Purpose Exposure to repetitive head impacts sustained during routine sports participation may result in elevated levels of brain-derived biomarkers (BDM) glial fibrillar acidic protein (GFAP), NFL, total tau and ubiquitin carboxyl-terminal hydrolase L1 (UCH-L1) independent of concussion occurrence. However, the extent to which sport career duration and sex influence BDM remains unclear. This cross-sectional study examined whether biological sex and exposure-related variables, including age of first exposure to contact sports and time since most recent concussion, were associated with preseason serum concentrations of four brain-derived biomarkers in healthy contact and collision sport athletes.Methods Male and female collegiate athletes (n=700) participating in contact and collision sports were recruited from six Concussion Assessment, Research and Education (CARE) Consortium sites. Non-fasting venous blood samples were collected during preseason testing, and serum concentrations of GFAP, NFL, UCH-L1 and total tau were quantified. General linear models were used to examine whether biomarker concentrations differed by sex, with sport included as a covariate to account for differences in head impact exposure profiles, age of first exposure (AFE) to contact sports and time since most recent concussion. Separate univariate regressions were conducted within football athletes.Results Sex significantly predicted GFAP (p<0.001, η²=0.123) and NFL (p=0.029, η² =0.042) concentrations, with females exhibiting higher serum levels than males. Neither sport, AFE nor time since concussion significantly influenced biomarker concentrations. No significant predictors were identified for UCH-L1 or total tau. In the football-specific analysis, AFE and time since concussion were not associated with biomarker levels.Conclusion Collegiate females participating in contact and collision sports have significantly higher GFAP and NFL serum concentrations than age-matched and sport-matched males, independent of sport, AFE and time since concussion. These findings may contribute to understanding sex-based biological sensitivity to head impact exposure and support the development of biomarker-informed monitoring strategies in athletes.

Background: Failing to obtain adequate sleep has been associated previously with greater postconcussion symptom burdens and protracted neurocognitive recovery. Sleep-related symptoms may delay concussion recovery. Active military populations frequently obtain less sleep than is recommended. Hypothesis: Cadets and midshipmen who reported less sleep experienced prolonged recovery trajectories postconcussion. Study Design: Retrospective observational cohort. Level of Evidence: Level 4. Methods: Study participants were military service academy members from 4 United States (US) Service Academies. The primary outcome of interest was the association between sleep duration recorded during the initial concussion injury assessment and time to unrestricted return to activity (URTA). Participants were divided into groups based on sleep duration (<6, ≥6 to <7, ≥7 to ≤8, >8 hours). Kaplan-Meier survival estimates were calculated for different recovery milestones, including time (days) from initial injury to clearance for URTA, and from initiation of a graduated return to activity (GRTA) protocol and URTA clearance. Univariate and multivariable Cox proportional-hazards regression models were used to estimate hazard ratios and 95% CI for recovery by sleep group. Results: During the study period, 1339 participants (39% female; age, 19.4 ± 1.5 years; height, 175.1 ± 14.8 cm; weight, 74.1 ± 15.2 kg) sustained a concussion. Participants reporting <6 hours of sleep at their initial injury evaluation took 19% longer to reach URTA when compared with participants reporting ≥7 hours to ≤8 hours of sleep. These participants also displayed GRTA protocol durations that were 18% longer than those reporting ≥7 hours to ≤8 hours of sleep. Conclusion: Sleep duration influenced postconcussion recovery trajectories. Participants who reported <6 hours of sleep took significantly longer to reach URTA. Clinical Relevance: The amount of sleep obtained before a concussion and during a postconcussion recovery trajectory may impact the total recovery duration.

OBJECTIVE:Patterns of clinical recovery and factors that may influence return to activity after concussion have been well studied; however, data regarding return-to-learn (RTL) duration after concussion and factors that influence this period have not been adequately explored. HYPOTHESIS:We have hypothesized that sport level, sex, concussion history, and initial symptom burden will be associated with RTL duration after concussion. SETTING:The study was conducted at US military service academies. STUDY DESIGN:This was a prospective cohort study. PARTICIPANTS:A total of 1509 service academy cadets (41% female, 20.2 ± 1.48 y, 174.9 ± 10.3 cm, 73.8 ± 14.0 kg) who sustained a concussion during the study period from December 2014 to March 2020 were included. MAIN MEASURES:The primary outcome of interest was time elapsed between an incident injury and self-reported return to normal academic performance. All participants provided baseline demographics, including sex (male, female), sport level (varsity, non-varsity), and concussion history (yes, no). Participants completed standardized concussion assessments at regular time points. Initial symptom burden was collected within 48 hours after injury, and self-reported RTL duration was collected during the unrestricted return-to-activity (URTA) evaluation. RESULTS:On average, RTL duration was faster in men (8.1 ± 11.2 days) than in women (13.6 ± 20.3 days). Univariate models demonstrated that participants with an initial symptom burden ≤6 returned sooner than those endorsing 7-15 symptoms (HR = 0.73, 95% CI = 0.64-0.83, P ≤ .001) and ≥16 symptoms (HR = 0.56, 95% CI = 0.48-0.65, P ≤ .001). Sex (HR = 0.70, 95% CI = 0.62-0.77, P ≤ .001), and sport level (HR = 0.66, 95% CI = 0.59-0.73, P ≤ .001) also contributed to RTL duration in the univariate model. In the multivariable model, participants with an initial symptom burden ≤6 returned 25%-41% sooner than those endorsing 7-15 symptoms (HR = 0.75, 95% CI = 0.65-0.86, P ≤ .001) and ≥16 symptoms (HR = 0.59, 95% CI = 0.51-0.69, P ≤ .001). Sex (HR = 0.71, 95% CI = 0.64-0.80, P ≤ .001) and sport level (HR = 0.75, 95% CI = 0.67-0.85, P < .001) also contributed to RTL duration in the multivariable model. CONCLUSIONS:RTL duration for men, varsity athletes, and individuals with fewer initial symptoms after injury was significantly faster than for women, nonvarsity athletes, and individuals with a greater initial symptom burden.

Shared genetic risk between Alzheimer’s disease (AD) and concussion may help explain the association between concussion and elevated risk for dementia. However, there has been little investigation into whether AD risk genes also associate with concussion severity/recovery, and the limited findings are mixed. We used AD polygenic risk scores (PRS) and APOE genotypes to investigate associations between AD genetic risk and concussion severity/recovery in the NCAA-DoD Grand Alliance CARE Consortium (CARE) dataset. There were 1,917 injuries in the dataset upon project initiation. After removing repeated injuries, related participants, and those without genetic/outcome data, we had 931 participants. Outcomes were number of days to return to play (RTP) as a recovery measure, and four severity measures (scores on SAC and BESS, SCAT symptom severity and total number of symptoms). We calculated PRS using a published score (de Rojas et al., 2021) and performed a linear regression (MLR) of RTP by PRS in normal (<24 days) and long (>24 days) RTP subgroups. We then compared severity measures by PRS using MLR. Next, we used t-tests to examine outcomes by APOE genotype in military and civilian subgroups. We also performed chi-squared tests of RTP category (normal vs. long) by APOE genotype. Finally, we analyzed outcomes by PRS in European or African genetic ancestry subgroups using MLR. Higher PRS was associated with longer injury to RTP interval in the normal RTP (<24 days) subgroup (estimate = 0.0412, SE = 0.182, p = 0.0237). 1 SD increase in PRS resulted in a 0.412 day (9.89 hours) increase to the interval. This may be clinically meaningful in the collegiate athlete environment. We did not identify any other significant differences. Our preliminary results provide limited evidence for an impact of AD PRS on concussion recovery, though the pattern was inconsistent and its clinical significance is uncertain. Future studies should attempt to replicate these findings in larger samples with longer follow-up using PRS calculated from multiple/diverse populations, which will be especially relevant for diverse datasets like CARE.

BACKGROUND:Military service members routinely participate in combatives training (boxing, judo, martial arts, and hand-to-hand combat) to acquire and maintain mission essential skills. Despite injury mitigation strategies, high concussion incidence rates of 20.8 concussions per 100 exposures while participating in combative sports have been reported. The purpose of this study was to identify factors potentially associated with greater odds of sustaining a concussion in these combative activities in a military training environment. METHODS:A retrospective cohort study was conducted with participants enrolled at 4 military service academies participating in the concussion assessment, research, and education consortium from 2014 to 2020. Demographic information (site, varsity status, sport contact level, sex, concussion history, and headache history) and pre-injury baseline assessments (e.g., Balance Error Scoring System (BESS), Brief Symptom Inventory (BSI)) were collected at the time of enrollment. Univariate and multivariable logistic regression models were used to estimate the odds of sustaining a concussion while participating in combatives training during the follow-up period based on these pre-injury characteristics. RESULTS:During the study period, 17,681 participants (25% female;19.11 ± 1.45 years (mean ± SD)) completed a baseline assessment and 484 (35% female;19.88 ± 1.43 years) sustained a concussion during a combatives training. Univariate logistic regression models revealed females (odds ratio (OR) = 1.71; p < 0.001; 95% confidence interval (95%CI): 1.41-2.07), participating in high contact varsity sports (OR = 0.52; p < 0.001; 95%CI: 0.38-0.71), BSI total score (OR = 1.03; p < 0.001; 95%CI: 1.01-1.04), BESS total score (OR = 1.02; p < 0.001; 95%CI: 1.02-1.04), and headache history (OR = 1.43; p < 0.001; 95%CI: 1.18-1.73) were associated with greater odds of sustaining a combatives-related concussion. Multivariable models yielded similar results after controlling for significant covariates. CONCLUSION:Females, higher BSI and BESS total scores at baseline, and participants with a history of headaches had greater odds of sustaining a combatives-related concussion during the follow-up period. Conversely, participants in high contact varsity sports had lower odds of sustaining a combatives-related concussion. These different variables should be taken into account when designing combatives training programs in a military setting.

PURPOSE:Following sport-related concussions, early head impact exposure and premature return to sport are known to increase the risk of repeat concussion in football athletes, yet athletes' true post-injury head impact exposure profiles (i.e., characteristics of recorded head impacts over a given time period) and biomechanical progression have not been explored. Accordingly, this study explored how head impact exposure in American college football athletes was altered during their return to sport from concussion, particularly within the same athletic season. METHODS:This analysis compared daily volume of head impacts following concussion with pre-injury levels using head impact exposure profiles of 52 concussed collegiate football athletes from six NCAA Division I programs, and further compared these athletes to team- and position-matched controls to minimize season- or team-related factors. In addition, this study provided an analysis of the possible association between duration of recovery and change in head impact exposure following concussion using continuous linear regression. RESULTS:When comparing to pre-injury levels, 75% of concussed athletes reduced their head impact exposure in their immediate return to sport, whereas over 40% of concussed athletes did not reach their pre-injury level of head impact exposure at any point during the remainder of the concussion season segment. Furthermore, concussed athletes significantly decreased their head impact exposure over their immediate return-to-sport period when compared with team- and position-matched healthy, nonconcussed athletes over the same time period. Finally, longer postconcussion recovery times were associated with larger decreases in head impact exposure after return to sport. CONCLUSIONS:This study provides evidence for a shift in head impact exposure after returning from concussion, seen most strongly in the immediate days after return to sport. These findings align with the recent shift toward more conservative postconcussion management seen across multiple sports and playing levels.

Objective To determine base rates of postconcussional syndrome (PCS) diagnostic categorization in service academy cadets with no recent concussion Design Cross-sectional, observational study Setting Participants were recruited from 3 U.S. service academies as part of the National Collegiate Athletic Association and U.S. Department of Defense Grand Alliance: Concussion Assessment, Research and Education (CARE) Consortium. Participants 13,009 cadets completed baseline preseason testing between 2014 and 2017. After inclusion/exclusion criteria were applied, the final sample included 12,039 cadets, 9,123 men (75.8%) and 2,916 women (24.2%). Participants were 19.2±1.5 years old. Assessment of Risk Factors Neurodevelopmental history, migraine history, psychiatric disorder, competition level (varsity or non-varsity), study site (U.S. Military Academy, U.S. Coast Guard Academy, U.S. Air Force Academy), academic year, self-reported hours of sleep the night before the baseline assessment (<5h, 5.5h-6.5h, 7h-8.5h, >9h), and concussion history (women, 0, 1, >2; men, 0, 1, 2, >3). Outcome Measures PCS diagnostic categorization was classified by the International Classification of Diseases, 10th Revision (ICD-10) symptom criteria for PCS. Main Results In the absence of recent concussion, 17.8% of men and 27.6% of women reported a cluster of symptoms that would meet the ICD-10 symptom criteria for PCS. First year cadets, cadets that completed baseline testing during basic cadet training, and cadets with insufficient sleep were more likely to report a cluster of symptoms that would meet the ICD-10 symptom criteria for PCS. Conclusions These findings suggest that the ICD-10 symptom criteria for PCS are non-specific to persistent symptoms following concussion. This abstract has been published in full manuscript format and has the following citation: BMJ Citation https://link.springer.com/article/10.1007/s40279-020-01415-4

Objective Explore the association between estimated age of first exposure (eAFE) and sex with inflammatory biomarker serum levels at baseline assessment in healthy, non-concussed athletes and military cadets. We hypothesize that inflammatory biomarkers will be positively associated with eAFE for both males and females such that an earlier eAFE would result in higher baseline biomarkers. Design Prospective. Setting Six Concussion Assessment, Research, and Education (CARE) Advanced Research Core sites. Participants Male and female college-aged adults (n=276). Interventions (or Assessment of Risk Factors) Non-fasting blood samples were collected by venipuncture during pre-season testing. Biomarker serum levels were quantified using the Quanterix Simoa multiplex assay. We defined eAFE as the participant's age at the time of evaluation minus the number of years the participant reported playing his primary sport. A series of linear regression models were used to determine if eAFE predicted biomarker levels at baseline assessment. Covariate of sex was added. Outcome Measures Neurofilament light (NF-L), ubiquitin carboxyl-terminal hydrolase L1 (UCH-L1), glial fibrillary acidic protein (GFAP), and tau serum concentrations. Main Results Our models explained a significant proportion of the variance in NF-L (R2=0.11; p<0.001), UCH-L1 (R2=0.05; p<0.001), GFAP (R2=0.09; p<0.001), and tau (R2=0.073; p<0.001) such that an earlier eAFE, when controlling for sex, was associated with higher baseline biomarker serum levels. Conclusions Earlier eAFE may predict elevated NF-L, UCH-L1, GFAP, and tau serum levels in female athletes and cadets at baseline assessment. This finding provides insight into possible underlying pathophysiological differences between sexes. If biomarkers are higher for females than males at baseline, this could play an essential role in mTBI recovery outcomes.

BACKGROUND:Normative student-athlete concussion assessment data may not be appropriate for service academy members (SAMs), particularly rugby players, because of the uniqueness of their academic/military training environment. Having accurate baseline data for this population is important because of their high risk for concussion and frequent lack of assigned sports medicine professional. The primary purpose of this study was to characterise baseline performance on a concussion assessment battery, with secondary purpose to determine effect of sex and concussion history on these measures among SAM rugby players. METHODS:601 rugby-playing SAMs (19.3±1.5 years, 37.9% female) completed baseline concussion assessments: the Sport Concussion Assessment Tool (SCAT) Symptom and Symptom Severity Checklist, Standard Assessment of Concussion (SAC) and a neuropsychological test (either ImPACT (Immediate Post Concussion Assessment and Cognitive Testing) or ANAM (Automated Neuropsychological Assessment Metrics)). Groups were compared using an independent samples t-test or Mann-Whitney U test. A 2 (sex) × 2 (concussion history) ANOVA was conducted to determine the effects of sex and concussion history on outcomes. RESULTS:Women reported greater SCAT total symptoms (3.3 vs 2.8, p<0.001, r=0.143) and symptom severities (5.7 vs 4.3, p<0.001, r=0.139), and performed worse on ImPACT Visual Memory (79.3 vs 82.6, p=0.002, r=0.144) than men. Women performed better than men on SAC (28.0 vs 27.7, p=0.03, r=0.088), ImPACT Reaction Time Composite (0.59 vs 0.61, p=0.04, r=0.092) and ANAM Code Substitution Delayed (64.3 vs 61.5, p=0.04, d=0.433). Individuals with a history of concussion reported lower ImPACT Symptom Severity (2.6 vs 4.2, p=0.02, r=0.110). There was no interaction between concussion history and sex on outcomes. CONCLUSIONS:These findings provide reference data for SAM rugby players on baseline assessments and to help in clinical decision-making when managing sports-related concussion in absence of baseline data.

Background:Current protein biomarkers are only moderately predictive at identifying individuals with mild traumatic brain injury or concussion.Therefore,more accurate diagnostic markers are needed for sport-related concussion.Methods:This was a multicenter,prospective,case-control study of athletes who provided blood samples and were diagnosed with a concussion or were a matched non-concussed control within the National Collegiate Athletic Association-Department of Defense Concussion Assessment,Research,and Education Consortium conducted between 2015 and 2019.The blood was collected within 48 h of injury to identify protein abnormalities at the acute and subacute timepoints.Athletes with concussion were divided into 6 h post-injury（0-6 h post-injury） and after 6 h postinjury（7-48 h post-injury） groups.We applied a highly multiplexed proteomic technique that used a DNA aptamers assay to target 1305proteins in plasma samples from athletes with and without sport-related concussion.Results:A total of 140 athletes with concussion（79.3% males;aged 18.71±1.10 years,mean±SD） and 21 non-concussed athletes（76.2%males;19.14±1.10 years） were included in this study.We identified 338 plasma proteins that significantly differed in abundance（319 upregulated and 19 downregulated） in concussed athletes compared to non-concussed athletes.The top 20 most differentially abundant proteins discriminated concussed athletes from non-concussed athletes with an area under the curve（AUC） of 0.954（95% confidence interval:0.922-0.986）.Specifically,after 6 h of injury,the individual AUC of plasma erythrocyte membrane protein band 4.1（EPB41） and alpha-synuclein（SNCA） were 0.956 and 0.875,respectively.The combination of EPB41 and SNCA provided the best AUC（1.000）,which suggests this combination of candidate plasma biomarkers is the best for diagnosing concussion in athletes after 6 h of injury.Conclusion:Our data suggest that proteomic profiling may provide novel diagnostic protein markers and that a combination of EPB41 and SNCA is the most predictive biomarker of concussion after 6 h of injury.

ObjectiveThe aim of this study was to investigate phosphorylated tau (p-tau181) protein in plasma in a cohort of mild traumatic brain injury (mTBI) patients and a cohort of concussed athletes.MethodsThis pilot study comprised two independent cohorts. The first cohort—part of a Traumatic Head Injury Neuroimaging Classification (THINC) study—with a mean age of 46 years was composed of uninjured controls (UIC, n = 30) and mTBI patients (n = 288) recruited from the emergency department with clinical computed tomography (CT) and research magnetic resonance imaging (MRI) findings. The second cohort—with a mean age of 19 years—comprised 133 collegiate athletes with (n = 112) and without (n = 21) concussions. The participants enrolled in the second cohort were a part of a multicenter, prospective, case-control study conducted by the NCAA-DoD Concussion Assessment, Research and Education (CARE) Consortium at six CARE Advanced Research Core (ARC) sites between 2015 and 2019. Blood was collected within 48 h of injury for both cohorts. Plasma concentration (pg/ml) of p-tau181 was measured using the Single Molecule Array ultrasensitive assay.ResultsConcentrations of plasma p-tau181 in both cohorts were significantly elevated compared to controls within 48 h of injury, with the highest concentrations of p-tau181 within 18 h of injury, with an area under the curve (AUC) of 0.690–0.748, respectively, in distinguishing mTBI patients and concussed athletes from controls. Among the mTBI patients, the levels of plasma p-tau181 were significantly higher in patients with positive neuroimaging (either CT+/MRI+, n = 74 or CT−/MRI+, n = 89) compared to mTBI patients with negative neuroimaging (CT−/MRI−, n = 111) findings and UIC (P-values < 0.05).ConclusionThese findings indicate that plasma p-tau181 concentrations likely relate to brain injury, with the highest levels in patients with neuroimaging evidence of injury. Future research is needed to replicate and validate this protein assay's performance as a possible early diagnostic biomarker for mTBI/concussions.

Background Molecular-based approaches to understanding concussion pathophysiology provide complex biological information that can advance concussion research and identify potential diagnostic and/or prognostic biomarkers of injury. Objective The aim of this study was to identify gene expression changes in peripheral blood that are initiated following concussion and are relevant to concussion response and recovery. Methods We analyzed whole blood transcriptomes in a large cohort of concussed and control collegiate athletes who were participating in the multicenter prospective cohort Concussion Assessment, Research, and Education (CARE) Consortium study. Blood samples were collected from collegiate athletes at preseason (baseline), within 6 h of concussion injury, and at four additional prescribed time points spanning 24 h to 6 months post-injury. RNA sequencing was performed on samples from 230 concussed, 130 contact control, and 102 non-contact control athletes. Differential gene expression and deconvolution analysis were performed at each time point relative to baseline. Results Cytokine and immune response signaling pathways were activated immediately after concussion, but at later time points these pathways appeared to be suppressed relative to the contact control group. We also found that the proportion of neutrophils increased and natural killer cells decreased in the blood following concussion. Conclusions Transcriptome signatures in the blood reflect the known pathophysiology of concussion and may be useful for defining the immediate biological response and the time course for recovery. In addition, the identified immune response pathways and changes in immune cell type proportions following a concussion may inform future treatment strategies.

INTRODUCTION:Concussion has become the signature injury facing the U.S. military. However, little is understood about the relationship between military fitness and concussion recovery. The current study examined the recoveries of cadets at a U.S. Service Academy to determine whether preinjury physical fitness improved recovery and whether recovery was associated with post-injury physical fitness measures. METHODS:Participants were enrolled in a longitudinal study of concussion. Aerobic Fitness Test (AFT) and Physical Fitness Test (PFT) data were used to estimate cadet fitness. Survival analysis evaluated significant estimators of concussion recovery time. Linear regression models were used to explore the relationship between recovery duration and change in physical fitness scores. RESULTS:Between 2014 and 2017, 307 (n = 70; 22.80% Women) cadets who had sustained a concussion were enrolled. Preinjury physical fitness was not significantly associated with recovery duration (P > .05). Men and intercollegiate cadets took fewer days to reach recovery milestones. Compared to women, men had greater decrements in the Aerobic Fitness Test total score (P < .05) and increased 1.5-mile time postconcussion (P < .05). Women had greater decreases in push-ups postconcussion compared to males (P < .05). There was a trend for a negative association between days until asymptomatic and change in the Physical Fitness Test score (P = .07). CONCLUSION:Preconcussion physical fitness levels do not appear to impact concussion recovery time among a highly physically fit cohort. Possible methods to reduce the effect of symptom duration on strength-related physical fitness should be investigated along with evaluating reductions in strength as a possible mechanism for postconcussion injury risk.

Background: The endorsement of symptoms upon initiation of a graduated return-to-activity (GRTA) protocol has been associated with prolonged protocols. It is unclear whether there are specific symptom clusters affecting protocol durations. Purpose: To describe the endorsement of specific concussion symptom clusters at GRTA protocol initiation and examine the association between symptom cluster endorsement and GRTA protocol duration. Study Design: Cohort study; Level of evidence, 2. Methods: This study was conducted among cadets enrolled at 3 US service academies. Participants completed an evaluation upon GRTA protocol initiation. Participants endorsing symptoms were binarized based on 6 symptom clusters (cognitive, emotional, insomnia, physical, sensitivity, and ungrouped). The primary outcome of interest was GRTA protocol duration based on symptom cluster endorsement severity. Prevalence rates were calculated to describe symptom cluster endorsement. Kaplan-Meier survival estimates and univariate and multivariable Cox proportional hazards regression models were calculated for all 6 symptom clusters to estimate GRTA protocol duration while controlling for significant covariates. Results: Data from 961 concussed participants were analyzed. Of these, 636 participants were asymptomatic upon GRTA protocol initiation. Among the 325 symptomatic participants, the physical symptom cluster (80%) was most endorsed, followed by the cognitive (29%), insomnia (23%), ungrouped (19%), sensitivity (15%), and emotional (9%) clusters. Univariate results revealed a significant association between endorsing cognitive (hazard ratio [HR], 0.79; p = .001), physical (HR, 0.84; p < .001), insomnia (HR, 0.83; p = .013), sensitivity (HR, 0.70; p < .001), and ungrouped (HR, 0.75; p = .005) symptom clusters and GRTA protocol duration. Endorsing physical (HR, 0.84; p < .001) and sensitivity (HR, 0.81; p = .036) clusters maintained a significant association with GRTA protocol duration in the multivariable models. Conclusion: Participants endorsing physical or sensitivity symptom clusters displayed GRTA protocols prolonged by 16% to 19% compared with participants not endorsing that respective cluster after controlling for significant covariates.

ObjectiveTo investigate the plasma proteomic profiling in identifying biomarkers related to return to sport (RTS) following a sport-related concussion (SRC).MethodsThis multicenter, prospective, case-control study was part of a larger cohort study conducted by the NCAA-DoD Concussion Assessment, Research, and Education (CARE) Consortium, athletes (n = 140) with blood collected within 48 h of injury and reported day to asymptomatic were included in this study, divided into two groups: (1) recovery <14-days (n = 99) and (2) recovery ≥14-days (n = 41). We applied a highly multiplexed proteomic technique that uses DNA aptamers assay to target 1,305 proteins in plasma samples from concussed athletes with <14-days and ≥14-days.ResultsWe identified 87 plasma proteins significantly dysregulated (32 upregulated and 55 downregulated) in concussed athletes with recovery ≥14-days relative to recovery <14-days groups. The significantly dysregulated proteins were uploaded to Ingenuity Pathway Analysis (IPA) software for analysis. Pathway analysis showed that significantly dysregulated proteins were associated with STAT3 pathway, regulation of the epithelial mesenchymal transition by growth factors pathway, and acute phase response signaling.ConclusionOur data showed the feasibility of large-scale plasma proteomic profiling in concussed athletes with a <14-days and ≥ 14-days recovery. These findings provide a possible understanding of the pathophysiological mechanism in neurobiological recovery. Further study is required to determine whether these proteins can aid clinicians in RTS decisions.

Sport-related concussions can result from a single high magnitude impact that generates concussive symptoms, repeated subconcussive head impacts aggregating to generate concussive symptoms, or a combined effect from the two mechanisms. The array of symptoms produced by these mechanisms may be clinically interpreted as a sport-related concussion. It was hypothesized that head impact exposure resulting in concussion is influenced by severity, total number, and frequency of subconcussive head impacts. The influence of total number and magnitude of impacts was previously explored, but frequency was investigated to a lesser degree. In this analysis, head impact frequency was investigated over a new metric called ‘time delta’, the time difference from the first recorded head impact of the day until the concussive impact. Four exposure metrics were analyzed over the time delta to determine whether frequency of head impact exposure was greater for athletes on their concussion date relative to other dates of contact participation. Those metrics included head impact frequency, head impact accrual rate, risk weighted exposure (RWE), and RWE accrual rate. Athletes experienced an elevated median number of impacts, RWE, and RWE accrual rate over the time delta on their concussion date compared to non-injury sessions. This finding suggests elevated frequency of head impact exposure on the concussion date compared to other dates that may precipitate the onset of concussion.

BACKGROUND:Symptom resolution is a key marker in determining fitness for return to activity following concussion, but in some cases, distinguishing persistent symptoms due to concussion versus symptoms related to other factors can be challenging.OBJECTIVE:To determine base rates of postconcussional syndrome (PCS) diagnostic categorization in healthy cadets and student athletes with no recent concussion.METHODS:13,009 cadets and 21,006 student athletes completed baseline preseason testing. After inclusion/exclusion criteria were applied, the final sample included 12,039 cadets [9123 men (75.8%); 2916 women (24.2%)] and 18,548 student athletes [10,192 men (54.9%); 8356 women (45.1%)]. Participants completed the Sport Concussion Assessment Tool-3rd Edition (SCAT3) symptom evaluation as part of baseline preseason testing. The PCS diagnostic categorization was classified by the International Classification of Diseases, 10th Revision (ICD-10) symptom criteria for PCS.RESULTS:In the absence of recent concussion, subgroups of cadets (17.8% of men; 27.6% of women) and student athletes (11.4% of men; 20.0% of women) reported a cluster of symptoms that would meet the ICD-10 symptom criteria for PCS. Participants with insufficient sleep and/or preexisting conditions (e.g., mental health problems), freshmen cadets, and cadets at the U.S. Coast Guard Academy and at the U.S. Air Force Academy (freshmen were tested during basic cadet training) were more likely to report a cluster of symptoms that would meet the ICD-10 symptom criteria for PCS.CONCLUSION:The ICD-10 symptom criteria for PCS can be mimicked by preexisting conditions, insufficient sleep, and/or stress. Findings support person-specific assessment and management of symptoms following concussion.

BackgroundThe relationship between head impact dose and observable functional deficits remains unclear. While studies have almost exclusively examined American football athletes, in Olympic athletes there are almost no data that explore this relationship.ObjectiveWe aimed to use an impact monitoring mouthguard (IMM) to quantify head impact doses in Olympic and non-Olympic Sports, identifying high-energy impacts on video as ‘No-go’ per the NFL protocol.DesignRetrospective meta-analysis from American football, basketball, boxing, ice hockey, karate, lacrosse, mixed martial arts, rugby, tae-kwon-do, soccer.SettingSporting fieldPatients (or Participants)4500 impacts over 800 player-games.Interventions (or Assessment of Risk Factors)Impact doses where the athlete was observed as ‘no-go’.Main Outcome MeasurementsKinetic energy transfer (KE), risk-weighted exposure (RWE), peak scalar linear acceleration (PLA), peak scalar linear velocity (PLV), peak scalar angular acceleration (PAA), peak scalar angular velocity (PAV), impact location, impact direction, ‘No-go’ status.ResultsThe median KE, RWE, PLA, PAA, PLV and PAV was 5 J, 0.0002, 20 g, 1500 rad/s2, 10 rad/s and 1.5 m/s, respectively. American football athletes sustained the highest energy impact doses, boxers and mixed-martial artists sustained the highest cumulative dose for a day of competition. Ice hockey had the highest rate of ‘no-go’ impacts versus total impacts collected. Karate had the highest rotational kinematics. Of the nine (9) highest energy impacts to the side and rear of the head, all were ‘no-go’ impacts. Of the top eight (8) highest energy impacts to the front of the head, none were ‘no-go’ impacts.Conclusions‘No-go’ observations occurred in high energy impact doses to the rear and the sides of the head, while similar impact doses to the forehead seemed tolerable. Prospective Olympic athlete impact monitoring could help identify risky exposures.

Importance Validation of protein biomarkers for concussion diagnosis and management in military combative training is important, as these injuries occur outside of traditional health care settings and are generally difficult to diagnose. Objective To investigate acute blood protein levels in military cadets after combative training-associated concussions. Design, Setting, and Participants This multicenter prospective case-control study was part of a larger cohort study conducted by the National Collegiate Athletic Association and the US Department of Defense Concussion Assessment Research and Education (CARE) Consortium from February 20, 2015, to May 31, 2018. The study was performed among cadets from 2 CARE Consortium Advanced Research Core sites: the US Military Academy at West Point and the US Air Force Academy. Cadets who incurred concussions during combative training (concussion group) were compared with cadets who participated in the same combative training exercises but did not incur concussions (contact-control group). Clinical measures and blood sample collection occurred at baseline, the acute postinjury point (<6 hours), the 24- to 48-hour postinjury point, the asymptomatic postinjury point (defined as the point at which the cadet reported being asymptomatic and began the return-to-activity protocol), and 7 days after return to activity. Biomarker levels and estimated mean differences in biomarker levels were natural log (ln) transformed to decrease the skewness of their distributions. Data were collected from August 1, 2016, to May 31, 2018, and analyses were conducted from March 1, 2019, to January 14, 2020. Exposure Concussion incurred during combative training. Main Outcomes and Measures Proteins examined included glial fibrillary acidic protein, ubiquitin C-terminal hydrolase-L1, neurofilament light chain, and tau. Quantification was conducted using a multiplex assay (Simoa; Quanterix Corp). Clinical measures included the Sport Concussion Assessment Tool-Third Edition symptom severity evaluation, the Standardized Assessment of Concussion, the Balance Error Scoring System, and the 18-item Brief Symptom Inventory. Results Among 103 military service academy cadets, 67 cadets incurred concussions during combative training, and 36 matched cadets who engaged in the same training exercises did not incur concussions. The mean (SD) age of cadets in the concussion group was 18.6 (1.3) years, and 40 cadets (59.7%) were male. The mean (SD) age of matched cadets in the contact-control group was 19.5 (1.3) years, and 25 cadets (69.4%) were male. Compared with cadets in the contact-control group, those in the concussion group had significant increases in glial fibrillary acidic protein (mean difference in ln values, 0.34; 95% CI, 0.18-0.50; P < .001) and ubiquitin C-terminal hydrolase-L1 (mean difference in ln values, 0.97; 95% CI, 0.44-1.50; P < .001) levels at the acute postinjury point. The glial fibrillary acidic protein level remained high in the concussion group compared with the contact-control group at the 24- to 48-hour postinjury point (mean difference in ln values, 0.22; 95% CI, 0.06-0.38; P = .007) and the asymptomatic postinjury point (mean difference in ln values, 0.21; 95% CI, 0.05-0.36; P = .01). The area under the curve for all biomarkers combined, which was used to differentiate cadets in the concussion and contact-control groups, was 0.80 (95% CI, 0.68-0.93; P < .001) at the acute postinjury point. Conclusions and Relevance This study's findings indicate that blood biomarkers have potential for use as research tools to better understand the pathobiological changes associated with concussion and to assist with injury identification and recovery from combative training-associated concussions among military service academy cadets. These results extend the previous findings of studies of collegiate athletes with sport-associated concussions.