SALIVARY BIOMARKERS OF BRAIN INJURY

FIELD

The present invention relates to compositions, kits, systems and methods for diagnosing and/or monitoring brain injury, including, without limitation, traumatic brain injury (TBI). More particularly, the present invention relates to the diagnosis and monitoring of TBI using RNA biomarkers.

BACKGROUND

Traumatic brain injury (TBI) is the leading cause of death and disability under the age of 45 years in Western countries. Its healthcare burden and social costs are expected to continue to rise and, by 2020, the World Health Organization projects TBI to become the third leading cause of disability worldwide.

Despite many studies, no reliable biomarkers have been found to assess the severity of TBI and predict recovery. This is especially true for mild TBI (mTBI), which remains currently difficult to assess in clinical practice. Although TBI patients are initially assessed by the Glasgow Coma Score (GCS) and neuroimaging techniques, which require costly equipment, the current diagnostic tools are lacking in the ability to precisely define and quantify the actual severity of the brain injury, thus leading to an easy detection of severe but not of mTBI, which represents the vast majority of cases (75-90%).

The correct diagnosis of mTBI is particularly important in patients, such as athletes, soldiers and children, who are at greater risk of repetitive mTBI and a catastrophic form of brain injury known as second impact syndrome (SIS) where the synergistic effects of repeated TBI result in profound damage and even death. Early diagnosis and evaluation of the severity of TBI thus becomes crucial for patients' wellbeing and ultimately saving their life.

The subject technology was devised with these issues in mind.

SUMMARY

The disclosure provides methods and detection systems relating to diagnosing, monitoring, and treating traumatic brain injury (TBI) including mild traumatic brain injury (mTBI) in a human subject who has suffered an injury to the head by detecting one or more miRNA molecules in a biological sample from the subject. In the context of the following disclosure, the terms ‘level’ and ‘amount’ in reference to the level or amount of an miRNA molecule or molecules in a biological sample are used interchangeably.

In one aspect, the disclosure relates to a method of diagnosing and treating traumatic brain injury (TBI) in a human subject in need thereof. The method involves: obtaining a saliva sample from the subject; contacting the saliva sample with a probe comprising a nucleic acid able to bind to at least one RNA biomarker: (a) selected from the group consisting of hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-16-1-3p, hsa-miR-339-5p, hsa-miR-497-5p, put-miR-1204, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-469, put-miR-594, put-miR-856, put-miR-893, put-miR-958, RNU4-6p, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.168, U6.601, UC022CJG1, YRNA-245, and YRNA-684, or any combination thereof, and/or (b) selected from the group consisting of put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-468, put-miR-476, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-92, put-miR-961, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, U6.1249, U6.375, U6.428, and YRNA-255, or any combination thereof; determining an amount of the at least one RNA biomarker in the saliva sample; identifying the subject as having TBI where the amount of the at least one RNA biomarker is increased or decreased relative to a predetermined threshold value or relative to the amount of the RNA biomarker in a control sample; and treating the subject identified as having TBI according to one or more of the following: subjecting the subject to a verbal, cognitive, motor, or optical test, or any combination of the foregoing; subjecting the subject to diagnostic imaging in the form of a CT or MRI, or a combination thereof; and/or administering to the subject one or more neuroprotective therapies.

In certain embodiments of this method, the at least one RNA biomarker further comprises one or more miRNA: (a) selected from the group consisting of hsa-let-7i-5p, hsa-miR-107, hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-148a-3p, hsa-miR-206, hsa-miR-29c-3p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-671-3p, hsa-miR-6748-3p, and hsa-miR-934, or any combination thereof, and/or (b) selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-miR-103a-3p, hsa-miR-21-5p, and hsa-miR-92a-3p, or any combination thereof.

In another aspect, the present disclosure relates to a method of diagnosing and/or monitoring traumatic brain injury (TBI) in a subject. This method involves: determining a level of at least one RNA biomarker in a saliva sample obtained from the subject, wherein the at least one RNA biomarker: (a) selected from the group consisting of hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-16-1-3p, hsa-miR-339-5p, hsa-miR-497-5p, put-miR-1204, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-469, put-miR-594, put-miR-856, put-miR-893, put-miR-958, RNU4-6p, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.168, U6.601, UC022CJG1, YRNA-245, and YRNA-684, or any combination thereof; and/or (b) selected from the group consisting of put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-468, put-miR-476, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-92, put-miR-961, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, U6.1249, U6.375, U6.428, and YRNA-255, or any combination thereof.

In one embodiment of this method, the at least one RNA biomarker further comprises one or more miRNA: (a) selected from the group consisting of hsa-let-7i-5p, hsa-miR-107, hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-148a-3p, hsa-miR-206, hsa-miR-29c-3p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-671-3p, hsa-miR-6748-3p, and hsa-miR-934, or any combination thereof, and/or (b) selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-miR-103a-3p, hsa-miR-21-5p, and hsa-miR-92a-3p, or any combination thereof.

In another aspect, the present disclosure relates to a sensor element for a detection system for diagnosing and/or monitoring TBI, the sensor element comprising a substrate functionalized with a probe specific for at least one RNA biomarker: (a) selected from the group consisting of hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-16-1-3p, hsa-miR-339-5p, hsa-miR-497-5p, put-miR-1204, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-469, put-miR-594, put-miR-856, put-miR-893, put-miR-958, RNU4-6p, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.168, U6.601, UC022CJG1, YRNA-245, and YRNA-684, or any combination thereof; and/or (b) selected from the group consisting of put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-468, put-miR-476, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-92, put-miR-961, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, U6.1249, U6.375, U6.428, and YRNA-255, or any combination thereof.

In one embodiment of the sensor element, the at least one RNA biomarker further comprises one or more miRNA: (a) selected from the group consisting of hsa-let-7i-5p, hsa-miR-107, hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-148a-3p, hsa-miR-206, hsa-miR-29c-3p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-671-3p, hsa-miR-6748-3p, and hsa-miR-934, or any combination thereof; and/or (b) selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-miR-103a-3p, hsa-miR-21-5p, and hsa-miR-92a-3p, or any combination thereof.

In another aspect, the present disclosure relates to a detection system for diagnosing and/or monitoring TBI, comprising: a sensor element according to the present disclosure, and a detection device capable of detecting the binding of a target RNA biomarker to the probe.

In another aspect, the present disclosure relates to a method for determining a course of action for a subject suspected of having TBI, comprising applying a saliva sample obtained from the subject to a detection system according to the present disclosure, and if an upregulated level or a downregulated level of the at least one RNA biomarker is detected, providing a treatment for TBI.

In another aspect, the present disclosure relates to a method of treating a subject with suspected TBI. This method involves: determining whether an upregulated level or a downregulated level of at least one RNA biomarker: (a) selected from the group consisting of hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-16-1-3p, hsa-miR-339-5p, hsa-miR-497-5p, put-miR-1204, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-469, put-miR-594, put-miR-856, put-miR-893, put-miR-958, RNU4-6p, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.168, U6.601, UC022CJG1, YRNA-245, and YRNA-684, or any combination thereof and/or (b) selected from the group consisting of put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-468, put-miR-476, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-92, put-miR-961, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, U6.1249, U6.375, U6.428, and YRNA-255, or any combination thereof, is detectable in a saliva sample obtained from the subject, and if an upregulated level or a downregulated level of at least one RNA biomarker is detected, providing treatment for TBI to the subject.

In one embodiment of this method, the at least one RNA biomarker further comprises one or more miRNA: (a) selected from the group consisting of hsa-let-7i-5p, hsa-miR-107, hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-148a-3p, hsa-miR-206, hsa-miR-29c-3p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-671-3p, hsa-miR-6748-3p, and hsa-miR-934, or any combination thereof and/or (b) selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-miR-103a-3p, hsa-miR-21-5p, and hsa-miR-92a-3p, or any combination thereof.

In another aspect, the present disclosure relates to a method of detecting an RNA biomarker in a saliva sample. This method involves: obtaining a saliva sample from a human subject, contacting the saliva sample with at least one oligonucleotide primer complementary to at least one RNA biomarker: (a) selected from the group consisting of hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-16-1-3p, hsa-miR-339-5p, hsa-miR-497-5p, put-miR-1204, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-469, put-miR-594, put-miR-856, put-miR-893, put-miR-958, RNU4-6p, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.168, U6.601, UC022CJG1, YRNA-245, and YRNA-684, or any combination thereof; and/or (b) selected from the group consisting of put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-468, put-miR-476, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-92, put-miR-961, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, U6.1249, U6.375, U6.428, and YRNA-255, or any combination thereof, amplifying the at least one RNA biomarker using a polymerase chain reaction; and detecting the amplified RNA biomarker.

In one embodiment of this method, the at least one RNA biomarker further comprises one or more miRNA: (a) selected from the group consisting of hsa-let-7i-5p, hsa-miR-107, hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-148a-3p, hsa-miR-206, hsa-miR-29c-3p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-671-3p, hsa-miR-6748-3p, and hsa-miR-934, or any combination thereof and/or (b) selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-miR-103a-3p, hsa-miR-21-5p, and hsa-miR-92a-3p, or any combination thereof.

In another aspect, the present disclosure relates to a kit for use in a method of diagnosing and/or monitoring traumatic brain injury (TBI) in saliva from a human subject, the kit comprising at least one probe specific for at least one RNA biomarker: (a) selected from the group consisting of hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-16-1-3p, hsa-miR-339-5p, hsa-miR-497-5p, put-miR-1204, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-469, put-miR-594, put-miR-856, put-miR-893, put-miR-958, RNU4-6p, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.168, U6.601, UC022CJG1, YRNA-245, and YRNA-684, or any combination thereof and/or (b) selected from the group consisting of put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-468, put-miR-476, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-92, put-miR-961, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, U6.1249, U6.375, U6.428, and YRNA-255, or any combination thereof.

In one embodiment of this kit, the at least one RNA biomarker further comprises one or more miRNA: (a) selected from the group consisting of hsa-let-7i-5p, hsa-miR-107, hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-148a-3p, hsa-miR-206, hsa-miR-29c-3p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-671-3p, hsa-miR-6748-3p, and hsa-miR-934, or any combination thereof and/or (b) selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-miR-103a-3p, hsa-miR-21-5p, and hsa-miR-92a-3p, or any combination thereof.

In another aspect, the present disclosure relates to a composition for use in a method of diagnosing and/or monitoring traumatic brain injury (TBI) in saliva from a human subject, the composition comprising at least one probe specific for at least one RNA biomarker: (a) selected from the group consisting of hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-16-1-3p, hsa-miR-339-5p, hsa-miR-497-5p, put-miR-1204, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-469, put-miR-594, put-miR-856, put-miR-893, put-miR-958, RNU4-6p, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.168, U6.601, UC022CJG1, YRNA-245, and YRNA-684, or any combination thereof; and/or (b) selected from the group consisting of put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-468, put-miR-476, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-92, put-miR-961, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, U6.1249, U6.375, U6.428, and YRNA-255, or any combination thereof.

In one embodiment of this composition, the at least one RNA biomarker further comprises one or more miRNA: (a) selected from the group consisting of hsa-let-7i-5p, hsa-miR-107, hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-148a-3p, hsa-miR-206, hsa-miR-29c-3p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-671-3p, hsa-miR-6748-3p, and hsa-miR-934, or any combination thereof and/or (b) selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-miR-103a-3p, hsa-miR-21-5p, and hsa-miR-92a-3p, or any combination thereof.

DETAILED DESCRIPTION

The present invention provides methods of diagnosing or monitoring traumatic brain injury (TBI) in a subject, as well as methods for treating a subject identified as suffering from TBI.

The quest for TBI biomarkers has received significant impetus by the increased profile of sport concussion in the media. In the last few years many studies have focused on biomarkers that can support clinical decision making pitch-side or in a sports clinic. However, protein biomarkers reported in the literature lack specificity or sensitivity, or are not detectable for some time after injury. This may be due to the fact that following concussion, which is a form of TBI, brain-derived compounds are only released in very small amounts and the blood-brain barrier remains mostly closed.

MicroRNAs (miRNAs) are an abundant class of highly conserved, non-coding RNA molecules of approximately 22 nucleotides in length that induce mRNA degradation, translational repression or both via pairing with partially complementary sites in the 3′UTR of target genes. The human genome encodes over 2,000 miRNAs, which may target about 60% of all genes. However, despite the abundance of miRNAs, their biomolecular functions and involvement in pathology remain to be fully elucidated. They play a central role in many biological processes including cell cycle, cell metabolism, apoptosis and immune responses, and are attracting increasing interest in clinical research as potential biomarkers for the detection, identification and classification of cancers and other disease states including neurodegenerative diseases.

For the avoidance of doubt, it will be understood that “the at least one miRNA is selected from a group of miRNAs”, as used herein, means that the method in question, whether carried out for a diagnostic, prognostic, or therapeutic purpose, can be carried out with any one of the listed miRNAs or with any plurality of the listed miRNAs (e.g., two, three, four, or more of the listed miRNAs). It follows that any one or more of the listed miRNAs may be explicitly excluded.

Traumatic brain injury occurs when an external force traumatically injures the brain. There are different systems for classifying TBI based on, for example, severity, type of injury and prognosis. The most commonly used system for classifying TBI is the Glasgow Coma Scale (GCS), which grades a person's level of consciousness on a scale of 3-15 based on verbal, motor, and eye-opening reactions to stimuli. In general, a TBI with a GCS score of 13 or above is defined as mild, 9-12 as moderate and 8 or below as severe. Another system, the Mayo Classification System, has three main classifications including definite moderate-severe TBI, probable mild TBI, and possible TBI. Multiple criteria are used in each diagnosis including loss of consciousness, post-traumatic amnesia, skull fracture, and evidence of neuroradiological abnormalities including subdural haematoma, cerebral contusion, and hemorrhagic contusion. The classification of TBI using the GCS or Mayo systems will be known to those skilled in the art.

As used herein, references to “mild”, “moderate” and “severe” TBI are made in accordance with the GCS. References herein to “moderate-to-severe” TBI encompass both moderate and severe TBI in accordance with the GCS.

As used herein, a reference to mild TBI (mTBI) is also a reference to concussion.

The diagnosis and/or monitoring of TBI using the biomarkers of the present invention is expected to support clinical decision making and treatment regimens in a variety of contexts, including the following situations: as part of the initial assessment by paramedics to determine whether patients should be transported to a facility with neurosurgical expertise, a major trauma centre or a local trauma unit; in the emergency department of hospitals to determine appropriate treatment, including the need for a CT brain scan; pitch-side, to assist decision making as to the removal of a player from play and assessment of the need to take a player to hospital; in sports clinics, to confirm a concussive event and enable decision making with regard to returning to play; in combat situations, to determine the need to dispatch a rescue team and evacuate a victim. Thus, subjects for whom the present invention provides particular benefit can include, without limitation, accident victims, sports players, and military personnel.

In any case, but perhaps particularly where the subject is at greater risk for a TBI (e.g., where the subject is a professional athlete or enlisted in the military), a sample may be obtained from the subject at a time prior to any known or recent trauma (e.g., near the beginning of a sporting career or prior to a military deployment) and any miRNAs of interest can be assessed at that time or later, when the subject has experienced a possible TBI. Such samples may thereby provide an internal reference standard.

In some embodiments, the subject is human.

The TBI may be mild TBI (mTBI), moderate TBI or severe TBI (sTBI). In some embodiments, the TBI is moderate-to-severe TBI (m-sTBI).

The level of the miRNA or of each miRNA in the sample may be determined quantitatively or semi-quantitatively. By “quantitatively”, it will be understood that the absolute amount or concentration of the miRNA or of each miRNA in the sample is determined. The absolute amount of the miRNA or of each miRNA in the sample can then be compared to a predetermined threshold (e.g. a published literature value for expected normal levels), a known level of the same or a reference miRNA in a control sample taken from a healthy subject, or the amount of a reference miRNA in the sample taken from the subject. In some embodiments, the subject is diagnosed as having a TBI when the level of the miRNA is below the predetermined threshold, or decreased relative to a reference or control sample. In other embodiments, the subject is diagnosed as having a TBI when the level of the miRNA is increased compared to the predetermined threshold.

By “semi-quantitatively”, it will be understood that the level of the or each miRNA of interest is measured relative to a reference.

The reference may be an invariant miRNA, i.e. a miRNA having an expression level that remains substantially unchanged between healthy subjects and those having a TBI. A subject may be diagnosed as suffering from a TBI if the level of the miRNA or of each miRNA of interest is increased or decreased relative to that of an invariant miRNA.

In some embodiments, the level of the miRNA or of each miRNA in the sample obtained from the subject may be about 0.01 times to about 100 times, about 0.05 times to about 50 times, about 0.1 times to about 10 times, about 0.5 times to about 5 times, about 1.0 to about 3 times, or about 1.5 times to about 2.0 times lower or higher than the level in the control sample, the reference level or the published value.

Where a device or method is employed to generate a value, we may qualify that value with the term “about” in order to capture the stated value and any variation of that value inherent to the device or method employed. Where values or ranges of values are specifically disclosed, “about” may mean plus-or-minus 10% of the stated value or range. For example, about 10 minutes may mean 9-11 minutes.

The level of the miRNA or of each miRNA of interest can be determined using methods known to those skilled in the art. In some embodiments, determining the level of the miRNA or of each miRNA of interest comprises amplifying the miRNA. In some embodiments, total miRNA may be first isolated from the sample using standard techniques, for example using the miRNeasy mini kit (Qiagen). The amount of the miRNA of interest can then be determined. In some embodiments, the level of the miRNA or of each miRNA of interest in the sample is determined using PCR (polymerase chain reaction). For example, quantitative PCR may be used for quantitative determination of the level of the miRNA or of each miRNA of interest. PCR may also be used for semi-quantitative determination, by comparing the level of the miRNA or of each miRNA of interest in the sample with that of a reference (e.g. an invariant miRNA).

Suitable techniques for miRNA detection and/or quantification, which will be known to those skilled in the art, include qPCR, miRNA assays, next-generation sequencing (NGS), and multiplex miRNA profiling assays.

In some embodiments, the level of the miRNA or of each miRNA of interest is determined using in-situ hybridization, for example using a probe (e.g., a labelled probe) specific for the miRNA.

The level of miRNA may be determined in a sample which was obtained from the subject immediately after injury (i.e. less than 1 hour after injury), and/or in a sample obtained at one or more time points a few hours or days after injury. Thus, changes in the miRNA level can be detected over time to enable monitoring of a TBI. In the event miRNA levels change over time, the methods described herein for monitoring TBI can be expanded to include maintaining or adjusting the subject's treatment regimen accordingly.

Depending on the specific miRNA and the type of TBI, the level of miRNA in the subject may change significantly over time. In some embodiments, it may therefore be advantageous to measure the miRNA relatively soon after injury to enable an accurate diagnosis. In some embodiments, the level of miRNA is determined in a sample obtained from the subject no more than 72 hours, no more than 48 hours, no more than 36 hours, no more than 24 hours, no more than 12 hours, no more than 6 hours, no more than 4 hours, no more than 2 hours or no more than 1 hour after injury.

The level of some miRNAs is substantially stable over time, thus allowing a diagnosis to be made a few hours, days or even weeks after injury. In some embodiments, the level of miRNA is determined in a sample obtained from the subject up to 20, 18, 15, 12, 10, 8, 5 or 2 days from injury.

In some embodiments, the level of miRNA is determined in a sample obtained from the subject immediately after injury (e.g. at T=0 h), at 4-12 hours after injury, at 48-72 hours after injury, or at 15 days after injury.

In some embodiments, the level of miRNA is determined in a sample obtained from the subject at least 24 hours after injury. In some embodiments, the level of miRNA is determined in a sample obtained from the subject 15 days or fewer after injury. In some embodiments, the level of miRNA is determined in a sample obtained from the subject between 24 hours and 15 days after injury, or between 24 hours and 10 days after injury, or between 24 hours and 7 days after injury, or between 48 hours and 5 days after injury.

In some embodiments, the TBI is mild TBI (mTBI) or moderate-to-severe TBI (m-sTBI).

In some embodiments, the TBI is mild TBI (mTBI).

Conveniently the sample may be any appropriate fluid or tissue sample obtained from the subject. For example, the biological sample may comprise at least one of the group consisting of: urine, saliva, whole blood, plasma, serum, sputum, semen, faeces, a nasal swab, tears, a vaginal swab, a rectal swab, a cervical smear, a tissue biopsy, and a urethral swab. In some embodiments the sample is a fluid sample. Suitably, the sample is one that can be readily obtained from the individual, such as urine, saliva, blood and sputum. In some embodiments, the sample comprises saliva, blood, plasma or serum. It will be appreciated that in some embodiments the process of obtaining the sample does not form part of the invention described herein.

In some embodiments, the sample comprises or is constituted by serum. Not only does serum have practical advantages, but it is also free of anticoagulants such as heparin, a potential inhibitor of PCR reactions. Serum may also be less affected by haemolysis, compared to plasma.

In some embodiments, the sample is saliva. Saliva can be easily obtained from the patient (e.g. pitch-side, or in the field), without specialist training or medical equipment.

The diagnosis of a subject as suffering from a TBI, and in particular diagnosis of mild TBI or moderate-to-severe TBI, may facilitate in the determination of an appropriate treatment. The present invention thus provides a test that enables healthcare workers, such as physicians, clinicians, paramedics, and even non-medical personnel (e.g. teachers, sports coaches, military personnel) to decide on appropriate action for a subject suspected of having a TBI. A subject determined as having a TBI may therefore receive the most appropriate treatment as a result of a diagnosis being made. The method of the invention may thus further comprise directing appropriate therapy to a subject diagnosed with a TBI.

A subject diagnosed with TBI may be further evaluated, e.g. by CT scanning. In some embodiments, the subject is admitted to hospital. In some embodiments, if moderate-to-severe TBI can be ruled out, the subject may not need to be admitted to hospital for evaluation. A subject diagnosed with moderate-to-severe TBI may be admitted to hospital, or a specialist centre with neurotrauma expertise.

A subject diagnosed with a TBI (particularly mTBI) outside a hospital environment, for example, at a sporting event, during combat or during play, may be removed from play or combat immediately. The subject may subsequently be started on a graduated return to play or combat.

In a further aspect, there is provided a method for determining whether it is appropriate to administer to a subject a therapy for alleviating TBI, the method comprising: determining a level of at least one miRNA in a sample from the subject; and determining whether or not it is appropriate to administer a therapy for alleviating TBI, based on the level of the at least one miRNA.

It will be appreciated that the step of administering the therapy to the subject does not form a part of the claimed method, unless specifically stated.

In some embodiments the method may further comprise administering to the subject an appropriate treatment. In some embodiments, the treatment may comprise a therapy for alleviating TBI. Accordingly, the invention features methods of diagnosing and treating TBI in a subject, the method comprising the steps of (a) obtaining a sample (e.g., a sample of blood, plasma, urine, or saliva) from the subject; (b) detecting one or more miRNAs (selected from those described herein); diagnosing the patient as having a TBI when the level(s) of the miRNA(s) differ from a reference standard (as described herein); and administering a treatment for the TBI.

In a further aspect, the invention provides a method of determining an appropriate treatment to a subject suspected of suffering from a TBI, the method comprising identifying whether or not the subject has a TBI by determining a level of at least one miRNA in a sample from the subject.

If a subject is identified as having a TBI, an appropriate treatment may include one or more of the following: further evaluating the subject, for example by further tests (e.g. verbal, cognitive, motor and/or optical tests), CT and/or Mill scanning; removing the subject from activity (e.g. the activity during which the TBI was incurred); admitting the subject to hospital or a specialist clinic; surgery; and administering a therapy for alleviating TBI to the subject.

The therapy for alleviating TBI may include neuroprotective drugs, e.g. drugs to treat cerebral swelling such as mannitol and hypertonic saline, and/or other neuroprotective measures, such as avoidance of hypertensive resuscitation and the use of sedation.

In some embodiments, the subject may be subsequently monitored to track their recovery, for example in a hospital or clinic setting.

According to a further aspect of the invention, there is provided a method of detecting and/or determining a level of a target miRNA in a subject, the method comprising the steps of (a) obtaining a sample from the subject; and (b) detecting and/or determining the level of the target miRNA in the sample by contacting the sample with a probe that is specific for the target miRNA.

The sample may be any appropriate fluid or tissue sample obtained from the subject, as defined above. In some embodiments, the sample is blood, serum, plasma, urine or saliva.

In some embodiments, the method may comprise determining the level of two or more target miRNAs in the sample.

According to a further aspect of the invention, there is provided a therapy for alleviating TBI for use in a method of treating a subject in need thereof, wherein said subject is identified as having a TBI by determining a level of at least one miRNA in a sample from the subject.

The step of determining the level of the target miRNA may comprise contacting the sample with a substrate functionalized with the probe, for example a chip comprising the probe. The substrate or chip may conveniently include multiple probes, each specific for a different target miRNA.

The subject may have suffered an injury, in particular a head injury. The subject may be suspected as having a TBI. The subject may be suspected of having mTBI or concussion. In some embodiments, the sample is obtained no more than 72 hours, no more than 48 hours, no more than 36 hours, no more than 24 hours, no more than 12 hours, no more than 6 hours, no more than 4 hours, no more than 2 hours or no more than 1 hour after injury. In some embodiments the sample is obtained 24 hours or more after the injury. In further embodiments the sample is obtained from the subject 15 days or fewer after injury. In some embodiments the sample is obtained from the subject between 24 hours and 15 days after injury, or between 24 hours and 10 days after injury, or between 24 hours and 7 days after injury, or between 48 hours and 5 days after injury.

In some embodiments, the method further comprises treating the subject. The treatment may include one or more of the following: further evaluating the subject, for example by further tests (e.g. verbal, cognitive, motor and/or optical tests), CT and/or MRI scanning; removing the subject from activity (e.g. the activity during which the TBI was incurred); admitting the subject to hospital or a specialist clinic; and administering a therapy for alleviating TBI to the subject. In some embodiments, the treatment comprises administering an effective amount of a neuroprotective drug.

Thus, in yet a further aspect the invention provides a method of treating TBI, the method comprising: determining a level of at least one miRNA in a sample from the subject; and if the level of the at least one miRNA is indicative of mTBI, administering a treatment appropriate for mTBI; or if the level of the at least one miRNA is indicative of m-sTBI, administering a treatment appropriate for m-sTBI.

It will be appreciated by those skilled in the art that different treatment pathways may be used for mTBI and m-sTBI.

A subject with mTBI may be treated as follows:

An athlete diagnosed with mTBI would typically be started on a graduated return to play protocol (as defined by the Berlin Consensus Conference on Concussion and individual sport authorities, e.g. RFU, IRB, NFL, NHL, NBA, IMMAF). This would involve a period of rest followed by a gradual increase in level of exertion and exposure to contact. An athlete with mTBI would typically not be able to play for a period that varies between 6 and 23 days, depending on level of medical supervision and age. Conversely, if mTBI was excluded, the athlete would not have any restrictions and could train as normal the following day. If diagnosed in a pre-hospital setting, mTBI would be an indication for a patient to seek medical attention (e.g. in hospital or in primary care), whereas, if mTBI was excluded no medical review would be indicated.

A person with mTBI must not be left unsupervised for 24-48 hours and must not drive or operate a fork lift or open machinery until recovered.

Military personnel diagnosed with mTBI would be removed from the operational theatre and would be rested, whereas, if mTBI could be excluded, that person would continue on active duties.

In the NHS, a person with mTBI may be kept in hospital for observation or may have a CT scan according to the guidance issued by NICE, whereas if mTBI could be excluded, that patient could be discharged straightaway.

A person diagnosed with mTBI would typically be asked not to return to work or study for a certain period of time.

A person diagnosed with mTBI may be referred to a mild TBI clinic or a neurology clinic or a neurosurgery clinic. Typical interventions for mTBI consist of education, advice in regard to work, study and driving, medical management of typical sequelae such as headache or anxiety or mood disorder or post-traumatic stress disorder with medication and/or psychological intervention if necessary, and referral to other services as indicated, e.g. neuropsychology, neurovestibular or ophthalmology.

A patient with mTBI would need to be monitored for delayed post-traumatic pituitary dysfunction according to the guidance issued by the Society of British Neurological Surgeons.

In the medico-legal context, the diagnosis of mTBI is often unclear and speculative, as the radiological investigations are typically normal and symptoms are non-specific. Objective confirmation of mTBI may lead to an award for damages and care needs. An appropriate treatment for mTBI may include: removing the subject from activity; treatment in situ or in the community; further evaluating the subject in hospital without overnight admission (typically mTBI patients are discharged with promptly with head injury advice); or admission to hospital for a period of observation (typically 1-2 days). The subject may be further evaluated using tests (e.g. verbal, cognitive, motor and/or optical tests). CT scanning is generally only required if certain indications are present, including suspected skull fracture, post-traumatic seizure, focal neurological defecit, repeated vomiting, a GCS score of less than 13 on initial assessment (less than 14 for children, or less than 15 for infants under 1 year), in accordance with NICE guidelines.

An appropriate treatment for m-sTBI may include: MRI or CT scanning (particularly within 1 hour of injury); admission to hospital (which may include admission to intensive care and/or transfer to a specialist clinic or major trauma centre with neurosurgical facilities); neuromonitoring; surgery; administering a therapy for alleviating TBI, such as administering neuroprotective drugs, e.g. drugs to treat cerebral swelling such as mannitol and hypertonic saline, and/or other neuroprotective measures, such as avoidance of hypertensive resuscitation and the use of sedation.

Thus, the present invention enables subjects with a TBI to be clinically and quickly stratified into mTBI or m-sTBI, so that they may receive the most appropriate treatment.

According to a further aspect of the invention, there is provided a detection system for diagnosing and/or monitoring TBI, the detection system comprising a sensor element comprising a substrate functionalized with a probe specific for a target miRNA The detection system can further comprise a detection device that is capable of detecting the binding of a target miRNA to the probe.

According to a yet further aspect of the invention, there is provided a sensor element for use in a detection system for diagnosing and/or monitoring TBI, the sensor element comprising a substrate functionalized with a probe specific for a target miRNA.

The sensor element may further comprise a sample addition zone for receiving a sample (e.g. a fluid sample) thereon.

The probe is capable of selectively binding the miRNA of interest. The substrate may be functionalized with a plurality of probes. The probes may all be the same, or two or more different probes may be provided. For example, in some embodiments, the substrate may be functionalized with a first probe specific for a first miRNA, and a second probe specific for a second miRNA. The first and second probes may be grouped together, for example on different portions of the sensor element.

In a further aspect of the invention, there is provided a composition for use in a method of diagnosing and/or monitoring traumatic brain injury (TBI) in a subject, the composition comprising a probe specific for a target miRNA. The composition may comprise any one of the listed miRNAs or with any plurality of the listed miRNAs (e.g., two, three, four, or more of the listed miRNAs).

The probe may comprise a biological molecule such as a protein (e.g. an antibody) or a nucleic acid. In some embodiments, the probe comprises a nucleic acid. The nucleic acid may comprise a sequence which is at least 70%, at least 75%, at least 80%, at least 85%, at least 90% or at least 95% identical to a sequence which is the complement of the full-length sequence of the target miRNA. In some embodiments, the nucleic acid comprises a sequence which is 100% identical to a sequence which is the complement of the sequence of the target miRNA (i.e. the receptor comprises a nucleic acid sequence which is the exact complement of the target miRNA sequence).

The probes may be attached to a surface of the substrate by any suitable means, such as by coupling chemistry known to those skilled in the art. In some embodiments, each probe is attached to a surface of the substrate via a linker. In some embodiments, the probe comprises a moiety for immobilizing the probe on the substrate, or for attaching the probe to a linker immobilized on the substrate.

Alternatively or in addition, the probe may comprise a detectable label. The detectable label may be, for example, radioactive, fluorescent, luminescent, or antibody-based (e.g., it may constitute a conventional tetrameric antibody or a detectable fragment thereof).

The substrate of the sensor element may be formed from any suitable material. In some embodiments, the substrate comprises or is formed from metal, plastic, glass, silica, silicon, graphite, graphene, or any combination thereof. In some embodiments, the substrate comprises multiple layers. For example, a substrate may be prepared by forming a surface or layer of graphene on a layer of silicon carbide or silica. The graphene surface may be chemically modified, for example to graphene-oxide (GO) or graphene-amine (GA). Methods for forming graphene layers, such as epitaxial growth and sublimation growth, will be known to those skilled in the art.

Conveniently, probes comprising or constituted by a nucleic acid can be attached to a GO surface via a linker, using an amide coupling reagent (e.g. (O-(7-azabenzotriazole-1-yl)-N,N,N,N′-tetramethyluronium hexafluorophosphate (HATU)). A sensor element comprising a surface functionalized with a nucleic acid probe can then be used to selectively detect its complementary miRNA.

Suitable linkers may comprise an aniline moiety (or a derivative thereof), a benzoic acid moiety (or a derivative thereof) or an ethendiamine moiety (or a derivative thereof). An aniline linker may be formed by attaching a nitrobenzene molecule (or derivative) to a graphene surface (e.g. using a diazonium salt), and reducing the nitrobenzene to aniline. The amine group of the aniline may then be used to attach to the probe. Similarly, a diazonium salt (e.g. 4-benzoic acid diazonium tetrafluoroborate) can be used to attach a benzoic acid or benzoic acid derivative to a graphene surface. An ethanediamine moiety may be attached to carboxylated graphene or graphene oxide.

The sensor element may be comprised within a test strip. The test strip may be disposable.

The detection device may be configured to detect the binding of a target miRNA to the receptor by any suitable means known to those skilled in the art, for example by detecting changes in electrical impedance, hydrogen ion concentration, or conformational changes resulting from hybridisation.

The detection device may further include a user interface to output data to a user.

In some embodiments, the detection device includes a database of treatment information. The device may be capable of identifying suitable treatment options from the database depending on the levels of the miRNA of interest. The treatment information may be provided to the user via the user interface.

Conveniently, the detection device may be portable, e.g. hand-held. The detection device may comprise a data storage unit for storing miRNA levels and other information relating to the subject. In some embodiments, the device comprises a data communication means for communicating data to other devices. For example, the device may communicate data wirelessly through WiFi, 3G, 4G, Bluetooth, or through a mobile app. This may conveniently enable the data to be easily accessed by medical professionals if necessary.

It is thus envisaged that the detection device of the invention provides an affordable, portable, point of care means for diagnosing and monitoring TBI non-invasively. The device may be used by ambulance crews, the military, schools, sports clubs and healthcare professionals, enabling the correct assessment and triage of patients suspected to have a TBI.

A further aspect of the present invention is a system for detecting and/or monitoring mTBI in a subject.

A type of detection system is based on complementarity between a target miRNA and a nucleic acid probe, generally an oligonucleotide probe. The complementary or base pairing region can be 7 or 8 or more nucleotides in length. In embodiments the complementary or base pairing region can be 9, 10, 12, 15 or more nucleotides in length or the complementary or base pairing region can be the full length of the miRNA. The substrate functionalised with an oligonucleotide can be a bead or a nanoparticle. The detection system can have further components capable of converting bound nucleic acid probe-miRNA into a detectable signal.

Another type of detection system is based on RT-PCT. Therefore the present invention embraces a detection system for detecting and/or monitoring mTBI in a subject comprising a primer pair designed for amplification of a cDNA complement of at least one miRNA described herein.

In a further aspect there is provided a kit for use in the present methods. The kit may comprise at least probe (e.g. a protein, such as an antibody, or a nucleic acid) which is capable of selectively binding the miRNA of interest. In some embodiments, the kit comprises an array comprising a plurality of probes. In some embodiments, the at least one probe is a primer for carrying out PCR. The kit may further comprise instructions for use, for example instructions for use in the diagnosis and/or monitoring of TBI. The kit may further comprise suitable buffers and reagents, such as amplification primers and enzymes (e.g. DNA polymerase, reverse transcriptase for conversion of miRNA to cDNA).

Additional Aspects and Embodiments

In further aspects, the present disclosure provides, inter alia, methods, sensor elements, detection systems, kits, and compositions involving various differentially expressed RNA biomarkers suitable for use in diagnosing, monitoring, and treating traumatic brain injury (TB), including mild traumatic brain injury (mTBI), in a human subject.

The sequences and accession numbers for these RNA biomarkers are provided in Table 1 below:

TABLE 1

RNA Biomarker
Sequence
Accession No.

put-miR-410
ggagaatagaacatgctgatt (SEQ ID No. 70)

put-miR-1306
ataacgtcatctagtgtg (SEQ ID No. 71)

put-miR-806
cacgagagaacgcacacc (SEQ ID No. 72)

put-miR-71
gaccttgggttgggtcgtggt (SEQ ID No. 73)

put-miR-468
ataaggaactgctctctc (SEQ ID No. 74)

put-miR-476
gtggtcaggtagagaa (SEQ ID No. 75)

put-miR-293
gggtaaaactgcagtgggcgttggtag (SEQ ID No. 76)

put-miR-742
cagggctgtgctaact (SEQ ID No. 77)

put-miR-6
gcggaccttgctcaagg (SEQ ID No. 78)

put-miR-1207
gtgaaaagacataggggg (SEQ ID No. 79)

put-miR-1084
aggaccattgcgttgcc (SEQ ID No. 80)

put-miR-92
agagactgactttgagta (SEQ ID No. 81)

put-miR-188
aaatggcgatactcagg (SEQ ID No. 82)

put-miR-1352
tggattgtgggggaacc (SEQ ID No. 83)

put-miR-1146
caactgtaagtccatt (SEQ ID No. 84)

put-miR-209
ggtcctcggatcggcc (SEQ ID No. 85)

put-miR-961
tagcttgatccagttg (SEQ ID No. 86)

put-miR-1080
tgtggattgatgctct (SEQ ID No. 87)

put-miR-750
caagagatgaggaatg (SEQ ID No. 88)

put-miR-1003
tggacttcagaacagc (SEQ ID No. 89)

put-miR-1098
aaggcgaaggatatgttg (SEQ ID No. 90)

hsa-miR-934
tgtctactactggagacactgg (SEQ ID No. 91)

hsa-miR-142-5p
cataaagtagaaagcactact (SEQ ID No. 92)

hsa-miR-6748-3p
tcctgtccctgtctcctacag (SEQ ID No. 93)
MIMAT0027397

hsa-miR-1271-5p
cttggcacctagcaagcactca (SEQ ID No. 94)
MIMAT0005796

hsa-miR-34b-3p
caatcactaactccactgccat (SEQ ID No. 95)
MIMAT0004676

hsa-miR-449a
tggcagtgtattgttagctggt (SEQ ID No. 96)
MIMAT0001541

hsa-miR-143-3p
tgagatgaagcactgtagctc (SEQ ID No. 48)
MIMAT0000435

hsa-miR-135b-5p
tatggcttttcattcctatgtga (SEQ ID No. 40)
MIMAT0000758

U6.428
aagattagcatgaggatgacacgcaaattcgtgaagcgttccatttc

ttt (SEQ ID No. 97)

RNU6-4
ggcccctgcacagggatgacacgcaaattcgtgaagcgttccatat

tttt (SEQ ID No. 98)

RNU6-7
ggcccctgcgcaaggatgacatgcaaattcgtgaagcgttccatatt

ttt (SEQ ID No. 99)

RNU6-6
ggcccctgtgcaaggatgacacgcaaattcgtgaagcgttccatatt

ttt (SEQ ID No. 100)

RNU6-45
ggcccttgtgcaaggatgacacgcaaattcgtgaagcgttccatatt

ttt (SEQ ID No. 101)

RNU6-73
ggcccctgtgcaaggatgacatgcaaattcgtgaagcgttccatatt

ttt (SEQ ID No. 102)

Y_RNA.255
gugucaccaacguugguauacaaccccccacaacuaaauuug

acuggcuu (SEQ ID No. 103)

U6.375
ggcccctgtgcaagaatgactcgcaaattcgtgaagcgttccatatt

ttt (SEQ ID No. 104)

U6.1249
gatggcatgacccctgatcaaggacggcatgcaaatttgtgaagta

tttc (SEQ ID No. 105)

According to an aspect of the present disclosure, there is provided a method of diagnosing and treating traumatic brain injury (TBI) in a human subject in need thereof, the method comprising: obtaining a saliva sample from the subject; contacting the saliva sample with a probe comprising a nucleic acid able to bind to at least one RNA biomarker selected from the group consisting of Y_RNA.255, RNU6-7, RNU6-4, RNU6-6, RNU6-73, RNU6-45, U6.375, put-miR-1207, U6.428, put-miR-742, hsa-miR-6748-3p, put-miR-6, put-miR-410, put-miR-476, put-miR-293, hsa-miR-34b-3p, hsa-miR-1271-5p, hsa-miR-449a, put-miR-806, put-miR-71, put-miR-468, put-miR-1306, put-miR-1146, put-miR-1084, put-miR-92, put-miR-209, put-miR-961, U6.1249, put-miR-188, put-miR-1352, put-miR-1080, put-miR-750, put-miR-1003, put-miR-1098, hsa-miR-934, and hsa-miR-142-5p; determining an amount of the at least one RNA biomarker in the saliva sample; identifying the subject as having TBI where the amount of the at least one RNA biomarker is increased or decreased relative to a predetermined threshold value or relative to the amount of the RNA biomarker in a control sample; and treating the subject identified as having TBI according to one or more of the following: subjecting the subject to a verbal, cognitive, motor, or optical test, or any combination of the foregoing; subjecting the subject to diagnostic imaging in the form of a CT or MRI, or a combination thereof; and/or administering to the subject one or more neuroprotective therapies.

Examples of neuroprotective therapies that may be chosen by a clinician for treating TBI can include, without limitation, statins, progesterone, corticosteroids, cell cycle inhibitors (such as flavopiridol, a semi-synthetic flavonoid, and purine analogs roscovitine and olomoucine), autophagy inhibitors including caspase inhibitors (such as the tetrapeptide caspase-3 inhibitor (z-DEVD-fmk), the pan-caspase peptide inhibitor Boc-aspartyl fluoromethylketone, and Boc-aspartyl fluoromethylketone), inhibitors of poly (ADP-ribose) polymerase (PARP), anti-inflammatory agents (such as minocycline and anti-inflammatory cytokines (e.g., IL-10) or interleukin-1 receptor antagonist (IL-1ra)), sulfonylurea receptor 1 (SUR1)-regulated calcium channel inhibitors (such as glibenclamide), Substance P (SP) antagonists, diketopiperazines, and cyclosporine A.

In some embodiments, the saliva sample is obtained during a period of time after injury selected from immediately after the injury to any period post-injury.

In some embodiments, the saliva sample is obtained during a period of time after injury selected from immediately after the injury until the expression level of at least one of the RNA biomarkers returns to the predetermined threshold value or to the amount of the RNA biomarker in the control sample.

In some embodiments, the saliva sample is obtained during a period of time after injury selected from immediately after the injury to up to 1 year, up to 10 months, up to 8 months, up to 6 months, up to 5 months, up to 4 months, up to 3 months, up to 2 months, up to 1 month, up to 25 days, up to 20 days, up to 15 days, up to 7 days, up to 5 days, up to 3 days, up to 2 days, and/or up to 24 hours post-injury.

In some embodiments, the saliva sample is obtained during a period of time after injury selected from immediately after the injury to 15 days, from 1 hour to 15 days, from 24 hours to 15 days, from 24 hours to 7 days, and from 2 to 5 days.

In some embodiments, the method further comprises obtaining one or more additional saliva samples from the subject at one or more additional times after the injury and repeating the detecting and amplifying steps for each additional sample.

In some embodiments, the one or more additional saliva sample is obtained during a period of time after injury selected from immediately after the injury to any period post-injury.

In some embodiments, the one or more additional saliva sample is obtained during a period of time after injury selected from immediately after the injury until the expression level of at least one of the RNA biomarkers returns to the predetermined threshold value or to the amount of the RNA biomarker in the control sample.

In some embodiments, the one or more additional saliva sample is obtained during a period of time after injury selected from immediately after the injury to up to 1 year, up to 10 months, up to 8 months, up to 6 months, up to 5 months, up to 4 months, up to 3 months, up to 2 months, up to 1 month, up to 25 days, up to 20 days, up to 15 days, up to 7 days, up to 5 days, up to 3 days, up to 2 days, and/or up to 24 hours post-injury.

In some embodiments, the one or more additional saliva sample is obtained during a period of time after injury selected from immediately after the injury to 15 days, from 1 hour to 15 days, from 24 hours to 15 days, from 24 hours to 7 days, and from 2 to 5 days.

In some embodiments, the one or more additional saliva samples is obtained at day 1, 1.5, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15 after the injury.

In some embodiments, the detecting an amount of the at least one RNA biomarker is performed using a PCR-based assay, a light array assay, a laminar flow chip assay, or any assay suitable for detecting that at least one RNA biomarker.

In some embodiments, when using the PCR-based assay the predetermined threshold is equivalent to a fold change of 1.5 or more using the 2-delta delta CT (2-ΔΔCT) method.

In some embodiments, the predetermined threshold is equivalent to a fold change of 2 or more using the 2-delta delta CT (2-ΔΔCT) method.

In some embodiments, the at least one RNA biomarker further comprises one or more miRNA selected from the group consisting of hsa-miR-143-3p and hsa-miR-135b-5p.

In some embodiments, the method further comprises identifying the human subject as being fit for normal activity after undergoing successful treatment for TBI.

In some embodiments, either an upregulated level or a downregulated level of the at least one RNA biomarker is indicative of TBI.

In some embodiments, the subject is diagnosed as having TBI if the level of the at least one RNA biomarker is either above or below a predetermined threshold or increased or decreased relative to a control.

In some embodiments, the method further comprises identifying the human subject as being fit for normal activity after undergoing successful treatment for TBI.

In some embodiments, the at least one RNA biomarker further comprises one or more miRNA selected from the group consisting of hsa-miR-143-3p and hsa-miR-135b-5p.

In some embodiments, the probe comprises a nucleic acid able to bind to the at least one RNA biomarker.

In some embodiments, the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of the sequence of the target RNA biomarker.

In some embodiments, the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of SEQ ID NO: 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, and 105.

In some embodiments, the at least one RNA biomarker further comprises one or more miRNA selected from the group consisting of hsa-miR-143-3p and hsa-miR-135b-5p.

In another aspect of the present disclosure, there is provided a detection system for diagnosing and/or monitoring TBI, comprising a sensor element according to the present disclosure, and a detection device capable of detecting the binding of a target RNA biomarker to the probe.

In some embodiments, the detection system further comprises means to determine whether the target RNA biomarker is upregulated or downregulated.

In another aspect of the present disclosure, there is provided a method for determining a course of action for a subject suspected of having TBI, comprising applying a saliva sample obtained from the subject to a detection system according to the present disclosure, and if an upregulated level or a downregulated level of the at least one RNA biomarker is detected, providing a treatment for TBI.

In some embodiments, the at least one RNA biomarker further comprises one or more miRNA selected from the group consisting of hsa-miR-143-3p and hsa-miR-135b-5p.

In some embodiments, the probe comprises a nucleic acid able to bind to the at least one RNA biomarker.

In some embodiments, the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of the sequence of the target RNA biomarker.

In some embodiments, the at least one RNA biomarker further comprises one or more miRNA selected from the group consisting of hsa-miR-143-3p and hsa-miR-135b-5p.

In some embodiments, the probe comprises a nucleic acid able to bind to the at least one RNA biomarker.

In some embodiments, the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of the sequence of the target RNA biomarker.

In some embodiments, the at least one RNA biomarker further comprises one or more miRNA selected from the group consisting of hsa-miR-143-3p and hsa-miR-135b-5p.

It will be appreciated that statements made herein in relation to any aspect of the invention may equally apply to any other aspect of the invention, as appropriate. Furthermore, the various aspects and embodiments of the present disclosure can also be used in combination with various techniques, methods, systems, compositions, devices, and/or disclosures as described in WO2017/153710A1 and WO2018/138468A1, the entire disclosures of which are hereby incorporated by reference herein.

Further Additional Aspects and Embodiments

As shown in Example 1 (below), in certain embodiments, the suitable RNA biomarkers were identified according to an MiRNA qPCR validation study performed in 176 saliva baseline samples (B); 42 samples form concussed players after injury (group Ca); 52 samples from concussed players post-match (group Cb) and 54 concussed players after 36-48 h (group Cc); 61 uninjured players post-match (group Ub); 45 uninjured players 36-48 h (group Uc); 30 musculoskeletal injury players post-match (group Mb); 24 musculoskeletal injury players 36-48 h (group Mc).

The sequences and accession numbers for these RNA biomarkers are provided in Table 2 below:

TABLE 2

miRBase
SEQ

RNA Biomarker
Sequence
Accession No.
ID NO.

hsa-let-7a-5p
ugagguaguagguuguauaguu
MIMAT0000062
106

hsa-let-7b-5p
ugagguaguagguugugugguu
MIMAT0000063
107

hsa-let-7f-5p
ugagguaguagauuguauaguu
MIMAT0000067
108

hsa-let-7i-5p
ugagguaguaguuugugcuguu
MIMAT0000415
29

hsa-miR-103a-3p
agcagcauuguacagggcuauga
MIMAT0000101
109

hsa-miR-107
agcagcauuguacagggcuauca
MIMAT0000104
39

hsa-miR-1246
aauggauuuuuggagcagg
MIMAT0005898
110

hsa-miR-126-3p
ucguaccgugaguaauaaugcg
MIMAT0000445
111

(miR-126*)

hsa-miR-126-5p
cauuauuacuuuugguacgcg
MIMAT0000444
14

(=miR-126*)

hsa-miR-135b-5p
uauggcuuuucauuccuauguga
MIMAT0000758
40

hsa-miR-142-3p
uguaguguuuccuacuuuaugga
MIMAT0000434
26

hsa-miR-142-5p
cauaaaguagaaagcacuacu
MIMAT0000433
112

hsa-miR-143-3p
ugagaugaagcacuguagcuc
MIMAT0000435
48

(=miR-143)

hsa-miR-144-3p
uacaguauagaugauguacu
MIMAT0000436
113

(miR-144*)

hsa-miR-144-5p
ggauaucaucauauacuguaag
MIMAT0004600
16

(=miR-144*)

hsa-miR-148a-3p
ucagugcacuacagaacuuugu
MIMAT0000243
27

hsa-miR-16-1-3p
ccaguauuaacugugcugcuga
MIMAT0004489
114

hsa-miR-206
uggaauguaaggaagugugugg
MIMAT0000462
115

hsa-miR-21-5p
uagcuuaucagacugauguuga
MIMAT0000076
1

hsa-miR-29c-3p
uagcaccauuugaaaucgguua
MIMAT0000681
116

hsa-miR-339-5p
ucccuguccuccaggagcucacg
MIMAT0000764
117

hsa-miR-34b-3p
caaucacuaacuccacugccau
MIMAT0004676
118

hsa-miR-425-5p
aaugacacgaucacucccguuga
MIMAT0003393
2

hsa-miR-449a
uggcaguguauuguuagcuggu
MIMAT0001541
119

hsa-miR-497-5p
cagcagcacacugugguuugu
MIMAT0002820
120

hsa-miR-671-3p
uccgguucucagggcuccacc
MIMAT0004819
23

hsa-miR-6748-3p
uccugucccugucuccuacag
MIMAT0027397
121

hsa-miR-92a-3p
uauugcacuugucccggccugu
MIMAT0000092
122

hsa-miR-934
ugucuacuacuggagacacugg
MIMAT0004977
123

put-miR-1003
tggacttcagaacagc

89

put-miR-1080
tgtggattgatgctct

87

put-miR-1084
aggaccattgcgttgcc

80

put-miR-1146
caactgtaagtccatt

84

put-miR-1204
agggctgggcacggggg

124

put-miR-1207
gtgaaaagacataggggg

79

put-miR-1306
ataacgtcatctagtgtg

71

put-miR-188
aaatggcgatactcagg

82

put-miR-209
ggtcctcggatcggcc

85

put-miR-323
ataaaatgggcgttgagg

125

put-miR-325
ttcaaatcccacttctgacacca

126

put-miR-444
ctgaaaaggggacggattgggaa

127

put-miR-465
ccagttgtcgtgggttttt

128

put-miR-468
ataaggaactgctctctc

74

put-miR-469
gcgggggattagctcagctggg

129

put-miR-476
gtggtcaggtagagaa

75

put-miR-594
tgattttttttggcgaa

130

put-miR-6
gcggaccttgctcaagg

78

put-miR-71
gaccttgggttgggtcgtggt

73

put-miR-742
cagggctgtgctaact

77

put-miR-806
cacgagagaacgcacacc

72

put-miR-856
aaggatagggaggtattt

131

put-miR-893
accatcctctgctacca

132

put-miR-92
agagactgactttgagta

81

put-miR-958
acagggctgtgcaaaaa

133

put-miR-961
tagcttgatccagttg

86

RNU4-6p
tatcgtagccaatgaggtttatccgag

134

gcgtgattattgctaattgaaaa

RNU6-4
ggcccctgcacagggatgacacgca

98

aattcgtgaagcgttccatattttt

RNU6-45
ggcccttgtgcaaggatgacacgcaa

101

attcgtgaagcgttccatattttt

RNU6-6
ggcccctgtgcaaggatgacacgca

100

aattcgtgaagcgttccatattttt

RNU6-7
ggcccctgcgcaaggatgacatgca

99

aattcgtgaagcgttccatattttt

RNU6-73
ggcccctgtgcaaggatgacatgcaa

102

attcgtgaagcgttccatattttt

SNORA57
tgctggcggcttcccatccgctggttct

135

atcctcaaacgccgggacaccg

SNORD3B-2
cttctctccgtattggggagtgagagg

136

gagagaacgcggtctgagtggtt

tRNA120-
gcgcatgcttagcatgcatgaggtccc

137

AlaAGC
gggttcgatccccagcatctcca

tRNA18-ArgCCT
gcactggcctcctaagccagggattgt

138

gggttcgagtcccacctggggta

tRNA27-MetCAT
gcgtcagtctcataatctgaaggtcct

139

gagttcgagcctcagagagggca

tRNA2-LeuTAA
gcataaaacttaaaattttataatcaga

140

ggttcaactcctcttcttaaca

tRNA73-ArgCCG
gcgtctgattccggatcagaagattga

141

gggttcgagtcccttcgtggtcg

tRNA8-ThrAGT
gcgcctgtctagtaaacaggagatcct

142

gggttcgaatcccagcggtgcct

tRNA9-TyrGTA
ctttttgactgtagagcaagaggtccct

143

ggttcaaatccaggttctccct

U2.3
tcacttcacgcatcgatctggtattgca

144

gtacctccaggaacagtgcacc

U4.64
gtatcgtagccaatgaggtttatccaa

145

ggtgcgattattgctaattgaaa

U6.1249
gatggcatgacccctgatcaaggacg

105

gcatgcaaatttgtgaagtatttc

U6.168
atggcccctgcgcaaggatgacacg

146

caaatttgtgaaggattccatattt

U6.375
ggcccctgtgcaagaatgactcgcaa

104

attcgtgaagcgttccatattttt

U6.428
aagattagcatgaggatgacacgcaa

97

attcgtgaagcgttccatttcttt

U6.601
ggcccctgcgcaaggatgacatgca

147

aatttgtgaagtgttccatattttt

UC022CJG1
cattgatcatcgacacttcgaacgcac

148

ttg

YRNA-245
gtctttgttgaactctttccctccttctcat

149

tactgtacttgaccagtct

YRNA-255
gugucaccaacguugguauacaac

103

cccccacaacuaaauuugacuggc

uu

YRNA-684
gcttcttttactctttcccttcattctcact

150

actgtacctgattcgtctt

As discussed in more detail in Example 1 (below), these biomarkers were found to be differentially expressed and statistically significant between the different group comparisons and the different time points (Ca vs Ub; Cb vs Ub; Cc vs Uc; Ca vs Mb; Cb vs Mb; Cc vs Mc; Ca vs U+M b; Cb vs U+M b; Cc vs U+M c; Ca vs B; Cb vs B; Cc vs B).

According to an aspect of the present disclosure, there is provided a method of diagnosing and treating traumatic brain injury (TBI) in a human subject in need thereof, the method comprising: obtaining a saliva sample from the subject; contacting the saliva sample with a probe comprising a nucleic acid able to bind to at least one RNA biomarker selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-let-7i-5p, hsa-miR-103a-3p, hsa-miR-107, hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-148a-3p, hsa-miR-16-1-3p, hsa-miR-206, hsa-miR-21-5p, hsa-miR-29c-3p, hsa-miR-339-5p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-497-5p, hsa-miR-671-3p, hsa-miR-6748-3p, hsa-miR-92a-3p, hsa-miR-934, put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1204, put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-468, put-miR-469, put-miR-476, put-miR-594, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-856, put-miR-893, put-miR-92, put-miR-958, put-miR-961, RNU4-6p, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.1249, U6.168, U6.375, U6.428, U6.601, UC022CJG1, YRNA-245, YRNA-255, and YRNA-684; determining an amount of the at least one RNA biomarker in the saliva sample; identifying the subject as having TBI where the amount of the at least one RNA biomarker is increased or decreased relative to a predetermined threshold value or relative to the amount of the RNA biomarker in a control sample; and treating the subject identified as having TBI according to one or more of the following: administering to the subject one or more neuroprotective therapies.

In some embodiments, the method further comprises identifying the human subject as being fit for normal activity after undergoing successful treatment for TBI.

In another aspect of the present disclosure, there is provided a method of diagnosing and/or monitoring traumatic brain injury (TBI) in a subject, the method comprising determining a level of at least one RNA biomarker in a saliva sample obtained from the subject, wherein the at least one RNA biomarker is selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-let-7i-5p, hsa-miR-103a-3p, hsa-miR-107, hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-148a-3p, hsa-miR-16-1-3p, hsa-miR-206, hsa-miR-21-5p, hsa-miR-29c-3p, hsa-miR-339-5p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-497-5p, hsa-miR-671-3p, hsa-miR-6748-3p, hsa-miR-92a-3p, hsa-miR-934, put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1204, put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-468, put-miR-469, put-miR-476, put-miR-594, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-856, put-miR-893, put-miR-92, put-miR-958, put-miR-961, RNU4-6p, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG SNORD3B-2, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.1249, U6.168, U6.375, U6.428, U6.601, UC022CJG1, YRNA-245, YRNA-255, and YRNA-684, or any combination thereof.

In some embodiments, either an upregulated level or a downregulated level of the at least one RNA biomarker is indicative of TBI.

In some embodiments, the method further comprises identifying the human subject as being fit for normal activity after undergoing successful treatment for TBI.

In some embodiments, the at least one RNA biomarker further comprises one or more miRNA selected from the group consisting of hsa-miR-143-3p and hsa-miR-135b-5p.

In another aspect of the present disclosure, there is provided a sensor element for a detection system for diagnosing and/or monitoring TBI, the sensor element comprising a substrate functionalized with a probe specific for at least one RNA biomarker selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-let-7i-5p, hsa-miR-103a-3p, hsa-miR-107, hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-148a-3p, hsa-miR-16-1-3p, hsa-miR-206, hsa-miR-21-5p, hsa-miR-29c-3p, hsa-miR-339-5p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-497-5p, hsa-miR-671-3p, hsa-miR-6748-3p, hsa-miR-92a-3p, hsa-miR-934, put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1204, put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-468, put-miR-469, put-miR-476, put-miR-594, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-856, put-miR-893, put-miR-92, put-miR-958, put-miR-961, RNU4-6p, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.1249, U6.168, U6.375, U6.428, U6.601, UC022CJG1, YRNA-245, YRNA-255, and YRNA-684.

In some embodiments, the probe comprises a nucleic acid able to bind to the at least one RNA biomarker.

In some embodiments, the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of the sequence of the target RNA biomarker.

In some embodiments, the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of SEQ ID NO: 1, 2, 14, 16, 23, 26, 27, 29, 39, 40, 48, 71, 72, 73, 74, 75, 77, 78, 79, 80, 81, 82, 84, 85, 86, 87, 89, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, and 150.

In some embodiments, the at least one RNA biomarker further comprises one or more miRNA selected from the group consisting of hsa-miR-143-3p and hsa-miR-135b-5p.

In some embodiments, the detection system further comprises means to determine whether the target RNA biomarker is upregulated or downregulated.

In another aspect of the present disclosure, there is provided a method of treating a subject with suspected TBI, the method comprising determining whether an upregulated level or a downregulated level of at least one RNA biomarker selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-let-7i-5p, hsa-miR-103a-3p, hsa-miR-107, hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-148a-3p, hsa-miR-16-1-3p, hsa-miR-206, hsa-miR-21-5p, hsa-miR-29c-3p, hsa-miR-339-5p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-497-5p, hsa-miR-671-3p, hsa-miR-6748-3p, hsa-miR-92a-3p, hsa-miR-934, put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1204, put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-468, put-miR-469, put-miR-476, put-miR-594, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-856, put-miR-893, put-miR-92, put-miR-958, put-miR-961, RNU4-6p, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.1249, U6.168, U6.375, U6.428, U6.601, UC022CJG1, YRNA-245, YRNA-255, and YRNA-684 is detectable in a saliva sample obtained from the subject, and if an upregulated level or a downregulated level of at least one RNA biomarker is detected, providing treatment for TBI to the subject.

In some embodiments, the at least one RNA biomarker further comprises one or more miRNA selected from the group consisting of hsa-miR-143-3p and hsa-miR-135b-5p.

In another aspect of the present disclosure, there is provided a method of detecting an RNA biomarker in a saliva sample, the method comprising obtaining a saliva sample from a human subject, contacting the saliva sample with at least one oligonucleotide primer complementary to at least one RNA biomarker selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-let-7i-5p, hsa-miR-103a-3p, hsa-miR-107, hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-148a-3p, hsa-miR-16-1-3p, hsa-miR-206, hsa-miR-21-5p, hsa-miR-29c-3p, hsa-miR-339-5p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-497-5p, hsa-miR-671-3p, hsa-miR-6748-3p, hsa-miR-92a-3p, hsa-miR-934, put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1204, put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-468, put-miR-469, put-miR-476, put-miR-594, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-856, put-miR-893, put-miR-92, put-miR-958, put-miR-961, RNU4-6p, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.1249, U6.168, U6.375, U6.428, U6.601, UC022CJG1, YRNA-245, YRNA-255, and YRNA-684; amplifying the at least one RNA biomarker using a polymerase chain reaction; and detecting the amplified RNA biomarker.

In some embodiments, the at least one RNA biomarker further comprises one or more miRNA selected from the group consisting of hsa-miR-143-3p and hsa-miR-135b-5p.

In another aspect of the present disclosure, there is provided a kit for use in a method of diagnosing and/or monitoring traumatic brain injury (TBI) in saliva from a human subject, the kit comprising at least one probe specific for at least one RNA biomarker selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-let-7i-5p, hsa-miR-103a-3p, hsa-miR-107, hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-148a-3p, hsa-miR-16-1-3p, hsa-miR-206, hsa-miR-21-5p, hsa-miR-29c-3p, hsa-miR-339-5p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-497-5p, hsa-miR-671-3p, hsa-miR-6748-3p, hsa-miR-92a-3p, hsa-miR-934, put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1204, put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-468, put-miR-469, put-miR-476, put-miR-594, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-856, put-miR-893, put-miR-92, put-miR-958, put-miR-961, RNU4-6p, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.1249, U6.168, U6.375, U6.428, U6.601, UC022CJG1, YRNA-245, YRNA-255, and YRNA-684.

In some embodiments, the probe comprises a nucleic acid able to bind to the at least one RNA biomarker.

In some embodiments, the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of the sequence of the target RNA biomarker.

In some embodiments, the at least one RNA biomarker further comprises one or more miRNA selected from the group consisting of hsa-miR-143-3p and hsa-miR-135b-5p.

In another aspect of the present disclosure, there is provided a composition for use in a method of diagnosing and/or monitoring traumatic brain injury (TBI) in saliva from a human subject, the composition comprising at least one probe specific for at least one RNA biomarker selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-let-7i-5p, hsa-miR-103a-3p, hsa-miR-107, hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-148a-3p, hsa-miR-16-1-3p, hsa-miR-206, hsa-miR-21-5p, hsa-miR-29c-3p, hsa-miR-339-5p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-497-5p, hsa-miR-671-3p, hsa-miR-6748-3p, hsa-miR-92a-3p, hsa-miR-934, put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1204, put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-468, put-miR-469, put-miR-476, put-miR-594, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-856, put-miR-893, put-miR-92, put-miR-958, put-miR-961, RNU4-6p, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.1249, U6.168, U6.375, U6.428, U6.601, UC022CJG1, YRNA-245, YRNA-255, and YRNA-684.

In some embodiments, the probe comprises a nucleic acid able to bind to the at least one RNA biomarker.

In some embodiments, the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of the sequence of the target RNA biomarker.

In some embodiments, the at least one RNA biomarker further comprises one or more miRNA selected from the group consisting of hsa-miR-143-3p and hsa-miR-135b-5p.

It will be appreciated that statements made herein in relation to any aspect of the invention may equally apply to any other aspect of the invention, as appropriate.

EXAMPLES

Embodiments of the invention will now be described by way of example.

Example 1
Salivary Non-Coding RNA: Next Generation Biomarkers in Concussed Rugby Football Union Players
Study Design

The Study of Concussion in Rugby Union through MicroRNAs (SCRUM study) is a prospective observational study of players (up to 1100) in the two highest tiers of senior professional domestic rugby competition in England, the Premiership and Championship. The study is embedded within the ongoing RFU Injury Surveillance Programme for the 2017-2018 seasons.

All players, previous written consent, were asked to provide a single baseline samples of approximately 2 mL of saliva during the preseason preparations (group B), before the training sessions if possible, at their clubs as well as completing a consent form detailing the processing and handling of their samples, the anonymisation of their data and their right to withdraw their voluntary consent at any time. The investigators recorded the timing of these baseline extractions in relation to preseason training sessions, other injuries, or supplement/medication use.

During the season each time a player entered the Head Injury Assessment (HIA) process (group C), he was asked to provide a saliva sample. Players who had been removed during the match for a pitch side assessment, provided a sample during this medical evaluation, called HIA1, and constituted group Ca. If players exhibited clear signs of concussion, also known as category 1 signs, no pitch side evaluation was necessary—in accordance with World Rugby guidance—and the player was immediately and permanently removed from the match. These players formed the “Immediate Permanent Removal” group (IPR). All players evaluated pitch-side or immediately and permanently removed for concussion were subsequently assessed immediately after the match (HIA2) and at 36-48 h post-match (HIA3). Samples were collected at each of these assessments. Therefore, we obtained saliva samples for groups C and IPR immediately post-match (group Cb and IPRb respectively) and 36 h-48 h HIA (group Cc and IPRc respectively).

The HIAs at each time point take the form of a modified Sport Concussion Assessment Tool 5th Edition (SCATS) which has been well studied as a diagnostic tool in the context of sports-related concussion and is complemented by baseline performance data in these assessments collected by the clubs during their preseason preparations. In this way, we investigated the presence of concussion diagnostic miRNAs noninvasively at multiple time points, which were matched to a standardised clinical assessment and diagnostic threshold for concussion performed by a clinician with experience in rugby head injuries. All IPR players were deemed to have been concussed. Group C players were deemed to be concussed if they failed the HIA at any time point (HIA1, HIA2 or HIA3); otherwise they were cleared of concussion. Players who entered the HIA process for suspected concussion but were cleared were analysed separately.

Players diagnosed with concussion were also asked for a sample of saliva at the point at which they were cleared by their team physician to return to competitive play (Stage VI) (group Cd and IPRd), as per the Berlin Consensus Graduated Return-to-Play (GRTP) protocol.

Whenever a player was removed for an HIA, club medical teams also approached an “uninjured control” (group U) player for saliva samples after the game (group Ub) and at 36-48 hours later (group Uc). An “uninjured control” is a non-concussed player who has played approximately a matched number of minutes in the same game and same playing position of the concussed player whenever possible. This allows for the description of miRNA profiles in response to the physical stress of athletic activity and exposure to the likely subconcussive blows, which come from participation in a collision sport.

To rule out contamination from non-neurological injuries and musculoskeletal trauma, club medics collected samples from players removed from the field of play due to musculoskeletal injuries (orthopaedic controls) (group M) at the same time points as the “uninjured control” group (group Mb and group Mc).

Ethics and Dissemination

The SCRUM study runs under University of Birmingham (UoB) ethics (ERN_11-0429AP28) as part of the Repetitive Concussion in Sport (RECOS) study. This study was approved by the East of England—Essex Research Ethics Committee (REC) on 22 Sep. 2017—REC 17/EE/0275; IRAS 216703.

Saliva Collection

The samples were collected in Oragene®-RNA RE-100 saliva self-collection kit (DNA Genotek) which contains a RNA stabilizing solution for a total of 8 weeks. Saliva was collected from each participant at enrollment following orally rinsing with tap water. The samples were then transported to the University of Birmingham where they were processed in line with the sample pot manufacturer's guidance to allow freezing and storage.

Materials and Methods
Next Generation Sequencing—Discovery Phase

All experiments were conducted at QIAGEN Genomic Services, Germany.

RNA Preparation

RNA preparation was performed according to Oragene recommendations, except the use of the miRNeasy kit (Qiagen, Germany) instead of the RNeasy kit.

Next Generation Sequencing
Library Preparation and Sequencing

The library preparation was done using the QIAseq miRNA Library Kit (QIAGEN). A total of 5 ul total RNA was converted into microRNA NGS libraries. Adapters containing UMIs were ligated to the RNA. Then RNA was converted to cDNA. The cDNA as amplified using PCR (22 cycles) and during the PCR indices were added. After PCR the samples were purified. Library preparation QC was performed using either Bioanalyzer 2100 (Agilent) or TapeStation4200 (Agilent). Based on quality of the inserts and the concentration measurements the libraries were pooled in equimolar ratios. The library pools were quantified using the qPCR ExiSEQ LNA™ Quant kit (Exiqon). The library pools were then sequenced on a NextSeq500 sequencing instrument according to the manufacturer instructions (NEBNext Multiplex Small RNA Library Prep Set for Illumina) to make approximately 163-175 base-pair sized libraries. Raw data as demultiplexed and FASTQ files for each sample were generated using the bcl2fastq software (Illumina inc.). FASTQ data were checked using the FastQC tool (www.bioinformatics.babraham.ac.uk/proeects/fastqc/).

Trimming

Cutadapt was used to extract information of adapter and UMI in raw reads, and output from cutadapt was used to remove adapter sequences and to collapse reads by UMI with inhouse script.

UMI Correction

According to the experiment protocol, each raw read was expected to contain, starting from 5′ end, an insert sequence, the adapter sequence, 12 nt-long UMI sequence, and other ligated sequence. Depending on the read length and insert length, not all parts were present in all reads. To correct PCR bias with UMI information, raw reads were processed as described below:

1. Use cutadapt on raw reads with provided adapter sequence to acquire output with information about the presence of adapter for each read.

2. Parse cutadapt output and keep only reads that fulfil all of the following requirements:

- Reads contain adapters.
- Insert sequence should be equal or larger than minimal insert length (default 16 nt).
- UMI sequence should be equal or longer than minimal UMI length (default 10 nt).

3. Extract insert sequences from reads which do not contain full length UMI sequence from step 2 output as partial-UMI reads.

4. Examine reads with full length UMI in step 2 output and identify all unique insert+UMI combinations. Extract insert sequences from unique insert+UMI combinations as full-UMI reads.

5. Combine partial-UMI reads and full-UMI reads as output of UMI correction.

Mapping

A reference profile of sequencing data for each sample was obtained using the whole human genome sequence GRCh37, downloaded from the Genome Reference Consortium and mirbase_20 as annotation reference. Reads were aligned to the miRbase using Bowtie2. The mapping criteria for aligning reads to spike-ins, abundant sequence and miRBase were the reads have to have perfect match to the reference sequences. For mapping to the genome the restriction of one mismatch was allowed in the first 32 bases of the read. No indels were allowed in mapping. Unaligned reads were mapped against the host reference genome and used as input for mirPara and miRbase to predict putative miRNAs.

Differential Expression

Aligned reads were counted and differential expression analysis, p-values for significantly differentially expressed microRNAs and false discovery rate according to Benjamini-Hochberg were performed with EdgeR. For normalisation, the trimmed mean of M-values (TMM) method based on log-fold and absolute gene-wise changes in expression levels between samples was used.

Unsupervised Analysis

Principal component analysis is performed with R using TMM-normalized quantifications from defined collections of samples as input.

MiRNA qPCR Data Analysis—Validation Study

All experiments were conducted at QIAGEN Genomic Services, Germany.

MiRNA qPCR validation was performed in 176 saliva baseline samples (B); 42 samples form concussed players after injury (group Ca); 52 samples from concussed players post-match (group Cb) and 54 concussed players after 36-48 h (group Cc); 61 uninjured players post-match (group Ub); 45 uninjured players 36-48 h (group Uc); 30 musculoskeletal injury players post-match (group Mb); 24 musculoskeletal injury players 36-48 h (group Mc).

RNA Extraction and qPCR

Total RNA was extracted from the samples using miRNeasy Serum/Plasma kit (QIAGEN) after manufacturer's instructions. The purified total RNA was eluted in a final volume of 32 μl. 14 μl RNA was reverse transcribed in 70 μl reactions using the miRCURY LNA RT Kit (QIAGEN). cDNA was diluted 50× and assayed in 10 μl PCR reactions according to the protocol for miRCURY LNA miRNA PCR; each miRNA was assayed once by qPCR on the miRNA Ready-to-Use PCR, Custom panel using miRCURY LNA SYBR Green master mix. Negative controls excluding template from the reverse transcription reaction was performed and profiled like the samples. The amplification was performed in a LightCyclerp 480 Real-Time PCR System (Roche) in 384 well plates. The amplification curves were analyzed using the Roche LC software, both for determination of Cq (by the 2nd derivative method) and for melting curve analysis. The amplification efficiency was calculated using algorithms similar to the LinReg software. All assays were inspected for distinct melting curves and the Tm was checked to be within known specifications for the assay. Furthermore assays must be detected with 0 Cq less than the negative control, and with Cq<37 to be included in the data analysis. Data that did not pass these criteria were omitted from any further analysis. Cq was calculated as the 2nd derivative. Normalization was performed based on the average of hsa-miR-29c-3p and hsa-let-7b-5p (custom normalizer assays), the two more stable miRs identified across all samples by Normofinder software (33). The formula used to calculate the normalized Cq values is the difference between the custom normalizer assays mean Cq and the assay Cq (miRNA of interest). A higher value indicates that the miRNA is more abundant in that sample.

Statistical Analyses

All analyses were carried out using SPSS 20.0 (SPSS Inc., Chicago, Ill., USA).

Group Comparisons

We used the two-tailed Independent-Samples T Test procedure to compare means for two groups of cases. The two-tailed Paired-Samples T Test procedure compares the means of two variables for a single group. The procedure computes the differences between values of the two variables for each case and tests whether the average differs from 0. Bootstrapping is a method for deriving robust estimates of standard errors and confidence intervals for estimates. Bootstrapping is most useful as an alternative to parametric estimates when the parametric inference is impossible.

The One-Way ANOVA procedure produces a one-way analysis of variance for a quantitative dependent variable by a single factor (independent) variable. Analysis of variance is used to test the hypothesis that several means are equal. This technique is an extension of the two-sample t test. In addition to determining that differences exist among the means, you may want to know which means differ. There are two types of tests for comparing means: a priori contrasts and post hoc tests. Contrasts are tests set up before running the experiment, and post hoc tests are run after the experiment has been conducted.

General Linear Model Repeated Measures analyzes groups of related dependent variables that represent different measurements of the same attribute. It is possible define one or more within-subjects factors for use in GLM Repeated Measures.

Discriminant Analysis

The Discriminant analysis (DA) was applied to the Cq values provided by Qiagen.

The main purpose of DA was to find the dimension(s) along which groups differ and to find classification function(s) to predict group membership from a combination of variables (predictors). In the present case, the two groups were concussed (group C+IPR) and uninjured subjects (group U), and the predictors were a set of biomarkers selected from the NGS study.

DA works with data that is already classified into groups to derive rules for classifying new (and as yet unclassified) individuals on the basis of their observed variable values.

In univariate terms (t-test, Oneway Anova) a significant difference among groups implies that, given a score, you can predict which group it comes from. In DA, there is often an effort to interpret the pattern of differences among the predictors as a whole in an attempt to understand the dimensions along which groups differ reliably.

With only two groups, there is only one linear combination of predictors that best separates them. The separation of two group centroids (multivariate version of means), represents the best linear combination of predictors that separate the groups 1 and 2. A line parallel that connects the two centroids represents the linear combination or discriminant function, a pattern of scores that discriminates between the two groups.

There are two facets of DA, and one or both may be emphasized in any given research application. The researcher may be interested in a decision rule for classifying cases where the number of dimensions and their meaning is irrelevant. Or the emphasis may be on interpreting the results of DA in terms of the combinations of predictors (discriminant functions) that separate various groups from each other.

Classification functions are used to predict group membership for new cases and to check the adequacy of classification for cases in the same sample through cross-validation.

The canonical correlation explains the percent of variance accounted by the scores for the discriminant function between these groups. A canonical correlation is a multiple-multiple correlation because there are multiple variables on both sides of the regression equation, and for each discriminant function, when squared, indicates the proportion of variance shared between groups and predictors on that function.

In Standard (direct) DA, like standard multiple regression, all predictors enter the equations at once and each predictor is assigned only the unique association it has with groups. Variance shared among predictors contributes to the total relationship, but not to any one predictor.

In Stepwise DA statistical criteria can be used to produce a reduced set of predictors.

All analyses were carried out using SPSS 20.0 (SPSS Inc., Chicago, Ill., USA).

ROC Curve Analyses

The diagnostic performance of a test, or the accuracy of a test to discriminate experimental cases from normal cases is evaluated using Receiver Operating Characteristic (ROC) curve analysis. ROC curves can also be used to compare the diagnostic performance of two diagnostic tests.

When one considers the results of a particular test in two populations, one population with a characteristic and the other population without the characteristic, you will rarely observe a perfect separation between the two groups. Indeed, the distribution of the test results will overlap.

In a ROC curve the true positive rate (Sensitivity) is plotted in function of the false positive rate (100−Specificity) for different cut-off points of a parameter. Each point (cut-off) on the ROC curve represents a sensitivity/specificity pair corresponding to a particular decision threshold. The area under the ROC curve (AUC) is a measure of how well a parameter can distinguish between two diagnostic groups (experimental/normal). A test with perfect discrimination (no overlap in the two distributions) has a ROC curve that passes through the upper left corner (100% sensitivity, 100% specificity). Therefore the closer the ROC curve is to the upper left corner, the higher the overall accuracy of the test.

ROC Statistics

Sensitivity: probability that a test result will be positive when the characteristic is present (true positive rate, expressed as a percentage).

Specificity: probability that a test result will be negative when the characteristic is not present (true negative rate, expressed as a percentage).

Positive likelihood ratio: ratio between the probability of a positive test result given the presence of the characteristic and the probability of a positive test result given the absence of the characteristic, i.e. =True positive rate/False positive rate=Sensitivity/(1−Specificity)

Negative likelihood ratio: ratio between the probability of a negative test result given the presence of the characteristic and the probability of a negative test result given the absence of the characteristic, i.e. =False negative rate/True negative rate=(1−Sensitivity)/Specificity

Results
Sample Size

A total of 906 players were recruited to the study between July 2017 and April 2018. This included players from 11 clubs playing in The Premiership and 11 clubs playing in the IPA Championship. One club in The Premiership chose not to take part after consultation with the RFU as they were already participating in a concussion research project involving saliva sampling for different purposes run by another organisation. One club in the IPA Championship chose not to take part as they felt they would struggle to fulfil the requirements of the study due to limited numbers of medical staff while another club in the IPA Championship felt decided to withdraw from the study for similar reasons but after their players had provided baseline samples. This made a total of 11 clubs in The Premiership and 10 clubs in the IPA Championship participating in collecting samples through the season from head injury events.

Overall, a total of 229 head injury incidents took place across both competitions. This figure is an amalgamation of incidents in which the player was immediately and permanently removed from play due to exhibiting “Category 1” signs and symptoms, as well as all of the incidents in which players were temporarily removed from play for an off field HIA1 assessment. Samples were received from a total of 129 of these incidents making overall compliance 56%.

Samples were received from 73 of a possible 120 incidents in which the on field or subsequent diagnosis was concussion (61%). Within this group 26 (36%) were incidents in which the player was immediately and permanently removed from play due to exhibiting “Category 1” signs and symptoms. Samples were received from 42 of a possible 109 incidents in which the on field or subsequent diagnosis excluded concussion (39%).

Matched uninjured control samples were received in 71 cases (55%). Matched musculoskeletal injury control samples were received in 39 cases (30%).

Next Generation Sequencing—Discovery Phase

MicroRNA/small RNA Next Generation Sequencing (NGS) was performed in the initial discovery phase using 15 saliva baseline samples (B), 15 samples from concussed players (consisting of 10 concussed (C) and 5 IPR) and 20 controls (consisting of 10 musculoskeletal injuries (M) and 10 uninjured players (U)). All samples analysed in this phase were collected post-match (time point b).

On average 16.3 million reads were obtained per sample. A detailed microRNA/small RNA NGS data analysis report was obtained. The differential expression analysis step attempts to distinguish biological variation from technical variation within the experiment, assuming that this varies amongst microRNAs.

P-values for significantly differentially expressed microRNAs are estimated by an exact test on the negative binomial distribution. A list of microRNAs predicted to be differentially expressed between the given experimental conditions was created. This list includes different RNA fragments, among these known microRNA, other small non-coding RNAs, and predicted microRNA (described as put-miR) differentially expressed between groups C+IP and M+U, B and C+IPR, and B and M+U.

Selection for Validation

A panel of microRNA/small RNA/put microRNA, differentially expressed in NGS analysis was selected in the group C+IPR and M+U according the following parameters: FDR<0.5 or p-value <0.05. The Panel consisting of 168 small RNAs, 38 known microRNAs and 233 put-miRs was used for the validation study by qPCR. Following this test, the most significantly altered biomarkers were reduced to 30 known microRNAs; 34 putative miRs; 28 small non-coding RNA, which were then analysed in a further 405 samples. The Cq values obtained from the 2 qPCR validation sets were finally merged and collected in a total of 598 samples.

Statistical Analysis—Validation Study
SncRNAs Differentially Expressed in Group C Vs U+M

Concussion samples were compared to uninjured and musculoskeletal injury at different time points. Table 5 shows the sncRNAs survived to a p value <0.05 among the different comparisons: Ca vs U+M b (no samples were collected at time point a for the category U and M, for this reason the group Ca was compared to the closest time point, U+M b), Cb vs U+M b; Cc vs U+M c. The table also includes: AUC, CI, count, CT average, SD, ddcq, fold change and power analysis for each individual biomarker.

The biomarkers selected from the STEPWISE analysis are shown in grey cells of Table 5 and presented an AUC of 0.86; 0.86 and 0.97 in Ca vs U+M b; Cb vs U+M b; Cc vs U+M c comparisons respectively.

SncRNAs Differentially Expressed in Group C Vs U

Concussion samples were compared to uninjured control group only at different time points. Table 6 shows the sncRNAs survived to a p value <0.05 among the different comparisons: Ca vs Ub; Cb vs Ub; Cc vs Uc. The table also includes: AUC, CI, count, CT average, SD, ddcq, fold change and power analysis for each individual biomarker. The biomarkers selected from the STEPWISE analysis are shown in grey cells of Table 6 and presented an AUC of 0.83; 0.91 and 0.97 in the following comparisons Ca vs Ub; Cb vs Ub; Cc vs Uc respectively.

SncRNAs Differentially Expressed in Group C Vs B

Concussion samples were compared to the baseline data of the same subjects. Table 7 shows the sncRNAs survived to a p value <0.05 in the different comparisons: Ca vs B Cb vs B; Cc vs B. The table also includes: count, CT average, SD, ddcq, fold change and power analysis for each individual biomarker.

SncRNAs Differentially Expressed in Group C Vs M

Concussion samples were compared to musculoskeletal injury control group only at different time points. Table 8 shows the sncRNAs survived to a p value <0.05 among the different comparisons: Ca vs Mb; Cb vs Mb; Cc vs Mc. The table also includes: AUC, CI, count, CT average, SD, ddcq, fold change and power analysis for each individual biomarker. The biomarkers selected from the STEPWISE analysis are shown in grey cells of Table 8 and presented an AUC 0.96; 0.83 and 0.94 in the following comparisons Ca vs Mb; Cb vs Mb; Cc vs Mc respectively.

MicroRNAs differentially expressed between Cb and U+M b groups (FDR<0.5 or p-value <0.05), selected by NGS analysis and used for the first qPCR validation step are shown in Table 3A, below.

TABLE 3A

microRNAs
logFC
logCPM
p-Value
FDR

hsa-miR-199a-5p
−3.79380184
5.744164606
8.15823E−06
0.004797041

hsa-miR-133a-3p
−4.95698696
10.40020121
7.04586E−05
0.020714819

hsa-miR-206
−4.6959152
9.788488822
0.000180043
0.03528849

hsa-miR-1273h-3p
2.629420889
3.481729832
0.001297451
0.190725263

hsa-miR-133b
−4.20181151
6.465178373
0.002184888
0.256942851

hsa-miR-561-5p
1.579551555
4.525850808
0.003970504
0.348018465

hsa-miR-126-3p
−1.41838668
8.449681001
0.004143077
0.348018465

hsa-miR-16-1-3p
1.43849327
4.458454478
0.005764959
0.352449414

hsa-miR-449b-3p
3.467958972
3.218975
0.005920497
0.352449414

hsa-miR-449c-5p
2.749952622
5.534179256
0.006033974
0.352449414

hsa-miR-6748-3p
4.143101791
3.188086662
0.007073212
0.352449414

hsa-miR-133a-5p
−3.92797466
4.752927061
0.008472679
0.352449414

hsa-miR-34b-3p
2.1437498
4.339967792
0.008637715
0.352449414

hsa-miR-6824-3p
2.731145621
3.076936275
0.008970282
0.352449414

hsa-miR-5195-5p
5.376105018
4.09767258
0.009313959
0.352449414

hsa-miR-5096
2.906908779
4.723794715
0.00959046
0.352449414

hsa-miR-4488
3.491520052
3.097320079
0.012515423
0.409279535

hsa-miR-92a-3p
−0.60902412
10.49283489
0.012885103
0.409279535

hsa-miR-1
−2.36876254
10.80951287
0.013692259
0.409279535

hsa-miR-885-5p
1.507019382
4.182851751
0.013921073
0.409279535

hsa-miR-548h-5p
2.055544755
3.480848725
0.015148132
0.42414769

hsa-miR-1246
0.980484408
14.78271469
0.017085283
0.445746733

hsa-miR-4492
−3.18487947
3.53612341
0.017435672
0.445746733

hsa-miR-484
1.274418725
6.148369199
0.019071294
0.449461809

hsa-miR-449a
2.203777576
6.338766334
0.019109771
0.449461809

hsa-miR-3122
3.142476669
3.078975177
0.02000366
0.452390465

hsa-miR-1180-3p
1.165471248
3.889331639
0.021316281
0.457201951

hsa-miR-619-5p
2.792045377
3.207604869
0.021771521
0.457201951

hsa-miR-2277-5p
1.067026052
4.057818901
0.023836409
0.474930011

hsa-miR-5699-3p
1.876788488
2.955683933
0.024231123
0.474930011

hsa-miR-125b-2-3p
−0.96587973
4.933520984
0.025679562
0.487083301

hsa-miR-4449
2.06863176
3.047374886
0.027679506
0.503997815

hsa-miR-671-3p
1.125735449
3.934232773
0.02867908
0.503997815

hsa-miR-33a-3p
0.959071217
4.091785492
0.029142731
0.503997815

hsa-miR-193b-5p
−1.14025756
4.138245693
0.031271072
0.522692794

hsa-miR-34c-3p
1.690242737
4.489423918
0.0320016
0.522692794

hsa-miR-339-5p
1.057419584
7.902671962
0.034354837
0.545963351

hsa-miR-6813-3p
2.813650185
2.933287004
0.035310016
0.546376034

hsa-miR-671-5p
0.838663749
5.600518309
0.047339286
0.598988904

hsa-miR-1537-5p
1.129462606
4.117629615
0.048138455
0.598988904

hsa-miR-193a-3p
−1.5845588
3.995294293
0.048897053
0.598988904

hsa-miR-130a-3p
−0.88824466
6.580760266
0.051263632
0.604409433

hsa-miR-126-5p
−1.22112275
8.006357503
0.051621005
0.604409433

Other sncRNAs differentially expressed between Cb and U+M b groups (FDR<0.5 or p-value <0.05), selected by NGS analysis and used for the first qPCR validation step are shown in Table 3B, below.

TABLE 3B

small non-coding RNAs
logFC
logCPM
p-Value
FDR

tRNA138-ArgACG
−2.27538237
7.674009775
0.000243882
0.204980883

RNU6-11
−1.67718785
4.732492163
0.000245185
0.204980883

tRNA11-ArgACG
−2.21044709
7.59261144
0.000408122
0.204980883

RNU6-36
−1.84798113
4.63862015
0.000436362
0.204980883

tRNA175-SerGCT
−1.84762954
8.390549302
0.001054009
0.290869197

U3.39
4.655316415
4.424357984
0.001147835
0.290869197

RNU4-6P
−1.71160894
4.864935322
0.001317818
0.290869197

U6.375
−1.86391998
4.231358228
0.001366655
0.290869197

snoU13.63
4.286830869
4.29762358
0.001552935
0.290869197

tRNA8-ThrAGT
−1.65324248
9.428427256
0.001556007
0.290869197

RNU6-1
−1.37118776
4.843026936
0.001713194
0.290869197

RNU6-31
−1.53604238
4.741724921
0.002351551
0.290869197

tRNA4-ArgTCG
−1.70070174
10.2139807
0.002452994
0.290869197

tRNA130-ValCAC
−2.21562973
4.853113645
0.002797565
0.290869197

U3.3
−1.72401526
5.267608648
0.002991025
0.290869197

U4.57
−1.55456476
4.807782758
0.003084965
0.290869197

tRNA84-GluTTC
−1.39818637
10.32369425
0.003223874
0.290869197

U6.428
−1.83108856
4.169870903
0.003289229
0.290869197

U3.4
−1.80036039
5.421618508
0.00346512
0.290869197

tRNA95-AsnGTT
−2.24304788
4.752212371
0.003469246
0.290869197

uc003oif.3
−2.59243747
4.028384043
0.003838286
0.290869197

U3.2
−1.73251154
5.414684824
0.003880282
0.290869197

U3.42
2.126244843
4.003126274
0.003910676
0.290869197

uc002tgp.1
2.810368883
4.510093789
0.004221387
0.290869197

tRNA105-PseudoTTC
−1.59015632
7.983774255
0.004475105
0.290869197

tRNA4-GluCTC
−1.60952388
8.107675756
0.00453217
0.290869197

RNU6-14
−1.86375965
4.058373711
0.004721183
0.290869197

tRNA4-ThrAGT
−1.34446936
8.68050744
0.004730298
0.290869197

U6.97
−2.76317407
3.745083257
0.004815026
0.290869197

tRNA120-AlaAGC
−1.31815493
9.587766586
0.004875694
0.290869197

snoU13.348
2.256666202
4.075754187
0.005036202
0.290869197

U1.105
−2.32216301
4.207692971
0.005058512
0.290869197

tRNA27-MetCAT
−2.34782418
6.706470837
0.0051084
0.290869197

U1.10
−2.59329176
4.816351388
0.005540106
0.306172302

tRNA134-GluTTC
−1.3431528
10.39664851
0.006091168
0.32697053

RNU6-6
−1.54430018
4.19348578
0.00626447
0.32697053

Y_RNA.75
1.904869354
5.50161645
0.006713926
0.340251318

tRNA8-Undet
1.964251986
4.197405842
0.006905386
0.340251318

SNORA25
−2.35025006
3.740784336
0.007062161
0.340251318

RNU6-39
−1.60601357
4.333253034
0.007621329
0.3538182

tRNA119-AlaCGC
−1.25397272
9.514833568
0.007808074
0.3538182

tRNA85-PseudoTTC
1.126764653
5.8624175
0.008322426
0.3538182

U6.254
−1.80163898
3.954386151
0.008365638
0.3538182

tRNA3-ArgCCT
−1.40848109
10.46544955
0.008483646
0.3538182

SNORD114-2
−3.1187271
3.929437693
0.008576479
0.3538182

tRNA162-MetCAT
−2.31337858
6.829504657
0.008700411
0.3538182

Y_RNA.661
−2.13613309
3.924521406
0.008896949
0.3538182

tRNA8-AlaTGC
−1.03417608
10.23229845
0.009262877
0.3538182

tRNA56-ThrTGT
−1.43137722
10.38511882
0.009580922
0.3538182

tRNA26-AsnGTT
−1.2260783
8.800207822
0.009587969
0.3538182

tRNA73-ArgCCG
−0.87676773
7.646480047
0.009603368
0.3538182

tRNA156-ArgACG
−1.38659506
6.417990561
0.009974671
0.36043089

tRNA28-IleAAT
−0.96475102
8.290575814
0.010463073
0.370945534

RNU6-33
−1.41177741
4.713635974
0.010694162
0.372117242

tRNA3-ProTGG
2.564031745
13.63247318
0.01106572
0.37247176

tRNA19-ArgTCG
−1.57386692
9.439040466
0.011100808
0.37247176

tRNA164-MetCAT
−2.24158666
6.824859219
0.011731788
0.372701442

tRNA13-AlaCGC
−1.05980195
9.619304583
0.011862589
0.372701442

U6atac.4
−2.29659983
4.169967341
0.012205483
0.372701442

tRNA9-AlaAGC
−1.76859219
4.913678407
0.012206837
0.372701442

tRNA132-PseudoCAC
−2.28282945
4.122549605
0.012249051
0.372701442

RNU6-7
−1.54429239
4.25135459
0.012297759
0.372701442

tRNA20-MetCAT
−1.09889413
8.557399735
0.012787128
0.376829052

U3.24
−1.49142526
5.576968961
0.01283505
0.376829052

U6atac.29
−2.38352866
3.785989635
0.013059629
0.377523747

tRNA2-LeuTAA
−1.66936742
3.974107686
0.013474016
0.383601155

tRNA1-AsnGTT
−0.93147558
7.962088764
0.014090452
0.39410967

tRNA40-ThrAGT
−1.20252417
8.00746198
0.014483817
0.39410967

Y_RNA.684
2.380168702
3.849210771
0.014510103
0.39410967

snoU13.86
3.047260829
3.887450563
0.014700195
0.39410967

uc021qtn.l
−2.42558461
4.054546636
0.015164662
0.39410967

RNU6-9
−1.27226823
4.707463894
0.01590456
0.39410967

tRNA13-AlaTGC
−1.07694323
9.510390292
0.016125256
0.39410967

tRNA36-ArgACG
−1.42222279
6.510745574
0.016234233
0.39410967

Y_RNA.719
−1.87621292
4.049552581
0.016340695
0.39410967

RNU6-10
−1.35736219
4.333057065
0.016389921
0.39410967

SCARNA4
0.900162218
5.772147414
0.016691546
0.39410967

tRNA10-AlaCGC
−1.08617369
9.364295675
0.016698714
0.39410967

tRNA12-SerAGA
−2.17129695
3.960150632
0.016746309
0.39410967

uc011ley.2
−1.1603733
7.787151849
0.01677955
0.39410967

U1.116
−2.53057666
4.143384152
0.017351703
0.3975759

tRNA7-SerGCT
−1.22744148
8.048077286
0.017683906
0.3975759

U6.266
−1.68215765
4.162672228
0.018006863
0.3975759

tRNA136-AsnGTT
−1.18546894
6.252578135
0.018057145
0.3975759

uc031qaf.1
3.07982529
4.21672176
0.018100789
0.3975759

RNU4-9P
1.971224737
3.892961999
0.018196662
0.3975759

RNU6-48
−1.41494718
4.179417866
0.018610429
0.40194249

U4.64-201
−1.46842052
4.573943777
0.019052174
0.405290215

SNORA70.5
−2.3066839
3.705457206
0.019552672
0.405290215

tRNA83-AsnGTT
−0.95893311
7.650753844
0.019695599
0.405290215

tRNA21-ArgCCT
−1.3243702
9.463647642
0.019740822
0.405290215

RNU6-26
−1.26772628
4.674223977
0.019843906
0.405290215

tRNA4-AsnGTT
−0.95216219
7.630343605
0.020477143
0.409060595

U1.28
−1.66671858
4.666167958
0.020920233
0.409060595

U6.168
−1.75957771
3.988195609
0.021394709
0.409060595

RNU6-41-201
−1.2429829
4.599263654
0.021413125
0.409060595

tRNA15-ThrCGT
−0.94643604
8.011751983
0.021715336
0.409060595

tRNA88-PseudoCCT
1.406009411
4.775992477
0.021727046
0.409060595

SNORD116-19-201
−2.08108498
3.769046556
0.022072958
0.409060595

uc031qtw.1
−1.59586877
3.698957807
0.022111714
0.409060595

U6.422-201
−2.18510267
3.771206474
0.022136152
0.409060595

U2.3-201
−1.09052752
5.567176812
0.022205525
0.409060595

U3.20-201
−1.55295135
5.225744713
0.022487766
0.410237987

tRNA165-IleAAT
−0.81674152
8.525161575
0.023067622
0.416176914

snoU13.160-201
−1.88380693
3.690235583
0.023604159
0.416176914

tRNA36-ThrAGT
−1.09203025
7.99788872
0.023653935
0.416176914

tRNA6-TrpCCA
−1.06582891
10.59444161
0.023699271
0.416176914

SNORA57-201
−1.08263716
5.14915277
0.024108905
0.416665441

tRNA10-PseudoTGA
−1.42087364
5.662435588
0.024173287
0.416665441

uc001myu.3
−2.42408101
4.681561536
0.02449142
0.416665441

Y_RNA.428-201
−1.2545658
6.369684888
0.024614084
0.416665441

SCARNA1-201
−1.61719768
3.852134167
0.025631096
0.427567583

tRNA95-AlaAGC
−1.73027899
5.825175769
0.02592783
0.427567583

RNU6-27-201
−1.6140049
3.926299889
0.025940769
0.427567583

SNORA79.1-201
−1.15165538
4.196182085
0.026538748
0.433620064

tRNA9-IleAAT
−0.73350055
8.536774944
0.027547951
0.446033785

tRNA9-TyrGTA
−1.6487492
3.959996969
0.027773259
0.446033785

tRNA23-ArgCCG
−1.31033598
11.27930104
0.029044541
0.450180862

snoU13.318-201
−1.91587082
3.698261411
0.029045067
0.450180862

snoU13.328-201
2.684496203
4.280709032
0.029064976
0.450180862

RNU4-4P-201
−1.2311376
4.615863264
0.029137817
0.450180862

Y_RNA.633-201
−1.30999509
4.118055921
0.029229412
0.450180862

RNU5F-4P-201
−1.48557387
4.239223966
0.03016703
0.460844298

tRNA7-AsnGTT
−0.88097126
7.861805832
0.031177808
0.472444358

tRNA2-ArgCCT
−1.14460252
9.768619156
0.031689267
0.476353057

tRNA18-ArgCCT
−1.24884324
9.421599432
0.032541851
0.484021239

SNORD116-25-201
1.724675764
6.034751745
0.032861609
0.484021239

uc021ybm.1
−0.9249247
7.924193472
0.033450576
0.484021239

tRNA8-SerGCT
−0.98753133
8.589816708
0.033481121
0.484021239

tRNA11-IleAAT
−0.72451906
8.545784821
0.033487366
0.484021239

Y_RNA.597-201
1.732733959
3.760735382
0.034265836
0.491492414

snoU13.120-201
2.312826375
3.740373282
0.034550843
0.491826017

uc031qpu.1
2.324532842
3.768342356
0.035349099
0.49676233

RNU6-32-201
−1.18812391
4.327815738
0.035426372
0.49676233

tRNA100-PseudoGAA
−1.02843913
9.329302032
0.036035102
0.501555229

SNORD116-21-201
2.33201432
3.747426753
0.039146195
0.532853476

tRNA5-IleTAT
−1.08777911
7.207879458
0.039415342
0.532853476

Y_RNA.522-201
−1.81515534
4.101934504
0.039799275
0.532853476

tRNA12-ArgCCT
−1.27295081
9.216801318
0.039946538
0.532853476

U6atac.20-201
−1.94596283
4.036085302
0.040551585
0.532853476

RNU6-4-201
−1.52406279
4.105411071
0.040667896
0.532853476

SNORD3B-2-201
−0.79576357
8.540015612
0.040838684
0.532853476

tRNA11-AsnGTT
−1.30462038
4.970141103
0.040850618
0.532853476

tRNA31-AsnGTT
−0.87710624
7.603607761
0.041107699
0.532853476

Y_RNA.727-201
−1.25639747
4.115195415
0.041225337
0.532853476

RNU6-73-201
−1.46456929
4.007858615
0.042069664
0.532853476

SNORA65-201
−0.88817274
4.89950806
0.042220138
0.532853476

tRNA7-LeuAAG
−0.71492427
8.880350642
0.042319347
0.532853476

tRNA144-AspGTC
−0.82964134
11.54055138
0.042320413
0.532853476

U6atac.25-201
−1.77774451
3.762252674
0.042537531
0.532853476

tRNA1-ArgCCG
−0.76847131
7.276226466
0.043525106
0.535998445

SNORA7.4-201
−1.13362614
3.738511771
0.043665668
0.535998445

tRNA125-ThrCGT
−1.08045128
5.458664529
0.043842913
0.535998445

RNU6-45-201
−1.22266691
4.217769003
0.043929622
0.535998445

tRNA131-GlnCTG
−1.07262477
7.700551934
0.04461864
0.538855811

U6.1249-201
1.668615649
3.756761746
0.044737364
0.538855811

Y_RNA.245
2.25187274
3.754483152
0.045943642
0.545496798

U6.601
−1.35324491
3.970443965
0.046003943
0.545496798

RNU5E-4P
−1.0837447
5.498269856
0.046159655
0.545496798

tRNA66-AlaTGC
−0.81125784
9.226831102
0.046988475
0.545729532

tRNA32-MetCAT
−0.82679514
8.99856138
0.047086999
0.545729532

U4.79
−1.25353509
4.433132105
0.047164353
0.545729532

tRNA4-HisGTG
−1.61899083
3.790696889
0.047553836
0.545729532

U3.13
−1.51261982
3.797771351
0.047790048
0.545729532

RNU6-5
−1.02972321
4.777615387
0.048416122
0.545729532

SNORD36A
−1.75616298
3.84054929
0.048459133
0.545729532

tRNA1-LeuAAG
−0.6699966
8.883794181
0.048648388
0.545729532

RNU6-29
−1.13048434
4.36662749
0.048793274
0.545729532

Putative microRNAs differentially expressed between Cb and U+M b groups (FDR<0.5 or p-value <0.05), selected by NGS analysis and used for the first qPCR validation step are shown in Table 3C, below.

TABLE 3C

putative

microRNAs
Sequences
logFC
logCPM
PValue
FDR

put-miR-718
TTCAGGTTACCGCAGG
6.825255
9.009089
1.21E-05
0.01609

put-miR-594
TGATTTTTTTTGGCGAA
8.122089
13.62184
4.24E-05
0.028197

put-miR-703
GACTGCTCGAGCTGCTT
4.582706
9.340091
0.000177
0.065276

put-miR-477
TGGGCAGCAAGAATGG
6.350308
8.65459
0.00021
0.065276

put-miR-727
GGAGGATTTCAATTGG
4.944239
7.848316
0.000246
0.065276

put-miR-646
TCTGTCATGGCTGAGC
6.551056
8.808979
0.000322
0.065276

put-miR-675
TACCTCAATTCTCTAGG
5.756095
8.531088
0.000387
0.065276

put-miR-319
TGTCGGCGGGGGCCCCGGAC
3.557921
10.21937
0.000409
0.065276

put-miR-327
CATTCTCTGAAACTACA
6.062301
8.473821
0.000441
0.065276

put-miR-338
GACTTGTGATTAGCGG
5.013978
10.59887
0.000571
0.067661

put-miR-1187
GAGCATGTTGACTGGAGA
6.150807
8.514764
0.000634
0.067661

put-miR-6
GCGGACCTTGCTCAAGG
8.830503
11.10951
0.000659
0.067661

put-miR-341
TGAGAAAACATTTGAGG
5.709943
8.260643
0.000661
0.067661

put-miR-750
CAAGAGATGAGGAATG
5.585098
8.184314
0.000814
0.07204

put-miR-183
CCAGGCTGGTCGTGATGA
5.716867
8.806919
0.000855
0.07204

put-miR-980
TCGGAAGAAGAAGCTGACCCA
5.533531
8.158978
0.000866
0.07204

put-miR-798
TAACTCTTGGAAATCTTGG
3.422593
9.962536
0.001016
0.075645

put-miR-765
AAAAAAGAGGGACAGAAATG
5.173073
7.963608
0.001123
0.075645

put-miR-71
GACCTTGGGTTGGGTCGTGGT
3.989796
8.732315
0.001131
0.075645

put-miR-1327
GAAAAGCAATCGTCACAG
7.093524
9.887535
0.001158
0.075645

put-miR-371
AATATTCAGCAGTCAGACTGG
6.778311
9.768186
0.001224
0.075645

put-miR-354
CAGGGTGATGACTTCTG
4.795128
7.781813
0.001302
0.075645

put-miR-688
GTGATGTCGGCTCATCGCAACCT
2.199185
10.66612
0.001307
0.075645

put-miR-756
TGAGGGATGTTTGGATGCTCGCTTTGA
2.032426
8.603553
0.001428
0.079215

put-miR-1146
CAACTGTAAGTCCATT
4.770832
9.196252
0.00158
0.079645

put-miR-1333
TAATTGTCCTCTTGGGG
4.794112
7.786171
0.001619
0.079645

put-miR-511
AAGCAGGCGTTACAATG
7.089632
9.54354
0.001631
0.079645

put-miR-1199
TGAACTCGGGAGAAGGAAGT
2.994051
11.94621
0.001702
0.079645

put-miR-705
CCTGTCTGACTGGGTCTCC
6.097356
9.460857
0.00175
0.079645

put-miR-1275
AAGAAGTAGACTGGATTGG
4.175643
7.541711
0.001817
0.079645

put-miR-1204
AGGGCTGGGCACGGGGG
3.329219
8.43806
0.00195
0.079645

put-miR-857
TAAGTGGGAGTGCTCATG
5.519775
8.389269
0.001957
0.079645

put-miR-806
CACGAGAGAACGCACACC
7.044016
9.996928
0.002048
0.079645

put-miR-6 80
GTTAAGTATGCACAGG
6.207669
9.293799
0.002048
0.079645

put-miR-576
TGGCATCCTGTCTCTTGC
5.455074
8.34397
0.002094
0.079645

put-miR-444
CTGAAAAGGGGACGGATTGGGAA
4.481465
8.254479
0.002327
0.083951

put-miR-1132
CACGCTGTCTTTTGTTTCTCT
5.505609
11.5441
0.002357
0.083951

put-miR-1025
TGGAAGAGGGGAAAGGAGA
4.492628
7.660657
0.002418
0.083951

put-miR-496
CTAAGAGTATGAGTAGC
8.320903
10.63469
0.00246
0.083951

put-miR-657
TCAGGACATTGGACTCT
4.875422
9.301419
0.002633
0.087604

put-miR-625
GAGAAGACTGAATGCTCTTCTC
5.988262
8.702871
0.002699
0.087604

put-miR-40
GCTGGAATAGCTCAGTTGC
4.339713
10.82143
0.00295
0.093474

put-miR-666
CAGCATCATGATCATTATGG
6.351541
8.967721
0.003077
0.095259

put-miR-1098
AAGGCGAAGGATATGTTG
7.117298
9.563651
0.003171
0.095916

put-miR-538
CATTGTGCTTCGTGGGAGAGTAGGGCA
1.614431
8.767576
0.003422
0.101205

put-miR-952
GCCGACAGGTCCGGGTAA
5.048736
10.09864
0.003556
0.101506

put-miR-572
TAGATTCAGGAACTGCCA
7.280517
9.715353
0.003598
0.101506

put-miR-972
TTTAGTAGAATTGTGTTGGGT
3.277557
9.430308
0.003661
0.101506

put-miR-650
AAAAGCAAGGCGAAGAGG
2.912473
9.278157
0.003775
0.102538

put-miR-134
CAGACTGCTCGAGCTGCTGC
3.339267
9.218851
0.003866
0.102908

put-miR-975
TTTGCAGACTGGAAACT
5.625435
8.451316
0.004252
0.109356

put-miR-161
TGTCTGTAGCAATGTGCT
6.214205
9.449224
0.004553
0.109356

put-miR-1265
TGGGGATAAAGTTAGGT
3.433066
12.55135
0.004559
0.109356

put-miR-968
TGGCTGTTGCACTTCT
8.03171
10.36384
0.004661
0.109356

put-miR-1125
TTGAAGACTGGCTCTCA
4.530734
8.355286
0.00501
0.109356

put-miR-892
CAACGGTCTTGAAAACA
3.239723
8.81171
0.005015
0.109356

put-miR-1306
ATAACGTCATCTAGTGTG
4.744221
10.56016
0.005065
0.109356

put-miR-948
TGGAAGAAAACGAGGAG
5.807023
8.569858
0.005204
0.109356

put-miR-925
ATTTTGGTCTGTTGGTT
4.384338
8.643659
0.005342
0.109356

put-miR-259
ATGTAACCGGGCTTTTGTGCT
1.786601
8.598848
0.005378
0.109356

put-miR-209
GGTCCTCGGATCGGCC
4.053427
9.542155
0.005417
0.109356

put-miR-773
CAGGCAGAAGGGAGCTTGT
-2.64537
7.45467
0.005514
0.109356

put-miR-910
CACGTTCTTCTCATGGT
3.449747
7.34067
0.00564
0.109356

put-miR-664
AAAGTTGTGTTAGCTGA
5.719212
8.51182
0.005786
0.109356

put-miR-1068
TATGATTGTAAACTCTGA
5.890866
8.622725
0.005843
0.109356

put-miR-265
CACATGGGGGTAGAGCACTGACTGGG
2.110742
12.54113
0.005876
0.109356

put-miR-490
CTGCAGGAGTGTTTGAGA
2.057932
11.07639
0.005969
0.109356

put-miR-1155
CAAATGATCAAAGCAGG
2.494173
8.354137
0.006008
0.109356

put-miR-893
ACCATCCTCTGCTACCA
2.575152
8.358309
0.006075
0.109356

put-miR-1342
ATCGGAAAATGTGGGAA
5.585468
8.418657
0.006226
0.109356

put-miR-967
AAATGCATTGGATATGG
7.085615
9.549591
0.006355
0.109356

put-miR-811
GTTGTAAAGCTCTGTTG
1.99226
9.063173
0.006362
0.109356

put-miR-812
GTTCTGAGTTCTTTGGTTGGA
7.523344
9.907158
0.006484
0.109356

put-miR-1084
AGGACCATTGCGTTGCC
6.454871
9.04042
0.006577
0.109356

put-miR-626
TTCACTACTTTATCTCTTTT
2.849801
9.706572
0.006577
0.109356

put-miR-127
AGACTGTGATGACTGGGAGAGCGGGCT
2.251745
7.719415
0.006585
0.109356

put-miR-219
GAGGCTCGAGAGCAATGGC
4.972872
8.410708
0.006604
0.109356

put-miR-863
AAGTTGGAGTATGTTTTAGG
4.174184
8.270046
0.006626
0.109356

put-miR-33
CCATGACTGCAGATGG
4.437318
8.062018
0.006671
0.109356

put-miR-1246
CTGGAGATCTGTTTGGGC
6.389535
8.993512
0.00675
0.109356

put-miR-126
GTGGGGCTTAGTGCTGA
4.160086
8.05272
0.006849
0.109356

put-miR-459
GGGATCAACCTGACAA
7.00545
9.47012
0.00689
0.109356

put-miR-907
CCAACAGCTTCTGAGTTG
5.599664
9.28021
0.006923
0.109356

put-miR-171
GTCCTGTGTCTTGTACGG
2.359948
10.86341
0.006942
0.109356

put-miR-1163
AGAGGACAGGGAAGCTT
6.420538
9.017069
0.006996
0.109356

put-miR-204
AGAAGTCAGAACCTCTAT
6.610111
9.154177
0.007138
0.109356

put-miR-498
GACAGATTTTAGCTTGTCC
2.214527
8.621153
0.007148
0.109356

put-miR-286
TAACAGGCGTTGAAATTGT
6.754071
9.266989
0.007468
0.112951

put-miR-223
GATGGGGGTAGAGCACTGC
2.25836
12.07399
0.007601
0.113671

put-miR-75
TGGGGATTGTGGGTTCTC
2.009287
9.598075
0.00774
0.114174

put-miR-548
AGAGGACAGGGAAGCT
6.104866
8.784136
0.007923
0.114174

put-miR-1118
AGAGGGTTCCTGTAGACCTAGGGAGGA
2.053777
10.22693
0.007925
0.114174

put-miR-943
AGCCAGAGTTCTGATTGTGAGTG
4.954652
9.727141
0.007978
0.114174

put-miR-313
TGAGTTCTTTGGTCAGAA
6.693723
9.211486
0.00821
0.114289

put-miR-659
AGTAGCTGGTCGATTTGGC
6.996383
11.79431
0.008416
0.114289

put-miR-210
CTTCAGACTGTGAAACTGA
2.997776
9.522779
0.008481
0.114289

put-miR-144
TAGAGATAGAGCTTATG
5.529267
8.376117
0.008489
0.114289

put-miR-563
TGGAGACATTAACTATGA
5.915791
8.643491
0.008604
0.114289

put-miR-1140
TGGGAAGGGCTGCCGG
5.145788
9.310603
0.008606
0.114289

put-miR-497
TTGGTAGACTCTCACTT
4.014605
9.04369
0.008664
0.114289

put-miR-573
TGGATAACTCTTTTTGTA
6.440895
9.021507
0.008788
0.114289

put-miR-906
TATGGGAAGAATCTGGG
6.054559
8.747883
0.008793
0.114289

put-miR-231
TATGTCATGGTGGCTTTGG
-2.9467
8.39848
0.008918
0.114289

put-miR-85
GAATCCCACTTCTGACACCA
2.952626
7.663083
0.00901
0.114289

put-miR-884
ATGGTCTAGAGCTACAGGT
5.870477
8.628199
0.00911
0.114289

put-miR-918
CAGCTTCTTCCGCTTCTT
5.860051
8.60284
0.009174
0.114289

put-miR-985
GTACTGCATCTCTGCA
5.898607
8.628545
0.009188
0.114289

put-miR-320
ACTGGATCCAAGAAAAG
2.920156
8.226536
0.009571
0.11795

put-miR-67
AGGACGTTGGTCAGAGC
2.895467
7.636799
0.009857
0.119419

put-miR-221
TCTCTCAATCCTCTTGG
5.954163
8.658651
0.009869
0.119419

put-miR-471
AGAAGCAGAGAACGAGG
3.987795
8.44957
0.009973
0.119585

put-miR-1352
TGGATTGTGGGGGAACC
5.478958
8.36409
0.010086
0.119857

put-miR-610
AGGAGATATAGCTCTTGT
5.722079
8.518132
0.010392
0.122408

put-miR-48
AAAATGGATTCGAACCA
5.632443
8.450136
0.010602
0.123785

put-miR-529
TGACCTTTTGCCTTCTGC
5.426419
8.338572
0.010802
0.125018

put-miR-424
TAAAAAGTTCTCTGTTTTTC
-2.78953
7.208748
0.010937
0.12549

put-miR-24
TTGGTGCATCTGTAGTCCAAC
4.932824
10.24045
0.011113
0.126418

put-miR-164
TGAAATTCTAAATATTGCA
5.725561
8.51014
0.011372
0.126957

put-miR-229
TGGGATTTAGCTCAGC
3.799609
8.12666
0.011424
0.126957

put-miR-525
AAGTGGGAAGGCCCAGA
3.723862
8.317629
0.011446
0.126957

put-miR-325
TTCAAATCCCACTTCTGACACCA
2.927094
7.781125
0.012443
0.136691

put-miR-188
AAATGGCGATACTCAGG
6.335286
9.481014
0.012559
0.136691

put-miR-1066
TGCTTTGATCGTAGCCC
3.205461
7.447675
0.012632
0.136691

put-miR-1295
GAGGTTAGGATATCTGGCT
3.324069
7.580857
0.012893
0.13839

put-miR-588
TTTTGAACGTTCTTTCTT
1.985563
8.910298
0.013328
0.141683

put-miR-1273
AAGGGGAGGAATTTCACGTG
4.845324
8.579749
0.013413
0.141683

put-miR-783
AAGGAAAAAGCGGATA
3.722555
7.559427
0.013621
0.14275

put-miR-37
TGGTGGAGTGAAGACG
4.836261
8.547591
0.014174
0.14647

put-miR-1317
TGGAGTGTGGATTGGGG
1.625507
8.870365
0.014196
0.14647

put-miR-97
CTGCGTGGCTCTGACAC
3.27664
9.296956
0.014347
0.146889

put-miR-1016
AGGTAAAGCTCATGAGG
2.141009
9.304303
0.014567
0.148003

put-miR-546
CCAAGGGGTTGTAGGGCCACT
3.880018
10.64815
0.015027
0.15152

put-miR-1099
AGACTCCTTTATCGTA
4.881265
8.359673
0.015178
0.151894

put-miR-874
ATGAGCATTGATTTAGG
4.133563
8.481847
0.015742
0.15277

put-miR-701
TTGAGATTTGAGGGGGCCT
2.361165
8.446935
0.015782
0.15277

put-miR-279
CTGTGAAGCCTGTTGGTTTGCTGCTG
2.002787
8.036423
0.015783
0.15277

put-miR-184
TGCTGAACCTCTGTATGT
5.624113
9.598097
0.015798
0.15277

put-miR-495
CAGGGAGTGAAAGAGAATT
2.791411
9.973484
0.015923
0.15277

put-miR-90
GAAGTTAAATCCTTGGG
3.643929
8.886684
0.016047
0.15277

put-miR-468
ATAAGGAACTGCTCTCTC
4.936942
8.333361
0.016099
0.15277

put-miR-469
GCGGGGGATTAGCTCAGCTGGG
1.223156
14.10575
0.016186
0.15277

put-miR-1195
ATTCTTTGACATGCAGAT
2.561114
9.286221
0.016299
0.15277

put-miR-250
CTGGTGTAGAATTGAGG
4.411037
8.166635
0.016733
0.153408

put-miR-1264
CAGGTTTCAGACTTTAGG
2.452989
9.271027
0.0168
0.153408

put-miR-465
CCAGTTGTCGTGGGTTTTT
2.030242
8.962972
0.016867
0.153408

put-miR-1243
TGTGGATTTTTGTCATGT
4.743252
8.639084
0.016871
0.153408

put-miR-771
CCTTGATCTGACTGGGGGCC
1.886812
8.602159
0.016943
0.153408

put-miR-534
CTGTTGGAGAATTTGGAATATTAGGT
-4.34848
8.658536
0.01741
0.155563

put-miR-80
GAAGAGGGAGTGGTCTGTAAATGCG
6.380693
9.533096
0.017415
0.155563

put-miR-347
AAAGGGAAACAAGAATTCTT
1.937026
10.57284
0.017748
0.156927

put-miR-410
GGAGAATAGAACATGCTGATT
6.652715
9.666187
0.017824
0.156927

put-miR-891
TAAATGTTGGTTTGTTTGT
1.858836
8.369573
0.017921
0.156927

put-miR-189
GAGCGAAACGGCAGGAT
2.368257
8.305643
0.018423
0.160266

put-miR-842
ACCCGGAGAACTGAACT
2.045068
9.280359
0.01862
0.160514

put-miR-81
ATTTGAAAGAATGCTTG
2.468711
8.296721
0.018693
0.160514

put-miR-824
CTAGCTGAACCTCTGTAT
5.277761
8.805933
0.018935
0.161554

put-miR-958
ACAGGGCTGTGCAAAAA
3.475245
8.121044
0.019332
0.163891

put-miR-742
CAGGGCTGTGCTAACT
2.255055
7.794269
0.020414
0.171266

put-miR-605
TGAGCTTTGGAAGAAGGACCA
2.303646
8.016644
0.020459
0.171266

put-miR-374
TGTGAGGATGTTCTGTAAGGAGTGTT
4.607626
8.644756
0.020848
0.173428

put-miR-135
TGAATTACGGAAGTGTTGGTTAAT
3.311813
7.404022
0.021756
0.179859

put-miR-323
ATAAAATGGGCGTTGAGG
3.262325
8.71569
0.022489
0.184771

put-miR-506
AAGAGGGGCTTTTAGAACC
6.174059
11.22955
0.022884
0.186859

put-miR-293
GGGTAAAACTGCAGTGGGCGTTGGTAG
1.800636
10.99339
0.02336
0.189584

put-miR-524
CGTGGTGATGCTCTGACA
2.434924
7.973262
0.023561
0.189632

put-miR-517
TTGGGAAGGGCTGCCGGA
4.206993
8.774926
0.023651
0.189632

put-miR-391
ATCTCGATCCAGTAGTC
1.801909
7.884667
0.024454
0.194897

put-miR-92
AGAGACTGACTTTGAGTA
5.755643
9.030306
0.025075
0.198658

put-miR-435
TTTAGACCGTTTTTATGTC
3.735696
9.202301
0.027033
0.212767

put-miR-1080
TGTGGATTGATGCTCT
1.707634
8.549845
0.027175
0.212767

put-miR-587
TTTGTAGAAGAGGAAGCG
2.497802
8.421284
0.029781
0.231807

put-miR-1220
TAGAATGGGGCTTGTTGC
3.980805
8.446505
0.030296
0.233459

put-miR-1134
AAAGAATGAAGTTGGTCTGG
1.684102
8.848135
0.030344
0.233459

put-miR-352
TAATGAATGACTGTTTG
1.774841
8.080119
0.030753
0.23524

put-miR-1162
AAAGAACGTTCAAAGG
2.807352
8.476403
0.030994
0.235731

put-miR-377
AAAGGGCTTTGACTATTT
1.681479
13.05617
0.031488
0.237918

put-miR-294
TGCTTCCTCAATCGGT
3.603279
8.466728
0.031639
0.237918

put-miR-1229
ACAGTAGCAATGTTCTGC
3.278472
7.88184
0.032091
0.238095

put-miR-1091
GATTATGATTGTGATTGTAGC
4.964642
9.493873
0.032144
0.238095

put-miR-419
AAAAAGTTAGACTTAGG
1.437457
9.015693
0.032199
0.238095

put-miR-249
GCCAGGATGTTGGCTTA
1.617688
9.173125
0.03244
0.238442

put-miR-122
GGAACTCATGATTGTTGACTTTGG
1.814811
8.353927
0.032687
0.238442

put-miR-1320
TTAGAGGCCACTCAAT
4.820365
8.331847
0.032994
0.238442

put-miR-335
TATTTAAATGAGAACTTTGAAGC
2.147361
9.043008
0.033061
0.238442

put-miR-166
CGTTTTGGTGTTGGTTG
-3.72297
8.052795
0.033142
0.238442

put-miR-1172
AGAACCAAGAAGCTCTGG
2.612818
8.384166
0.034733
0.246677

put-miR-1207
GTGAAAAGACATAGGGGG
1.882735
9.817827
0.034763
0.246677

put-miR-1130
TAGAAGAGGGAGCTTCTTT
2.429349
9.717761
0.034842
0.246677

put-miR-247
AGAGCTAGAATCCAGG
1.990242
8.786356
0.035469
0.249784

put-miR-246
TTTATTAGAGACGGGACTTT
4.838701
8.30995
0.035789
0.250379

put-miR-870
AAAGGATGTAGACAAGGGA
1.480442
8.130793
0.03593
0.250379

put-miR-704
CAAATGAATATCTGGGA
2.582114
8.282107
0.037366
0.258799

put-miR-266
TTTAGGTACTCTGAACAA
2.505244
8.581082
0.037586
0.258799

put-miR-928
CACAGAAGGAACGTTTAGA
2.539814
8.530779
0.037862
0.258799

put-miR-959
GAAAGAGAGTGAGACTCA
2.359451
8.451334
0.038062
0.258799

put-miR-676
TGGTGGTTGGTTTTGGG
1.247728
9.504279
0.03818
0.258799

put-miR-1095
ATTGTGAATGATCTGG
4.006586
8.691739
0.038403
0.258799

put-miR-550
GCACTCTGGACTCTGAATCC
1.460704
9.782298
0.038501
0.258799

put-miR-835
TTAGGAGTAGGTTACT
1.888177
8.674219
0.038693
0.258799

put-miR-686
TGACTGTTTTATATGAGTAA
1.693385
10.42287
0.038917
0.258993

put-miR-32
ATCCCGGACGAGCCCCCATTA
1.878608
11.03059
0.039456
0.260368

put-miR-151
TTGAAACTGATATACTGTCTTAGG
2.781416
7.308382
0.039515
0.260368

put-miR-726
GATGGGCTGATTGAGGGAT
3.117005
10.49059
0.039816
0.261058

put-miR-256
ATGAGGCTGAGATTGTCC
1.962535
8.272489
0.040595
0.264863

put-miR-368
AATGAGAACTTTGAAGGCCGAAG
2.363048
14.35762
0.041097
0.266314

put-miR-1232
ACAGACTGTCTTTGGG
2.165428
8.620526
0.041263
0.266314

put-miR-1219
GAAATTATTGATCCAGTCACGA
1.298803
9.720145
0.041418
0.266314

put-miR-1276
GAAGAGTTGATCCATG
1.907277
9.309298
0.041682
0.266725

put-miR-1119
GTTTTGGGTTGAGTGAGGA
2.455642
8.629875
0.042052
0.267807

put-miR-901
GTCTATTTGGATTATCGTC
1.728483
8.113002
0.042255
0.267816

put-miR-356
GTTTGAATTGGGAAGCTGGGGG
1.750022
8.007003
0.043232
0.272707

put-miR-856
AAGGATAGGGAGGTATTT
2.182062
8.400665
0.044086
0.276787

put-miR-1244
CAGTTGGTAGAGCACCTGAC
-1.24774
10.46658
0.045019
0.281317

put-miR-476
GTGGTCAGGTAGAGAA
1.919551
8.047207
0.046618
0.288241

put-miR-142
CAGTATAATTAGGGGTTAATTGTGGGA
1.249016
8.70991
0.046684
0.288241

put-miR-639
TGGAGTGTGGATTGGG
1.474835
8.945467
0.046777
0.288241

put-miR-622
TGAGTGGTCAATGGGGG
1.336255
8.590784
0.047597
0.291931

put-miR-337
TGGGCTCAAGCTTTCTCT
2.374139
8.27944
0.047999
0.291931

put-miR-422
TTTAGGGTTTTAAGGTGTTA
1.290525
11.98963
0.048034
0.291931

put-miR-1339
GGACTGAGAGCTCTTTCTG
3.091573
10.60449
0.048448
0.293113

put-miR-1356
GTGCTGCATGGCTGTCA
1.345358
8.820822
0.049044
0.295237

put-miR-29
GAGATTTACGACCTAGG
1.337942
9.63023
0.049243
0.295237

put-miR-128
TGGCTCTGACACTAGTA
2.165955
8.272955
0.049525
0.295593

put-miR-359
GAAGTGGAAGGACTATGAA
2.152809
8.475685
0.050666
0.301056

put-miR-1003
TGGACTTCAGAACAGC
4.029771
7.874318
0.050924
0.301242

put-miR-238
AGAGACAGGAACTTTGATTTT
3.690637
8.383615
0.051316
0.302217

put-miR-961
TAGCTTGATCCAGTTG
2.181109
9.760789
0.052445
0.307507

put-miR-751
AGGCTGAGACTGGACAGAAAGACCT
1.317479
8.022761
0.053486
0.312239

put-miR-1184
GCCTGCCCGGTGCTGGT
1.707305
8.999909
0.053825
0.312845

put-miR-379
GCGTGTGCGCGGGAGG
2.352869
7.584474
0.054246
0.313921

put-miR-361
CAGGTGAAATCGTGGATGT
2.224017
10.34793
0.05535
0.318896

put-miR-1111
TGATGCGTTGGGATGTAGC
1.424105
8.543294
0.055717
0.318896

put-miR-938
TTAGGAAGCTGCTGATT
1.317019
9.281869
0.055825
0.318896

MicroRNAs ID selected for the second qPCR validation step are shown in Table 4A, below.

TABLE 4A

microRNAs
Gene Number

hsa-let-7f-5p
MIMAT0000067

hsa-miR-1246
MIMAT0005898

hsa-miR-126-5p
MIMAT0000444

hsa-miR-135b-5p
MIMAT0000758

hsa-miR-21-5p
MIMAT0000076

hsa-miR-425-5p
MIMAT0003393

hsa-miR-497-5p
MIMAT0002820

hsa-miR-148a-3p
MIMAT0000243

hsa-let-7a-5p
MIMAT0000062

hsa-let-7i-5p
MIMAT0000415

hsa-miR-143-3p
MIMAT0000435

hsa-miR-34b-3p
MIMAT0004676

hsa-miR-449a
MIMAT0001541

hsa-miR-144-3p
MIMAT0000436

hsa-miR-144-5p
MIMAT0004600

hsa-miR-16-1-3p
MIMAT0004489

has-miR-934
MIMAT0004977

hsa-miR-206
MIMAT0000462

hsa-miR-103a-3p
MIMAT0000101

hsa-miR-671-3p
MIMAT0004819

hsa-miR-92a-3p
MIMAT0000092

hsa-let-7b-5p
MIMAT0000063

hsa-miR-142-3p
MIMAT0000434

hsa-miR-142-5p
MIMAT0000433

hsa-miR-29c-3p
MIMAT0000433

hsa-miR-6748-3p
MIMAT0027397

has-miR-339-5p
MIMAT0000764

has-miR-107
MIMAT0000104

hsa-miR-126-3p
MIMAT0000445

Genome position and sequence of putative microRNAs selected for the second qPCR validation step are shown in Table 4B, below.

TABLE 4B

putative microRNAs
Chr
Strand
Start
Stop
Sequence

put-miR-1204
4
+
1661740
1661756
AGGGCTGGGCACGGGGG

put-miR-1207
X
+
12647513
12647530
GTGAAAAGACATAGGGGG

put-miR-444
6
+
20984875
20984897
CTGAAAAGGGGACGGATTGGGAA

put-miR-465
2
+
29475435
29475453
CCAGTTGTCGTGGGTTTTT

put-miR-468
5
+
62391321
62391338
ATAAGGAACTGCTCTCTC

put-miR-6
16
+
67911172
67911188
GCGGACCTTGCTCAAGG

put-miR-958
16
+
51873548
51873564
ACAGGGCTGTGCAAAAA

put miR-71
10
+
132351412
132351432
GACCTTGGGTTGGGTCGTGGT

put-miR-1003
X
+
96505351
96505366
TGGACTTCAGAACAGC

put-miR-1080
12
+
131562933
131562948
TGTGGATTGATGCTCT

put-miR-188
2
+
96290475
96290491
AAATGGCGATACTCAGG

put-miR-323
12
+
54420991
54421008
ATAAAATGGGCGTTGAGG

put-miR-92
13
+
28849073
28849090
AGAGACTGACTTTGAGTA

put-miR-209
18
+
13603389
13603404
GGTCCTCGGATCGGCC

put-miR-1084
14
+
51649977
51649993
AGGACCATTGCGTTGCC

put-miR-1306
13
+
100000004
100000021
ATAACGTCATCTAGTGTG

put-miR-325
3
+
193330821
193330843
TTCAAATCCCACTTCTGACACCA

put-miR-1146
5
+
67892184
67892199
ATAGGAGACTTCTATC

put-miR-594
17
+
46822348
46822364
TGATTTTTTTTGGCGAA

put-miR-961
7
+
150352937
150352952
TAGCTTGATCCAGTTG

put-miR-742
16
+
49579869
49579884
CAGGGCTGTGCTAACT

put-miR-469
1
+
22441119
22441140
GCGGGGGATTAGCTCAGCTGGG

put-miR-806
16
+
964420
964437
CACGAGAGAACGCACACC

put-miR-476
4
+
100244534
100244549
GTGGTCAGGTAGAGAA

put-miR-856
16
+
50873777
50873794
AAGGATAGGGAGGTATTT

put-mir-893
5
+
58317814
58317830
ACCATCCTCTGCTACCA

Genome position and sequence of other sncRNAs selected for the second qPCR validation step are shown in Table 4C, below.

TABLE 4C

small non-

coding

RNAs
Chr
Strand
Start
Stop
Sequence

RNU4-6p
X
-
16893269
16893390
TATCGTAGCCAATGAGGTTTATCCGA

GGCGTGATTATTGCTAATTGAAAA

tRNA18Arg
17
+
73030001
73030073
GCACTGGCCTCCTAAGCCAGGGATTG

CCT

TGGGTTCGAGTCCCACCTGGGGTA

U6.428
1
+
180727858
180727953
AAGATTAGCATGAGGATGACACGCA

AATTCGTGAAGCGTTCCATTTCTTT

RNU6-45
11
+
63737942
63738048
GGCCCTTGTGCAAGGATGACACGCA

AATTCGTGAAGCGTTCCATATTTTT

RNU6-4
1
-
31970419
31970525
GGCCCCTGCACAGGGATGACACGCA

AATTCGTGAAGCGTTCCATATTTTT

RNU6-6
2
+
201694732
201694839
GGCCCCTGTGCAAGGATGACACGCA

AATTCGTGAAGCGTTCCATATTTTT

RNU6-7
3
+
194935516
194935622
GGCCCCTGCGCAAGGATGACATGCA

AATTCGTGAAGCGTTCCATATTTTT

RNU6-73
13
+
28402900
28403006
GGCCCCTGTGCAAGGATGACATGCA

AATTCGTGAAGCGTTCCATATTTTT

SNORD3B
17
+
18965225
18965440
CTTCTCTCCGTATTGGGGAGTGAGAG

GGAGAGAACGCGGTCTGAGTGGTT

tRNA120-
6
-
28626014
28626085
GCGCATGCTTAGCATGCATGAGGTCC

AlaAGC

CGGGTTCGATCCCCAGCATCTCCA

tRNA73Arg
6
+
28849165
28849237
GCGTCTGATTCCGGATCAGAAGATTG

CCG

AGGGTTCGAGTCCCTTCGTGGTCG

U6.168
6
-
18307204
18307310
ATGGCCCCTGCGCAAGGATGACACG

CAAATTTGTGAAGGATTCCATATTT

U6.375
4
+
109573306
109573412
GGCCCCTGTGCAAGAATGACTCGCA

AATTCGTGAAGCGTTCCATATTTTT

YRNA-684
18
+
20604559
20604666
GCTTCTTTTACTCTTTCCCTTCATTCT

CACTACTGTACCTGATTCGTCTT

U6.601
19
-
39287642
39287749
GGCCCCTGCGCAAGGATGACATGCA

AATTTGTGAAGTGTTCCATATTTTT

YRNA-255
17
+
80375102
80375197
GUGUCACCAACGUUGGUAUACAACC

CCCCACAACUAAAUUUGACUGGCUU

tRNA9-
7
+
149255133
149255205
CTTTTTGACTGTAGAGCAAGAGGTCC

TyrGTA

CTGGTTCAAATCCAGGTTCTCCCT

U2.3
1
+
150209315
150209504
TCACTTCACGCATCGATCTGGTATTG

CAGTACCTCCAGGAACAGTGCACC

U4.64
9
+
36267780
36267919
GTATCGTAGCCAATGAGGTTTATCCA

AGGTGCGATTATTGCTAATTGAAA

SNORA57
10
+
27077946
27078086
TGCTGGCGGCTTCCCATCCGCTGGTT

CTATCCTCAAACGCCGGGACACCG

UC022CJG1
Y
+
10037846
10037870
CATTGATCATCGACACTTCGAACGCA

CTTG

tRNA27-
6
+
26766444
26766516
GCGTCAGTCTCATAATCTGAAGGTCC

MetCAT

TGAGTTCGAGCCTCAGAGAGGGCA

tRNA8-
17
+
8090478
8090551
GCGCCTGTCTAGTAAACAGGAGATCC

ThrAGT

TGGGTTCGAATCCCAGCGGTGCCT

tRNA2-
4
-
156384978
156385052
GCATAAAACTTAAAATTTTATAATCA

LeuTAA

GAGGTTCAACTCCTCTTCTTAACA

tRNA9-
7
+
149255133
149255205
CTTTTTGACTGTAGAGCAAGAGGTCC

TyrGTA

CTGGTTCAAATCCAGGTTCTCCCT

YRNA-245
2
-
25919945
25920057
GTCTTTGTTGAACTCTTTCCCTCCTTC

TCATTACTGTACTTGACCAGTCT

U6.1249
1
+
67661823
67661926
GATGGCATGACCCCTGATCAAGGAC

GGCATGCAAATTTGTGAAGTATTTC

SncRNAs differentially expressed in group C vs U+M at the 3 time points are shown in Table 5, below. This table also includes: AUC, CI, count, CT average, SD, ddcq, fold change and power analysis for each individual biomarker and STEPWISE analysis.

TABLE 5

95%

Ave.
Ave.

ddcq

Power

Confidence

dcq
dcq
SD
SD
Ca −
Fold change
t-test
analysis

Ca vs U + M b
AUC
interval
Count
Ca
U + M b
Ca
U + M b
U + M b
Ca/U + M b
p-value
(p = 0.05)

hsa-let-7f-5p
0.71
0.63-0.79
134
−18.01
−16.95
0.74
1.47
−1.07
−2.09
0.00
78

hsa-miR-1246
0.69
0.61-0.77
135
−21.66
−21.17
0.75
1.11
−0.49
−1.41
0.00
221

hsa-miR-135b-5p
0.66
0.58-0.75
133
−15.34
−14.68
0.64
1.06
−0.66
−1.58
0.00
111

hsa-miR-21-5p
0.66
0.57-0.74
135
−22.44
−22.00
0.66
0.87
−0.43
−1.35
0.00
183

RNU4-6p
0.67
0.59-0.75
135
−17.44
−16.78
1.12
1.35
−0.66
−1.58
0.00
200

hsa-miR-126-5p
0.76
0.68-0.83
76
−8.25
−9.12
1.23
2.02
0.87
1.83
0.01
231

put-miR-1207
0.66
0.57-0.74
132
−15.59
−13.83
3.27
2.68
−1.76
−3.39
0.01
141

put-miR-444
0.70
0.61-0.77
100
−12.05
−11.06
1.70
1.84
−0.99
−1.98
0.01
174

U6.428
0.68
0.59-0.76
122
−12.69
−13.43
1.51
1.60
0.74
1.67
0.01
237

hsa-miR-497-5p
0.71
0.63-0.79
99
−15.22
−14.69
1.09
1.14
−0.52
−1.44
0.02
243

put-miR-465
0.81
0.73-0.87
67
−16.09
−14.64
2.07
2.28
−1.45
−2.74
0.02
125

put-miR-1204
0.63
0.54-0.71
132
−18.25
−17.26
2.39
2.37
−0.99
−1.98
0.03
305

hsa-miR-425-5p
0.63
0.54-071
135
−18.65
−18.93
0.83
0.82
0.28
1.21
0.05
457

tRNA18ArgCCT
0.62
0.59-0.75
135
−22.56
−23.05
1.67
1.63
0.50
1.41
0.05
571

put-miR-468 *
0.84
0.77-0.90
50
−14.10
−13.02
1.33
1.77
−1.08
−2.12
0.07
129

has-miR-148a-3p *
0.61
0.52-0.69
135
−19.97
−19.55
0.88
1.08
−0.41
−1.33
0.08
323

STEPWISE
0.86

95%

Average
Average

ddcq

Power

Confidence

dcq
dcq
SD
SD
Cb −
Fold change
t-test
analysis

Cb vs U + M b
AUC
interval
Count
Cb
U + M b
Cb
U + M b
U + M b
Cb/U + M b
p-value
(p = 0.05)

tRNA18ArgCCT
0.66
0.573-0.736
145
−22.31
−23.05
1.80
1.63
0.74
1.67
0.00
273

hsa-let-7a-5p
0.68
0.591-0.751
145
−20.09
−20.33
0.49
0.51
0.23
1.18
0.00
244

RNU6-45
0.67
0.584-0.745
145
−18.86
−20.02
2.19
2.20
1.16
2.23
0.00
189

RNU6-4
0.68
0.593-0.753
144
−19.90
−21.05
2.19
1.89
1.15
2.22
0.00
161

RNU6-6
0.66
0.580-0.741
144
−19.79
−20.79
2.01
1.90
1.01
2.01
0.00
194

95%

Ave.
Ave.

ddcq

Power

Confidence

dcq
dcq
SD
SD
Ca −
Fold change
t-test
analysis

Ca vs U + M b
AUC
interval
Count
Ca
U + M b
Ca
U + M b
U + M b
Ca/U + M b
p-value
(p = 0.05)

RNU6-7
0.66
0.576-0.738
145
−19.82
−20.85
2.01
1.78
1.02
2.03
0.00
175

RNU6-73
0.66
0.577-0.739
145
−19.76
−20.72
1.87
1.86
0.96
1.95
0.00
197

hsa-let-7f-5p
0.65
0.556-0.720
144
−16.24
−16.95
1.30
1.47
0.71
1.64
0.01
207

hsa-miR-135b-5p
0.64
0.555-0.719
141
−14.17
−14.68
0.90
1.06
0.51
1.43
0.01
205

hsa-let-7i-5p
0.64
0.558-0.722
145
−18.49
−18.69
0.42
0.54
0.20
1.15
0.01
328

hsa-miR-34b-3p
0.71
0.630-0.785
102
−12.33
−13.57
2.02
2.26
1.24
2.36
0.01
164

tRNA120-AlaAGC
0.76
0.677-0.824
99
−16.28
−17.76
2.95
2.61
1.48
2.79
0.01
179

U6.601
0.65
0.560-0.724
145
−18.17
−19.01
1.96
1.86
0.83
1.79
0.01
268

YRNA_255
0.64
0.558-0.722
145
−23.71
−24.55
1.77
1.65
0.84
1.79
0.01
214

U6.168
0.63
0.542-0.707
143
−16.74
−17.36
1.67
1.59
0.62
1.54
0.02
361

hsa-miR-143-3p
0.62
0.529-0.695
145
−18.17
−17.88
0.92
1.01
−0.29
−1.22
0.03
612

put-miR-6
0.90
0.839-0.944
46
−14.02
−15.23
1.82
2.12
1.21
2.31
0.03
142

SN0RD3B
0.63
0.544-0.709
145
−19.25
−19.79
1.62
1.33
0.53
1.45
0.03
383

uc022cjg1
0.61
0.524-0.690
145
−22.04
−22.40
1.05
1.00
0.36
1.28
0.03
421

tRNA73ArgCCG
0.60
0.516-0.683
145
−16.65
−17.20
2.31
1.69
0.56
1.47
0.04
634

put-miR-958
0.73
0.650-0.802
73
−10.56
−11.37
2.04
1.75
0.81
1.76
0.05
273

U6.375
0.65
0.560-0.724
144
−16.38
−17.13
1.77
1.49
0.75
1.68
0.05
237

put miR-71
0.81
0.730-0.867
49
−8.76
−9.86
1.97
2.19
1.09
2.13
0.05
196

YRNA-684 *
0.61
0.520-0.687
126
−12.30
−11.25
2.68
2.76
−1.05
−2.07
0.08
355

STEPWISE
0.86

95%

Average
Average

ddcq

Power

Confidence

dcq
dcq
SD
SD
Cb −
Fold change
t-test
analysis

Cc vs U + M c
AUC
interval
Count
Cb
U + M b
Cb
U + M b
U + M b
Cb/U + M b
p-value
(p = 0.05)

hsa-miR-144-3p
0.75
0.659-0.821
98
−12.54
−14.12
1.94
2.52
1.59
3.00
0.00
110

put-miR-1084
0.85
0.770-0.906
53
−8.30
−10.33
1.87
2.70
2.03
4.07
0.00
73

hsa-miR-144-5p
0.89
0.821-0.940
50
−10.11
−12.06
2.34
2.15
1.95
3.87
0.01
70

put-miR-188
0.87
0.796-0.924
41
−11.85
−10.13
2.23
1.91
−1.72
−3.31
0.01
80

put-miR-323
0.93
0.863-0.965
27
−6.46
−7.95
1.37
1.44
1.49
2.81
0.01
49

hsa-miR-16-1-3p
0.63
0.540-0.718
124
−13.80
−14.45
1.59
1.46
0.65
1.57
0.02
281

put-miR-92
0.88
0.809-0.932
35
−7.25
−9.07
1.94
2.98
1.82
3.53
0.02
98

put-miR-1003
0.88
0.797-0.925
41
−8.33
−9.96
1.79
2.36
1.64
3.11
0.03
92

put-miR-1080
0.84
0.765-0.902
45
−9.87
−11.22
2.42
2.20
1.35
2.55
0.04
152

RNU6-4
0.61
0.515-0.695
125
−20.26
−20.92
1.88
1.99
0.66
1.58
0.05
453

tRNA120-AlaAGC
0.67
0.576-0.751
97
−17.21
−18.21
2.63
2.52
1.00
2.00
0.05
343

hsa-miR-206 *
0.79
0.701-0.854
51
−12.09
−10.79
3.41
3.02
−1.30
−2.46
0.06
321

put-miR-6 *
0.84
0.763-0.901
39
−13.85
−15.03
1.71
2.37
1.17
2.26
0.08
168

STEPWISE
0.97

SncRNAs differentially expressed in group C vs U at the 3 time points are shown in Table 6, below. This table also includes: AUC, CI, count, CT average, SD, ddcq, fold change and power analysis for each individual biomarker and STEPWISE analysis.

TABLE 6

95%

Average
Average

Power

Confidence

dcq
dcq
SD
SD
ddcq
Fold change
t-test
analysis

Ca vs Ub
AUC
interval
Count
Ca
Ub
Ca
Ub
Ca − Ub
Ca/Ub
p-value
(p = 0.05)

hsa-let-7f-5p
0.66
0.56-0.75
104
−18.01
−17.22
0.74
1.32
−0.80
−1.74
0.00
105

hsa-miR-1246
0.69
0.59-0.78
104
−21.66
−21.17
0.75
1.04
−0.49
−1.41
0.00
189

hsa-miR-135b-5p
0.65
0.55-0.74
102
−15.34
−14.79
0.64
0.97
−0.55
−1.47
0.00
126

put-miR-465
0.84
0.75-0.90
48
−16.09
−14.27
2.07
2.37
−1.82
−3.53
0.01
83

put-miR-444
0.69
0.58-0.77
79
−12.05
−11.06
1.70
1.88
−0.99
−1.98
0.02
177

RNU4-6P
0.65
0.55-0.74
104
−17.44
−16.90
1.12
1.37
−0.54
−1.46
0.02
287

U6.428
0.67
0.57-0.76
93
−12.69
−13.33
1.51
1.56
0.64
1.56
0.02
298

hsa-miR-497-5p
0.71
0.61-0.79
80
−15.22
−14.70
1.09
1.28
−0.52
−1.44
0.03
280

put-miR-1204
0.64
0.53-0.73
101
−18.25
−17.26
2.39
2.35
−0.99
−1.98
0.03
301

hsa-miR-21-5p
0.63
0.52-0.72
104
−22.44
−22.09
0.66
0.84
−0.35
−1.27
0.04
256

put-miR-742 *
0.79
0.69-0.86
46
−21.16
−20.30
1.62
1.27
−0.86
−1.82
0.06
144

hsa-miR-126-5p *
0.74
0.65-0.83
60
−8.25
−9.06
1.23
2.05
0.81
1.76
0.07
254

put-miR-468 *
0.83
0.74-0.89
38
−14.10
−12.93
1.33
1.89
−1.17
−2.26
0.07
118

STEPWISE
0.83

95%

Average
Average

Power

Confidence

dcq
dcq
SD
SD
ddcq
Fold change
t-test
analysis

Cb vs Ub
AUC
interval
Count
Ub
Cb
Ub
Cb
Ub − Cb
Ub/Cb
p-value
(p = 0.05)

hsa-let-7f-5p
0.69
0.60-0.78
114
−17.22
−16.24
1.32
1.30
−0.98
−1.97
0.00
96

hsa-let-7a-5p
0.70
0.59-0.77
114
−20.36
−20.09
0.37
0.49
−0.27
−1.20
0.00
139

hsa-let-7i-5p
0.65
0.55-0.73
114
−18.71
−18.49
0.49
0.42
−0.22
−1.16
0.00
234

95%

Average
Average

Power

Confidence

dcq
dcq
SD
SD
ddcq
Fold change
t-test
analysis

Ca vs Ub
AUC
interval
Count
Ca
Ub
Ca
Ub
Ca − Ub
Ca/Ub
p-value
(p = 0.05)

hsa-miR-135b-5p
0.68
0.58-0.76
110
−14.79
−14.17
0.97
0.90
−0.62
−1.53
0.00
122

hsa-miR-34b-3p
0.75
0.66-0.83
78
−13.97
−12.33
2.48
2.02
−1.64
−3.12
0.00
104

RNU6-4
0.67
0.57-0.76
113
−20.97
−19.90
1.78
2.19
−1.07
−2.10
0.00
181

RNU6-45
0.66
0.56-0.75
114
−19.86
−18.86
2.20
2.19
−1.00
−2.01
0.01
250

RNU6-6
0.65
0.56-0.74
113
−20.70
−19.79
1.79
2.01
−0.91
−1.88
0.01
228

RNU6-7
0.64
0.55-0.73
114
−20.72
−19.82
1.78
2.01
−0.89
−1.85
0.01
236

RNU6-73
0.65
0.55-0.73
114
−20.62
−19.76
1.80
1.87
−0.86
−1.82
0.01
238

SNORD3B-2
0.65
0.55-0.74
114
−19.83
−19.25
1.25
1.62
−0.58
−1.49
0.01
321

YRNA-255
0.63
0.53-0.72
114
−24.44
−23.71
1.65
1.77
−0.73
−1.66
0.01
287

hsa-miR-103a-3p
0.61
0.52-0.70
112
−20.08
−19.70
0.77
0.88
−0.37
−1.30
0.02
255

U6.375
0.63
0.53-0.72
114
−17.01
−16.38
1.47
1.77
−0.63
−1.54
0.02
349

U6.601
0.62
0.53-0.72
114
−18.91
−18.17
1.75
1.96
−0.74
−1.67
0.02
329

hsa-miR-449a
0.74
0.65-0.82
65
−13.41
−11.88
3.01
2.60
−1.53
−2.89
0.03
181

hsa-miR-671-3p
0.67
0.58-0.76
78
−11.81
−12.62
1.57
1.83
0.82
1.76
0.03
222

YRNA-684
0.63
0.53-0.72
101
−11.07
−12.30
2.73
2.68
1.23
2.35
0.04
254

put-miR-1306
0.90
0.83-0.95
27
−7.93
−10.51
2.29
3.34
2.58
5.99
0.05
65

put-miR-958
0.73
0.64-0.81
59
−11.49
−10.56
1.73
2.04
−0.94
−1.91
0.05
211

tRNA120-AlaAGC
0.72
0.62-0.79
80
−17.35
−16.28
2.66
2.95
−1.07
−2.10
0.05
355

put-miR-6 *
0.90
0.82-0.95
39
−15.14
−14.02
2.21
1.82
−1.12
−2.17
0.06
169

put-miR-469 *
0.85
0.77-0.91
23
−7.16
−9.23
1.72
2.39
2.06
4.18
0.06
61

put-miR-806 *
0.82
0.73-0.8
38
−9.55
−8.60
1.49
1.81
−0.95
−1.93
0.08
159

STEPWISE
0.91

95%

Average
Average

Power

Confidence

dcq
dcq
SD
SD
ddcq
Fold change
t-test
analysis

Cc vs Uc
AUC
interval
Count
Uc
Cc
Uc
Cc
Uc − Cc
Uc/Cc
p-value
(p = 0.05)

hsa-miR-144-3p
0.72
0.62-0.80
83
−13.95
−12.54
2.54
1.94
−1.41
−2.66
0.00
133

put-miR-1084
0.83
0.74-0.89
45
−10.29
−8.30
2.54
1.87
−1.99
−3.97
0.01
67

put-miR-188
0.87
0.79-0.93
38
−10.50
−11.85
1.36
2.23
1.35
2.55
0.01
110

95%

Average
Average

Power

Confidence

dcq
dcq
SD
SD
ddcq
Fold change
t-test
analysis

Ca vs Ub
AUC
interval
Count
Ca
Ub
Ca
Ub
Ca − Ub
Ca/Ub
p-value
(p = 0.05)

put-miR-323
0.95
0.88-0.98
23
−8.07
−6.46
1.27
1.37
−1.61
−3.04
0.01
37

hsa-let-7f-5p
0.63
0.52-0.72
101
−16.95
−16.33
1.41
1.44
−0.62
−1.54
0.03
279

hsa-miR-144-5p
0.88
0.79-0.94
39
−11.85
−10.11
2.36
2.34
−1.74
−3.34
0.03
97

put-miR-92
0.96
0.89-0.99
28
−9.86
−7.25
3.06
1.94
−2.61
−6.11
0.03
44

hsa-miR-206 *
0.78
0.69-0.86
45
−10.74
−12.09
3.03
3.41
1.34
2.54
0.07
306

put-miR-476 *
0.84
0.75-0.91
37
−15.04
−16.43
1.79
2.45
1.38
2.60
0.08
131

STEPWISE
0.97

SncRNAs differentially expressed in group C vs B at the 3 time points are shown in Table 7, below. This table also includes: count, CT average, SD, ddcq, fold change and power analysis for each individual biomarker.

TABLE 7

Average
Average

Fold
Pair sample
Power

dcq
dcq
SD
SD
ddcq
change
test
analysis

Ca vs B
Count
Ca
B
Ca
B
Ca − B
Ca/B
Sig. (2-tailed)
(p = 0.05)

hsa-miR-1246
219
−21.66
−20.79
0.75
1.04
−0.87
−1.83
0.00
69

put-miR-1207
207
−15.59
−12.28
3.27
2.22
−3.30
−9.88
0.00
31

RNU4-6p
219
−17.44
−16.85
1.12
1.09
−0.59
−1.51
0.00
178

hsa-miR-143-3p
114
−18.00
−18.17
0.99
0.92
0.16
1.12
0.00
1821

hsa-miR-34b-3p
182
−13.93
−12.33
1.51
1.87
−1.60
−3.04
0.00
69

hsa-miR-449a
155
−13.48
−11.38
1.89
2.62
−2.10
−4.28
0.00
75

U4.64
107
−11.33
−11.90
2.36
2.64
0.57
1.49
0.00
991

hsa-let-7b-5p
219
−20.07
−20.26
0.58
0.58
0.19
1.14
0.00
480

hsa-miR-142-3p
114
−23.48
−23.56
0.77
0.87
0.08
1.06
0.00
5191

hsa-miR-142-5p
219
−20.83
−20.14
0.90
1.03
−0.69
−1.61
0.00
114

hsa-miR-29c-3p
219
−19.93
−19.74
0.58
0.58
−0.19
−1.14
0.00
480

put-miR-1146
122
−12.59
−11.17
2.39
2.97
−1.43
−2.69
0.00
210

tRNA9-TyrGTA
206
−13.04
−11.65
2.42
2.07
−1.39
−2.61
0.00
127

put-miR-444
133
−12.05
−10.06
1.70
2.27
−1.99
−3.96
0.01
64

has-miR-148a-3p
219
−19.97
−19.67
0.88
0.66
−0.29
−1.22
0.01
305

U2.3
219
−27.18
−27.13
1.32
1.31
−0.05
−1.03
0.01
43231

tRNA27-MetCAT
112
−18.60
−18.36
1.48
1.88
−0.24
−1.18
0.01
2548

tRNA2-LeuTAA
219
−16.87
−17.65
1.30
1.47
0.78
1.71
0.01
181

YRNA-245
219
−15.50
−14.70
1.42
1.36
−0.80
−1.74
0.01
155

hsa-let-7f-5p
219
−18.01
−17.67
0.74
1.27
−0.35
−1.27
0.02
598

hsa-miR-6748-3p
94
−14.95
−12.10
3.29
3.04
−2.85
−7.20
0.02
64

put-miR-468
64
−14.10
−12.25
1.33
1.70
−1.85
−3.60
0.05
44

put-miR-594
190
−15.15
−13.30
4.79
3.42
−1.85
−3.61
0.05
212

Average
Average

Fold
Pair sample
Power

dcq
dcq
SD
SD
ddcq
change
test
analysis

Cb vs B
Count
Cb
B
Cb
B
Cb − B
Cb/B
Sig. (2-tailed)
(p = 0.05)

hsa-miR-135b-5p
226
−14.17
−15.45
0.90
0.96
1.28
2.43
0.00
31

hsa-miR-425-5p
229
−18.87
−18.37
0.71
0.86
−0.50
−1.41
0.00
146

hsa-let-7a-5p
229
−20.09
−20.65
0.49
0.41
0.56
1.47
0.00
33

hsa-miR-143-3p
229
−18.17
−17.60
0.92
1.18
−0.57
−1.48
0.00
206

YRNA-684
196
−12.30
−10.58
2.68
2.12
−1.72
−3.29
0.00
93

U4.64
221
−11.90
−10.76
2.64
1.89
−1.14
−2.20
0.00
176

hsa-miR-142-3p
229
−23.56
−22.94
0.87
1.11
−0.63
−1.55
0.00
151

hsa-miR-142-5p
229
−20.82
−20.14
0.97
1.03
−0.68
−1.61
0.00
117

tRNA9-TyrGTA
213
−13.06
−11.65
2.84
2.07
−1.41
−2.65
0.00
137

YRNA-245
229
−15.18
−14.70
1.83
1.36
−0.48
−1.40
0.00
493

put-miR-961
144
−12.72
−11.03
3.34
2.55
−1.68
−3.21
0.00
143

hsa-let-7f-5p
229
−16.24
−17.67
1.30
1.27
1.43
2.69
0.01
44

hsa-miR-1246
229
−21.39
−20.79
1.33
1.04
−0.60
−1.52
0.01
179

hsa-miR-126-5p
144
−9.35
−8.15
1.87
1.60
−1.20
−2.30
0.01
101

hsa-miR-144-3p
208
−14.19
−13.70
2.60
2.06
−0.49
−1.41
0.01
1021

hsa-let-7b-5p
229
−20.21
−20.26
0.90
0.58
0.05
1.04
0.01
8840

hsa-miR-29c-3p
229
−19.79
−19.74
0.90
0.58
−0.05
−1.04
0.01
8840

SN0RD3B
229
−19.25
−20.20
1.62
1.03
0.94
1.92
0.02
86

hsa-miR-671-3p
157
−12.62
−11.09
1.83
1.35
−1.53
−2.89
0.02
49

UC022CJG1
229
−22.04
−22.64
1.05
0.94
0.60
1.51
0.02
139

tRNA2-LeuTAA
227
−16.87
−17.65
1.99
1.47
0.78
1.72
0.02
220

hsa-miR-339-5p
229
−15.89
−15.50
1.60
1.30
−0.39
−1.31
0.02
639

hsa-miR-21-5p
229
−21.86
−22.45
0.99
0.74
0.59
1.51
0.03
98

hsa-miR-34b-3p
180
−12.33
−12.33
2.02
1.87
0.00
−1.00
0.03
11336078

U6.168
228
−16.74
−16.82
1.67
1.56
0.07
1.05
0.03
25072

hsa-miR-16-1-3p
226
−14.16
−13.71
1.41
1.49
−0.45
−1.36
0.03
564

put-miR-1207
217
−13.48
−12.28
3.36
2.22
−1.20
−2.30
0.04
234

put-miR-468
69
−13.67
−12.25
1.68
1.70
−1.42
−2.67
0.04
77

put-miR-893
229
−28.04
−27.27
2.65
1.94
−0.77
−1.71
0.04
396

SNORA57
229
−20.82
−20.63
1.15
1.06
−0.20
−1.15
0.04
1593

Average
Average

Fold
Pair sample
Power

dcq
dcq
SD
SD
ddcq
change
test
analysis

Cc vs B
Count
Cc
B
Cc
B
Cc − B
Cc/B
Sig. (2-tailed)
(p = 0.05)

hsa-miR-135b-5p
228
−14.95
−15.45
0.96
0.96
0.50
1.41
0.00
194

hsa-miR-1246
231
−21.19
−20.79
1.21
1.04
−0.40
−1.32
0.01
378

Average
Average

Fold
Pair sample
Power

dcq
dcq
SD
SD
ddcq
change
test
analysis

Ca vs B
Count
Ca
B
Ca
B
Ca − B
Ca/B
Sig. (2-tailed)
(p = 0.05)

hsa-miR-21-5p
231
−21.88
−22.45
0.92
0.74
0.57
1.48
0.01
101

hsa-let-7f-5p
231
−16.33
−17.67
1.44
1.27
1.34
2.52
0.02
52

U6.428
215
−13.10
−12.76
1.53
1.69
−0.34
−1.26
0.02
1253

YRNA-684
201
−11.24
−10.58
3.03
2.12
−0.66
−1.58
0.02
681

U4.64
231
−16.98
−16.85
1.49
1.09
−0.13
−1.09
0.02
4432

U6.1249
160
−10.16
−8.96
3.17
2.18
−1.20
−2.30
0.02
223

RNU4-6P
231
−16.98
−16.85
1.49
1.08
−0.13
−1.09
0.03
4432

U6.168
231
−16.78
−16.82
1.57
1.56
0.04
1.03
0.04
84454

hsa-miR-92a-3p
231
−20.47
−20.50
0.68
0.46
0.03
1.02
0.04
11846

put-miR-209
97
−8.94
−8.42
2.79
2.89
−0.52
−1.43
0.04
1580

SncRNAs differentially expressed in group C vs M at the 3 time points are shown in Table 8, below. This table also includes: AUC, CI, count, CT average, SD, ddcq, fold change and power analysis for each individual biomarker and STEPWISE analysis.

TABLE 8

95%

Average
Average

Fold

Power

Confidence

dcq
dcq
SD
SD
ddcq
change
t-test
analysis

Ca vs Mb
AUC
Interval
Count
Ca
Mb
Ca
Mb
Ca − Mb
Ca/Mb
p-value
(p = 0.05)

hsa-let-7f-5p
0.81
0.69-0.92
63
−17.93
−16.40
0.763
1.62
−1.53
−2.89
0.00
37

hsa-miR-135b-5p
0.71
0.58-0.84
63
−15.26
−14.48
0.63
1.22
−0.78
−1.72
0.00
81

hsa-miR-21-5p
0.71
0.59-0.83
64
−22.36
−21.84
0.69
0.90
−0.52
−1.43
0.00
127

put-miR-1207
0.74
0.63-0.86
62
−15.73
−13.08
3.33
2.63
−2.66
−6.26
0.00
69

RNU4-6P
0.71
0.58-0.84
64
−17.37
−16.56
0.94
1.32
−0.81
−1.75
0.00
105

hsa-miR-148a-3p
0.70
0.58-0.82
64
−19.90
−19.31
0.93
1.06
−0.59
−1.50
0.01
151

hsa-miR-34b-3p
0.72
0.60-0.84
52
−14.01
−12.84
1.49
1.58
−1.18
−2.26
0.01
90

tRNA18-ArgCCT
0.68
0.55-0.80
64
−22.65
−23.57
1.69
1.45
0.92
1.89
0.01
157

U6.428
0.67
0.54-0.79
58
−12.61
−13.60
1.39
1.69
0.99
1.99
0.01
128

hsa-miR-425-5p
0.66
0.53-0.79
64
−18.68
−19.09
0.83
0.81
0.41
1.33
0.02
208

U6.168
0.65
0.52-0.78
63
−17.03
−17.78
1.30
1.62
0.75
1.68
0.03
201

hsa-miR-103a-3p
0.65
0.51-0.78
63
−20.05
−19.82
0.597
0.79
−0.23
−1.17
0.04
490

hsa-miR-1246
0.68
0.55-0.82
64
−21.64
−21.17
0.72
1.24
−0.47
−1.38
0.04
242

hsa-miR-16-1-3p
0.65
0.53-0.79
63
−14.44
−14.94
1.26
1.36
0.50
1.41
0.04
362

put-miR-323
0.91
0.82-0.99
15
−8.42
−6.72
1.85
1.66
−1.70
−3.25
0.04
58

put-miR-594
0.71
0.59-0.84
54
−15.24
−12.40
4.90
3.97
−2.84
−7.18
0.04
131

hsa-miR-126-5p
0.80
0.68-0.92
34
−8.18
−9.25
1.12
1.99
1.06
2.09
0.05
119

hsa-miR-143-3p
0.64
0.50-0.78
64
−17.96
−17.63
0.86
1.03
−0.32
−1.25
0.05
445

hsa-miR-497-5p
0.68
0.55-0.80
42
−15.28
−14.69
1.22
0.72
−0.59
−1.50
0.05
161

put-miR-444*
0.72
0.59-0.84
44
−12.21
−11.06
1.71
1.78
−1.15
−2.21
0.06
123

STEPWISE
0.96

95%

Average
Average

Fold

Power

Confidence

dcq
dcq
SD
SD
ddcq
change
t-test
analysis

Cb vs Mb
AUC
Interval
Count
Cb
Mb
Cb
Mb
Cb − Mb
Cb/Mb
p-value
(p = 0.05)

tRNA18ArgCCT
0.73
0.62-0.83
64
−22.54
−23.57
1.66
1.45
1.03
2.04
0.00
123

RNU6-7
0.69
0.57-0.81
64
−20.44
−21.11
1.54
1.77
0.67
1.59
0.00
322

tRNA120-AlaAGC
0.84
0.74-0.93
42
−16.44
−18.71
2.90
2.27
2.27
4.83
0.00
72

U6.168
0.69
0.57-0.81
63
−17.17
−17.78
1.46
1.62
0.61
1.52
0.00
335

hsa-miR-143-3p
0.68
0.56-0.81
64
−18.25
−17.64
0.87
1.03
−0.61
−1.53
0.01
128

RNU6-45
0.69
0.57-0.81
64
−19.49
−20.32
1.68
2.21
0.83
1.78
0.01
290

RNU6-4
0.69
0.57-0.86
64
−20.55
−21.20
1.47
2.09
0.65
1.57
0.01
396

RNU6-73
0.69
0.57-0.82
64
−20.34
−20.93
1.45
2.01
0.59
1.50
0.01
458

U6.375
0.67
0.55-0.79
63
−16.88
−17.39
1.43
1.50
0.51
1.42
0.01
433

hsa-miR-16-1-3p
0.68
0.56-0.79
62
−14.19
−14.94
1.28
1.36
0.75
1.68
0.01
166

YRNA-255
0.67
0.55-0.79
64
−24.05
−24.77
1.52
1.67
0.71
1.64
0.01
260

RNU6-6
0.69
0.57-0.81
64
−20.40
−20.98
1.48
2.10
0.59
1.50
0.02
499

tRNA73ArgCCG
0.63
0.51-0.75
64
−16.84
−17.44
2.15
1.42
0.60
1.51
0.02
495

U6.601
0.69
0.56-0.81
64
−18.76
−19.21
1.62
2.07
0.45
1.37
0.02
868

UC022CJG1
0.66
0.54-0.78
64
−22.05
−22.65
0.84
0.99
0.59
1.51
0.02
127

SNORA57
0.63
0.50-0.76
64
−20.98
−21.33
1.13
1.13
0.36
1.28
0.05
516

put-miR-6 *
0.91
0.82-0.99
22
−13.78
−15.46
1.62
2.03
1.68
3.21
0.06
59

put-miR-856 *
0.81
0.71-0.92
24
−12.97
−14.65
1.46
1.65
1.68
3.21
0.08
46

STEPWISE
0.83

95%

Average
Average

Fold

Power

Confidence

dcq
dcq
SD
SD
ddcq
change
t-test
analysis

Cc vs Mc
AUC
Interval
Count
Cc
Mc
Cc
Mc
Cc − Mc
Cc/Mc
p-value
(p = 0.05)

hsa-let-7f-5p
0.71
0.59-0.83
61
−16.44
−15.49
1.51
1.06
−0.95
−1.93
0.00
107

hsa-miR-135b-5p
0.73
0.61-0.86
58
−15.06
−14.08
0.99
1.30
−0.99
−1.98
0.00
72

hsa-miR-425-5p
0.71
0.53-0.85
61
−18.60
−19.20
0.84
1.09
0.60
1.51
0.00
134

hsa-miR-16-1-3p
0.74
0.63-0.86
60
−13.75
−15.06
1.68
1.33
1.30
2.47
0.00
75

U6.428
0.71
0.58-0.83
53
−13.29
−14.26
1.64
1.59
0.97
1.96
0.01
147

95%

Average
Average

Fold

Power

Confidence

dcq
dcq
SD
SD
ddcq
change
t-test
analysis

Ca vs Mb
AUC
Interval
Count
Ca
Mb
Ca
Mb
Ca − Mb
Ca/Mb
p-value
(p = 0.05)

tRNA120-AlaAGC
0.76
0.64-0.87
46
−17.20
−19.02
2.30
2.47
1.82
3.54
0.01
90

hsa-miR-144-3p
0.80
0.69-0.91
45
−12.65
−14.57
2.17
2.49
1.92
3.80
0.01
75

put-miR-1003
0.95
0.89-1.00
17
−8.45
−11.23
2.00
1.74
2.78
6.86
0.01
28

YRNA-255
0.70
0.58-0.82
61
−24.38
−25.06
1.71
1.47
0.69
1.61
0.01
292

SNORA57
0.68
0.55-0.81
61
−20.75
−21.42
1.25
1.05
0.68
1.60
0.01
159

hsa-miR-21-5p
0.67
0.53-0.80
61
−21.96
−21.40
0.87
1.03
−0.56
−1.47
0.02
151

hsa-miR-144-5p
0.91
0.83-1.00
22
−11.26
−12.45
2.21
1.73
1.19
2.28
0.02
148

put-miR-1080
0.86
0.75-0.96
24
−10.51
−12.11
2.45
2.06
1.60
3.04
0.02
108

tRNA27-MetCAT
0.65
0.53-0.78
61
−18.80
−19.42
1.66
1.53
0.63
1.54
0.02
346

tRNA18ArgCCT
0.64
0.52-0.77
61
−23.00
−23.74
2.12
1.60
0.74
1.67
0.03
358

tRNA8-ThrAGT
0.64
0.51-0.76
61
−24.04
−24.37
2.50
2.31
0.33
1.26
0.03
2778

tRNA73ArgCCG
0.63
0.51-0.76
61
−17.19
−17.74
2.32
1.66
0.54
1.46
0.04
758

put-miR-325
0.63
0.51-0.76
61
−18.96
−19.78
2.67
1.98
0.82
1.77
0.04
448

RNU4-6P
0.61
0.47-0.74
61
−17.00
−16.23
1.57
1.09
−0.77
−1.71
0.05
173

U6.168
0.64
0.49-0.78
61
−17.09
−17.60
1.64
1.92
0.51
1.42
0.05
619

hsa-miR-671-3p
0.76
0.64-0.87
37
−11.40
−12.77
1.74
1.50
1.38
2.60
0.05
76

YRNA-245
0.62
0.49-0.74
61
−14.91
−15.30
1.79
1.07
0.39
1.31
0.05
801

put-miR-6
0.86
0.75-0.96
17
−14.22
−15.33
1.78
2.15
1.10
2.15
0.07
167

STEPWISE
0.94

First Set of Examples of Embodiments of the Present Disclosure

A1. A method of diagnosing and treating traumatic brain injury (TBI) in a human subject in need thereof, the method comprising:

- obtaining a saliva sample from the subject;
- contacting the saliva sample with a probe comprising a nucleic acid able to bind to at least one RNA biomarker selected from the group consisting of Y_RNA.255, RNU6-7, RNU6-4, RNU6-6, RNU6-73, RNU6-45, U6.375, put-miR-1207, U6.428, put-miR-742, hsa-miR-6748-3p, put-miR-6, put-miR-410, put-miR-476, put-miR-293, hsa-miR-34b-3p, hsa-miR-1271-5p, hsa-miR-449a, put-miR-806, put-miR-71, put-miR-468, put-miR-1306, put-miR-1146, put-miR-1084, put-miR-92, put-miR-209, put-miR-961, U6.1249, put-miR-188, and put-miR-1352;
- determining an amount of the at least one RNA biomarker in the saliva sample;
- identifying the subject as having TBI where the amount of the at least one RNA biomarker is increased or decreased relative to a predetermined threshold value or relative to the amount of the RNA biomarker in a control sample; and treating the subject identified as having TBI according to one or more of the following:
- subjecting the subject to a verbal, cognitive, motor, or optical test, or any combination of the foregoing;
- subjecting the subject to diagnostic imaging in the form of a CT or MRI, or a combination thereof and/or
- administering to the subject one or more neuroprotective therapies.

A2. The method according to claim A1 further comprising identifying the human subject as being fit for normal activity after undergoing successful treatment for TBI.

B1. A method of diagnosing and/or monitoring traumatic brain injury (TBI) in a subject, the method comprising determining a level of at least one RNA biomarker in a saliva sample obtained from the subject, wherein the at least one RNA biomarker is selected from the group consisting of Y_RNA.255, RNU6-7, RNU6-4, RNU6-6, RNU6-73, RNU6-45, U6.375, put-miR-1207, U6.428, put-miR-742, hsa-miR-6748-3p, put-miR-6, put-miR-410, put-miR-476, put-miR-293, hsa-miR-34b-3p, hsa-miR-1271-5p, hsa-miR-449a, put-miR-806, put-miR-71, put-miR-468, put-miR-1306, put-miR-1146, put-miR-1084, put-miR-92, put-miR-209, put-miR-961, U6.1249, put-miR-188, and put-miR-1352, or any combination thereof.

B2. The method of claim B1, wherein either an upregulated level or a downregulated level of the at least one RNA biomarker is indicative of TBI.

B3. The method of claim B1, wherein the subject is diagnosed as having TBI if the level of the at least one RNA biomarker is either above or below a predetermined threshold or increased or decreased relative to a control.

B4. The method according to claim B1 further comprising identifying the human subject as being fit for normal activity after undergoing successful treatment for TBI.

B5. The method of any one of claims B1-B4, wherein the at least one RNA biomarker further comprises one or more miRNA selected from the group consisting of hsa-miR-143-3p and hsa-miR-135b-5p.

C1. A sensor element for a detection system for diagnosing and/or monitoring TBI, the sensor element comprising a substrate functionalized with a probe specific for at least one RNA biomarker selected from the group consisting of Y_RNA.255, RNU6-7, RNU6-4, RNU6-6, RNU6-73, RNU6-45, U6.375, put-miR-1207, U6.428, put-miR-742, hsa-miR-6748-3p, put-miR-6, put-miR-410, put-miR-476, put-miR-293, hsa-miR-34b-3p, hsa-miR-1271-5p, hsa-miR-449a, put-miR-806, put-miR-71, put-miR-468, put-miR-1306, put-miR-1146, put-miR-1084, put-miR-92, put-miR-209, put-miR-961, U6.1249, put-miR-188, and put-miR-1352.

C2. The sensor element of claim C1, wherein the probe comprises a nucleic acid able to bind to the at least one RNA biomarker.

C3. The sensor element of claim C1 or C2, wherein the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of the sequence of the target RNA biomarker.

C4. The sensor element of claim C1 or C2, wherein the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of SEQ ID NO: 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, and 99.

C5. The sensor element of any one of claims C1-C4, wherein the at least one RNA biomarker further comprises one or more miRNA selected from the group consisting of hsa-miR-143-3p and hsa-miR-135b-5p.

D1. A detection system for diagnosing and/or monitoring TBI, comprising a sensor element according to the present disclosure, and a detection device capable of detecting the binding of a target RNA biomarker to the probe.

D2. The detection system according to claim D1, further comprising means to determine whether the target RNA biomarker is upregulated or downregulated.

E1. A method for determining a course of action for a subject suspected of having TBI, comprising applying a saliva sample obtained from the subject to a detection system according to the present disclosure, and if an upregulated level or a downregulated level of the at least one RNA biomarker is detected, providing a treatment for TBI.

F1. A method of treating a subject with suspected TBI, the method comprising

- determining whether an upregulated level or a downregulated level of at least one RNA biomarker selected from the group consisting of Y_RNA.255, RNU6-7, RNU6-4, RNU6-6, RNU6-73, RNU6-45, U6.375, put-miR-1207, U6.428, put-miR-742, hsa-miR-6748-3p, put-miR-6, put-miR-410, put-miR-476, put-miR-293, hsa-miR-34b-3p, hsa-miR-1271-5p, hsa-miR-449a, put-miR-806, put-miR-71, put-miR-468, put-miR-1306, put-miR-1146, put-miR-1084, put-miR-92, put-miR-209, put-miR-961, U6.1249, put-miR-188, and put-miR-1352 is detectable in a saliva sample obtained from the subject, and
- if an upregulated level or a downregulated level of at least one RNA biomarker is detected, providing treatment for TBI to the subject.

F2. The method of claim F1, wherein the at least one RNA biomarker further comprises one or more miRNA selected from the group consisting of hsa-miR-143-3p and hsa-miR-135b-5p.

G1. A method of detecting an RNA biomarker in a saliva sample, the method comprising

- obtaining a saliva sample from a human subject,
- contacting the saliva sample with at least one oligonucleotide primer complementary to at least one RNA biomarker selected from the group consisting of Y_RNA.255, RNU6-7, RNU6-4, RNU6-6, RNU6-73, RNU6-45, U6.375, put-miR-1207, U6.428, put-miR-742, hsa-miR-6748-3p, put-miR-6, put-miR-410, put-miR-476, put-miR-293, hsa-miR-34b-3p, hsa-miR-1271-5p, hsa-miR-449a, put-miR-806, put-miR-71, put-miR-468, put-miR-1306, put-miR-1146, put-miR-1084, put-miR-92, put-miR-209, put-miR-961, U6.1249, put-miR-188, and put-miR-1352;
- amplifying the at least one RNA biomarker using a polymerase chain reaction; and
- detecting the amplified RNA biomarker.

G2. The method of claim G1, wherein the at least one RNA biomarker further comprises one or more miRNA selected from the group consisting of hsa-miR-143-3p and hsa-miR-135b-5p.

H1. A kit for use in a method of diagnosing and/or monitoring traumatic brain injury (TBI) in saliva from a human subject, the kit comprising at least one probe specific for at least one RNA biomarker selected from the group consisting of Y_RNA.255, RNU6-7, RNU6-4, RNU6-6, RNU6-73, RNU6-45, U6.375, put-miR-1207, U6.428, put-miR-742, hsa-miR-6748-3p, put-miR-6, put-miR-410, put-miR-476, put-miR-293, hsa-miR-34b-3p, hsa-miR-1271-5p, hsa-miR-449a, put-miR-806, put-miR-71, put-miR-468, put-miR-1306, put-miR-1146, put-miR-1084, put-miR-92, put-miR-209, put-miR-961, U6.1249, put-miR-188, and put-miR-1352.

H2. The kit of claim H1, wherein the probe comprises a nucleic acid able to bind to the at least one RNA biomarker.

H3. The kit of claim H1 or H2, wherein the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of the sequence of the target RNA biomarker.

H4. The kit of claim H1 or H2, wherein the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of SEQ ID NO: 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, and 99.

H5. The kit of any one of claims H1-H4, wherein the at least one RNA biomarker further comprises one or more miRNA selected from the group consisting of hsa-miR-143-3p and hsa-miR-135b-5p.

I1. A composition for use in a method of diagnosing and/or monitoring traumatic brain injury (TBI) in saliva from a human subject, the composition comprising at least one probe specific for at least one RNA biomarker selected from the group consisting of Y_RNA.255, RNU6-7, RNU6-4, RNU6-6, RNU6-73, RNU6-45, U6.375, put-miR-1207, U6.428, put-miR-742, hsa-miR-6748-3p, put-miR-6, put-miR-410, put-miR-476, put-miR-293, hsa-miR-34b-3p, hsa-miR-1271-5p, hsa-miR-449a, put-miR-806, put-miR-71, put-miR-468, put-miR-1306, put-miR-1146, put-miR-1084, put-miR-92, put-miR-209, put-miR-961, U6.1249, put-miR-188, and put-miR-1352.

I2. The composition of claim I1, wherein the probe comprises a nucleic acid able to bind to the at least one RNA biomarker.

I3. The composition of claim I1 or I2, wherein the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of the sequence of the target RNA biomarker.

I4. The composition of claim I1 or I2, wherein the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of SEQ ID NO: 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, and 99.

I5. The composition of any one of claims I1-I4, wherein the at least one RNA biomarker further comprises one or more miRNA selected from the group consisting of hsa-miR-143-3p and hsa-miR-135b-5p.

Second Set of Examples of Embodiments of the Present Disclosure

A1. A method of diagnosing and treating traumatic brain injury (TBI) in a human subject in need thereof, the method comprising:

- obtaining a saliva sample from the subject;
- contacting the saliva sample with a probe comprising a nucleic acid able to bind to at least one RNA biomarker:
- a. selected from the group consisting of hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-16-1-3p, hsa-miR-339-5p, hsa-miR-497-5p, put-miR-1204, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-469, put-miR-594, put-miR-856, put-miR-893, put-miR-958, RNU4-6p, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.168, U6.601, UC022CJG1, YRNA-245, and YRNA-684, or any combination thereof; and/or
- b. selected from the group consisting of put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-468, put-miR-476, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-92, put-miR-961, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, U6.1249, U6.375, U6.428, and YRNA-255, or any combination thereof;
- determining an amount of the at least one RNA biomarker in the saliva sample;
- identifying the subject as having TBI where the amount of the at least one RNA biomarker is increased or decreased relative to a predetermined threshold value or relative to the amount of the RNA biomarker in a control sample; and
- treating the subject identified as having TBI according to one or more of the following:
- subjecting the subject to a verbal, cognitive, motor, or optical test, or any combination of the foregoing;
- subjecting the subject to diagnostic imaging in the form of a CT or MRI, or a combination thereof; and/or
- administering to the subject one or more neuroprotective therapies.

A2. The method of claim A1, wherein the at least one RNA biomarker further comprises one or more miRNA:

- a. selected from the group consisting of hsa-let-7i-5p, hsa-miR-107, hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-148a-3p, hsa-miR-206, hsa-miR-29c-3p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-671-3p, hsa-miR-6748-3p, and hsa-miR-934, or any combination thereof; and/or
- b. selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-miR-103a-3p, hsa-miR-21-5p, and hsa-miR-92a-3p, or any combination thereof.

A3. The method according to claim A1 further comprising identifying the human subject as being fit for normal activity after undergoing successful treatment for TBI.

- a. selected from the group consisting of hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-16-1-3p, hsa-miR-339-5p, hsa-miR-497-5p, put-miR-1204, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-469, put-miR-594, put-miR-856, put-miR-893, put-miR-958, RNU4-6p, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.168, U6.601, UC022CJG1, YRNA-245, and YRNA-684, or any combination thereof; and/or
- b. selected from the group consisting of put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-468, put-miR-476, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-92, put-miR-961, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, U6.1249, U6.375, U6.428, and YRNA-255, or any combination thereof.

B2. The method of claim B1, wherein either an upregulated level or a downregulated level of the at least one RNA biomarker is indicative of TBI.

B4. The method of any one of claims B1-B3, wherein the at least one RNA biomarker further comprises one or more miRNA:

- a. selected from the group consisting of hsa-let-7i-5p, hsa-miR-107, hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-148a-3p, hsa-miR-206, hsa-miR-29c-3p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-671-3p, hsa-miR-6748-3p, and hsa-miR-934, or any combination thereof; and/or
- b. selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-miR-103a-3p, hsa-miR-21-5p, and hsa-miR-92a-3p, or any combination thereof.

B5. The method according to claim B1 further comprising identifying the human subject as being fit for normal activity after undergoing successful treatment for TBI.

B6. The method of any one of claims B1-B7, wherein the at least one RNA biomarker further comprises one or more miRNA:

- a. selected from the group consisting of hsa-let-7i-5p, hsa-miR-107, hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-148a-3p, hsa-miR-206, hsa-miR-29c-3p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-671-3p, hsa-miR-6748-3p, and hsa-miR-934, or any combination thereof; and/or
- b. selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-miR-103a-3p, hsa-miR-21-5p, and hsa-miR-92a-3p, or any combination thereof.

C1. A sensor element for a detection system for diagnosing and/or monitoring TBI, the sensor element comprising a substrate functionalized with a probe specific for at least one RNA biomarker:

- a. selected from the group consisting of hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-16-1-3p, hsa-miR-339-5p, hsa-miR-497-5p, put-miR-1204, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-469, put-miR-594, put-miR-856, put-miR-893, put-miR-958, RNU4-6p, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.168, U6.601, UC022CJG1, YRNA-245, and YRNA-684, or any combination thereof; and/or
- b. selected from the group consisting of put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-468, put-miR-476, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-92, put-miR-961, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, U6.1249, U6.375, U6.428, and YRNA-255, or any combination thereof.

C2. The sensor element of claim C1, wherein the probe comprises a nucleic acid able to bind to the at least one RNA biomarker.

C3. The sensor element of claim C1 or C2, wherein the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of the sequence of the target RNA biomarker.

C4. The sensor element of claim C1 or C2, wherein the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of SEQ ID NO: 1, 2, 14, 16, 23, 26, 27, 29, 39, 40, 48, 71, 72, 73, 74, 75, 77, 78, 79, 80, 81, 82, 84, 85, 86, 87, 89, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, and 150.

C5. The sensor element of any one of claims C1-C4, wherein the at least one RNA biomarker further comprises one or more miRNA:

- a. selected from the group consisting of hsa-let-7i-5p, hsa-miR-107, hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-148a-3p, hsa-miR-206, hsa-miR-29c-3p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-671-3p, hsa-miR-6748-3p, and hsa-miR-934, or any combination thereof; and/or
- b. selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-miR-103a-3p, hsa-miR-21-5p, and hsa-miR-92a-3p, or any combination thereof.

D2. The detection system according to claim D1, further comprising means to determine whether the target RNA biomarker is upregulated or downregulated.

F1. A method of treating a subject with suspected TBI, the method comprising determining whether an upregulated level or a downregulated level of at least one RNA biomarker:

- a. selected from the group consisting of hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-16-1-3p, hsa-miR-339-5p, hsa-miR-497-5p, put-miR-1204, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-469, put-miR-594, put-miR-856, put-miR-893, put-miR-958, RNU4-6p, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.168, U6.601, UC022CJG1, YRNA-245, and YRNA-684, or any combination thereof; and/or
- b. selected from the group consisting of put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-468, put-miR-476, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-92, put-miR-961, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, U6.1249, U6.375, U6.428, and YRNA-255, or any combination thereof,
- is detectable in a saliva sample obtained from the subject, and
- if an upregulated level or a downregulated level of at least one RNA biomarker is detected, providing treatment for TBI to the subject.

F2. The method of claim F1, wherein the at least one RNA biomarker further comprises one or more miRNA:

- a. selected from the group consisting of hsa-let-7i-5p, hsa-miR-107, hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-148a-3p, hsa-miR-206, hsa-miR-29c-3p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-671-3p, hsa-miR-6748-3p, and hsa-miR-934, or any combination thereof; and/or
- b. selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-miR-103a-3p, hsa-miR-21-5p, and hsa-miR-92a-3p, or any combination thereof.

G1. A method of detecting an RNA biomarker in a saliva sample, the method comprising

- obtaining a saliva sample from a human subject,
- contacting the saliva sample with at least one oligonucleotide primer complementary to at least one RNA biomarker:
- a. selected from the group consisting of hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-16-1-3p, hsa-miR-339-5p, hsa-miR-497-5p, put-miR-1204, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-469, put-miR-594, put-miR-856, put-miR-893, put-miR-958, RNU4-6p, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.168, U6.601, UC022CJG1, YRNA-245, and YRNA-684, or any combination thereof; and/or
- b. selected from the group consisting of put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-468, put-miR-476, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-92, put-miR-961, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, U6.1249, U6.375, U6.428, and YRNA-255, or any combination thereof;
- amplifying the at least one RNA biomarker using a polymerase chain reaction; and
- detecting the amplified RNA biomarker.

G2. The method of claim G1, wherein the at least one RNA biomarker further comprises one or more miRNA:

- a. selected from the group consisting of hsa-let-7i-5p, hsa-miR-107, hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-148a-3p, hsa-miR-206, hsa-miR-29c-3p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-671-3p, hsa-miR-6748-3p, and hsa-miR-934, or any combination thereof; and/or
- b. selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-miR-103a-3p, hsa-miR-21-5p, and hsa-miR-92a-3p, or any combination thereof.

- a. selected from the group consisting of hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-16-1-3p, hsa-miR-339-5p, hsa-miR-497-5p, put-miR-1204, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-469, put-miR-594, put-miR-856, put-miR-893, put-miR-958, RNU4-6p, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.168, U6.601, UC022CJG1, YRNA-245, and YRNA-684, or any combination thereof; and/or
- b. selected from the group consisting of put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-468, put-miR-476, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-92, put-miR-961, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, U6.1249, U6.375, U6.428, and YRNA-255, or any combination thereof.

H2. The kit of claim H1, wherein the probe comprises a nucleic acid able to bind to the at least one RNA biomarker.

H3. The kit of claim H1 or H2, wherein the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of the sequence of the target RNA biomarker.

H4. The kit of claim H1 or H2, wherein the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of SEQ ID NO: 1, 2, 14, 16, 23, 26, 27, 29, 39, 40, 48, 71, 72, 73, 74, 75, 77, 78, 79, 80, 81, 82, 84, 85, 86, 87, 89, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, and 150.

H5. The kit of any one of claims H1-H4, wherein the at least one RNA biomarker further comprises one or more miRNA:

- a. selected from the group consisting of hsa-let-7i-5p, hsa-miR-107, hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-148a-3p, hsa-miR-206, hsa-miR-29c-3p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-671-3p, hsa-miR-6748-3p, and hsa-miR-934, or any combination thereof; and/or
- b. selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-miR-103a-3p, hsa-miR-21-5p, and hsa-miR-92a-3p, or any combination thereof.

- a. selected from the group consisting of hsa-miR-1246, hsa-miR-126-3p (miR-126*), hsa-miR-144-3p (miR-144*), hsa-miR-144-5p (=miR-144*), hsa-miR-16-1-3p, hsa-miR-339-5p, hsa-miR-497-5p, put-miR-1204, put-miR-323, put-miR-325, put-miR-444, put-miR-465, put-miR-469, put-miR-594, put-miR-856, put-miR-893, put-miR-958, RNU4-6p, SNORA57, SNORD3B-2, tRNA120-AlaAGC, tRNA18-ArgCCT, tRNA27-MetCAT, tRNA2-LeuTAA, tRNA73-ArgCCG, tRNA8-ThrAGT, tRNA9-TyrGTA, U2.3, U4.64, U6.168, U6.601, UC022CJG1, YRNA-245, and YRNA-684, or any combination thereof; and/or
- b. selected from the group consisting of put-miR-1003, put-miR-1080, put-miR-1084, put-miR-1146 (2), put-miR-1207, put-miR-1306, put-miR-188, put-miR-209, put-miR-468, put-miR-476, put-miR-6, put-miR-71, put-miR-742, put-miR-806, put-miR-92, put-miR-961, RNU6-4, RNU6-45, RNU6-6, RNU6-7, RNU6-73, U6.1249, U6.375, U6.428, and YRNA-255, or any combination thereof.

I2. The composition of claim I1, wherein the probe comprises a nucleic acid able to bind to the at least one RNA biomarker.

I3. The composition of claim I1 or I2, wherein the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of the sequence of the target RNA biomarker.

I4. The composition of claim I1 or I2, wherein the probe comprises a nucleic acid having at least 70% identity with a sequence which is the complement of SEQ ID NO: 1, 2, 14, 16, 23, 26, 27, 29, 39, 40, 48, 71, 72, 73, 74, 75, 77, 78, 79, 80, 81, 82, 84, 85, 86, 87, 89, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, and 150.

I5. The composition of any one of claims I1-I4, wherein the at least one RNA biomarker further comprises one or more miRNA:

- a. selected from the group consisting of hsa-let-7i-5p, hsa-miR-107, hsa-miR-126-5p (=miR-126*), hsa-miR-135b-5p, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143-3p (=miR-143), hsa-miR-148a-3p, hsa-miR-206, hsa-miR-29c-3p, hsa-miR-34b-3p, hsa-miR-425-5p, hsa-miR-449a, hsa-miR-671-3p, hsa-miR-6748-3p, and hsa-miR-934, or any combination thereof; and/or
- b. selected from the group consisting of hsa-let-7a-5p, hsa-let-7b-5p, hsa-let-7f-5p, hsa-miR-103a-3p, hsa-miR-21-5p, and hsa-miR-92a-3p, or any combination thereof.

Other advantages that are obvious and/or inherent to the disclosure will be evident to one skilled in the art. It will be understood that certain features and sub-combinations are of utility and may be employed without reference to other features and sub-combinations. This is contemplated by and is within the scope of the claims. Since many possible embodiments may be made of the disclosure without departing from the scope thereof, it is to be understood that all matter herein set forth or shown in the accompanying drawings is to be interpreted as illustrative and not in a limiting sense.

	Number	Date	Country
	62805761	Feb 2019	US
	62884104	Aug 2019	US

	Number	Date	Country
Parent	PCT/IB2020/051273	Feb 2020	US
Child	17402491		US

SALIVARY BIOMARKERS OF BRAIN INJURY

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