Biomarker panels for brain-specific neurological abnormalities using biofluid samples

Abstract

A method for determining the degree of a central nervous system (CNS)-specific neurological condition in a subject includes collecting a biological sample of a biofluid from the subject and measuring the amount of a first biomarker, a metabolite of the first biomarker, or mRNA corresponding to the first biomarker from the sample via a dried spot or a microfluidic device. The biofluid is capillary blood or saliva, which offers the advantage of easy collection, making it attractive for field, hospital, and home environments. The method is useful in the diagnosis, care, and management of brain-specific abnormal neurological conditions in general, and specifically for traumatic brain injury (TBI), and (TBI-induced) Alzheimer's disease (AD) and Alexander disease (in which GFAP mutations are involved in white matter deterioration).

Description

[Technical Field]

[0001] [Related Applications] This application claims the benefit of priority to U.S. Provisional Application No. 63 / 425,761, filed November 16, 2022; the contents of which are incorporated herein by reference.

[0002] [Technical field] The present invention generally relates to determining an individual's brain- or central nervous system (CNS)-specific abnormal neurological condition, e.g., brain / CNS injury, and specifically relates to measuring the amount of brain-specific neuropredictive conditional biomarkers in biofluid samples of saliva or fingerstick capillary blood (wet and dried blood, dried serum, or dried plasma samples), alone or in combination with additional biomarkers from venous blood plasma or serum, to detect, monitor, diagnose, prognose, predict, identify, assist in treatment, or a combination thereof. For optimal clinical utility, biomarkers in biofluid samples and in combination with additional biomarkers in venous or arterial blood samples are most ideally measured at multiple time points in field, hospital, and home settings following a brain / CNS injury event or brain / CNS disorder. [Background technology]

[0003] The field of clinical neurology remains frustrated by the realization that secondary damage to central nervous system tissues associated with the physiological response to an initial insult can only be mitigated if the initial insult can be diagnosed promptly, or in the case of progressive disorders, before stress on central nervous system tissues reaches a preselected threshold. Traumatic, ischemic, and neurotoxic chemical insults, as well as genetic disorders, can all cause brain injury. While the diagnosis of severe forms of each of these causes of brain injury is straightforward through clinical response testing and computed tomography (CT) and magnetic resonance imaging (MRI) scans, these diagnostic methods have limitations. Specifically, spectroscopic imaging is expensive and time-consuming, while clinical response testing in individuals with impaired consciousness is of limited value and often precludes subtle diagnoses. Furthermore, the limitations of existing diagnostic methods often result in situations in which subjects are stressed by neurological symptoms, resulting in subjects often not realizing that damage is occurring or seeking treatment because subtle symptoms often subside quickly. If left untreated, these mild to moderate impairments to a subject's neurological condition can have a cumulative effect or lead to subsequent severe brain injury events, both of which have a poor clinical prognosis.

[0004] There is also growing recognition that rapid intervention when TBI is detected can greatly improve outcomes. The ability of first responders to detect TBI provides an optimal clinical opportunity to limit the secondary inflammatory cascade that follows injury. Growing evidence suggests that TBI is also a risk factor for the development of age-related neurodegenerative diseases, including Alzheimer's disease (AD) and Parkinson's disease (PD) (Dams-O'Connor, K. et al.; Duan, Y. et al.; Lee, PC et al.; Sivanandam, TM et al.). Moderate to severe TBI has been shown in autopsy studies to result in increased deposition of amyloid and the microtubule-associated protein tau (Tau) in the brain. Tau is a neuronal protein that helps stabilize microtubules within axons. Tau can be phosphorylated at multiple sites (P-Tau) by cellular protein kinases. Of particular interest are P-Tau phosphorylations at Thr181, Ser202 & Thr231, and S396 / 404 (Duan, Y. et al.), as well as P-Tau phosphorylation at Thr217 (Thijssen, La Joie et al. 2021; Mielke, Aakre et al. 2022; Mielke, Dage et al. 2022). In chronic traumatic encephalopathy, elevated levels of P-Tau are observed in the brain for years after mild TBI or concussion (McKee, AC et al.; and Omalu, BI et al.).

[0005] To overcome the limitations associated with spectroscopic diagnosis and clinical response diagnosis of neurological symptoms, there has been growing interest in using biomarkers as internal indicators of changes in the subject's molecular or cellular health status. Biomarker detection involves using a sample obtained from a subject to detect biomarkers in the sample, typically cerebrospinal fluid, blood, or plasma, so biomarker detection can be an inexpensive, rapid, and objective measurement of neurological symptoms. The achievement of a rapid and objective indicator of neurological symptoms makes it possible to determine the severity of abnormal brain symptoms on a scale with some objectivity, predict outcomes, provide treatment guidelines for symptoms, and monitor the subject's responsiveness and recovery. Furthermore, such information obtained from a large number of subjects allows for some insight into the mechanisms of brain damage.

[0006] Many biomarkers have been identified that are associated with severe traumatic brain injury, such as that often seen in vehicular crashes and combat casualties. However, there is still a lack of understanding about how multiple biomarkers interact and how they correlate with injury severity. This lack of understanding is particularly evident with traumatic brain injury.

[0007] Analysis of blast injury in subjects has yielded multiple novel correlations between proteins and neuronal damage, an example of a neurological condition. Neuronal damage may be the result of a blast to the whole body, blast force to a specific body part, or other neurotrauma or disease that results in detectable or identifiable levels of neuroactive biomarkers. Therefore, identifying the pathogenic pathways of primary blast brain injury (BBI) in reproducible experimental models is crucial for developing diagnostic algorithms to distinguish severe, moderate, and mild (mTBI) from post-traumatic stress disorder (PTSD). Accordingly, many experimental animal models have been implemented to study the mechanisms of blast impact, including rodents and large animals such as sheep. However, due to the fairly general nature of the blast generators used in different studies, data on brain injury mechanisms and putative biomarkers have been difficult to analyze and compare.

[0008] Despite extensive research into brain-specific proteins or autoantibodies thereto that become systemic in response to brain-specific abnormal neurological symptoms, the use of such markers has met with limited success in the field due to various issues such as sensitivity and the ability to obtain results in a clinically timely manner.

[0009] The requirement for venous blood sampling as a sampling method for detecting elevated blood biomarkers of neurological abnormalities limits the utility of such tests, resulting in either no data or delayed data relevant to care and / or treatment. This has proven problematic because care and / or treatment for many neurological abnormalities is time-sensitive to avoid secondary injury.

[0010] Thus, there is a need for methods and assays to improve the measurement of brain-specific abnormal neurological conditions based on a subject's biological fluids, such as saliva or blood drawn from a subject's capillaries, and there is a need for samples obtained by finger stick. There is also a need for detection methods and assays that can correlate saliva, dried blood, serum, or plasma spots drawn from biological fluids with traditional venous or arterial blood samples for abnormal neurological conditions. Summary of the Invention

[0011] The present invention provides a method for determining the degree of a central nervous system (CNS)-specific neurological condition in a subject, comprising the steps of collecting a biological sample of a biofluid from the subject and measuring the amount of a first biomarker, a metabolite of the first biomarker, or mRNA corresponding to the first biomarker from the sample from a dried spot or via a microfluidic device. The biofluid may be capillary blood or saliva, which offers the advantage of ease of collection, making it attractive for field, hospital, and home environments. The present invention has utility in the diagnosis, care, and management of brain-specific abnormal neurological conditions generally, and specifically for traumatic brain injury (TBI), and (TBI-induced) Alzheimer's disease (AD) and Alexander disease (in which GFAP mutations contribute to white matter deterioration). [Brief explanation of the drawings]

[0012] [Figure 1A] 1 illustrates a kit suitable for capillary blood biological fluid collection according to the present invention; [Figure 1B] Dried plasma spot (DPS) sampling and immunoassays are shown, with exemplary biomarkers shown as a function of concentration profiles relative to clinical events and cytotoxic cascades, with each temporal peak of the biomarkers correlated with an exemplary cellular source of the biomarker; [Figure 1C] illustrates a TBI temporal biomarker platform solution and workflow according to an embodiment of the present invention, using serial dry and wet plasma sample collections from TBI patients, which are then processed and analyzed in a centralized testing laboratory, and the results of a selected TBI temporal biomarker panel are reported to hospitals, physicians, and / or patients; [Figure 2] Graph showing high frequency dried plasma spot (DPS) sampling and highly sensitive immunoassay for a proprietary panel of blood-based temporal TBI biomarkers as a single platform solution (SPS); [Figure 3A]Plot of median / IQR (interquartile range) of pilot data for longitudinal wet serum tertiary NF-L against days after injury; [Figure 3B] Graph showing median / IQR of NF-L ratio on day 1 versus days post-injury; [Figure 3C] Boxplots showing NF-L levels for healthy controls, 1 day post-injury, 20 days post-injury, and 6 months post-injury; [Figure 3D] Boxplots showing pNF-H levels for healthy controls, 1 day post-injury, 20 days post-injury, and 6 months post-injury; [Figure 4A] Showing localization of MOG in the outer lamella of the myelin sheath; [Figure 4B] Elevated serum MOG levels in acute and subacute-chronic TBI samples. Comparison of median values ​​(Kruskal-Wallis test, ***P<0.001 compared with control, or ##, p<0.01); [Figure 4C] Showing the time course of serum MOG, showing the temporal profile for 12 patients; [Figure 4D-4E] The mean levels (and range) of anti-MOG antibody IgG and IgM compared with those of healthy controls at 1 day, 2 weeks, and 6 months post-injury are shown, respectively. *p<0.01, **p<0.05 difference from healthy control IgG, and p<0.05 difference from TBI day 1; [Figure 4F-4G] Shown are levels of MOG antibodies IgG and IgM, respectively, expressed as a ratio to the patient's own ratio on day 1. The red dotted line indicates that the ratio remains at 1, meaning no change from baseline on day 1. Some TBI patients show a 2- to >20-fold increase in IgG or IgM by 2 weeks or 6 months after injury; [Figure 4H] Figure 1 shows that when MOG IgG and IgM levels (as ratios of day 1 levels) were subjected to unsupervised trajectory analysis over time, three potential trajectory classes were identified: class 1 is a decreasing trajectory, class 2 is a flat trajectory, while class 3 is an increasing or ascending trajectory; [Figure 5A] Median / IQR plot of the temporal profile of the pilot data for serum total tau; [Figure 5B] Median / IQR plot of the temporal profile of the pilot data for serum pTau(231); [Figure 5C] Median / IQR plot of the temporal profile of the pilot data for serum p-Tau(181); [Figure 5D] Median / IQR plot of the temporal profile of the pilot data for serum pTau(231); [Figure 5E] Median / IQR plot of the temporal profile of the pilot data for serum P-Tau(181); [Figure 6A] Pilot data from the first highly sensitive immunoassay platform are presented, showing that the synaptic marker VAMP5 had elevated levels in TBI patients 2 weeks and 6 months after TBI compared with healthy controls and TBI day 1. *p<0.05, ANOVA of means; n=5–7; [Figure 6B] Pilot data from the first highly sensitive immunoassay platform are presented, showing that the neuronal cell body marker WASF1 had elevated levels in TBI patients 2 weeks and 6 months after TBI compared with healthy controls and TBI day 1. *p<0.05, ANOVA of means; n=5–7; [Figure 7] Graph showing pilot data of serum VEGF-A levels in the days following TBI and in healthy controls. Notably, VEGF peaked at days 7–10, which is later than p-TAU but earlier than NF-L and NF-H; [Figure 8] Graph of IL-6 levels over several days after TBI and in healthy controls. Notably, CSF and serum IL-6 levels are elevated from days 0 to 7 after severe TBI. IL-6 assay was by sandwich ELISA (R&D Systems); [Figure 9A]Graph showing preliminary validation of analytical equivalence between the first highly sensitive immunoassay platform and the second conventional immunoassay platform using NFL measurements of de-identified, stored wet plasma samples from a full spectrum of TBI subjects (day 1 to 6 months post-injury), with the first NFL data showing very strong correlation with the second NFL data (R2=0.861); [Figure 9B] Graph showing preliminary validation of analytical equivalence between the first highly sensitive immunoassay platform and the third immunoassay platform using NFL measurements of de-identified and stored wet plasma samples from a full spectrum of TBI subjects (day 1 to 6 months post-injury), with the first NFL data showing good correlation with the third NFL data (R2=0.656); [Figure 10A] Graph showing preliminary validation of analytical equivalence of wet versus DPS sampling for NFL and WASF1 measurement of de-identified and stored plasma specimens from a full spectrum of TBI subjects (day 1 to 6 months post-injury) using the first highly sensitive immunoassay platform; [Figure 10B] Graph showing preliminary validation of analytical equivalence of wet versus DPS sampling for WASF1 measurement of de-identified and stored plasma specimens from a full spectrum of TBI subjects (day 1 to 6 months post-injury) using the first highly sensitive immunoassay platform; [Figure 11A] Graph showing preliminary validation of analytical equivalence of wet versus DPS sampling for recovery of TBI biomarkers using serial dilutions across five orders of magnitude of the recombinant protein biomarker GFAP in spike recovery studies in pooled plasma from 10 healthy controls aged 40-45 years; [Figure 11B] Graph showing preliminary validation of analytical equivalence of wet versus DPS sampling for recovery of TBI biomarkers using serial dilutions across five orders of magnitude of the recombinant protein biomarker NFL in spike recovery studies in pooled plasma from 10 healthy controls aged 40-45 years; [Figure 11C]Graph showing preliminary validation of analytical equivalence of wet versus DPS sampling for recovery of TBI biomarkers using serial dilutions across five orders of magnitude of the recombinant protein biomarker tau in spike recovery studies in pooled plasma from 10 healthy controls aged 40-45 years; [Figure 11D] Graph showing preliminary validation of analytical equivalence of wet versus DPS sampling for recovery of TBI biomarkers using serial dilutions across five orders of magnitude of the recombinant protein biomarker UCH-L1 in spike recovery studies in pooled plasma from 10 healthy controls aged 40-45 years; [Figure 12] Showing levels of wet-biologically derived MOG at various test time points over time; [Figure 13] The results of the Kruskal-Wallis test for serum MBP elevation in samples from the control group, TBI days 0-10, and TBI days 12-12 months are shown, indicating that the difference from the control is significant (***p<0.0001) and that the delayed increase in MBP blood levels is similar to the pattern of NF-L; [Figure 14A] Scatter plot of serum GFAP over 14 days post-injury, with a reference baseline of 60 pg / mL; [Figure 14B] Scatter plot of the ratio of serum GFAP to day 1 over 14 days post-injury; [Figure 15] Shown are wet plasma GFAP (third platform) levels at various test time points over time; [Figure 16A] Showing levels of NFL (first platform) in wet plasma at various test time points over time; [Figure 16B] Showing levels of NFL (second platform) in wet plasma at various test time points over time; [Figure 16C] Showing levels of NFL (third platform) in wet plasma at various test time points over time; [Figure 17A] Showing wet plasma pNFH (second platform) levels at various test time points over time; [Figure 17B] Plasma or serum BDNF (second platform) levels at various test time points or TBI severities over time are shown compared to controls; [Figure 18A] GFAP day 1 healthy controls vs. ER TBI subjects, ROC curve; [Figure 18B] Graph showing GFAP levels in ER TBI subjects versus healthy controls; [Figure 19A] ROC curve showing GFAP at 2 weeks post-TBI; [Figure 19B] Graph showing GFAP in ER TBI subjects versus healthy controls at 2 weeks post-TBI; [Figure 20A] This is the ROC curve showing the NFL; [Figure 20B] Graph showing NFL levels in ER TBI subjects versus healthy controls less than 24 hours after TBI; [Figure 21A] ROC curve showing NFL at 2 weeks after TBI; [Figure 21B] Graph showing NFL levels in ER TBI subjects versus healthy controls at 2-3 weeks post-TBI; [Figure 22] Showing levels of TBCB (wet plasma) at various test time points over time; [Figure 23] Showing levels of WASF-1 (wet plasma) at various test time points over time; [Figure 24] Showing levels of WASF3 (wet plasma) at various test time points over time; [Figure 25] Shows levels of VAMP5 (wet plasma) at various test time points over time; [Figure 26] Shows levels of CAMKK1 (wet plasma) at various test time points over time; [Figure 27] Shows the levels of Ninjurin-1 (wet plasma) at various test time points over time; [Figure 28] Showing the levels of IMPA1 (wet plasma) at various test time points over time; [Figure 29]Shows levels of ZBTB16 (wet plasma) at various test time points over time; [Figure 30] Shows levels of PRDX6 (wet plasma) at various test time points over time; [Figure 31] Shown are levels of NFATC1 (wet plasma) at various test time points over time; [Figure 32] Showing levels of NAA10 (wet plasma) at various test time points over time; [Figure 33] Shown are levels of ING1 (wet plasma) at various test time points over time; [Figure 34] 1 shows CSF MOG levels in patients with multimorbidity neurological conditions with levels higher than those in matched pooled healthy controls. [Figure 35] Serum MOG levels in patients with multimorbid neurological conditions with higher levels than those in corresponding pooled healthy controls (p=0.007, two-tailed ANOVA analysis); [Figure 36] CSF MOG levels in secondary primary multiple sclerosis (SPMS) patients with higher levels than those in corresponding pooled healthy controls (p=0.033, two-tailed T-test analysis); [Figure 37] Serum MBP levels in patients with multimorbid neurological conditions with higher levels than those in corresponding pooled healthy controls (p=0.0285, two-tailed T-test analysis); [Figure 38] 1 is a graph showing the temporal profile of serum MOG levels over time in four subjects with out-of-hospital cardiac arrest (OHC). Two subjects with poor prognosis (cerebral function category / CPC score 4) have higher temporal levels of serum MOG compared to the levels in two PHCA patients with low (or normal) CPC scores. [Figure 39]1 shows the temporal profile of serum MBP levels over time in four subjects with out-of-hospital cardiac arrest (OHC). Two subjects with poor prognosis (cerebral function category / CPC score 4) have higher temporal levels of serum MOG compared to the levels in two PHCA patients with low (or normal) CPC scores. [Figure 40A] Graph showing the levels of various TBI temporal biomarkers over time after TBI; [Figure 40B] Showing example output of "Gryphon Temporagram" for severity / grade (high, medium, low) versus time; [Figure 41A] Graph showing levels of a temporal brain biomarker profile (Gryphon Temporagram) that indicate a high probability or risk for complications, readmission, or persistent PCS after TBI; [Figure 41B] Graph showing levels of a temporal brain biomarker profile (Gryphon Temporagram) that indicate a moderate probability or risk for complications, readmission, or persistent PCS after TBI; [Figure 41C] Graph showing levels of a temporal brain biomarker profile (Gryphon Temporagram) indicating a low probability or risk for complications, readmission, or persistent PCS after TBI; [Figure 42] 1 is a flow diagram illustrating the benefits of embodiments of the present invention and how they can lead to improved patient care for brain injuries; [Figure 43A] Graph showing measurement of glial fibrillary acidic protein (GFAP) from dried plasma spot (DPS) samples of TBI patients on day 1 of injury; [Figure 43B] Graph showing measurement of neurofilament light chain (NfL) from dried plasma spot (DPS) samples of TBI patients on day 1 of injury; [Figure 43C] Graph showing measurement of total tau from dried plasma spot (DPS) samples of TBI patients on day 1 of injury; [Figure 43D] Graph showing measurement of phosphorylated threonine 181 tau (pTau181) from dried plasma spot (DPS) samples of TBI patients at day 1 of injury; [Figure 43E] Graph showing measurement of glial fibrillary acidic protein (GFAP) from plasma samples of TBI patients on day 1 of injury; [Figure 43F] Graph showing measurement of neurofilament light chain (NfL) from plasma samples of TBI patients on day 1 of injury; [Figure 43G] Graph showing measurement of total tau from plasma samples of TBI patients on day 1 of injury; [Figure 43H] Graph showing measurement of phosphorylated threonine 181 tau (pTau181) from plasma samples of TBI patients on day 1 of injury; [Figure 43I] Graph showing measurement of glial fibrillary acidic protein (GFAP) from saliva samples of TBI patients on day 1 of injury; [Figure 43J] Graph showing measurement of neurofilament light chain (NfL) from saliva samples of TBI patients on day 1 of injury; [Figure 43K] Graph showing measurement of total tau from saliva samples of TBI patients on day 1 of injury; [Figure 43L] Graph showing measurement of phosphorylated threonine 181 tau (pTau181) from saliva samples of TBI patients on day 1 of injury; [Figure 43M] Graph showing longitudinal plasma samples from individual TBI patients taken at 6 and 12 months for measurement; [Figure 43N] Graph showing longitudinal saliva samples from individual TBI patients collected at 6 and 12 months for measurement; [Figure 44A] 43A-43N are matrix correlation plots of dried plasma spot (DPS) sampling device, plasma, and saliva for GFAP; [Figure 44B]Matrix correlation plots of dried plasma spot (DPS) sampling device, plasma, and saliva for NfL from the data in Figures 43A-43N; [Figure 44C] Matrix correlation plots of dried plasma spot (DPS) sampling device, plasma, and saliva for total tau from the data in Figures 43A-43N; [Figure 44D] 43A-43N are matrix correlation plots of dried plasma spot (DPS) sampling device, plasma, and saliva for pTau181; and [Figure 44E] A 1:1 comparison of DPS sampling recovery from a single patient sampling compared to plasma and saliva is shown. DETAILED DESCRIPTION OF THE INVENTION

[0013] The present invention has utility in the diagnosis, care, and management of brain-specific abnormal neurological conditions generally, and specifically in traumatic brain injury (TBI) and (TBI-induced) Alzheimer's disease (AD) and Alexander disease (in which GFAP mutations contribute to white matter deterioration). The present invention also has utility in detecting brain-specific abnormal neurological conditions through the detection of temporal biomarkers in saliva or finger-prick biofluid samples (saliva, wet and dried blood, plasma, and serum), including proteins, metabolites, lipids, mRNA, DNA, cells, microRNA, and / or autoantibodies thereto. Abnormal neurological conditions can result from neurotrauma, such as from a percussion, blast, or impact injury, or from damage resulting from ischemia or disease. The use of microfluidic devices or dry sample assays provides a detection system suitable for use in the field, at home, and / or during patient transport, as well as in the hospital.

[0014] The present invention provides early detection and monitoring of subclinical evidence of disease activity (sEDA) before, during, and / or after the onset of clinical evidence of disease activity (EDA).

[0015] The ability to use saliva samples or capillary-collected blood samples offers the advantage of ease of collection compared with venous or arterial sources, making them attractive for field, hospital, and home environments. Challenges associated with capillary-collected samples include small sample volumes and correlation of detection results with venous or arterial blood samples. The use of dried blood, dried plasma, and / or dried serum spots as samples facilitates transportation and storage, but adds complexity to testing because biomarker recovery, solubility, protection, and degradation must be considered, as well as the correlation of the concentration of any biomarker detected in biological fluids with the concentration of the biomarker in venous or arterial (tube) blood.

[0016] FIG. 1A illustrates a kit (generally designated 10) for collecting capillary blood biofluids. The kit 10 includes a lancet 12 for puncturing the skin to collect capillary blood biofluids. Capillary blood collection is typically performed on a subject's finger, although the heel, forearm, and earlobe are other examples of conventional sites for collecting capillary blood. A single expressed drop of blood typically has a volume of 20 to 50 microliters. The resulting drop of blood is transferred, either directly or with the use of an applicator (not shown), to a porous substrate 14 or a microfluidic device 16. In some invention embodiments, the porous substrate 14 has a known blood retention capacity, and each unit area of ​​the porous substrate 16 corresponds to a known blood volume. Typically, one square millimeter of porous substrate 16 will retain between 1 and 20 microliters of capillary blood, with the thickness of the substrate and its capillary wickability to blood being important factors in determining the blood retention capacity of the porous substrate 16. After absorption, the liquid components of the blood droplet evaporate, and the biomarkers and cellular components from the blood droplet are retained within the porous substrate. In some invention embodiments, a surface coating 17 is present on the porous substrate 14, which has channels sized to allow plasma components to pass through, while preferentially excluding cellular components of the blood from entering the porous substrate 14.

[0017] Alternatively, or in combination with the porous substrate 14, a microfluidic device 16 is included in the kit 10. The microfluidic device 16 has an inlet 18 for receiving a drop of blood, indicated by a curved inlet arrow. A buffer inlet 20 is also provided to dilute the blood and transport its components, including the biomarker of interest, through a channel system (simply designated 20). One or more outlets 22 and 24 are provided for discharging waste, biomarker-containing fractions, etc. It is understood that determining the amount of a given biomarker in a sample of biological fluid can provide clinically useful information regarding the nature of an abnormal neurological condition. Further information useful for treatment may reside in the detection of isoforms, degree of splicing, phosphorylation, other chemical or post-translational modifications, mutations, or combinations thereof, in a given biomarker. Tau protein is an example of a biomarker that includes secondary information, such as phosphorylation at specific amino acid residues. Elution of the biomarker from the microfluidic device 16 provides the option of further evaluating the biomarker through techniques not incorporated into the microfluidic device.

[0018] In some invention embodiments, kit 10 includes a device that is a lightweight, non-refrigerated, scalable, cost-effective, and minimally invasive dried plasma spot (DPS) sampling device. Such devices, as shown for example in reference to 14 or 16, are specifically designed for self- or caregiver-assisted fingerstick collection of capillary blood biofluids at home, in the field (e.g., at sporting events or in harsh military environments), or in hospitals. The ability to collect capillary blood biofluid samples simultaneously with suspected TBI, TBI-induced Alzheimer's disease (AD), or other events indicative of neurological deterioration, even by untrained or limitedly trained individuals, increases the likelihood of detecting one or more biomarkers that reach peak concentrations in the blood within four hours of injury, thereby providing important clinical information regarding the cell types involved. Alexander disease is also believed to be detectable according to the present invention through GFAP protein sequencing from samples. This is illustrated in Figure 1B, which shows the relative dynamics of various biomarkers along with the cell types that are the source of specific biomarkers upon injury. The present invention eliminates the need for venipuncture blood collection, thereby eliminating the associated refrigerated transport and storage of blood sample tubes. Dried (whole) blood spot sampling is well known as part of prenatal testing and reported in longitudinal studies for indications outside the CNS (Curtis, Ambrose et al. 2014; Mussa, Ciuffreda et al. 2019). However, it has not previously been applied to the detection of biomarkers of abnormal neurological conditions, particularly in capillary blood biofluids collected as dried plasma or serum, or saliva biofluid samples.

[0019] The present invention provides a highly sensitive immunoassay requiring a small sample volume: a temporal biomarker panel using capillary blood or saliva samples for biomarkers present at relatively high concentrations or for which sensitive detection techniques exist. Biofluid-based biomarkers that function in the present invention include, by way of example, P-Tau (181, 202, 217, 231, 396 / 404), tau, IL-6, IL-15, GFAP and its breakdown products (BDPS), NF-L, MOG, aquaporin 4, apolipoprotein E4, SAA, adenosine, myo-inositol, norepinephrine, NAA, NAAG, glutamate, glutamine, combinations thereof, and metabolic breakdown products of any of the above. It is understood that the breakdown products of GFAP and their temporal cascades are well known to those skilled in the art.

[0020] In some embodiments of the invention, capillary blood biofluid collection of the present invention is used in combination with traditional collection of venous or arterial blood samples to establish analytical equivalence of the sampling panels of temporal (acute, subacute, and chronic) CNS and non-CNS blood biomarkers of the present invention (FIG. 1B), using both samples from capillary blood biofluid collection (e.g., fingerstick capillary blood collection and dried plasma spot (DPS) sampling) and samples from venous blood collection. Notable differences between traditional venous or arterial blood samples and DPS samples include differences in at least one of the relative recovery levels, composite scores, and temporal profiles of a given biomarker. Thus, differences cannot be predicted from the amino acid sequence or structure of a given biomarker.

[0021] According to the present invention, biofluids are analyzed for a given biomarker from a saliva sample or a dried blood spot, or using a microfluidic device, an example of a microfluidic device that works here is that disclosed in US 20090053732 A1.

[0022] As used herein, the abbreviations "D," "mo.", and "Y" are used synonymously for day, month, and year, respectively.

[0023] As used herein, "clinical EDA" illustratively includes subject imaging, CSF biomarkers, cognitive function assessments, and other clinical measurements that are not based on blood biomarkers.

[0024] Where a range of values ​​is given, it should be understood that the range is intended to encompass not only the endpoints of the range, but also intermediate values ​​expressly included within the range and varied by the last significant digit of the range. As an example, the stated range of 1 to 4 is intended to include 1 to 2, 1 to 3, 2 to 4, 3 to 4, and 1 to 4.

[0025] According to embodiments, a lightweight, non-refrigerated, scalable, cost-effective, minimally invasive biofluid sampling device, such as the dried plasma spot (DPS) sampling device, is provided that is specifically designed for field-assisted blood collection as part of a single platform solution (SPS). This significantly improves the feasibility of sample collection for TBI patients during chronic field care (PFC), transport from the field to a hospital, hospital stays, and outpatient stays in out-of-hospital settings. By maintaining a single sampling platform throughout patient management and treatment, a composite score (threshold) is calculated between a point-of-care measurement solution, such as the iSTAT platform, and a more sensitive hospital-based solution, such as the core lab Anility immunoassay platform, without the need for difficult or nearly impossible bridging studies. Furthermore, unlike the iSTAT platform, DPS sampling does not require venipuncture blood collection or refrigerated transport and storage of blood specimens.

[0026] Embodiments of the present invention utilize DPS testing for TBI biomarkers in biological fluids. According to some invention embodiments, 5-25 μL of plasma from 3-4 drops (70 μL) of fingerstick capillary blood is placed on a DPS. According to embodiments, the present invention includes a dried plasma spot (DPS) sampling device. According to embodiments, the present invention uses a five-step procedure from sequential sampling of 70 μL (3-4 drops) of fingerstick blood to capillary transport of a preselected amount (e.g., 10 μL) of plasma to the DPS collection disk. The system collects 2 x 10 μL of plasma from fingerstick blood in the 35-55% hematocrit range. Utilizing the biomarkers and technology described in WO2016 / 209147A1 and WO2020 / 050770A, all functions of the system are passively driven, including blood pre-metering (1), plasma extraction (2), plasma metering (3), and collection into a dried sample format (4), as shown in Figure 1B. This design allows for fluid manipulation solely through capillary forces, resulting in a fully autonomous, multifunctional system. In some inventive embodiments, the system is constructed using foil-based microfluidic technology, enabling roll-to-roll high-throughput manufacturing. The device builds on the successful dried blood spot sampling device, capable of measuring analytes with unprecedented volumetric accuracy from a wide range of applied sample volumes and hematocrit levels.

[0027] The present invention provides a fast and effective single-platform solution (SPS) for clinically validating a single panel of temporal biomarkers of the brain environment, using distinct and complementary biomarkers representing vulnerable brain cell types, subcellular structures, TBI-related pathophysiological events, and / or subphenotypes. These include axonal injury (neurofilament proteins NF-L, pNF-H) (Figures 3A, 3B, and 3C), myelin / white matter damage (myelin oligodendrocyte glycoprotein / MOG) (Figures 4A, 4B, and 4C), MOG antibodies IgG and IgM (Figures 4D, 4E, 4G, and 4H), neurodegeneration (tau, p-Tau(T231)) (Figures 5A, 5B, 5C, 5D, and 5F), synaptic damage (vesicle-associated membrane protein 5 (VAMP5)), Wiskott-Aldrich syndrome protein family member 1 (WASF1) (Figures 6A and 6B), vascular injury / remodeling marker VEGF-A (Figure 7), neuroinflammatory marker (IL-6) (Figure 8), and are complemented by the astroglial injury marker GFAP (Figures 14A, 14B, and 15), which is by far the most robust marker for TBI diagnosis (Czeiter, (Amrein et al. 2020). The SPS of the present invention combines high-frequency DPS sampling with sensitive immunoassays for a unique panel of blood-based temporal TBI biomarkers (acute, subacute, and chronic) to monitor patient progression and phenotype individual trajectories, reconstructing and informing critical decision-making from initial injury in the field to the hospital and home environment, as shown in Figure 2. Figure 2 is a graph illustrating high-frequency dried plasma spot (DPS) sampling and sensitive immunoassays for a unique panel of blood-based temporal TBI biomarkers as a single platform solution (SPS). Critical decisions include triage decisions, injury severity, need for higher levels of care, management and treatment, and return-to-duty / work / play decisions (Orszag and Emanuel 2010; Brito, Costantini et al. 2019; Shrank, DeParle et al. 2021).

[0028] According to some invention embodiments, a single highly sensitive immunoassay platform is provided with multiplexing capabilities to test a panel of up to seven biomarkers indicative of TBI, and in other embodiments, up to 20 such biomarkers. According to other invention embodiments, the immunoassay platform of the present invention utilizes the first platform described above. The diagnostic methods of the present invention are carefully designed to include multiple key TBI-tracking protein biomarkers with distinct yet complementary acute and subacute temporal profiles to identify secondary injury, PCS, or the onset of immune responses that inform return-to-duty / work / play decisions.

[0029] According to some embodiments of the invention, the CP of the present invention described above allows for repeated fingerstick-based blood sampling from the same subject throughout all stages of TBI using a single platform. For example, the CP is ideal for pre-hospital specimen collection, including during field care, during transport, at hospitals or other care facilities, and after discharge. Advantageously, the present invention reduces the burden of biosampling.

[0030] UniProt reference numbers for biomarkers used in embodiments of the present invention are as follows: NFL - Neurofilament L (UniProtKB-P07196, P07197, P12036 (NFL_HUMAN)) GFAP - Glial fibrillary acidic protein (astrocyte integrity) (UniProtKB-P14136 (GFAP_HUMAN)) GFAP breakdown products (BDPS) 38K, Tau / p-Tau (based on WO2020124013A1), TCBB - Tubulin folding cofactor B (elevated by injury) (UniProtKB-Q99426 (TBCB_HUMAN)) Non-brain specific subacute markers IMPA1 - Inositol monophosphatase 1 (UniProtKB-P29218 (IMPA1_HUMAN)) NNA10 - N-terminal acetyltransferase 10 (UniProtKB-P29218 (IMPA1_HUMAN)) BDNF - Brain-derived neurotrophic factor (UniProtKB-P23560(BDNF_HUMAN)) WASF1 - Wiskott-Aldrich syndrome protein family member 1 (UniProtKB-Q92558(WASF1_HUMAN)) WASF3 - Wiskott-Aldrich syndrome protein family member 3 (UniProtKB-Q9UPY6(WASF3_HUMAN)) CAMKK1 - Calcium / calmodulin-dependent protein kinase kinase 1 (UniProtKB-Q8N5S9(KKCC1_HUMAN)) Ninjurin-1 (vascular injury) (UniProtKB-Q92982(NINJ1_HUMAN)) ICAM1 (intercellular adhesion molecule 1) (UniProtKB-P05362(ICAM1_HUMAN)).

[0031] Acute and delayed axonal damage has been suggested after brain injury, but it can be difficult to grasp. Neselius et al. found elevated pNF-H levels in CSF after bouts in amateur boxers (Neselius, Zetterberg et al. 2013). pNF-H may also be a predictor of mortality after brain injury in children (Hu, He et al. 2002). Furthermore, serum NF-L also appears to be elevated throughout the season in American football players and in TBI subjects. Importantly, the release of NF proteins into biofluids is a delayed process (several days after the initial insult) (Yuan and Nixon 2021). More recent data indicate that NF-L continues to be elevated within the first 14 days post-injury (dpi) and then clearly declines 1–3 months later (Shahim, Politis et al. 2020). Frequent serum sampling from severe-moderate TBI patients is used to establish that both NF-L (third platform) and pNF-H are elevated from days 1 to 14, as shown in Figures 3A-3B. Furthermore, using serum samples from longitudinal severe-moderate TBI patients, the present invention demonstrates that both NF-L and pNF-H indeed peak between days 14 and 20 after injury and then decline 6 months after injury. However, even after 6 months, NF-L and pNF-H levels are still higher than their respective normal controls.

[0032] White matter injury (WMI) is clinically significant in brain injury patient populations. WMI is often associated with myelin damage and demyelination. As mentioned above, oligodendrocytes form myelin sheaths that protect long intracerebral axons (myelinated fiber tracts) in the white matter, as shown in Figure 4. However, WMI and myelin damage and demyelination are difficult to assess noninvasively. Figures 4B-4C show pilot data for the demyelination marker MOG, demonstrating persistently elevated levels from the subacute to chronic phases of TBI. Specifically, Figure 4A shows the localization of MOG in the outer lamella of the myelin sheath. While not intending to be bound by any particular theory, it is believed that its location on the outer surface of the myelin sheath makes MOG highly vulnerable to structural damage to myelin, leading to its release into the circulation. Figure 4B shows elevated serum MOG levels in acute (days 1-8) and subacute-chronic (days 15-1 year) TBI samples. Comparison of medians (Kruskal-Wallis test, ***P<0.001 compared with control, p<0.01). Figure 4C shows the time course of serum MOG, showing the temporal profile for 12 patients. The myelin sheath found in the CNS functions as an insulator, increasing the velocity of axonal impulse conduction. MOG is found on the outer lamella associated with the myelin sheath. Myelin basic protein (MBP) is found in the compact myelin layer of the myelin sheath. Previously, MOG has only been studied as a potential biomarker for demyelinating diseases such as multiple sclerosis (MS) (Galazka, Mycko et al. 2018), but not for TBI or Alexander disease. However, the present invention is based on the finding that in human MOG ELISA assays, there is robust release of MOG into human serum from TBI patients and Alexander disease subjects throughout the acute (1-10 days post-injury) to chronic (10 days-12 months post-injury) phases, as shown in Figure 4B. Importantly, the MOG biomarker showed higher chronic than acute levels in 14 of 15 TBI patients, as shown in Figure 4C, suggesting that demyelination persists long after the initial injury.This set of data and observations regarding blood-based measurement of MOG as a biomarker for delayed demyelination / WMI following acute brain injury, such as TBI, are novel and, to our knowledge, have not previously been disclosed in the literature or in patent applications. The sustained elevation of MOG levels in the chronic phase (e.g., 1 month to 1 year) after injury compared with the acute phase and its temporal profile are unique and unobvious among other brain injury biomarkers. Importantly, this invention reveals that this delayed and sustained release of MOG contributes to previously unknown persistent damage to the myelin sheath and the associated potential chronic vulnerability of white matter. Furthermore, MOG is an autoantigen recognized in certain central nervous system autoimmune diseases. MOG antibody-associated disease (MOGAD) is defined as a neurological and immune-mediated disorder associated with inflammation in the optic nerve, spinal cord, and / or brain. The production of MOG antibodies (autoantibodies) in the immune system can actually lead to CNS demyelination and neuromyelitis optica (NMO) (Marignier et al., Lancet Neurol. 2021, vol. 20, 767). Previously, it has been shown that another brain protein, glial fibrillary acidic protein (GFAP), can trigger an autoimmune response after TBI (Zhang Z, et al., PLoS One. 2014, vol. 9(3):e92698; Wang, KKW, J. Neurotrauma, 2016, vol. 33:1270). However, because MOG is continuously released, TBI patients are thought to be at high risk for developing an autoantibody response against MOG after the initial brain injury. Given that MOG antibody-associated disorders have already been reported, the present invention utilizes elevated MOG levels as a diagnostic test result to predict a patient's risk of developing MOGAD or a MOGAD-like autoimmune disorder. The metabolites of MOG are known (Peschl, Patrick et al.).

[0033] As shown in Figure 4D, mean values ​​of both anti-MOG antibody IgG and IgM isoforms were significantly elevated in patients (across the full severity spectrum, N = 500) 2 weeks and 6 months after TBI compared with those in healthy controls (N = 150). Meanwhile, Figure 5E shows that mean anti-MOG antibody IgM levels 2 weeks after TBI were higher than mean levels on day 1 after TBI. The delayed increase in MOG antibodies is consistent with an autoimmune response. Figures 4F and 4G further demonstrate that when MOG IgG and IgM levels in the same subjects are expressed as a ratio to their day 1 IgG and IgM levels, respectively, a 2- to over 20-fold increase in MOG antibodies (as IgG or IgM) is evident in some TBI patients 2 weeks and 6 months after injury. Figure 4H shows that machine learning-based trajectory analysis can indeed classify MOG antibody IgG and IgM levels into three potential trajectory classes: Class 1 (decreasing trajectory), Class 2 (flat trajectory), and Class 3 (high or increasing trajectory). Samples from the same subjects were taken 1–5 days, 2 weeks, and 6 months after TBI. Notably, 3.8% of patients had elevated MOG IgG over time, and 6.3% had elevated MOG IgM. While not intending to be bound by any particular theory, it is believed that such elevated MOG levels may be associated with persistently elevated blood MOG levels across time points after brain injury. Therefore, the present invention has utility in measuring MOG biomarkers in blood (or serum or plasma) to inform clinicians and patients about their risk of developing MOGAD or MOGAD-like disorders.

[0034] As mentioned above, autopsy studies have shown that moderate to severe TBI results in increased deposition of amyloid and the microtubule-associated protein tau (Tau) in the brain. In chronic traumatic encephalopathy, elevated levels of P-Tau are observed in the brain for several years after mild TBI or concussion (McKee, Cantu et al. 2009; Omalu, Hamilton et al. 2010). Prior art offers an ultrasensitive peripheral fiber optic immunosorbent assay (RCA-SOFIA) for total tau (T-Tau) and P-Tau using rolling cycle amplification. The sensitivity (fg / mL) of this platform exceeds that of the next most sensitive platform (the third). Therefore, T-Tau is readily detected in serum / plasma, and much less P-Tau (231) is also detectable in blood. Using the RCA-SOFIA assay, we surprisingly found that P-Tau(231) or P-Tau(217) and total tau elevated several days after TBI. Figure 5A shows the median / IQR scatter plots of the pilot data temporal profiles of serum P-Tau. Figures 5B and 5C show the median / IQR scatter plots of the distinct temporal profiles of serum P-Tau(231) and P-Tau(181). Similar results exist for P-Tau(217). Furthermore, in Figures 5A-5C, the third T-Tau and P-Tau(Thr-231) assays can distinguish serum samples from severe TBI from controls. In these figures, TBI (n=45 each) is distinguishable from controls (n=30). T-Tau and the two species of P-Tau(231, 181) also have distinctly different temporal profiles. Notably, both P-Tau species exhibit a U-shaped curve and a second peak at day 14 after TBI. Both the initial (day 1) and day 14 tau species are higher than controls. Control: P-Tau(231), 0.876 pg / mL; T-Tau, 0.342 pg / mL; P-Tau(181), 3.61 pg / mL (illustrated as blue horizontal bars). Furthermore, Figures 5D and 5E show that the ratios of P-Tau(231) / total tau and P-Tau(181) / total tau, respectively, have very different temporal profiles.It is understood that the ratio between freely circulating P-Tau in serum and plasma from the same subject will provide additional information of the subject's condition.

[0035] Synaptic and neuronal cell body damage are underestimated in TBI. Loss of synaptic connections can be permanent and severely impact brain function. Vesicle-associated membrane protein 5 (VAMP5) belongs to the VAMP-synaptobrevin family of proteins, which also includes VAMP2 (synaptobrevin 2), VAMP3, and VAMP7. These are small (18 kDa) transmembrane proteins involved in docking neurotransmitter-filled synaptic vesicles to presynaptic terminals. Similarly, Wiskott-Aldrich syndrome protein family member 1 (WASF1, also known as WASP family verprolin homologous protein 1 (WAVE1)) and another WASP family member protein, WASF3, are enriched in the brain and localized to the neuronal cell body cytoplasm. WASF1 has been shown to associate with the actin nucleation core Arp2 / 3 complex, promoting actin polymerization in vitro. WASF1 is involved in the transport of vesicle-associated proteins, such as amyloid precursor protein (APP), to the cell surface. Using a neurological panel (192 analytes), significant elevations of both VAMP5 and WASF1 were observed in the subacute phase. Specifically, VAMP5 and WASF1 levels were elevated at 2 weeks and 6 months post-TBI compared with day 1 post-TBI injury and healthy control subjects, as shown in Figures 6A and 6B. Figure 6A shows pilot data from a highly sensitive immunoassay platform, demonstrating that the synaptic marker VAMP5 was elevated in TBI patients at 2 weeks and 6 months post-TBI compared with healthy controls and day 1 post-TBI. *p<0.05, ANOVA of means; n=5–7. Figure 6B shows data from a highly sensitive immunoassay platform, demonstrating that the synaptic marker and vesicle transport marker WASF1 was elevated in TBI patients at 2 weeks and 6 months post-TBI compared with healthy controls and day 1 post-TBI. *p<0.05, ANOVA of means; n=5–7. Levels are expressed in arbitrary units (AU). This suggests that WASF1 and VAMP5 are markers of delayed synaptic and vesicle transport dysfunction.

[0036] Vascular injury and vascular remodeling markers represent another major phenotype and characteristic of brain injury. For example, the neurovasculature (arteries, veins, and microvessels) can be directly or indirectly damaged during the course of brain injury. Therefore, monitoring injury or recovery / remodeling at different time points after injury is clinically important. Figure 7 shows that serum vascular endothelial growth factor (VEGF-A) is elevated above baseline control levels even at days 0–2 after TBI, but does not peak until days 7–10 and 11–20, suggesting delayed vascular involvement and remodeling effects. There are other isoforms of VEGF, including VEGF-D, VEGF-C, and VEGF-B.

[0037] Neuroinflammatory markers represent a major systemic response to changes in the brain environment (Simon, McGeachy et al. 2017). One of the most robust biomarkers is interleukin-6 (IL-6). After TBI, IL-6 cerebrospinal fluid (CSF) and serum levels rise early above baseline control levels, as shown in Figure 8. Figure 8 is a graph of pilot data showing the temporal profile of serum IL-6 elevation in acute and subacute severe TBI, with the horizontal line representing the median level in normal controls. While levels tend to decrease over time in the majority of subjects, serum levels remain elevated in at least half of the subjects surveyed in this pilot study.

[0038] Measurement of brain injury biomarkers using multiple platforms: Figures 9A and 9B show that three conventional assay platforms report similar levels in wet plasma from TBI patients and controls, demonstrating the ability of the present invention to use multiple available assay platforms to perform such biomarker assessments.

[0039] Measurement of brain injury biomarkers comparing dried plasma spot collection samples with wet plasma samples. Remote blood sample collection is desirable and clinically useful to improve access to patient care for patients who have difficulty accessing medical, clinical, or diagnostic laboratories for blood collection. Furthermore, as shown in Figure 1, fingerstick-based blood collection and / or saliva sampling offers advantages over venous blood collection due to its simplicity, minimal invasiveness, and ability to be performed by the patient or caregiver rather than by a medically trained professional. Furthermore, dried plasma samples are stable and can be stored at ambient temperature and transported or shipped to the analysis site. After arrival at the analytical testing site, a rehydration procedure for the dried plasma may be performed. Importantly, Figures 10A and 10B show that two of our brain injury secondary protein biomarker candidates, namely NFL and WASF1, showed strong correlations between rehydrated dried samples and their corresponding wet plasma samples across more than 30 TBI plasma samples. Furthermore, by mixing the four TBI biomarker analyte standards and spiking them into healthy control wet plasma and its corresponding DPS at different dilutions, Figures 11A, 11B, 11C, and 11D show that parallel concentration-response dilution curves exist for all four TBI markers.

[0040] Figure 12 shows that MOG measurement in various blood samples was characterized using a sandwich ELISA assay. Importantly, plasma from 2-week and 6-month TBI patients had approximately 2- to 3-fold higher MOG levels compared to their corresponding control plasma, while pooled serum samples from severe, moderate, and mild TBI patients had up to 30- to 50-fold higher MOG levels compared to their corresponding pooled control serum. The present invention provides the surprising result that MOG measurement in serum (or rehydrated dried serum samples) may be superior to similar measurements in plasma matrix samples. While not intending to be bound by any particular theory, MOG may partition or bind to fatty acids or phospholipids and other lipids in plasma via its two lipid membrane-binding domains, thereby partially evading detection and only being released into the serum compartment upon blood clotting.

[0041] Figure 13 shows that other myelin / WMI markers are also elevated in serum samples from TBI patients taken from days 0-10 and days 12-1 month. This temporal profile also parallels that of MOG, further supporting the idea that myelin markers are elevated in the blood during the acute and persistent chronic phases following brain injury.

[0042] As mentioned above, glial fibrillary acidic protein (GFAP) is one of the most robust markers capable of detecting mild TBI with anatomical lesions (Czeiter, Amrein et al. 2020; Wang, Kobeissy et al. 2021). The temporal profile of GFAP has been extensively characterized, as shown in Figure 14A. The plot of the GFAP ratio versus day 1 in Figure 14B clearly shows a rapid decay of GFAP over time, with elevated GFAP levels persisting throughout the subacute phase after TBI, albeit at low levels, above the baseline level (60 pg / mL) indicated by the arrow in Figure 14A. Figure 15 further demonstrates that elevated GFAP levels in wet plasma are primarily observed at day 1, but not at 2 weeks or 6 months post-injury. In contrast, Figures 16A, 16B, and 16C show that NF-L measured using conventional platforms all had the highest mean levels at 2 weeks compared to healthy control levels, regardless of whether the data was detected in serum or plasma samples. Similarly, pNF-H measured using the Ella platform also showed a greater mean increase at 2 weeks post-injury. Figures 18A and 18B show that GFAP on day 1 was the most powerful in discriminating between moderate-to-mild TBI (mmTBI) and healthy controls, with an area under the receiver operating characteristic (AUC) of 0.8904; however, its diagnostic accuracy decreased to an AUC of 0.7753 (Figures 19A and 19B). In contrast, NF-L remained useful in discriminating between mmTBI and healthy controls, with an AUC of 0.7418, but Figures 21A and 21B show that serum NF-L levels increased to an AUC of 0.8220 on day 14 post-injury. Thus, this is another example of why measuring multiple brain injury biomarkers at multiple time points is advantageous in the present invention.

[0043] Combining measurements of the highly specific neuroactivity biomarker MOG from a subject with values ​​obtained from the highly sensitive, low-selectivity secondary neuroactivity biomarkers described above provides a more specific determination of the subject's neurological symptoms regarding the presence and severity of TBI. TBI severity is defined based on the Glasgow Scale, which spans a spectrum from severe through moderate to mild.

[0044] MOG has been found to be a reliable marker of brain injury in TBI. Specifically, MOG is robustly released in human serum from the acute phase, days 1–10 after injury, to the chronic phase, up to 12 months after injury. Importantly, the MOG biomarker shows higher levels in the chronic phase than in the acute phase, as shown in Figure 4C, suggesting that demyelination continues long after the initial injury.

[0045] Assessment of MOG as a marker of injury severity is achieved by obtaining serial wet plasma and DPS samples from patients experiencing head trauma: after admission (recording time post-injury), 24 hours after admission, twice daily thereafter for up to 14 days, once on day 30, and once at discharge (total wet and dry samples by discharge, n=30). One wet plasma sample and DPS are also collected from healthy control individuals.

[0046] In patients with a favorable prognosis, initial slight elevations in MOG levels return to normal within 3–4 days. However, in patients with a poor prognosis, initial levels tend to be significantly elevated and gradually decline only after day 20. Thus, MOG is a reliable indicator of clinically severe TBI, which is associated with a poor prognosis. Correlated elevations of MOG have not been observed in the absence of severe TBI. In contrast to severe head injury, which is relatively easy to diagnose, mild head injury is typically defined as a clinical condition associated with a Glasgow Coma Scale (GCS) score of 13–15; the lower the score, the more severe the injury. In contrast to prior art attempts to use other biomarkers as sole biomarkers, the inventors have made the surprising discovery that detecting moderately elevated levels of MOG alone or in combination with changes in the levels of secondary biomarkers can synergistically distinguish and diagnose mild and moderate traumatic brain injury, enabling physicians to identify subjects more likely to require intensive treatment. Thus, the first biomarker used herein is illustratively MOG. Again, as mentioned above, MOG released into the circulation may induce an immune response by producing MOG antibodies IgG and IgM. Such an autoimmune response may lead to MOGAD or MOGAD-like disorders or symptoms as an autoimmune attack on the myelin sheath. This again highlights the unique and non-obvious advantages of measuring MOG over time as a biomarker of brain injury. Furthermore, simultaneously measuring the levels of anti-MOG autoantibodies IgG and IgM in serial samples from the same brain injury may also be important for gaining further information about a patient's clinical recovery and autoimmune status.

[0047] UCH-L1 (a neuronal cell body injury marker) has a high degree of specificity for trauma, and when measured in conjunction with MOG, provides more clinically meaningful information about the nature and extent of the injury involved compared to simply measuring MOG alone. The properties of the UCH-L1 biomarker are described in detail in U.S. Patent Nos. 7,291,710 and 7,396,654, the contents of which are incorporated herein by reference.

[0048] It is understood that MOG becomes a synergistic biomarker when used in combination with one or more additional biomarkers. Illustratively, the amount of the second biomarker is determined in the same sample, or in a second biological sample obtained at the same time, before, or after the time point when the first biological sample is obtained. Illustratively, the second biomarker is MOG antibody IgG and IgM, UCH-L1; GFAP, vimentin, pNF-H, MBP, NFL; tau; p-tau; αII-spectrin breakdown products (SBDPs): SBDBP150N, SBDP150, SBDP145, SBDP150i, SBDP120; MAP2; VAMP5; WASF1; CAMKK1; BDNF; or additional combinations thereof. In some embodiments, three biomarkers are detected, including MOG, a second biomarker, and a third biomarker. The third biomarker is illustratively UCH-L1; GFAP; NFL; tau; P-Tau; αII-spectrin breakdown products (SBDP): SBDBP150N, SBDP150, SBDP145, SBDP150i, SBDP120; MAP2; vimentin; VAMP5; WASF1; CAMKK1; BDNF; or additional combinations thereof.When a third biomarker exists, it is understood that it is a biomarker that is different from the first biomarker or the second biomarker.The second biomarker and the third biomarker are not MOG.The difference is different proteins, different cleavage products, different dimerization states, or different modifications (for example, but not limited to, phosphorylation state, glycosylation state, or other known modifications).

[0049] In other embodiments of the invention, the ratio of P-Tau:Tau is understood to be synergistic when used as a detection panel in combination with one or more additional biomarkers. P-Tau181 is a particularly advantageous phosphorylation site of P-Tau. The amount of a second biomarker is determined in the same sample or in a second biological sample obtained at the same time, earlier, or later than the time point when the first biological sample is obtained. The second biomarker illustratively includes MOG, MOG antibody IgG and IgM, GFAP, GFAP degradation products (BDPS); interleukins, pNF-H, MBP, NF-L; MAP2; or a combination thereof. In some embodiments, the combination of second biomarkers includes GFAP and at least two of MOG, MOG antibody IgG and IgM, IL-6, IL-15, pNF-H, MBP, NF-L, MAP2, or an additional combination thereof. In yet other embodiments, the second combination of biomarkers comprises GFAP, or BDPS, IL-6, IL-15, and NF-L.

[0050] The recognition of the above combination as a novel and unexpectedly powerful biomarker panel for neurological injuries such as TBI or stroke, MS or Alexander disease highlights the importance of the multiple associations identified by the inventors between these biomarkers, as exemplified in Table 1.

[0051] JPEG2025541672000002.jpg237166JPEG2025541672000003.jpg105166

[0052] As an illustration of the utility of biomarkers that may complement MOG, Figure 22 shows elevated blood levels of tubulin folding cofactor B (TBCB), which is enriched in the brain, at 2 weeks and 6 months. Figures 23-26 show that the synaptic markers WASF1, WAF3, and VAMP5, and the postsynaptic density marker CAMKK1, respectively, peak in blood at 2 weeks post-injury and slightly decline but remain elevated at 6 months. Figure 27 shows that mean serum indulin-1 levels are most significantly elevated at 2 weeks post-injury compared to levels at day 1 post-TBI or normal controls. However, pooled plasma day 1 TBI samples are approximately three-fold higher than control plasma levels. The temporal profiles of these biomarkers, which may complement MOG, were quantified and revealed by a conventional platform screen of over 400 proteins.

[0053] Figures 28, 29, 30, 31, 32, and 33 further show the temporal profiles of other potentially complementary biomarkers quantified by conventional platforms for over 400 proteins. This set of markers includes inositol monophosphatase 1 (IMPA1) (Figure 28), zinc finger and BTB domain-containing protein 16 (ZBTB16) (Figure 29), peroxiredoxin 6 (PRDX6) (Figure 30), nuclear factor of activated T cells 1 (NFATC1) (Figure 31), N-α-acetyltransferase 10 (NAA10) (Figure 32), and growth inhibitory factor family member 1 (ING1) (Figure 33), all of which show robust mean elevations at 2 weeks and 6 months post-TBI, respectively.

[0054] The recognition of the above combinations as novel and unexpectedly powerful biomarkers for neurological injury such as TBI or stroke highlights the importance of the multiple associations identified by the inventors between these biomarkers, as illustrated in Table 1.

[0055] JPEG2025541672000004.jpg229166 JPEG2025541672000005.jpg239166JPEG2025541672000006.jpg201166

[0056] In some embodiments of the invention, the first biomarker is MOG and the second biomarker is GFAP.

[0057] In another embodiment of the invention, glial fibrillary acidic protein (GFAP) is detected in biological samples along with UCH-L1 and MOG. GFAP belongs to the cytoskeletal protein family and is the major 8-9 nanometer intermediate filament in glial cells, such as mature astrocytes, in the central nervous system (CNS). GFAP is a monomeric molecule with a molecular weight between 40 and 53 kDa and an isoelectric point between 5.7 and 5.8. GFAP is a highly brain-specific protein and is not found outside the CNS under normal physiological conditions. GFAP is released in response to neurological insults and is subsequently released into the blood and CSF. After CNS injury, whether as a result of trauma, disease, genetic disorder, or chemical insult, astrocytes become reactive in a manner known as astrogliosis or gliosis, which is characterized by the rapid synthesis of GFAP. It is understood that GFAP may be detected as a monomer or as a multimer, such as a dimer.

[0058] Any subject that expresses the biomarker of the present invention can be used herein.Exemplary subjects include dogs, cats, horses, cows, pigs, sheep, goats, chickens, non-human primates, humans, rats, mice, and cells.The subjects that can benefit from the present invention are typically those suspected of having or at risk of developing abnormal neurological symptoms, such as those that have suffered brain damage caused by traumatic insults (e.g., gunshot wounds, car accidents, sports accidents, shaken baby syndrome) and ischemic events (e.g., stroke, cerebral hemorrhage, cardiac arrest).

[0059] The neuroactive biomarker analysis of the present invention of MOG and one or more additional biomarkers can illustratively be used to detect and diagnose all degrees of TBI, from severe to mild, due to the specificity of the second or third biomarker and the higher sensitivity for MOG.

[0060] In vivo or in vitro screening or assay protocols illustratively involve the measurement of neuroactive biomarkers in a biological sample obtained from a subject.

[0061] Studies to determine or monitor the levels of neuroactive biomarker levels of MOG and one or more additional biomarkers may be combined with behavioral or movement disorder analyses, such as: motor coordination tests, including, for example, the rotarod test, beam walk test, gait analysis, grid test, hanging test, and string test; sedation tests, including those that detect spontaneous motor activity in an open field test; tests for sensitivity to allodynia—the cold water bath test, the hot plate test at 38°C, and the von Frey test; tests for sensitivity to hyperalgesia—the hot plate test at 52°C, and the Randall-Sellito test; and EMG assessments, such as sensory and motor nerve conduction, compound muscle action potential (CMAP), and H-wave reflex.

[0062] An exemplary method for detecting the presence or absence of MOG and a second biomarker in one or more biological samples includes obtaining a biological sample from a subject, such as a human, contacting the biological sample with a reagent (e.g., comprising an antibody or nucleic acid probe) capable of detecting the marker to be analyzed, and, optionally after washing, analyzing binding of the reagent. Those samples with specifically bound reagent (or reduced levels of reagent in a competitive assay) express the marker to be analyzed.

[0063] To provide a correlation between neurological symptoms and the measured amounts of MOG and one or more additional biomarkers, a CSF or serum sample is collected from the subject, and the sample is subjected to measurement of MOG and one or more additional biomarkers. The subjects have various neurological symptoms. The detected biomarker levels can then be correlated with CT scan results and GCS scores. Based on these results, the assay of the present invention is developed and validated, for example, by the method of Lee et al., Pharmacological Research 23:312-328, 2006. It is understood that the biomarker levels can be obtained from one or more of a wide variety of biological samples. The neuroactive biomarker levels can be obtained not only from biological samples such as CSF and serum, but also easily from blood, plasma, saliva, urine, and solid tissue biopsies. While CSF is a commonly used sampling fluid due to its direct contact with the nervous system, it will be appreciated that other biological fluids may have advantages in sampling for the same or other purposes, and thus the determination of a neurological condition in accordance with the present invention may be performed as part of a battery of tests performed on a single biological sample such as blood, plasma, serum, saliva, or urine.

[0064] Biological samples are obtained from subjects by conventional techniques. For example, CSF is obtained by lumbar puncture. Blood is obtained by venipuncture, while plasma and serum are obtained by fractionating whole blood according to known methods. Surgical techniques for obtaining solid tissue samples are well known in the art. For example, methods for obtaining nervous system tissue samples are described in standard neurosurgery textbooks, such as Atlas of Neurosurgery: Basic Approaches to Cranial and Vascular Procedures, by F. Meyer, Churchill Livingstone, 1999; Stereotactic and Image Directed Surgery of Brain Tumors, 1st ed., by David GT Thomas, WB Saunders Co., 1993; and Cranial Microsurgery: Approaches and Techniques, by LN Sekhar and E. De Oliveira, 1st ed., Thieme Medical Publishing, 1999, the contents of each of which are incorporated herein by reference. Methods for obtaining and analyzing brain tissue are also described in Belay et al., Arch. Neurol. 58: 1673-1678 (2001); and Seijo et al., J. Clin. Microbiol. 38: 3892-3895 (2000), the contents of which are incorporated herein by reference.

[0065] The methods provided herein can be used to detect MOG and one or more additional biomarkers in a biological sample in vitro and in vivo. The expression levels of MOG and one or more additional biomarkers in a sample can be compared to appropriate controls, such as a first sample known to express a detectable level of the marker being analyzed (positive control) and / or a second sample known not to express a detectable level of the marker being analyzed (negative control). For example, in vitro techniques for detecting markers include enzyme-linked immunosorbent assay (ELISA), Western blot, immunoprecipitation, and immunofluorescence. In vivo techniques for detecting markers illustratively involve introducing a labeled reagent that specifically binds to the marker into a biological sample or test subject. For example, the reagent can be labeled with a radioactive marker, and its presence and location within the biological sample or test subject can be detected by standard imaging techniques.

[0066] Any suitable molecule that specifically binds to MOG or one or more additional biomarkers, or any suitable molecule that specifically binds to one or more other neuroactive biomarkers, functions in the present invention to achieve a synergistic assay. An exemplary reagent for detecting and quantifying a biomarker is an antibody capable of binding to the biomarker being analyzed. The antibody may be conjugated to a detectable label. Such antibodies may be polyclonal or monoclonal. Complete antibodies, fragments thereof (e.g., Fab or F(ab')2), or engineered variants thereof (e.g., sFv) may also be used. Such antibodies may belong to any immunoglobulin class, including IgG, IgM, IgE, IgA, IgD, and any subclass thereof. Other examples of binding reagents for MOG are single-stranded DNA or RNA nucleic acids.

[0067] Antibody-based assays are typically used to analyze biological samples for the presence of biomarkers. A suitable Western blot method may be used. For more rapid analysis (which may be important in emergency medical situations), immunosorbent assays (e.g., ELISA and RIA) and immunoprecipitation assays may be used. For example, a biological sample or a portion thereof is immobilized on a substrate (e.g., a membrane made of nitrocellulose or PVDF); or on a rigid substrate made of polystyrene or other plastic polymers (e.g., a microtiter plate). The substrate is contacted with an antibody that specifically binds to a second or additional biomarker and a second antibody specific to MOG under conditions that allow the antibodies to bind to the biomarker being analyzed. After washing, the presence of the antibody on the substrate indicates that the sample contained the marker being evaluated. If the antibody is directly or indirectly (via a hapten) conjugated to a detectable label, such as an enzyme, fluorescent dye, or radioisotope, the presence of the label may be detected by examining the substrate for the detectable label. Alternatively, a detectably labeled secondary antibody that binds to the marker-specific antibody is added to the substrate. The presence of detectable label on the substrate after washing indicates that the sample contained the marker.

[0068] Numerous permutations of these basic immunoassays also work in the present invention. These involve immobilizing a sample on a substrate, which contains a biomarker-specific antibody, and contacting the substrate with a biomarker conjugated with a detectable label under conditions that allow the antibody to bind to the labeled marker. The substrate is then contacted with the sample under conditions that allow the marker to be analyzed to bind to the antibody. A decrease in the amount of detectable label on the substrate after washing indicates that the sample contained the marker. Other biomarker detection methods that work herein include mass spectrometry and lateral flow immunoassays.

[0069] It is understood that measuring mRNA in a sample according to the present invention can be used as a substitute for detecting the level of the corresponding biomarker protein in the sample. Accordingly, any biomarker or biomarker panel described herein can also be detected by detecting the appropriate RNA. As an example, one or more nucleic acid probes specific for the corresponding biomarker(s) can be reacted with a histological or cytological sample and serve as nucleic acid targets in a nucleic acid amplification method. Suitable nucleic acid amplification methods include, for example, PCR, q-β replicase, rolling circle amplification, strand displacement amplification (SDA), helicase-dependent amplification, loop-mediated isothermal amplification (LAMP), ligase chain reaction, and restriction and circularization-aided rolling circle amplification. Non-amplification-based methods for biomarkers can also be used, including DNA or RNA nucleic acids for protein biomarker targets, as described below.

[0070] Antibodies are preferred for use in the present invention because they have been extensively characterized, but other suitable reagents (e.g., peptides, nucleic acid probes, or small organic compounds) that specifically bind to biomarkers can also be used instead of antibodies in the above-mentioned immunoassays. Aptamers are nucleic acid-based molecules that bind to specific ligands, including protein biomarkers. Methods for generating aptamers with specific binding specificities are known and are described in detail in U.S. Patent Nos. 5,475,096; 5,670,637; 5,696,249; 5,270,163; 5,707,796; 5,595,877; 5,660,985; 5,567,588; 5,683,867; 5,637,459; and 6,011,020, the contents of each of which are incorporated herein by reference.

[0071] Numerous detectable labels function in diagnostic assays for biomarker expression and are known in the art. Labels and labeling kits are commercially available, for example, from Invitrogen Corp. (Carlsbad, CA). Reagents used in methods for detecting neuroactive biomarkers may be conjugated to a detectable label (e.g., an enzyme such as horseradish peroxidase). A horseradish peroxidase-labeled reagent can be detected by adding an appropriate substrate that produces a color change in the presence of horseradish peroxidase. Several other detectable labels are known that can be used. Common examples include alkaline phosphatase, horseradish peroxidase, fluorescent molecules, luminescent molecules, colloidal gold, magnetic particles, biotin, radioisotopes, and other enzymes.

[0072] The present invention utilizes a step of correlating the presence or amount of MOG and one or more additional biomarkers in a biological sample with the severity and / or type of TBI. For example, the amount of UCH-L1 and MOG in a biological sample is associated with neurological symptoms related to traumatic brain injury, for example, by methods detailed in the Examples. The results of synergistically measuring MOG and one or more additional biomarkers using the assay of the present invention can help physicians, veterinarians, or scientists determine the type and severity of injury, thereby indicating which types of cells have been damaged. These results are consistent with those of CT scans and GCS, but are quantitative, obtained more quickly, and at a much lower cost.

[0073] The assay or method may include comparing the amount of MOG and one or more additional biomarkers with their respective normal levels to determine the subject's neurological condition. The method of the present invention provides a test that helps physicians determine the appropriate treatment that will provide optimal benefit to the subject.

[0074] Assays for analyzing cell damage in a subject are also provided. The assays include: (a) a substrate for holding a sample isolated from a subject suspected of having damaged nerve cells, the sample being a fluid that was in contact with the subject's nervous system before being isolated from the subject; (b) a MOG-specific binding reagent; (c) a second biomarker-specific binding reagent; and, optionally, (d) printed instructions for reacting the second biomarker-specific reagent with a biological sample or a portion of the biological sample to detect the presence or amount of the second biomarker, and reacting the MOG-specific reagent with a biological sample or a portion of the biological sample to detect the presence or amount of MOG and the second biomarker in the biological sample. The assays of the present invention can be used to detect neurological conditions for financial reward. In some embodiments, a third biomarker-specific reagent is included, which is specific for a third biomarker different from the second biomarker and is not MOG.

[0075] The baseline level of a biomarker is the level obtained in a target biological sample from a desired subject species without known neurological symptoms. These levels do not need to be expressed as an exact concentration; instead, they may be known from parallel control experiments and expressed in terms of fluorescence units, density units, etc. Typically, in the absence of neurological symptoms, one or more biomarkers are present in only trace amounts in a biological sample. However, UCH-L1 is a highly abundant protein in neurons. Determining the baseline level of a biomarker (e.g., including UCH-L1 or MOG protein and RNA in neurons, plasma, or CSF of a particular species) is within the skill of a person skilled in the art. Similarly, determining the baseline concentration of other biomarkers is within the skill of a person skilled in the art. The baseline level is illustratively the amount or activity of a biomarker in a sample from one or more subjects not suspected of having neurological symptoms.

[0076] The relative level of MOG or one or more additional biomarkers can be expressed as a ratio to control, baseline, or known elevated biomarker level.As used herein, " ratio " refers to a positive ratio when the level of target biomarker is greater than that of the target in the second sample, or compared with the known or known baseline level of the same target.A negative ratio refers to a situation when the level of target is lower than that of the target in the second sample, or compared with the known or known baseline level of the same target.A neutral ratio refers to a situation when no change is observed in target biomarker.

[0077] Neurological symptoms may result in or cause injury. As used herein, "injury" refers to a change in the integrity, activity, level, robustness, state, or other change of a cell or molecule that is traceable to an event. Injury illustratively includes physical, mechanical, chemical, biological, functional, infectious, or other modulators of cellular or molecular properties. Injury may result from an event. An event illustratively is a physical trauma, such as a blow (e.g., a percussive injury), or a biological abnormality, such as a stroke resulting from a blood vessel blockage (ischemic). Thus, the term "traumatic brain injury" (TBI) refers to damage to the brain resulting from an event, such as a blow or other impact, or a blood vessel blockage.

[0078] The injury may be a physical event such as a percussive impact. The impact may be, for example, a percussive injury caused by a blow to the head, body, or a combination thereof, and the cranial structure may remain intact or may be damaged as a result. Experimentally, several impact methods have been used, illustratively including controlled cortical impact (CCI) with a depression depth of 1.6 mm, which corresponds to severe TBI in humans. This method is described in detail in Cox, CD, et al., J Neurotrauma, 2008; 25(11):1355-65, the contents of which are incorporated herein by reference. It is understood that other experimental methods of producing percussive trauma may also be used.

[0079] Damage may also result from stroke. Ischemic stroke may be modeled by middle cerebral artery occlusion (MCAO) in rodents. For example, UCH-L1 protein levels are elevated after mild MCAO and further elevated after severe MCAO injury. Mild MCAO injury may result in a transient increase in biomarker levels within 2 hours, returning to control levels within 24 hours. In contrast, severe MCAO injury may result in an increase in biomarker levels within 2 hours after injury, which may be much more persistent and show statistically significant levels for more than 72 hours.

[0080] A step of correlating the presence or amount of biomarkers in a biological sample with the severity and / or type of neuronal (or other biomarker-expressing) toxicity may be provided. The amount of biomarker(s) in a biological sample is directly related to the severity of neurological symptoms, with more severe injury damaging a greater number of neurons, resulting in greater accumulation of biomarker(s) in the biological sample (e.g., CSF; serum). Illustratively, elevated levels of UCH-L1, GFAP, or both, plus moderately elevated levels of MOG, indicate severe TBI. Elevated levels of UCH-L1, GFAP, or both, plus the absence of a significant increase in MOG, indicate moderate TBI. Absence of a post-impact increase in MOG and any one of UCH-L1, GFAP, or both, indicates mild TBI. The level or kinetic range of biomarkers present in a biological sample may also distinguish between mild and more severe injuries. In one example, severe MCAO (2 hours) results in elevated UCH-L1 in both CSF and serum compared to mild injury (30 minutes), while in both cases, UCH-L1 levels are higher than in uninjured subjects. Furthermore, the persistence or dynamic range of markers in biological samples indicates the severity of neurotoxicity, with greater toxicity resulting in increased persistence of UCH-L1 or MOG biomarkers in subjects, as measured in biological samples taken at multiple time points after injury.

[0081] The present invention may involve the administration of one or more compounds, such as therapeutic agents, or molecules being evaluated for therapeutic or other potential, which may alter one or more characteristics of a target biomarker, such as its concentration in a biological sample. Therapeutic agents may function as agonists or antagonists of the target biomarker or an upstream effector of the biomarker. Therapeutic agents may also affect downstream functions of the biomarker. For example, acetylcholine (Ach) is involved in pathological neuronal excitation, and TBI-induced activation of muscarinic cholinergic receptors may contribute to excitotoxicity processes. Thus, biomarkers may include the level or activity of Ach or muscarinic receptors. Optionally, usable biomarkers may be molecules, proteins, nucleic acids, or other molecules affected by the activity of muscarinic receptor(s). Thus, therapeutic agents usable in the present invention illustratively include those that modulate various aspects of muscarinic cholinergic receptor activation.

[0082] Particular muscarinic receptors that can be used as therapeutic targets or modulators of therapeutic targets include the M1, M2, M3, M4, and M5 muscarinic receptors.

[0083] The suitability of the muscarinic cholinergic receptor pathway for the detection and treatment of TBI is based on studies demonstrating elevated levels of ACh in the cerebrospinal fluid (CSF) of the brain after experimental TBI (Gorman et al., 1989; Lyeth et al., 1993a), ischemia (Kumagae and Matsui, 1991), and the detrimental effects of high levels of muscarinic cholinergic receptor activation through the application of cholinergic agonists (Olney et al., 1983; Turski et al., 1983). Furthermore, acute administration of muscarinic antagonists improves behavioral recovery after experimental TBI (Lyeth et al., 1988a; Lyeth et al., 1988b; Lyeth and Hayes, 1992; Lyeth et al., 1993b; Robinson et al., 1990). Thus, chemical or biological agents, such as compounds that bind to or alter the properties of muscarinic cholinergic receptors, may be screened for neurotoxicity in cells or tissues, such as during target optimization in preclinical drug discovery.

[0084] The compound, illustratively a therapeutic compound, chemical compound, or biological compound, illustratively any molecule, family, extract, solution, drug, prodrug, or other compound that can be used to alter and optionally improve the therapeutic outcome of a subject at risk of or undergoing neurotoxic insult. The therapeutic compound may be a muscarinic cholinergic receptor modulator (e.g., an agonist or antagonist), an amphetamine. The agonist or antagonist may be direct or indirect. An indirect agonist or antagonist may be a molecule that degrades or synthesizes acetylcholine or other muscarinic receptor-related molecules, illustratively molecules currently used to treat Alzheimer's disease. Cholinergic agonists or similar molecules can be used herein. An exemplary list of therapeutic compounds that can be used herein includes: dicyclomine, scopolamine, miramelin, N-methyl-4-piperidinyl benzilate, NMP, pilocarpine, pirenzepine, acetylcholine, methacholine, carbachol, bethanechol, muscarine, oxotremorine M, oxotremorine, thapsigargin, calcium channel blockers or agonists, nicotine, xanomeline, BuTAC, clozapine, olanzapine, cevimeline, aceclidine, arecoline, tolterodine, rociverine, IQNP, indole alkaloids, himbacine, cyclostretamine, derivatives thereof, prodrugs thereof, and combinations thereof. The therapeutic compound may also be a molecule that can be used to alter the level or activity of calpain or caspase. Such molecules and their administration are known in the art. A compound is understood to be any molecule, including molecules under 700 daltons, peptides, proteins, nucleic acids, or other organic or inorganic molecules, that is contacted with a subject or portion thereof.

[0085] The compound may be any molecule, protein, nucleic acid, or other compound that alters the level of a neuroactive biomarker in a subject. The compound may be an experimental drug being evaluated in preclinical or clinical trials, or a compound whose properties or actions are being elucidated. The compound may be kainic acid, MPTP, amphetamine, cisplatin or other chemotherapeutic compounds, NMDA receptor antagonists, any other compound described herein, their prodrugs, their racemates, their isomers, or combinations thereof. Examples of amphetamines include ephedrine, amphetamine aspartate monohydrate, amphetamine sulfate, dextroamphetamine (including dextroamphetamine saccharide and dextroamphetamine sulfate), methamphetamine, methylphenidate, levoamphetamine, their racemates, their isomers, their derivatives, or combinations thereof. Exemplary NMDA receptor antagonists include those listed in Table 3, their racemates, their isomers, their derivatives, or combinations thereof:

[0086] JPEG2025541672000007.jpg108166

[0087] As used herein, the term "administering" refers to delivering a compound to a subject. A compound is a chemical or biological agent administered with the intention of alleviating one or more symptoms of a condition or treating a condition. The therapeutic compound is administered by a route determined by one of ordinary skill in the art to be appropriate for a particular subject. For example, the therapeutic compound may be administered orally, parenterally (e.g., intravenously, by intramuscular injection, by intraperitoneal injection, intratumorally, by inhalation, or transdermally). The exact amount of therapeutic compound required will vary from subject to subject and will depend on the subject's age, weight, and general condition, the severity of the neurological condition being treated, the particular therapeutic compound used, its mode of administration, and the like. The appropriate amount can be determined by one of ordinary skill in the art using only routine experimentation without undue experimentation, following the teachings herein or knowledge in the art.

[0088] Also provided is a method for detecting or identifying the severity of traumatic brain injury (TBI). Traumatic brain injury is illustratively mild TBI, moderate TBI, or severe TBI. As used herein, mild TBI is defined as an individual with a CGS score of 12-15, or an individual with any of the characteristics described in the National Center for Injury Prevention and Control, Report to Congress on Mild Traumatic Brain Injury in the United States: Steps to Prevent a Serious Public Health Problem. Atlanta, GA: Centers for Disease Control and Prevention; 2003 (incorporated herein by reference). Moderate TBI is defined as an individual with a GCS score of 9-11. Severe TBI is defined as an individual with a GCS score of less than 9, abnormal CT scan findings, or symptoms including loss of consciousness for more than 30 minutes, post-traumatic amnesia lasting more than 24 hours, and perforating brain injury.

[0089] A method for detecting or identifying mild or moderate TBI illustratively includes obtaining a sample from a subject at a first time point and measuring the amount of MOG and a second biomarker in the sample, where elevated levels of MOG and the second biomarker indicate the presence of traumatic brain injury. The method may further include correlating the amount of MOG and the second biomarker with a normal CT scan or GCS score. A positive correlation for mild TBI is observed when the GCS score is 12 or higher and neither MOG nor the second biomarker is elevated. A positive correlation for moderate TBI is observed when the GCS score is 9-11 and the second biomarker is elevated, with the moderate elevation of MOG returning to a low level within 24 hours of injury. Alternatively, or in addition, a positive correlation for moderate TBI is observed when the CT scan result is abnormal and the second biomarker level is elevated. An abnormal CT scan result illustratively indicates the presence of a lesion. A non-abnormal or normal CT scan result indicates the absence of a lesion.

[0090] The levels of MOG and one or more additional biomarkers may be measured in samples obtained within 24 hours of injury. Illustratively, UCH-L1 and MOG levels are measured in samples obtained from 0 to 24 hours after injury, including all time points in between. In some embodiments, a second sample is obtained 24 hours or more after injury, and the amount of MOG alone or in combination with the additional biomarkers is measured.

[0091] Various aspects of the present invention are illustrated by the following non-limiting examples. The examples are for illustrative purposes only and do not limit any practice of the present invention. It will be understood that changes and modifications can be made without departing from the spirit and scope of the present invention. While the examples are generally directed to the analysis of mammalian tissue, specifically rat tissue, those skilled in the art will recognize that similar techniques, and others known in the art, will readily adapt the examples to other mammals, such as humans. Reagents exemplified herein generally have cross-reactivity between mammalian species, or alternative reagents with similar properties are commercially available, and those skilled in the art will readily understand where such reagents can be obtained. [Example]

[0092] [Example 1] Materials for biomarker analysis: Tris-buffered saline (TBST) containing sodium bicarbonate, blocking buffer (Startingblock T20-TBS), and Tween 20; phosphate-buffered saline (PBS); Tween 20; Ultra TMB ELISA; and Nunc maxisorp ELISA plates. Monoclonal and polyclonal UCH-L1 antibodies were produced in-house or obtained from Santa Cruz Biotechnology (Santa Cruz, CA). Antibodies against MOG were available from Santa Cruz Biotechnology (Santa Cruz, CA). Antibodies against GFAP were produced in-house or obtained from Santa Cruz Biotechnology (Santa Cruz, CA). Antibodies for multiple subtypes were labeled with antibodies from Invitrogen, Corp. (Carlsbad, CA). Protein concentrations in biological samples are determined using the bicinchoninic acid microprotein assay (Pierce Inc., Rockford, IL, USA) with albumin standards. All other necessary reagents and materials are known to those skilled in the art and are readily ascertainable.

[0093] Biomarker-specific rabbit polyclonal and monoclonal antibodies are produced in the laboratory or are available from commercial sources known to those skilled in the art. To determine the reactive specificity of the antibodies, tissue panels are probed by Western blot.

[0094] Indirect ELISA is used to immobilize recombinant biomarker proteins on ELISA plates to determine the optimal concentration of antibody used in the assay. This assay determines the appropriate concentration of biomarker-specific binding reagents to use in the assay. Microplate wells are coated with rabbit polyclonal anti-human biomarker antibodies. After determining the concentration of rabbit anti-human biomarker antibodies to obtain a maximum signal, the maximum detection limit of the indirect ELISA for each antibody is determined. Appropriately diluted samples are incubated with rabbit polyclonal anti-human biomarker antibodies (capture antibodies) for 2 hours and then washed. Next, biotin-labeled monoclonal anti-human biomarker antibodies are added and incubated with the captured biomarkers. After extensive washing, streptavidin-horseradish peroxidase conjugate is added. After a 1-hour incubation and a final wash step, the remaining conjugate is reacted with hydrogen peroxide-tetramethylbenzidine substrate. The reaction is stopped by the addition of an acidic solution, and the absorbance of the resulting yellow reaction product is measured at 450 nanometers. The absorbance is proportional to the concentration of the biomarker. A standard curve is constructed using calibrator samples by plotting absorbance values ​​as a function of biomarker concentration, and the concentrations of unknown samples are determined using the standard curve.

[0095] ELISA is used to detect and quantify UCH-L1 in biological samples from rats after CCI more quickly and easily. For the UCH-L1 sandwich ELISA (swELISA), a 96-well plate is coated with 100 μl / well of capture antibody (500 ng / well of purified rabbit anti-UCH-L1, prepared in-house using conventional techniques) in 0.1 M sodium bicarbonate (pH 9.2). The plate is incubated overnight at 4°C, the contents are removed, and 300 μl / well of blocking buffer (Startingblock T20-TBS) is added. The plate is then incubated for 30 minutes at room temperature with gentle shaking. Subsequently, antigen standards (recombinant UCH-L1) for the standard curve are added (0.05–50 ng / well) or samples in sample diluent (3–10 μl of CSF) are added (total volume 100 μl / well). Plates are incubated at room temperature for 2 hours and then washed using an automated plate washer (5 x 300 μl / well with wash buffer, TBST). The detection antibody, conjugated mouse anti-UCH-L1-HRP (homemade, 50 μg / ml) in blocking buffer, is then added to the wells at 100 μl / well and incubated at room temperature for 1.5 hours, followed by washing. If amplification is required, biotinyl tyramide solution (Perkin Elmer Elast Amplification Kit) is added for 15 minutes at room temperature, followed by washing. This is followed by 100 μl / well of streptavidin-HRP (1:500) in PBS containing 0.02% Tween-20 and 1% BSA for 30 minutes, followed by washing. Finally, the wells are developed with 100 μl / well of TMB substrate solution (Ultra-TMB ELISA, Pierce, #34028). The incubation time is 5-30 minutes. The signal is read at 652 nm using a 96-well spectrophotometer (Molecular Device Spectramax 190). Similar assays are performed using primary antibodies against S-100β and UCH-L1.

[0096] To specifically detect dimers of MOG, UCH-L1, or GFAP, an ELISA assay was used, in which the capture and detection antibodies target the same epitope that is not involved in biomarker dimerization. The technique used was similar to that described in El-Agnaf OMA, et al., The FASEB Journal, 2006; 20:419-425, the contents of which are incorporated herein by reference. The above assay for UCH-L1 was repeated using a 96-well plate coated with MOG antibody from Santa Cruz Biotechnology and blocked with blocking buffer (Startingblock T20-TBS) as described above. Samples (100 μL / well) were incubated with the plate at room temperature for 2 hours, and then washed using an automated plate washer (5 × 300 μL / well with wash buffer, TBST). The detection antibody, the same as the primary antibody but conjugated with HRP (homemade, 50 μg / ml), was added to the wells at 100 μL / well and incubated at room temperature for 1.5 hours, followed by washing. The wells were developed with 100 μL / well of TMB substrate solution (Ultra-TMB ELISA, Pierce, #34028), with incubation times ranging from 5 to 30 minutes. The signal was read at 652 nm using a 96-well spectrophotometer (Molecular Device Spectramax 190). This assay allows for the specific detection of dimers. While the assay was running, the same samples were subjected to size-exclusion chromatography according to known methods, and fractions were assayed by single-antibody ELISA. A positive result in the high-molecular-weight protein-containing fractions indicates biomarker dimers.

[0097] [Example 2] DPS sampling and a conventional immunoassay platform are combined with a proprietary panel of evidence-based, blood-based, temporal TBI protein biomarkers, including the astrocyte biomarker GFAP; the neural biomarkers neurofilament light protein (NF-L), phosphorylated neurofilament heavy chain (pNF-H), and phosphorylated microtubule-associated protein tau (p-Tau); the novel demyelination biomarker myelin oligodendrocyte glycoprotein (MOG); and cytokine measures of immunosuppression / inflammation (e.g., IL-6). Spiked plasma / serum samples are generated using recombinant proteins as TBI biomarkers, and pooled control / TBI samples from both wet plasma / serum samples and mock DPS samples (created by pipetting wet samples onto the plasma collection disk of the DPS sampling device) are tested. This will: (i) establish a certified gold standard for custom panels and positive / negative sample controls; (ii) standardize pre-analytical conditions, such as the effect of different detergent concentrations on the release of TBI biomarkers that bind to hydrophobic proteins (e.g., albumin) for maximum recovery from DPS samples from CP; (iii) determine LLOQ, linear dynamic range, accuracy, precision, and the effect of matrix interference (e.g., EDTA); and (iv) establish analytical equivalence between preserved wet samples from historical TBI cohorts and their mock DPS samples from moderate-to-severe TBI patients (collected up to daily from intensive care units (ICUs), emergency departments (EMs), and hospitalized patients). To generate longitudinal mock DPS samples, longitudinal serum samples from CENTER-TBI at 5–10 time points post-injury will be analyzed as a training set, and additional serum samples at 4, 24, and 48 hours post-injury from the ProTECTIII / BioProTECT study will be analyzed as a test set. Here, samples from patients without extracranial injury are preferentially selected for enrichment. Longitudinal plasma samples from the University of Pittsburgh are used as an additional test / training set.GFAP measurement by the iSTAT immunoassay platform will be used as a benchmark and predicate for future regulatory approval. A third immunoassay platform will be used to confirm the "ground truth" levels of the biomarker in these samples.

[0098] [Example 3] Remarkable preliminary data on the SPS of the present invention have been generated using a prototype DPS sampling device (Capitainer-P or CP) from Capitainer and a highly sensitive immunoassay platform from a conventional platform, which, combined with longitudinal data from conventional "wet" TBI specimens and immunoassay platforms, provide strong evidence supporting the success of the DPS of the present invention for blood testing of TBI biomarkers.

[0099] First, data on the preliminary validation of analytical equivalence between the high-sensitivity immunoassay platform and other immunoassay platforms are presented in Figures 9A and 9B. Briefly, 44 plasma samples from TBI subjects and healthy controls were analyzed in parallel on these three immunoassay platforms for biomarkers (e.g., NFL) selected from the panel of the present invention. As shown in Figure 9A, a very strong correlation (R2 = 0.861) was observed between the NFL data from the wet platform and the NFL data from the wet Ella. As shown in Figure 9B, a good correlation (R2 = 0.656) was observed between the NFL data from the wet platform and the NFL data from the wet Third. Figure 9A is a graph showing the preliminary validation of analytical equivalence between the high-sensitivity immunoassay platform and other immunoassay platforms using NFL measurements from de-identified, stored wet plasma samples from a full spectrum of TBI subjects (day 1 to 6 months post-injury). The NFL data from the wet platform showed a very strong correlation (R2 = 0.861) with the NFL data from the other platforms. Figure 9B is a graph showing preliminary validation of analytical equivalence between the high-sensitivity immunoassay platform and other immunoassay platforms using NFL measurements of de-identified, stored wet plasma samples from a full spectrum of TBI subjects (day 1 to 6 months post-injury). The platform's NFL data showed good correlation (R2 = 0.656) with a third NFL data.

[0100] Second, preliminary validation of analytical equivalence between wet and DPS sampling is shown in Figures 10A and 10B. Briefly, 44 plasma samples from TBI subjects and healthy controls were dropped onto the collection disk of a DPS sampling device, dried at room temperature, and stored in a desiccator for 24 hours, mimicking actual sampling and storage conditions. DPS proteins were then recovered from the collection disk using an elution buffer, and selected biomarkers from our panel (e.g., NFL and WASF1) were assayed in parallel with their corresponding wet plasma samples. In Figure 10A, a very strong correlation (R2 = 0.9531) was observed between the NFL data from the DPS platform and the wet platform, and a strong correlation (R2 = 0.861) was also observed between the WASF1 data from the DPS platform and the wet platform (Figure 10B). Figure 10A is a graph showing preliminary validation of analytical equivalence of wet vs. DPS sampling for measurement of NFL and WASF1 in de-identified and stored plasma specimens from a full spectrum of TBI subjects (day 1 to 6 months post-injury) using a platform-sensitive immunoassay platform. Figure 10B is a graph showing preliminary validation of analytical equivalence of wet vs. DPS sampling for measurement of WASF1 in de-identified and stored plasma specimens from a full spectrum of TBI subjects (day 1 to 6 months post-injury) using a platform-sensitive immunoassay platform.

[0101] Third, preliminary validation of the analytical equivalence of wet versus DPS sampling for the recovery of TBI biomarkers is shown in Figures 11A-11D. Figure 11A is a graph showing preliminary validation of the analytical equivalence of wet versus DPS sampling for the recovery of TBI biomarkers using a five-order serial dilution of the recombinant protein biomarker GFAP in a spiked recovery study in pooled plasma from 10 healthy controls aged 40-45 years. Figure 11B is a graph showing preliminary validation of the analytical equivalence of wet versus DPS sampling for the recovery of TBI biomarkers using a five-order serial dilution of the recombinant protein biomarker NFL in a spiked recovery study in pooled plasma from 10 healthy controls aged 40-45 years. Figure 11C is a graph showing preliminary validation of the analytical equivalence of wet versus DPS sampling for the recovery of TBI biomarkers using a five-order serial dilution of the recombinant protein biomarker tau in a spiked recovery study in pooled plasma from 10 healthy controls aged 40-45 years. Figure 11D is a graph showing preliminary validation of analytical equivalence of wet versus DPS sampling for recovery of TBI biomarkers using serial dilutions over five orders of magnitude of the recombinant protein biomarker UCH-L1 in spiked recovery studies in pooled plasma from 10 healthy controls aged 40-45 years. In Figures 11A-11D, assays were performed using a third immunoassay platform (3) as a benchmark.

[0102] A wide dynamic range is an important analytical performance indicator for the SPS of the present invention. Similarly, to maximize protein recovery from the DPS collection disk, the impact of matrix effects must be evaluated and considered. To this end, spike recovery studies using serial dilutions spanning five orders of magnitude of four recombinant protein biomarkers (GFAP, NFL, tau, and UCH-L1) in pooled plasma from 10 healthy controls aged 40–45 years were performed. Assays were performed using a third immunoassay platform (3) as a benchmark. As shown in Figures 11A–11D, excellent recoveries (>75%) were observed for all four biomarkers, except for the two lowest levels of tau. This evidence supports the optimization of conditions for eluting proteins captured on the DPS collection disk. For example, several mild detergents, detergent concentrations, buffer pH and osmolality, and extraction times and volumes were investigated. The concentration-response relationships of the biomarkers in the panel will be carefully established through such spike recovery studies and additional studies using pooled samples from mild, moderate, and severe TBI patients and healthy controls.

[0103] Finally, evidence supporting the need for frequent longitudinal sampling and measurement is provided in longitudinal pilot data for selected biomarkers from our panel (GFAP, NFL, PNF-H, tau, P-Tau, IL-6, and MOG) in wet serum specimens, as shown in Figures 3A-8. Notably, the distinct temporal profiles and peaks or waveforms of GFAP, tau, P-Tau, IL-6, NFL, and MOG strongly support the need for frequent DPS sampling to aid in monitoring TBI patients in military settings from acute to subacute / chronic phases, provide the best possible SPS in pre-hospital, in-hospital, and home care settings, and accelerate recovery from TBI.

[0104] [Example 4] Moderate-Severe Civilian Traumatic Brain Injury Study - Thirty subjects with moderate-to-severe TBI will be studied for 12 months for biomarker levels in various tissues and at various time points after injury to demonstrate the safety and feasibility of the SPS platform. Each subject will be over 18 years of age, have moderate-to-severe TBI as defined by a GCS of 13 or less with positive evidence of TBI on CT imaging, and a GCS motor score of less than 6. Additionally, 15 age- and sex-matched control subjects will also be studied.

[0105] Data will be collected in the form of case report forms (CRFs) and will be primarily collected by clinical service staff when part of standard data collection or standard of care. CRF data will be collected for each subject throughout their study participation. This includes data derived from chart review and post-discharge telephone interviews. This data includes the following: subject's age, sex, GCS, time / date of initial injury, polytrauma status, ICU / general ward classification, and ventilator status.

[0106] The TBI phenotype is classified on CT (e.g., epidural hematoma, diffuse axonal injury, subdural hematoma, intracerebral parenchymal hemorrhage, cerebral edema, subarachnoid hemorrhage, maximum intracranial lesion, and herniation), and changes in CT findings during hospitalization are collected.

[0107] Clinical history, including surgical interventions, intracranial pressure monitoring, PbtO2 monitoring, and occurrence of adverse events, will be collected.

[0108] Clinical outcome measures will be collected to quantify the severity of injury and include: deterioration of neurological examination, need for operative intervention, need for intubation, length of hospitalization / ICU care, 30-day and 1-year mortality / readmission rates, and Extended Glasgow and Disability Rating Scales (DRS) at 1 and 6 months.

[0109] All data collected is HIPAA compliant.

[0110] During hospitalization: Serial wet plasma and DPS samples will be collected from hospitalized patients at the following time points: at enrollment (recording time after injury), 24 hours, and twice daily for up to 14 days until discharge (28 time points), once on day 30, and once at discharge (total wet and dry samples by discharge, both n=30).

[0111] Healthy controls will have one wet plasma sample and one DPS sample collected.

[0112] Post-Discharge: Prior to discharge, all TBI patients and / or their family or guardians will be instructed on how to use the CP and provided with eight DPS collection kits (four for use and four as spares). They will be instructed to collect four additional sets of DPS specimens (7, 14, 30, and 60 days after discharge). The specimens will be returned unrefrigerated by prepaid courier to the study's regional laboratory. At the laboratory, the QR code on each CP will be scanned to uniquely identify the TBI outpatient specimen for analysis.

[0113] Clinical course, including surgical intervention, intracranial pressure monitoring, PbtO2 monitoring, and occurrence of adverse events, will be collected. Clinical outcome measures will also be collected to quantify injury severity and patient outcome, including: deterioration of neurological examination, need for surgical intervention, need for intubation, length of hospitalization / ICU care, 30-day and 1-year mortality / readmission rates, and the Extended Glasgow Outcome Scale and Disability Rating Scale (DRS) at 1 and 6 months.

[0114] Moderate to severe civilian traumatic brain injury studies have shown that: The SPS (Single Platform Solution for TBI Temporal Biomarker Panel) is deployable within a healthcare setting after acute moderate-to-severe TBI to collect serial blood samples and arrange their cold-chain transport to a single testing site for TBI temporal biomarker panel analysis; · The SPS platform is deployable for use by patients and their caregivers after discharge from hospital following incident TBI to collect serial dried blood spot samples and arrange for their transportation at ambient temperature to a single testing site for TBI temporal biomarker panel analysis; · Key biomarker levels obtained from dried and corresponding wet plasma samples collected acutely from TBI and control subjects in a hospital setting have a robust correlation of r ≥ 0.60; · The SPS platform can be used to distinguish wet and dried plasma samples from TBI subjects from age-matched control subjects; The SPS platform is deployable within a healthcare setting after acute moderate-to-severe TBI to collect serial blood samples and return them for transport and analysis; · The SPS platform is deployable for use by patients and their caregivers after discharge from hospital following an incident TBI, collecting serial blood samples that are then transported and returned for analysis; The SPS platform will be trialed in age-matched control subjects.

[0115] [Example 5] Two hundred subjects with severe TBI (sTBI) are enrolled in a clinical trial. Of the enrolled patients, 114 subjects consented to donate remaining biological samples after study completion for future research. Approximately 80 of these patients have sufficient remaining biological samples for inclusion in the current project. The following characteristics of these patients are typical of the sTBI population: the mean age of the patients was 32.5 years; 18 (16%) were female and 96 (84%) were male; 23 (20%) were Black, 3 (3%) were Asian, 27 (24%) were White non-Hispanic, and 61 (54%) were White Hispanic. Marshall CT score: diffuse injury I (0), diffuse injury I (49), diffuse injury III (30), diffuse injury IV (0), mass lesion removed (32), mass lesion not removed (3). Six-month outcome (GOSE) results were as follows: good recovery (15); moderate disability (29); severe disability (42), vegetative state (6), death (15), and loss to follow-up (7). Other data collected included out-of-hospital hypotension, out-of-hospital hypoxemia, Sepsis-Related Organ Failure Assessment (SOFA) score, Abbreviated Injury Scale (AIS), Injury Severity Score (ISS), and Acute Physiology and Chronic Health Evaluation I (APACHE II). Whenever possible, serial serum and CSF samples were collected at 6, 12, 18, 24, 48, 72, 96, 120, 144, 168, 192, 216, and 240 hours post-injury (Aisiku, Yamal et al. 2016).

[0116] We have obtained IRB approval for new subject enrollment and will begin enrolling new subjects in the following BCMs: (a) sTBI Subjects (N = 63): Inclusion criteria are severe TBI due to blunt trauma, motor GCS ≤ 5, age ≥ 18 years, and enrollment within 12 hours of injury; exclusion criteria are penetrating injury, life-threatening systemic injury, spinal cord injury, and severe pre-existing medical conditions that may interfere with 6-month follow-up. (b) Orthopedic Injury Controls (N = 20): Inclusion criteria are limb sprain or fracture but no TBI, enrollment within 12 hours of injury, and age and gender matching with TBI subjects; exclusion criteria are pre-existing health problems and TBI within the past year. (c) Healthy Controls (N = 20): Inclusion criteria are normal volunteers with no history of TBI within the past year and age and gender matching with sTBI subjects; exclusion criteria are pre-existing health problems and TBI within the past year. In TBI subjects, serial CSF and serum samples (8 mL blood collection tubes) will be collected at the following time points: 12 hours after injury, daily samples (days 1–10 after injury); additional serum samples at day 14, 1, 3, and 6 months; Glasgow Outcome Scale-Extended (GOSE) and Disability Rating Scale (DRS) at 1, 3, and 6 months; and CT lesion volume changes will be collected at admission, 24 hours, and again based on clinical findings. In HC subjects, a single serum sample will be collected.

[0117] Biological sample collection, processing, and cold-chain transport and storage. Serum (using 8 mL clot separator collection tubes) and CSF samples were collected in timed batches into 15 mL conical disposable centrifuge tubes (BD) according to our established standard operating procedures and in accordance with the published Biospecimens and Biomarkers Recommendations from the TBI common Data Element Working Group (Manley, Diaz-Arrastia et al. 2010). Each serum sample was approximately 3-4 mL, and CSF was 10 mL. All samples were stored in 500 μL microaliquots at -85°C in a freezer until use.

[0118] [Example 6] Biostatistically, two primary comparisons based on the clinical trial objectives and study design include: comparing the feasibility and utility between dried plasma collection and its traditional wet plasma counterpart in terms of its utility in reporting key TBI biomarker levels on a single assay platform, and comparing key biomarker levels (wet or dried plasma) between severe-to-moderate TBI subjects and control subjects.

[0119] For correlations between dry and wet plasma, R values ​​ranged from 0.65 to 0.95 based on data for multiple biomarkers (NFL, GFAP, WASF1, VAMP5, and UCH-L1). Therefore, (α) was set at 0.05 (two-tailed) and (1-β) at 0.80, with R = 0.50 (as a conservative estimate) and a minimum sample size of N = 29. The experimental group included N = 30 TBI patients and N = 15 normal controls (total N = 45) for all key biomarker measurements, providing sufficient statistical power to examine correlations between wet and dry plasma biomarker levels.

[0120] For the comparison between TBI and healthy controls, a power analysis was performed based on pilot data to detect a difference in the mean or median value of each biomarker between the two groups (TBI vs. controls), with (α) set to 0.05 (two-tailed) and (1-β) set to 0.80. Based on pilot data using a key protein biomarker, NFL, for example, a mean between-group fold difference of 1.50 and a standard deviation of 28%, resulting in a Cohen's d of 1.307. A minimum of 11 subjects per group was required. For another marker, WASF1, a smaller mean difference (TBI vs. controls) was used, with a mean between-group difference of 1.30 and a standard deviation of 27%, resulting in a Cohen's d of 0.959 and a calculated sample size of N = 15 per group. Therefore, the enrollment of 30 TBI subjects and 15 healthy controls provided sufficient power.

[0121] Data Analysis Plan: (I) Descriptive Analysis. Prior to analysis, the statistical properties of our biomarkers, outcome measures, and other demographic and clinical characteristics will be assessed. Descriptive statistics (mean, median, other percentiles) and dispersion (standard deviation, range) will be calculated for continuous data. Outliers, normality, and missing data will be checked. For categorical data, frequency distributions will be calculated. Repeated-measurement data will be "binned" into discrete time intervals.

[0122] (II) For each biomarker (or ratio between two markers), a line graph is generated to examine the time trends for each of these biomarkers, stratified by group. To compare a given biomarker at each time point between two outcome groups, a two-sample t-test or Wilcoxon rank-sum test is used, depending on the distribution of the biomarker.

[0123] (III) For each biomarker measured at its optimal time point, both a comparison of medians between groups (TBI and control) and a receiver operating characteristic (ROC) analysis will be performed to examine the sensitivity and specificity of each marker to predict TBI for each dichotomous outcome of interest (e.g., TBI vs. control), as described above. The difference between the areas under the two ROC curves (one for one biomarker and one for another) will be tested using the method of Hanley and McNeil (1983).

[0124] (III) Comparisons of wet and dried plasma for each key biomarker are examined for all subjects (TBI, control) or only TBI subjects, and correlation graph (X, Y) plots are examined. Each data point represents one subject, and X and Y are the values ​​of the biomarker measured in wet versus dried plasma at the same time point. Linear regression is then used to examine Pearson's r (correlation coefficient) and R-squared values ​​to determine whether the r value is different from zero. The significance threshold p-value is set at 0.05.

[0125] (III) As an exploratory analysis, we will examine whether adding biomarkers improves the prediction of outcome measures. For each significant bivariate biomarker associated with outcome, a multivariate logistic regression model will be created using important clinical factors (e.g., injury severity, age, sex) and single biomarker values ​​or trajectory (TRAJ) group membership. For each biomarker, the optimal time point with the highest predictive ability will be selected based on prior analyses. Two multivariate models will then be constructed to predict outcome based on the presence or absence of biomarker values ​​measured at that optimal time point. The independent association of IMPACT scores will be assessed by including both in the same model (see references). For longitudinal data, multivariate models with random effects will be considered.

[0126] (VI) Again, as an exploratory analysis, generalized linear mixed models and trajectory analysis are used: when dealing with repeated measurements over time from the same patient, mixed-effects modeling is used to add random effects to the model to account for clustering effects within each patient. 30 Similarly, trajectory class analysis is used to examine whether groupings by different outcomes exhibit different temporal profiles or trajectories.

[0127] Power Analysis: The power analysis for the R33 phase was based on testing whether the AUC of the ROC curve exceeded at least 80%. Based on preliminary data, approximately 41% of patients demonstrated favorable GOSE outcomes. A sample size of N = 63 sTBI patients would provide at least 80% power to detect an AUC effect size of 80%–95%. Comparisons between sTBI and control groups would provide increased power. Furthermore, a power analysis was performed to detect mean differences in each biomarker between the sTBI and control groups based on pilot data, with (α) set to 0.05 (two-tailed) and (1-β) set to 0.80. Based on our pilot data (shown in Figure 4C), the two primary outcome groups (GOSE ≤ 4 and ≥ 5) required a minimum of 20 subjects / group, with a mean intergroup fold difference of 1.35, a standard deviation of 36%, and a Cohen's d of -0.814. Therefore, we conclude that a minimum of n = 63 TBI subjects in both R61 and R33 provides sufficient power. Similarly, for controls versus sTBI, based on pilot data (shown in Figures 2-3D), a 1.5% and 30% difference between groups was found, with a Cohen's d of 1.307, and a minimum of n = 11 per group. Therefore, a sample size of n = 63 TBI subjects and n = 40 controls in R33 provides sufficient power. Because this study lacks power to detect subgroups / subphenotypes (e.g., gender), these results are considered exploratory and should be interpreted with caution. Considering a 5% loss to follow-up for 6-month outcomes, 63 sTBI patients will be recruited. Prior to analysis, the statistical properties of our biomarkers, outcome measures, and other demographic and clinical characteristics will be assessed. Descriptive statistics (mean, median, other percentiles) and dispersion (standard deviation, range) will be calculated for continuous data. Outliers, normality, and missing data are checked. For categorical data, frequency distributions are calculated. Repeated-measurement data are "binned" by discrete time intervals (e.g., days: acute markers; months: chronic markers) before analysis. First, for each miRNA (or ratio between two markers), line graphs are generated to examine temporal trends for each of these biomarkers, stratified by group.To compare a given biomarker at each time point between two outcome groups, a two-sample t-test or Wilcoxon rank-sum test is used, depending on the distribution of the biomarker. Second, for each significant bivariate miRNA associated with the outcome, a multivariate logistic regression model is created using important clinical factors (e.g., injury severity, age, and sex) and the single miRNA value or trajectory group membership. For each miRNA, the optimal time point with the highest predictive ability is selected based on prior analysis. Two multivariate models are then constructed to predict outcome based on the presence or absence of the miRNA measured at that optimal time point. The independent association of the IMPACT score is assessed by including both in the same model, and the AUC is estimated with and without the IMPACT score. For longitudinal data, a multivariate model with random effects is considered. Third, a receiver operating characteristic (ROC) analysis is performed for each biomarker measured at the optimal time point to examine the AUC at which each marker predicts each outcome for each binary outcome of interest (e.g., GOSE, DRS score, and CT lesion volume increase), as described above. The method of Hanley and McNeil (1983) for the difference between the areas under two ROC curves (one model with the biomarker of interest and one without). 29 Fourth, when dealing with repeated measurements over time from the same patient, a random effect is added to the model using mixed effects modeling to account for clustering effects within each patient. 30 Similarly, trajectory class analysis 31,32 will be used to examine whether groupings according to different outcomes exhibit different temporal profiles or trajectories.

[0128] The methods described herein include conventional biological techniques.Such techniques are well known in the art and are described in detail in methodological books such as: Molecular Cloning: A Laboratory Manual, 2nd ed., vol. 1-3, ed. Sambrook et al., Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY, 1989; and Current Protocols in Molecular Biology, ed. Ausubel et al., Greene Publishing and Wiley-Interscience, New York, 1992 (regularly updated).Immunological techniques (such as the preparation of antigen-specific antibodies, immunoprecipitation, and immunoblotting) are described, for example, in: Current Protocols in Immunology, ed. Coligan et al., John Wiley & Sons, New York, 1991; and Methods of Immunological Analysis, ed. Masseyeff et al., John Wiley & Sons, New York, 1992. The entire contents of each of the above publications are incorporated herein by reference as if each were expressly incorporated herein in its entirety.

[0129] [Example 7] Table 4 below shows an example of a proteomics-based search for a panel of TBI serum and plasma-based biomarker proteins that are elevated in TBI and have very strong diagnostic and temporal biomarker characteristics. These candidates were identified based on: (A) comparisons (expressed as ratios) of average TBI day 1, day 14, and 6-month serum levels (N=7 each) to average healthy control serum levels (N=7), and (B) comparisons (expressed as ratios) of pooled severe TBI day 1 plasma levels (pooled equally from N=10), two separate pooled moderate-to-mild TBI plasma levels (designated #1 and #2, each pooled equally from N=12), and pooled healthy control plasma levels (pooled equally from 200 subjects). Of the biomarker candidates shown in this table, all selected candidates demonstrate a mean TBI / mean control serum ratio and a pooled TBI / pooled control plasma ratio of at least 1.40 (i.e., a 1.40-fold increase) in at least one time interval. Those achieving such criteria are indicated with an (*). The protein abbreviation, protein full name, and Uniprot accession number are provided. In the "Potential Clinical Utility of Brain Injury Biomarkers" column, very high, high, and moderately high overall TBI / control discrimination ratios are indicated with ++++, +++, ++, and +, respectively. na - Not available.

[0130] JPEG2025541672000008.jpg185166JPEG2025541672000009.jpg195166

[0131] [Example 8] Table 5 shows an example of a proteomics-based search for a panel of TBI serum and plasma-based biomarker proteins that are elevated in TBI and have strong diagnostic and temporal biomarker characteristics. These candidates were identified based on: (A) comparisons (expressed as ratios) of average TBI day 1, day 14, and 6-month serum levels (N=7 each) with average healthy control serum levels (N=7), and (B) comparisons (expressed as ratios) of pooled severe TBI day 1 plasma levels (pooled equally from N=10), two separate pooled moderate-to-mild TBI plasma levels (designated #1 and #2, each pooled equally from N=12), and pooled healthy control plasma levels (pooled equally from 200 subjects). Of the biomarker candidates shown in this table, all selected candidates demonstrate a mean TBI / mean control serum ratio or pooled TBI / pooled control plasma ratio of at least 1.40 (i.e., a 1.40-fold increase) in at least one time interval. Those achieving such a criterion are indicated with an (*). Protein abbreviation, protein full name, and Uniprot accession number. In the column "Potential clinical utility of brain injury biomarkers," all markers are rated as either moderately high (if relevant to brain or disease mechanism) (indicated by ++) or showing a moderate overall difference in TBI / control ratios (indicated by "+"), respectively.

[0132] JPEG2025541672000010.jpg195166JPEG2025541672000011.jpg123166

[0133] [Example 9] Given the above findings regarding the nontrivial and unique temporal profiles of MOG, MOG-Ab, pTau, tau, WASF1 or WASF3, VAMP5 or VAMP2, CAMKKI, VEGF-A, MBP, IL-6, and other biomarkers presented herein, two important uses of brain injury biomarkers are supported in the context of clinical patient care, management, and monitoring: (i) First, instead of measuring a single biomarker, it is clinically important to simultaneously measure multiple biomarkers, preferably at least three markers, such as a panel of MOG plus two or more other biomarker proteins (e.g., but not limited to, MOG-Ab, pTau, tau, WASF1 or WASF3, VAMP5 or VAMP2, CAMKKI, VEGF-A, MBP, and IL-6). (ii) Second, it is important for clinical monitoring and care purposes to repeatedly measure such a panel of brain injury biomarkers at more than one or multiple time points after the onset of injury or damage.

[0134] [Example 10] Patients presenting with traumatic brain injury (TBI) are enrolled for biofluid sampling. Plasma, serum, saliva, and dried plasma spot (DPS) samples are collected from each patient. Figures 43A-44E show preliminary results from the first patient. For DPS samples, fingerstick capillary blood is collected from each patient by pricking the fingertip, and 3-4 drops of blood are placed into the Gryphon DPS device. The DPS device separates red blood cells from plasma through a capillary mechanism, where the plasma is captured on the device's collection disc and allowed to dry at room temperature. Saliva is collected using a cotton-swab syringe-type sampling device. The cotton swab is attached to the plunger of a syringe, which is inserted under the patient's tongue for several minutes, allowing the swab to fill with saliva. The cotton swab and plunger are inserted into the barrel of the syringe device and forced through a filter on the end of the syringe into an Eppendorf collection tube. Plasma and serum are collected by conventional methods. Plasma from the collection disks was eluted and measured in the same manner as wet plasma, demonstrating a low-cost, effective method for plasma collection. Figures 43A-L show that glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), total tau, and pTau181 were successfully collected using the DPS device of the present invention (Figures 43A-D), plasma (Figures 43E-H), and saliva (Figures 43I-L) from the same control and TBI patients. GFAP, NfL, total tau, and pTau181 were also measured, demonstrating correlations between measurements in the matrices, which can subsequently be used as correction factors for normalization. Figures 43M and 43N are graphs showing longitudinal plasma and saliva samples, respectively, collected for measurements at 6 and 12 months from an individual TBI patient. Figures 44A-E show side-by-side matrix comparisons, demonstrating that correction factors can be used to correlate biomarker levels between matrices for each biomarker. Also shown is a rough recovery comparison for biomarkers collected on the DPS compared to plasma and saliva. Recovery values ​​greater than 100% indicate higher biomarker levels in saliva than in plasma.In a separate preclinical study, similar recovery and biomarker measurements were demonstrated when blood drawn from mice was loaded into our DPS device, and these results were also reproducible when dried saliva was used.

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[0162] Ambrosius W, Michalak S, et al. Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease: Current Insights into the Disease Pathophysiology, Diagnosis and Management. Int J Mol Sci. 2020 Dec 24;22(1):100. doi: 10.3390 / ijms22010100. PMID: 33374173; PMCID: PMC7795410.

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[0164] Zhang Z, Zoltewicz JS, et al. Wang KKW (2014) Human Traumatic Brain Injury Induces Autoantibody Response against Glial Fibrillary Acidic Protein and Its Breakdown Products. PLoS One. 2014 Mar 25;9(3):e92698

[0165] The patent documents and publications mentioned in this specification are indicative of the level of those skilled in the art to which this invention pertains, and are herein incorporated by reference to the same extent as if each individual document or publication was specifically and individually incorporated by reference.

[0166] The above description illustrates specific embodiments of the present invention, but is not meant to limit its practice. The following claims, including all equivalents thereof, are intended to define the scope of the present invention.

[0167] The referenced publications are indicative of the level of skill of those skilled in the art to which this invention pertains. These publications are herein incorporated by reference to the same extent as if each individual publication was specifically and individually indicated to be incorporated by reference.

Claims

1. 1. A method for determining the extent of a central nervous system (CNS)-specific neurological condition in a subject, comprising: obtaining a biological sample of a biological fluid from said subject; and measuring the amount of a first biomarker, or a metabolite of said first biomarker, or an mRNA corresponding to said first biomarker, from the saliva, from the dried spot, or from said sample via a microfluidic device; Including, method.

2. 2. The method of claim 1, wherein determining the extent of the neurological symptom includes determining the magnitude of biomarker levels, composite score, disease burden, burden amount, severity, stage, disease course, or any combination thereof using statistical, machine learning, or other methods. method.

3. 2. The method of claim 1, the amount of the first biomarker is measured from the dried spot or dried saliva; method.

4. 2. The method of claim 1, the first biomarker is a protein or autoantibody, or a metabolite of the first biomarker, or an mRNA corresponding to the first biomarker, which is not detected in the absence of the neurological symptom or is detected at a level lower than that in the absence of the neurological symptom; method.

5. 2. The method of claim 1, measuring the amount of a second biomarker in a biological sample obtained from the biological fluid or venous or arterial blood from the subject to further determine the extent of the neurological condition; further comprising The second biomarker is one of the following: MOG, anti-MOG autoantibody IgG, anti-MOG autoantibody IgM, GFAP (glial fibrillary acidic protein; molecular weight 50K); GFAP degradation products (GBDP) of 38K (GBDP38K), 44K (GBDP44K), and those in the molecular weight range between 38K and 49K (GBDP38K-49K); NF-L (neurofilament light chain protein), NFL-M (neurofilament medium chain protein) protein), NF-H (neurofilament heavy chain protein), pNF-H (phosphorylated NF-H), α-internexin (NEF5); T-Tau (total tau), P-Tau (phosphorylated tau), P-Tau:T-Tau ratio, P-Tau(231), P-Tau(396 / 404), P-Tau(181), P-Tau(S202), P-Tau(217), OMG (oligodendrocyte myelin glycoprotein), MBP (myelin basic protein), MAG (myelin-associated glycoprotein), anti-MAG autoantibody IgG, anti-MAG autoantibody IgM, anti-GFAP autoantibody IgG, anti-GFAP autoantibody IgM, synapsin-1, -2, -3, VILIP-1 (visinin-like protein 1), VILIP-3 (visinin-like protein 3), UCH-L1 (ubiquitin C-terminal hydrolase L1); αII- Spectrin breakdown products (SBDPs): SBDP150N, SBDP150, SBDP145, SBDP150i, SBDP120; MAP2 (microtubule-associated protein 2), MAP6 (microtubule-associated protein 6); vimentin; WASF1 (WASP family member 1), WASF3 (WASP family member 3), VAMP5 (vesicle-associated membrane protein 5), VAMP2 (synaptobrevin;Vesicle-associated membrane protein 2), SNAP25 (synaptosomal-associated protein 25), SNAP23 (synaptosomal-associated protein 23), BDNF (brain-derived neurotrophic factor), ProBDNF (brain-derived neurotrophic factor precursor), CAMKK1, CAMK-II (calcium / calmodulin-dependent protein kinase II), COL4A3BP, CERT1 (ceramide transfer protein (CERT1)), DUSP3 (dual specificity phosphatase 3 ), TBCB (tubulin folding cofactor B), Ninj-1 (ninjulin-1), HMGB-1 (high mobility group box 1), SAA (serum amyloid A), C-RP (C-reactive protein), C-fibronectin, VEGF-A (vascular endothelial growth factor A), VEGF-C (vascular endothelial growth factor C), MCP-4 (monocyte chemotactic protein 4), eotaxin-3, sCD30 (soluble CD30 glycoprotein), ITAC (CXCL11;Interferon-inducible T-cell alpha chemoattractant), sICAM1 (soluble intercellular adhesion molecule 1), IL-6 (interleukin-6), IL-15 (interleukin-15), PDGF-A (platelet-derived growth factor A), IMPA1 (inositol monophosphatase 1), ZBTB16 (zinc finger and BTB domain-containing protein 16), PRDX6 (peroxiredoxin 6), NFATC1 (N-alpha-acetyltransferase 10), NAA10 (N-alpha-acetyltransferase 10), ING1 (growth inhibitor family member 1), BCR (breakpoint cluster region protein), DCTN2 (dynectin-2), FHIT (fragile histidine triad diadenosine triphosphatase), MAP2K6 (dual specificity mitogen-activated protein kinase kinase 6), METAP1D (methionyltransferase 1), aminopeptidase type 1D), NAA10 (N-α-acetyltransferase 10, NatA), SULT2A1 (sulfotransferase 2A1), ZBTB16 (zinc finger and BTB domain-containing protein 16), ARHGEF12 (Rho guanine nucleotide exchange factor 12), and TACC3 (transforming acidic coiled-coil-containing protein 3), amyloid beta peptide (1-40), amyloid beta peptide (1-42), SV2A (synaptic vesicle glycoprotein 2A), SV2B (synaptic vesicle glycoprotein 2B), SV2C (synaptic vesicle glycoprotein 2C), apolipoprotein E4 (APOE4), amyloid beta peptide (1-40 and 1-42 and their ratio), adenosine, NAA, NAAG, norepinephrine, myo-inositol, glutamate, glutamine, or a combination thereof; That is, method.

6. 2. The method of claim 1, the amount of the first biomarker is correlated to the amount of the first biomarker obtained from a second biological sample from the subject via a correction factor; the biological sample is cerebrospinal fluid, tears, saliva, sweat, exhaled air, urine, venous or arterial whole blood, a fraction of said whole blood, venous or arterial serum, venous or arterial plasma, body tissue or tissue lysate, or a dried spot derived from any of the above; method.

7. 2. The method of claim 1, measuring the amount of a second biomarker from the biological sample of the biological fluid at a second time point. method.

8. 2. The method of claim 1, the first biomarker is MOG; method.

9. 2. The method of claim 1, the first biomarker is one of neurofilament L, tau, glial fibrillary acidic protein (GFAP), or a GFAP degradation product; method.

10. 6. The method according to claim 5, the first biomarker is one of neurofilament L, tau, glial fibrillary acidic protein (GFAP), or a GFAP degradation product; and the second biomarker is neurofilament L, tau, glial fibrillary acidic protein (GFAP), or another one of the GFAP degradation products; method.

11. 11. The method of claim 10, wherein at least one additional of neurofilament L, tau, glial fibrillary acidic protein (GFAP), or a GFAP degradation product is measured; method.

12. 12. The method of claim 11, further comprising measuring MOG; method.

13. 2. The method of claim 1, and comparing the amount of the first biomarker in the subject with other individuals without a known CNS-specific neurological condition. method.

14. 2. The method of claim 1, The amount of the first biomarker is determined by any of the following: Head computed tomography (CT) scan findings, head magnetic resonance imaging (MRI) findings, head positron emission tomography (PET) findings, physiological findings such as intracranial pressure or sleep measurements, glymphatic clearance / dysfunction, sensory, ocular, language, memory, and motor neurobehavioral, cognitive decline, or outcome measures such as GCS (Glasgow Coma Scale) score, CPC (Cerebral Performance Category), mental status changes, and other concussion symptom assessments (e.g., Rivermead Postconcussion Questionaire), and Sport Concussion Assessment Tool. 3 (SCAT3), EDSS (Extended Disability Status Scale (EDSS)), and MSFC (Multiple Sclerosis Functional Composite), Amyloid / Tau / Neurodegeneration (ATN) Classification System for Alzheimer's Disease (AD), ISS (Injury Severity Score (ISS)), global functional outcome assessments such as GOSE (Extended Glasgow Outcome Scale), DRS (Disability Rating Scale), IMPACT (International Mission for Prognosis and Clinical Trials) score for TBI outcome, CRASH (Corcicosteroidoid Randomization after Significant Head Injury) prognostic model for TBI, Quality of life questionnaires Inventories), e.g., Health-Related Quality of Life (HRQoL), Quality of Life after Brain Injury [QOLIBRI], Trauma-Quality of Life [TQoL], digital biomarkers including step counts, sleep duration detected from smart devices or internet-based assessments, cognitive and neuropsychological assessments, e.g., Brief Test of Adult Cognition by Telephone* (BTACT), TBIQOL* Applied Cognition modules, NIH Toolbox Cognitive Battery, California Verbal Learning Test-secondedition (CVLT-II), Wechsler Adult Intelligence Scale, Third Edition (WAIS-III), Delis-Kaplan Executive Function System (DKEFS), Trail making test -A and -B, ACS wordlist (previous function test), MOCA, WAIS 4, WMI and PSI, Auditory consonant trigrams, paired-associate learning, RAVLT learning and recall / recognition, logical memory, NAB naming, letter and categorical fluency, Trails A and B B, Ecog / CDR, FAQ, PASAT (two speeds), or a combination thereof; and further comprising the step of correlating the method.

15. 2. The method of claim 1, The CNS-specific condition is traumatic brain injury (TBI, including mild traumatic brain injury, concussion, moderate traumatic brain injury, or severe traumatic brain injury), multiple sclerosis (MS, including clinically isolated syndrome, relapsing-remitting multiple sclerosis, secondary progressive multiple sclerosis, and primary progressive multiple sclerosis), brain metastatic breast cancer (bmBC), post-traumatic epilepsy (PTE), Alzheimer's disease (AD, including preclinical Alzheimer's disease, mild cognitive impairment, prodromal Alzheimer's disease, and various dementias), Alzheimer's disease-related dementia (ADRD), chronic traumatic encephalopathy (CTE), frontotemporal dementia (FTD), spinal cord injury (SCI), COVID-19, or Alexander disease (AxD). method.

16. 2. The method of claim 1, administering to said subject a compound, imaging agent, or drug, including a small or large molecule such as a biologic, antibody, fusion protein, virus, cell, or antibody conjugate, or a non-pharmacological treatment or intervention, before or after said measuring begins; method.

17. 6. The method according to claim 5, the amount of the first biomarker and the amount of the second biomarker are measured from the same biological sample; method.

18. 1. A method for determining the magnitude of multiple sclerosis (MS), post-traumatic epilepsy (PTE), Alexander disease (AxD), Alzheimer's disease (AD), or traumatic brain injury (TBI) in a subject, comprising: The method includes measuring at least two biomarkers of myelin oligodendrocyte glycoprotein (MOG), anti-MOG autoantibody IgG, or anti-MOG autoantibody IgM, the amount of NFL, the amount of GFAP, the amount of GFAP degradation products, and the amount of tau in one or more biological fluid biological samples obtained from the subject at a first time point to determine the extent or phenotypic outcome of multiple sclerosis, post-traumatic epilepsy, Alexander disease (AxD), Alzheimer's disease (AD), or traumatic brain injury (TBI) in the subject; method.

19. 20. The method of claim 18, measuring at least four of the above; method.

20. 20. The method of claim 18, The biological sample is cerebrospinal fluid, tears, saliva, sweat, exhaled air, urine, whole blood, a fraction of whole blood, serum, plasma, tissue or tissue lysate, or a dried spot derived from any of the above; method.

21. 20. The method of claim 18, the amount of the NFL, GFAP, or both is measured simultaneously with the amount of the MOG or the MOG antibody; method.

22. 20. The method of claim 18, comparing the amount of MOG, anti-MOG autoantibody IgG, or anti-MOG autoantibody IgM, NFL, GFAP or degradation products thereof, or a combination thereof in the subject with other individuals without known Alzheimer's disease (AD), multiple sclerosis (MS), Alexander disease (AxD), post-traumatic epilepsy (PTE), or traumatic brain injury (TBI); method.

23. 20. The method of claim 18, further comprising correlating the results with CT scan abnormalities or GCS scores. method.

24. 20. The method of claim 18, wherein the severity of traumatic brain injury (TBI) is concussion, mild traumatic brain injury, mild to moderate traumatic brain injury, moderate traumatic brain injury, moderate to severe traumatic brain injury, or severe traumatic brain injury; method.

25. 20. The method of claim 18, administering to said subject a compound, imaging agent, or drug, including a small or large molecule such as a biologic, antibody, fusion protein, virus, cell, or antibody conjugate, or a non-pharmacological treatment or intervention, before or after said measuring begins; method.

26. 20. The method of claim 18, the amounts of Tau, P-Tau, VAMP isoform, WASF isoform, CAMKK1, synapsin isoform, MBP, pNF-H, MOG, anti-MOG autoantibody IgG, or anti-MOG autoantibody IgM, NFL, GFAP, IL-6 are measured in the same biological sample; method.

27. 20. The method of claim 18, measuring a combined score that is the sum of the normalized or non-normalized amount of MOG and the amount of a second and third or more biomarkers selected from GFAP, NFL, VEGF-A, P-Tau, T-Tau, and the P-Tau:T-Tau ratio; method.

28. 20. The method of claim 18, measuring a combined score, which is the sum of the normalized or non-normalized amounts of the at least two biomarkers and the amount of: The amount is GFAP (glial fibrillary acidic protein; molecular weight 50K); GFAP degradation products (GBDP) of 38K (GBDP38K) or 44K (GBDP44K), or in the molecular weight range between 38K and 49K (GBDP38K-49K); or a second and third or more biomarkers selected from: NFL-L (neurofilament light chain protein), NFL-M (neurofilament medium chain protein), NF-H (neurofilament heavy chain protein), pNF-H (phosphorylated NF-H), α-internexin (NEF5); T-Tau (total tau), P-Tau (phosphorylated tau), P-Tau:T-Tau ratio, P-Tau(231), P-Tau(396 / 404), P-Tau(181), P-Tau(S202), P-Tau(217), OMG (oligodendrocyte myelin glycoprotein), MBP (myelin basic protein) Protein), MAG (myelin-associated glycoprotein), anti-MAG autoantibody IgG, anti-MAG autoantibody IgM, anti-GFAP autoantibody IgG, anti-GFAP autoantibody IgM, synapsin-1, -2, -3, VILIP (visinin-like protein 1), VILIP (visinin-like protein 3), UCH-L1 (ubiquitin C-terminal hydrolase 1); αII-spectrin breakdown products (SBDPs): SBDP150N, SBDP150, SBDP145, SBDP150i, SBDP120; MAP2 (microtubule-associated protein 2), MAP6 (microtubule-associated protein 6); vimentin; WASF1 (WASP family member 1), WASF3 (WASP family member 3), VAMP5 (vesicle-associated membrane protein 5), VAMP2 (synaptobrevin; vesicle-associated membrane protein 2), SNAP25 (synaptosomal-associated protein 25), SNAP23 (synaptosomal-associated protein 23), BDNF (brain-derived neurotrophic factor precursor), ProBDNF (brain-derived neurotrophic factor precursor), CAMKK1, CAMKII (calcium / calmodulin-dependent protein kinase II), COL4A3BP, CERT1 (ceramide transfer protein (CERT1)), DUSP3 (dual specificity phosphatase 3), TBCB (tubulin folding cofactor B), Ninj-1 (ninjurin-1), HMGB-1 (high mobility group box 1), SAA (serum amyloid A), C-RP (C-reactive protein), C-fibronectin, VEGF-A (vascular endothelial growth factor A), VEGF-C (vascular endothelial growth factor C), MCP-4 (monocyte chemotactic protein 4), eotaxin-3, sCD30 (soluble CD30 glycoprotein), ITAC (CXCL11;Interferon-inducible T-cell alpha chemoattractant), sICAM1 (soluble intercellular adhesion molecule 1), IL-6 (interleukin-6), IL-15 (interleukin-15), PDGF-A (platelet-derived growth factor A), IMPA1 (inositol monophosphatase 1), ZBTB16 (zinc finger and BTB domain-containing protein 16), PRDX6 (peroxiredoxin 6), NFATC1 (N-alpha-acetyltransferase 10), NAA10 (N-alpha-acetyltransferase 10), ING1 (growth inhibitor family member 1), BCR (breakpoint cluster region protein), DCTN2 (dynectin-2), FHIT (Fragile histidine triad diadenosine triphosphatase)), MAP2K6 (dual specificity mitogen-activated protein kinase kinase 6), METAP1D (methionyl aminopeptidase type 1D) NAA10 (N-α-acetyltransferase 10, NatA); SULT2A1 (sulfotransferase 2A1), ZBTB16 (zinc finger and BTB domain-containing protein 16), ARHGEF12 (Rho guanine nucleotide exchange factor 12), and TACC3 (transforming acidic coiled-coil-containing protein 3), amyloid beta peptide (1-40), amyloid beta peptide (1-42), SV2A (synaptic vesicle glycoprotein 2A), SV2B (synaptic vesicle glycoprotein 2B), SV2C (synaptic vesicle glycoprotein 2C), apolipoprotein E4 (APOE4), amyloid beta peptide (1-40 and 1-42 and their ratio), adenosine, NAA, NAAG, norepinephrine, glutamate, glutamine, myo-inositol, or a combination thereof; is the amount of method.

29. 29. The method of claim 27 or 28, the amount of each of the biomarkers is measured at the same time point; method.

30. 29. The method of claim 27 or 28, the peak amount of each of the biomarkers is based on the range of amounts recorded from repeated or multiple measurements of each of the biomarkers over a period of time following injury or clinical diagnosis of disease; method.

31. 29. The method of claim 27 or 28, The minimum detectable level of each of the biomarkers, or a composite score of biomarker levels for preclinical or subclinical evidence of disease activity and / or evidence of disease activity therefrom, is based on the range of amounts recorded from repeated or multiple measurements of each of the biomarkers over a period of time following injury or clinical diagnosis of disease. method.

32. 2. The method of claim 1, The biomarker is detected from the metabolite thereof or the corresponding mRNA. method.

33. 1. A method for determining the severity of Alzheimer's disease (AD), multiple sclerosis (MS), Alexander disease (AxD), post-traumatic epilepsy (PTE), or traumatic brain injury (TBI) in a subject, comprising: The method includes measuring a ratio of the amount of P-Tau:Tau and at least one of the amount of MOG, anti-MOG autoantibody IgG, or anti-MOG autoantibody IgM, the amount of NFL, the amount of GFAP or its degradation products, the amount of MBP, and the amount of an interleukin in one or more biological fluid biological samples obtained from the subject at a first time point to determine an outcome of Alzheimer's disease (AD), multiple sclerosis (MS), Alexander disease (AxD), post-traumatic epilepsy (PTE), or the extent of traumatic brain injury (TBI) in the subject; method.

34. 34. The method of claim 33, comprising: The biological sample is cerebrospinal fluid, tears, saliva, sweat, exhaled air, urine, whole blood, a fraction of whole blood, serum, plasma, tissue or tissue lysate, or a dried spot derived from any of the above; method.

35. 29. The method of claim 27 or 28, wherein the amount of MOG, anti-MOG autoantibody IgG, or anti-MOG autoantibody IgM, the amount of NFL, and the amount of GFAP or its degradation product, the amount of MBP, the amount of interleukin, or a combination thereof, are measured simultaneously with the ratio. method.

36. 34. The method of claim 33, comprising: and comparing the results in the subject with other individuals without known Alzheimer's disease (AD), multiple sclerosis (MS), Alexander disease (AxD), post-traumatic epilepsy (PTE), or traumatic brain injury (TBI). method.

37. 34. The method of claim 33, comprising: wherein the severity of traumatic brain injury (TBI) is concussion, mild traumatic brain injury, mild to moderate traumatic brain injury, moderate traumatic brain injury, moderate to severe traumatic brain injury, or severe traumatic brain injury; method.

38. 34. The method of claim 33, comprising: administering to said subject a compound, imaging agent, or drug, including a small or large molecule such as a biologic, antibody, fusion protein, virus, cell, or antibody conjugate, or a non-pharmacological treatment or intervention, before or after said measuring begins; method.

39. 34. The method of claim 33, comprising: wherein at least one of the amount of myelin oligodendrocyte glycoprotein (MOG), anti-MOG autoantibody IgG, or anti-MOG autoantibody IgM, the amount of NFL, the amount of GFAP or its degradation product, the amount of MBP, and the amount of interleukin are measured in the same biological sample. method.

40. 34. The method of claim 33, comprising: measuring a combined score that is the sum of the ratio, the amount of myelin oligodendrocyte glycoprotein (MOG), anti-MOG autoantibody IgG, or anti-MOG autoantibody IgM, the amount of NFL, the amount of GFAP or its degradation products, the amount of MBP, and the amount of interleukin, either normalized or unnormalized; method.

41. 34. The method of claim 33, comprising: The biomarker is detected from its metabolite or its corresponding mRNA. method.

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