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IJTMInternational Journal of Translational Medicine
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11 April 2026

Mild Traumatic Brain Injury Biomarkers: Current Status and Future Directions

,
,
and
1
Houston Methodist Hospital, Houston, TX 77030, USA
2
Asterion AI, Dallas, TX 75230, USA
3
San Antonio Military Medical Center, San Antonio, TX 78234, USA
4
Brooke Army Medical Center, Fort Sam Houston, TX 78234, USA
Int. J. Transl. Med.2026, 6(2), 16;https://doi.org/10.3390/ijtm6020016
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Abstract

Mild traumatic brain injury (mTBI) contributes substantially to years lived with disability (YLD), decreases health-related quality of life, and imposes significant costs on healthcare systems and society. Millions of people experience mTBI each year, and healthcare costs for mTBI in just the first year after injury exceed $44 billion USD. Despite the common occurrence of mTBI, estimates of incidence, prevalence, related disability, and costs vary widely. This variance is attributed to the underreporting of head impacts, inconsistent definitions of mTBI, and a lack of objective biomarkers. Currently available clinical blood biomarkers primarily assist in ruling out CT-detectable intracranial injury rather than definitively diagnosing mTBI itself, underscoring the continued need for objective, portable, and clinically specific biomarkers. Numerous imaging findings, blood proteins, and physiological measures are under investigation for these purposes, and some may have multiple uses. Specific biomarkers for acute diagnosis are needed urgently. Although many systematic reviews have been published, most focus on a single biomarker or class of biomarkers. Given the breadth of potential biomarker categories, conducting a comprehensive, systematic review across modalities is challenging. Here, we provide a narrative review summarizing the extant literature across major biomarker domains studied in adolescents and adults. We emphasize candidates supported by the most robust evidence to guide continued research and clinical translation.

1. Introduction: Clinical Impact of Mild Traumatic Brain Injury

Head impacts generate physical forces on the brain that cause structural and functional changes, producing symptoms known as mild traumatic brain injury (mTBI). Blood vessels and brain cells—especially neuronal axons—can be stretched and torn. Microstructural damage disrupts the blood–brain barrier, neurotransmitter systems, and cellular and extracellular environments [1]. These disruptions cause symptoms that include altered mental status and cognitive problems, dizziness, balance and gait disturbances, headaches, mood changes, seizures, visual problems, and sleep difficulties [2,3].
Most of the 19 to 22 million people who experience mTBI each year [4,5] recover in one to three weeks. However, 16% to 31% of patients develop long-lasting symptoms known as post-concussion syndrome (PCS) [6,7,8], which is associated with increased healthcare utilization, disability, morbidity, and mortality [6,7,8,9,10,11]. After a first mTBI, patients have an increased risk of another, which increases further after each subsequent occurrence [12]. Repeat mTBIs can cause cumulative, microscopic brain damage consistent with advanced brain aging and neurodegenerative disease (e.g., chronic traumatic encephalopathy or Alzheimer’s disease) [13,14,15].
Social determinants of health are associated with mTBI epidemiology and outcomes. Incidence and prevalence increase with age [2,3,16,17,18,19,20], and outcomes are worse for the very young and the very old. Black/African American, Hispanic/Latin, and rural patients appear to experience diagnostic and treatment disparities [21,22,23,24]. mTBI occurs slightly more often in men than in women (ratio 4:3) [25,26].
Estimates of hospital and emergency department-related costs in the first year after injury range from $13,564 in 2016 dollars to $28,563 in 2017 dollars [5,23], suggesting that annual costs for new mTBIs are $44 to $92 billion. US military service members with mTBI had three times higher health-related costs compared with those without mTBI [24]. Indirect costs include lost productivity, disability, caregiving costs, diminished quality of life, and increased morbidity and mortality. Approximately 59% of people with mTBI miss at least two weeks of work after injury, 17% do not return to work at 12 months, and 21% have reductions in their annual income [27]. Costs borne by family members and loved ones who help care for people with mTBI are both intangible and difficult to overstate.

2. The Need for Objective mTBI Biomarkers and Scope of This Review

The large ranges in estimates of mTBI incidence, prevalence, prognosis, and outcomes reflect our still nascent understanding of mTBI as a serious injury. Many head impacts go unreported, and even when a head impact is reported, mTBI is underdiagnosed, in part because of the absence of an objective diagnostic test for mTBI [2,3]. These challenges also make it difficult to assess mTBI prognosis and outcomes. Biomarkers—objective, measurable characteristics of biological processes—are needed and in development for these endpoints. Biomarkers are also important for identifying patients for clinical trials and, eventually, matching the right treatment to the right patient.
Candidate biomarkers range from changes in RNA and protein levels to structural and physiological differences measured with biofluid transcriptomics and proteomics, myriad imaging modalities, and multiple neurophysiologic measures. Studied endpoints vary from acute diagnosis to long-term prognosis. In addition to head injuries among the general public, specific populations studied include high school or professional athletes, military trainees, active-duty service members, and veterans. Adding to this high variability, different definitions of mTBI and its outcomes have been used across studies.
A systematic review across this broad range of candidates, modalities, and populations with varied definitions and endpoints is impractical. Instead, we provide a narrative review presenting our assessment based on a comprehensive literature search of which biomarkers studied in adolescents and adults have the strongest evidence to support further development for clinical use. Limited research on potential mTBI biomarkers in pre-adolescent children suggests that ongoing neurodevelopment in this population makes potential brain biomarkers inappropriate, warranting a separate study and evaluation. As such, studies on subjects younger than 12 years are outside the scope of this review. We identified articles on mTBI biomarkers in the PubMed.gov and EMBASE literature databases published between 2016 and 2024 using the search terms “(mTBI OR concussion) AND biomarker(s).” We limited the search to English-language articles with findings in adolescent and adult humans and freely available abstracts. We excluded addresses, biographies, duplicate publications, editorials, festschrifts, interviews, news, patient education, personal narratives, protocols, retracted publications, and veterinary studies. We screened abstracts to identify 269 articles presenting evidence related to mTBI biomarkers and reviewed those articles in full to assess which biomarkers had the strongest evidence to support continued development. As needed, we also read articles that were cited within those 269 articles to ensure accurate reporting of research results. Because this was a narrative review rather than a formal systematic review or meta-analysis, the selection and emphasis of biomarker domains necessarily involved author judgment, although we sought to minimize bias through a broad literature search and full-text review. The references cited include those found through our literature search or cited in the search results and verified.

3. Potential Structural Imaging Biomarkers for mTBI

Conventional CT and MRI typically do not show macroscopic changes in mTBI. Some diagnostic criteria even make the absence of MRI or CT findings a requirement to classify a traumatic brain injury (TBI) as mild. More advanced MRI techniques provide evidence of microstructural changes in mTBI and are being evaluated as potential mTBI biomarkers (Table 1).
Brain volume measurement with T1-weighted MRI shows post-mTBI atrophy that, in some cases, resembles patterns observed in aging [28,29]. Similar changes have been observed in some studies of post-traumatic stress disorder (PTSD) [30]. In T1-weighted studies that control for comorbid PTSD, specific mTBI-related differences include volume changes in areas related to cognition and memory (i.e., the hippocampus, medial orbitofrontal cortex, and entorhinal cortex). Emerging evidence, however, suggests that deficits in these functions are a long-term consequence of mTBI [31,32,33], which raises the possibility that prior mTBIs may confound the interpretation of acute mTBI. To make T1-weighted MRI useful as a clinically meaningful mTBI biomarker, the temporal evolution of these changes and their specificity relative to comorbid or overlapping conditions would need to be better defined.
Fluid-attenuated inversion recovery MRI (FLAIR) and susceptibility-weighted imaging (SWI) both show white-matter hyperintensities (WMHs) and microscopic bleeds in patients with mTBI, as early as the day of injury and for years later. However, WMHs are not specific to mTBI and so are not yet useful as a biomarker [29,34,35,36,37,38].
Diffusion-tensor imaging (DTI) provides information about axon tract integrity and connections between brain regions [39,40,41,42,43]. A systematic review reported that most reviewed studies demonstrated white matter changes after mTBI. However, variability in designs, methods, and specific findings made it difficult to draw conclusions [41]. More recent studies in military personnel and veterans show that white-matter abnormalities are present up to five years after an mTBI and may correlate with premature aging and executive function deficits [39,42]. Another study combining DTI and T1-weighted MRI volumetric measurements suggests military service members with a history of mTBI have differences at the border of white and gray matter [43]. Based on this evidence, DTI holds promise as a useful prognostic biomarker. Whether DTI is useful for diagnosis is unclear because most DTI studies have been conducted months after an mTBI occurred. Well-controlled longitudinal studies with consistent, standardized methods and analytic techniques are needed [41].
Table 1. Comparison of potential structural and functional imaging biomarkers for mild traumatic brain injury.
MR spectroscopy (MRS) evaluates changes in brain metabolites thought to reflect brain cell injury. Metabolites evaluated as potential mTBI biomarkers include N-acetyl aspartate (NAA), creatine, choline, glutamate/glutamine, and myo-inositol. A small meta-analysis of six articles presenting results in 30 patients with mTBI compared with 31 age- and sex-matched healthy individuals suggested that decreased NAA and choline and increased glutamate correlated with cognitive changes in patients with mTBI [44]. A large meta-analysis of 138 studies found that changes were most frequently seen in the corpus callosum, reflecting axonal injuries. Decreases in NAA were most consistently observed and occurred at all endpoints, from acute injury and for weeks and months to come, and the amount of decrease correlated with time since injury, with the largest occurring immediately after injury. However, NAA changes occurred across all severities of brain injury, making NAA nonspecific for mTBI [45]. Ratios of these metabolites have also shown promise as a potential biomarker. A meta-analysis across TBI severities found overall decreased NAA/Cr compared with the controls. However, in pooled analyses, NAA/Cr reductions were more consistently detected in moderate-to-severe TBI rather than mTBI [46]. A better understanding of how these metabolites change over time after an mTBI is needed for any to be useful as biomarkers.

4. Potential Functional Neuroimaging Biomarkers for mTBI

4.1. Functional MRI

Functional MRI (fMRI) measures task-related changes in cerebral blood flow, which are commonly used as a proxy for neural activity during tasks. fMRI studies suggest that mTBI causes larger areas of the brain to be activated during tasks in comparison to people without mTBI [47,48,49,50]. The fMRI studies of TBI to date have been performed months after injury, however, and more research is needed to understand longitudinal changes in fMRI after mTBI to clarify whether it could become a clinically useful biomarker.
Resting-state fMRI (rs-fMRI) evaluates brain activity in the absence of a task, observing how activity shifts from one brain region to another over time to identify functional networks. In people with mTBI, rs-fMRI shows increases in functional connectivity that may correlate with working memory [51]. Some researchers postulate that this reflects brain recovery, with increased connections in one area compensating for damage in others. Of note, rs-fMRI findings may differ between mTBI and PTSD [52], making rs-fMRI a possible way of differentiating between these conditions, which often occur together. Once again, however, these studies have been conducted months after injury and technique is still highly variable [53], precluding clinical use. Accordingly, current fMRI and rs-fMRI findings are more suggestive of subacute or chronic network alteration than clinically deployable acute diagnostic biomarkers.

4.2. Single-Photon Emission CT

Single-photon emission CT (SPECT) also measures brain activity via blood flow. SPECT has lower spatial and temporal resolution compared with fMRI or rs-fMRI. Systematic reviews suggest that SPECT may detect perfusion abnormalities not evident on standard structural imaging in some TBI populations. However, the utility of SPECT for mTBI remains limited by heterogeneity of methodology, interpretation, and clinical reference standards. The most commonly reported SPECT finding was hypoperfusion (i.e., lower blood flow) of the frontal and temporal lobes of patients with mTBI [54,55]. Several studies have reported associations between hypoperfusion and clinical mTBI symptoms [56,57,58,59,60]. Evidence for SPECT studies in mTBI diagnosis is limited by variable image interpretation methods and a lack of sensitivity and specificity data [54]. Notably, SPECT is the one imaging modality discussed in this review that requires an intravenous radioactive tracer, which may also decrease its clinical utility.

4.3. Functional Near-Infrared Spectroscopy

Functional near-infrared spectroscopy (fNIRS) uses a cap on the head that transmits light through the skull to measure blood flow. Although this technique measures blood flow only near the brain surface, a meta-analysis shows that it is useful in diagnosing and monitoring moderate-to-severe TBI [61]. fNIRS identifies alterations in patients with a history of mTBI that resemble changes reported in some neurodegenerative diseases [62,63,64,65,66]. Emerging evidence suggests that fNIRS may have the potential to detect day-of-injury changes and could eventually prove useful in the prehospital setting [67,68].

4.4. Electroencephalography

EEG directly measures electric pulses of brain activity with high temporal resolution if there is an adequate signal-to-noise ratio and appropriate artifact interpretation [69,70,71,72,83]. Like most other measures of brain activity, traditional EEG has low spatial resolution. Quantitative EEG (qEEG) uses mathematical calculations to analyze digitally recorded EEG and arrive at a more nuanced level of detail. The derived power spectrum characterizes functional interactions among brain region interactions and can be compared to normative data from age- and sex-matched healthy controls. Oscillation of brain activity in “frequency bands” can be evaluated independently or in aggregate as ratios between bands. Evaluation of these patterns over milliseconds to minutes can provide a functional interpretation of the recorded brain activity. Portable qEEG systems are being evaluated for use in prehospital settings with the same quality recording as in-hospital qEEG at the time of injury (e.g., in athletes on sidelines, in the ambulance, and upon presentation to an emergency department) [69,71,72,73,74].
In the 1930s, soon after EEG first became available, EEG changes after head trauma were reported [84]. Systematic reviews suggest that qEEG features can differentiate some mTBI cohorts from non-injured controls, although methods and findings remain variable. A systematic review showed that multiple studies identified P300 event-related potential differences in mTBI [85,86]. Recent studies suggest that both eye-blink-related and beta oscillations observed on qEEG could be mTBI biomarkers [76,87]. Multiple studies are exploring the use of machine learning to identify mTBI biomarkers within the wealth of data that EEG provides, alone or in combination with other biomarkers [79,80,81,82]. However, there is a risk of overfitting, in which signal noise is erroneously classified as a pathological pattern, producing apparently high accuracy in small training datasets that fails to generalize to independent cohorts. This failure of cross-validation accuracy may limit the usefulness of EEG features as mTBI biomarkers, and models using multiple, larger datasets with EEG from hundreds of patients and healthy individuals are needed. Additionally, the methodologies used in EEG and qEEG studies have been highly variable, and standardization of machinery, electrodes, and machine learning algorithms is needed [88].

4.5. Magnetoencephalography

Magnetoencephalography (MEG) directly measures magnetic fields of electric brain activity with a helmet connected to a large device in a temperature-controlled room. Similar to EEG, MEG offers millisecond temporal resolution, but the two modalities differ in source sensitivity and spatial distortion, making them complementary rather than interchangeable. A systematic review suggested that MEG may be more sensitive than MRI or EEG for detecting changes associated with mTBI. After an mTBI, MEG findings most commonly involve atypical low-frequency magnetic activity. MEG differences in mTBI also correlate with clinical symptoms. However, the differences observed in mTBI with MEG are not specific; similar changes occur in PTSD, brain tumors, WMHs/infarcts, epilepsy, and neurodegenerative diseases [75]. Until specificity is improved, MEG is likely to have the greatest clinical utility as part of a multimodal assessment strategy rather than as a stand-alone test. MEG measures activity only in one plane (tangential to the cortex), whereas EEG measures activity in three dimensions. Combined EEG-MEG approaches may improve source characterization by leveraging the complementary strengths of electrical and magnetic recordings [75,76,77,78].

5. Blood Biomarkers for mTBI

Blood levels of many proteins change immediately after an mTBI, and approximately 20 blood-based biomarker candidates have been evaluated [89,90]. Here, we focus on the two blood biomarkers that have been approved for clinical use and briefly summarize others that have the most accumulated evidence for eventual use.
Glial fibrillary acidic protein (GFAP) is also found primarily in astrocytes and re-leased in the acute phase of brain injury. Ubiquitin C terminal hydrolase L1 (UCH-L1), also released in the acute phase of TBI, is highly expressed in neurons. GFAP shows high sensitivity and moderate specificity for detecting intracranial injury after mild head trauma, whereas UCH-L1 shows high sensitivity but lower specificity. When used together, sensitivity and specificity for the absence of acute intracranial lesions that could be visualized on CT increase [91,92,93,94,95]. In 2018, the U.S. Food and Drug Administration approved the GFAP/UCH-L1 assay to aid with the evaluation of potential TBI in adults with a Glasgow coma score of 13 to 15, noting that a negative assay result is associated with the absence of acute intracranial lesions visualized on a head CT [90,96]. Several factors affect the test results, including age [97,98,99], levels of other brain proteins (i.e., amyloid-β) [97], and physical activity level [100]. This consideration is particularly relevant in highly active populations, such as athletes and military personnel. Although GFAP and UCH-L1 are stable after collection, post-injury elevations are transient. A blood sample must be taken within 12 h of injury for the test to have utility [90]. A point-of-care assay for GFAP/UCH-L1 that uses a stabilized plasma sample has been approved [91], but preparation of such a sample may not always be feasible (e.g., in a setting remote from advanced healthcare facilities). A whole-blood assay is being developed [90]. Importantly, current clinical use of GFAP/UCH-L1 is best understood as aiding triage for CT-detectable intracranial injury rather than establishing a definitive diagnosis of clinical mTBI itself.
Protoplasmic astrocytes surround blood vessels and synapses in the brain to regulate the blood–brain barrier and maintain synapse structure. These astrocytes selectively express S-100 calcium-binding protein B (S-100B) in the brain, which is released in the acute phase of brain injury [101]. Blood levels of S-100B are highly sensitive for intracranial CT findings (e.g., contusion or hemorrhage) after adjusting for age [102,103,104,105]. Several European professional organizations recommend incorporating S-100B into the management of selected patients with potential TBIs to reduce unnecessary head CTs [90]. Considering the low incidence of intracranial lesions on CT in the population tested, the negative predictive value was 100% in one study (95% CI: 99–100%) [106]. However, S-100B has limited specificity for mTBI and may increase downstream imaging or referral in some patients. Additionally, the diagnostic utility of S-100B is optimized when samples are obtained within three hours of injury [107], which is not feasible in many cases of mTBI.
Other potential blood biomarkers include neurofilament light (NF-L), inflammatory cytokines (e.g., interleukins [ILs]), and tau, a protein implicated in neurodegenerative diseases. Elevated NF-L levels have been reported in some sports-related and military-associated mTBI cohorts, although the timing and magnitude of these elevations have varied across studies [108,109,110]. However, observed NF-L elevations last months to years, which could confound the diagnosis of mTBI in those who have repeated events [108,109]. A meta-analysis suggests that NF-L may be better suited to prognostication than to acute diagnosis [111]. A systematic review of cytokines as potential mTBI biomarkers suggests high potential for IL-10, but varied methods across studies make it difficult to draw conclusions [112,113]. Elevated phosphorylated tau-181 levels have been correlated with mTBI in athletes and were significantly higher in those with MRI findings suggestive of mTBI [114]. Elevated tau has also been seen in military service members after exposure to sub-concussive blasts [115] with repeated mTBI, and with PCS [116,117].

6. Pupillometry

The pupillary light reflex (PLR) quantifies the speed and magnitude of pupil changes in response to light. mTBI alters PLR metrics [118,119,120], likely because attention affects PLR. However, because PLR metrics vary with age, gender, and race, multiple adjustments to normative values would be required in practice, which could complicate use. Fatigue, baseline vision, and other medical conditions also affect PLR, so pupillometry may not be specific enough to differentiate mTBI and other conditions [119,120,121,122,123]. Concerns have also been raised that PLR results in clinical trials differ from real-world implementation [120]. At present, pupillometry is best regarded as a potentially useful adjunctive physiologic marker rather than a stand-alone diagnostic or prognostic test.

7. Discussion

7.1. Current Barriers to Use and Development of mTBI Biomarkers

mTBI affects millions each year and causes adverse health, social, and economic outcomes. Objective biomarkers are needed to improve diagnostic certainty for improved clinical management and research to develop more effective treatments. Recent progress includes the development of blood biomarkers that can help rule out CT-detectable intracranial injuries, and these may reduce the use of head CTs. However, we still do not have an objective biomarker for mTBI diagnosis or prognosis with both sensitivity and specificity.
Although advanced structural and functional imaging measures show promise as potential mTBI biomarkers, only MEG and qEEG/MEG have sub-centimeter spatial resolution and sub-second temporal resolution (see Table 1). All but qEEG and MRS require large and costly equipment that is not always available, especially in the settings where mTBIs occur. Because many biomarker studies have been conducted months after injury, much of the current evidence is more relevant to prognosis than to acute diagnosis, with the notable exceptions of FLAIR, MRS, qEEG, and MEG. Currently available blood-based biomarkers primarily assist in ruling out CT-detectable intracranial injury rather than establishing a definitive diagnosis of clinical mTBI. However, these are not specific to mTBI, and the search for a blood biomarker that is both sensitive and specific for mTBI continues.
As noted throughout this review, populations and injury mechanisms (e.g., sports-related, blast injuries, falls, vehicle crashes) studied in the quest for mTBI biomarkers vary widely across studies. Biomarker research provides evidence that mTBI pathophysiology may differ with sex, age, race, and ethnicity, but few studies capture these demographics. Within biomarker domains (e.g., structural imaging, functional imaging, and blood or physiological tests), study methodology is also variable, including the timing of testing, the equipment used, and how the recorded data is analyzed. Small sample sizes and publication bias further limit generalizability and cross-study comparison.

7.2. Future Directions

Understanding prognosis and identifying reliable prognostic biomarkers depends on ensuring that the population evaluated has been correctly identified as having an mTBI, making diagnostic biomarkers a priority. Ideally, large longitudinal studies would evaluate multiple biomarkers across modalities in a well-defined population with carefully recorded mechanisms of injury or the absence of head injury. Considering that such a study is likely infeasible, research into any potential diagnostic mTBI biomarker should carefully record and control demographic factors, injury mechanisms, and data collection methodologies. Potential biomarkers with high structural and temporal resolution warrant prioritization but typically have the drawback of not being available at the time of injury. Thus, research should also focus on evaluating potential mTBI biomarkers that could be available in remote or austere locations where mTBI is likely to occur (e.g., sports arenas, combat zones, worksites, and roads). Such candidates include blood biomarkers (if results can be available without large lab equipment), EEG, fNIRS, and pupillometry. Studies evaluating more than one potential biomarker in the same population might better optimize the trade-offs of resolution and portability. For example, a population could be evaluated at the time of injury in the field with a blood draw or an EEG, and then at the hospital within 72 h with MRS or MEG. The use of multiple biomarkers might also improve specificity and sensitivity that are still lacking. Immediate research priorities should include prospective, endpoint-specific studies that standardize case definitions, timing of collection, and analytic methods across sites. Acute field-deployable candidates such as EEG, fNIRS, and blood-based approaches merit priority for translational development, whereas advanced imaging modalities may be better positioned for prognostic enrichment and mechanistic studies. Ultimately, multimodal biomarker panels may prove more clinically useful than any single biomarker class alone.

Author Contributions

Conceptualization, E.F. and A.H.; methodology, E.F., M.W.C., G.P. and A.H., validation, E.F. and A.H.; formal analysis, E.F., M.W.C., G.P., and A.H.; investigation, E.F., M.W.C., G.P., and A.H.; data curation, E.F.; writing—original draft preparation, E.F.; writing—review and editing, M.W.C., G.P., and A.H.; visualization, E.F.; supervision, A.H.; project administration, E.F. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this review article.

Conflicts of Interest

Authors EF and AH were employed by the company Asterion. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Abbreviations

The following abbreviations are used in this manuscript:
DTIDiffusion-tensor imaging
EEGElectroencephalography
FLAIRFluid-attenuated inversion recovery MRI
fMRIFunctional MRI
fNIRSFunctional near-infrared spectroscopy
GFAPGlial fibrillary acidic protein
MEGMagnetoencephalography
mTBIMild traumatic brain injury
NF-LNeurofilament light
PCSPost-concussive syndrome
PLRPupillary light reflex
PTSDPost-traumatic stress disorder
SPECTSingle-photon emission CT
SWISusceptibility-weighted imaging
qEEGQuantitative electroencephalography
rs-MRIResting-state MRI
S-100BS-100 calcium-binding protein B
TBITraumatic brain injury
UCH-L1Ubiquitin C terminal hydrolase L1
WHMWhite-matter hyperintensities

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