FIELD OF THE INVENTION:

The invention relates to saliva based diagnostics and treatment of concussion and traumatic brain injury(TBI) including mild traumatic brain injury(mTBI).

BACKGROUND OF THE INVENTION:

Traumatic Brain Injury (TBI) is one of the most significant socioeconomic and public health burdens in both developed and developing countries. It is a main cause of death and disability in the United States, which contributes to about 30% of all injury deaths (Taylor CA, Bell JM, Breiding MJ, Xu L. Traumatic Brain Injury-Related Emergency Department Visits, Hospitalizations, and Deaths — United States, 2007 and 2013. MMWR Surveill Summ 2017; 66: 1-16). The effect is impaired thinking or memory, movement, sensation, emotional functioning, depression, personality changes etc., not only affects individuals but also families and communities (Taylor CA, Bell JM, Breiding MJ, Xu L. Traumatic Brain Injury-Related Emergency Department Visits, Hospitalizations, and Deaths — United States, 2007 and 2013.

MMWR Surveill Summ 2017; 66: 1-16). TBI can be divided into different types such as primary injury, secondary injury and severe stages, characterized by attempted, but ineffective, regeneration and repair. Most TBI cases are classified as mild traumatic brain injury (mTBI), also known as concussion. There are no reported treatments for mTBI and diagnosis represents a significant challenge. Diagnosis to date has been subjective and frequently based on self-reported neurological symptoms, some of which are often ignored, concealed, or overstated. Timely actions in both pre-hospital and early in-hospital stays are taken as important factors in decreasing mortality and the recovery of the patient’s neurological outcome (Taylor CA, Bell JM, Breiding MJ, Xu L. Traumatic Brain Injury- Related Emergency Department Visits, Hospitalizations, and Deaths — United States, 2007 and 2013. MMWR Surveill Summ 2017; 66: 1-16). To date, no routine tests exist to objectively diagnose mTBI, so taking into consideration the above-mentioned facts as a whole, it is in mTBI patients, where clinical diagnosis is complicated, that a laboratory-based test, point of care test, or other non-invasive tests has the greatest opportunity to aid greatly in therapeutic interventions that may be on the horizon. Recently, a test detecting two brainspecific protein biomarkers Ubiquitin Carboxy-terminal Hydrolase-Ll (UCH-L1) and Glial Fibrillary Acidic Protein (GFAP) in blood was approved by the FDA, but this test, relying on blood is invasive in nature.

Currently there are no non-invasive tests for mTBI available nor any reliable laboratory-based tests, point of care tests, or any other non-invasive tests for detection and diagnosis of mTBI exist, particularly in the early stages of mTBI. As a result, there is an urgentneed for a method of pre-symptomatic diagnosis of mTBI, a method for the diagnosis of symptomatic mTBI, a method of evaluating the risk of developing mTBI and of estimating the prognosis of a treatment of mTBI though a laboratory, point of care, field kit, mobile phone or smartphone based test. Such a test would provide physicians with objective tools for the diagnosis and treatment of patients sustaining concussions or mTBI.

IN201711027532 relates to novel set of biomarkers to assess the risk, screening, diagnosis, treatment and detection of mild (concussion), moderate, severe traumatic brain injury, etc. and to assess prognosis of concussion and traumatic brain injury such as mild, moderate, severe etc., following therapeutic or other treatment and intervention. The set of biomarkers consists of at least t- tau, p-tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein-1, ApoA-I etc.

SUMMARY OF THE INVENTION:

Provided herein is a non-invasive means for detecting, measuring, diagnosing, treating and monitoring traumatic brain injury; e.g., mild (concussion), moderate, severe traumatic brain injury using salivary biomarkers.

A mild traumatic brain injury (mTBI) that occurs in sports is mainly referred to as a concussion. A concussion may cause changes in the structure of the brain that causes downstream cognitive problems and increases the risk of depression. The category of injury, i.e. mild, moderate and severe TBI depends on a number of factors, including the type of injury (diffuse or focal), extension, location and other factors. As a result there are different patterns of damage (Teasdale G, Jennett B. Assessment of coma and impaired consciousness. A practical scale. Lancet 1974;2:81-84) . The Glasgow Coma Scale is one of the most commonly used tools to evaluate the level of TBI (Teasdale G, Jennett B. Assessment of coma and impaired consciousness. A practical scale. Lancet 1974;2:81-84). It is based on the scores for the best motor and verbal responses as well as the minimum stimulus required to cause eye opening (Severe Level: 3 to 8; Moderate Level: 9 to 12; and Mild Level: 13 to 15, according to the Advanced Trauma Life Support (ATLS), American College of Surgeons Committee on Trauma, Chicago, 2004).

As disclosed herein, one or multiple biomarkers in the bodily fluids of an individual might be quantitatively measured alone, or in combination with additional biomarkers for the detection, diagnosis and treatment of mild, moderate and I or severe traumatic brain injury. Levels of biomarkers may also be used to monitor the progression and severity of mild, moderate, severe traumatic brain injury and determine the effectiveness of a particular treatment in arresting or reversing the progression of these disorders.

The methods described herein comprise the identification of biomarkers such as proteins, and genetic and transcriptomic biomarkers in a biological fluid, such as saliva. Such biomarkers may be identified by any means generally used by one skilled in the art. In some embodiments, these biomarkers are identified using antibody-based methods, such as, but not limited to, an enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA), antibody based assays, western blot technologies, mass spectrometry, microarray, protein microarray, flow cytometry, immunofluorescence, PCR, aptamer-based assay, immunohistochemistry, multiplex detection assays, lateral flow immunoassays, assays utilizing exosomes and for applications at the point of care in field situations using mobile phones, and methods using proteomic approaches that utilize various detection methods. Biomarkers as used herein may be one or more of t-tau, p-tau, matrix metalloproteinases -9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein- 1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3.

In another aspect, the present invention includes a system of diagnosing mild, moderate or severe traumatic brain injury, using a computer readable media which contains a computer- readable program code, which also includes instructions for performing the diagnosis. The system consists of an assay for determining the appropriate level of one or a set of biomarkers that could use computer hardware, and a software program stored on computer-readable media or smart technologies including smart mobile phone, iphone, ipad etc., to analyze the levels of biomarkers from assays for the diagnosis, detection and treatment of the subject having mild (concussion), moderate or severe traumatic brain injury according to reference levels. In addition the concentrations of biomarkers indicate whether the subject is having a mild (concussion), moderate or severe traumatic brain injury.

In yet another aspect, the present invention includes a kit for the diagnosis of mild (concussion), moderate or severe traumatic brain injury. In this case, the kit consists of testing reagents for one or a set of biomarkers and an instructional material for use thereof.

In another embodiment, the present invention further provides a kit for the diagnosis, monitoring, prognosis, treatment and detection of mild (concussion), moderate or severe traumatic brain injury. The kit consists of: (a) a panel of any one or two or more than two or more of the above identified biomarkers; (b) a substrate for holding a biological sample isolated from a human subject suspected of having a mild (concussion), moderate or severe traumatic brain injury, etc., or being under treatment or intervention for mild (concussion), moderate or severe traumatic brain injury; (c) an agent which connects or binds to at least one of the biomarkers; (d) a measurable label; i.e. one conjugated to the agent, or one conjugated to a substance which specially binds at least to one or more of the biomarkers and presents a proportional reaction, based on the level of biomarker present and (e) printed or computer based or e-printed or remote instructions for reacting the agent with the biological sample, or a portion of the biological sample, to detect the presence or concentration of at least one biomarker in the biological sample and estimating if the biomarker is within a reference level for that particular biomarker.

In other embodiments, the kits are used within the same time of day window, in a similar way and/or with the same test used to estimate the reference levels.

In yet another aspect, the invention includes compositions, methods and uses of a novel set of biomarkers to assess the risk, screening, diagnosis, treatment and detection of mild (concussion), moderate and severe traumatic brain injury, etc. and to assess prognosis of concussion and traumatic brain injury which might include mild, moderate, or severe concussion following therapeutic administration or other treatments and / or interventions. The set of biomarkers consists of at least t-tau, p-tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein- 1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3.

In another embodiment the reference levels for biomarkers are found, based on biomarker levels in a sample taken from a subject at a previous point in time. The subject is seen to be reacting to treatment, intervention and management for mild (concussion), moderate and I or severe traumatic brain injury, if levels of the biomarkers in the biological samples have changed positively or negatively from the biomarker levels in a biological sample taken at an earlier time point from the same subject.

These and other embodiments and the specific advantages of the technology will become evident from reading the following Detailed Description.

DETAILED DESCRIPTION

Traumatic brain injury (TBI) is an acquired brain injury resulting from sudden trauma to the head. In the general population, motor vehicle accidents are the main cause of TBI (Traumatic Brain Injury (http://emedicine.medscape.com/article/326510- overview). Symptoms of TBI can vary from mild to moderate to severe. During a concussive event there may or may not be a loss of consciousness. Symptoms of mTBI include headache, confusion, lightheadedness, dizziness, blurred vision, tinnitus, dysgeusia [altered taste], fatigue, changes in sleep patterns or behavior and impairment of memory or cognition. Regardless of variable clinical presentations, patients with mTBI are assessed clinically by experts only. mTBI is defined as the effect of the forceful motion of the head, or impact, causing a short term change in mental status, or loss of consciousness for less than 30 minutes (CDC-Injury-Concussion-Tool Kit for Physicians). Currently diagnosis of mTBI needs a clinical assessment. There is no ideal test. Furthermore, lack of tests for detection, diagnosis and treatment of mild (concussion), moderate and / or severe traumatic brain injury, is one of the obstacles in the development of new treatments. The intricacy in precisely diagnosing mild (concussion), moderate and / or severe traumatic brain injury, additionally leads to high rates of misdiagnosis or improper diagnosis, negatively effecting families and delaying or preventing treatment for mild (concussion), moderate and / or severe traumatic brain injury.

Described herein is the detection of appropriate biomarkers and combinations of biomarkers useful for the prediction, diagnosis, prognosis, treatment and monitoring of mild (concussion), moderate and / or severe traumatic brain injury. Biomarkers are useful for diagnosing early stage mild (concussion), moderate and / or severe traumatic brain injury allowing for earlier treatment options. Moreover, the biomarkers disclosed herein may be used as drug targets to develop new drugs, as well as to monitor different therapies for the treatment and management of mild (concussion), moderate and / or severe traumatic brain injury.

TBI is classified based on the Glasgow Coma Scale (Teasdale, G, Jennett, B.Assessment of coma and impaired consciousness. A practical scale. Lancet.1974; 304(7872):81-84). It is a clinical tool designed to assess coma and impaired consciousness and is one of the most commonly used severity scoring systems.

Persons with GCS scores of 3 to 8 are classified as severe TBI, those with scores of 9 to 12 are classified as a moderate TBI, and those with scores of 13 to 15 are classified as a mild TBI. “Evaluate”, “diagnosis”, “determinant”, “found”, “discriminate”, detection” and “establish” are interchangeably used for diagnosis. “Subject” and “individual” are interchangeably when used for a Human individual.

As used herein, the terms "comprising," "including," "containing", "composition" "consisting" and "characterized by" are interchangeable, inclusive, open-ended and do not exclude additional, methods or procedural steps.

The terminology used herein is for the purpose of describing specific embodiments only and is not intended to be limiting of the invention. As used in this document, the singular forms “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise. Unless defined otherwise, all technical and scientific terms used herein have the same meanings as commonly understood by one of normative skill in the art.

“Detecting,” “measuring”, or “taking a measurement” defines a quantitative or qualitative determination of the amount or level or concentration of the biomarker in the sample.

As used herein, the terms “treatment”, “therapeutic effect,” “therapeutic activity” or “therapeutic action” refer to the mitigation, amelioration, and/or stabilization of symptoms and signs, as well as a delay in the progression of symptoms and signs of a particular disorder, through the use of some external drug, device, technology or others.

As used herein, a “reference value” of a biomarker is a relative value, an absolute value, a range of values, a value that has an upper and/or lower limit, an average value, a median value, a mean value, a value as compared to a control or baseline value or a combination thereof.

As used herein, a “time of day window”, when referring to times in which samples are taken, means a period of time defined via a window start time and a window stop time.

As used herein, “biomarker panel” defines a set of biomarkers used alone, in combinations, or in sub combinations for the detection, diagnosis, prognosis, treatment or monitoring of a disease or condition, based on detection values for the set of biomarkers. The biomarkers within the panel of biomarkers used herein include t-tau, p-tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein- 1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3.

Matrix metalloproteinases (MMPs) are extracellular enzymes that are concerned with the pathophysiology of the blood-brain barrier (BBB) breakdown, contusion expansion, and vasogenic edema after traumatic brain injury (TBI). Matrix metalloproteinases (MMPs) are a family of over 20 extracellular endopeptidases which cleave a wide range of protein substrates in diverse signaling pathways (Nagase H, Visse R, Murphy G. Structure and function of matrix metalloproteinases and TIMPs. Cardiovasc. Res. 2006; 69: 562-573). More particularly, the subfamily of gelatinases, MMP-2 and MMP-9, have been concerned as important mediators of proteolytic blood-brain barrier (BBB) interruption, linked with traumatic injury, ischemia, and neuroinflammatory disorders (Hadass O., Tomlinson B.N., Gooyit M., Chen S., Purdy J.J., Walker J.M., Zhang C., Giritharan A.B., Purnell W., Robinson C.R., Shin D., Schroeder V.A., Suckow M.A., Simonyi A., Sun G.Y., Mobashery S., Cui J., Chang M., and Gu Z. Selective inhibition of matrix metalloproteinase-9 attenuates secondary damage resulting from severe traumatic brain injury. PLoS One. 2013; 8: e76904).

Traumatic brain injury (TBI) frequently develops conditions which promote secondary injury propagation (Rose J, Valtonen S, Jennett B. Avoidable factors contributing to death after head injury. Br Med J. 1977; 2: 615-618). The significance of the hypoxic or ischemic lesion in the mechanism of TBI is evident as is the inflammatory process taking place after the primary lesion (Prins RM, Liau LM. Immunology and immunotherapy in neurosurgical disease. Neurosurgery. 2003; 53: 144-152.). In these processes, the increase of pro- inflammatory cytokines such as the production of interleukin-6 (IL-6) is evident (Heesen M, Deinsberger W, Dietrich GV, Detsch O, Boldt J, Hempelmann G. Increase of interleukin-6 plasma levels after elective craniotomy: influence of interleukin- 10 and catecholamines.

Acta Neurochir (Wien) 1996; 138: 77-80). Also, IL-6 acts as a cellular mediator for immunological responses and can be produced in response to inflammatory events in the central nervous system (Heesen M, Deinsberger W, Dietrich GV, Detsch O, Boldt J, Hempelmann G. Increase of interleukin-6 plasma levels after elective craniotomy: influence of interleukin- 10 and catecholamines. Acta Neurochir (Wien) 1996; 138: 77-80).

Tau is a 48- to 68-kDa protein which stabilizes microtubular assembly. It is enriched in the axons of neurons (Goedert M, Spillantini MG, Jakes R, Rutherford D, Crowther RA. Multiple isoforms of human microtubule-associated protein tau: sequences and localization in neurofibrillary tangles of Alzheimer’s disease. Neuron 1989; 3:519— 526). It is cleaved into fragments of 10-18 kDa and 30-50 kDa in response to cellular injury. Furthermore, injuries can lead to the phosphorylation of tau (Simic' G, Babic' Leko M, Wray S, Harrington C, Delalle I, JovanovMilosevic' N, Bazadona D, Buee L, de Silva RD, Giovanni G, Wischik C, Hof PR. Tau protein hyperphosphorylation and aggregation in Alzheimer’s disease and other tauopathies, and possible neuroprotective strategies. Biomolecules. 2016; 6: 6, doi: 10.3390/biom6010006). Serum tau levels were increased in mTBI (Bulut M, Koksal O, Dogan S, Bolca N, Ozguc H, Korfali E, Ilcol YO, Parklak M. Tau protein as a serum marker of brain damage in mild traumatic brain injury: preliminary results. Adv Ther. 2006; 23: 12- 22).

Occludin is a tight junction protein which maintains the endothelial blood brain barrier (BBB), as a reliable biomarker with high serum concentrations and a broad temporal profile.

ApoA-I is a 28kDa apolipoprotein mainly produced in the small intestine and liver (Rader DJ. Molecular regulation of HDL metabolism and function: implications for novel therapies. J. Clin. Invest. 2006; 116: 3090- 3100). It is the main protein component of high density lipoprotein particles which play a vital role in reverse cholesterol transport. ApoA-I is a negative biomarker of inflammation, decreasing more than 25% during sepsis and burns (Van Lenten BJ, Reddy ST, Navab M, and Fogelman AM. Understanding changes in high density lipoproteins during the acute phase response. Arterioscler. Thromb. Vase. Biol. 2006;26: 1687- 1688.). ApoA-I is considered to function in the transport of lipids and interacts with the blood-brain barrier in a fashion analogous to apoE in the brain (Yu C, Youmans KL, LaDu MJ. Proposed mechanism for lipoprotein remodelling in the brain. Biochim. Biophys. Acta 2010; 1801: 819-823). Monocyte chemotactic protein- 1 (MCP-1, also referred to as chemokine ligand 2 CCL-2) is a small chemoattractant cytokine produced by phagocytes and endothelial cells which attracts immune cells, chiefly monocytes, to sites of inflammation. Non-inflamed tissues express little to no MCP-1, but inflamed tissues show MCP-1 -positive cells in numbers that correlate to the severity of the inflammation (Blennow K, Hardy J, Zetterberg H. The Neuropathology and Neurobiology of Traumatic Brain Injury. Neuron. 2012; 76(5): 886- 99).

Copeptin levels are elevated in severe medical conditions, an effect that is recognized to be due to elevated arginine vasopressin levels in response to physiological stress, resulting in activation of the hypothalamus-pituitary-adrenal axis.

Galectin-3 has different functions depending on cell type and cellular location. It is found inside the nucleus and the cytosol and is released extracellularly upon exposure to definite stimuli such as lipopolysaccharide (LPS) or IFNy (Burguillos MA. et al. Microglia- Secreted Galectin-3 Acts as a Toll-like Receptor 4 Ligand and Contributes to Microglial Activation. Cell Rep. 2015; pii: S2211-1247:00140-0). Galectin-3 acts as a regulator during the inflammatory response in neurodegenerative diseases.

Human kallikrein 6 (hk6) is a serine protease with high brain and spinal cord expression, particularly in oligodendrocytes (Shaw JL, Diamandis EP: Distribution of 15 human kallikreins in tissues and biological fluids. Clin Chem. 2007; 53(8): 1423- 32). It has been evident that hK6 linked to brain-related disorders such as spinal cord injury, and might offer a protective role in myelin repair (Scarisbrick IA, Sabharwal P, Cruz H, et al.: Dynamic role of kallikrein 6 in traumatic spinal cord injury. Eur J Neurosci. 2006; 24(5): 1457-69.).

Prostaglandin D synthase (PS) is a highly expressed enzyme which is 3% of the total protein in cerebrospinal fluid (Gonzalez -Rodriguez PJ, Li Y, Martinez F, et al.: Dexamethasone protects neonatal hypoxic-ischemic brain injury via L-PGDS-dependent PGD2 -DPI - pERK signaling pathway. PLoS One. 2014; 9(12): el 14470). PS plays an important role in hypoxic- ischemic brain injury (Taniguchi H, Mohri I, Okabe-Arahori H, et al.: Early induction of neuronal lipocalin-type prostaglandin D synthase after hypoxic-ischemic injury in developing brains. Neurosci Lett. 2007; 420(1): 39-44).

Leptin is a 16 kDa protein secreted predominantly via white adipose tissue which regulates neuroendocrine function, energy homeostasis, inflammatory response and metabolism (Kelesidis T, Kelesidis I, Chou S, Mantzoros CS. Narrative review: The role of leptin in human physiology: emerging clinical applications. Ann Intern Med. (2010) 152:93-100.). It is released from adipocytes which might cross the blood brain barrier (BBB) to regulate different functions in the central nervous system such as synaptic plasticity and spatial learning and memory.

Up until this time, no study has been conducted on salivary t-tau, p-tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein- 1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3 levels for the risk analysis, early detection, diagnosis, treatment, management, monitoring and prognosis mTBI and TBI.

Contrasting recently reported tests, which utilized proteins released from damaged neurons or glia and others cells or tissues, etc, the diagnostic test described herein, for concussion or mTBI, was developed based on a novel combination of salivary biomarkers with high sensitivity and specificity. Further described are compositions and methods for laboratory methods, test kits, field tests, smart assayst and point- of-care tests for measuring biomarkers in a sample from a subject. Astonishingly, such high accuracy is not affected by any others diseases in the subject, resulting in high sensitivity and specificity of these biomarkers in identifying mTBI.

Saliva samples were collected from each subject. Ten minutes prior to the collection of unstimulated saliva samples, subjects were asked to rinse orally with water. At the time of sample collection, subjects were asked to relax for 5-15 minutes. They were then seated in a bent forward position in an ordinary chair and asked to put their tongues on the lingual surfaces of the upper incisors and allow the saliva to drip into sterile plastic (glass) tubes treated with 50 g of 2% sodium azide solution to prevent microbial decomposition of saliva. The tubes were held to the lower lip for 10 minutes resulting in a collection of 1-5 ml of saliva per individual. Saliva samples were then centrifuged using a Sorvall RT6000D centrifuge (Sorvall, Minn.) at 1800 rpm for 5 minutes to remove debris and were immediately frozen at 80° C. awaiting further analysis.

The compositions and methods described herein detail the invention of a process for detection of a novel combination of salivary biomarkers and biomarker complexes which allow for detection, screening or diagnosis of concussion or mTBI.

Production of these proteins, such as t-tau, p-tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein-1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3 is changed in response to mTBI. These changes lead to changes in salivary levels of these proteins, which are detectable using a variety of different assays, methods and other analysis systems known to those with skill in the art.

The biomarkers used herein to predict, diagnose, detect, treat or monitor mTBI may be measured using any process known to those with skill in the art including, but not limited to, enzyme linked immunosorbent assay [ELISA], fluorescence polarization immunoassay (FPIA) and homogeneous immunoassays as well as point of care tests using conventional lateral flow immunochromatography (LFA), quantitative point of care tests using determination of chemiluminescence, fluorescence, and magnetic particles, latex agglutination, biosensors, gel electrophoresis, gas chromatograph-mass spectrometry (GC- MS), nanotechnology, immunoassay, separation immunoassays, heterogeneous immunoassays, homogenous immunoassays, paper-based microfluidic devices (Yetisen AK, Akram MS, Lowe CR. Paper-based microfluidic point-of-care diagnostic devices. Lab Chip. 2013; 13(12): 2210-51), enzyme- linked immunosorbent assay (ELISA), indirect ELISA, sandwich ELISA (Tahara T, Usuki K, Sato H, Ohashi H, Morita H, Tsumura H, Matsumoto A, Miyazaki H, Urabe A, Kato T. A sensitive sandwich ELISA for measuring thrombopoietin in human serum: serum thrombopoietin levels in healthy volunteers and in patients with haemopoietic disorders. Br J Haematol. 1996 ; 93(4): 783-8.), competitive ELISA (EP0202890 A2), multiplex ELISA, western blotting, protein immunoblot, mass spectrometry (MS), electrospray ionization (ESI), matrix-assisted laser desorption/ionization (MALDI), protein microarray, protein chip, multiplex detection assay, DNA microarray, SAGE, multiplex PCR, multiplex ligation-dependent probe amplification, LUMINEX®/XMAP®, aptamer-based assay, SOMASCAN® assay, LUMINEX®-based immunoassay, enzyme immunoassays, radioimmunoassays, chemiluminescent assays, microfluidic or MEMS technologies, re- engineering technologies (e.g. instruments utilizing sensors for biomarkers used for telemedicine purposes), epitope -based technologies, other fluorescence technologies, microarrays, lab-on-a-chip, and rapid point-of-care screening technologies. These technologies include qualitative or quantitative measurement of the levels of mTBI biomarkers in a biological sample such as saliva. For example, as shown in Example I below, biomarkers may be identified using an ELISA test specific for the biomarker(s) of interest.

At least one of the biomarkers is an important target for therapeutic intervention in mTBI. The approach described herein is completely different from the conventional approach of identifying salivary biomarkers for mTBI, which focus on nervous system proteins released by damaged or traumatic brain cells.

The compositions and methods described herein constitute a combination of biomarkers, which includes, but is not limited to, the following proteins t-tau, p-tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein- 1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3, and any combination thereof. The panel of these biomarkers distinguishes mTBI patients from normal healthy subjects. Salivary levels of at least two biomarkers are changed beyond the cutoff values in 75 to 86 % of mTBI patients, while 0 to 5% of healthy controls have changes in salivary levels of each of the two biomarkers.

Accordingly, provided herein is a method for identifying concussion or traumatic brain injury ii including mild, moderate or severe forms. The method comprises steps involving taking a test sample from a subject, where the sample includes a bodily fluid, especially saliva; completing a reaction in vitro by contacting the test sample with a binding agent which forms a complex and detecting the complex. The change in the level of the complex, including t-tau, p-tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein- 1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3 etc. compared to a healthy control indicates mild (concussion), moderate or severe traumatic brain injury. One, or two, or more than two of the biomarkers described herein (t-tau, p-tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein-1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3) are also identified as clinical targets; e.g., inhibition of any one or two of the biomarkers leads to clinical improvement of a subject having been diagnosed with mild (concussion), moderate or severe traumatic brain injury.

According to the embodiments of the present invention, a machine learning system or Digital enzyme-linked immunosorbent assay point of care system for detection t-tau, p-tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein- 1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3 may also be utilized for the early detection, diagnosis, prognosis, treatment and management mTBI. In other embodiments of the present invention, a point of care technology incorporating a microfluidic spatial-spectral encoding method with a machine learning-based image processing algorithm covering single, two, more than two or multiplex -biomarker detection may be used. The spatial-spectral encoding method confines color-encoded magnetic beads or gold nanoparticles or other nanoparticles such as silver particles into the arrayed pattern of microwells on a microfluidic chip. The locations of the microwell patterns on the chip or lines on the point of care technologies show which target analytes are detected via attentive color- coded beads.

In other embodiments of the present invention, a machine learning system or Digital enzyme- linked immunosorbent point of care system needs a sample volume less than 20 LIL or less than 10 pL, a 2 min or 5-min or 10 min assay incubation time and a 50 mm x 50 mm chip size or standard point of care parameters.

In other embodiments of the present invention, a machine learning system or Digital enzyme- linked immunosorbent point of care system includes a dual-pathway parallel-computing algorithm based on convolutional neural network (CNN) visualization for image processing.

The term therapeutically effective dosage, as used herein, refers to an amount of a pharmaceutical agent to treat or improve an identified disease or condition, or to show a detectable therapeutic or inhibitory effect, such as mitigation or amelioration of symptoms. The effect can be detected or estimated by known methods present in the current art. The invention here also provides a method of treating mild (concussion), moderate or severe traumatic brain injury, by administering an inhibitor of any of the biomarkers; t-tau, p-tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein- 1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B- 100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3. Those skilled in the art will realize that it is occasionally necessary to make routine variations to the dosage depending on age, route of administration and condition of the patient such as age, weight, and clinical condition of the recipient patient, etc.

The following studies are provided to illustrate the invention, but are not intended to limit in any way the scope of the invention.

Example 1: To determine whether the biomarkers t-tau, p- tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein-1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3 levels after sports-related concussion (SRC) relate to return to play (RTP).

Materials and methods: Informed and written consents were taken from each participant. Matched sex and age of athletes with sports-related concussion (SRC) and athlete controls (AC) were selected. Sixty [60] sporting athletes were selected and saliva sampling and cognitive testing were performed before the sports season of Kabaddi, and were followed for a diagnosis of SRC. SRC was assessed by a field certified athletic trainer and concussion and using the Sport Concussion Assessment Tool 2 (McCrory P, Meeuwisse W, Johnston K, et al. Consensus statement on concussion in sport: the 3rd international conference on concussion in sport held in Zurich, November 2008. J Athletic Train 2009; 44: 434-448). Saliva sampling was performed on two control groups; 30 athlete controls (AC) without concussion and 30 healthy non-athlete controls (NAC), without a history of head injuries, at the same time lines as specimens were taken from SRC athletes. The athletes and controls had gone through Immediate Post Concussion Assessment and Cognitive Testing (ImPACT) and Balance Error Scoring System (BESS) following the date of the concussion. Head injury history was estimated by the Ohio State Traumatic Brain Injury Identification Method (Corrigan JD, Bogner J. Initial reliability and validity of the Ohio State University TBI identification method. J Head Trauma Rehabil 2007; 318-329). Return to play (RTP) for each athlete was assessed by both the athletic trainers and sports team physicians. The NCAARTP guidelines were followed to assess RTP. Saliva samples were obtained at the following time points: within one hour of injury, within 6 hours, after two days, four days, one week and two weeks after injury.

Saliva samples were collected from each subject. Ten to fifteen minutes prior to collection of unstimulated saliva samples, subjects were asked to rinse orally with water. At the time of sample collection, each subject was asked to relax for 5-15 minutes. They were then seated in a bent forward position in an ordinary chair and asked to put their tongues on the lingual surfaces of the upper incisors and to allow saliva to drip into sterile plastic (glass) tubes treated with 50 g of 2% sodium azide solution, to prevent microbial decomposition of saliva constituents. The tubes were held to the lower lip for 10 minutes resulting in a collection of 1- 5 ml of saliva per individual. Saliva samples were then centrifuged using a Sorvall RT6000D centrifuge (Sorvall, Minn.) at 1800 rpm for 5 minutes to remove debris and were then immediately frozen at-80° C, awaiting further analysis. Salivary t-tau, p-tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein- 1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3 were analyzed by using ELISA kits. Salivary MMP-9 was estimated by using the Biotrak ELISA system (Amersham Biosciences, Bucks, UK). Salivary IL-6 was measured by using ELISA kits (American Research Products and R&D Systems, USA).

Salivary occludin was estimated by using ELISA (OCLN ELISA Kit, Aviva, USA). hk6 levels were estimated using ELISA kits (Wisent Bioproducts, Quebec, Canada) and PS was also estimated using ELISA kits (Cayman Chemical, Ann Arbor, MI, USA). Salivary t-tau and p-tau levels were estimated using Luminex assays (Shi M, Bradner J, Hancock AM, Chung KA, Quinn JF, Peskind ER, Galasko D, Jankovic J, Zabetian CP, Kim HM, Leverenz JB, Montine TJ, Ginghina C, Kang UJ, Cain KC, Wang Y, Aasly J, Goldstein DS, Zhang J. Cerebrospinal Fluid Biomarkers for Parkinson Disease Diagnosis and Progression. Ann Neurol. 2011; 69: 570-580) with slight changes to the protocol to minimize the medium effect in saliva and to allow for better accuracy. In brief, 50 pl of saliva was treated by using 0.24% Triton X-100 for 50 minutes on ice, followed by diluting 100 pl with the diluent from the INNO-BIA AlzBio3 kit (Innogenetics, Gent, Belgium) before integration with the coating beads and the revealing antibody. A total of 20-30 pl of the diluent was added to all background and standard wells to make the total volume (125-130 pl) equivalent between samples. All samples were estimated using a LiquiChip Luminex 200™ Workstation (Qiagen, Valencia, CA, USA). Salivary ApoA-I was estimated using Apolipoprotein Al (AP0A1) Human ELISA Kits (abeam, UK). Salivary monocyte chemotactic protein- 1 was estimated using assay kits on the BioPlex 200 by multiplex immunochemistry according to the manufacturer’s instructions. Salivary copeptin values were estimated using an automated immunofluorescent assay (BRAHMS CT -pro A VP KRYPTOR, Thermo Scientific Biomarkers, Hennigsdorf, Germany). Salivary galectin-3 was estimated using an ELISA assay kit (Abeam Human Galectin-3 ELISA kit (AB119525, Cambridge, UK). Data were analyzed using the Statistical Package for the Social Sciences (SPSS version 22; IBM Corporation, Armonk, NY).

Results: Both the Athlete Controls (AC) and non-athletic controls (NAC), as well as the athletes with SRC, did not significantly differ in demographic variables (Table 1).

Within the SRC group, there were no differences in the sport played, or history of concussion, whether based on long RTP (n=25) or short RTP (n =35). Both athlete groups had significantly higher t-tau, p-tau, matrix metalloproteinases-9, IL-6, galectin-3, monocyte chemotactic protein levels, haptoglobin, leptin, apolipoprotein B-100, tyrosine kinase 2 and IL36A levels while lower occludin, copeptin, hk6, PS, ApoA-I, protein S100-A12, ATP synthase subunit beta and lysine deficient protein kinase 3 levels, compared to NAC (p= 0.005, Table 2A and 2B) at baseline, as well as at all other time points. Also, the SRC group had significantly t-tau, p-tau, matrix metalloproteinases-9, IL-6, galectin-3, monocyte chemotactic protein levels, haptoglobin, leptin, apolipoprotein B-100, tyrosine kinase 2 and IL36A levels while lower occludin, copeptin, hk6, PS, ApoA-I, protein S100-A12, ATP synthase subunit beta and lysine deficient protein kinase 3 levels compared to AC (p= 0.005, Table 2). The SRC group with prolonged RTP showed higher t-tau, p-tau, matrix metalloproteinases-9, IL-6, galectin-3, monocyte chemotactic protein levels, haptoglobin, leptin, apolipoprotein B-100, tyrosine kinase 2 and IL36A levels while lower occludin, copeptin, hk6, PS, ApoA-I, protein S 100-A12, ATP synthase subunit beta and lysine deficient protein kinase 3 levels at one hour after injury, within 6 hours after injury and after two days post-SRC, as compared to the SRC group with short RTP. Conclusions: Salivary t-tau, p-tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein- 1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3 act as screening, detection, diagnostic or treatment biomarkers for mTBI. Higher t-tau, p-tau, matrix metalloproteinases-9, IL-6, galectin-3, monocyte chemotactic protein levels, haptoglobin, leptin, apolipoprotein B-

100, tyrosine kinase 2 and IL36A levels while lower occludin, copeptin, hk6, PS, ApoA-I, protein S100-A12, ATP synthase subunit beta and lysine deficient protein kinase 3 levels at 6 hours after injury are predictive of RTP. This suggests that levels of t-tau, p-tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein- 1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3 may help in the determination of timing of RTP.

Table 1: Characteristics of study participants Table 2 A: Salivary biomarkers (t-tau, p-tau, matrix metalloproteinases -9, occludin, IL- 6, copeptin, galectin-3, monocyte chemotactic protein-1, ApoA-I, hk6, and prostaglandin D2 synthase (PS)) in sports-related concussions (SRC) using athlete controls (AC) and healthy non-athlete control (NAC) subjects.

Table 2 B: Salivary biomarkers (haptoglobin, leptin, apolipoprotein B-100, protein S100- A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3) in sports-related concussions (SRC) using athlete controls (AC) and healthy non-athlete control (NAC) subjects.

Example 2: A panel of salivary biomarkers for screening, detection, diagnosis and treatment of mTBI, or concussion.

A total of 80 athletic subjects were selected, 40 of whom had sustained a sports -related concussion (SRC), 20 athletic control subjects without sports-related concussions and/or other injury (AC) and 20 athletic subjects with only bone fractures (BF). The characteristics of the subjects are shown in Table 3. Saliva samples were taken from each subject and salivary biomarkers were measured as in Example 1. Data were analyzed as in Example 1. In brief, to find out the diagnostic value of biomarkers that can discriminate between mTBI and control subjects, receiver operating characteristics (ROC) curves were generated and the area under the curve (AUC), together with its 95% confidence interval (CI), were estimated for each ROC curve.

Results: A two to four-fold increase in salivary levels of t-tau, p-tau, matrix metalloproteinases-9, IL-6, galectin-3, monocyte chemotactic protein levels, haptoglobin, leptin, apolipoprotein B-100, tyrosine kinase 2 and IL36A, and a two to four-fold decrease in salivary levels of occludin, copeptin, hk6, PS, ApoA-I, protein S100-A12, ATP synthase subunit beta and lysine deficient protein kinase 3 levels were found in mTBI patients within 6 hours after SRC as compared to the AC control subjects.

The levels of at least two salivary biomarkers were changed above the established cutoff values in 91% of mTBI patients (Table 4 A and 4B). Furthermore, levels of salivary galectin-3 and occludin were increased in the BF population in comparison to those in the SRC group.

Conclusions: Salivary t-tau, p-tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein- 1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3 act as detection, screening, diagnostic, or treatment biomarkers of mTBI. Salivary galectin-3 and occludin can be used successfully to discriminate mTBI from facture injury. Salivary biomarkers such as t-tau, p- tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein- 1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B- 100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3 have been identified as satisfactory biomarkers for screening, diagnosis and treatment of concussion. Some of or all of these (t-tau, p-tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein- 1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3) are targets for therapeutic intervention. Salivary biomarkers described in this invention are easily and satisfactorily quantified using standard ELISA methodologies.

These salivary biomarkers can also be measured using fluorescence polarization immunoassay (FPIA) and homogeneous immunoassays, point of care tests using conventional lateral flow immunochromatography (LFA), quantitative point of care tests incorporating chemiluminescence, fluorescence, and magnetic particles, latex agglutination, biosensors, gel electrophoresis, gas chromatograph-mass spectrometry (GC-MS), nanotechnology, standard immunoassays separation immunoassays, heterogeneous immunoassays, homogenous immunoassays, paper-based microfluidic devices, indirect ELISA, sandwich ELISA, competitive ELISA, multiplex ELISA, western blotting, protein immunoblot, mass spectrometry (MS), electrospray ionization (ESI), matrix-assisted laser desorption/ionization (MALDI), protein microarray, protein chip, multiplex detection assay, DNA microarray, SAGE, multiplex PCR, multiplex ligation-dependent probe amplification, LUMINEX®/XMAP®, aptamer-based assay, SOMASCAN® assay, LUMINEX® -based immunoassay, enzyme immunoassays, radioimmunoassays, microfluidic or MEMS technologies, re-engineering technologies (e.g. instruments utilizing sensors for biomarkers used for telemedicine purposes), epitope -based technologies, other fluorescence technologies, microarrays, lab- on-a-chip, and rapid point-of-care screening technologies not described above

Table: 3 Characteristics of subjects

Table: 4 A Diagnostic value of salivary biomarkers in mTBI

Table: 4 B Diagnostic value of salivary biomarkers in mTBI

Example 3: Analysis of the accuracy of a combination biomarker panel of t-tau, p-tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein-1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3 for the diagnosis of and discrimination between mTBI and controls.

Statistical comparison of the two populations (by the combination of the salivary biomarkers in Examples 1 and 2) was performed using the two-tailed t-test using GraphPad Prism for Windows, v 5.01 (GraphPad Software, San Diego, Calif.). Receiver operating characteristic curves (ROC) were generated using R (R Foundation for Statistical Computing, Vienna, Austria). Reference levels used are those described in Tables 2 A and B and 4 A and 4B.

Salivary biomarker concentrations were compared among the three groups using an ANOVA, with a Bonferroni post hoc test at all 6 time points by using the data from examples 1 to 3. Area under the curve (AUC) using a receiver operating characteristic analysis was also used to determine the screening ability of salivary biomarkers at each time point to predict the appropriate group, that is, the area under the receiver operating characteristic curve (AUC) was calculated in order to determine the prognostic accuracy of the salivary biomarkers.

Data were analyzed using the Statistical Package for the Social Sciences (SPSS version 22; IBM Corporation, Armonk, NY.). The best biomarkers were selected based on higher sensitivity and specificity characteristics of greater than 70%. The combinations of the best two biomarkers were calculated and are illustrated in Table 5 A. Two biomarkers were chosen and each of these biomarkers was evaluated separately and in combination to evaluate the capability of these biomarkers to identify mTBI in the control and

SRC subjects. The data are presented in Table 5A.

Table 5 A: ROC analysis and diagnostic performance for various biomarker combinations (Salivary t-tau, p-tau, matrix metalloproteinases-9, IL-6, galectin-3 and monocyte chemotactic protein (MCP-1), occludin, copeptin, ApoA-I, PS and hk6) for the diagnosis of and discrimination between mTBI and controls Table 5 B: ROC analysis and diagnostic performance for various biomarker combinations [ (Salivary t-tau, p-tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein-1, ApoA-I, hk6, prostaglandin D2 synthase (PS)) (A) , haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3) for the diagnosis of and discrimination between mTBI and controls

Results and conclusions: ROC analysis established diagnostic sensitivity and specificity for mTBI as shown in Table 5 A and 5B. The combination models of t-tau, p- tau, MMP-9, copeptin, galectin-3 and occluding (table 5C) indicate higher diagnostic values for the diagnosis of mTBI in comparison to other combination models.

Table 5 C Area Under the Curve for Distinguishing Between mTBI and Controls

Example 4: Evaluation of the Reproducibility and Stability of Salivary Biomarkers:

Saliva samples from 10 athletes with sport-related concussion (SRC) and 10 athlete control subjects (AC) were taken (samples collected as in Example 1). The specimens were randomly arranged and labeled such that the laboratories could not identify the individuals sampled. For each analysis, the assay reproducibility of blinded quality control replicates was examined using the coefficient of variation (CV), a commonly used statistical analysis technique to describe laboratory technical error, and a determination was made of the effect of delayed sample processing on analyte concentrations in frozen samples at -80 degrees C (at 24 hours, 7 days and 14 days after sampling; i.e. the reproducibility obtained with delayed processing of the specimens). Reproducibility was assessed over a one week and two week period for salivary biomarkers, by taking samples at 7 days and 14 days, without any treatment of the specimens. The CV was determined by estimating the SD (standard deviation) of the quality control values, divided by the mean of these values, multiplied by 100. Inter-observer and intra-observer variances were estimated from repeated sample measurements using a random effects model, with sample identification number as the random variable.

To assess reproducibility, the ICCs (Intra-class Correlation Coefficients) were calculated by dividing the intra-observer variance by the sum of the within- and inter-observer variances; 95% confidence intervals (CI) were also calculated. The inter- and intra- observer CVs were determined by taking the square root of the inter and intra observer variance components from the random effects mixed model on the In [log] transformed scale, with approximate estimates derived by the eta method (Rosner B. Fundamentals of biostatistics. Belmont, Calif.: Duxbury; 2006). An ICC of <0.40indicates poor reproducibility, 0.40 to 0.8 indicates fair to good reproducibility, and more than 0.8 indicates excellent reproducibility. Results are shown in Tables 6 and 7.

Table 6: ICCs Calculated for Delayed Analysis and Processing of a Single Frozen Sample at Day 1, Day 7 and Day 14 for salivary biomarkers in various subjects. Table 7: Calculated ICCs for saliva samples tested at various time points (day 1, day 7 and dDay 14) for all subjects

Results and conclusions: The ICCs for the range of salivary biomarkers were high (ICCs; 0.87-0.93), indicating good to excellent reproducibility and stability. Example 5: Digital enzyme-linked immunosorbent point of care assay system for the detection of t-tau, p-tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin- 3, monocyte chemotactic protein-1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3 for the early detection, diagnosis, prognosis, treatment and management mTBI .

Described herein is a novel system or device, which integrates a small footprint point of care test system that minimizes the number of images which are required to read the results and completely automates the signal counting or image process. The analysis incorporates a point of care or microfluidic spatial-spectral encoding method and a machine learning-based image processing algorithm compatible with single or two, two or more or a multiplex biomarker detection system. The spatial-spectral encoding method confines color-encoded magnetic beads or gold nanoparticles or other nanoparticles such as silver particles into the arrayed patterns of microwells on a microfluidic chip. The locations of the microwell patterns on the chip or lines on the point of care technology show which target analytes are detected via attentive color-coded beads. In such cases the sample volume requirement is less than 20 pL or less than 10 p L, involving a 2 minute, 5 minute or 10 minute assay incubation time and a 50 mm x 50 mm chip size or standard point of care test system. Based on a convolutional neural network (CNN), the machine learning algorithm permits unsupervised image data analysis. This novel platform permits the simultaneous quantification of a large panel of biomarkers or one biomarker, two or more biomarkers, or more than two biomarkers in half an hour without sacrificing accuracy of the downstream assay.

Microfluidic chip and Point of Care Platform

It consists of two compact laser diodes for multicolour fluorescence imaging and a white light-emitting diode for bright-field transmission imaging having a sample holder with three- dimensional movement and alignment of the inserted sample, an optomechanical connection to the mobile phone, or any smart phone or ipad, outfitted with an external lens module providing a half-pitch resolution of 0.4-0.98 mm2 and an imaging field of view of 0.4-0.9 mm2.

The microfluidic chip is fabricated using polydimethylsiloxane based soft lithography. The chip consists of parallel sample detection channels (10- 25) on a glass substrate, each with an array of hexagonal biosensing patterns. The hexagonal shape allows each biosensing pattern to densely pack 40,501 fL-sized microwells into a very small area, which encompasses the entire field of view of a full-frame CMOS sensor through a lOx objective lens. Magnetic beads or nanoparticles deposited are encoded with non-fluorescent color and color into physically separated microwell arrays. The beads [or nanoparticles used] are previously conjugated to different capture antibodies (t-tau, p-tau, matrix metalloproteinases -9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein-1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3) as per the specific colors and locations on the chip. In the current design, the arrangement of 2 to three colors and 10 biosensing patterns in each detection channel allows the technology to detect 2 x 10 = 20 protein species (20-plex) at its maximum capacity for each sample loaded onto the detection channel. The pre-deposition guarantees a fixed number of beads or nanoparticles to target each biomarker, which provides more accurate digital counting for each biomarker. The microwell structure has been designed to generate sufficient surface tension to hold beads in the microwells.

A unique challenge posed by highly multiplexed digital assays is to provide fast and accurate analysis of fluorescence signals originating from more than 5 million microwells per chip or more than 7 million line per lateral flow immunochromatographic test strip. In addition, the signal counting process distinguishes accurately between images of multi-colors or different grey scales or bead-filled systems in addition to empty microwells and also identifies signals accurately while subjected to a large fluorescence intensity variance, occasional image defects due to reagent mishandling, and image focus shifts. This method is in essence, a novel dualpathway parallel-computing algorithm based on convolutional neural network (CNN) visualization for image processing. The CNN-based analysis procedure includes multi-color fluorescence image data read-in or pre-processing features including image crop, noise filtering, and contrast enhancement, microwell or and bead image segmentation via pretrained dual-pathway CNN, post-processing, and result output. The architecture of the network is divided into a down sampling process for category classification and an up sampling process for pixel segmentation. The down sampling process consists of three layers, including two convolution layers i.e. 5 to 10 filters, with a rectified linear unit, and a maxpooling layer in between. The up sampling process consists of a transposed convolution layer with rectified linear unit, a softmax layer and a pixel classification layer. In the Al training process, the system will be divided into an image with 32 x 32 pixels, classifying them with labels and then eventually expanding the image pixel size to 256 x 256 using a pre-trained network. This will resolve the large intensity variance across the optical signals from beads in different microwell reactors or different lines such as the test and control lines on lateral flow point of care devices. Microwells or different lines are lithographically patterned to have an identical size, labeled them using the same prefixed area scale. The majority of pixel labels are for the background label 4 with no assay information in typical digital assay images to enhance the classification accuracy, giving more weight to less frequently appearing classes that are identified via labels I, II, and III

Table 8 A. Limit of Quantification (LOQ) of t-tau, p-tau, matrix metalloproteinases-9, IL-6, galectin-3 and monocyte chemotactic protein (MCP-1), occludin, copeptin, ApoA-I, PS and hk6.

Table 8 B. Limit of Quantification (LOQ) of haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3 Al work flows

A convolutional neural network-guided image processing algorithm for high throughput and accurate single molecule counting.

Image input

Preprocessing

Dual pathway CNN

Pathway A Pathway B

Image Target

Defect Signal

Recognition Recognition

Generating an output mask for post data processing.

Analysis of the bright field image using a Sobel edge detection algorithm.

The images were overlaid to estimate the fraction of enzyme active beads emitting to total beads for each color label.

Conclusions: Digital enzyme-linked immunosorbent point of care assay system for the detection of t-tau, p-tau, matrix metalloproteinases-9, occludin, IL-6, copeptin, galectin-3, monocyte chemotactic protein- 1, ApoA-I, hk6, prostaglandin D2 synthase (PS), haptoglobin, leptin, apolipoprotein B-100, protein S100-A12, ATP synthase subunit beta, tyrosine kinase 2, IL36A and lysine deficient protein kinase 3 with lower detection limit is 0.3-3.2 pg/ml ( table

8 A and 8 B) for the early detection, diagnosis, prognosis, treatment and management mTBI.