[go: up one dir, main page]

WO2025179300A1 - Biomarkers, compositions, kits, and methods distinguishing acute geriatric tbi from pre-existing dementia or cognitive impairment - Google Patents

Biomarkers, compositions, kits, and methods distinguishing acute geriatric tbi from pre-existing dementia or cognitive impairment

Info

Publication number
WO2025179300A1
WO2025179300A1 PCT/US2025/017101 US2025017101W WO2025179300A1 WO 2025179300 A1 WO2025179300 A1 WO 2025179300A1 US 2025017101 W US2025017101 W US 2025017101W WO 2025179300 A1 WO2025179300 A1 WO 2025179300A1
Authority
WO
WIPO (PCT)
Prior art keywords
tau
nrgn
gfap
bdnf
biomarkers
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/US2025/017101
Other languages
French (fr)
Inventor
Timothy Emmons VAN METER
Nazanin Mirshahi
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Brainbox Solutions Inc
Original Assignee
Brainbox Solutions Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Brainbox Solutions Inc filed Critical Brainbox Solutions Inc
Publication of WO2025179300A1 publication Critical patent/WO2025179300A1/en
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
    • A61P25/00—Drugs for disorders of the nervous system
    • A61P25/28—Drugs for disorders of the nervous system for treating neurodegenerative disorders of the central nervous system, e.g. nootropic agents, cognition enhancers, drugs for treating Alzheimer's disease or other forms of dementia
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6893—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
    • G01N33/6896—Neurological disorders, e.g. Alzheimer's disease
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/28—Neurological disorders
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/28—Neurological disorders
    • G01N2800/2814—Dementia; Cognitive disorders
    • G01N2800/2821—Alzheimer
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/28—Neurological disorders
    • G01N2800/2835—Movement disorders, e.g. Parkinson, Huntington, Tourette
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/28—Neurological disorders
    • G01N2800/2871—Cerebrovascular disorders, e.g. stroke, cerebral infarct, cerebral haemorrhage, transient ischemic event

Definitions

  • TBI Traumatic brain injury
  • Applicant recognized that there is a clinical need to accurately determine acute TBI diagnoses in the elderly population, compared with age-related atrophy and brain disease, for proper diagnosis, prognosis and/or treatment of elderly patients.
  • Methods, compositions, and kits made according to the principles and illustrative embodiments of the invention can determine acute TBI by measuring unique combinations of biomarkers that were discovered and developed for their capacity to differentiate geriatric TBI from other conditions.
  • methods, compositions, and kits made according to the principles and illustrative embodiments of the invention are capable of detecting, identifying, diagnosing, prognosing, assessing, monitoring, and/or treating a neurological injury such as acute TBI and distinguishing geriatric TBI from conditions such as dementia, Alzheimer’s Disease, Parkinson’s disease and the like.
  • a method for diagnosing an acute TBI in an elderly subject includes the steps of: (A) obtaining a biological sample from the elderly subject; (B) measuring the levels of one or more biomarkers present in the biological samples by a protein detection assay, wherein the one or more biomarkers are selected from the group consisting of: brain derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), interleukin-6 (IL-6), metallothionein 3 (MT3), neurofilament light chain (NfL), neurogranin (NRGN), neuron specific enolase (NSE), synuclein alpha (SNCA), synuclein beta (SNCB), Patent Application Attorney Docket No.179.0009-WO00 phosphorylated Ser129 SNCA (pS129-SNCA), soluble receptor for interleukin 33 (ST2), phosphorylated Thr181 tau (pT181 tau), phosphorylated Ser217tau (pS2
  • the method may further include treating the elderly subject for an acute TBI when at least one increased level of the one or more biomarkers is detected.
  • the biological sample used may be selected from blood, plasma, serum, cerebrospinal fluid (CSF), tears or lacrimal fluid, urine, and saliva.
  • Two or more of the biomarkers used in step (A) may be selected from the group consisting of BDNF, GFAP, IL-6, MT3, NfL, NRGN, NSE, SNCA, SNCB, pS129-SNCA, sST2, pT181 tau, pS217 tau, pT231 tau, and vWF, and, optionally, one or more of ALDOC.
  • the biomarkers used in the method may include a panel selected from one of the following groups of biomarker combinations: (a) two or more of NRGN, ST2, NSE, and BDNF; (b) two or more of NRGN, NSE, BDNF, and vWF; (c) two or more of NRGN, ST2, vWF, and pSNCA; (d) two or more of GFAP, ST2, NSE, and BDNF; (e) two or more of GFAP ,NRGN, ST2, and pSNCA; (f) two or more of GFAP, NRGN, ST2, and BDNF; (g) two or more of GFAP, NRGN, and pSNCA; (h) two or more of ST2, NSE, and BDNF; (i) two or more of GFAP, ST2, BDNF, and pSNCA; (j) two or more of NRGN, ST2, NSE, and vWF; (k) two or more of
  • a method of treating an elderly patient with traumatic brain injury or suspected of having traumatic brain injury includes: (A) administering over time a drug or drug treatment for traumatic brain injury comprising a single dose or multiple doses of the drug to the patient; (B) detecting at least one of the biomarker proteins selected from a group of biomarker proteins that distinguish traumatic brain injury from dementia, the group of biomarkers proteins including brain derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), interleukin-6 (IL-6), metallothionein 3 (MT3), neurofilament light chain (NfL), neurogranin (NRGN), neuron specific enolase (NSE), synuclein alpha (SNCA), synuclein beta (SNCB), phosphorylated Ser129 SNCA (pS129-SNCA), soluble receptor for interleukin 33 (ST2), phosphorylated Thr181 tau (pT181 tau), phosphorylated Ser
  • BDNF brain derived neurotrophic
  • the biological sample used may be selected from blood, plasma, serum, cerebrospinal fluid (CSF), tears or lacrimal fluid, urine, and saliva.
  • Two or more of the biomarkers used in step (A) may be selected from the group consisting of BDNF, GFAP, IL-6, MT3, NfL, NRGN, NSE, SNCA, SNCB, pS129-SNCA, sST2, pT181 tau, pS217 tau, pT231 tau, and vWF, and, optionally, one or more of ALDOC, FABP7, IL-7, and IL-33.
  • the biomarkers used in the method may include a panel selected from one of the following groups of biomarker combinations: (a) two or more of NRGN, ST2, NSE, and BDNF; (b) two or more of NRGN, NSE, BDNF, and vWF; (c) two or more of NRGN, ST2, vWF, and pSNCA; (d) two or more of GFAP, ST2, NSE, and BDNF; (e) two or more of GFAP ,NRGN, ST2, and pSNCA; (f) two or more of GFAP, NRGN, ST2, and BDNF; (g) two or more of GFAP, NRGN, and pSNCA; (h) two or more of ST2, NSE, and BDNF; (i) two or more of GFAP, ST2, BDNF, and pSNCA; (j) two or more of NRGN, ST2, NSE, and vWF; (k) two or more of
  • a method of distinguishing an acute TBI from an age- related atrophy or brain disease in an elderly subject includes the steps of: (A) obtaining a biological sample from the elderly subject; (B) measuring the levels of one or more protein biomarkers present in the biological samples by immunoassay or mass spectroscopy, wherein the one or more protein biomarkers are selected from the group consisting of: brain derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), interleukin-6 (IL-6), metallothionein 3 (MT3), neurofilament light chain (NfL), neurogranin (NRGN), neuron specific enolase (NSE), synuclein alpha (SNCA), synuclein beta (SNCB), phosphorylated Ser129 SNCA (pS129- SNCA), soluble receptor for interleukin 33 (ST2), phosphorylated Thr181 tau (pT181 tau), phosphorylated Ser217 tau (p
  • the method may further include treating the elderly subject for an acute TBI when at least one increased level of the one or more biomarkers is detected.
  • the biological sample used may be selected from blood, plasma, serum, cerebrospinal fluid (CSF), tears or lacrimal fluid, urine, and saliva.
  • Two or more of the biomarkers used in step (A) may be selected from the group consisting of BDNF, GFAP, IL-6, MT3, NfL, NRGN, NSE, SNCA, SNCB, pS129-SNCA, sST2, pT181 tau, pS217 tau, pT231 tau, and vWF, and, optionally, one or more of ALDOC, FABP7, IL-7, and IL-33.
  • the biomarkers may include a panel selected from one of the following groups of biomarker combinations: (a) two or more of NRGN, ST2, NSE, and BDNF; (b) two or more of NRGN, NSE, BDNF, and vWF; (c) two or more of NRGN, ST2, vWF, and pSNCA; (d) two or more of GFAP, ST2, NSE, and BDNF; (e) two or more of GFAP ,NRGN, ST2, and pSNCA; (f) two or more of GFAP, NRGN, ST2, and BDNF; (g) two or more of GFAP, NRGN, and pSNCA; (h) two or more of ST2, NSE, and BDNF; (i) two or more of GFAP, ST2, BDNF, and pSNCA; (j) two or more of NRGN, ST2, NSE, and vWF; (k) two or more of GFAP,
  • a method of monitoring and treating a traumatic brain injury (TBI) over time in an elderly subject that sustained or is believed to have sustained a TBI includes the steps of: (A) obtaining a first biological sample from the subject at a first timepoint; (B) obtaining one or more subsequent biological samples from the same subject at one or more later timepoints; (C) detecting neurogranin (NRGN) levels in the first and subsequent one or more biological samples; (D) measuring the levels of NRGN in the first and subsequent one or more biological samples relative to a reference level of NRGN indicative of neurodegeneration; and (E) determining that subject has neurodegeneration and, optionally, treating the subject for neurodegeneration when the levels of NRGN at the one or more later timepoints remain increased relative to the reference levels.
  • NRGN neurogranin
  • a composition includes a solid substrate and a plurality of antibodies or antigen-binding fragments thereof immobilized on the substrate, wherein the antibodies, or antigen-binding fragments thereof, specifically and respectively bind to a plurality of protein biomarkers including three or more of Brain derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), Fatty acid binding protein 7 (FABP7), interleukin-6 (IL-6), metallothionein 3 (MT3), neurofilament light chain (NfL), neurogranin (NRGN), neuron specific enolase (NSE), synuclein alpha (SNCA), synuclein beta (SNCB), phosphorylated Ser129 SNCA (pS129-SNCA), soluble receptor for interleukin 33 (sST2), phosphorylated Thr181 tau (pT181 tau), phosphorylated Ser217 tau (pS217 tau), phosphorylated Thr231 tau (pTNF), Brain derived neurotrophic factor (
  • the solid substrate of the composition may include antibodies, or antigen-binding fragments thereof, specific for one or more combinations of protein biomarkers including: a) NRGN, ST2, NSE, and BDNF; (b) NRGN, NSE, BDNF, and vWF; (c) NRGN, ST2, vWF, and pSNCA; (d) GFAP, ST2, NSE, and BDNF; (e) GFAP ,NRGN, Patent Application Attorney Docket No.179.0009-WO00 ST2, and pSNCA; (f) GFAP, NRGN, ST2, and BDNF; (g) GFAP, NRGN, and pSNCA; (h) ST2, NSE, and BDNF; (i) GFAP, ST2, BDNF, and pSNCA; (j) NRGN, ST2, NSE, and vWF; (k) GFAP, NRGN, IL-6 and p181-Tau; (l)
  • a kit for detecting an acute TBI in an elderly subject includes one or more biomarker panels that distinguish traumatic brain injury from dementia , the one or more biomarker panels including three or more antibodies, or antigen-binding fragments thereof, that specifically and respectively bind to a plurality of protein biomarkers including one or more of brain derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), interleukin-6 (IL-6), metallothionein 3 (MT3), neurofilament light chain (NfL), neurogranin (NRGN), neuron specific enolase (NSE), synuclein alpha (SNCA), synuclein beta (SNCB), phosphorylated Ser129 SNCA (pS129-SNCA), soluble receptor for interleukin 33 (sST2), phosphorylated Thr181 tau (pT181-tau), phosphorylated Ser217 tau (pS217-tau), phosphorylated Thr2
  • BDNF brain derived neurotrophic
  • the one or more biomarker panels of the kit may include four or more biomarkers selected from the group consisting of BDNF, GFAP, IL-6, MT3, NfL, NRGN, NSE, SNCA, SNCB, pS129-SNCA, sST2, pT181 tau, pS217 tau, pT231-tau, and vWF, and, optionally, one or more of ALDOC , FABP7, IL-7, and IL-33.
  • the one or more biomarker panels of the kit may include antibodies or antigen-binding fragments thereof specifically bind to one of the following combinations of biomarkers: a) NRGN, ST2, NSE, and BDNF; (b) NRGN, NSE, BDNF, and vWF; (c) NRGN, ST2, vWF, and pSNCA; (d) GFAP, ST2, NSE, and BDNF; (e) GFAP ,NRGN, ST2, and pSNCA; (f) GFAP, NRGN, ST2, and BDNF; (g) GFAP, NRGN, and pSNCA; (h) ST2, NSE, and BDNF; (i) GFAP, ST2, BDNF, and pSNCA; (j) NRGN, ST2, NSE, and vWF; (k) GFAP, NRGN, IL-6 and p181-Tau; (l) NRGN, ST2, NSE, and
  • the kit may further include one or more pre-coated strip plates, one or more biotinylated secondary antibodies, one or more standard solutions, one or more assay controls, one or more buffer solutions, streptavidin-horse radish peroxidase (HRP), tetramethyl benzidine (TMB), one or more stop reagents, and detailed instructions for carrying out the kit assay.
  • HRP streptavidin-horse radish peroxidase
  • TMB tetramethyl benzidine
  • a method of testing an elderly subject suspected of having head injury to distinguish between traumatic brain injury (TBI) and dementia includes: (a) testing a bodily sample from the subject for an acute injury using one of more of the following biomarkers: soluble receptor for interleukin-33 (ST2), neurogranin (NRGN), Interleukin 6 (IL-6), and von Willebrand factor (vWF); (b) if the results of step (a) show an acute injury, testing the subject for an intracranial injury using one or more of the following biomarkers: GFAP and SNCB; and (c) If the results of steps (a) and (b) do not show an acute injury, Patent Application Attorney Docket No.179.0009-WO00 testing the subject for dementia using one or more of the following biomarkers: phosphorylated Thr181 tau (pT181 tau), IL-6, and brain derived neurotrophic factor (BDNF).
  • ST2 soluble receptor for interleukin-33
  • NRGN neurogranin
  • IL-6 Inter
  • the method may further include comparing levels of one or more of (i) ST2, NRGN, IL-6 and vWF and/or one or more of (ii) pT181-tau, IL-6, and BDNF in the elderly subject to the levels of the same biomarkers in trauma controls.
  • the trauma controls may be age-matched.
  • the level of pT181-tau may be increased and the level of at least one of IL-6 or BDNF may be decreased relative to the levels in the age-matched controls.
  • the method may further include treating the subject for an acute TBI injury if the results of the tests in steps a) and b) show an acute injury.
  • the elderly subject tested may be monitored over time, and the method may further include comparing levels of one or more of (i) ST2, NRGN, IL-6 and vWF and/or one or more of (ii) pT181-tau, IL-6, and BDNF in the subject at one or more successive timepoints to the levels of the same biomarkers in trauma controls or to the levels of the same biomarkers in the subject at an earlier timepoint.
  • the method may further include treating the subject for TBI injury if the level of pT181-tau increases over time.
  • the method may further include treating the elderly subject for dementia if the results of the testing in step c) show dementia.
  • FIG.1A shows plasma and serum concentrations of GFAP.
  • FIG.1B shows plasma and serum concentrations of NRGN.
  • FIG.1C shows plasma and serum concentrations of ST2.
  • FIG.1D shows plasma and serum concentrations of NSE.
  • FIG.1E shows plasma and serum concentrations of BDNF.
  • FIG.1F shows plasma and serum concentrations of SNCA.
  • FIG.1G shows plasma and serum concentrations of pSNCA.
  • FIG.1H shows plasma and serum concentrations of SNCB.
  • FIG.1I shows plasma and serum concentrations of NfL.
  • FIG.1J shows plasma and serum concentrations of vWF.
  • FIG.1K shows plasma and serum concentrations of MT3.
  • FIG.1L shows plasma and serum concentrations of IL-6.
  • FIG.1M shows plasma and serum concentrations of p181-tau.
  • FIG.1N shows plasma and serum concentrations of pS217-tau.
  • FIG.1O shows plasma and serum concentrations of pT231-tau.
  • FIGS.2A-J show distributions of biomarker blood level profiles in healthy controls (HC), trauma controls (TC), TBI, and Dementia cohorts across the following age brackets: 18-39 years (young adult) 40-64 years (middle aged adult), 65-74 years (late middle age, early geriatric adult), and 75 to 100 years (old age geriatric.
  • FIG.2A shows blood concentrations of GFAP.
  • FIG.2B shows blood concentrations of NSE.
  • FIG.2C shows blood concentrations of NRGN.
  • FIG.2D shows blood concentrations of BDNF.
  • FIG.2E shows blood concentrations of vWF.
  • FIG.2F shows blood concentrations of ST2.
  • FIG.2G shows blood concentrations of SNCA.
  • FIG.2H shows blood concentrations of pSNCA.
  • FIG.2I shows blood concentrations of SNCB.
  • FIG.2J shows blood concentrations of NfL.
  • FIGS.3A-O shows Bland-Altman plots for each of the 15 biomarkers analyzed, assessing the agreement between paired plasma and serum samples. Middle horizontal lines represent the mean difference between biofluids and the upper and lower lines represent limits with mean of the difference ⁇ 1.96x standard deviation of the mean of the difference. Proximity of the points to the mean difference line permits assessment of the agreement between the paired plasma and serum samples drawn from subjects simultaneously.
  • FIG.3A shows Bland-Altman plots for GFAP. Patent Application Attorney Docket No.179.0009-WO00
  • FIG.3B shows Bland-Altman plots for NRGN.
  • FIG.3C shows Bland-Altman plots for ST2.
  • FIG.3D shows Bland-Altman plots for NSE.
  • FIG.3E shows Bland-Altman plots for BDNF.
  • FIG.3F shows Bland-Altman plots for SNCA.
  • FIG.3G shows Bland-Altman plots for pSNCA.
  • FIG.3H shows Bland-Altman plots for SNCB.
  • FIG.3I shows Bland-Altman plots for NfL.
  • FIG.3J shows Bland-Altman plots for vWF.
  • FIG.3K shows Bland-Altman plots for MT3.
  • FIG.3L shows Bland-Altman plots for IL-6.
  • FIG.3M shows Bland-Altman plots for p181-tau.
  • FIG.3N shows Bland-Altman plots for pS217-tau.
  • FIG.3O shows Bland-Altman plots for pT231-tau.
  • FIG.4 shows trajectories of cognitive impairment measured after injury using digital health software. Individual patients are assigned 5-digit identifiers. Boxed graphs represent individuals had poor cognitive outcomes and/or did not recover.
  • FIGS.5A-C show directional changes in blood biomarker concentrations over time. Blood samples drawn 1-4 hours apart in the same subjects (multiple sampling for degree and direction of change).
  • FIG.5A shows blood concentrations of GFAP, NRGN, ST2, NSE, BDNF, NfL, vWF, MT3, and IL-6 (collectively: trauma control and mild TBI profile biomarkers) at T0 (first blood draw at initial emergency department presentation) and T1 (1-4 hours after T0) samples.
  • FIG.5B shows blood concentrations of pSNCA, SNCA, and SNCB (collectively: synuclein biomarkers) at T0 and T1 samples.
  • FIG.5C shows blood concentrations of p181-tau, pS217, and pT231-tau (collectively: tau biomarkers) at T0 and T1 samples.
  • FIGS.6A-6C show robust linear regression plots demonstrating significant directional changes in biomarker concentrations over 1-4 hours after injury (delta analysis) in geriatric subjects after mild TBI. Light- shaded lines bound by Delta characters indicate robust linear regression.
  • Fig.6A shows linear regression from T0 to T1 for BDNF.
  • Fig.6B shows linear regression from T0 to T1 for vWF.
  • Fig.6 C shows linear regression from T0 to T1 for pS217-tau .
  • FIGS.7A-7C show the overall appearance of biomarker distributions between injury types when age, preinjury status, and other factors are not considered. These data show the distributions of blood biomarker levels as measured by immunoassays in serum samples from enrolled trauma control and TBI subjects and from retrospective dementia samples, displayed according to study groups.
  • Fig.7A shows blood concentrations of GFAP, NRGN, ST2, NSE, BDNF, NfL, vWF, MT3, and IL-6 in dementia, trauma control, and mTBI subjects.
  • FIG.7B shows blood concentrations of pSNCA, SNCA, and SNCB (collectively: synuclein biomarkers) in dementia, trauma control, and mTBI subjects.
  • Fig.7C shows blood concentrations of p181-tau, pS217, and pT231-tau (collectively: tau biomarkers) in dementia, trauma control, and mTBI subjects.
  • FIGS.8A-8J show further analysis of biomarker distributions when separated by pre-injury cognitive impairment status (HC, TC normal, TC impaired, TBI negative normal, TBI positive normal, TBI positive impaired, and Dementia), using validated dementia assessments in the emergency medical setting.
  • FIG.8A shows plasma and serum concentrations of GFAP.
  • FIG.8B shows plasma and serum concentrations of NRGN.
  • FIG.8C shows plasma and serum concentrations of BDNF.
  • FIG.8D shows plasma and serum concentrations of NSE.
  • FIG.8E shows plasma and serum concentrations of vWF.
  • FIG.8F shows plasma and serum concentrations of ST2.
  • FIG.8G shows plasma and serum concentrations of SNCA.
  • FIG.8H shows plasma and serum concentrations of pSNCA.
  • FIG.8I shows plasma and serum concentrations of SNCB
  • FIG.8J shows plasma and serum concentrations of NfL.
  • Fig.9A shows the ROC curve for combined TC and TBI patients.
  • Fig.9B shows the ROC curve for TBI patients.
  • DETAILED DESCRIPTION [0047] The methods, compositions, and kits described herein are based on the discovery that changes in blood levels of certain protein biomarkers over time may distinguish acute TBI from other conditions in elderly patients that present similar symptoms as TBI.
  • TBI is an injury to the head that typically involves an acute mechanical event, in which sheer force, blunt force, or linear acceleration or deceleration damages brain tissue.
  • sheer force blunt force
  • linear acceleration or deceleration damages brain tissue.
  • Those having skill in the art appreciate that even individuals who are completely asymptomatic after a head injury can have symptoms or disabilities that develop over time, such as weeks to months after the initial injury. Late emerging deficits in patients can also result from multiple subclinical or sub-concussive head injuries.
  • biological samples from the patients are examined at several time points after the patient experiences or presents with TBI.
  • Certain protein biomarkers are detected in elevated (increased), acutely elevated, or decreased amounts, levels, or concentrations in the patient’s sample as well as are biomarkers that are involved with chronic degradative processes in the patient.
  • the methods in which these protein biomarkers are detected allow for determining the evolution of post- TBI responses and for arriving at an accurate molecular and anatomical picture of TBI in a patient across a given time course.
  • the term “about” as used herein means, in quantitative terms, plus or minus 5%, or in another embodiment, plus or minus 10%, or in another embodiment, plus or minus 15%, or in another embodiment, plus or minus 20%.
  • the term “one or more of” refers to combinations of various biomarkers. The term encompasses 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15 ,16 ,17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40... to N, where “N” is the total number of protein biomarkers and/or defined sets of protein biomarkers, in the particular embodiment.
  • the term also encompasses at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, at least 12, at least 13, at least 15 ,16 ,17, at least 18, at least 19, at least 20, at least 21, at least 22, at least 23, at least 24, at least 25, at least 26, at least 27, at least 28, at least 29, at least 30, at least 31, at least 32, at least 33, at least 34, at least 35, at least 36, at least 37, at least 38, at least 39, at least 40... to N.
  • biomarkers herein includes the phrase “one or more of” the biomarkers and, in particular, includes the “at least 1, at least 2, at least 3” and so forth language in each recited embodiment of a biomarker panel.
  • “Altered” as used herein can refer to an increase or decrease, as in, for example, an increase or decrease in biomarker concentrations or levels in a biological sample.
  • An increase is any positive change, e.g., by at least about 5%, 10%, or 20%; by at least about 25%, 50%, 75%, or even by 100%, 200%, 300% or more, Patent Application Attorney Docket No.179.0009-WO00 including values between the stated percentages.
  • a decrease is a negative change, e.g., a decrease by at least about 5%, 10%, or 20%; by at least about 25%, 50%, 75%; or even an increase by 100%, 200%, 300% or more, including values between the stated percentages.
  • the terms “comparing”, or “comparison” refers to assessing how the proportion, level or cellular localization of one or more biomarkers in a sample from a patient relates to the proportion, level or cellular localization of the corresponding one or more biomarkers in a standard or control sample.
  • comparing may refer to assessing whether the proportion, level, or cellular localization of one or more biomarkers in a sample from a patient is the same as, more or less than, or different from the proportion, level, or cellular localization of the corresponding one or more biomarkers in standard or control sample.
  • the term may refer to assessing whether the proportion, level, or cellular localization of one or more biomarkers in a sample from a patient is the same as, more or less than, different from or otherwise corresponds (or not) to the proportion, level, or cellular localization of predefined biomarker levels/ratios that correspond to, for example, a patient having a neurological injury or brain injury, not having a neurological injury or brain injury, is responding to treatment for a neurological injury or brain injury, is not responding to treatment for the neurological injury or brain injury, is/is not likely to respond to a particular treatment for the neurological injury or brain injury, or having /not having another disease or condition like, for example, dementia.
  • the term “comparing” refers to assessing whether the level of one or more biomarkers of embodiments of the invention in a sample from an individual is the same as, more or less than, different from or other otherwise corresponds (or not) to levels/ratios of the same biomarkers in a control sample (e.g., predefined levels/ratios that correlate to: Healthy individuals; Individuals with no neurological injury or brain injury, Individuals with a lesser degree of neurological injury or brain injury, standard brain injury levels/ratios, etc.; Individuals with a non-neurological or brain trauma injury; and Individuals with other types of neurological disorders (e.g., Dementia, Alzheimer’s Disease, etc.).
  • a control sample e.g., predefined levels/ratios that correlate to: Healthy individuals; Individuals with no neurological injury or brain injury, Individuals with a lesser degree of neurological injury or brain injury, standard brain injury levels/ratios, etc.; Individuals with a non-neurological or brain trauma injury; and Individuals with other types of
  • the terms “comparing”, or “comparison” refers to assessing how the proportion, level or cellular localization of one or more biomarkers in a sample from a patient relates to the proportion, level or tissue localization of another biomarker in the same sample. For example, a ratio of one biomarker to another from the same patient sample can be compared.
  • the terms “comparing”, or “comparison” refers to assessing how the proportion, level of one or more biomarkers in a sample from a subject relates to the proportion or level of one or more biomarkers in the same subject at one or more different timepoints.
  • the terms “indicates” or “correlates” in reference to a parameter, e.g., a modulated proportion, level, or cellular localization in a sample from a patient, may mean that the patient is improving, not improving, etc.
  • the parameter may include the level of one or more biomarkers as described herein. A particular set or pattern of the amounts of one or more biomarkers may indicate that a patient has improved or worsened.
  • brain injury refers to a condition in which the brain (central nervous system or neurological system) is damaged by injury caused by an event.
  • an “injury” is an alteration in cellular or molecular integrity, activity, level, robustness, state, or other alteration that is traceable to an event.
  • an injury includes a physical, mechanical, chemical, biological, functional, infectious, or other modulator of cellular or molecular characteristics.
  • An event can include a physical trauma such as a single or repetitive impact (percussive) or a biological abnormality such as a stroke resulting from either blockade or leakage of a blood vessel.
  • An event is optionally an infection by an infectious agent.
  • brain injury refers to a condition that results in central nervous system damage, irrespective of its pathophysiological basis. Among the most frequent origins of a “brain injury” are stroke and traumatic brain injury (TBI).
  • BBI traumatic brain injury
  • the term “brain injury” also refers to subclinical brain injury, spinal cord injury, and anoxic-ischemic brain injury.
  • the term “subclinical brain injury” (SCI) refers to brain injury without overt clinical evidence of brain injury. A lack of clinical evidence of brain injury when brain injury exists could result from degree of injury, type of injury, level of consciousness, medications particularly sedation and anesthesia.
  • brain injury status includes any distinguishable manifestation of brain injury, as the case may be, (e.g., TBI, mTBI or concussion), including not having brain injury.
  • brain injury status includes, without limitation, brain injury or non-injury in a patient, the stage or severity of brain injury, the progress of brain injury (e.g., progress of brain injury over time), or the effectiveness or response to treatment of brain injury (e.g., clinical follow up and surveillance of brain injury after treatment). Based on this status, further procedures may be indicated, including additional diagnostic tests or therapeutic procedures or regimens.
  • yielderly is understood by an individual of an ordinary skill in the art, for example, a clinician, based on various factors, which may not necessarily be based on chronological age, including, for example, general health, and familial history (e.g., genetics) of a subject and a diagnosis of dementia, Alzheimer’s, Parkinson’s or similar conditions (hereinafter “Elderly Conditions”).
  • An “elderly subject” refers to a subject who is at least 50 year old, and, more particularly, at least 65 years old; however, subjects younger than 50 who have any of Elderly Conditions or are suspected of having any of Elderly Conditions may be included as well.
  • the terms “elderly subject” and “geriatric subject” can be used interchangeably.
  • TBI traumatic brain injury
  • Symptoms of TBI can be mild (even imperceptible at first) and include headache, confusion, visual disturbances, and nausea. Signs of severe TBI include loss of consciousness exceeding six hours, convulsions, dilation of the pupils, and dizziness.
  • TBI is graded as mild (mild TBI or “mTBI”) meaning a brief change in mental status or consciousness), moderate, or severe (meaning an extended period of unconsciousness or amnesia after the injury) on the basis of the level of consciousness or Glasgow coma scale (GCS) score after resuscitation.
  • GCS Glasgow coma scale
  • Acute TBI refers to the period of TBI that extends from the time of injury through about the first three days.
  • Post-acute TBI refers to the period of TBI that extends from the acute period days and up to about one month after injury.
  • Non-traumatic brain injury refers to brain injuries that do not involve ischemia or external mechanical force (e.g., stroke, Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, multiple sclerosis, amyotrophic lateral sclerosis, brain hemorrhage, brain infections, brain tumor, among others).
  • mTBI traumatic brain injury
  • concussion refers to the occurrence of injury to the head or brain arising from blunt trauma or impact, or forceful motion of the head (acceleration or deceleration forces) causing one or more of the following conditions attributable to head injury: transient confusion, disorientation, or impaired consciousness; dysfunction of memory around the time of injury; or loss of consciousness lasting less than 30 minutes.
  • mTBI can last a year or more following the initial head or brain injury. While early mTBI symptoms may appear to be mild, they can lead to significant, life-long impairment in an individual’s ability to function physically, cognitively and psychologically.
  • concussion is used interchangeably with mTBI at times, concussions cover a clinical spectrum and may occur without loss of consciousness. Mild concussion may be present even if there is Patent Application Attorney Docket No.179.0009-WO00 no external sign of trauma to the head.
  • acute brain injury refers to the condition of a patient who has suffered a neurological or brain injury and at a relatively short number of hours, such as 1-10 hours, 1-8 hours, 1-5 hours, 2-5 hours, 3- 5 hours, 4-5 hours, and the like from the actual time of the injury.
  • sub-acute brain injury refers to the condition of a patient who has suffered a neurological or brain injury from about 2-5 days post injury.
  • chronic brain injury refers to the condition of a patient who has suffered a neurological or brain injury from about three days post injury until at least 12 months previously, or from about 1-5 months, or about 1-3 months from the actual time of injury yet continues to present symptoms of brain injury.
  • biomarker refers to a molecule that is associated either quantitatively or qualitatively with a biological change. Examples of biomarkers include polypeptides, proteins or fragments of a polypeptide or protein; and polynucleotides, such as a gene product, RNA or RNA fragment, or encoding polynucleotides; and other body metabolites.
  • a “biomarker” means a molecule (e.g., a protein) that is differentially present (i.e., increased or decreased) in a biological sample from a subject or a group consisting of subjects having a first phenotype (e.g., having a disease or condition) as compared to a biological sample from a subject or group consisting of subjects having a second phenotype (e.g., not having the disease or condition or having a less severe version of the disease or condition).
  • a first phenotype e.g., having a disease or condition
  • a second phenotype e.g., not having the disease or condition or having a less severe version of the disease or condition.
  • a biomarker may be differentially present at any level, but is generally present at a level that is decreased by at least 5%, by at least 10%, by at least 15%, by at least 20%, by at least 25%, by at least 30%, by at least 35%, by at least 40%, by at least 45%, by at least 50%, by at least 55%, by at least 60%, by at least 65%, by at least 70%, by at least 75%, by at least 80%, by at least 85%, by at least 90%, by at least 95%, or by 100% (i.e., absent); or that is increased by at least 5%, by at least 10%, by at least 15%, by at least 20%, by at least 25%, by at least 30%, by at least 35%, by at least 40%, by at least 45%, by at least 50%, by at least 55%, by at least 60%, by at least 65%, by at least 70%, by at least 75%, by at least 80%, by at least 85%, by at least 90%, by at least 95%, by Patent Application Attorney Docket
  • the differential presence of a biomarker can be characterized by a -fold change in level including, for example, a level that is decreased by 1.1-fold, at least 1.2-fold, at least 1.3-fold, at least 1.4-fold, at least 1.5-fold, at least 2.0-fold, at least 2.5-fold, at least 3.0-fold, at least 3.5-fold, at least 4.0-fold, at least 5-fold, at least 5.5-fold, at least 6-fold, at least 6.5-fold, at least 7.0-fold, at least 7.5-fold, at least 8.0-fold, at least 9-fold, at least 10-fold, at least 11-fold, at least 12-fold, at least 13-fold, at least 14-fold, at least 15-fold, at least 16- fold, at least 17-fold, at least 18-fold, at least 19-fold, at least 20-fold, at least 25-fold, at least 30-fold, at least 40-fold, or at least 50-fold; or that is increased by 1.1-fold, at least 1.2-fold,
  • a biomarker is preferably differentially present at a level that is statistically significant (e.g., a p-value less than 0.05 and/or a q-value of less than 0.10 as determined using, for example, either Welch’s T-test or Wilcoxon’s rank-sum Test).
  • the term “peptide biomarkers derived therefrom” includes the isoforms and/or post-translationally modified forms of any of the foregoing.
  • Embodiments of the invention contemplate the detection, measurement, quantification and/or determination or other analysis of both unmodified and modified (e.g., citrullination or other post-translational modification) proteins/polypeptides/peptides, as well as autoantibodies to any of the foregoing.
  • the method includes the detection, measurement, quantification and/or determination or other analysis of both unmodified and modified forms of Aldolase C (ALDOC), BDNF, GFAP, IL-6, MT3, NfL, NRGN, NSE, SNCA, SNCB, pS129-SNCA, sST2, pT181 tau, pS217 tau, pT231 tau, and/or vWF.
  • ADOC Aldolase C
  • BDNF BDNF
  • GFAP GFAP
  • IL-6 MT3
  • NfL NRGN
  • NSE NRGN
  • NRGN NRGN
  • NSE SNCA
  • SNCB pS129-SNCA
  • sST2 pT181 tau
  • pS217 tau pT231 tau
  • vWF vWF.
  • a biomarker panel may include vWF and one or more of NRGN, BDNF, and FABP7.
  • Patent Application Attorney Docket No.179.0009-WO00 [0073]
  • a particular set or pattern of the amounts of one or more biomarkers may be correlated to a patient being unaffected (i.e., indicates a patient does not have brain injury).
  • “indicating,” or “correlating,” as used according to embodiments of the invention may be by any linear or non-linear method of quantifying the relationship between levels/ratios of biomarkers to a standard, control or comparative value for the assessment of the diagnosis, prediction of a neurological injury, brain injury or progression thereof, assessment of efficacy of clinical treatment, identification of a patient who may respond to a particular treatment regime or pharmaceutical agent, monitoring of the progress of treatment, and in the context of a screening assay, for the identification of a therapeutic for the neurological injury or brain injury.
  • Magnetic resonance imaging (MRI)” of the brain is a noninvasive and painless neuroimaging test for detailed visualization and analysis that uses a magnetic field and radio waves to produce detailed images of the brain and the brain stem.
  • a CAT scan also called a CT scan; computed axial tomography scan
  • an MRI scan does not use radiation.
  • a dye (contrast dye) or contrast material e.g., iodine, barium, or gadolinium
  • the dye may show blood flow and areas of inflammation or edema.
  • the method detects changed or altered blood-brain barrier permeability signals in the brain by using Dynamic Contrast Enhanced MRI (DCE-MRI).
  • DCE-MRI Dynamic Contrast Enhanced MRI
  • MRI is used to detect changed or altered blood-brain barrier permeability signals in the brain.
  • diffusion weighted tensor imaging DTI-MRI
  • JD Jacobian determinant
  • variations of either T1-weighted or T2-weighted MRI methods are used to measure or quantify the number of microhemorrhages or to calculate a sum or overall hemorrhage burden value.
  • the terms “patient,” “individual,” or “subject” are used interchangeably herein, and refer to a mammal, particularly, a human. The patient may have a mild, intermediate or severe disease or condition. The patient may be an individual in need of treatment or in need of diagnosis based on particular symptoms or personal or family history. In some cases, the terms may refer to treatment in experimental animals, in veterinary application, and in the development of animal models for disease, including, but not limited to, rodents including mice, rats, and hamsters; and primates.
  • the terms “measuring” and “determining” are used interchangeably throughout and refer to methods which include obtaining or providing a patient sample and/or detecting the level (or amount) of a biomarker(s) in a sample. In one embodiment, the terms refer to obtaining or providing a patient sample and detecting the Patent Application Attorney Docket No.179.0009-WO00 level of one or more biomarkers in the sample. In another embodiment, the terms “measuring” and “determining” mean detecting the level of one or more biomarkers in a patient sample.
  • sample is also used interchangeably throughout with the term “detecting.” In certain embodiments, the term is also used interchangeably with the term “quantifying.”
  • sample encompasses a variety of sample types obtained from a patient, individual, or subject and can be used in a diagnostic, screening, or monitoring assay.
  • the patient sample may be obtained from a healthy subject, or a patient suspected of having or having associated symptoms of neurological injury or brain injury.
  • a sample obtained from a patient can be divided, and only a portion may be used for diagnosis.
  • the sample, or a portion thereof can be stored under conditions to maintain sample for later analysis.
  • sample specifically encompasses blood, serum, plasma, cerebrospinal fluid (CSF) and other liquid samples of biological origin, including, but not limited to, peripheral blood, blood plasma, serum, cerebrospinal fluid, amniotic fluid, tears, urine, saliva, stool, semen, sweat, secretions and synovial fluid.
  • CSF cerebrospinal fluid
  • a sample also encompasses solid tissue samples, such as a biopsy specimen or cells derived therefrom, or tissue culture cells and the progeny thereof.
  • a tissue or cell sample may be processed (e.g., homogenized, etc.) to produce a suspension or dispersion in liquid form, as discussed below.
  • a sample includes a blood sample.
  • a sample includes a plasma sample.
  • a serum sample is used.
  • a sample includes cerebrospinal fluid.
  • sample also includes samples that have been manipulated in any way after their procurement, such as by centrifugation, filtration, precipitation, dialysis, chromatography, treatment with reagents, washed, or enriched for certain cell populations.
  • the terms further encompass a clinical sample, and includes cells in culture, cell supernatants, tissue samples, organs, and the like. Samples may also include fresh- frozen and/or formalin-fixed, paraffin-embedded tissue blocks, such as blocks prepared from clinical or pathological biopsies, prepared for pathological analysis or study by immunohistochemistry.
  • a sample may be tested immediately after collection, or it may be tested after storage at 4°C, -20°C, or -80°C. Storage times may be 24 hours, 1 week, 1 month, 1 year, 10 years or up to 30 years, depending on stability of the sample and storage conditions.
  • Various methodologies of the embodiments of the invention include a step that involves comparing a value, level, feature, characteristic, property, etc. to a “suitable control,” referred to interchangeably herein as an “appropriate control,” a “control sample,” a “reference” or simply a “control.”
  • a “suitable control,” “appropriate control,” “control sample,” “reference” or a “control” is any control or standard familiar to one of ordinary skill in the art useful for comparison purposes.
  • a “reference level” of a biomarker means a level of the biomarker that is indicative of a particular disease state, phenotype, or lack thereof, as well as combinations of Patent Application Attorney Docket No.179.0009-WO00 disease states, phenotypes, or lack thereof.
  • a “positive” reference level of a biomarker means a level that is indicative of a particular disease state or phenotype.
  • a “negative” reference level of a biomarker means a level that is indicative of a lack of a particular disease state or phenotype.
  • a “brain injury-positive reference level” of a biomarker means a level of a biomarker that is indicative of brain injury in a subject
  • a “brain injury-negative reference level” of a biomarker means a level of a biomarker that is indicative of no brain injury of in a subject.
  • a “reference level” of a biomarker may be an absolute or relative amount or concentration of the biomarker, a presence or absence of the biomarker, a range of amount or concentration of the biomarker, a minimum and/or maximum amount or concentration of the biomarker, a mean amount or concentration of the biomarker, and/or a median amount or concentration of the biomarker; and, in addition, “reference levels” of combinations of biomarkers may also be ratios of absolute or relative amounts or concentrations of two or more biomarkers with respect to each other.
  • Appropriate positive and negative reference levels of biomarkers for a particular disease state, phenotype, or lack thereof may be determined by measuring levels of desired biomarkers in one or more appropriate subjects, and such reference levels may be tailored to specific populations of subjects (e.g., a reference level may be age-matched so that comparisons may be made between biomarker levels in samples from subjects of a certain age and reference levels for a particular disease state, phenotype, or lack thereof in a certain age group). Such reference levels may also be tailored to specific techniques that are used to measure levels of biomarkers in biological samples (e.g., ELISA, PCR, LC-MS, GC-MS, etc.), where the levels of biomarkers may differ based on the specific technique that is used.
  • a “suitable control” or “appropriate control” is a value, level, feature, characteristic, property, etc., determined in an individual or biological sample obtained from an individual or group of individuals, (e.g., a control or normal cell, organ, or patient, exhibiting, for example, normal traits.
  • the biomarkers of the embodiments of the invention may be assayed for levels/ratios in a sample from an unaffected individual (UI) (e.g., no brain injury) or a normal control individual (NC) (both terms are used interchangeably herein).
  • UI unaffected individual
  • NC normal control individual
  • a “suitable control” or “appropriate control” can be a value, level, feature, characteristic, property, ratio, etc.
  • a “suitable control” or “appropriate control” is a predefined value, level, feature, characteristic, property, ratio, etc.
  • a “suitable control” can be a profile or pattern of levels/ratios of one or more biomarkers of embodiments of the invention that correlates to brain injury, to which a patient sample can be compared. The patient sample can also be compared to a negative control, i.e., a profile that correlates to not having brain injury.
  • the term “predetermined threshold value of expression” of a biomarker refers to the level of expression of the same biomarker (expressed, for example, in ng/ml) in a corresponding control/normal sample or group consisting of control/normal samples obtained from normal, or healthy, subjects, i.e., subject who do not have brain injury.
  • the term “altered level of expression” of a biomarker in a sample refers to a level that is either below or above the predetermined threshold value of expression for the same biomarker and thus encompasses either high (increased) or low (decreased) expression levels.
  • the biomarkers described herein are increased or decreased relative to age-matched (and/or sex-matched) controls.
  • the terms “specifically binds to,” “specific for,” and related grammatical variants refer to that binding which occurs between such paired species as enzyme/substrate, receptor/agonist, antibody/antigen, aptamer/target, and lectin/carbohydrate which may be mediated by covalent or non-covalent interactions or a combination of covalent and non-covalent interactions.
  • the binding which occurs is typically electrostatic, hydrogen-bonding, or the result of lipophilic interactions.
  • “specific binding” occurs between a paired species where there is interaction between the two which produces a bound complex having the characteristics of an antibody/antigen or enzyme/substrate interaction.
  • the specific binding is characterized by the binding of one member of a pair to a particular species and to no other species within the family of compounds to which the corresponding member of the binding member belongs.
  • an antibody typically binds to a single epitope and to no other epitope within the family of proteins.
  • specific binding between an antigen and an antibody will have a binding affinity of at least 10 -6 M.
  • the antigen and antibody will bind with affinities of at least 10-7 M, 10-8 M to 10-9 M, 10-10 M, 10 -11 M, or 10 -12 M.
  • affinities of at least 10-7 M, 10-8 M to 10-9 M, 10-10 M, 10 -11 M, or 10 -12 M.
  • specific binding or “specifically binding” when used in reference to the interaction of an antibody and a protein or peptide means that the interaction is dependent upon the presence of a particular structure (i.e., the epitope) on the protein.
  • antibody means any immunoglobulin polypeptide, or fragment thereof, having immunogen or antigen binding ability.
  • antibody fragments refer to a portion of an intact antibody, in particular, an immunogen- or antigen-binding portion of the antibody.
  • antibody fragments include, but are not limited to, linear antibodies; single-chain antibody molecules; Fc or Fc’ peptides, Fab and Fab fragments, and multi-specific antibodies formed from antibody fragments.
  • the terms also refer to fragments that bind an antigen of a target molecule (e.g., a protein biomarker described herein) and can be referred to as “antigen-binding fragments.”
  • the term “antibody” is used in reference to any immunoglobulin molecule that reacts with a specific antigen.
  • any immunoglobulin e.g., IgG, IgM, IgA, IgE, IgD, etc.
  • Patent Application Attorney Docket No.179.0009-WO00 obtained from any source (e.g., humans, rodents, non-human primates, caprines, bovines, equines, ovines, etc.).
  • Specific types/examples of antibodies include polyclonal, monoclonal, humanized, chimeric, human, or otherwise-human-suitable antibodies.
  • Antibodies also includes any fragment or derivative of any of the herein described antibodies that specifically binds the target antigen.
  • an effective amount means the amount of a required to ameliorate the symptoms of a disease relative to an untreated patient.
  • the effective amount of active compound(s) used to practice embodiments of the invention for therapeutic treatment of brain injury varies depending upon the manner of administration, the age, body weight, and general health of the subject. Ultimately, the attending physician or veterinarian will decide the appropriate amount and dosage regimen. Such amount is referred to as an “effective” amount.
  • an effective amount As used herein and in the appended claims, the singular forms “a,” “an,” and “the” include the plural reference unless the context clearly dictates otherwise. Thus, for example, a reference to a “protein” is a reference to one or more proteins, and includes equivalents thereof known to those skilled in the art and so forth.
  • biomarkers may be detected and/or measured by immunoassay.
  • An immunoassay requires biospecific capture reagents/binding agents, such as antibodies, to capture the biomarkers. Many antibodies are available commercially. Antibodies also can be produced by methods well known in the art, e.g., by immunizing animals with the biomarkers. Biomarkers can be isolated from samples based on their binding characteristics. Alternatively, if the amino acid sequence of a polypeptide biomarker is known, the polypeptide can be synthesized and used to generate antibodies by methods well- known in the art.
  • Detection methods suitable for use methods of the invention include, without limitation, traditional immunoassays including, for example, sandwich immunoassays including enzyme-linked immunosorbent assays (ELISA) or fluorescence-based immunoassays, immunoblots, Western Blots (WB), as well as other enzyme immunoassays. Multiplex ELISA assays are also suitable for use. Nephelometry is an assay performed in Patent Application Attorney Docket No.179.0009-WO00 liquid phase, in which antibodies are in solution. The binding of a protein antigen to a specific antibody results in changes in absorbance, a parameter that is measured.
  • traditional immunoassays including, for example, sandwich immunoassays including enzyme-linked immunosorbent assays (ELISA) or fluorescence-based immunoassays, immunoblots, Western Blots (WB), as well as other enzyme immunoassays. Multiplex ELISA assays are also suitable for use.
  • Nephelometry is an
  • a biospecific capture reagent for the biomarker is attached to the surface of an MS probe, such as a pre-activated protein chip array.
  • the biomarker is then specifically captured on the biochip through this reagent, and the captured biomarker is detected by mass spectrometry.
  • the expression levels of the biomarkers employed herein are quantified by immunoassay, such as ELISA technology.
  • the levels of expression of the biomarkers are determined by contacting the biological sample with a plurality of antibodies, or antigen binding fragments thereof, that selectively bind to the biomarkers; and detecting binding of the antibodies, or antigen binding fragments thereof, to the biomarkers.
  • the binding agents employed in the disclosed methods and compositions are labeled with a detectable moiety.
  • the level of a biomarker in a sample can be assayed by contacting the biological sample with an antibody, or antigen binding fragment thereof, that selectively binds to the target biomarker (referred to as a capture molecule or antibody or a binding agent), and detecting the binding of the antibody, or antigen- binding fragment thereof, to the biomarker.
  • the detection can be performed using a second antibody to bind to the capture antibody complexed with its target biomarker.
  • a target biomarker can be an entire protein, or a variant or modified form thereof.
  • Kits for the detection of biomarkers as described herein can include pre- coated strip plates, biotinylated secondary antibody, standards, controls, buffers, streptavidin-horse radish peroxidase (HRP), tetramethyl benzidine (TMB), stop reagents, and detailed instructions for carrying out the tests including performing standards. Further embodiments of the invention provide compositions that can be employed in the disclosed methods.
  • compositions include a solid substrate and a plurality of antibodies, commonly known in the art as a “panel” of antibodies, that are immobilized on the substrate, wherein each of the antibodies is immobilized at a different, indexable, location on the substrate and the antibodies selectively bind to a plurality of biomarkers present in a biological sample.
  • Panels of the invention may include antibodies or antigen-binding fragments to specifically detect 2 or more, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more, 9 or more, 10 or more, 11 or more, 12 or more, 13 or more, 14 or more, 15 or more, 16 or more, 17 or more, 18 or more, 19 or more, 20 or more, 30 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 or more, 90 or more, or 100 or more, biomarkers.
  • the one of more protein biomarkers may include a panel that includes 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15 of the following biomarkers: NRGN, ST2, NSE, BDNF; NRGN, NSE, BDNF, vWF; NRGN, ST2, vWF, pSNCA; GFAP, ST2, NSE, BDNF; GFAP, NRGN, ST2, pSNCA; GFAP, NRGN, ST2, BDNF; GFAP, NRGN, pSNCA; ST2, NSE, BDNF; GFAP, ST2, BDNF, pSNCA; NRGN, ST2, NSE, BDNF; GFAP, ST2, BDNF, pSNCA; NRGN, ST2, NSE, and vWF.
  • a biomarker panel of the invention may include antibodies specific for one or more of the following sets of (a) NRGN, ST2, NSE, and BDNF; (b) NRGN, NSE, BDNF, and vWF; (c) NRGN, ST2, vWF, and pSNCA; (d) GFAP, ST2, NSE, and BDNF; (e) GFAP ,NRGN, ST2, and pSNCA; (f) GFAP, NRGN, ST2, and BDNF; (g) GFAP, NRGN, and pSNCA; (h) ST2, NSE, and BDNF; (i) GFAP, ST2, BDNF, and pSNCA; (j) NRGN, ST2, NSE, and vWF; (k) GFAP, NRGN, IL-6 and p181- Tau; (l) NRGN, ST2, NSE, and SNCA; (m) GFAP, NRGN, IL,
  • Solid phase substrates, or carriers, that can be effectively employed in such assays are well known to those of skill in the art and include, for example, 96-well microtiter plates, glass, paper, and microporous membranes constructed, for example, of nitrocellulose, nylon, polyvinylidene difluoride, polyester, cellulose acetate, mixed cellulose esters and polycarbonate.
  • Suitable microporous membranes include, for example, those described in U.S. Patent Application Publication No. U.S.2010/0093557 A1.
  • Methods for performing assays employing such panels include those described, for example, in U.S. Patent Application Publication Nos.
  • methods for assessing brain injury, e.g., mTBI or concussion, in a subject including: (a) contacting a biological sample obtained from the subject with a composition disclosed herein for a period of time sufficient to form binding agent-polypeptide biomarker complexes; (b) detecting binding of the plurality of binding agents to the plurality of polypeptide biomarkers in the protein biomarker panel, thereby determining the levels of expression of the plurality of polypeptide biomarkers in the biological sample; and (c) comparing the levels of expression of the plurality of polypeptide biomarkers in the biological sample with predetermined threshold values, wherein levels of expression of at least one of the plurality of polypeptide biomarkers above or below the predetermined threshold values indicates brain injury status in the subject.
  • Flow cytometric multiplex arrays in several different formats based on the utilization of, for example, flow cytometry, chemiluminescence or electron-chemiluminescence technology, can be used.
  • Flow cytometric multiplex arrays also known as bead-based multiplex arrays, include the Cytometric Bead Array (CBA) system from BD Biosciences (Bedford, Mass.), and several bead based microfluidics cassette systems, for rapid immunological Patent Application Attorney Docket No.179.0009-WO00 testing suitable for point of care solutions, spinning disc based microfluidics technologies using antibody-bead conjugates such as Quanterix Simoa assays or SpinDisc assays, and multi-analyte profiling (xMAP®) technology from Luminex Corp.
  • CBA Cytometric Bead Array
  • xMAP® multi-analyte profiling
  • each bead set is coated with a specific capture antibody.
  • Fluorescence or streptavidin-labeled detection antibodies bind to specific capture antibody-biomarker complexes formed on the bead set. Multiple biomarkers can be recognized and measured by differences in the bead sets, with chromogenic or fluorogenic emissions being detected using flow cytometric analysis.
  • a multiplex ELISA from Quansys Biosciences (Logan, Utah) coats multiple specific capture antibodies at multiple spots (one antibody at one spot) in the same well on a 96-well microtiter plate.
  • biomarkers may be detected by mass spectrometry, a method that employs a mass spectrometer to detect gas phase ions.
  • mass spectrometers are time-of- flight, magnetic sector, quadrupole filter, ion trap, ion cyclotron resonance, OrbitrapTM, hybrids or combinations of the foregoing, and the like.
  • biomarkers are detected using SRM (Selected Reaction Monitoring), MRM (Multiple Reaction Monitoring), and PRM (Parallel Reaction Monitoring), which are all targeted analysis techniques used to specifically quantify pre-selected peptides or molecules within a complex sample such as a biospecimen.
  • SRM Selected Reaction Monitoring
  • MRM Multiple Reaction Monitoring
  • PRM Parallel Reaction Monitoring
  • SRM Selected reaction monitoring
  • MRM Multiple Reaction Monitoring
  • PRM Parallel Reaction Monitoring
  • SRM Selected reaction monitoring
  • SRM is a non-scanning mass spectrometry technique, performed on triple quadrupole-like instruments and in which collision-induced dissociation is used as a means to increase selectivity.
  • two mass analyzers are used as static mass filters, to monitor a particular fragment ion of a selected precursor ion.
  • the specific pair of mass-over-charge (m/z) values associated to the precursor and fragment ions selected is referred to as a “transition” and can be written as parent m/z ⁇ fragment m/z (e.g., 673.5 ⁇ 534.3).
  • m/z mass-over-charge
  • the detector acts as a counting device for the ions matching the selected transition thereby returning an intensity distribution over time.
  • Multiple SRM transitions can be measured within the same experiment on the chromatographic time scale by rapidly toggling between the different precursor/fragment pairs (sometimes called multiple reaction monitoring, MRM).
  • the triple quadrupole instrument cycles through a series of transitions and records the signal of each transition as a function of the elution time.
  • the method allows for additional selectivity by monitoring the chromatographic co-elution of multiple transitions for a given analyte.
  • SRM/MRM are occasionally used also to describe experiments conducted in mass spectrometers other than triple quadrupoles (e.g., in trapping Patent Application Attorney Docket No.179.0009-WO00 instruments) where upon fragmentation of a specific precursor ion a narrow mass range is scanned in MS2 mode, centered on a fragment ion specific to the precursor of interest or in general in experiments where fragmentation in the collision cell is used as a means to increase selectivity.
  • MRM protein methyl mesenchymal RNA
  • SRM mass spectrometer operating principle
  • PRM is a similar method to detect and quantify target molecules where all forms are detected in parallel. MRM, SRM and PRM all allow relative and absolute quantification of proteins, peptides and metabolites.
  • MRM is used throughout the text, but the term includes SRM, MRM, PRM, as well as any analogous technique, such as e.g.
  • hSRM highly-selective reaction monitoring
  • LC-SRM or any other SRM/MRM-like or SRM/MRM-mimicking approaches performed on any type of mass spectrometer and/or, in which the peptides are fragmented using any other fragmentation method such as e.g. CAD (collision-activated dissociation (also known as CID or collision-induced dissociation), HCD (higher energy CID), ECD (electron capture dissociation), PD (photodissociation) or ETD (electron transfer dissociation).
  • CAD collision-activated dissociation
  • HCD higher energy CID
  • ECD electron capture dissociation
  • PD photodissociation
  • ETD electrostatic transfer dissociation
  • the mass spectrometric method includes matrix assisted laser desorption/ionization time-of-flight (MALDI-TOF MS or MALDI-TOF).
  • method includes MALDI-TOF tandem mass spectrometry (MALDI-TOF MS/MS).
  • mass spectrometry can be combined with another appropriate method(s) as may be contemplated by one of ordinary skill in the art.
  • MALDI-TOF can be utilized with trypsin digestion and tandem mass spectrometry as described herein.
  • a mass spectrometric technique includes surface enhanced laser desorption and ionization or “SELDI,” as described, for example, in U.S.
  • SELDI refers to a method of desorption/ionization gas phase ion spectrometry (e.g., mass spectrometry) in which an analyte (here, one or more of the biomarkers) is captured on the surface of a SELDI mass spectrometry probe.
  • analyte here, one or more of the biomarkers
  • SELDI mass spectrometry probe There are several versions of SELDI that may be utilized including, but not limited to, Affinity Capture Mass Spectrometry (also called Surface-Enhanced Affinity Capture (SEAC)), and Surface-Enhanced Neat Desorption (SEND) which involves the use of probes including energy absorbing molecules that are chemically bound to the probe surface (SEND probe).
  • SEAC Surface-Enhanced Affinity Capture
  • SEND Surface-Enhanced Neat Desorption
  • SELDI Surface-Enhanced Photolabile Attachment and Release
  • SEPAR Surface-Enhanced Photolabile Attachment and Release
  • SEPAR and other forms of SELDI are readily adapted to detecting a biomarker or biomarker panel, pursuant to the invention.
  • the biomarkers can be first captured on a chromatographic resin having chromatographic properties that bind the biomarkers.
  • a chromatographic resin having chromatographic properties that bind the biomarkers.
  • a cation exchange resin such as CM Ceramic HyperD® F resin
  • wash the resin elute the biomarkers and detect by MALDI.
  • this method could be preceded by fractionating the sample on an anion exchange resin before application to the cation exchange resin.
  • biomarkers may be detected by means of an electrochemiluminescence assay developed by Meso Scale Discovery. Electrochemiluminescence detection uses labels that emit light when electrochemically stimulated. Background signals are minimal because the stimulation mechanism (electricity) is decoupled from the signal (light). Labels are stable, non-radioactive and offer a choice of convenient coupling chemistries.
  • TBI biomarkers may be detected by other suitable methods known in the art.
  • Detection paradigms which may be employed to this end, include optical methods, electrochemical methods (voltammetry and amperometry techniques), atomic force microscopy, and radio frequency methods, e.g., multipolar resonance spectroscopy.
  • a sample such as a sample containing the protein biomarkers described herein, may also be analyzed by means of a biochip.
  • Biochips generally include solid substrates and have a generally planar surface, to which a capture reagent (also called an adsorbent or affinity reagent) is Patent Application Attorney Docket No.179.0009-WO00 attached. Frequently, the surface of a biochip includes a plurality of addressable locations, each of which has the capture reagent bound there.
  • Protein biochips are biochips adapted for the capture of polypeptides. Many protein biochips are described in the art. These include, for example, protein biochips produced by Ciphergen Biosystems, Inc.
  • SIMOATM single-molecule arrays
  • QuanterixTM e.g., as provided by QuanterixTM, Lexington, MA
  • Femtomolar (fg/mL) concentrations of proteins can be measured in a SIMOA bead-based immunoassay, which involves arrays of femtoliter-sized reaction chambers that can isolate and detect single protein molecules.
  • the power of a diagnostic test to correctly predict TBI status is commonly measured as the sensitivity of the assay, the specificity of the assay or the area under a receiver operated characteristic (“ROC”) curve.
  • Sensitivity is the percentage of true positives that are predicted by a test to be positive, while specificity is the percentage of true negatives that are predicted by a test to be negative.
  • a ROC curve provides the sensitivity of a test as a function of 1-specificity. The greater the area under the ROC curve, the more powerful the predictive value of the test. Other useful measures of the utility of a test are positive predictive value and negative predictive value.
  • biomarker panels may show a statistical difference in different brain injury statuses of at least p ⁇ 0.05, p ⁇ 10 -2 , p ⁇ 10 -3 , p ⁇ 10 -4 or p ⁇ 10 -5 . Diagnostic tests that use these biomarkers may show an ROC of at least 0.6, at least about 0.7, at least about 0.8, or at least about 0.9.
  • the biomarkers may be differentially present in biological samples from uninjured (UI) control subjects (healthy controls (HC) or non-brain injury controls, (e.g., age-matched HC), trauma control subjects (e.g., age-matched orthopedic injury subjects without intracranial injury, often abbreviated TC), and biological samples from subjects with a brain injury, and, thus, are useful in aiding in the determination of brain injury status.
  • biomarkers are measured in a patient sample using the methods described herein and compared, for example, to predefined biomarker levels/ratios and correlated to brain Patent Application Attorney Docket No.179.0009-WO00 injury status.
  • the measurement(s) may then be compared with a relevant diagnostic amount(s), cut-off(s), or multivariate model scores that distinguish a positive brain injury status from a negative brain injury status.
  • the diagnostic amount(s) represents a measured amount of a biomarker(s) above which or below which a patient is classified as having a particular brain injury status. For example, if the biomarker(s) is/are upregulated compared to normal, then a measured amount(s) above (or greater than) the diagnostic cutoff(s) provides an assessment of brain injury status. Alternatively, if the biomarker(s) is/are down-regulated, then a measured amount(s) at or below the diagnostic cutoff(s) provides an assessment of brain injury status.
  • the particular diagnostic cut-off(s) used in an assay by adjusting the particular diagnostic cut-off(s) used in an assay, one can increase sensitivity or specificity of the diagnostic assay depending on the preference of the diagnostician.
  • the particular diagnostic cut-off can be determined, for example, by measuring the levels of biomarkers in a statistically significant number of samples from patients with the different brain injury statuses and drawing the cut-off to suit the desired levels of specificity and sensitivity.
  • the relative or normalized amounts of biomarkers to each other are useful in aiding in the determination of brain injury status.
  • the biomarker ratios are indicative of diagnosis.
  • a biomarker ratio can be compared to another biomarker ratio in the same sample or to a set of biomarker ratios from a control or reference sample.
  • the measured values (i.e., levels) of the biomarkers detected by a biomarker panel are mathematically combined and the combined value is correlated to the underlying diagnostic question. Biomarker values may be combined by any appropriate state of the art mathematical method.
  • Mathematical methods useful for correlating a marker combination to a brain injury status employ methods like discriminant analysis (DA) (e.g., linear-, quadratic-, regularized-DA), Discriminant Functional Analysis (DFA), Kernel Methods (e.g., SVM), Multidimensional Scaling (MDS), Nonparametric Methods (e.g., k- Nearest-Neighbor Classifiers), PLS (Partial Least Squares), Tree-Based Methods (e.g., Logic Regression, CART, Random Forest Methods, Boosting/Bagging Methods), Generalized Linear Models (e.g., Logistic Regression), Principal Components based Methods (e.g., SIMCA), Generalized Additive Models, Fuzzy Logic based Methods, Neural Networks and Genetic Algorithms based Methods.
  • DA discriminant analysis
  • DFA Discriminant Functional Analysis
  • Kernel Methods e.g., SVM
  • MDS Multidimensional Scaling
  • the method used in correlating a biomarker combination of the invention is selected from DA (e.g., Linear-, Quadratic-, Regularized Discriminant Analysis), DFA, Kernel Methods (e.g., SVM), MDS, Nonparametric Methods (e.g., k-Nearest-Neighbor Classifiers), PLS (Partial Least Squares), Tree-Based Methods (e.g., Logic Regression, CART, Random Forest Methods, Boosting Methods), or Generalized Linear Models (e.g., Logistic Regression), and Principal Components Analysis.
  • DA e.g., Linear-, Quadratic-, Regularized Discriminant Analysis
  • DFA Kernel Methods
  • MDS Nonparametric Methods
  • PLS Partial Least Squares
  • Tree-Based Methods e.g., Logic Regression, CART, Random Forest Methods, Boosting Methods
  • Generalized Linear Models e.g., Logistic Re
  • the risk of brain injury is determined by measuring the relevant biomarkers in a protein biomarker panel, and then either submitting them to a classification algorithm or comparing them with a reference amount, i.e., a predefined level or pattern of biomarkers that is associated with the particular risk level. Determining Severity of Brain Injury [0112] In some embodiments of the invention, methods are provided for determining the severity of brain injury, e.g., TBI, mTBI, in a patient. Each grade or stage of brain injury likely has a characteristic level of a biomarker or relative levels/ratios of a set of biomarkers (a pattern or ratio).
  • the severity of brain injury is determined by measuring the relevant biomarkers and then either submitting them to a classification algorithm or comparing them with a reference amount, i.e., a predefined level or pattern of biomarkers that is associated with the particular stage.
  • severity of brain injury e.g., TBI
  • Neuroimaging analysis e.g., using contrast MRI, allows for the detection and visualization of injury such as bleeding, hemorrhage, or other insult or damage to the integrity to the brain, white matter, axons, fascicles, fiber tracts, or its blood-brain barrier.
  • Determining Brain Injury Prognosis [0113]
  • methods are provided for determining the course of brain injury, e.g., TBI, mTBI or concussion, in a patient, e.g., a patient who has experienced repetitive injury.
  • Brain injury course refers to changes in brain injury status over time, including brain injury progression (worsening) and brain injury regression (improvement).
  • a method involves measuring the level of one Patent Application Attorney Docket No.179.0009-WO00 or more biomarkers in a patient at least two different time points, e.g., at a first time point and at a second time point, and comparing the change, if any.
  • methods of identifying or qualifying the status of a neurological injury or a brain injury include determining and/or managing patient treatment based on injury status and/or risk.
  • Such management includes the decisions and actions of the medical practitioner, physician, or clinician subsequent to determining brain injury status, e.g., as to TBI, mTBI, or concussion. For example, if a physician makes a diagnosis of TBI, mTBI or concussion, then a certain monitoring regimen would follow.
  • An assessment of the course of brain injury using the described methods may then require a certain treatment or therapy regimen.
  • Profiles of the levels of a set of biomarkers in the biological sample, combined with the age, sex, and acute symptoms of a patient can provide a risk stratification (e.g., classifying patients into categories such as high risk, lower risk, or little to no risk likelihood of developing a certain post-TBI outcome, such as seizures, chronic pain, chronic headache, post-concussive symptoms, incomplete recovery assessed by GOS-E ⁇ 8, sleep disturbances, mild to severe depressive symptoms, mild to severe anxiety, PTSD, chronic headache or migraine, poor attention or cognitive performance, or motor deficits).
  • Each model profile with these biomarkers allows the physician to better make an informed decision to direct the TBI, mild TBI, or concussion patient down a treatment pathway tailored for each of the outcomes, having determined the symptoms for which he or she is at high risk.
  • An assessment of the course of brain injury using the described methods may then require a certain treatment or therapy regimen, including identifying an individual’s eligibility for clinical trials that investigate therapeutics for a symptom or set of symptoms that results from TBI.
  • a diagnosis of no brain injury might be followed with further testing or monitoring.
  • further tests may be called for if the diagnostic test gives an inconclusive result for neurological or brain injury status.
  • any of the biomarker combinations disclosed herein may be used with any of the embodiments relating to patient management described herein
  • the biomarkers include: Brain derived neurotrophic factor (BDNF); Glial Fibrillary Acidic Protein (GFAP); Interleukin- 6 (IL-6); Metallothionein 3 (MT3); Neurofilament light chain (NF-L); Neurogranin (NRGN); Neuron Specific Enolase (NSE); Phosphorylated Tau at Threonine 181 (pT181), Serine 217 (pS217), and Threonine 231 (pT231), together p-Tau); phosphorylated Synuclein alpha at Serine 129 (pS129-SNCA); Synuclein alpha (SNCA); Synuclein beta (SNCB); Tumorigenicity 2 protein (sST2); and von Willebrand Factor (vWF).
  • BDNF Brain derived neurotrophic factor
  • GFAP Glial Fibrillary Acidic Protein
  • IL-6 Interleukin- 6
  • MT3 Metallothionein 3
  • NF-L
  • TBI mild TBI
  • the subjects are also adjudicated for mild TBI (mTBI) diagnosis by a panel of expert clinicians and have blood draws and digital neurocognitive battery assessments, obtained using identical procedures as described in a study design in NIH grant Small Business Innovation Research Project No.1R44NS127732-01 awarded by the National Institute of Neurological Disorders and Stroke awarded to the assignee of this application.
  • TBI status was , defined as either the American Congress of Rehabilitation Medicine diagnostic criteria for mTB) diagnosis ( ACRM +) or evidence of traumatic intracranial injury by CT or MRI scan.
  • the retrospective dementia samples obtained for the study were comprised of Alzheimer’s Disease (64.3%), Parkinson’s Disease (21.4%), Vascular Dementia (3.6%) and Dementia diagnosed but not otherwise specified (10.7%). These provided a spectrum of dementia subtypes with chronic neuropathology to compare biomarker signatures with acute mild TBI pathology.
  • Patent Application Attorney Docket No.179.0009-WO00 Table 1 Subject demographics for the Phase I feasibility study Table 2. Clinical data for enrolled subjects
  • Patent Application Attorney Docket No.179.0009-WO00 for trauma controls and TBI subjects. Vital signs can be seen to be very consistent between study subgroups, with nearly all subjects having neuroimaging by CT or MRI in the TBI group, and the cognitively impaired trauma controls, and a slightly lower percentage in trauma controls with normal cognition. One difference that was observed in the subgroups was a slightly longer time from injury to arrival at the emergency department. This difference is worth considering when evaluating biomarker profiles. Because individual biomarkers have different kinetic profiles, variation in the time from injury to arrival could affect the patterns observed in study groups.
  • Patent Application Attorney Docket No.179.0009-WO00 Mechanisms of injury in the geriatric age group were like what has been reported in the literature, which are predominantly falls ( ⁇ 70%). Roughly 65% (54/83) of subjects in the study described herein were found to have been injured due to falls in this cohort. The next most common injury mechanisms were motor vehicle accidents and the head being struck by an object. In the TBI group and the trauma control group, an average of 25-26% of subjects had prior concussion history. There were very few elderly athletes enrolled (8.3%) in the TBI group, and none in the trauma controls.
  • Patent Application Attorney Docket No.179.0009-WO00 Historically, patients with GCS 13-15 have been considered to have mild TBI, although this grading of signs and symptoms is being reconsidered in light of the lasting and debilitating symptoms that are experienced by a significant number of patients with mild injury. In the current study, headache was the most common symptom in TBI subjects (72.4%), with more than 50% of all TBI subjects having severe headache post-injury. Disorientation and confusion, loss of consciousness, neurological deficits and amnesia were also prevalent as expected. Table 4. Acute symptoms of injury for enrolled subjects Patent Application Attorney Docket No.179.0009-WO00 Example 2.
  • Biomarkers were tested in 15 biomarker assays as described above, using custom and predeveloped Mesoscale Discovery (MSD) electrochemiluminescence immunoassays.
  • the phospho-Tau specific assays e.g., pT181-Tau, pS217-Tau, and pT231-Tau
  • Another biomarker studied was a promising neuroinflammatory biomarker, the soluble IL-33 receptor, ST2.
  • the ST2 assay also adds to the vascular and inflammatory biomarker indicators, together with vWF and IL-6.
  • the aim in evaluating 15 different biomarkers was to have broad representation of the endophenotypes of injury (e.g., vascular injury, neuronal/axonal injury, glial injury, inflammation).
  • This approach allowed for a comprehensive set of biomarkers from which to assess differences among mTBI endophenotypes (injury subtypes).
  • the assay performance metrics are provided in Table 5. Clinical sample testing allowed for determination of biomarker distributions and the lower limits of detection to assess whether the assays address the true clinical ranges.
  • Fig. 1 shows the distributions of biomarkers in paired serum and plasma samples from enrolled subjects. The study comparing different commonly used biofluids permitted cross-comparisons of results with data in published neurodegenerative disease literature, in which most studies have used plasma as a biofluid matrix, as well as comparisons with the serum data in the TBI literature and earlier studies by BRAINBox®.
  • CSF Cerebrospinal fluid
  • Biomarker levels were detected in serum or plasma using paired samples measured within the same multiwell plates simultaneously were compared for overall distributions separated by age ranges 18-39 years (young adult) 40-64 years (middle aged adult), 65-74 years (late middle age, early geriatric adult), and 75 to 100 years (old age geriatric) (Figure 2, A through J). Results show that blood levels of certain biomarkers, including BDNF and NRGN, are diminished with age, and are diminished further still in dementia, likely due to synaptic loss.
  • LCC correlation coefficient
  • Biomarker differences between clinical subgroups were tested in univariate analysis first, followed by iterative multivariate modeling to identify the best performing biomarker panels for discriminating acute mild TBI from other injury or pathology. Comparisons of acute geriatric trauma controls having age-normal cognitive status with trauma controls having cognitive impairment did not reveal any significant differences in biomarker distributions (Wilcoxon rank sum test, p>0.05 for all). Cognitively age-normal trauma controls versus cognitively age-normal TBI comparisons showed significant differences for GFAP. Cognitively impaired trauma controls versus cognitively impaired TBI. Table 7 shows the univariate analysis results for determining statistical differences between the distributions of individual biomarkers between groups.
  • Biomarker levels detected in serum versus plasma were compared for overall distributions (Fig.1). Distributions in this small sample set showed group-level differences for roughly half of the biomarkers studied. Further analysis of differences was performed using Bland-Altman plots, which indicated equivalence or difference for each. Bland-Altman analysis, also known as intra-class correlation (ICC), was used for studying biomarker levels as continuous variables in the 2 matrix types, which is shown in Fig.2.
  • ICC intra-class correlation
  • Dementia versus TBI signatures [0136] Dementia subjects from commercial biorepositories were studied for serum and plasma levels of biomarkers. The cohort consisted of subjects with Alzheimer’s Disease, Parkinson’s Disease, Vascular Dementia, and other dementias. These subjects were demographically balanced to the extent possible, given the availability of samples obtained from commercial biorepositories. It is believed that this study is the first side-by-side comparison of trauma controls, geriatric mTBI, MCI and dementia subtypes.
  • BDNF Median BDNF levels were found to be decreased in the serum of dementia subjects compared to trauma controls or TBI subjects of similar age. Fig.3 shows the group distributions which show a significant overlap between groups. BDNF is known to dynamically expressed during exercise or other exertion and to differ between male and females, and this could affect the overall variance within the distributions. Group differences between TBI and trauma controls were shown to be significant in this analysis.
  • GFAP Contrary to preinjury assumptions, GFAP was not seen to be significantly elevated in dementia at the group level compared to the elevation seen in acute mTBI in this age group (Fig.2). Age-matched trauma controls also had similar levels to dementia subjects at the group level. Although not part of the current study, healthy controls aged 65 and older, previously enrolled, were available for development studies in BRAINBox biorepositories, and were also examined to aid in interpreting the results.
  • IL-6 The proinflammatory cytokine IL-6 is not specific to the CNS but has been repeatedly shown to increase in the blood as a pro-inflammatory biomarker after TBI. The study described herein showed that IL-6 was detected at significantly lower levels in dementia subjects compared with trauma controls or TBI subjects in the same age range.
  • MT3 Metallothionein 3 is an astrocyte specific biomarker that plays a role in modulating the bioavailability of metal cations, including zinc, copper and cadmium, preventing cellular toxicity. Immunostaining of mammalian brains has indicated a predominant expression in white matter astrocytes (unpublished data). Detection of MT3 may be indicative of neurotrauma and has been reported to decrease in Parkinson’s and Alzheimer’s disease patients. The study described herein did not show a median difference in the detection of MT3 between Alzheimer’s Disease and Trauma controls. However, most of the samples tested were below the detection level of the MT3 assay.
  • NfL Neurofilament Light chain is a component of axonal neurofilament bundles, where NfL multimerizes to form the core of the main neuronal intermediate filament fiber, encapsulated with neurofilament heavy and medium chains (NfH and NfM, respectively).
  • NfL has been advanced as both a neurotrauma and a neurodegeneration biomarker but is not specific to the CNS. It is widely recognized as a useful indicator of neuronal damage or degeneration of all types and has been characterized in many TBI and neurodegenerative disease cohort studies. The results described herein indicate that NfL levels were increased in both dementia and TBI. , NfL nonetheless may be included in panels with other biomarkers for distinguishing between TBI and dementia.
  • NRGN Neurogranin is a post-synaptic neuronal biomarker that has been reported to have decreased levels in the CSF of Alzheimer’s Disease patients compared to controls and is being evaluated as an additional clinical biomarker for Alzheimer’s Disease.
  • NRGN has also been shown to increase after acute TBI in previous Patent Application Attorney Docket No.179.0009-WO00 reports. Neurogranin was not found to differ significantly between dementia and either geriatric mTBI or trauma controls, as shown in Table 5. Geriatric trauma controls and TBI did not differ significantly in this feasibility study. The differences seen in prior studies and the performance in classifier models in prior TBI studies indicate that NRGN may be used as a biomarker for distinguishing TBI from dementia, particularly in indicating long term symptoms, and possibly for tracking post-injury changes indicative of a neurodegenerative trajectory, if NRGN decreases over time, as well as in panels with other biomarkers for distinguishing between TBI and dementia.
  • NSE Neuron specific enolase, or Enolase 2
  • Enolase 2 is a metabolic neuronally expressed glycolytic enzyme that is released after injury and is detectable with similar kinetics to GFAP, where NSE is known to reach peak levels at 12-24 hours post-injury.
  • NSE was shown to have significantly different median levels in trauma controls versus dementia. These data suggest that NSE may be elevated both in acute TBI and in chronic dementias. While NSE may also be present at high levels in erythrocytes and thus, its levels can be affected by hemolysis, NSE nonetheless may be included in panels with other biomarkers for distinguishing between TBI and dementia.
  • SNCA and phosphorylated at-Serine129-SNCA (pS129-SNCA): Synuclein alpha (SNCA) has been a target gene in neurology since the discovery that senile plaques and Lewy Bodies have aggregated SNCA as a principal component.
  • SNCA As a component protein of complexes involved in neurotransmitter release from neurons, changes in SNCA could reflect changes in neurotransmission or pathologies associated with neural activity.
  • One of the downsides of this protein is that there is substantial expression in peripheral tissue, including the gut and the enteric nervous system, and importantly expressed in high levels in erythrocytes.
  • SNCA has been extensively studied in synucleinopathies, including in Parkinson’s Disease pathology, due to the early finding of SNCA gene mutations in some familial Parkinson’s subjects. It is less well studied in TBI but is known to play a role in neurotransmission as a presynaptic vesicle transport protein.
  • Phosphorylated SNCA at serine 129 is associated with SNCA deposited in Lewy bodies, hence pathological, aggregated SCNA. SCNA could be significantly affected by peripheral sources since it is highly expressed in red blood cells and could therefore be affected by hemorrhage and hemolysis.
  • the study described herein reported that SNCA levels differ between acute TBI and dementia, thereby showing that SNCA can be used as a biomarker to distinguish between these disease states, , as well as in panels with other biomarkers for distinguishing between TBI and dementia.
  • pS129- SNCA where detected, was not found to be significantly difference between the study groups, despite being tightly correlated with overall SNCA levels.
  • SNCB Synuclein beta is another synaptic protein expressed predominantly in the CNS and thought to play a similar role to SNCA in neurotransmitter release, as experiments have shown that SNCB may modulate the toxicity of aggregated SNCA when bound together.
  • SNCB SNCA ratios are altered during pathogenesis of neurodegenerative disease.
  • SNCB has been reported to decrease in chronic neurodegeneration.
  • SNCB levels were detected in a some TBI subjects, but with many subjects having very low or undetectable levels, similar to control levels, SNCB levels were demonstrated to be different in TBI and trauma controls.
  • SNCB is a biomarker that can be used to distinguish between those two conditions, as well as in panels with other biomarkers for distinguishing between TBI and dementia.
  • sST2 Soluble suppressor of tumorigenesis-2 is a soluble form of interleukin 33 receptor that has been extensively studied in relation to heart failure, renal failure and inflammation. ST2 is also released by endothelial cells.
  • Increased ST2 indicates tissue damage, particularly in the cardiovascular system, and has been studied in many disease states.
  • the assignee of this application has studied its use as biomarker indicative of traumatic brain injury, particularly mTBI. See, e.g., US 2023/0238143, WO2023/092157, and US 2025/0035650, which are incorporated by reference herein in their entireties. As such, it may provide information on different aspects of trauma, inflammation and vascular injury or repair.
  • ST2 levels were similar in trauma controls and TBI subjects, but detected levels were significantly lower in dementias.
  • Phospho-Tau Three phospho-Tau biomarkers were studied. The first of these studied in TBI was phospho- Threonine 231 (pT231-tau), which was reported to be increased in TBI subjects compared with controls in prior publications. Phospho-Threonine 181 (pT181-tau) has also been studied in TBI subjects using available pre- developed immunoassays. More recently phospho-Serine217 (pS217-tau), which was recently recommended by researchers for its correlation in Alzheimer’s Disease patients to amyloid plaque burden and neurofibrillary tangle burden. To date, no publications have characterized pS217-tau in TBI.
  • T231-Tau phosphorylation as reported in prior TBI publications, appeared to be elevated in geriatric TBI subjects compared to trauma controls and dementia.
  • Serine217-Tau phosphorylation showed a similar pattern to that of pT231-Tau but was significant for distinguishing dementia from trauma or TBI.
  • PhosphoTau181 showed the largest difference and was elevated in dementia compared to either TBI or trauma controls.
  • mTBI and trauma controls were also significantly different between groups in this analysis.
  • vWF is elevated in both trauma controls and TBI, using a custom assay that targets epitopes in the region cleaved by ADAMTS13.
  • vWF levels were shown to have statistically significant differences in median levels between study groups, particularly in distinguishing dementia from other clinical groups, since vWF levels were lower than TBI or peripheral trauma controls.
  • Subanalysis of dementia types included in the study showed differences in subtype distributions, so while further detailed analysis of this biomarker in a balanced study of neurodegenerative diseases will provide more information, this study showed that vWF is a biomarker for distinguishing between TBI and dementia-related conditions, as well as in panels with other biomarkers for distinguishing between TBI and dementia.
  • GFAP was the best biomarker to distinguish mTBI from peripheral trauma.
  • BDNF was also found to differ in mTBI and dementia, with a similar decrease in median levels in univariate comparisons, and this was represented in some of the top performing models.
  • Clinically, ruling out mTBI in geriatric subjects would add value to the CT imaging findings, since a very high percentage of patients get CT scans in this age group. More than 90% with no CT findings will still need assessment for clinically important brain injury.
  • Patent Application Attorney Docket No.179.0009-WO00 Table 8 Top multivariate models for discriminating geriatric acute mTBI from non-CNS trauma (trauma controls), and for distinguishing geriatric mTBI or dementia using biofluid biomarkers and, optionally, neurocognitive testing metrics.
  • Model classifiers for distinguishing acute traumatic brain injury events from chronic dementia were generated. Table 8 shows the top performing models to have vWF and IL-6, with one additional biomarker being p-Thr181 Tau, BDNF or NRGN.
  • Top performing models are shown in Table 10.
  • a model with GFAP, NRGN, IL- 6 and vWF was shown to have the highest AUC. Discussion and potential uses of this technology Patent Application Attorney Docket No.179.0009-WO00 [0154] Custom immunoassays were used to characterize an understudied age group in TBI research, but one that is a growing demographic as the population is surviving longer.
  • biomarkers were only detected in a subset of subjects in this feasibility study due to very low levels in blood. This was evident in MT3 and SNCB assays, technically sound assays but with many individuals having undetectable circulating levels. Along with phospho-Tau, these biomarkers appear to be promising candidates to distinguish between TBI and dementia, but may require an enhancement in detected signal by additional signal boosting techniques. In the case of phospho-Tau assays, these were developed with a boosted signal chemistry for detection which increased the signal 100-fold. This could be developed for the SNCB and MT3 immunoassays as well. For the majority of biomarkers, the full clinical ranges were detectable with very few samples below the limits of detection.
  • Comparisons showed distinctive profiles for dementia and acute mild TBI, supporting the utility of specific biomarker subsets in detecting mild TBI in this age group, irrespective of cognitive status or decline. Differences in biomarker distributions were less evident within subgroups that differ by pre-injury cognitive status. No statistically significant differences were seen between cognitively impaired and cognitively normal trauma controls, or between TBI subjects that were cognitively impaired prior to injury compared to cognitively age-normal subjects prior to injury. [0155] Based on ANOVA analysis (e.g., comparison of median biomarker levels), univariate analysis highlighted biomarkers that differed between the overall study groups.
  • the standout biomarkers for geriatric acute trauma controls versus acute mTBI were GFAP and SNCB, two of the more CNS specific biomarkers.
  • comparisons with acute TBI showed statistically significant differences in median levels of GFAP, NRGN, IL-6 and p181-tau, with SNCA and ST2 also showing differences that approached significance in this small sample set.
  • Dementia subjects compared with non-brain trauma controls of the same age range showed significant differences in NRGN, ST2, NSE, and SNCA.
  • IL-6 and p181-iau also showed differences and thus may be promising, but the number of subjects with evaluable data was low.
  • Model classifiers were constructed with up to five covariates, limited due to the group sizes. These model sizes have been shown in previous studies to be sufficient to provide clinically relevant performance in ROC curve analysis. Like the results of univariate comparisons, GFAP, NRGN, BDNF, vWF, IL-6, ST2, and phosphoS217-tau were found to be present in the top performing classifier models. Some models also included BDNF and vWF in equivalent models.
  • Different optional models may be used to distinguish trauma that is acute intracranial brain insult from non-CNS trauma, and for distinguishing dementias from TBI. Since the model tested in our longitudinal study must discriminate acute mTBI from either preexisting dementia or acute peripheral trauma, a combined class model (combining dementia and trauma control) was also developed and tested against mTBI. This model showed clinically useful discrimination, with all top models showing sensitivity above 0.85 and specificity over 0.70.
  • Cross-platform studies can be performed on a point of care (POC) test, main hospital laboratory instrument, or other immunological, immune-PCR or aptamer or other binding agent assay to determine. Biomarker levels.
  • POC point of care
  • send-out assays using mass spectroscopy or other techniques could also be performed to assess neurological injury or disease subtype, stage or post-therapy response.
  • the current analysis of measured biomarkers in the clinical subgroups studied indicates that, in the geriatric population, acute mild TBI is discernable from trauma controls and chronic dementia.
  • acute injury biomarker panels clearly allow for distinction between TBI and dementia as well.
  • the biomarker distributions that differ between TBI and non- CNS, trauma and between acute TBI and chronic dementia pathologies are somewhat different, which is to be expected. This analysis provides evidence that multiple models can achieve clinically useful accuracy, sensitivity, and specificity, and by utilizing detected levels of 3-4 blood biomarkers.
  • BrainCheck or other neurocognitive testing instrument when BrainCheck or other neurocognitive testing instrument is used clinically in cognitively age-normal individuals (i.e., having no detectable cognitive impairment compared to normative ranges for their age), the TBI-related impairment can be discerned and can provide valuable information to the testing system and ultimately can assist the clinician with diagnosis.
  • the models with blood biomarkers can be relied on alone, and thus the testing system could shift the algorithm setting (down-weight the BrainCheck component) if necessary.
  • One of the benefits of having the digital neurocognitive function assessment is the ability to remotely monitor the subject for functional changes that are reflected in the brief digital assessment, whether they indicate a downward trend toward increasing functional deficit, or the upward trend indicating the recovery of the subject to an improved functional status.
  • the longitudinal follow-up testing by clinicians or home testing kits and/or apps, software applications will allow for confirmation of the prognosis.
  • the biomarker multivariate models could be combined computationally with other modalities Patent Application Attorney Docket No.179.0009-WO00 and data available at the time of assessment or at a later time, potentially including advanced MRI tracking of vascular, axonal, and other intracranial abnormalities, which may provide additional improvement to prognostic models and improvement over use of the blood biomarker profiles alone, and better relate to symptomatic and functional outcomes, providing a more complete “ground truth” for assessment and monitoring of post-injury pathology. Trauma Control versus TBI Signatures Several biomarkers were found to be elevated in both trauma controls and TBI subjects, as is described in the literature for some of the proteins measured here.
  • BrainCheck® Battery software was designed to detect and monitor neurocognitive impairment across several functional domains, and today is used clinically within neurology practices. Evaluating whether this digital health technology can be applied to the acute evaluation of head trauma to identify mild brain injury in elderly subjects is complicated by varying degrees of pre-existing cognitive decline and dementia.
  • results from several neurocognitive assessments administered in the study were considered to clarify the pre-existing cognitive status of the subject before the head injury event.
  • the informant sections of the CDR and FAQ were relied upon, as suggested by our expert neurologists and neuropsychologists on the clinical and consulting teams. The informants were spouses, siblings or individuals who knew the enrolled subject well.
  • BrainCheck® concordance with diagnosis was conducted as follows. Subjects enrolled under the current protocol were evaluated with the BrainCheck® neurocognitive battery as well as multiple clinical gold standard assessments for cognitive function and dementia. For all subjects, the informant portion of the Clinical Dementia Rating Scale (CDR) and the Functional Assessment Questionnaire (FAQ) were used as primary determinants of pre-injury cognitive status.
  • CDR Clinical Dementia Rating Scale
  • FAQ Functional Assessment Questionnaire
  • Fig.9 shows the ROC curves for both assessments. In both cases, roughly 70% concordance was shown. This is likely due to lack of detailed pre-trauma neurocognitive assessment in the HeadSMART II subjects and may be clarified by analysis of just the subset of subjects enrolled and evaluated through the current study, where pre-existing status can be verified.
  • CDR Clinical Dementia Rating Scale
  • FAQ Functional Assessment Questionnaire
  • the TBI positive individuals (assigned by expert review, ACRM criteria and/or neuroimaging) were shown to have an 82.6% concordance BrainCheck classification of likely or possible impairment.17.4 % were classified as “unlikely” impaired. Within the cognitively impaired TBI positive group, 100% of individuals were classified as likely or possible for cognitive impairment. Considering trauma controls (isolated non-head injury), both pre- existing cognitive impairment and cognitively age-normal subjects were also considered. Among the evaluable cognitively normal trauma controls, 6 of 18 (30%) were classified as “unlikely” for impairment, with 9/18 (50%) classified as “possible”, and 3/18 (16.7%) as “likely” impaired.
  • Patent Application Attorney Docket No.179.0009-WO00 Table 9 Comparison of adjudicated cognitive status versus BrainCheck: Subgroup specific accuracy for enrolled trauma control and TBI subjects Concordance N subjects yes no Accuracy(%) Trauma control Normal 17 14 3 82.4 Trauma control Impaired 5 5 0 100 TBI Normal 50 39 11 82.6 TBI Impaired 9 8 1 88.9 Total 81 [0164] Overall, there is a high degree of consistency between BrainCheck Battery classification of neurocognitive impairment and validated standard assessments. This has been indicated in previously published studies, where BrainCheck Battery classification was compared with MMSE, MoCA and SLUMS cognitive assessments and showed high concordance(ref).
  • Example 3 Clinical Milestone 3 – Development of a trained algorithm that provide a diagnostic TBI score
  • the full data set of blood biomarkers, age, sex, BrainCheck individual test metrics and overall BrainCheck Clinician Scores were used in multivariate models for geriatric TBI specific diagnosis. Certain biomarkers were found to be undetectable in a significant proportion of individuals. Where more than 30% of subjects had undetectable values, the data were converted to a categorical present/absent dichotomization (binary value) rather than a continuous variable.
  • BDNF was also found to differ in mTBI and dementia, with a similar decrease in median levels in univariate comparisons, and this was represented in some of the top performing models.
  • the 4 plex model consisting of GFAP, NRGN, ST2, BDNF had the highest negative predictive value (NPV) of the models generated, when a minimum of 85% sensitivity is set, which could be advantageous for a rule out test in geriatric mTBI.
  • NPV negative predictive value

Landscapes

  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biomedical Technology (AREA)
  • Neurology (AREA)
  • Neurosurgery (AREA)
  • Chemical & Material Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • General Health & Medical Sciences (AREA)
  • Hematology (AREA)
  • Immunology (AREA)
  • Medicinal Chemistry (AREA)
  • Molecular Biology (AREA)
  • Urology & Nephrology (AREA)
  • Cell Biology (AREA)
  • Psychiatry (AREA)
  • Microbiology (AREA)
  • Physics & Mathematics (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • Biotechnology (AREA)
  • General Physics & Mathematics (AREA)
  • Pathology (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Hospice & Palliative Care (AREA)
  • Food Science & Technology (AREA)
  • Chemical Kinetics & Catalysis (AREA)
  • General Chemical & Material Sciences (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Organic Chemistry (AREA)
  • Pharmacology & Pharmacy (AREA)
  • Animal Behavior & Ethology (AREA)
  • Public Health (AREA)
  • Veterinary Medicine (AREA)
  • Investigating Or Analysing Biological Materials (AREA)

Abstract

Methods, compositions, and kits are capable of detecting, identifying, diagnosing, prognosing, assessing, monitoring, and/or treating a neurological injury such as acute TBI and distinguishing geriatric TBI from conditions such as dementia, Alzheimer's Disease, Parkinson's disease and the like. Also disclosed are methods of testing elderly patients who have or are suspected of having traumatic brain injury using panels of biomarkers that distinguish TBI from dementia, and, optionally, treating such patients for TBI or dementia based upon the results of the biomarker tests.

Description

Patent Application Attorney Docket No.179.0009-WO00 BIOMARKERS, COMPOSITIONS, KITS, AND METHODS DISTINGUISHING ACUTE GERIATRIC TBI FROM PRE- EXISTING DEMENTIA OR COGNITIVE IMPAIRMENT GOVERNMENT SUPPORT [0001] This invention was made with government support under the Small Business Innovation Research Project No.1R44NS127732-01 awarded by the National Institute of Neurological Disorders and Stroke. The government has certain rights in the invention. CROSS-REFERENCE TO RELATED APPLICATIONS [0002] This application claims priority to U.S. Application No.63/557,525, filed on February 24, 2024, the disclosure of which is incorporated by reference in its entirety. BACKGROUND OF THE INVENTION [0003] Brain injury can occur due to acute blunt force trauma, or from intrinsic damage due to hemorrhage, or a degenerative process in the brain. Traumatic brain injury (TBI) has historically been studied as an acute event of force-related damage to the brain, but with the understanding that lasting symptomatic deficits can result. Among elderly subjects, TBIs can present physical symptoms that are indistinguishable from age-related brain atrophy and diseases, such as dementia. SUMMARY OF THE INVENTION [0004] Applicant recognized that there is a clinical need to accurately determine acute TBI diagnoses in the elderly population, compared with age-related atrophy and brain disease, for proper diagnosis, prognosis and/or treatment of elderly patients. Methods, compositions, and kits made according to the principles and illustrative embodiments of the invention can determine acute TBI by measuring unique combinations of biomarkers that were discovered and developed for their capacity to differentiate geriatric TBI from other conditions. For example, methods, compositions, and kits made according to the principles and illustrative embodiments of the invention are capable of detecting, identifying, diagnosing, prognosing, assessing, monitoring, and/or treating a neurological injury such as acute TBI and distinguishing geriatric TBI from conditions such as dementia, Alzheimer’s Disease, Parkinson’s disease and the like. [0005] According to one aspect of the invention, a method for diagnosing an acute TBI in an elderly subject includes the steps of: (A) obtaining a biological sample from the elderly subject; (B) measuring the levels of one or more biomarkers present in the biological samples by a protein detection assay, wherein the one or more biomarkers are selected from the group consisting of: brain derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), interleukin-6 (IL-6), metallothionein 3 (MT3), neurofilament light chain (NfL), neurogranin (NRGN), neuron specific enolase (NSE), synuclein alpha (SNCA), synuclein beta (SNCB), Patent Application Attorney Docket No.179.0009-WO00 phosphorylated Ser129 SNCA (pS129-SNCA), soluble receptor for interleukin 33 (ST2), phosphorylated Thr181 tau (pT181 tau), phosphorylated Ser217tau (pS217 tau), phosphorylated Thr231 tau (pT231 tau), and von Willebrand factor (vWF); and (C) diagnosing the presence of an acute TBI if the level of one or more of the biological markers are altered relative to their respective reference levels. [0006] The method may further include treating the elderly subject for an acute TBI when at least one increased level of the one or more biomarkers is detected. [0007] The biological sample used may be selected from blood, plasma, serum, cerebrospinal fluid (CSF), tears or lacrimal fluid, urine, and saliva. [0008] Two or more of the biomarkers used in step (A) may be selected from the group consisting of BDNF, GFAP, IL-6, MT3, NfL, NRGN, NSE, SNCA, SNCB, pS129-SNCA, sST2, pT181 tau, pS217 tau, pT231 tau, and vWF, and, optionally, one or more of ALDOC. [0009] The biomarkers used in the method may include a panel selected from one of the following groups of biomarker combinations: (a) two or more of NRGN, ST2, NSE, and BDNF; (b) two or more of NRGN, NSE, BDNF, and vWF; (c) two or more of NRGN, ST2, vWF, and pSNCA; (d) two or more of GFAP, ST2, NSE, and BDNF; (e) two or more of GFAP ,NRGN, ST2, and pSNCA; (f) two or more of GFAP, NRGN, ST2, and BDNF; (g) two or more of GFAP, NRGN, and pSNCA; (h) two or more of ST2, NSE, and BDNF; (i) two or more of GFAP, ST2, BDNF, and pSNCA; (j) two or more of NRGN, ST2, NSE, and vWF; (k) two or more of GFAP, NRGN, IL-6 and p181-Tau; (l) two or more of NRGN, ST2, NSE, and SNCA; (m) two or more of GFAP, NRGN, IL-6 and vWF; (m) two or more of SNCA and ST2; (n) GFAP and SNCB; (o) GFAP and ST2; and (p) two or more of GFAP, NRGN, BDNF, vWF, IL-6, ST2, and pS217-tau.FABP7, IL-7, and IL-33. [0010] According to another aspect of the invention, a method of treating an elderly patient with traumatic brain injury or suspected of having traumatic brain injury includes: (A) administering over time a drug or drug treatment for traumatic brain injury comprising a single dose or multiple doses of the drug to the patient; (B) detecting at least one of the biomarker proteins selected from a group of biomarker proteins that distinguish traumatic brain injury from dementia, the group of biomarkers proteins including brain derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), interleukin-6 (IL-6), metallothionein 3 (MT3), neurofilament light chain (NfL), neurogranin (NRGN), neuron specific enolase (NSE), synuclein alpha (SNCA), synuclein beta (SNCB), phosphorylated Ser129 SNCA (pS129-SNCA), soluble receptor for interleukin 33 (ST2), phosphorylated Thr181 tau (pT181 tau), phosphorylated Ser217 tau (pS217 tau), phosphorylated Thr231 tau (pT231 tau), and von Willebrand factor (vWF) at (i) a first time point and (ii) at least one second time point following the first time point; (C) measuring levels of the at least one biomarker protein detected at the at least one second time point relative to the same biomarker proteins in a brain injury or healthy control compared to the measured levels of the at least one biomarker protein detected at the first time point; and (D) administering, maintaining Patent Application Attorney Docket No.179.0009-WO00 administering, or discontinuing administering the drug or drug treatment to the patient if the level of one or more of the biological markers at the second time point are altered relative to level at the first timepoint. [0011] The biological sample used may be selected from blood, plasma, serum, cerebrospinal fluid (CSF), tears or lacrimal fluid, urine, and saliva. [0012] Two or more of the biomarkers used in step (A) may be selected from the group consisting of BDNF, GFAP, IL-6, MT3, NfL, NRGN, NSE, SNCA, SNCB, pS129-SNCA, sST2, pT181 tau, pS217 tau, pT231 tau, and vWF, and, optionally, one or more of ALDOC, FABP7, IL-7, and IL-33. [0013] The biomarkers used in the method may include a panel selected from one of the following groups of biomarker combinations: (a) two or more of NRGN, ST2, NSE, and BDNF; (b) two or more of NRGN, NSE, BDNF, and vWF; (c) two or more of NRGN, ST2, vWF, and pSNCA; (d) two or more of GFAP, ST2, NSE, and BDNF; (e) two or more of GFAP ,NRGN, ST2, and pSNCA; (f) two or more of GFAP, NRGN, ST2, and BDNF; (g) two or more of GFAP, NRGN, and pSNCA; (h) two or more of ST2, NSE, and BDNF; (i) two or more of GFAP, ST2, BDNF, and pSNCA; (j) two or more of NRGN, ST2, NSE, and vWF; (k) two or more of GFAP, NRGN, IL-6 and p181-Tau; (l) two or more of NRGN, ST2, NSE, and SNCA; (m) two or more of GFAP, NRGN, IL-6 and vWF; (m) two or more of SNCA and ST2; (n) GFAP and SNCB; (o) GFAP and ST2; and (p) two or more of GFAP, NRGN, BDNF, vWF, IL-6, ST2, and pS217-tau. [0014] According to another aspect of the invention, a method of distinguishing an acute TBI from an age- related atrophy or brain disease in an elderly subject includes the steps of: (A) obtaining a biological sample from the elderly subject; (B) measuring the levels of one or more protein biomarkers present in the biological samples by immunoassay or mass spectroscopy, wherein the one or more protein biomarkers are selected from the group consisting of: brain derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), interleukin-6 (IL-6), metallothionein 3 (MT3), neurofilament light chain (NfL), neurogranin (NRGN), neuron specific enolase (NSE), synuclein alpha (SNCA), synuclein beta (SNCB), phosphorylated Ser129 SNCA (pS129- SNCA), soluble receptor for interleukin 33 (ST2), phosphorylated Thr181 tau (pT181 tau), phosphorylated Ser217 tau (pS217 tau), phosphorylated Thr231 tau (pT231 tau), and von Willebrand factor (vWF); and (C) determining the presence of an acute TBI if the level of the one or more biological markers are altered relative to their respective control or reference levels. [0015] The method may further include treating the elderly subject for an acute TBI when at least one increased level of the one or more biomarkers is detected. [0016] The biological sample used may be selected from blood, plasma, serum, cerebrospinal fluid (CSF), tears or lacrimal fluid, urine, and saliva. Patent Application Attorney Docket No.179.0009-WO00 [0017] Two or more of the biomarkers used in step (A) may be selected from the group consisting of BDNF, GFAP, IL-6, MT3, NfL, NRGN, NSE, SNCA, SNCB, pS129-SNCA, sST2, pT181 tau, pS217 tau, pT231 tau, and vWF, and, optionally, one or more of ALDOC, FABP7, IL-7, and IL-33. [0018] The biomarkers may include a panel selected from one of the following groups of biomarker combinations: (a) two or more of NRGN, ST2, NSE, and BDNF; (b) two or more of NRGN, NSE, BDNF, and vWF; (c) two or more of NRGN, ST2, vWF, and pSNCA; (d) two or more of GFAP, ST2, NSE, and BDNF; (e) two or more of GFAP ,NRGN, ST2, and pSNCA; (f) two or more of GFAP, NRGN, ST2, and BDNF; (g) two or more of GFAP, NRGN, and pSNCA; (h) two or more of ST2, NSE, and BDNF; (i) two or more of GFAP, ST2, BDNF, and pSNCA; (j) two or more of NRGN, ST2, NSE, and vWF; (k) two or more of GFAP, NRGN, IL-6 and p181-Tau; (l) two or more of NRGN, ST2, NSE, and SNCA; (m) two or more of GFAP, NRGN, IL-6 and vWF; (m) two or more of SNCA and ST2; (n) GFAP and SNCB; (o) GFAP and ST2; and (p) two or more of GFAP, NRGN, BDNF, vWF, IL-6, ST2, and pS217-tau. [0019] According to another aspect of the invention, a method of monitoring and treating a traumatic brain injury (TBI) over time in an elderly subject that sustained or is believed to have sustained a TBI includes the steps of: (A) obtaining a first biological sample from the subject at a first timepoint; (B) obtaining one or more subsequent biological samples from the same subject at one or more later timepoints; (C) detecting neurogranin (NRGN) levels in the first and subsequent one or more biological samples; (D) measuring the levels of NRGN in the first and subsequent one or more biological samples relative to a reference level of NRGN indicative of neurodegeneration; and (E) determining that subject has neurodegeneration and, optionally, treating the subject for neurodegeneration when the levels of NRGN at the one or more later timepoints remain increased relative to the reference levels. [0020] According to another aspect of the invention a composition includes a solid substrate and a plurality of antibodies or antigen-binding fragments thereof immobilized on the substrate, wherein the antibodies, or antigen-binding fragments thereof, specifically and respectively bind to a plurality of protein biomarkers including three or more of Brain derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), Fatty acid binding protein 7 (FABP7), interleukin-6 (IL-6), metallothionein 3 (MT3), neurofilament light chain (NfL), neurogranin (NRGN), neuron specific enolase (NSE), synuclein alpha (SNCA), synuclein beta (SNCB), phosphorylated Ser129 SNCA (pS129-SNCA), soluble receptor for interleukin 33 (sST2), phosphorylated Thr181 tau (pT181 tau), phosphorylated Ser217 tau (pS217 tau), phosphorylated Thr231 tau (pT231 tau), and von Willebrand factor (vWF). [0021] The solid substrate of the composition may include antibodies, or antigen-binding fragments thereof, specific for one or more combinations of protein biomarkers including: a) NRGN, ST2, NSE, and BDNF; (b) NRGN, NSE, BDNF, and vWF; (c) NRGN, ST2, vWF, and pSNCA; (d) GFAP, ST2, NSE, and BDNF; (e) GFAP ,NRGN, Patent Application Attorney Docket No.179.0009-WO00 ST2, and pSNCA; (f) GFAP, NRGN, ST2, and BDNF; (g) GFAP, NRGN, and pSNCA; (h) ST2, NSE, and BDNF; (i) GFAP, ST2, BDNF, and pSNCA; (j) NRGN, ST2, NSE, and vWF; (k) GFAP, NRGN, IL-6 and p181-Tau; (l) NRGN, ST2, NSE, and SNCA; (m) GFAP, NRGN, IL-6 and vWF; (m) SNCA and ST2; (n) GFAP and SNCB; (o) GFAP and ST2; and (p) GFAP, NRGN, BDNF, vWF, IL-6, ST2, and pS217-tau. [0022] According to another aspect of the invention, a kit for detecting an acute TBI in an elderly subject includes one or more biomarker panels that distinguish traumatic brain injury from dementia , the one or more biomarker panels including three or more antibodies, or antigen-binding fragments thereof, that specifically and respectively bind to a plurality of protein biomarkers including one or more of brain derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), interleukin-6 (IL-6), metallothionein 3 (MT3), neurofilament light chain (NfL), neurogranin (NRGN), neuron specific enolase (NSE), synuclein alpha (SNCA), synuclein beta (SNCB), phosphorylated Ser129 SNCA (pS129-SNCA), soluble receptor for interleukin 33 (sST2), phosphorylated Thr181 tau (pT181-tau), phosphorylated Ser217 tau (pS217-tau), phosphorylated Thr231 tau (pT231-tau), and von Willebrand factor (vWF). [0023] The one or more biomarker panels of the kit may include four or more biomarkers selected from the group consisting of BDNF, GFAP, IL-6, MT3, NfL, NRGN, NSE, SNCA, SNCB, pS129-SNCA, sST2, pT181 tau, pS217 tau, pT231-tau, and vWF, and, optionally, one or more of ALDOC , FABP7, IL-7, and IL-33. [0024] The one or more biomarker panels of the kit may include antibodies or antigen-binding fragments thereof specifically bind to one of the following combinations of biomarkers: a) NRGN, ST2, NSE, and BDNF; (b) NRGN, NSE, BDNF, and vWF; (c) NRGN, ST2, vWF, and pSNCA; (d) GFAP, ST2, NSE, and BDNF; (e) GFAP ,NRGN, ST2, and pSNCA; (f) GFAP, NRGN, ST2, and BDNF; (g) GFAP, NRGN, and pSNCA; (h) ST2, NSE, and BDNF; (i) GFAP, ST2, BDNF, and pSNCA; (j) NRGN, ST2, NSE, and vWF; (k) GFAP, NRGN, IL-6 and p181-Tau; (l) NRGN, ST2, NSE, and SNCA; (m) GFAP, NRGN, IL-6 and vWF; (m) SNCA and ST2; (n) GFAP and SNCB; (o) GFAP and ST2; and (p) GFAP, NRGN, BDNF, vWF, IL-6, ST2, and pS217-tau. [0025] The kit may further include one or more pre-coated strip plates, one or more biotinylated secondary antibodies, one or more standard solutions, one or more assay controls, one or more buffer solutions, streptavidin-horse radish peroxidase (HRP), tetramethyl benzidine (TMB), one or more stop reagents, and detailed instructions for carrying out the kit assay. [0026] According to another aspect of the invention, a method of testing an elderly subject suspected of having head injury to distinguish between traumatic brain injury (TBI) and dementia includes: (a) testing a bodily sample from the subject for an acute injury using one of more of the following biomarkers: soluble receptor for interleukin-33 (ST2), neurogranin (NRGN), Interleukin 6 (IL-6), and von Willebrand factor (vWF); (b) if the results of step (a) show an acute injury, testing the subject for an intracranial injury using one or more of the following biomarkers: GFAP and SNCB; and (c) If the results of steps (a) and (b) do not show an acute injury, Patent Application Attorney Docket No.179.0009-WO00 testing the subject for dementia using one or more of the following biomarkers: phosphorylated Thr181 tau (pT181 tau), IL-6, and brain derived neurotrophic factor (BDNF). [0027] The method may further include comparing levels of one or more of (i) ST2, NRGN, IL-6 and vWF and/or one or more of (ii) pT181-tau, IL-6, and BDNF in the elderly subject to the levels of the same biomarkers in trauma controls. [0028] The trauma controls may be age-matched. [0029] The level of pT181-tau may be increased and the level of at least one of IL-6 or BDNF may be decreased relative to the levels in the age-matched controls. [0030] The method may further include treating the subject for an acute TBI injury if the results of the tests in steps a) and b) show an acute injury. [0031] The elderly subject tested may be monitored over time, and the method may further include comparing levels of one or more of (i) ST2, NRGN, IL-6 and vWF and/or one or more of (ii) pT181-tau, IL-6, and BDNF in the subject at one or more successive timepoints to the levels of the same biomarkers in trauma controls or to the levels of the same biomarkers in the subject at an earlier timepoint. [0032] The method may further include treating the subject for TBI injury if the level of pT181-tau increases over time. [0033] The method may further include treating the elderly subject for dementia if the results of the testing in step c) show dementia. [0034] The method may further include treating the elderly subject for dementia if the level of pT181-tau remains unchanged over time and the levels of one or more of IL-6 and BDNF increases over time. [0035] The method may further include performing neurocognitive testing on the elderly subject. [0036] The neurocognitive testing may include battery and/or digitized neurocognitive tests, or digitized neurocognitive tests conducted using remote computing capability,. [0037] The results of biomarker and/or neurocognitive testing on the elderly subject in the method may predict ongoing symptom burden and, optionally, treating the elderly subject for the symptom burden. DESCRIPTION OF THE FIGURES [0038] FIGS.1A-O show the distributions of brain injury biomarker levels in paired serum (S) and plasma (P) samples from subjects enrolled in the HeadSMART Geriatric Study (n=139). The biomarker levels were determined in simultaneous blood draws obtained in the emergency department. Levels of BDNF, ps129-SNCA, NF-L, vWF, and pT231-tau were higher in serum than in plasma. Levels of p181-Tau, IL-6, and NSE plasma than in serum. FIG.1A shows plasma and serum concentrations of GFAP. Patent Application Attorney Docket No.179.0009-WO00 FIG.1B shows plasma and serum concentrations of NRGN. FIG.1C shows plasma and serum concentrations of ST2. FIG.1D shows plasma and serum concentrations of NSE. FIG.1E shows plasma and serum concentrations of BDNF. FIG.1F shows plasma and serum concentrations of SNCA. FIG.1G shows plasma and serum concentrations of pSNCA. FIG.1H shows plasma and serum concentrations of SNCB. FIG.1I shows plasma and serum concentrations of NfL. FIG.1J shows plasma and serum concentrations of vWF. FIG.1K shows plasma and serum concentrations of MT3. FIG.1L shows plasma and serum concentrations of IL-6. FIG.1M shows plasma and serum concentrations of p181-tau. FIG.1N shows plasma and serum concentrations of pS217-tau. FIG.1O shows plasma and serum concentrations of pT231-tau. [0039] FIGS.2A-J show distributions of biomarker blood level profiles in healthy controls (HC), trauma controls (TC), TBI, and Dementia cohorts across the following age brackets: 18-39 years (young adult) 40-64 years (middle aged adult), 65-74 years (late middle age, early geriatric adult), and 75 to 100 years (old age geriatric. FIG.2A shows blood concentrations of GFAP. FIG.2B shows blood concentrations of NSE. FIG.2C shows blood concentrations of NRGN. FIG.2D shows blood concentrations of BDNF. FIG.2E shows blood concentrations of vWF. FIG.2F shows blood concentrations of ST2. FIG.2G shows blood concentrations of SNCA. FIG.2H shows blood concentrations of pSNCA. FIG.2I shows blood concentrations of SNCB. FIG.2J shows blood concentrations of NfL. [0040] FIGS.3A-O shows Bland-Altman plots for each of the 15 biomarkers analyzed, assessing the agreement between paired plasma and serum samples. Middle horizontal lines represent the mean difference between biofluids and the upper and lower lines represent limits with mean of the difference ± 1.96x standard deviation of the mean of the difference. Proximity of the points to the mean difference line permits assessment of the agreement between the paired plasma and serum samples drawn from subjects simultaneously. FIG.3A shows Bland-Altman plots for GFAP. Patent Application Attorney Docket No.179.0009-WO00 FIG.3B shows Bland-Altman plots for NRGN. FIG.3C shows Bland-Altman plots for ST2. FIG.3D shows Bland-Altman plots for NSE. FIG.3E shows Bland-Altman plots for BDNF. FIG.3F shows Bland-Altman plots for SNCA. FIG.3G shows Bland-Altman plots for pSNCA. FIG.3H shows Bland-Altman plots for SNCB. FIG.3I shows Bland-Altman plots for NfL. FIG.3J shows Bland-Altman plots for vWF. FIG.3K shows Bland-Altman plots for MT3. FIG.3L shows Bland-Altman plots for IL-6. FIG.3M shows Bland-Altman plots for p181-tau. FIG.3N shows Bland-Altman plots for pS217-tau. FIG.3O shows Bland-Altman plots for pT231-tau. [0041] FIG.4 shows trajectories of cognitive impairment measured after injury using digital health software. Individual patients are assigned 5-digit identifiers. Boxed graphs represent individuals had poor cognitive outcomes and/or did not recover. [0042] FIGS.5A-C show directional changes in blood biomarker concentrations over time. Blood samples drawn 1-4 hours apart in the same subjects (multiple sampling for degree and direction of change). FIG.5A shows blood concentrations of GFAP, NRGN, ST2, NSE, BDNF, NfL, vWF, MT3, and IL-6 (collectively: trauma control and mild TBI profile biomarkers) at T0 (first blood draw at initial emergency department presentation) and T1 (1-4 hours after T0) samples. FIG.5B shows blood concentrations of pSNCA, SNCA, and SNCB (collectively: synuclein biomarkers) at T0 and T1 samples. FIG.5C shows blood concentrations of p181-tau, pS217, and pT231-tau (collectively: tau biomarkers) at T0 and T1 samples. [0043] FIGS.6A-6C show robust linear regression plots demonstrating significant directional changes in biomarker concentrations over 1-4 hours after injury (delta analysis) in geriatric subjects after mild TBI. Light- shaded lines bound by Delta characters indicate robust linear regression. Fig.6A shows linear regression from T0 to T1 for BDNF. Fig.6B shows linear regression from T0 to T1 for vWF. Fig.6 C shows linear regression from T0 to T1 for pS217-tau . Patent Application Attorney Docket No.179.0009-WO00 [0044] FIGS.7A-7C show the overall appearance of biomarker distributions between injury types when age, preinjury status, and other factors are not considered. These data show the distributions of blood biomarker levels as measured by immunoassays in serum samples from enrolled trauma control and TBI subjects and from retrospective dementia samples, displayed according to study groups. Fig.7A shows blood concentrations of GFAP, NRGN, ST2, NSE, BDNF, NfL, vWF, MT3, and IL-6 in dementia, trauma control, and mTBI subjects. Fig.7B shows blood concentrations of pSNCA, SNCA, and SNCB (collectively: synuclein biomarkers) in dementia, trauma control, and mTBI subjects. Fig.7C shows blood concentrations of p181-tau, pS217, and pT231-tau (collectively: tau biomarkers) in dementia, trauma control, and mTBI subjects. [0045] FIGS.8A-8J show further analysis of biomarker distributions when separated by pre-injury cognitive impairment status (HC, TC normal, TC impaired, TBI negative normal, TBI positive normal, TBI positive impaired, and Dementia), using validated dementia assessments in the emergency medical setting. FIG.8A shows plasma and serum concentrations of GFAP. FIG.8B shows plasma and serum concentrations of NRGN. FIG.8C shows plasma and serum concentrations of BDNF. FIG.8D shows plasma and serum concentrations of NSE. FIG.8E shows plasma and serum concentrations of vWF. FIG.8F shows plasma and serum concentrations of ST2. FIG.8G shows plasma and serum concentrations of SNCA. FIG.8H shows plasma and serum concentrations of pSNCA. FIG.8I shows plasma and serum concentrations of SNCB FIG.8J shows plasma and serum concentrations of NfL. [0046] FIGS.9A-9B show the Area Under the Curve (AUC)- Receiver Operating Characteristic (ROC) curves for concordance of BrainCheck® Battery digital neurocognitive assessment with clinical gold-standard assessments for cognitive function for all subjects (A; AUC = 0.70) and TBI subjects (B; AUC = 0.71). Fig.9A shows the ROC curve for combined TC and TBI patients. Fig.9B shows the ROC curve for TBI patients. DETAILED DESCRIPTION [0047] The methods, compositions, and kits described herein are based on the discovery that changes in blood levels of certain protein biomarkers over time may distinguish acute TBI from other conditions in elderly patients that present similar symptoms as TBI. Patent Application Attorney Docket No.179.0009-WO00 [0048] TBI is an injury to the head that typically involves an acute mechanical event, in which sheer force, blunt force, or linear acceleration or deceleration damages brain tissue. Those having skill in the art appreciate that even individuals who are completely asymptomatic after a head injury can have symptoms or disabilities that develop over time, such as weeks to months after the initial injury. Late emerging deficits in patients can also result from multiple subclinical or sub-concussive head injuries. [0049] For example, to follow the course of neural inflammation and subsequent degeneration or repair mechanisms in patients who have or are suspected of having TBI, biological samples from the patients are examined at several time points after the patient experiences or presents with TBI. Certain protein biomarkers are detected in elevated (increased), acutely elevated, or decreased amounts, levels, or concentrations in the patient’s sample as well as are biomarkers that are involved with chronic degradative processes in the patient. Thus, the methods in which these protein biomarkers are detected allow for determining the evolution of post- TBI responses and for arriving at an accurate molecular and anatomical picture of TBI in a patient across a given time course. Definitions [0050] The meaning of certain terms and phrases employed in the specification, examples, and appended claims are provided. The definitions are not meant to be limiting in nature and are intended to provide a clearer understanding of certain aspects and embodiments of the invention. [0051] The term “about” as used herein means, in quantitative terms, plus or minus 5%, or in another embodiment, plus or minus 10%, or in another embodiment, plus or minus 15%, or in another embodiment, plus or minus 20%. [0052] The term “one or more of” refers to combinations of various biomarkers. The term encompasses 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15 ,16 ,17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40... to N, where “N” is the total number of protein biomarkers and/or defined sets of protein biomarkers, in the particular embodiment. The term also encompasses at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, at least 12, at least 13, at least 15 ,16 ,17, at least 18, at least 19, at least 20, at least 21, at least 22, at least 23, at least 24, at least 25, at least 26, at least 27, at least 28, at least 29, at least 30, at least 31, at least 32, at least 33, at least 34, at least 35, at least 36, at least 37, at least 38, at least 39, at least 40... to N. It is understood that the recitation of biomarkers herein includes the phrase “one or more of” the biomarkers and, in particular, includes the “at least 1, at least 2, at least 3” and so forth language in each recited embodiment of a biomarker panel. [0053] “Altered” as used herein can refer to an increase or decrease, as in, for example, an increase or decrease in biomarker concentrations or levels in a biological sample. An increase is any positive change, e.g., by at least about 5%, 10%, or 20%; by at least about 25%, 50%, 75%, or even by 100%, 200%, 300% or more, Patent Application Attorney Docket No.179.0009-WO00 including values between the stated percentages. A decrease is a negative change, e.g., a decrease by at least about 5%, 10%, or 20%; by at least about 25%, 50%, 75%; or even an increase by 100%, 200%, 300% or more, including values between the stated percentages. [0054] As used herein, the terms “comparing”, or “comparison” refers to assessing how the proportion, level or cellular localization of one or more biomarkers in a sample from a patient relates to the proportion, level or cellular localization of the corresponding one or more biomarkers in a standard or control sample. For example, “comparing” may refer to assessing whether the proportion, level, or cellular localization of one or more biomarkers in a sample from a patient is the same as, more or less than, or different from the proportion, level, or cellular localization of the corresponding one or more biomarkers in standard or control sample. More specifically, the term may refer to assessing whether the proportion, level, or cellular localization of one or more biomarkers in a sample from a patient is the same as, more or less than, different from or otherwise corresponds (or not) to the proportion, level, or cellular localization of predefined biomarker levels/ratios that correspond to, for example, a patient having a neurological injury or brain injury, not having a neurological injury or brain injury, is responding to treatment for a neurological injury or brain injury, is not responding to treatment for the neurological injury or brain injury, is/is not likely to respond to a particular treatment for the neurological injury or brain injury, or having /not having another disease or condition like, for example, dementia. In one embodiment of the invention, the term “comparing” refers to assessing whether the level of one or more biomarkers of embodiments of the invention in a sample from an individual is the same as, more or less than, different from or other otherwise corresponds (or not) to levels/ratios of the same biomarkers in a control sample (e.g., predefined levels/ratios that correlate to: Healthy individuals; Individuals with no neurological injury or brain injury, Individuals with a lesser degree of neurological injury or brain injury, standard brain injury levels/ratios, etc.; Individuals with a non-neurological or brain trauma injury; and Individuals with other types of neurological disorders (e.g., Dementia, Alzheimer’s Disease, etc.). In another embodiment of the invention, the terms “comparing”, or “comparison” refers to assessing how the proportion, level or cellular localization of one or more biomarkers in a sample from a patient relates to the proportion, level or tissue localization of another biomarker in the same sample. For example, a ratio of one biomarker to another from the same patient sample can be compared. In yet another embodiment of the invention, the terms “comparing”, or “comparison” refers to assessing how the proportion, level of one or more biomarkers in a sample from a subject relates to the proportion or level of one or more biomarkers in the same subject at one or more different timepoints. [0055] As used herein, the terms “indicates” or “correlates” (or “indicating” or “correlating,” or “indication” or “correlation,” depending on the context) in reference to a parameter, e.g., a modulated proportion, level, or cellular localization in a sample from a patient, may mean that the patient is improving, not improving, etc. In Patent Application Attorney Docket No.179.0009-WO00 specific embodiments of the invention, the parameter may include the level of one or more biomarkers as described herein. A particular set or pattern of the amounts of one or more biomarkers may indicate that a patient has improved or worsened. [0056] The term “brain injury” refers to a condition in which the brain (central nervous system or neurological system) is damaged by injury caused by an event. As used herein, an “injury” is an alteration in cellular or molecular integrity, activity, level, robustness, state, or other alteration that is traceable to an event. For example, an injury includes a physical, mechanical, chemical, biological, functional, infectious, or other modulator of cellular or molecular characteristics. An event can include a physical trauma such as a single or repetitive impact (percussive) or a biological abnormality such as a stroke resulting from either blockade or leakage of a blood vessel. An event is optionally an infection by an infectious agent. A person of skill in the art recognizes numerous equivalent events that are encompassed by the terms "injury" and "event". [0057] More specifically, the term “brain injury” refers to a condition that results in central nervous system damage, irrespective of its pathophysiological basis. Among the most frequent origins of a “brain injury” are stroke and traumatic brain injury (TBI). [0058] The term “brain injury” also refers to subclinical brain injury, spinal cord injury, and anoxic-ischemic brain injury. The term “subclinical brain injury” (SCI) refers to brain injury without overt clinical evidence of brain injury. A lack of clinical evidence of brain injury when brain injury exists could result from degree of injury, type of injury, level of consciousness, medications particularly sedation and anesthesia. [0059] The phrase “brain injury status” includes any distinguishable manifestation of brain injury, as the case may be, (e.g., TBI, mTBI or concussion), including not having brain injury. For example, brain injury status includes, without limitation, brain injury or non-injury in a patient, the stage or severity of brain injury, the progress of brain injury (e.g., progress of brain injury over time), or the effectiveness or response to treatment of brain injury (e.g., clinical follow up and surveillance of brain injury after treatment). Based on this status, further procedures may be indicated, including additional diagnostic tests or therapeutic procedures or regimens. [0060] The meaning of the term “elderly” is understood by an individual of an ordinary skill in the art, for example, a clinician, based on various factors, which may not necessarily be based on chronological age, including, for example, general health, and familial history (e.g., genetics) of a subject and a diagnosis of dementia, Alzheimer’s, Parkinson’s or similar conditions (hereinafter “Elderly Conditions”). An “elderly subject” refers to a subject who is at least 50 year old, and, more particularly, at least 65 years old; however, subjects younger than 50 who have any of Elderly Conditions or are suspected of having any of Elderly Conditions may be included as well. The terms “elderly subject” and “geriatric subject” can be used interchangeably. Patent Application Attorney Docket No.179.0009-WO00 [0061] The term “traumatic brain injury” or “TBI” refers to traumatic injuries to the brain which occur when physical trauma causes brain damage. For example, TBI can result from a closed head injury or a penetrating head injury. Symptoms of TBI can be mild (even imperceptible at first) and include headache, confusion, visual disturbances, and nausea. Signs of severe TBI include loss of consciousness exceeding six hours, convulsions, dilation of the pupils, and dizziness. TBI is graded as mild (mild TBI or “mTBI”) meaning a brief change in mental status or consciousness), moderate, or severe (meaning an extended period of unconsciousness or amnesia after the injury) on the basis of the level of consciousness or Glasgow coma scale (GCS) score after resuscitation. The GCS scores eye opening (spontaneous =4, to speech=3, to pain=3, none=1), motor response (obeys=6, localizes=5, withdraws=4, abnormal flexion=3, extensor response=2, none=1), and verbal response (oriented=5, confused=4, inappropriate=3, incomprehensible=2, none=1). Mild TBI (GCS 13-15) is in most cases a concussion and there is full neurological recovery, although many of these patients have short-term memory and concentration difficulties. In moderate TBI (GCS 9-13) the patient is lethargic or stuporous, and in severe injury (GCS 3-8) the patient is comatose, unable to open his or her eyes or follow commands. [0062] “Acute TBI” refers to the period of TBI that extends from the time of injury through about the first three days. [0063] “Post-acute TBI” refers to the period of TBI that extends from the acute period days and up to about one month after injury. [0064] “Chronic TBI” chronic period is generally understood in the TBI field to begin at least about 3 months after injury, when initial symptoms should have resolved. Persisting injury related symptoms and processes are then considered to be in the chronic period after injury when tested at 6 months, as presented in this application. [0065] A “non-traumatic brain injury” refers to brain injuries that do not involve ischemia or external mechanical force (e.g., stroke, Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, multiple sclerosis, amyotrophic lateral sclerosis, brain hemorrhage, brain infections, brain tumor, among others). [0066] The term “mild traumatic brain injury (mTBI)” is also commonly known as “concussion” and refers to the occurrence of injury to the head or brain arising from blunt trauma or impact, or forceful motion of the head (acceleration or deceleration forces) causing one or more of the following conditions attributable to head injury: transient confusion, disorientation, or impaired consciousness; dysfunction of memory around the time of injury; or loss of consciousness lasting less than 30 minutes. One or more of the symptoms of mTBI can last a year or more following the initial head or brain injury. While early mTBI symptoms may appear to be mild, they can lead to significant, life-long impairment in an individual’s ability to function physically, cognitively and psychologically. While the term “concussion” is used interchangeably with mTBI at times, concussions cover a clinical spectrum and may occur without loss of consciousness. Mild concussion may be present even if there is Patent Application Attorney Docket No.179.0009-WO00 no external sign of trauma to the head. The spectrum of concussions related to sports injuries are defined by The Quality Standards Subcommittee of the American Academy of Neurology as follows: Grade 1 concussion: transient confusion, no loss of consciousness and duration of mental status abnormalities on examination that resolve in less than 15 minutes; Grade 2 concussion: transient confusion, no loss of consciousness, concussion symptoms or mental status abnormalities on examination that last more than 15 minutes; and Grade 3 concussion: any loss of consciousness, either brief (seconds) or prolonged (minutes).(Centers for Disease Control and Prevention). [0067] As used herein, “secondary brain trauma” refers to damage to the brain of a patient post-acute brain injury, i.e., during the secondary injury phase of a TBI. [0068] As used herein, “acute brain injury” refers to the condition of a patient who has suffered a neurological or brain injury and at a relatively short number of hours, such as 1-10 hours, 1-8 hours, 1-5 hours, 2-5 hours, 3- 5 hours, 4-5 hours, and the like from the actual time of the injury. [0069] As used herein, “sub-acute brain injury” refers to the condition of a patient who has suffered a neurological or brain injury from about 2-5 days post injury. [0070] As used herein, “chronic brain injury” refers to the condition of a patient who has suffered a neurological or brain injury from about three days post injury until at least 12 months previously, or from about 1-5 months, or about 1-3 months from the actual time of injury yet continues to present symptoms of brain injury. [0071] As used herein, the term “biomarker” refers to a molecule that is associated either quantitatively or qualitatively with a biological change. Examples of biomarkers include polypeptides, proteins or fragments of a polypeptide or protein; and polynucleotides, such as a gene product, RNA or RNA fragment, or encoding polynucleotides; and other body metabolites. In certain embodiments of the invention, a “biomarker” means a molecule (e.g., a protein) that is differentially present (i.e., increased or decreased) in a biological sample from a subject or a group consisting of subjects having a first phenotype (e.g., having a disease or condition) as compared to a biological sample from a subject or group consisting of subjects having a second phenotype (e.g., not having the disease or condition or having a less severe version of the disease or condition). A biomarker may be differentially present at any level, but is generally present at a level that is decreased by at least 5%, by at least 10%, by at least 15%, by at least 20%, by at least 25%, by at least 30%, by at least 35%, by at least 40%, by at least 45%, by at least 50%, by at least 55%, by at least 60%, by at least 65%, by at least 70%, by at least 75%, by at least 80%, by at least 85%, by at least 90%, by at least 95%, or by 100% (i.e., absent); or that is increased by at least 5%, by at least 10%, by at least 15%, by at least 20%, by at least 25%, by at least 30%, by at least 35%, by at least 40%, by at least 45%, by at least 50%, by at least 55%, by at least 60%, by at least 65%, by at least 70%, by at least 75%, by at least 80%, by at least 85%, by at least 90%, by at least 95%, by Patent Application Attorney Docket No.179.0009-WO00 at least 100%, by at least 110%, by at least 120%, by at least 130%, by at least 140%, by at least 150%, or more. Alternatively, the differential presence of a biomarker can be characterized by a -fold change in level including, for example, a level that is decreased by 1.1-fold, at least 1.2-fold, at least 1.3-fold, at least 1.4-fold, at least 1.5-fold, at least 2.0-fold, at least 2.5-fold, at least 3.0-fold, at least 3.5-fold, at least 4.0-fold, at least 5-fold, at least 5.5-fold, at least 6-fold, at least 6.5-fold, at least 7.0-fold, at least 7.5-fold, at least 8.0-fold, at least 9-fold, at least 10-fold, at least 11-fold, at least 12-fold, at least 13-fold, at least 14-fold, at least 15-fold, at least 16- fold, at least 17-fold, at least 18-fold, at least 19-fold, at least 20-fold, at least 25-fold, at least 30-fold, at least 40-fold, or at least 50-fold; or that is increased by 1.1-fold, at least 1.2-fold, at least 1.3-fold, at least 1.4-fold, at least 1.5-fold, at least 2.0-fold, at least 2.5-fold, at least 3.0-fold, at least 3.5-fold, at least 4.0-fold, at least 5- fold, at least 5.5-fold, at least 6-fold, at least 6.5-fold, at least 7.0-fold, at least 7.5-fold, at least 8.0-fold, at least 9-fold, at least 10-fold, at least 11-fold, at least 12-fold, at least 13-fold, at least 14-fold, at least 15-fold, at least 16-fold, at least 17-fold, at least 18-fold, at least 19-fold, at least 20-fold, at least 25-fold, at least 30-fold, at least 40-fold, or at least 50-fold. A biomarker is preferably differentially present at a level that is statistically significant (e.g., a p-value less than 0.05 and/or a q-value of less than 0.10 as determined using, for example, either Welch’s T-test or Wilcoxon’s rank-sum Test). The term “peptide biomarkers derived therefrom” includes the isoforms and/or post-translationally modified forms of any of the foregoing. Embodiments of the invention contemplate the detection, measurement, quantification and/or determination or other analysis of both unmodified and modified (e.g., citrullination or other post-translational modification) proteins/polypeptides/peptides, as well as autoantibodies to any of the foregoing. For example, in some embodiments of the invention, the method includes the detection, measurement, quantification and/or determination or other analysis of both unmodified and modified forms of Aldolase C (ALDOC), BDNF, GFAP, IL-6, MT3, NfL, NRGN, NSE, SNCA, SNCB, pS129-SNCA, sST2, pT181 tau, pS217 tau, pT231 tau, and/or vWF.. [0072] The term “biomarker panel” refers to a collection of a plurality of biomarkers grouped together for use in the embodiments of the methods, compositions and kits of the invention. The biomarkers in the panel may be protein biomarkers, or peptide biomarkers derived therefrom. In some embodiments of the methods, compositions or kits of the invention, the protein biomarker panel includes, but is not limited to any combination of brain derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), interleukin-6 (IL- 6), metallothionein 3 (MT3), neurofilament light chain (NfL), neurogranin (NRGN), neuron specific enolase (NSE), synuclein alpha (SNCA), synuclein beta (SNCB), phosphorylated Ser129 SNCA (pS129-SNCA), soluble receptor for interleukin-33 (ST2), phosphorylated Thr181 tau (pT181 tau), phosphorylated Ser217 tau (pS217 tau), phosphorylated Thr231 tau (pT231 tau), and von Willebrand factor (vWF), and Fatty acid binding protein 7 (FABP7). For example, a biomarker panel may include vWF and one or more of NRGN, BDNF, and FABP7. Patent Application Attorney Docket No.179.0009-WO00 [0073] In other embodiments, a particular set or pattern of the amounts of one or more biomarkers may be correlated to a patient being unaffected (i.e., indicates a patient does not have brain injury). In certain embodiments, “indicating,” or “correlating,” as used according to embodiments of the invention, may be by any linear or non-linear method of quantifying the relationship between levels/ratios of biomarkers to a standard, control or comparative value for the assessment of the diagnosis, prediction of a neurological injury, brain injury or progression thereof, assessment of efficacy of clinical treatment, identification of a patient who may respond to a particular treatment regime or pharmaceutical agent, monitoring of the progress of treatment, and in the context of a screening assay, for the identification of a therapeutic for the neurological injury or brain injury. [0074] “Magnetic resonance imaging (MRI)” of the brain is a noninvasive and painless neuroimaging test for detailed visualization and analysis that uses a magnetic field and radio waves to produce detailed images of the brain and the brain stem. Unlike a CAT scan (also called a CT scan; computed axial tomography scan), an MRI scan does not use radiation. In some cases, a dye (contrast dye) or contrast material (e.g., iodine, barium, or gadolinium) is used during the MRI to allow visualization of the brain structures (e.g., blood vessels and tissue) more clearly. For example, the dye may show blood flow and areas of inflammation or edema. In some embodiments of the invention, the method detects changed or altered blood-brain barrier permeability signals in the brain by using Dynamic Contrast Enhanced MRI (DCE-MRI). In other embodiments of the invention, MRI is used to detect changed or altered blood-brain barrier permeability signals in the brain. In yet other embodiments of the invention, diffusion weighted tensor imaging (DTI-MRI) is used to detect changed or altered white matter integrity signals in the brain. In other embodiments, T1 weighted MRI images are analyzed, with Jacobian determinant (JD) brain atrophy rates or other quantification method is used in white matter, grey matter and CSF to quantify loss or to determine TBI-specific spatial patterns. In other embodiments, variations of either T1-weighted or T2-weighted MRI methods are used to measure or quantify the number of microhemorrhages or to calculate a sum or overall hemorrhage burden value. [0075] The terms “patient,” “individual,” or “subject” are used interchangeably herein, and refer to a mammal, particularly, a human. The patient may have a mild, intermediate or severe disease or condition. The patient may be an individual in need of treatment or in need of diagnosis based on particular symptoms or personal or family history. In some cases, the terms may refer to treatment in experimental animals, in veterinary application, and in the development of animal models for disease, including, but not limited to, rodents including mice, rats, and hamsters; and primates. [0076] The terms “measuring” and “determining” are used interchangeably throughout and refer to methods which include obtaining or providing a patient sample and/or detecting the level (or amount) of a biomarker(s) in a sample. In one embodiment, the terms refer to obtaining or providing a patient sample and detecting the Patent Application Attorney Docket No.179.0009-WO00 level of one or more biomarkers in the sample. In another embodiment, the terms “measuring” and “determining” mean detecting the level of one or more biomarkers in a patient sample. The term “measuring” is also used interchangeably throughout with the term “detecting.” In certain embodiments, the term is also used interchangeably with the term “quantifying.” [0077] The terms “sample,” “patient sample,” “biological sample,” “biologic sample,” “biofluid sample,” and the like, encompass a variety of sample types obtained from a patient, individual, or subject and can be used in a diagnostic, screening, or monitoring assay. The patient sample may be obtained from a healthy subject, or a patient suspected of having or having associated symptoms of neurological injury or brain injury. Moreover, a sample obtained from a patient can be divided, and only a portion may be used for diagnosis. Furthermore, the sample, or a portion thereof, can be stored under conditions to maintain sample for later analysis. The definition of “sample” specifically encompasses blood, serum, plasma, cerebrospinal fluid (CSF) and other liquid samples of biological origin, including, but not limited to, peripheral blood, blood plasma, serum, cerebrospinal fluid, amniotic fluid, tears, urine, saliva, stool, semen, sweat, secretions and synovial fluid. A sample also encompasses solid tissue samples, such as a biopsy specimen or cells derived therefrom, or tissue culture cells and the progeny thereof. A tissue or cell sample may be processed (e.g., homogenized, etc.) to produce a suspension or dispersion in liquid form, as discussed below. In a specific embodiment, a sample includes a blood sample. In another embodiment, a sample includes a plasma sample. In yet another embodiment, a serum sample is used. In certain embodiments, a sample includes cerebrospinal fluid. [0078] The definition of “sample” also includes samples that have been manipulated in any way after their procurement, such as by centrifugation, filtration, precipitation, dialysis, chromatography, treatment with reagents, washed, or enriched for certain cell populations. The terms further encompass a clinical sample, and includes cells in culture, cell supernatants, tissue samples, organs, and the like. Samples may also include fresh- frozen and/or formalin-fixed, paraffin-embedded tissue blocks, such as blocks prepared from clinical or pathological biopsies, prepared for pathological analysis or study by immunohistochemistry. A sample may be tested immediately after collection, or it may be tested after storage at 4°C, -20°C, or -80°C. Storage times may be 24 hours, 1 week, 1 month, 1 year, 10 years or up to 30 years, depending on stability of the sample and storage conditions. [0079] Various methodologies of the embodiments of the invention include a step that involves comparing a value, level, feature, characteristic, property, etc. to a “suitable control,” referred to interchangeably herein as an “appropriate control,” a “control sample,” a “reference” or simply a “control.” A “suitable control,” “appropriate control,” “control sample,” “reference” or a “control” is any control or standard familiar to one of ordinary skill in the art useful for comparison purposes. A “reference level” of a biomarker means a level of the biomarker that is indicative of a particular disease state, phenotype, or lack thereof, as well as combinations of Patent Application Attorney Docket No.179.0009-WO00 disease states, phenotypes, or lack thereof. A “positive” reference level of a biomarker means a level that is indicative of a particular disease state or phenotype. A “negative” reference level of a biomarker means a level that is indicative of a lack of a particular disease state or phenotype. For example, a “brain injury-positive reference level” of a biomarker means a level of a biomarker that is indicative of brain injury in a subject, and a “brain injury-negative reference level” of a biomarker means a level of a biomarker that is indicative of no brain injury of in a subject. [0080] A “reference level” of a biomarker may be an absolute or relative amount or concentration of the biomarker, a presence or absence of the biomarker, a range of amount or concentration of the biomarker, a minimum and/or maximum amount or concentration of the biomarker, a mean amount or concentration of the biomarker, and/or a median amount or concentration of the biomarker; and, in addition, “reference levels” of combinations of biomarkers may also be ratios of absolute or relative amounts or concentrations of two or more biomarkers with respect to each other. Appropriate positive and negative reference levels of biomarkers for a particular disease state, phenotype, or lack thereof may be determined by measuring levels of desired biomarkers in one or more appropriate subjects, and such reference levels may be tailored to specific populations of subjects (e.g., a reference level may be age-matched so that comparisons may be made between biomarker levels in samples from subjects of a certain age and reference levels for a particular disease state, phenotype, or lack thereof in a certain age group). Such reference levels may also be tailored to specific techniques that are used to measure levels of biomarkers in biological samples (e.g., ELISA, PCR, LC-MS, GC-MS, etc.), where the levels of biomarkers may differ based on the specific technique that is used. [0081] In one embodiment, a “suitable control” or “appropriate control” is a value, level, feature, characteristic, property, etc., determined in an individual or biological sample obtained from an individual or group of individuals, (e.g., a control or normal cell, organ, or patient, exhibiting, for example, normal traits. For example, the biomarkers of the embodiments of the invention may be assayed for levels/ratios in a sample from an unaffected individual (UI) (e.g., no brain injury) or a normal control individual (NC) (both terms are used interchangeably herein). For example, a “suitable control” or “appropriate control” can be a value, level, feature, characteristic, property, ratio, etc. determined prior to performing a therapy (e.g., brain injury treatment) on a patient or a value, level, feature, characteristic, property, ratio, etc. determined prior to disease development (e.g., a baseline test). In a further embodiment, a “suitable control” or “appropriate control” is a predefined value, level, feature, characteristic, property, ratio, etc. A “suitable control” can be a profile or pattern of levels/ratios of one or more biomarkers of embodiments of the invention that correlates to brain injury, to which a patient sample can be compared. The patient sample can also be compared to a negative control, i.e., a profile that correlates to not having brain injury. Patent Application Attorney Docket No.179.0009-WO00 [0082] As used herein, the term “predetermined threshold value of expression” of a biomarker refers to the level of expression of the same biomarker (expressed, for example, in ng/ml) in a corresponding control/normal sample or group consisting of control/normal samples obtained from normal, or healthy, subjects, i.e., subject who do not have brain injury. Further, the term “altered level of expression” of a biomarker in a sample refers to a level that is either below or above the predetermined threshold value of expression for the same biomarker and thus encompasses either high (increased) or low (decreased) expression levels. In particular embodiments, the biomarkers described herein are increased or decreased relative to age-matched (and/or sex-matched) controls. [0083] The terms “specifically binds to,” “specific for,” and related grammatical variants refer to that binding which occurs between such paired species as enzyme/substrate, receptor/agonist, antibody/antigen, aptamer/target, and lectin/carbohydrate which may be mediated by covalent or non-covalent interactions or a combination of covalent and non-covalent interactions. When the interaction of the two species produces a non-covalently bound complex, the binding which occurs is typically electrostatic, hydrogen-bonding, or the result of lipophilic interactions. Accordingly, “specific binding” occurs between a paired species where there is interaction between the two which produces a bound complex having the characteristics of an antibody/antigen or enzyme/substrate interaction. In particular, the specific binding is characterized by the binding of one member of a pair to a particular species and to no other species within the family of compounds to which the corresponding member of the binding member belongs. Thus, for example, an antibody typically binds to a single epitope and to no other epitope within the family of proteins. In some embodiments, specific binding between an antigen and an antibody will have a binding affinity of at least 10-6 M. In other embodiments, the antigen and antibody will bind with affinities of at least 10-7 M, 10-8 M to 10-9 M, 10-10 M, 10-11 M, or 10-12 M. As used herein, the terms “specific binding” or “specifically binding” when used in reference to the interaction of an antibody and a protein or peptide means that the interaction is dependent upon the presence of a particular structure (i.e., the epitope) on the protein. [0084] By “antibody” means any immunoglobulin polypeptide, or fragment thereof, having immunogen or antigen binding ability. As used herein, the terms “antibody fragments”, “fragment”, or “fragment thereof” refer to a portion of an intact antibody, in particular, an immunogen- or antigen-binding portion of the antibody. Examples of antibody fragments include, but are not limited to, linear antibodies; single-chain antibody molecules; Fc or Fc’ peptides, Fab and Fab fragments, and multi-specific antibodies formed from antibody fragments. In most embodiments, the terms also refer to fragments that bind an antigen of a target molecule (e.g., a protein biomarker described herein) and can be referred to as “antigen-binding fragments.” As used herein, the term “antibody” is used in reference to any immunoglobulin molecule that reacts with a specific antigen. It is intended that the term encompass any immunoglobulin (e.g., IgG, IgM, IgA, IgE, IgD, etc.) Patent Application Attorney Docket No.179.0009-WO00 obtained from any source (e.g., humans, rodents, non-human primates, caprines, bovines, equines, ovines, etc.). Specific types/examples of antibodies include polyclonal, monoclonal, humanized, chimeric, human, or otherwise-human-suitable antibodies. “Antibodies” also includes any fragment or derivative of any of the herein described antibodies that specifically binds the target antigen. [0085] By “an effective amount” means the amount of a required to ameliorate the symptoms of a disease relative to an untreated patient. The effective amount of active compound(s) used to practice embodiments of the invention for therapeutic treatment of brain injury varies depending upon the manner of administration, the age, body weight, and general health of the subject. Ultimately, the attending physician or veterinarian will decide the appropriate amount and dosage regimen. Such amount is referred to as an “effective” amount. [0086] As used herein and in the appended claims, the singular forms “a,” “an,” and “the” include the plural reference unless the context clearly dictates otherwise. Thus, for example, a reference to a “protein” is a reference to one or more proteins, and includes equivalents thereof known to those skilled in the art and so forth. [0087] 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. Specific methods, devices, and materials are described, although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of embodiments of the invention. It is understood that embodiments of the invention are not limited to the particular methods and components, etc., described herein, as these may vary. It is also to be understood that the terminology used herein is used for the purpose of describing particular embodiments only and is not intended to limit the scope of the invention. [0088] All publications cited herein are hereby incorporated by reference, including all grants, journal articles, books, manuals, published patent applications, and issued patents. [0089] In some embodiments of the invention, biomarkers may be detected and/or measured by immunoassay. An immunoassay requires biospecific capture reagents/binding agents, such as antibodies, to capture the biomarkers. Many antibodies are available commercially. Antibodies also can be produced by methods well known in the art, e.g., by immunizing animals with the biomarkers. Biomarkers can be isolated from samples based on their binding characteristics. Alternatively, if the amino acid sequence of a polypeptide biomarker is known, the polypeptide can be synthesized and used to generate antibodies by methods well- known in the art. [0090] Detection methods suitable for use methods of the invention, include, without limitation, traditional immunoassays including, for example, sandwich immunoassays including enzyme-linked immunosorbent assays (ELISA) or fluorescence-based immunoassays, immunoblots, Western Blots (WB), as well as other enzyme immunoassays. Multiplex ELISA assays are also suitable for use. Nephelometry is an assay performed in Patent Application Attorney Docket No.179.0009-WO00 liquid phase, in which antibodies are in solution. The binding of a protein antigen to a specific antibody results in changes in absorbance, a parameter that is measured. In a SELDI-based immunoassay, a biospecific capture reagent for the biomarker is attached to the surface of an MS probe, such as a pre-activated protein chip array. The biomarker is then specifically captured on the biochip through this reagent, and the captured biomarker is detected by mass spectrometry. [0091] In certain embodiments of the invention, the expression levels of the biomarkers employed herein are quantified by immunoassay, such as ELISA technology. In specific embodiments of the invention, the levels of expression of the biomarkers are determined by contacting the biological sample with a plurality of antibodies, or antigen binding fragments thereof, that selectively bind to the biomarkers; and detecting binding of the antibodies, or antigen binding fragments thereof, to the biomarkers. In certain embodiments, the binding agents employed in the disclosed methods and compositions are labeled with a detectable moiety. [0092] For example, the level of a biomarker in a sample can be assayed by contacting the biological sample with an antibody, or antigen binding fragment thereof, that selectively binds to the target biomarker (referred to as a capture molecule or antibody or a binding agent), and detecting the binding of the antibody, or antigen- binding fragment thereof, to the biomarker. The detection can be performed using a second antibody to bind to the capture antibody complexed with its target biomarker. A target biomarker can be an entire protein, or a variant or modified form thereof. Kits for the detection of biomarkers as described herein can include pre- coated strip plates, biotinylated secondary antibody, standards, controls, buffers, streptavidin-horse radish peroxidase (HRP), tetramethyl benzidine (TMB), stop reagents, and detailed instructions for carrying out the tests including performing standards. Further embodiments of the invention provide compositions that can be employed in the disclosed methods. In certain embodiments of the invention, such compositions include a solid substrate and a plurality of antibodies, commonly known in the art as a “panel” of antibodies, that are immobilized on the substrate, wherein each of the antibodies is immobilized at a different, indexable, location on the substrate and the antibodies selectively bind to a plurality of biomarkers present in a biological sample. Panels of the invention may include antibodies or antigen-binding fragments to specifically detect 2 or more, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more, 9 or more, 10 or more, 11 or more, 12 or more, 13 or more, 14 or more, 15 or more, 16 or more, 17 or more, 18 or more, 19 or more, 20 or more, 30 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 or more, 90 or more, or 100 or more, biomarkers. For example, two or more protein biomarkers may be selected from brain derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), interleukin-6 (IL-6), metallothionein 3 (MT3), neurofilament light chain (NfL), neurogranin (NRGN), neuron specific enolase (NSE), synuclein alpha (SNCA), synuclein beta (SNCB), phosphorylated Ser129 SNCA (pS129-SNCA); soluble receptor for interleukin-33 (sST2); phosphorylated Thr181 tau (pT181-tau); Patent Application Attorney Docket No.179.0009-WO00 phosphorylated Ser217-tau (pS217-tau); phosphorylated Thr231 tau (pT231 tau); and von Willebrand factor (vWF). More particularly, the one of more protein biomarkers may include a panel that includes 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15 of the following biomarkers: NRGN, ST2, NSE, BDNF; NRGN, NSE, BDNF, vWF; NRGN, ST2, vWF, pSNCA; GFAP, ST2, NSE, BDNF; GFAP, NRGN, ST2, pSNCA; GFAP, NRGN, ST2, BDNF; GFAP, NRGN, pSNCA; ST2, NSE, BDNF; GFAP, ST2, BDNF, pSNCA; NRGN, ST2, NSE, and vWF. For example, a biomarker panel of the invention may include antibodies specific for one or more of the following sets of (a) NRGN, ST2, NSE, and BDNF; (b) NRGN, NSE, BDNF, and vWF; (c) NRGN, ST2, vWF, and pSNCA; (d) GFAP, ST2, NSE, and BDNF; (e) GFAP ,NRGN, ST2, and pSNCA; (f) GFAP, NRGN, ST2, and BDNF; (g) GFAP, NRGN, and pSNCA; (h) ST2, NSE, and BDNF; (i) GFAP, ST2, BDNF, and pSNCA; (j) NRGN, ST2, NSE, and vWF; (k) GFAP, NRGN, IL-6 and p181- Tau; (l) NRGN, ST2, NSE, and SNCA; (m) GFAP, NRGN, IL-6 and vWF; (n) SNCA and ST2; (n) GFAP and SNCB; (o) GFAP and ST2; and (p) GFAP, NRGN, BDNF, vWF, IL-6, ST2, and phosphoS217-Tau.Each of the sets of biomarker panels disclosed in this application, such as sets (a) – (o) immediately above, may include any one, more than one, or all of the biomarkers in the set. [0093] Solid phase substrates, or carriers, that can be effectively employed in such assays are well known to those of skill in the art and include, for example, 96-well microtiter plates, glass, paper, and microporous membranes constructed, for example, of nitrocellulose, nylon, polyvinylidene difluoride, polyester, cellulose acetate, mixed cellulose esters and polycarbonate. Suitable microporous membranes include, for example, those described in U.S. Patent Application Publication No. U.S.2010/0093557 A1. Methods for performing assays employing such panels include those described, for example, in U.S. Patent Application Publication Nos. US2010/0093557A1 and US2010/0190656A1, the disclosures of which are incorporated by reference herein. [0094] In a related aspect, methods for assessing brain injury, e.g., mTBI or concussion, in a subject are provided, such methods including: (a) contacting a biological sample obtained from the subject with a composition disclosed herein for a period of time sufficient to form binding agent-polypeptide biomarker complexes; (b) detecting binding of the plurality of binding agents to the plurality of polypeptide biomarkers in the protein biomarker panel, thereby determining the levels of expression of the plurality of polypeptide biomarkers in the biological sample; and (c) comparing the levels of expression of the plurality of polypeptide biomarkers in the biological sample with predetermined threshold values, wherein levels of expression of at least one of the plurality of polypeptide biomarkers above or below the predetermined threshold values indicates brain injury status in the subject. [0095] Multiplex arrays in several different formats based on the utilization of, for example, flow cytometry, chemiluminescence or electron-chemiluminescence technology, can be used. Flow cytometric multiplex arrays, also known as bead-based multiplex arrays, include the Cytometric Bead Array (CBA) system from BD Biosciences (Bedford, Mass.), and several bead based microfluidics cassette systems, for rapid immunological Patent Application Attorney Docket No.179.0009-WO00 testing suitable for point of care solutions, spinning disc based microfluidics technologies using antibody-bead conjugates such as Quanterix Simoa assays or SpinDisc assays, and multi-analyte profiling (xMAP®) technology from Luminex Corp. (Austin, Tex.), all of which employ bead sets which are distinguishable by fluidics. For example, each bead set is coated with a specific capture antibody. Fluorescence or streptavidin-labeled detection antibodies bind to specific capture antibody-biomarker complexes formed on the bead set. Multiple biomarkers can be recognized and measured by differences in the bead sets, with chromogenic or fluorogenic emissions being detected using flow cytometric analysis. [0096] In an alternative format, a multiplex ELISA from Quansys Biosciences (Logan, Utah) coats multiple specific capture antibodies at multiple spots (one antibody at one spot) in the same well on a 96-well microtiter plate. Chemiluminescence technology is then used to detect multiple biomarkers at the corresponding spots on the plate. Detection by Mass Spectrometry [0097] In one embodiment of the invention, biomarkers may be detected by mass spectrometry, a method that employs a mass spectrometer to detect gas phase ions. Examples of mass spectrometers are time-of- flight, magnetic sector, quadrupole filter, ion trap, ion cyclotron resonance, Orbitrap™, hybrids or combinations of the foregoing, and the like. [0098] In some embodiments of the invention, biomarkers are detected using SRM (Selected Reaction Monitoring), MRM (Multiple Reaction Monitoring), and PRM (Parallel Reaction Monitoring), which are all targeted analysis techniques used to specifically quantify pre-selected peptides or molecules within a complex sample such as a biospecimen. Selected reaction monitoring (SRM) is a non-scanning mass spectrometry technique, performed on triple quadrupole-like instruments and in which collision-induced dissociation is used as a means to increase selectivity. In SRM experiments two mass analyzers are used as static mass filters, to monitor a particular fragment ion of a selected precursor ion. The specific pair of mass-over-charge (m/z) values associated to the precursor and fragment ions selected is referred to as a “transition” and can be written as parent m/z→fragment m/z (e.g., 673.5→534.3). Unlike common MS based proteomics, no mass spectra are recorded in a SRM analysis. Instead, the detector acts as a counting device for the ions matching the selected transition thereby returning an intensity distribution over time. Multiple SRM transitions can be measured within the same experiment on the chromatographic time scale by rapidly toggling between the different precursor/fragment pairs (sometimes called multiple reaction monitoring, MRM). Typically, the triple quadrupole instrument cycles through a series of transitions and records the signal of each transition as a function of the elution time. The method allows for additional selectivity by monitoring the chromatographic co-elution of multiple transitions for a given analyte. The terms SRM/MRM are occasionally used also to describe experiments conducted in mass spectrometers other than triple quadrupoles (e.g., in trapping Patent Application Attorney Docket No.179.0009-WO00 instruments) where upon fragmentation of a specific precursor ion a narrow mass range is scanned in MS2 mode, centered on a fragment ion specific to the precursor of interest or in general in experiments where fragmentation in the collision cell is used as a means to increase selectivity. In this application the terms SRM and MRM or also SRM/MRM can be used interchangeably because they both refer to the same mass spectrometer operating principle. PRM is a similar method to detect and quantify target molecules where all forms are detected in parallel. MRM, SRM and PRM all allow relative and absolute quantification of proteins, peptides and metabolites. As a matter of clarity, the term MRM is used throughout the text, but the term includes SRM, MRM, PRM, as well as any analogous technique, such as e.g. highly-selective reaction monitoring, hSRM, LC-SRM or any other SRM/MRM-like or SRM/MRM-mimicking approaches performed on any type of mass spectrometer and/or, in which the peptides are fragmented using any other fragmentation method such as e.g. CAD (collision-activated dissociation (also known as CID or collision-induced dissociation), HCD (higher energy CID), ECD (electron capture dissociation), PD (photodissociation) or ETD (electron transfer dissociation). [0099] In another embodiment of the invention, the mass spectrometric method includes matrix assisted laser desorption/ionization time-of-flight (MALDI-TOF MS or MALDI-TOF). In another embodiment, method includes MALDI-TOF tandem mass spectrometry (MALDI-TOF MS/MS). In yet another embodiment, mass spectrometry can be combined with another appropriate method(s) as may be contemplated by one of ordinary skill in the art. For example, MALDI-TOF can be utilized with trypsin digestion and tandem mass spectrometry as described herein. [0100] In yet another embodiment of the invention, a mass spectrometric technique includes surface enhanced laser desorption and ionization or “SELDI,” as described, for example, in U.S. Patents No.6,225,047 and No.5,719,060, which are included herein in their entireties. Briefly, SELDI refers to a method of desorption/ionization gas phase ion spectrometry (e.g., mass spectrometry) in which an analyte (here, one or more of the biomarkers) is captured on the surface of a SELDI mass spectrometry probe. There are several versions of SELDI that may be utilized including, but not limited to, Affinity Capture Mass Spectrometry (also called Surface-Enhanced Affinity Capture (SEAC)), and Surface-Enhanced Neat Desorption (SEND) which involves the use of probes including energy absorbing molecules that are chemically bound to the probe surface (SEND probe). Another SELDI method is called Surface-Enhanced Photolabile Attachment and Release (SEPAR), which involves the use of probes having moieties attached to the surface that can covalently bind an analyte, and then release the analyte through breaking a photolabile bond in the moiety after exposure to light, e.g., to laser light (see, U.S. Patent No.5,719,060, which is included herein in its entirety). SEPAR and other forms of SELDI are readily adapted to detecting a biomarker or biomarker panel, pursuant to the invention. Patent Application Attorney Docket No.179.0009-WO00 [0101] In another mass spectrometry method, the biomarkers can be first captured on a chromatographic resin having chromatographic properties that bind the biomarkers. For example, one could capture the biomarkers on a cation exchange resin, such as CM Ceramic HyperD® F resin, wash the resin, elute the biomarkers and detect by MALDI. Alternatively, this method could be preceded by fractionating the sample on an anion exchange resin before application to the cation exchange resin. In another alternative, one could fractionate on an anion exchange resin and detect by MALDI directly. In yet another method, one could capture the biomarkers on an immuno-chromatographic resin that includes antibodies that bind the biomarkers, wash the resin to remove unbound material, elute the biomarkers from the resin and detect the eluted biomarkers by MALDI or by SELDI. Detection by Electrochemiluminescence Assay [0102] In some embodiments of the invention, biomarkers may be detected by means of an electrochemiluminescence assay developed by Meso Scale Discovery. Electrochemiluminescence detection uses labels that emit light when electrochemically stimulated. Background signals are minimal because the stimulation mechanism (electricity) is decoupled from the signal (light). Labels are stable, non-radioactive and offer a choice of convenient coupling chemistries. They emit light at ~620 nm, eliminating problems with color quenching. See U.S. Patent No.7,497,997; No.7,491,540; No.7,288,410; No.7,036,946; No.7,052,861; No. 6,977,722; No.6,919,173; No.6,673,533; No.6,413,783; No.6,362,011; No.6,319,670; No.6,207,369; No. 6,140,045; No.6,090,545; and No.5,866,434, which are included herein in their entireties. See also U.S. Patent Appl. Pub. No.2009/0170121; No.2009/006339; No.2009/0065357; No.2006/0172340; No.2006/0019319; No.2005/0142033; No.2005/0052646; No.2004/0022677; No.2003/0124572; No.2003/0113713; No. 2003/0003460; No.2002/0137234; No.2002/0086335; and No.2001/0021534, which are included herein in their entireties. Other Methods for Detecting Biomarkers [0103] TBI biomarkers may be detected by other suitable methods known in the art. Detection paradigms, which may be employed to this end, include optical methods, electrochemical methods (voltammetry and amperometry techniques), atomic force microscopy, and radio frequency methods, e.g., multipolar resonance spectroscopy. Illustrative of optical methods, in addition to microscopy, both confocal and non-confocal, are detection of fluorescence, luminescence, chemiluminescence, absorbance, reflectance, transmittance, and birefringence or refractive index (e.g., surface plasmon resonance, ellipsometry, a resonant mirror method, a grating coupler waveguide method or interferometry). [0104] In another embodiment of the invention, a sample, such as a sample containing the protein biomarkers described herein, may also be analyzed by means of a biochip. Biochips generally include solid substrates and have a generally planar surface, to which a capture reagent (also called an adsorbent or affinity reagent) is Patent Application Attorney Docket No.179.0009-WO00 attached. Frequently, the surface of a biochip includes a plurality of addressable locations, each of which has the capture reagent bound there. Protein biochips are biochips adapted for the capture of polypeptides. Many protein biochips are described in the art. These include, for example, protein biochips produced by Ciphergen Biosystems, Inc. (Fremont, CA.), Invitrogen Corp. (Carlsbad, CA), Affymetrix, Inc. (Fremont, CA), Zyomyx™ (Hayward, CA), R&D Systems, Inc. (Minneapolis, MN), Biacore® (Uppsala, Sweden) and Procognia™ (Berkshire, UK). Examples of such protein biochips are described in the following patents or published patent applications: U.S. Patent No.6,537,749; U.S. Patent No.6,329,209; U.S. Patent No.6,225,047; U.S. Patent No.5,242,828; PCT International Publication No. WO 2000/56934; and PCT International Publication No. WO 03/048768. [0105] Other assays useful for detecting biomarkers include single-molecule arrays (SIMOA™), (e.g., as provided by Quanterix™, Lexington, MA), which are bead-based detection assays, in which antibody capture molecules are attached to the surface of paramagnetic beads that are capable of detecting thousands of single protein molecules simultaneously and use the same reagents as are used in conventional ELISA assays described herein. Femtomolar (fg/mL) concentrations of proteins can be measured in a SIMOA bead-based immunoassay, which involves arrays of femtoliter-sized reaction chambers that can isolate and detect single protein molecules. Because the array volumes are significantly smaller than those of a conventional ELISA, a rapid increase of fluorescent product is generated if a labeled protein is present. [0106] The power of a diagnostic test to correctly predict TBI status is commonly measured as the sensitivity of the assay, the specificity of the assay or the area under a receiver operated characteristic (“ROC”) curve. Sensitivity is the percentage of true positives that are predicted by a test to be positive, while specificity is the percentage of true negatives that are predicted by a test to be negative. A ROC curve provides the sensitivity of a test as a function of 1-specificity. The greater the area under the ROC curve, the more powerful the predictive value of the test. Other useful measures of the utility of a test are positive predictive value and negative predictive value. Positive predictive value is the percentage of people who test positive that are actually positive. Negative predictive value is the percentage of people who test negative that are actually negative. [0107] In particular embodiments of the invention, biomarker panels may show a statistical difference in different brain injury statuses of at least p<0.05, p<10-2, p<10-3, p<10-4 or p<10-5. Diagnostic tests that use these biomarkers may show an ROC of at least 0.6, at least about 0.7, at least about 0.8, or at least about 0.9. [0108] The biomarkers may be differentially present in biological samples from uninjured (UI) control subjects (healthy controls (HC) or non-brain injury controls, (e.g., age-matched HC), trauma control subjects (e.g., age- matched orthopedic injury subjects without intracranial injury, often abbreviated TC), and biological samples from subjects with a brain injury, and, thus, are useful in aiding in the determination of brain injury status. In some embodiments of the invention, biomarkers are measured in a patient sample using the methods described herein and compared, for example, to predefined biomarker levels/ratios and correlated to brain Patent Application Attorney Docket No.179.0009-WO00 injury status. In particular embodiments, the measurement(s) may then be compared with a relevant diagnostic amount(s), cut-off(s), or multivariate model scores that distinguish a positive brain injury status from a negative brain injury status. The diagnostic amount(s) represents a measured amount of a biomarker(s) above which or below which a patient is classified as having a particular brain injury status. For example, if the biomarker(s) is/are upregulated compared to normal, then a measured amount(s) above (or greater than) the diagnostic cutoff(s) provides an assessment of brain injury status. Alternatively, if the biomarker(s) is/are down-regulated, then a measured amount(s) at or below the diagnostic cutoff(s) provides an assessment of brain injury status. As is well understood in the art, by adjusting the particular diagnostic cut-off(s) used in an assay, one can increase sensitivity or specificity of the diagnostic assay depending on the preference of the diagnostician. In particular embodiments, the particular diagnostic cut-off can be determined, for example, by measuring the levels of biomarkers in a statistically significant number of samples from patients with the different brain injury statuses and drawing the cut-off to suit the desired levels of specificity and sensitivity. [0109] In other embodiments of the invention, the relative or normalized amounts of biomarkers to each other are useful in aiding in the determination of brain injury status. In certain embodiments, the biomarker ratios are indicative of diagnosis. In other embodiments, a biomarker ratio can be compared to another biomarker ratio in the same sample or to a set of biomarker ratios from a control or reference sample. [0110] Furthermore, in some embodiments, the measured values (i.e., levels) of the biomarkers detected by a biomarker panel are mathematically combined and the combined value is correlated to the underlying diagnostic question. Biomarker values may be combined by any appropriate state of the art mathematical method. Mathematical methods useful for correlating a marker combination to a brain injury status employ methods like discriminant analysis (DA) (e.g., linear-, quadratic-, regularized-DA), Discriminant Functional Analysis (DFA), Kernel Methods (e.g., SVM), Multidimensional Scaling (MDS), Nonparametric Methods (e.g., k- Nearest-Neighbor Classifiers), PLS (Partial Least Squares), Tree-Based Methods (e.g., Logic Regression, CART, Random Forest Methods, Boosting/Bagging Methods), Generalized Linear Models (e.g., Logistic Regression), Principal Components based Methods (e.g., SIMCA), Generalized Additive Models, Fuzzy Logic based Methods, Neural Networks and Genetic Algorithms based Methods. In one embodiment, the method used in correlating a biomarker combination of the invention, e.g. to assess brain injury, is selected from DA (e.g., Linear-, Quadratic-, Regularized Discriminant Analysis), DFA, Kernel Methods (e.g., SVM), MDS, Nonparametric Methods (e.g., k-Nearest-Neighbor Classifiers), PLS (Partial Least Squares), Tree-Based Methods (e.g., Logic Regression, CART, Random Forest Methods, Boosting Methods), or Generalized Linear Models (e.g., Logistic Regression), and Principal Components Analysis. Details relating to these statistical methods are found in the following references: Ruczinski et al.,12 J. OF COMPUTATIONAL AND GRAPHICAL STATISTICS 475-511 (2003); Friedman, J. H., 84 J. OF THE AMERICAN STATISTICAL ASSOCIATION 165-75 (1989); Hastie, Trevor, Tibshirani, Patent Application Attorney Docket No.179.0009-WO00 Robert, Friedman, Jerome, The Elements of Statistical Learning, Springer Series in Statistics (2001); Breiman, L., Friedman, J. H., Olshen, R. A., Stone, C. J. Classification and regression trees, California: Wadsworth (1984); Breiman, L., 45 MACHINE LEARNING 5-32 (2001); Pepe, M. S., The Statistical Evaluation of Medical Tests for Classification and Prediction, Oxford Statistical Science Series, 28 (2003); and Duda, R. O., Hart, P. E., Stork, D. G., Pattern Classification, Wiley Interscience, 2nd Edition (2001). Determining Risk of Brain Injury [0111] In some embodiments of the invention, methods are provided for determining the risk of brain injury, such as TBI, in a patient. Biomarker percentages, ratios, amounts, or patterns are characteristic of various risk states, e.g., high, medium or low. The risk of brain injury is determined by measuring the relevant biomarkers in a protein biomarker panel, and then either submitting them to a classification algorithm or comparing them with a reference amount, i.e., a predefined level or pattern of biomarkers that is associated with the particular risk level. Determining Severity of Brain Injury [0112] In some embodiments of the invention, methods are provided for determining the severity of brain injury, e.g., TBI, mTBI, in a patient. Each grade or stage of brain injury likely has a characteristic level of a biomarker or relative levels/ratios of a set of biomarkers (a pattern or ratio). The severity of brain injury is determined by measuring the relevant biomarkers and then either submitting them to a classification algorithm or comparing them with a reference amount, i.e., a predefined level or pattern of biomarkers that is associated with the particular stage. In embodiments, severity of brain injury, e.g., TBI, is further determined by performing neuroimaging analysis to detect more serious or severe damage or insult, such as a change in vascular permeability, such as, for example, blood vessel leakage or intracranial hemorrhage (ICH). Neuroimaging analysis, e.g., using contrast MRI, allows for the detection and visualization of injury such as bleeding, hemorrhage, or other insult or damage to the integrity to the brain, white matter, axons, fascicles, fiber tracts, or its blood-brain barrier. Determining Brain Injury Prognosis [0113] In one embodiment of the invention, methods are provided for determining the course of brain injury, e.g., TBI, mTBI or concussion, in a patient, e.g., a patient who has experienced repetitive injury. Brain injury course refers to changes in brain injury status over time, including brain injury progression (worsening) and brain injury regression (improvement). Over time, the levels, amounts, or relative levels or amounts (e.g., the pattern or ratio) of the biomarkers change. For example, biomarker “X” may be increased with brain injury, while biomarker “Y” may be decreased with brain injury. Therefore, the trend of these biomarkers, either increased or decreased over time toward neurological injury or brain injury, or recovery, indicates the course of the condition. Accordingly, in an embodiment of the invention, a method involves measuring the level of one Patent Application Attorney Docket No.179.0009-WO00 or more biomarkers in a patient at least two different time points, e.g., at a first time point and at a second time point, and comparing the change, if any. The course of brain injury, as well as a determination of injury status, are determined based on these comparisons. Patient Management [0114] In some embodiments of the invention, methods of identifying or qualifying the status of a neurological injury or a brain injury, e.g., TBI, mTBI or concussion include determining and/or managing patient treatment based on injury status and/or risk. Such management includes the decisions and actions of the medical practitioner, physician, or clinician subsequent to determining brain injury status, e.g., as to TBI, mTBI, or concussion. For example, if a physician makes a diagnosis of TBI, mTBI or concussion, then a certain monitoring regimen would follow. An assessment of the course of brain injury using the described methods may then require a certain treatment or therapy regimen. Profiles of the levels of a set of biomarkers in the biological sample, combined with the age, sex, and acute symptoms of a patient, can provide a risk stratification (e.g., classifying patients into categories such as high risk, lower risk, or little to no risk likelihood of developing a certain post-TBI outcome, such as seizures, chronic pain, chronic headache, post-concussive symptoms, incomplete recovery assessed by GOS-E <8, sleep disturbances, mild to severe depressive symptoms, mild to severe anxiety, PTSD, chronic headache or migraine, poor attention or cognitive performance, or motor deficits). Each model profile with these biomarkers allows the physician to better make an informed decision to direct the TBI, mild TBI, or concussion patient down a treatment pathway tailored for each of the outcomes, having determined the symptoms for which he or she is at high risk. An assessment of the course of brain injury using the described methods may then require a certain treatment or therapy regimen, including identifying an individual’s eligibility for clinical trials that investigate therapeutics for a symptom or set of symptoms that results from TBI. Alternatively, a diagnosis of no brain injury might be followed with further testing or monitoring. Also, further tests may be called for if the diagnostic test gives an inconclusive result for neurological or brain injury status. In some embodiments of the invention, any of the biomarker combinations disclosed herein may be used with any of the embodiments relating to patient management described herein EXAMPLES Example 1: Feasibility studies for detecting and differentiating acute traumatic brain injury (TBI) [0115] Feasibility testing was conducted for methods of detecting acute traumatic brain injury (TBI) in the elderly and for differentiating TBI from existing cognitive impairment using single and combinations of biomarkers or with neurocognitive battery and digitized neurocognitive tests using remote computing Patent Application Attorney Docket No.179.0009-WO00 capability, such as neurocognitive battery and digitized neurocognitive tests marketed by the BrainCheck® and/or implemented on handhelds like an Apple iPhone® or iPAD®. [0116] Two clinical centers in a feasibility study enrolled a total of 68 subjects (45 TBI subjects and 20 trauma controls). To increase the number of subjects meeting the criteria for the current geriatric study, and to advance the study to meet the timelines, analysis of concurrently enrolled subjects from the feasibility phase of BRAINBox’s HeadSMART II (HEAD injury Serum markers and Multi-modalities for Assessing Response to Trauma) clinical study to develop an in-vitro diagnostic test for acute traumatic encephalopathy (ATE) was also performed. A full panel of 15 biomarkers were assayed in all subjects that met the study criteria. The biomarkers include: Brain derived neurotrophic factor (BDNF); Glial Fibrillary Acidic Protein (GFAP); Interleukin- 6 (IL-6); Metallothionein 3 (MT3); Neurofilament light chain (NF-L); Neurogranin (NRGN); Neuron Specific Enolase (NSE); Phosphorylated Tau at Threonine 181 (pT181), Serine 217 (pS217), and Threonine 231 (pT231), together p-Tau); phosphorylated Synuclein alpha at Serine 129 (pS129-SNCA); Synuclein alpha (SNCA); Synuclein beta (SNCB); Tumorigenicity 2 protein (sST2); and von Willebrand Factor (vWF). [0117] The feasibility or training set for the HeadSMART II study from which the additional geriatric subjects were enrolled, shared a highly similar study design and identical sample processing procedures with the Geriatric Feasibility Study. Because the subjects of the HeadSMART II study include a broad range of ages, including a head injury population 18 years and older, a subset of those enrolled subjects are also geriatric subjects, which were the subset used to supplement the analysis herein. The subjects are also adjudicated for mild TBI (mTBI) diagnosis by a panel of expert clinicians and have blood draws and digital neurocognitive battery assessments, obtained using identical procedures as described in a study design in NIH grant Small Business Innovation Research Project No.1R44NS127732-01 awarded by the National Institute of Neurological Disorders and Stroke awarded to the assignee of this application. For these reasons, the experimental approach was to run the proposed biomarker testing on the full additive data set of geriatric subjects qualified for trauma only or TBI status. TBI status was , defined as either the American Congress of Rehabilitation Medicine diagnostic criteria for mTB) diagnosis ( ACRM +) or evidence of traumatic intracranial injury by CT or MRI scan. Given the challenges of diagnosing these subjects, within the contexts of age-related cognitive decline, this rigorous adjudication of diagnosis was an essential part of the process of assigning accurate subgroup labels for analysis. A process was proposed that will continue to serve as a foundation for analysis throughout the longitudinal design of Phase II. These processes should give added confidence regarding the results. Demographics Summary The subjects were screened, consented, and enrolled by trained research coordinators, working closely with attending clinicians, and regularly reviewed for accuracy, with results entered into the forms provided by Patent Application Attorney Docket No.179.0009-WO00 BRAINBox® in the online EDC (Electronic Data Capture instrument, RedCAP® Cloud). The collected information was source-verified during monitoring by external clinical research monitors, audited for completeness and compliance with the study protocols. All variances, corrections and adjustments were documented. Tables 1-4 summarize the subject demographics and clinical assessments. [0118] None of the trauma controls or TBI subjects had a known previous diagnosis of dementia at enrollment. However, expert adjudication of the neurocognitive assessments did indicate cognitive impairment in some enrolled subjects. Cognitive impairment pre-injury was assessed using the informant portions of the Clinical Dementia Rating scale (CDR®) and Functional Assessment Questionnaire (FAQ) Scores and this information was then used to generate the impaired or nonimpaired subgroups for trauma controls and TBI subjects for all tabulated data. [0119] The retrospective dementia samples obtained for the study were comprised of Alzheimer’s Disease (64.3%), Parkinson’s Disease (21.4%), Vascular Dementia (3.6%) and Dementia diagnosed but not otherwise specified (10.7%). These provided a spectrum of dementia subtypes with chronic neuropathology to compare biomarker signatures with acute mild TBI pathology.
Patent Application Attorney Docket No.179.0009-WO00 Table 1. Subject demographics for the Phase I feasibility study Table 2. Clinical data for enrolled subjects
Patent Application Attorney Docket No.179.0009-WO00 for trauma controls and TBI subjects. Vital signs can be seen to be very consistent between study subgroups, with nearly all subjects having neuroimaging by CT or MRI in the TBI group, and the cognitively impaired trauma controls, and a slightly lower percentage in trauma controls with normal cognition. One difference that was observed in the subgroups was a slightly longer time from injury to arrival at the emergency department. This difference is worth considering when evaluating biomarker profiles. Because individual biomarkers have different kinetic profiles, variation in the time from injury to arrival could affect the patterns observed in study groups. Patent Application Attorney Docket No.179.0009-WO00 [0121] Mechanisms of injury in the geriatric age group were like what has been reported in the literature, which are predominantly falls (~70%). Roughly 65% (54/83) of subjects in the study described herein were found to have been injured due to falls in this cohort. The next most common injury mechanisms were motor vehicle accidents and the head being struck by an object. In the TBI group and the trauma control group, an average of 25-26% of subjects had prior concussion history. There were very few elderly athletes enrolled (8.3%) in the TBI group, and none in the trauma controls. [0122] Consistent with other studies of TBI in the Emergency Department setting, about half of the TBI subjects also had other extracranial injuries, highlighting the need for objective diagnostics that show specificity to the intracranial injury pathology. Table 3. Mechanisms of Injury for enrolled subjects [0123] As reported in Table 4, assessment of symptoms after acute injury was also performed and documented in the study, many of which are used to generate diagnostic criteria such as the American Congress of Rehabilitative Medicine (ACRM) diagnostic criteria for mTBI. Both neurological signs and acute symptoms form the basis for widely used grading of TBI severity, along with the Glasgow Coma Scale (GCS). Patent Application Attorney Docket No.179.0009-WO00 Historically, patients with GCS 13-15 have been considered to have mild TBI, although this grading of signs and symptoms is being reconsidered in light of the lasting and debilitating symptoms that are experienced by a significant number of patients with mild injury. In the current study, headache was the most common symptom in TBI subjects (72.4%), with more than 50% of all TBI subjects having severe headache post-injury. Disorientation and confusion, loss of consciousness, neurological deficits and amnesia were also prevalent as expected. Table 4. Acute symptoms of injury for enrolled subjects Patent Application Attorney Docket No.179.0009-WO00 Example 2. Selection of biomarkers for inclusion in assay to differentiate mTBI diagnosis [0124] The results of 15 immunoassay tests used to detect BDNF, GFAP, IL-6, MT3, NF-L, NRGN, NSE, SNCA (total, pS129), SNCB, p-Tau (pT181, pS217, pT231, and pS396), and vWF and select biomarker panel for inclusion in final multiplexed assay based on ability to differentiate 100 patients diagnosed with TBI (GCS 13-15, and CT+ or ACRM+) from 50 retrospective trauma controls of the same age range (e.g., hip fractures or long bone injuries without head impacts) and 50 dementia samples. [0125] Biomarkers were tested in 15 biomarker assays as described above, using custom and predeveloped Mesoscale Discovery (MSD) electrochemiluminescence immunoassays. The phospho-Tau specific assays (e.g., pT181-Tau, pS217-Tau, and pT231-Tau) were performed as a readout of acute axonal injury pathology versus neurodegenerative processes. Another biomarker studied was a promising neuroinflammatory biomarker, the soluble IL-33 receptor, ST2. The ST2 assay also adds to the vascular and inflammatory biomarker indicators, together with vWF and IL-6. The aim in evaluating 15 different biomarkers was to have broad representation of the endophenotypes of injury (e.g., vascular injury, neuronal/axonal injury, glial injury, inflammation). This approach allowed for a comprehensive set of biomarkers from which to assess differences among mTBI endophenotypes (injury subtypes). [0126] The assay performance metrics are provided in Table 5. Clinical sample testing allowed for determination of biomarker distributions and the lower limits of detection to assess whether the assays address the true clinical ranges. Standard assay parameters for acceptance of assay runs include: % recovery of each calibrant step between 80-120% of the expected value; a coefficient of linearity, using 4-point logistic regression of 0.99; and sample and standard coefficients of variations (CVs) less than 20%. All accepted data met these criteria to ensure robust data was obtained from 2 replicates. [0127] Fig. 1 shows the distributions of biomarkers in paired serum and plasma samples from enrolled subjects. The study comparing different commonly used biofluids permitted cross-comparisons of results with data in published neurodegenerative disease literature, in which most studies have used plasma as a biofluid matrix, as well as comparisons with the serum data in the TBI literature and earlier studies by BRAINBox®. Cerebrospinal fluid (CSF) was studied extensively in those earlier studies but is generally not an available biofluid for a mild TBI population like the one studied here. However, CSF may be used as a sample biofluid for detecting and differentiating mTBI. Distributions of biomarkers in serum and plasma [0128] Paired serum and plasma samples were evaluated simultaneously on the same multi-well plate for each assay. Differences observed were therefore obtained simultaneously under identical assay conditions. In paired samples, the following analytes were found to be detected at higher levels in serum than in plasma: Patent Application Attorney Docket No.179.0009-WO00 BDNF, pS129-SNCA, MT3, and pT231-Tau. Analytes that were detected at higher levels in plasma of the same timed blood draw from the same individuals included phosphothreonine181-Tau, SNCB, and NSE. These data were further analyzed by Bland-Altmann Plots and calculation of Lin’s Correlation Coefficient for each biomarker to assess whether differences are present between matrices in the paired samples. Table 11 summarizes the calculated values for Lin’s coefficient. In addition, Bland-Altman plots for each of the 15 biomarkers studied are shown in Fig.3. Observed differences in median values reflect the biomarker. All samples were collected under the same protocols and the plasma tubes were EDTA, which could affect the conformation and binding activity in the matrix. The collective results suggest that separate diagnostic models for serum and plasma are required when certain biomarkers are utilized in diagnostic models. [0129] Biomarker levels were detected in serum or plasma using paired samples measured within the same multiwell plates simultaneously were compared for overall distributions separated by age ranges 18-39 years (young adult) 40-64 years (middle aged adult), 65-74 years (late middle age, early geriatric adult), and 75 to 100 years (old age geriatric) (Figure 2, A through J). Results show that blood levels of certain biomarkers, including BDNF and NRGN, are diminished with age, and are diminished further still in dementia, likely due to synaptic loss. Other protein biomarkers also appear to show a similar pattern, with vWF and soluble ST2, both vascular reactivity or injury related, showing a decrease in injury related elevation with advancing age and a further diminished level in dementias, compared to controls of the same age range. This may be related to changes in vascular biology (diminished vWF and ST2) and the robustness of inflammatory pathways (diminished ST2 and IL-6) with advancing age. The converse is also seen for certain biomarkers, including synucleins (Figure 2, G,H,I). Injury levels of synuclein alpha (SNCA and the specifically modified form phosphorylated at Serine 129, pSNCA, in Figs.2G and 2H) both increase in the blood during acute injury response compared to healthy subjects and in chronic dementias. These differences must be considered in geriatric diagnostic tests that utilize these proteins as biomarkers. Summary of age and matrix-specific differences [0130] Distributions pf biomarker proteins in this sample set show between matrix differences for roughly half of the biomarkers studied. Further analysis of differences was performed using Bland-Altman plots, which indicate equivalences or differences among detected biomarker levels for each biomarker. Bland-Altman analysis, also known as intra-class correlation (ICC), was used for studying biomarker levels as continuous variables in the two matrix types, which is shown in Fig.3. Calculation of Lin’s correlation coefficient (LCC) indicated high correlation between serum and plasma values for 8 of the 15 biomarker assays including GFAP, IL-6, MT3, NfL, NSE, phosphor-Ser129-SNCA, SNCB, and ST2. Each of these showed correlation coefficient > 0.9. The biomarker levels detected in the remaining 7 assays were not well correlated, ranging from least Patent Application Attorney Docket No.179.0009-WO00 correlated biomarkers pT231-Tau (LCC = -0.061), pT181-Tau (0.113), SNCA (0.315), Neurogranin (0.422) and BDNF. Table 5. Clinical performance of immunoassays tested for geriatric trauma controls, dementia, and TBI. Immunoassay Target Studied Pathological Significance for Mean Observed Acute TBI and in AD, PD LLOD Range serum (ng/mL) (ng/mL) 1 BDNF (Brain Derived Neurotrophic Neuronal 0.03623 0.711-75.66 Factor) activity/Neurotrophic 2 GFAP (Glial Fibrillary Acidic Protein) Astrocyte/Vascular 0.00466 0.007-33.500 3 IL-6 (Interleukin-6) Proinflammatory 0.000097 0.00005-0.070 4 MT3 (Metallothionein 3) Astrocyte/Neuroprotective 0.00300 0.2105-79.020 5 NfL (Neurofilament Light Chain) Axonal Injury, degeneration 0.00560 0.0057-9.860 6 NRGN (Neurogranin) Synaptic Damage, loss 0.00602 0.025-3.6600 7 NSE (Neuron Specific Enolase) Neuronal Damage, 0.00396 0.058-8.5700 metabolism 8 PS129-SNCA (Phosphorylated Ser129 Synaptic Damage, 0.07385 0.023-5.1000 Synuclein Alpha) degeneration 9 SNCA (Synuclein Alpha, PARK1) Synaptic Damage, 0.08249 3.802-358.73 degeneration 10 SNCB (Synuclein Beta) Synaptic Damage, 0.31986 0.082-0.3800 degeneration 11 sST2 (Soluble receptor for Interleukin 33) Endothelial/Inflammation 0.06254 7.86-119.570 12 P181 Tau (Phosphorylated Thr 181-Tau) Axonal Injury, degeneration 0.00012 0.0001-0.0095 13 P217 Tau (Phosphorylated Ser 217-Tau) Axonal Injury, degeneration 0.00062 0.00002-0.313 14 P231 Tau (Phosphorylated Thr 231-Tau) Axonal Injury, degeneration 0.00134 0.00025-0.058 15 vWF (von Willebrand Factor) Endothelial Damage, Clotting 0.55431 879.5-8101.5 Abbreviations: AD, Alzheimer’s Disease; PD, Parkinson’s Disease; LLOD, Lower Limit of Detection; ng/mL, nanograms per milliliter. Distributions of biomarkers in Serum and Plasma Paired serum and plasma samples were evaluated simultaneously on the same multi-well plate for each assay. Differences observed were, therefore, obtained simultaneously under identical assay conditions. In paired samples, the following biomarker analytes were found to be detected at higher levels in serum than in plasma: BDNF; ps129-SNCA; NF-L; vWF; and ps231-Tau. Analytes that were higher in plasma included phosphothreonine181-Tau, IL-6, and NSE. These data were further analyzed by Bland-Altmann Plots and calculation of Lin’s Correlation Coefficient for each biomarker. Table 6 summarizes the calculated values for Lin’s coefficient. Bland-Altman plots for each of the 15 biomarkers studied are shown in Figs.1 and 2. The collective results suggested that separate diagnostic models for serum and plasma are required when certain biomarkers are assayed. Patent Application Attorney Docket No.179.0009-WO00 Table 6. Lin’s Correlation Coefficient of biomarker levels in the same blood draws processed in paired serum and plasma. Analyte Studied in Paired Serum/Plasma Lin's Correlation Coefficient (Bold text indicates biofluid differences) BDNF (Brain Derived Neurotrophic Factor) 0.432 GFAP (Glial Fibrillary Acidic Protein) 0.985 IL-6 (Interleukin 6) 0.922 MT3 (Metallothionein 3) 0.994 NfL (Neurofilament Light) 0.998 NRGN (Neurogranin) 0.53 NSE (Neuron Specific Enolase) 1 pS129-SNCA (Phosphorylated at Ser129 Synuclein Alpha) 0.917 SCNA (Synuclein Alpha, PARK1) 0.076 SNCB (Synuclein Beta) 0.347 sST2 (Soluble Receptor for Interleukin 33) 0.988 pT181-Tau (Phosphorylated at Thr181- Tau) 0.015 pS217-Tau (Phosphorylated at Ser217-Tau) 0.495 pT231-Tau (Phosphorylated at Thr231- Tau) -0.083 vWF (von Willebrand Factor) 0.9 Bolded values indicate the least well-correlated biomarker levels detected in paired samples from trauma control and TBI. Biomarker differences between clinical subgroups. [0131] The entire 15-biomarker data set was tested in univariate analysis first, followed by iterative multivariate modeling to identify the best performing biomarker panels for discriminating acute mild TBI from other injury or pathology. Comparisons of acute geriatric trauma controls having age-normal cognitive status with trauma controls having cognitive impairment did not reveal any significant differences in biomarker distributions (Wilcoxon rank sum test, p>0.05 for all). Cognitively age-normal trauma controls versus cognitively age-normal TBI comparisons showed significant differences for GFAP. Cognitively impaired trauma controls versus cognitively impaired TBI. Table 7 shows the univariate analysis results for determining statistical differences between the distributions of individual biomarkers between groups. Patent Application Attorney Docket No.179.0009-WO00 Table 7. Comparison of serum biomarker distributions among study groups Immunoassay Target Studied TBI Vs. Dementia TC Vs. TBI TC vs. Dementia (Wilcoxon (Wilcoxon) (Wilcoxon) p value) 1 BDNF (Brain Derived Neurotrophic 0.0184 0.7133 0.1530 Factor) 2 GFAP (Glial Fibrillary Acidic Protein) 0.0036 0.0156 0.4592 3 IL-6 (Interleukin-6) 0.0656 0.9654 0.0003 4 MT3 (Metallothionein 3) 0.6461 * * 5 NfL (Neurofilament Light Chain) 0.4196 0.3963 0.9143 6 NRGN (Neurogranin) <0.0001 0.6514 0.0115 7 NSE (Neuron Specific Enolase) 0.1994 0.1599 0.0038 8 PS129-SNCA (Phosphorylated at Ser129 0.9247 0.7833 0.8958 Synuclein Alpha) 9 SNCA (Synuclein Alpha, PARK1) 0.0184 0.1084 0.0050 10 SNCB (Synuclein Beta) NT 0.0545 * 11 sST2 (Soluble receptor for Interleukin <0.0001 0.6615 <0.0001 33) 12 P181 Tau (Phosphorylated Thr 181-Tau) 0.0039 0.6730 0.0007 13 P217 Tau (Phosphorylated Ser 217-Tau) 0.4181 0.3312 0.7627 14 P231 Tau (Phosphorylated Thr 231-Tau) 0.6722 0.3704 0.1827 15 vWF (von Willebrand Factor) 0.1239 0.9025 0.3997 NT, Not tested; * Undetermined due to low # measurable samples. Measurement of Blood Biomarkers by Quantitative Immunoassay. [0132] Analysis of the 15 biomarkers was performed in replicate assays and the mean values were analyzed via an established Quality Assurance process prior to being released for further analysis at BRAINBox®. Comparisons of the distributions between groups were the first means of identifying a subset of biomarkers that could provide a pathology-specific profile for diagnostic use. The immunoassays were tested for interferents, optimal dilutions, and conditions prior to implementation. All materials were evaluated, qualified, and released within the Quality Management System at BRAINBox® to ensure consistency and performance to specifications in this study. Use of univariate analysis of biomarker levels in between was shown using Wilcoxon rank sum test to compare median values. [0133] Biomarker levels detected in serum versus plasma, using paired samples measured within the same multiwell plates simultaneously, were compared for overall distributions (Fig.1). Distributions in this small sample set showed group-level differences for roughly half of the biomarkers studied. Further analysis of differences was performed using Bland-Altman plots, which indicated equivalence or difference for each. Bland-Altman analysis, also known as intra-class correlation (ICC), was used for studying biomarker levels as continuous variables in the 2 matrix types, which is shown in Fig.2. Patent Application Attorney Docket No.179.0009-WO00 Trauma Controls versus TBI Signatures [0134] To justify the combination of geriatric subjects from two cohorts, a sub-analysis was performed, which indicated the distributions of biomarkers were similar between them. This approach provided reassurance that the combination of cohorts was appropriate. Fig.3 shows the similarity in biomarker distributions, separated by each available subclass. [0135] Biomarkers, which are non-specific to the central nervous system, but altered by tissue injury or trauma, were variably elevated in trauma controls and in mTBI. Differences between trauma and TBI for the median IL-6 and ST2 were not observed, as well as for some additional biomarkers. There was a significant difference in median values for GFAP, which was increased in geriatric mTBI subjects. These groupwise comparisons are likely affected by the small sample sizes in the feasibility study and potentially by the level of cognitive decline in some individuals of both groups. Dementia versus TBI signatures [0136] Dementia subjects from commercial biorepositories were studied for serum and plasma levels of biomarkers. The cohort consisted of subjects with Alzheimer’s Disease, Parkinson’s Disease, Vascular Dementia, and other dementias. These subjects were demographically balanced to the extent possible, given the availability of samples obtained from commercial biorepositories. It is believed that this study is the first side-by-side comparison of trauma controls, geriatric mTBI, MCI and dementia subtypes. Comparing demographically balanced TBI and dementia subjects, the following results were obtained. Levels of individual biomarkers [0137] BDNF: Median BDNF levels were found to be decreased in the serum of dementia subjects compared to trauma controls or TBI subjects of similar age. Fig.3 shows the group distributions which show a significant overlap between groups. BDNF is known to dynamically expressed during exercise or other exertion and to differ between male and females, and this could affect the overall variance within the distributions. Group differences between TBI and trauma controls were shown to be significant in this analysis. The change score between two acute blood draws suggested a decrease over time after injury for BDNF (Fig.5), thus supporting the use of BDNF as biomarker for geriatric acute TBI, and the inclusion of BDNF in a geriatric acute TBI diagnostic panel. [0138] GFAP: Contrary to preinjury assumptions, GFAP was not seen to be significantly elevated in dementia at the group level compared to the elevation seen in acute mTBI in this age group (Fig.2). Age-matched trauma controls also had similar levels to dementia subjects at the group level. Although not part of the current study, healthy controls aged 65 and older, previously enrolled, were available for development studies in BRAINBox biorepositories, and were also examined to aid in interpreting the results. This additional analysis confirmed the elevation in TBI subjects and the relatively modest increased levels in dementia subjects. GFAP was shown Patent Application Attorney Docket No.179.0009-WO00 to be elevated significantly in TBI subjects compared to controls or dementias. These data support the use of GFAP as a biomarker for geriatric acute TBI, and the inclusion of GFAP in a geriatric TBI diagnostic panel. [0139] IL-6: The proinflammatory cytokine IL-6 is not specific to the CNS but has been repeatedly shown to increase in the blood as a pro-inflammatory biomarker after TBI. The study described herein showed that IL-6 was detected at significantly lower levels in dementia subjects compared with trauma controls or TBI subjects in the same age range. Differences between TBI and trauma controls were not demonstrated for IL-6. Levels in dementia samples were low compared to age matched controls or TBI subjects. This finding was unexpected, because neuroinflammation is a known aspect of chronic neurodegenerative pathologies. We concluded that the results support higher levels of IL-6 after acute injury (either extracranial or intracranial) when compared to healthy age-matched controls. The decrease in detected levels of IL-6 is a generalizable finding in this context of use; however, these data show IL-6 is useful as a biomarker for distinguishing acute injury from chronic conditions and in a geriatric TBI diagnostic panel. [0140] MT3: Metallothionein 3 is an astrocyte specific biomarker that plays a role in modulating the bioavailability of metal cations, including zinc, copper and cadmium, preventing cellular toxicity. Immunostaining of mammalian brains has indicated a predominant expression in white matter astrocytes (unpublished data). Detection of MT3 may be indicative of neurotrauma and has been reported to decrease in Parkinson’s and Alzheimer’s disease patients. The study described herein did not show a median difference in the detection of MT3 between Alzheimer’s Disease and Trauma controls. However, most of the samples tested were below the detection level of the MT3 assay. The presence or absence of MT3 could be used as a dichotomized variable, or the assay detection sensitivity could be improved to demonstrate MT3 levels in most patients (at least 70%) in peripheral biofluids. Thus, MT3 may be used as a biomarker for distinguishing acute injury from chronic conditions and in a geriatric TBI diagnostic panel. [0141] NfL: Neurofilament Light chain is a component of axonal neurofilament bundles, where NfL multimerizes to form the core of the main neuronal intermediate filament fiber, encapsulated with neurofilament heavy and medium chains (NfH and NfM, respectively). NfL has been advanced as both a neurotrauma and a neurodegeneration biomarker but is not specific to the CNS. It is widely recognized as a useful indicator of neuronal damage or degeneration of all types and has been characterized in many TBI and neurodegenerative disease cohort studies. The results described herein indicate that NfL levels were increased in both dementia and TBI. , NfL nonetheless may be included in panels with other biomarkers for distinguishing between TBI and dementia. [0142] NRGN: Neurogranin is a post-synaptic neuronal biomarker that has been reported to have decreased levels in the CSF of Alzheimer’s Disease patients compared to controls and is being evaluated as an additional clinical biomarker for Alzheimer’s Disease. NRGN has also been shown to increase after acute TBI in previous Patent Application Attorney Docket No.179.0009-WO00 reports. Neurogranin was not found to differ significantly between dementia and either geriatric mTBI or trauma controls, as shown in Table 5. Geriatric trauma controls and TBI did not differ significantly in this feasibility study. The differences seen in prior studies and the performance in classifier models in prior TBI studies indicate that NRGN may be used as a biomarker for distinguishing TBI from dementia, particularly in indicating long term symptoms, and possibly for tracking post-injury changes indicative of a neurodegenerative trajectory, if NRGN decreases over time, as well as in panels with other biomarkers for distinguishing between TBI and dementia. Synaptic loss during gradual degeneration of the hippocampus and other areas where NRGN is enriched, is expected to be reflected in lower protein levels in the CSF. The serum and plasma decreases in NRGN levels observed in chronic dementia subjects studied here are consistent with this hypothesis. [0143] NSE: Neuron specific enolase, or Enolase 2, is a metabolic neuronally expressed glycolytic enzyme that is released after injury and is detectable with similar kinetics to GFAP, where NSE is known to reach peak levels at 12-24 hours post-injury. Analysis of mTBI versus trauma controls in geriatric subjects suggested that NSE was not significantly different in trauma controls and TBI, nor in TBI compared to dementias in groupwise comparisons. However, NSE was shown to have significantly different median levels in trauma controls versus dementia. These data suggest that NSE may be elevated both in acute TBI and in chronic dementias. While NSE may also be present at high levels in erythrocytes and thus, its levels can be affected by hemolysis, NSE nonetheless may be included in panels with other biomarkers for distinguishing between TBI and dementia. [0144] SNCA and phosphorylated at-Serine129-SNCA (pS129-SNCA): Synuclein alpha (SNCA) has been a target gene in neurology since the discovery that senile plaques and Lewy Bodies have aggregated SNCA as a principal component. As a component protein of complexes involved in neurotransmitter release from neurons, changes in SNCA could reflect changes in neurotransmission or pathologies associated with neural activity. One of the downsides of this protein is that there is substantial expression in peripheral tissue, including the gut and the enteric nervous system, and importantly expressed in high levels in erythrocytes. SNCA has been extensively studied in synucleinopathies, including in Parkinson’s Disease pathology, due to the early finding of SNCA gene mutations in some familial Parkinson’s subjects. It is less well studied in TBI but is known to play a role in neurotransmission as a presynaptic vesicle transport protein. Phosphorylated SNCA at serine 129 is associated with SNCA deposited in Lewy bodies, hence pathological, aggregated SCNA. SCNA could be significantly affected by peripheral sources since it is highly expressed in red blood cells and could therefore be affected by hemorrhage and hemolysis. The study described herein reported that SNCA levels differ between acute TBI and dementia, thereby showing that SNCA can be used as a biomarker to distinguish between these disease states, , as well as in panels with other biomarkers for distinguishing between TBI and dementia. In contrast, pS129- SNCA, where detected, was not found to be significantly difference between the study groups, despite being tightly correlated with overall SNCA levels. Of additional interest, several publications reported that MT3 can Patent Application Attorney Docket No.179.0009-WO00 bind to synucleins and may also be bound to SNCA aggregates in diseases such as Alzheimer’s and Parkinson’s diseases. Therefore, ratios of SNCA bound MT3 or MT3 oligomers could be used to provide a readout of disease stage, subtype or using bispecific antibodies or other types of combination assays. [0145] SNCB: Synuclein beta is another synaptic protein expressed predominantly in the CNS and thought to play a similar role to SNCA in neurotransmitter release, as experiments have shown that SNCB may modulate the toxicity of aggregated SNCA when bound together. Published studies suggest that SNCB:SNCA ratios are altered during pathogenesis of neurodegenerative disease. SNCB has been reported to decrease in chronic neurodegeneration. Although SNCB levels were detected in a some TBI subjects, but with many subjects having very low or undetectable levels, similar to control levels, SNCB levels were demonstrated to be different in TBI and trauma controls. Thus, SNCB is a biomarker that can be used to distinguish between those two conditions, as well as in panels with other biomarkers for distinguishing between TBI and dementia. [0146] sST2: Soluble suppressor of tumorigenesis-2 is a soluble form of interleukin 33 receptor that has been extensively studied in relation to heart failure, renal failure and inflammation. ST2 is also released by endothelial cells. Increased ST2 indicates tissue damage, particularly in the cardiovascular system, and has been studied in many disease states. In particular, the assignee of this application has studied its use as biomarker indicative of traumatic brain injury, particularly mTBI. See, e.g., US 2023/0238143, WO2023/092157, and US 2025/0035650, which are incorporated by reference herein in their entireties. As such, it may provide information on different aspects of trauma, inflammation and vascular injury or repair. In the study described herein, ST2 levels were similar in trauma controls and TBI subjects, but detected levels were significantly lower in dementias. These results indicate ST2’s utility as a biomarker distinguishing acute from chronic brain injury, as well as in panels with other biomarkers for distinguishing between TBI and dementia. Phospho-Tau: Three phospho-Tau biomarkers were studied. The first of these studied in TBI was phospho- Threonine 231 (pT231-tau), which was reported to be increased in TBI subjects compared with controls in prior publications. Phospho-Threonine 181 (pT181-tau) has also been studied in TBI subjects using available pre- developed immunoassays. More recently phospho-Serine217 (pS217-tau), which was recently recommended by researchers for its correlation in Alzheimer’s Disease patients to amyloid plaque burden and neurofibrillary tangle burden. To date, no publications have characterized pS217-tau in TBI. The study described herein suggests that all three phosphor-Tau forms are detectable in TBI. T231-Tau phosphorylation, as reported in prior TBI publications, appeared to be elevated in geriatric TBI subjects compared to trauma controls and dementia. Serine217-Tau phosphorylation showed a similar pattern to that of pT231-Tau but was significant for distinguishing dementia from trauma or TBI. PhosphoTau181 showed the largest difference and was elevated in dementia compared to either TBI or trauma controls. In contrast, mTBI and trauma controls were also significantly different between groups in this analysis. Thus, all three of these phosphor-Tau forms are Patent Application Attorney Docket No.179.0009-WO00 biomarkers for distinguishing between TBI and dementia-related conditions, as well as in panels with other biomarkers for distinguishing between TBI and dementia. [0147] von Willebrand Factor: The endothelial activation biomarker vWF has been shown to increase after vascular injury and plays a significant role in thrombosis after any tissue injury. As the brain is a densely vascularized tissue, vWF is of high interest as a potential vascular injury biomarker in TBI. In the study described herein, vWF is elevated in both trauma controls and TBI, using a custom assay that targets epitopes in the region cleaved by ADAMTS13. vWF levels were shown to have statistically significant differences in median levels between study groups, particularly in distinguishing dementia from other clinical groups, since vWF levels were lower than TBI or peripheral trauma controls. Subanalysis of dementia types included in the study showed differences in subtype distributions, so while further detailed analysis of this biomarker in a balanced study of neurodegenerative diseases will provide more information, this study showed that vWF is a biomarker for distinguishing between TBI and dementia-related conditions, as well as in panels with other biomarkers for distinguishing between TBI and dementia. In that regard, in the two vascular dementia cases studied, for example, reported very low levels of vWF. Individual Biomarker Receiver Operating Characteristic Curve Performance [0148] Table 10 shows the area under the ROC curve for each biomarker studied, according to the two critical clinical questions for this analysis. Two biomarkers had AUC above 0.7, GFAP and ST2, with many others > 0.6 AUC. Accuracy as high as 78% was seen (ST2). Combinations of biomarkers will increase the diagnostic performance for diagnostic classification. Analysis of change between the first and second blood draw. [0149] A comparison of the first (Time 0, initial blood draw) and second (T1 = T0+ 1-4 hrs.) acute blood draws was performed to assess whether the change in biomarker level over time could be a useful parameter indicating heightened static levels, as would be expected in chronic neuropathology with a slow or no rate of change. This contrasts with acute injuries, in which some directional change could be expected (Figures 5A-J). Change scores can therefore be calculated as the difference between the levels (T1-T0) and these can be studied in relation to the time from injury to blood draw. Because the time frame can vary in the emergency room or urgent care environments, enrollments studied spanned up to 96 hours, and the sample draws being close together allowed the results to show any significant association to injury time frame. Differences were assessed using an analysis of covariance (ANCOVA) approach. Robust linear regression was then used to look at directional change across all samples, which did show significant trajectories for some biomarkers. Figure 6 shows plots of robust linear regression lines demonstrating a directional decrease in BDNF, and increases in vWF and pSer217-Tau between the two time points. BDNF mat decrease with stunted metabolism after injury and vWF and phosphor-Tau may increase due to evolving hemorrhage and white matter (axonal) injury, Patent Application Attorney Docket No.179.0009-WO00 aspects that are consistent with the location and biological roles of these proteins. Significant ANCOVA p values indicating change over time were found for BDNF (p<0.001), GFAP(p<0.001), ST2 (p<0.001), NSE, IL-6 (p<0.001), vWF (p<0.001), SNCB (p=0.0048), NfL (p<0.001), pThr181-Tau (p=0.0064), pSer217-Tau (p=0.0012). Paired T- tests were also performed, which confirmed differences between time points for each biomarker. This change score parameter may therefore be worth further study and justifies the retention of the second blood draw in Phase II. Further analysis within the first 24 hours and other time periods closer to injury may be particularly informative since the greatest rate of change may be expected then. Robust modeling studies to generate a kinetic model of change overtime for each biomarker would be valuable for interpreting results. Combining results of neurocognitive testing and blood biomarkers for patient assessment [0150] To further derive the combined diagnostic models incorporating blood biomarkers and digital neurocognitive testing results from the BrainCheck device, the full data set of blood biomarkers, age, sex, BrainCheck individual test metrics and overall BrainCheck Clinician Scores (aggregated percentile score derived from comparison with a normative database) were used in multivariate models for geriatric TBI specific diagnosis. Certain biomarkers were found to be undetectable using the bioassays used in the study, in some cases in a significant proportion of individuals. Where more than 30% of subjects had undetectable values, the data were converted to a categorical present/absent dichotomization (binary value) rather than a continuous variable. All data processing and model building was performed in the R statistical environment. [0151] Multivariate models were computed using random forest with age and sex included as potential covariates in the classifier models (Table 8). There were several models that performed similarly by ROC curve analysis, which suggests that several indicators of TBI pathology subtypes can be combined to improve diagnostic performance. Compared with the median differences seen in the univariate analysis, we see recurring biomarkers NRGN and ST2 for discriminating TBI from dementia, together with GFAP, which was found to be elevated in acute mTBI more than non-brain trauma or dementia. GFAP was the best biomarker to distinguish mTBI from peripheral trauma. BDNF was also found to differ in mTBI and dementia, with a similar decrease in median levels in univariate comparisons, and this was represented in some of the top performing models. The 4 plex model consisting of GFAP, NRGN, vWF and IL-6 had the highest AUC, sensitivity and specificity of the models, which could be advantageous for a rule out test in geriatric mTBI. Clinically, ruling out mTBI in geriatric subjects would add value to the CT imaging findings, since a very high percentage of patients get CT scans in this age group. More than 90% with no CT findings will still need assessment for clinically important brain injury. Patent Application Attorney Docket No.179.0009-WO00 Table 8. Top multivariate models for discriminating geriatric acute mTBI from non-CNS trauma (trauma controls), and for distinguishing geriatric mTBI or dementia using biofluid biomarkers and, optionally, neurocognitive testing metrics. Key: RF= random forest models; n= number of subjects total; n.TC= number of trauma controls used in the model; n.TBI=number of TBI subjects used in the model; AUC, area under the ROC curve; PPV, positive predictive value; NPV, negative predictive value; LR+ , log ratio positive predictive; LR-, log ratio negative [0152] Model classifiers for distinguishing acute traumatic brain injury events from chronic dementia were generated. Table 8 shows the top performing models to have vWF and IL-6, with one additional biomarker being p-Thr181 Tau, BDNF or NRGN. The narrowest confidence intervals and highest log ratio found for IL-6 and pSer217-Tau when paired with pThr181-Tau (LR = 34.96), BDNF (33.164), SNCA (32.473), or ST2 (31.418), each with AUCs >0.90 and specificities >0.97. Should these models be stable across independent cohorts, they would provide clinical useful tools for distinguishing TBI from underlying stages of dementia. [0153] Finally, a combined multivariate model was derived using both blood biomarkers and scores from each of the 8 neurocognitive assessments in BrainCheck. Having a single model for the basis of a test that can distinguish mTBI is ideal. For this purpose, the dementia and trauma control groups were combined into one class and random forest models derived to discriminate the mTBI group from the dementia/trauma control group (= the not acute TBI label). Top performing models are shown in Table 10. A model with GFAP, NRGN, IL- 6 and vWF was shown to have the highest AUC. Discussion and potential uses of this technology Patent Application Attorney Docket No.179.0009-WO00 [0154] Custom immunoassays were used to characterize an understudied age group in TBI research, but one that is a growing demographic as the population is surviving longer. With the goal of identifying distinct profiles for acute TBI detection and clarification of differences with neurodegenerative disease processes, assays were deliberately chosen that have been used in both TBI and neurodegenerative disease studies, each compared between disease and controls, but not yet studied to discriminate acute vs chronic brain injury. This discrimination was hypothesized to be clinically important to identify suspected or occult TBI in the elderly, since TBI will often occur in the context of cognitive decline and some stage of pathological neuronal loss in these subjects. Complex medical histories and polypharmacy also contribute to the difficulty in assessing acute brain injury in this patient population. The identification of objective biomarkers as tools to identify geriatric TBI will be the output of this study. Certain biomarkers were only detected in a subset of subjects in this feasibility study due to very low levels in blood. This was evident in MT3 and SNCB assays, technically sound assays but with many individuals having undetectable circulating levels. Along with phospho-Tau, these biomarkers appear to be promising candidates to distinguish between TBI and dementia, but may require an enhancement in detected signal by additional signal boosting techniques. In the case of phospho-Tau assays, these were developed with a boosted signal chemistry for detection which increased the signal 100-fold. This could be developed for the SNCB and MT3 immunoassays as well. For the majority of biomarkers, the full clinical ranges were detectable with very few samples below the limits of detection. Comparisons showed distinctive profiles for dementia and acute mild TBI, supporting the utility of specific biomarker subsets in detecting mild TBI in this age group, irrespective of cognitive status or decline. Differences in biomarker distributions were less evident within subgroups that differ by pre-injury cognitive status. No statistically significant differences were seen between cognitively impaired and cognitively normal trauma controls, or between TBI subjects that were cognitively impaired prior to injury compared to cognitively age-normal subjects prior to injury. [0155] Based on ANOVA analysis (e.g., comparison of median biomarker levels), univariate analysis highlighted biomarkers that differed between the overall study groups. The standout biomarkers for geriatric acute trauma controls versus acute mTBI were GFAP and SNCB, two of the more CNS specific biomarkers. In the dementia group, comparisons with acute TBI showed statistically significant differences in median levels of GFAP, NRGN, IL-6 and p181-tau, with SNCA and ST2 also showing differences that approached significance in this small sample set. Dementia subjects compared with non-brain trauma controls of the same age range showed significant differences in NRGN, ST2, NSE, and SNCA. IL-6 and p181-iau also showed differences and thus may be promising, but the number of subjects with evaluable data was low. These results suggested panels of specific biomarkers that could be tested to discriminate subgroups. Diagnostic performance of Individual biomarkers assessed by ROC Curve analysis demonstrated AUCs equal to or greater than 0.7 for GFAP and ST2. Patent Application Attorney Docket No.179.0009-WO00 [0156] Model classifiers were constructed with up to five covariates, limited due to the group sizes. These model sizes have been shown in previous studies to be sufficient to provide clinically relevant performance in ROC curve analysis. Like the results of univariate comparisons, GFAP, NRGN, BDNF, vWF, IL-6, ST2, and phosphoS217-tau were found to be present in the top performing classifier models. Some models also included BDNF and vWF in equivalent models. Different optional models may be used to distinguish trauma that is acute intracranial brain insult from non-CNS trauma, and for distinguishing dementias from TBI. Since the model tested in our longitudinal study must discriminate acute mTBI from either preexisting dementia or acute peripheral trauma, a combined class model (combining dementia and trauma control) was also developed and tested against mTBI. This model showed clinically useful discrimination, with all top models showing sensitivity above 0.85 and specificity over 0.70. [0157] Cross-platform studies can be performed on a point of care (POC) test, main hospital laboratory instrument, or other immunological, immune-PCR or aptamer or other binding agent assay to determine. Biomarker levels. Similarly, send-out assays using mass spectroscopy or other techniques could also be performed to assess neurological injury or disease subtype, stage or post-therapy response. [0158] The current analysis of measured biomarkers in the clinical subgroups studied indicates that, in the geriatric population, acute mild TBI is discernable from trauma controls and chronic dementia. In a real-world clinical scenario within the context of MCI and early dementia, acute injury biomarker panels clearly allow for distinction between TBI and dementia as well. The biomarker distributions that differ between TBI and non- CNS, trauma and between acute TBI and chronic dementia pathologies are somewhat different, which is to be expected. This analysis provides evidence that multiple models can achieve clinically useful accuracy, sensitivity, and specificity, and by utilizing detected levels of 3-4 blood biomarkers. Operationally, when BrainCheck or other neurocognitive testing instrument is used clinically in cognitively age-normal individuals (i.e., having no detectable cognitive impairment compared to normative ranges for their age), the TBI-related impairment can be discerned and can provide valuable information to the testing system and ultimately can assist the clinician with diagnosis. In individuals with pre-injury cognitive impairment or dementia, the models with blood biomarkers can be relied on alone, and thus the testing system could shift the algorithm setting (down-weight the BrainCheck component) if necessary. [0159] One of the benefits of having the digital neurocognitive function assessment is the ability to remotely monitor the subject for functional changes that are reflected in the brief digital assessment, whether they indicate a downward trend toward increasing functional deficit, or the upward trend indicating the recovery of the subject to an improved functional status. In addition, the longitudinal follow-up testing by clinicians or home testing kits and/or apps, software applications, will allow for confirmation of the prognosis. In certain embodiments, the biomarker multivariate models could be combined computationally with other modalities Patent Application Attorney Docket No.179.0009-WO00 and data available at the time of assessment or at a later time, potentially including advanced MRI tracking of vascular, axonal, and other intracranial abnormalities, which may provide additional improvement to prognostic models and improvement over use of the blood biomarker profiles alone, and better relate to symptomatic and functional outcomes, providing a more complete “ground truth” for assessment and monitoring of post-injury pathology. Trauma Control versus TBI Signatures Several biomarkers were found to be elevated in both trauma controls and TBI subjects, as is described in the literature for some of the proteins measured here. Use of univariate analysis to compare distributions of biomarkers (Wilcoxon rank sum test) yielded initial indication of differences (comparison of median values). Additional tests included determination of differences using exact match permutation and generalized linear models (GLMs). Results are summarized in Table 8. Circulating blood biomarkers that are not specific to CNS proteins would be expected to be elevated during trauma induced inflammation, including IL-6 and ST2, and for vascular endothelial cell biomarkers such as vWF, indicating vascular damage and thrombosis. Because of the systemic contribution to blood levels of these biomarkers, it was expected that these might provide contribution to the severity of injury but might also lack specificity to acute intracranial damage. Neurocognitive Concordance with clinical assessment and TBI diagnosis. [0160] Neurocognitive assessment using the BrainCheck® Battery software was designed to detect and monitor neurocognitive impairment across several functional domains, and today is used clinically within neurology practices. Evaluating whether this digital health technology can be applied to the acute evaluation of head trauma to identify mild brain injury in elderly subjects is complicated by varying degrees of pre-existing cognitive decline and dementia. To robustly assess the concordance of BrainCheck® Battery classification with TBI diagnosis, results from several neurocognitive assessments administered in the study were considered to clarify the pre-existing cognitive status of the subject before the head injury event. In particular, the informant sections of the CDR and FAQ were relied upon, as suggested by our expert neurologists and neuropsychologists on the clinical and consulting teams. The informants were spouses, siblings or individuals who knew the enrolled subject well. [0161] The evaluation of BrainCheck® concordance with diagnosis was conducted as follows. Subjects enrolled under the current protocol were evaluated with the BrainCheck® neurocognitive battery as well as multiple clinical gold standard assessments for cognitive function and dementia. For all subjects, the informant portion of the Clinical Dementia Rating Scale (CDR) and the Functional Assessment Questionnaire (FAQ) were used as primary determinants of pre-injury cognitive status. [0162] For the diagnostic accuracy overall, area under the curve for receiver operator characteristic (AUC- ROC) curves distinguishing trauma controls from TBI was calculated for all subjects used in the full analysis (TC Patent Application Attorney Docket No.179.0009-WO00 and TBI subjects, current study and geriatric subjects from concurrent HeadSMART II feasibility phase). A separate BrainCheck concordance accuracy assessment for all TBI subjects was performed. Fig.9 shows the ROC curves for both assessments. In both cases, roughly 70% concordance was shown. This is likely due to lack of detailed pre-trauma neurocognitive assessment in the HeadSMART II subjects and may be clarified by analysis of just the subset of subjects enrolled and evaluated through the current study, where pre-existing status can be verified. [0163] The informant sections of the Clinical Dementia Rating Scale (CDR) and Functional Assessment Questionnaire (FAQ) were also used to assign a cognitively normal or cognitively impaired status pre-injury to both the TBI arm and the trauma control arm. The results of this refined analysis are shown in Table 9. The TBI positive individuals (assigned by expert review, ACRM criteria and/or neuroimaging) were shown to have an 82.6% concordance BrainCheck classification of likely or possible impairment.17.4 % were classified as “unlikely” impaired. Within the cognitively impaired TBI positive group, 100% of individuals were classified as likely or possible for cognitive impairment. Considering trauma controls (isolated non-head injury), both pre- existing cognitive impairment and cognitively age-normal subjects were also considered. Among the evaluable cognitively normal trauma controls, 6 of 18 (30%) were classified as “unlikely” for impairment, with 9/18 (50%) classified as “possible”, and 3/18 (16.7%) as “likely” impaired. Since these individuals are expected not to show impairment Within the trauma controls with preexisting cognitive impairment, all subjects were classified by BrainCheck as “likely” cognitive impairment (5/5, 100%). The evaluable sample sizes were small in this feasibility study but continue to support the use of BrainCheck for sensitivity in determining cognitive impairment in TBI, MCI or dementia. Further testing on a larger number of subjects will indicate whether specific digitized neurocognitive tests can discriminate TBI impairment from stages of dementia. This will require apply the same testing technology to dementia patients in a separate clinical study, but preliminary results may also be achieved by additional analysis of the current study in Phase II, after adjudication of the controls and TBI subjects for preexisting cognitive status that indicates MCI or early dementia.
Patent Application Attorney Docket No.179.0009-WO00 Table 9. Comparison of adjudicated cognitive status versus BrainCheck: Subgroup specific accuracy for enrolled trauma control and TBI subjects Concordance N subjects yes no Accuracy(%) Trauma control Normal 17 14 3 82.4 Trauma control Impaired 5 5 0 100 TBI Normal 50 39 11 82.6 TBI Impaired 9 8 1 88.9 Total 81 [0164] Overall, there is a high degree of consistency between BrainCheck Battery classification of neurocognitive impairment and validated standard assessments. This has been indicated in previously published studies, where BrainCheck Battery classification was compared with MMSE, MoCA and SLUMS cognitive assessments and showed high concordance(ref). If we consider the well characterized cohort in the current study design, there is also a high concordance with the impaired individuals (90-100%), but in cognitively normal individuals in either the trauma control or TBI arms there were many subjects with “possible” impairment. This is likely to be clarified in an algorithm that combines sensitive blood biomarker assays to detect injury-related analytes with the BrainCheck functional assessments. This is the POCT system being considered in this project. Example 3: Clinical Milestone 3 – Development of a trained algorithm that provide a diagnostic TBI score [0165] To further derive the combined diagnostic models incorporating blood biomarkers and digital neurocognitive testing results from the BrainCheck device, the full data set of blood biomarkers, age, sex, BrainCheck individual test metrics and overall BrainCheck Clinician Scores (aggregated percentile score derived from comparison with a normative database) were used in multivariate models for geriatric TBI specific diagnosis. Certain biomarkers were found to be undetectable in a significant proportion of individuals. Where more than 30% of subjects had undetectable values, the data were converted to a categorical present/absent dichotomization (binary value) rather than a continuous variable. All data processing and model building was performed in the R statistical environment. [0166] Multivariate models were computed using random forest with age and sex included as potential covariates in the classifier models (Table 10). There were several models that performed similarly by ROC curve analysis, which suggests that several indicators of TBI pathology subtypes can be combined to improve diagnostic performance. Compared with the median differences seen in the univariate analysis, we see recurring biomarkers NRGN and ST2 for discriminating TBI from dementia, and GFAP, which we found to be elevated in acute mTBI more than dementia, as a biomarker that can also distinguish mTBI from peripheral Patent Application Attorney Docket No.179.0009-WO00 trauma. BDNF was also found to differ in mTBI and dementia, with a similar decrease in median levels in univariate comparisons, and this was represented in some of the top performing models. The 4 plex model consisting of GFAP, NRGN, ST2, BDNF had the highest negative predictive value (NPV) of the models generated, when a minimum of 85% sensitivity is set, which could be advantageous for a rule out test in geriatric mTBI. Clinically, ruling out mTBI in geriatric subjects would add value to the CT imaging findings, since a very high percentage of patients get CT scans in this age group. More than 90% with no CT findings will still need assessment for clinically important brain injury. The added advantages of this chosen model above others include a strong intellectual property position for BRAINBox, established through years of careful prosecution and strategic licensing to support a commercial advantage. Table 10. Top 10 multivariate models using 3-4 biomarkers and age for discriminating acute mTBI from non- CNS trauma or dementia (combined class mTBI versus “else” in emergency trauma care) Random Forest ML Models TBI+ vs Dementia or Trauma Control Model covariates AUC Sensitivity Specificity Accuracy PPV NPV LR+ LR- NRGN,ST2,NSE,BDNF 0.84 0.857 0.657 0.739 0.636 0.868 2.5 0.217 NRGN,NSE,BDNF,vWF 0.833 0.857 0.687 0.759 0.667 0.868 2.735 0.208 NRGN,ST2,vWF,pSNCA 0.823 0.86 0.716 0.774 0.672 0.883 3.03 0.195 GFAP,ST2,NSE,BDNF 0.822 0.854 0.58 0.692 0.586 0.851 2.032 0.252 GFAP,NRGN,ST2,pSNCA 0.821 0.857 0.645 0.728 0.609 0.875 2.413 0.222 GFAP,NRGN,ST2,BDNF* 0.82 0.878 0.636 0.73 0.606 0.891 2.413 0.192 GFAP,NRGN,pSNCA,Age 0.819 0.857 0.724 0.776 0.667 0.887 3.102 0.197 ST2,NSE,BDNF 0.814 0.857 0.586 0.697 0.592 0.854 2.069 0.244 GFAP,ST2,BDNF,pSNCA 0.813 0.857 0.587 0.694 0.575 0.863 2.074 0.244 NRGN,ST2,NSE,vWF 0.812 0.857 0.676 0.752 0.656 0.868 2.649 0.211 Abbreviations: AUC, area under the ROC curve; PPV, positive predictive value; NPV, negative predictive value; LR+, Log ratio for predicting TBI+; LR-, Log ratio for predicting TBI-. pSNCA was used as binary variable present/absent due to significant number of subjects for which levels were undetectable; Age, age of the subject in years. Preferred model for advancement.

Claims

Patent Application Attorney Docket No.179.0009-WO00 CLAIMS 1. A method of diagnosing an acute TBI in an elderly subject, the method comprising the steps of: (A) obtaining a biological sample from the elderly subject; (B) measuring the levels of one or more biomarkers present in the biological samples by a protein detection assay, wherein the one or more biomarkers are selected from the group consisting of: brain derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), interleukin-6 (IL-6), metallothionein 3 (MT3), neurofilament light chain (NfL), neurogranin (NRGN), neuron specific enolase (NSE), synuclein alpha (SNCA), synuclein beta (SNCB), phosphorylated Ser129 SNCA (pS129-SNCA), soluble receptor for interleukin 33 (ST2), phosphorylated Thr181 tau (pT181 tau), phosphorylated Ser217tau (pS217 tau), phosphorylated Thr231 tau (pT231 tau), and von Willebrand factor (vWF); and (C) diagnosing the presence of an acute TBI if the level of one or more of the biological markers are altered relative to their respective reference levels. 2. A method of treating an elderly patient with traumatic brain injury or suspected of having traumatic brain injury, the method comprising: (A) administering over time a drug or drug treatment for traumatic brain injury comprising a single dose or multiple doses of the drug to the patient; (B) detecting at least one of the biomarker proteins selected from a group of biomarker proteins that distinguish traumatic brain injury from dementia, the group of biomarkers proteins comprising brain derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), interleukin-6 (IL-6), metallothionein 3 (MT3), neurofilament light chain (NfL), neurogranin (NRGN), neuron specific enolase (NSE), synuclein alpha (SNCA), synuclein beta (SNCB), phosphorylated Ser129 SNCA (pS129-SNCA), soluble receptor for interleukin 33 (ST2), phosphorylated Thr181 tau (pT181 tau), phosphorylated Ser217 tau (pS217 tau), phosphorylated Thr231 tau (pT231 tau), and von Willebrand factor (vWF) at (i) a first time point and (ii) at least one second time point following the first time point; (C) measuring levels of the at least one biomarker protein detected at the at least one second time point relative to the same biomarker proteins in a brain injury or healthy control compared to the measured levels of the at least one biomarker protein detected at the first time point; and (D) administering, maintaining administering, or discontinuing administering the drug or drug treatment to the patient if the level of one or more of the biological markers at the second time point are altered relative to level at the first timepoint. Patent Application Attorney Docket No.179.0009-WO00 3. A method of distinguishing an acute TBI from an age-related atrophy or brain disease in an elderly subject, the method comprising the steps of: (A) obtaining a biological sample from the elderly subject; (B) measuring the levels of one or more protein biomarkers present in the biological samples by immunoassay or mass spectroscopy, wherein the one or more protein biomarkers are selected from the group consisting of: brain derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), interleukin-6 (IL-6), metallothionein 3 (MT3), neurofilament light chain (NfL), neurogranin (NRGN), neuron specific enolase (NSE), synuclein alpha (SNCA), synuclein beta (SNCB), phosphorylated Ser129 SNCA (pS129-SNCA), soluble receptor for interleukin 33 (ST2), phosphorylated Thr181 tau (pT181 tau), phosphorylated Ser217 tau (pS217 tau), phosphorylated Thr231 tau (pT231 tau), and von Willebrand factor (vWF); and (C) determining the presence of an acute TBI if the level of the one or more biological markers are altered relative to their respective control or reference levels. 4. The method of any one of claims 1 or 3, further comprising treating the elderly subject for an acute TBI when at least one increased level of the one or more biomarkers is detected. 5. The method of any of claims 1-4, wherein the biological sample is selected from blood, plasma, serum, cerebrospinal fluid (CSF), tears or lacrimal fluid, urine, and saliva. 6. The method of any one of claims 1-5, wherein the one or more of biomarkers comprise two or more biomarkers selected from the group consisting of BDNF, GFAP, IL-6, MT3, NfL, NRGN, NSE, SNCA, SNCB, pS129- SNCA, sST2, pT181 tau, pS217 tau, pT231 tau, and vWF, and, optionally, one or more of ALDOC, FABP7, IL-7, and IL-33, 7. The method of claim 6, wherein the one or more biomarkers comprise a panel selected from one of the following groups of biomarker combinations: (a) two or more of NRGN, ST2, NSE, and BDNF; (b) two or more of NRGN, NSE, BDNF, and vWF; (c) two or more of NRGN, ST2, vWF, and pSNCA; (d) two or more of GFAP, ST2, NSE, and BDNF; (e) two or more of GFAP ,NRGN, ST2, and pSNCA; (f) two or more of GFAP, NRGN, ST2, and BDNF; (g) two or more of GFAP, NRGN, and pSNCA; Patent Application Attorney Docket No.179.0009-WO00 (h) two or more of ST2, NSE, and BDNF; (i) two or more of GFAP, ST2, BDNF, and pSNCA; (j) two or more of NRGN, ST2, NSE, and vWF; (k) two or more of GFAP, NRGN, IL-6 and p181-Tau; (l) two or more of NRGN, ST2, NSE, and SNCA; (m) two or more of GFAP, NRGN, IL-6 and vWF; (m) two or more of SNCA and ST2; (n) GFAP and SNCB; (o) GFAP and ST2; and (p) two or more of GFAP, NRGN, BDNF, vWF, IL-6, ST2, and pS217-tau. 8. A method of monitoring and treating a traumatic brain injury (TBI) over time in an elderly subject that sustained or is believed to have sustained a TBI, the method comprising the steps of: (A) obtaining a first biological sample from the subject at a first timepoint; (B) obtaining one or more subsequent biological samples from the same subject at one or more later timepoints; (C) detecting neurogranin (NRGN) levels in the first and subsequent one or more biological samples; (D) measuring the levels of NRGN in the first and subsequent one or more biological samples relative to a reference level of NRGN indicative of neurodegeneration; and (E) determining that subject has neurodegeneration and, optionally, treating the subject for neurodegeneration when the levels of NRGN at the one or more later timepoints remain increased relative to the reference levels. 9. A composition comprising a solid substrate and a plurality of antibodies or antigen-binding fragments thereof immobilized on the substrate, wherein the antibodies, or antigen-binding fragments thereof, specifically and respectively bind to a plurality of protein biomarkers comprising three or more of Brain derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), Fatty acid binding protein 7 (FABP7), interleukin-6 (IL-6), metallothionein 3 (MT3), neurofilament light chain (NfL), neurogranin (NRGN), neuron specific enolase (NSE), synuclein alpha (SNCA), synuclein beta (SNCB), phosphorylated Ser129 SNCA (pS129- SNCA), soluble receptor for interleukin 33 (sST2), phosphorylated Thr181 tau (pT181 tau), phosphorylated Ser217 tau (pS217 tau), phosphorylated Thr231 tau (pT231 tau), and von Willebrand factor (vWF). Patent Application Attorney Docket No.179.0009-WO00 11. The composition of claim 10, wherein the solid substrate comprises antibodies, or antigen-binding fragments thereof, specific for one or more combinations of protein biomarkers comprising: (a) NRGN, ST2, NSE, and BDNF; (b) NRGN, NSE, BDNF, and vWF; (c) NRGN, ST2, vWF, and pSNCA; (d) GFAP, ST2, NSE, and BDNF; (e) GFAP ,NRGN, ST2, and pSNCA; (f) GFAP, NRGN, ST2, and BDNF; (g) GFAP, NRGN, and pSNCA; (h) sST2, NSE, and BDNF; (i) GFAP, ST2, BDNF, and pSNCA; (j) NRGN, ST2, NSE, and vWF (k) GFAP, NRGN, IL-6 and p181-Tau; (l) NRGN, ST2, NSE, and SNCA; (m) GFAP, NRGN, IL-6 and vWF; (m) SNCA and ST2; (n) GFAP and SNCB; (o) GFAP and ST2; and (p) GFAP, NRGN, BDNF, vWF, IL-6, ST2, and phosphoS217-Tau. 12. A kit for detecting an acute TBI in an elderly subject, the kit comprising one or more biomarker panels that distinguish traumatic brain injury from dementia , the one or more biomarker panels comprising three or more antibodies, or antigen-binding fragments thereof, that specifically and respectively bind to a plurality of protein biomarkers comprising one or more of brain derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), interleukin-6 (IL-6), metallothionein 3 (MT3), neurofilament light chain (NfL), neurogranin (NRGN), neuron specific enolase (NSE), synuclein alpha (SNCA), synuclein beta (SNCB), phosphorylated Ser129 SNCA (pS129-SNCA), soluble receptor for interleukin 33 (sST2), phosphorylated Thr181 tau (pT181 tau), phosphorylated Ser217 tau (pS217 tau), phosphorylated Thr231 tau (pT231 tau), and von Willebrand factor (vWF). 13. The kit of claim 12, wherein the one or more biomarker panels comprise four or more biomarkers selected from the group consisting of BDNF, GFAP, IL-6, MT3, NfL, NRGN, NSE, SNCA, SNCB, pS129-SNCA, sST2, pT181 tau, pS217 tau, pT231 tau, and vWF, and, optionally, one or more of ALDOC , FABP7, IL-7, and IL-33. Patent Application Attorney Docket No.179.0009-WO00 14. The kit of claim 13, wherein the one or more biomarker panels comprise antibodies or antigen-binding fragments thereof specifically bind to one of the following combinations of biomarkers: (a) NRGN, ST2, NSE, and BDNF; (b) NRGN, NSE, BDNF, and vWF; (c) NRGN, ST2, vWF, and pSNCA; (d) GFAP, ST2, NSE, and BDNF; (e) GFAP ,NRGN, ST2, and pSNCA; (f) GFAP, NRGN, ST2, and BDNF; (g) GFAP, NRGN, and pSNCA; (h) ST2, NSE, and BDNF; (i) GFAP, ST2, BDNF, and pSNCA; (j) NRGN, ST2, NSE, and vWF (k) GFAP, NRGN, IL-6 and p181-Tau; (l) NRGN, ST2, NSE, and SNCA; (m) GFAP, NRGN, IL-6 and vWF; (m) SNCA and ST2; (n) GFAP and SNCB; (o) GFAP and ST2; and (p) GFAP, NRGN, BDNF, vWF, IL-6, ST2, and phosphoS217-Tau. 15. The kit of claim 13 or 14, further comprising one or more pre-coated strip plates, one or more biotinylated secondary antibodies, one or more standard solutions, one or more assay controls, one or more buffer solutions, streptavidin-horse radish peroxidase (HRP), tetramethyl benzidine (TMB), one or more stop reagents, and detailed instructions for carrying out the kit assay. 16. A method of testing an elderly subject suspected of having head injury to distinguish between traumatic brain injury (TBI) and dementia, the method comprising: (a) testing a bodily sample from the subject for an acute injury using one of more of the following biomarkers: soluble receptor for interleukin-33 (ST2), neurogranin (NRGN), Interleukin 6 (IL-6), and von Willebrand factor (vWF); (b) if the results of step (a) show an acute injury, testing the subject for an intracranial injury using one or more of the following biomarkers: GFAP and SNCB; and Patent Application Attorney Docket No.179.0009-WO00 (c) If the results of steps (a) and (b) do not show an acute injury, testing the subject for dementia using one or more of the following biomarkers: phosphorylated Thr181 tau (pT181 tau), IL-6, and brain derived neurotrophic factor (BDNF). 17. The method of claim 16, further comprising comparing levels of one or more of (i) ST2, NRGN, IL-6 and vWF and/or one or more of (ii) pT181-tau, IL-6, and BDNF in the elderly subject to the levels of the same biomarkers in trauma controls. 18. The method of claim 17, wherein the trauma controls are age-matched. 19. The method of claim 18, wherein the level of pT181-tau is increased and the level of at least one of IL-6 or BDNF is decreased relative to the levels in the age-matched controls. 20. The method of any one of claims 16-19, further comprising treating the subject for an acute TBI injury if the results of the tests in steps a) and b) show an acute injury. 21. The method of any one of claims 16-19, wherein the elderly subject is monitored over time, and further comprising comparing levels of one or more of (i) ST2, NRGN, IL-6 and vWF and/or one or more of (ii) pT181- tau, IL-6, and BDNF in the subject at one or more successive timepoints to the levels of the same biomarkers in trauma controls or to the levels of the same biomarkers in the subject at an earlier timepoint. 22. The method of claim 21, further comprising treating the subject for TBI injury if the level of pT181-tau increases over time. 23. The method of any one of claims 16-19, further comprising treating the elderly subject for dementia if the results of the testing in step c) show dementia. 24. The method of claim 21, further comprising treating the elderly subject for dementia if the level of pT181- tau remains unchanged over time and the levels of one or more of IL-6 and BDNF increases over time. 25. The method of any one of claims 16-24, further comprising performing neurocognitive testing on the elderly subject. Patent Application Attorney Docket No.179.0009-WO00 26. The method of claim 25, wherein the neurocognitive testing comprises battery and/or digitized neurocognitive tests, or digitized neurocognitive tests conducted using remote computing capability,. 27. The method of any one of claims 25-26, wherein the results of biomarker and/or neurocognitive testing on the elderly subject predict ongoing symptom burden and, optionally, treating the elderly subject for the symptom burden.
PCT/US2025/017101 2024-02-24 2025-02-24 Biomarkers, compositions, kits, and methods distinguishing acute geriatric tbi from pre-existing dementia or cognitive impairment Pending WO2025179300A1 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US202463557525P 2024-02-24 2024-02-24
US63/557,525 2024-02-24

Publications (1)

Publication Number Publication Date
WO2025179300A1 true WO2025179300A1 (en) 2025-08-28

Family

ID=96847876

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2025/017101 Pending WO2025179300A1 (en) 2024-02-24 2025-02-24 Biomarkers, compositions, kits, and methods distinguishing acute geriatric tbi from pre-existing dementia or cognitive impairment

Country Status (1)

Country Link
WO (1) WO2025179300A1 (en)

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190195893A1 (en) * 2015-02-05 2019-06-27 Brainbox Solutions, Inc. Methods and compositions for diagnosing brain injury or neurodegeneration
WO2023154860A1 (en) * 2022-02-11 2023-08-17 Tzerma Llc Methods for preventing ectopic brain mineralization in alzheimer's disease and dementias

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190195893A1 (en) * 2015-02-05 2019-06-27 Brainbox Solutions, Inc. Methods and compositions for diagnosing brain injury or neurodegeneration
WO2023154860A1 (en) * 2022-02-11 2023-08-17 Tzerma Llc Methods for preventing ectopic brain mineralization in alzheimer's disease and dementias

Similar Documents

Publication Publication Date Title
US12265091B2 (en) Circulating biomarker levels for diagnosis and risk-stratification of traumatic brain injury
JP6980291B2 (en) Compositions and Kits Useful for Diagnosis / Prognosis / Evaluation of Brain Injury
US12461112B2 (en) Biomarker levels and neuroimaging for detecting, monitoring and treating brain injury or trauma
An et al. Dynamic changes of oligomeric amyloid β levels in plasma induced by spiked synthetic Aβ42
US20250044303A1 (en) Protein biomarker indicators of neurological injury and/or disease and methods of use thereof
Herskovits et al. A Luminex assay detects amyloid β oligomers in Alzheimer’s disease cerebrospinal fluid
JP6265507B2 (en) Biomarker for cognitive dysfunction disease and method for detecting cognitive dysfunction disease using the biomarker
EP3452830B1 (en) Assay for the diagnosis of a neurological disease
US10739355B2 (en) Serum biomarker panels for bipolar disorder
Vanderstichele et al. Alzheimer’s disease biomarkers: from concept to clinical utility
US20250035650A1 (en) Biomarker testing for chronic persistent injury following brain trauma
US20250155455A1 (en) Protein biomarker indicators of neurological injury and/or disease and methods of use thereof
US20250067731A1 (en) Serological assays for parkinson&#39;s disease
WO2025179300A1 (en) Biomarkers, compositions, kits, and methods distinguishing acute geriatric tbi from pre-existing dementia or cognitive impairment
KR20220125640A (en) Use of tropomyosin alpha-4 chain and platelet glycoprotein Ib beta chain for diagnosis of Alzheimer&#39;s disease

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 25759029

Country of ref document: EP

Kind code of ref document: A1