“control signature”,“reference profile” or“control profile”, and“reference score” or“control score” as used herein mean a standardized biomarker signature, e.g. biomarker profile or biomarker score, that may be used to interpret the PE biomarker signature of a given patient and assign a diagnostic, prognostic, and/or responsiveness class thereto. The reference or normal control is

SUBSTITUTE SHEET (RULE 26) typically a PE biomarker signature that is obtained from a sample (e.g., a body fluid, e.g. blood) with a known association with a particular phenotype, Typically, the comparison between the PE signature and reference will determine whether the PE signature correlates more closely with the positive reference or the negative reference, and the correlation employed to make the assessment. By "correlates closely", it is meant is within about 40% of the reference, e.g. 40%, 35%, or 30%, in some embodiments within 25%, 20%, or 15%, sometimes within 10%, 8%, 5%, or less.

In certain embodiments, the obtained PE signature for a subject is compared to a single reference/control biomarker signature to obtain information regarding the phenotype. In other embodiments, the obtained biomarker signature for the subject is compared to two or more different reference/control biomarker signatures to obtain more in-depth information regarding the phenotype of the assayed tissue. For example, a biomarker profile, or a biomarker score to obtain confirmed information regarding whether the tissue has the phenotype of interest. As another example, a biomarker profile or score may be compared to multiple biomarker profiles or scores, each correlating with a particular diagnosis, prognosis or therapeutic responsiveness.

In some instances, the subject methods of determining or obtaining a

preeclampsia marker representation (e.g. preeclampsia profile or preeclampsia score) for a subject further comprise providing the preeclampsia marker representation as a report. Thus, in some instances, the subject methods may further include a step of generating or outputting a report providing the results of a preeclampsia marker evaluation in the sample, which report can be provided in the form of an electronic medium (e.g., an electronic display on a computer monitor), or in the form of a tangible

SUBSTITUTE SHEET (RULE 26) medium (e.g., a report printed on paper or other tangible medium). Any form of report may be provided, e.g. as known in the art or as described in greater detail below.

REPORTS

A "report," as described herein, is an electronic or tangible document which includes report elements that provide information of interest relating to the assessment of a subject and its results. In some embodiments, a subject report includes at least a preeclampsia marker representation, e.g. a preeclampsia profile or a preeclampsia score, as discussed in greater detail above. In some embodiments, a subject report includes at least an artisan's preeclampsia assessment, e.g. preeclampsia diagnosis, preeclampsia prognosis, an analysis of a preeclampsia monitoring, a treatment recommendation, etc. A subject report can be completely or partially electronically generated. A subject report can further include one or more of: 1) information regarding the testing facility; 2) service provider information; 3) patient data; 4) sample data; 5) an assessment report, which can include various information including: a) reference values employed, and b) test data, where test data can include, e.g., a protein level

determination; 6) other features.

In some embodiments, providing a PE signature or providing a PE assessment, e.g., a diagnosis of PE, a prognosis for a patient with PE, a prediction of

responsiveness of a patient with PE to a cancer therapy, includes generating a written report that includes that PE signature and/or the PE assessment e.g. a "diagnosis assessment", a "prognosis assessment", a suggestion of possible treatment regimens (a "treatment assessment") and the like. Thus, the subject methods may further include

SUBSTITUTE SHEET (RULE 26) a step of generating or outputting a report providing the results of an analysis of a PE biomarker or biomarker panel, a diagnosis assessment, a prognosis assessment, or a treatment assessment, which report can be provided in the form of an electronic medium (e.g., an electronic display on a computer monitor), or in the form of a tangible medium (e.g., a report printed on paper or other tangible medium).

The report may include information about the testing facility, which information is relevant to the hospital, clinic, or laboratory in which sample gathering and/or data generation was conducted. Sample gathering can include obtaining a fluid sample, e.g. blood, saliva, urine etc.; a tissue sample, e.g. a tissue biopsy, etc. from a subject. Data generation can include measuring the marker concentration in preeclampsia patients versus healthy individuals, i.e. individuals that do not have and/or do not develop preeclampsia. This information can include one or more details relating to, for example, the name and location of the testing facility, the identity of the lab technician who conducted the assay and/or who entered the input data, the date and time the assay was conducted and/or analyzed, the location where the sample and/or result data is stored, the lot number of the reagents (e.g., kit, etc.) used in the assay, and the like. Report fields with this information can generally be populated using information provided by the user.

The report may include information about the service provider, which may be located outside the healthcare facility at which the user is located, or within the healthcare facility. Examples of such information can include the name and location of the service provider, the name of the reviewer, and where necessary or desired the

SUBSTITUTE SHEET (RULE 26) name of the individual who conducted sample gathering and/or data generation. Report fields with this information can generally be populated using data entered by the user, which can be selected from among pre-scripted selections (e.g., using a drop-down menu). Other service provider information in the report can include contact information for technical information about the result and/or about the interpretive report.

The report may include a patient data section, including patient medical history (which can include, e.g., age, race, serotype, prior preeclampsia episodes, and any other characteristics of the pregnancy), as well as administrative patient data such as information to identify the patient (e.g., name, patient date of birth (DOB), gender, mailing and/or residence address, medical record number (MRN), room and/or bed number in a healthcare facility), insurance information, and the like), the name of the patient's physician or other health professional who ordered the monitoring assessment and, if different from the ordering physician, the name of a staff physician who is responsible for the patient's care (e.g., primary care physician). The report may include a sample data section, which may provide information about the biological sample analyzed in the monitoring assessment, such as the source of biological sample obtained from the patient (e.g. blood, saliva, or type of tissue, etc.), how the sample was handled (e.g. storage temperature, preparatory protocols) and the date and time collected. Report fields with this information can generally be populated using data entered by the user, some of which may be provided as pre-scripted selections (e.g., using a drop-down menu).

SUBSTITUTE SHEET (RULE 26) It will also be readily appreciated that the reports can include additional elements or modified elements. For example, where electronic, the report can contain hyperlinks which point to internal or external databases which provide more detailed information about selected elements of the report. For example, the patient data element of the report can include a hyperlink to an electronic patient record, or a site for accessing such a patient record, which patient record is maintained in a confidential database.

This latter embodiment may be of interest in an in-hospital system or in-clinic setting. When in electronic format, the report is recorded on a suitable physical medium, such as a computer readable medium, e.g., in a computer memory, zip drive, CD, DVD, etc. It will be readily appreciated that the report can include all or some of the elements above, with the proviso that the report generally includes at least the elements sufficient to provide the analysis requested by the user (e.g. a calculated preeclampsia marker level representation; a prediction, diagnosis or characterization of PE).

REAGENTS, SYSTEMS AND KITS Also provided are reagents, devices and kits thereof for practicing one or more of the above-described methods. The subject reagents, devices and kits thereof may vary greatly. Reagents and devices of interest include those mentioned above with respect to the methods of assaying proteins levels, where such reagents may include stable isotope labeled internal standards. The subject kits may also comprise one or more biomarker signature references, e.g. a reference for a PE signature, for use in employing the biomarker signature obtained from a patient sample. For example, the reference may be a sample of a known phenotype, e.g. an unaffected individual, or an

SUBSTITUTE SHEET (RULE 26) affected individual, e.g. from a particular risk group that can be assayed alongside the patient sample, or the reference may be a report of disease diagnosis, disease

prognosis, or responsiveness to therapy that is known to correlate with one or more of the subject PE biomarker signatures.

In addition to the above components, the subject kits may further include instructions for practicing the subject methods. These instructions may be present in the subject kits in a variety of forms, one or more of which may be present in the kit. One form in which these instructions may be present is as printed information on a suitable medium or substrate, e.g., a piece or pieces of paper on which the information is printed, in the packaging of the kit, in a package insert, etc. Yet another means would be a computer readable medium, e.g., diskette, CD, DVD, etc., on which the information has been recorded. Yet another means that may be present is a website address which may be used via the internet to access the information at a removed site. Any convenient means may be present in the kits.

The following examples are offered by way of illustration and not by way of limitation.

Examples

The following examples are put forth so as to provide those of ordinary skill in the art with a complete disclosure and description of how to make and use the present invention, and are not intended to limit the scope of what the inventors regard as their invention nor are they intended to represent that the experiments below are all or the only experiments performed. Efforts have been made to ensure accuracy with respect to

SUBSTITUTE SHEET (RULE 26) numbers used (e.g. amounts, temperature, etc.) but some experimental errors and deviations should be accounted for. Unless indicated otherwise, parts are parts by weight, molecular weight is weight average molecular weight, temperature is in degrees Centigrade, and pressure is at or near atmospheric.

Example 1

Study design

The study for PE proteomics experiment was comprised of the analysis of an independent PE cohort (n=32) and normal control cohort (n=32) (Figure 1). PE and normal control cohorts were constructed to match gestation age, ethnicity, and parity.

Sample purchase

All the serum samples were purchased from ProMedDX Inc. (Norton, MA 02766, http://www.promeddx.com). All pregnancy collections were with informed consent and supplied with detailed case report forms. Subjects, who were current smokers, or with substance abuse, or used in vitro fertilization assistance, or with chronic hypertension, or with intrauterine growth restriction complicating pregnancy, were excluded from the study.

Statistical analyses for sample clinical information Patient demographic data was analyzed using“Epidemiological calculator” (R epicalc package). Student t test was performed to calculate p value for continuous variables, and Fisher exact test was used for comparative analysis of categorical variables.

SUBSTITUTE SHEET (RULE 26) Sample characteristics

The PE and normal control subjects were used for serological protein biomarker discovery and validation. No significant difference in gender and in age.

As shown in Table 1 , the PE and normal control subjects were used for serological protein biomarker validation (PE, n=32; control, n=32). No significant differences in age (p value, 0.63), gestational age (p value, 0.79) at enrollment, or ethnical origin (p value, 1.00) were observed. Subjects’ concurrent medical conditions and other clinical features were analyzed.

Table 1. Ethnicity, age and weeks of gestation

Characteristic PE Control. p value

Ethicity 1

African American 7 (21.9%). 9 (28.1%)

Asian 2 (6.2%). 0 (0)

Hispanic 19 (59.4%). 22 (68.8%).

Others 4 (12.5%). 1 (3.1%).

Age (year)

Mean (SD) 26.7 (7.3). 25.8 (6.9) 0.63

Week of gestation³

Mean (SD) 33.9 (4.2). 33.7 (4.3) 0.79

Internal standard preparation

Dilute to 200 ml_ with 70%MeOH in a 200-mL volumetric flask to obtain concentrations of different analytes. Vortex vigorously and stored at 4 °C prior to use

SUBSTITUTE SHEET (RULE 26) Sample preparation

Preparation of serum sample: Serum sample was taken from -80 °C freezer and thawed on ice.10 mI_ of each serum sample was transferred into a new tube, and 90 mΐ_ extraction buffer was added for extraction. The samples were vortexed vigorously for 1 min and subjected to high-speed centrifuge at 12,000 g for 5 min under room

temperature. The supernatant from each sample was collected for analysis

Preparation of quality control samples (Serum): 1 ml_ of serum samples from 3-5 normal control individuals were pooled and vortexed for 1 min, then centrifuge at 3,000 g for 1 min. The pooled serum sample was divided into 10-uL aliquots and stored at -80 °C before use. 6 of 10-uL aliquots from pooled serum were unambiguously processed as internal quality controls for 90 unknown samples in a 96-well plate during the sample prep. Data analysis and statistics for metabolomics panel construction

Software and packages used in the data analysis included: random forest modeling analysis was performed using R random Forest package (http://www.r- project.org/). Biomarker feature selection and panel optimization was performed using a genetic algorithm (R genalg package). The predictive performance of each biomarker panel analysis was evaluated by ROC curve analysis (Zweig et al. Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clinical chemistry 1993;39:561-77; Sing et al. ROCR: visualizing classifier performance in R. Bioinformatics 2005;21 :3940-1).

SUBSTITUTE SHEET (RULE 26) The targeted proteomics profile was firstly normalized to z-score across all the samples (n = 64). The z-scores of the metabolomics profiles of subjects that were randomized to construct a training cohort (n = 64) were trained to develop a model by Random Forest analysis using the R package‘random Forest’. All subjects in the training cohort were assigned to one of two possible subgroups (normal control and T2DM) by the model. The model was developed specifically for PE identification. The model was applied to both training cohort and cross validation cohort (n=64 for PE, n=64 for normal control), and the probability of having PE for each corresponding subject was calculated. Receiver-operator characteristic (ROC) analysis was conducted to evaluate the ability of the targeted proteomics profile in differentiating the subjects in the cross-validation cohort with PE from those normal control subjects. This process was repeated by 5 times using a bootstrapping algorithm to get extensive evaluation of the model.

Unsupervised hierarchical clustering analysis was performed to visually depict the association between the PE outcomes and the abundance patterns of these proteomics profile. This analysis was used to demonstrate the effectiveness of the proteomics profile in differentiating PE from normal control subjects.

Example 2

Sample collection

32 PE serum samples and 32 normal controls were purchased from ProMedEx tissue banks. To compare the 20 proteins between PE and normal control samples, 10 pi of each serum samples were extracted and analyzed by flow injection MS/MS on a TSQ Quantiva (Thermo) triple quadrupole mass spectrometer. Tandem MS data were

SUBSTITUTE SHEET (RULE 26) processed using a meta-calculation software iRC PRO (2Next srl, Prato, Italy). Serum concentration for each analyte was calculated in mM unit and used for further analysis.

Statistical analysis for 20 proteomic analytes and panel construction

A t-test was performed for metabolomics profile between PE and corresponding normal control subjects (Table 2), P-values, odds ratios, and fold change for each metabolomics analyte were listed.

Table 2. Statistical summary of selected analytes in identifying PE

Analyte p-value Foldchange

Prothrombin 3.55E-07 1.1116236

Protein AMBP 2.05E-06 1.23158368

Apolipoprotein E 2.87E-05 1.46955486

Apolipoprotein C-lll 0.00172904 1.15523838

Retinol-binding protein 4 0.00266074 1.20356549

Antithrombin-lll 0.00278816 1.13973374

Alpha-l-antitrypsin 0.00292104 1.16870163

Alpha-l-antitrypsin 0.00439802 1.16118627

Apolipoprotein A-ll 0.01581695 1.1762557

Heparin cofactor 2 0.0164308 0.8749545

Alpha-l-antitrypsin 0.01909677 1.13402724

Histidine-rich glycoprotein 0.02056404 1.14744681

Prothrombin 0.02056404 1.12954287

L-selectin 0.02294606 1.12086998

Zinc-alpha-2-glycoprotein 0.02648629 1.11055253

Apolipoprotein A-ll 0.02842414 1.15671448

Alpha-l-antitrypsin 0.03155578 1.15439142

Hemopexin 0.03497407 0.90682791

Vitronectin 0.03618056 1.0889534

Beta-2-glycoprotein 1 0.05028293 0.90316301

SUBSTITUTE SHEET (RULE 26) We used p-value = 0.01 as the threshold to select metabolomics analytes. Two panels were constructed for early stage PE and late stage PE identification, respectively. The panel for early stage PE identification consisted of the following metabolomics analytes: Prothrombin, Protein AMBP, Apolipoprotein E, Apolipoprotein C-lll, Retinol binding protein 4, Antithrombin-Ill, Alpha-1 -antitrypsin, Alpha-1 -antitrypsin,

Apolipoprotein A-ll, Heparin cofactor 2, Alpha-1 -antitrypsin, Histidine-rich glycoprotein, Prothrombin, L-selectin, Zinc-alpha-2-glycoprotein, Apolipoprotein A-ll, Alpha-1- antitrypsin, Hemopexin, Vitronectin, Beta-2-glycoprotein 1.

Unsupervised hierarchical clustering with metabolomics profiles

Unsupervised hierarchical clustering analysis was applied to the targeted proteomics profiles to visually depict the association of the PE outcomes with the abundance patterns of these proteomics profiles (Figure 2). This analysis demonstrated two major clusters reflecting PE and normal (Figure 3).. The error rate (miss- classification rate) of the unsupervised clustering is 0% for PE, which reinforcing the effectiveness of for which reinforcing the effectiveness of proteomics panels for PE assessment (Figure 4,5).

SUBSTITUTE SHEET (RULE 26)

Claims

Claims What is claimed is:

1. A method of providing a preeclampsia (PE) marker level representation for a subject, the method comprising:

evaluating a panel of preeclampsia markers in a blood sample from a subject to determine the level of each preeclampsia marker in the blood sample; and

calculating the PE marker level representation based on the level of each preeclampsia marker in the panel.

2. The method according to claim 1 , wherein the panel of preeclampsia markers further comprise one or more preeclampsia markers selected from the group consisting of 1 to 20 proteins: Prothrombin, Protein AMBP, Apolipoprotein E, Apolipoprotein C-lll, Retinolbinding protein 4, Antithrombin-Ill, Alpha-1 -antitrypsin, Alpha-1 -antitrypsin,

Apolipoprotein A-ll, Heparin cofactor 2, Alpha-1 -antitrypsin, Histidine-rich glycoprotein, Prothrombin, L-selectin, Zinc-alpha-2-glycoprotein, Apolipoprotein A-ll, Alpha-1 - antitrypsin, Hemopexin, Vitronectin, Beta-2-glycoprotein 1..

3. The method of measuring the concentration of 1 to 20 proteins species in a sample of a bio-fluid from a subject to be tested for PE, wherein the 1 to 20 proteins species is a component of a panel of a plurality of protein species, wherein a change in the concentration of the protein species is a characteristic that is associated with PE.

4. The method of claim 1 wherein the concentrations of the protein species are normalized.

5. The method of claim 1 , further comprising the step of comparing the measured concentration of the 1 to 20 protein species to a predetermined value calculated using a

SUBSTITUTE SHEET (RULE 26) model based on concentrations of a plurality of the protein species that are components of the panel.

6. The method of claim 1 wherein the panel comprises protein species that have been identified by liquid chromatography-mass spectrometry (LC-MS).

7. The method of claim 1 , wherein the bio-fluid is selected from the group consisting of blood, plasma, serum, sweat, saliva, sputum, and urine.

8. The method of claim 1 , wherein the bio-fluid is serum.

9. A panel of metabolite species, the proteomic species are selected from a group consisting of Prothrombin, Protein AMBP, Apolipoprotein E, Apolipoprotein C-lll, Retinol-binding protein 4, Antithrombin-lll, Alpha-1 -antitrypsin, Alpha-1 -antitrypsin, Apolipoprotein A-ll, Heparin cofactor 2, Alpha-1 -antitrypsin, Histidine-rich glycoprotein, Prothrombin, L-selectin, Zinc-alpha-2-glycoprotein, Apolipoprotein A-ll, Alpha-1- antitrypsin, Hemopexin, Vitronectin, Beta-2-glycoprotein 1.

10. The panel of claim 7, wherein the panel is provided in a diagnostic cassette.

11. The diagnostic cassette of claim 8, further comprising reagents for the detection of the protein species of the panel.

12. A kit for making a preeclampsia diagnosis, comprising:

(a) one or more detection elements for measuring the amount of marker in a sample for a panel of preeclampsia markers comprising: Prothrombin, Protein AMBP,

Apolipoprotein E, Apolipoprotein C-lll, Retinol-binding protein 4, Antithrombin-lll, Alpha- 1 -antitrypsin, Alpha-1 -antitrypsin, Apolipoprotein A-ll, Heparin cofactor 2, Alpha-1 - antitrypsin, Histidine-rich glycoprotein, Prothrombin, L-selectin, Zinc-alpha-2-

SUBSTITUTE SHEET (RULE 26) glycoprotein, Apolipoprotein A-ll, Alpha-1 -antitrypsin, Hemopexin, Vitronectin, Beta-2- glycoprotein 1.

13. The kit of claim 12, further comprising (b) a preeclampsia phenotype determination element.

14. The kit of claim 12, wherein the panel of preeclampsia markers further comprises one or more markers selected from the group.

15. The kit of claim 12, wherein the one or more detection elements are antibodies directed to any one or more of the markers, probe nucleic acids directed to genes encoding any one or more of the markers, or gene specific primers directed to a fragment of a gene encoding any one or more of the markers.

16. The kit of claim 15, wherein the one or more detection elements comprising antibodies directed to no more than seven markers beside a control antibody.

17. The kit according to claim 12, wherein the panel of preeclampsia markers comprises of an aliquot of an internal standard and an aliquot of a control biofluid.

18. The kit of claim 12, wherein the control biofluid is serum from a control source that is conspecific with the subject.

19. The kit of claim 12, further comprising instructions for use.

SUBSTITUTE SHEET (RULE 26)