ABSTRACT
Objectives: To characterise a panel of neuroinjury-related blood biomarkers after sport-related concussion (SRC). We hypothesised significant differences in biomarker profiles between athletes with SRC and healthy controls at both subacute and medical clearance time points.
Methods: Thirty-eight interuniversity athletes were recruited over two athletic seasons (n = 19 SRC; n = 19 healthy matched-control). High-sensitivity immunoassay was used to evaluate 11 blood analytes at both the subacute phase after SRC and at medical clearance.
Results: Univariate analysis identified elevated circulating peroxiredoxin-6 (PRDX-6) in athletes with SRC compared to healthy controls at the subacute time point. Multivariate analyses yielded similar results in the subacute phase, but identified both PRDX-6 and T-tau as significant contributors to class separation between athletes with SRC and controls at medical clearance.
Conclusions: Our results are consistent with the increasing recognition that physiological recovery after SRC extends beyond clinical recovery. Blood biomarkers appear to be useful in elucidating the biology of brain restitution after SRC. However, their implementation requires mindfulness of factors such as academic stress, exercise, and injury heterogeneity.
Introduction
Concussion spans all age groups and includes specialised sub-populations such as athletes and military personnel (Citation1,Citation2). Despite the high prevalence and societal burden, concussion pathophysiology is unclear Citation(3). A better understanding of the complex biological processes occurring after injury is needed to help guide therapy and management (Citation4,Citation5).
Experimental animal studies have helped identify numerous secondary brain injury sequelae in the acute and subacute phases of mild traumatic brain injury (mTBI), such as local metabolic disruption, neuronal injury, and inflammation (Citation6,Citation7). In humans, recent studies employing advanced neuroimaging techniques support these early findings (Citation3,Citation8–Citation11), yet our understanding of secondary injury after sport-related concussion (SRC) remains limited Citation(12).
Peripheral blood biomarkers have emerged as a viable, non-invasive tool to further our knowledge of SRC pathophysiology (Citation13–Citation15). Multiple lines of evidence suggest that markers reflecting brain injury and repair may appear in the peripheral circulation through several mechanisms, including transport across a disrupted blood-brain barrier (BBB) (Citation15–Citation17), glymphatic clearance Citation(18), or aberrant neuroendocrine signalling (Citation19–Citation21). Indeed, alterations in various circulating indices of brain tissue damage such as glial fibrillary acidic protein (GFAP), s100 calcium-binding protein B (s100B), neuron specific enolase (NSE), αII-spectrin N-terminal fragment (SNTF) (Citation22–Citation24), and inflammatory genes (Citation25,Citation26) have been observed in the acute and sub-acute phases after SRC.
Recent evidence suggests that physiological perturbations found after concussion may extend beyond clinical recovery. Changes in functional and structural connectivity in the brain, neurometabolism, and heart-rate variability have been observed at medical clearance in athletes with SRC (Citation27–Citation30). In addition, we recently identified elevated peripheral blood chemokine levels in healthy athletes participating in collision sports Citation(14). While the consequence of these findings are yet unknown, it is possible that athletes may be exposed to additional risk by returning to play while there is potential ongoing brain dysfunction Citation(31).
Research employing blood biomarkers to characterise SRC at both the subacute phase of injury and medical clearance is limited. A number of studies have evaluated a small panel of blood biomarkers in professional men’s ice hockey, and from these investigations it appears that altered levels of markers, such as s100B, NSE, and Tau return to pre-injury levels at return to play (Citation22,Citation23,Citation32). However, there are a lack of studies that have evaluated biomarkers in multiple sports, in both male and female athletes. In addition, few indices of inflammation have been examined throughout recovery milestones in athletes; characterising blood signatures that encompass neuroinjury and inflammation at both post-injury and recovery time points may lend insight into the dynamic nature of secondary injury pathophysiology, and could highlight important biological processes related to brain restitution. Furthermore, the most recent Concussion in Sport Group Consensus Statement highlights blood biomarkers as an important research tool, but recommends further validation to determine their ultimate utility to SRC Citation(31). Hence, the purpose of this study was to advance our understanding of SRC pathophysiology, through the characterisation of blood-based biomarkers related to brain injury in the subacute period post-injury and at medical clearance. Athletes with SRC were compared to healthy athletes individually matched on sex, age, sport participation, time of season, and concussion history.
Methods
Participants
Thirty-eight interuniversity athletes were recruited between August 2014 and April 2016 from basketball (M/F), football (M), ice hockey (M/F), lacrosse (M/F), rugby (M/F), soccer (M/F), volleyball (M/F), and wrestling (M) (16 total sports). Nineteen athletes with a physician-diagnosed SRC were enrolled and assessed within the first week post-injury (average = 4 days, range = 2–8 days). Concussion diagnosis was made by a staff physician from a single clinic, in accordance to the definition set forth by the Concussion in Sport Group Citation(33). In addition, 19 healthy control athletes matched for age, sex, sport participation, previous concussion history, and time of season were enrolled; matched healthy control samples were recruited and sampled within close proximity of their injured counterparts, and then again approximately 3 weeks later to match the projected average recovery time for athletes after SRC. Participants were excluded if they were suffering from an acute illness, recovering from a musculoskeletal injury, disclosed any inflammatory-related healthy conditions (i.e., seasonal allergies), or were taking any medications beyond oral contraceptives. Throughout the study, three matched healthy controls and two athletes with SRC were lost due to attrition and/or inability to acquire a blood sample. Blood collection and administration of the Sport Concussion Assessment Tool 3 (SCAT3) was performed by members of the research team. Medical history was obtained by medical record. All participants provided written informed consent prior to enrollment, and all study procedures were approved by the Health Sciences Research Ethics Board, University of Toronto (protocol reference # 27958).
Sport concussion assessment tool – 3 (SCAT3)
The Sport Concussion Assessment Tool (SCAT) is the one of the most widely used tools to assist in the diagnosis, management, and prognosis of individuals with concussion. The SCAT3 was developed at the 4th International Conference on Concussion in Sport in 2012. The SCAT3 is comprised of a symptom evaluation, cognitive assessment by the Standardised Assessment of Concussion (SAC), neck examination, balance examination by the modified balance error scoring system (BESS), and a coordination exam. The symptom score is comprised of a 22-item post-concussion symptom scale using a seven-point Likert scale rating. Symptom severity is obtained by summing the rated symptom score for each symptom Citation(34). This symptom scale has shown reliability and validity for the assessment of both symptom presence and severity (Citation35–Citation37).
Blood sample collection
Venous blood samples were obtained from athletes at the time of their cognitive assessment. Samples were drawn into a 10-mL K2EDTA tube. At approximately one hour post-draw, specimens were centrifuged for 2 min using a PlasmaPrep 12TM centrifuge (Separation Technology Inc., FL, USA). The plasma supernatant was then aliquoted and frozen at −70°C until analysis. All samples were processed in the same manner.
Blood biomarker analysis
Biomarkers were evaluated using Meso Scale Diagnostics (MSD) 96-well MULTI-ARRAY® technology. The platform uses an array-based multiplex format with sensitive electrochemiluminescence detection via sandwich immunoassay; the capture antibody is coated on arrays within plate wells, and the detection antibody is conjugated with an electrochemiluminescent SULFO-TagTM.
A prototype assay panel was used to quantitate 11 neuroinjury-associated biomarkers; this panel was developed at MSD in part through work supported by US Army Medical Research and Materiel Command (Contract No. W81XWH-13-C-0196). The panel included GFAP, s100B, NSE, Total-tau (T-tau), neurogranin (NRGN), creatine kinase-BB isoenzyme (CKBB), visinin-like protein (VILIP)-1, von Willebrand factor (vWF), brain derived neurotrophic factor (BDNF), peroxiredoxin (PRDX)-6, and monocyte chemoattractant protein (MCP)-1.
Statistical analysis
Individual biomarker values were statistically evaluated only if they fell within the range of detection, and displayed a coefficient of variance <20% between duplicate samples. Please see supplementary Table 1 for level of detection information for all analytes, supplementary Table 2 for inter- and intra-assay variability data for each analyte, and supplementary Table 3 for the percentage of values that fell within the detectable range for each analyte.
Multivariate analysis was conducted by partial least squares discriminant analysis (PLS-DA). PLS-DA is a supervised technique used to robustly characterise the relationship between a set of predictor variables and a binary response variable. If >20% of the data points were missing for any individual biomarker, that marker was removed from the PLSDA analysis. Furthermore, if >5% of the data points were missing across the entire dataset, subjects with missing data points were removed. Missing biomarker values were then imputed using the variable mean, and were rank-transformed to ensure robustness against non-normality. Significant biomarker loadings were identified by performing bootstrap resampling on subjects (1000 iterations) to obtain empirical p-values, which were then corrected for multiple comparisons at a false discovery rate (FDR) of 0.05. For PLS plots, biomarkers are represented as the mean and standard error of the bootstrapped loadings. Univariate statistics comparing biomarker concentrations between athletes with SRC and matched controls were calculated by Mann Whitney U, and corrected at a FDR of 0.05. All Statistical analyses were conducted using in house software developed in R (RStudio, version 1.0.136, Boston, USA)
Results
Description of participants
summarises demographics and characteristics for athletes with SRC. Median total symptoms and symptom severity were 7.5 (IQR 5 – 13) and 12.0 (IQR 5.3 – 22.6), respectively, at the time of medical evaluation. At the time of blood sampling, the median total symptoms reported by athletes with SRC was 5 (IQR 4–11), and the median symptom severity was 8 (IQR 4–17). At the time of blood sampling, compared to healthy controls, athletes with SRC had significantly higher total symptoms scores (median score = 5.0 vs. 3.0 respectively; p = 0.04, data not shown) but not symptom severity scores. Six of 22 SCAT3 symptoms were significantly elevated in athletes with SRC, with “sensitivity to light” displaying the greatest difference (median score 1.0 vs. 0.0; p = 0.0009, data not shown). There was also a significant, positive correlation identified between total symptoms and days to medical clearance (rho = 0.63; p = 0.03, data not shown).
Table 1. Athlete demographics and characteristics.
Univariate analysis
Eight of 11 neuroinjury-related biomarkers fell within the detectable range in >50% of samples across all groups, and were therefore included for statistical analysis (see Supplementary Table 3 for the percentage of samples within the detectable range for all biomarkers). Biomarker concentrations for all groups can be seen in . In the subacute period after injury, PRDX-6 levels were significantly higher in athletes with SRC compared to controls (29.3 vs. 19.5 ng/mL). At medical clearance, both PRDX-6 and T-tau were significantly elevated in athletes with SRC compared to controls prior to FDR adjustment (PRDX-6; 24.6 vs. 20.7 ng/mL, T-tau; 20.4 vs. 14.4 pg/mL).
Table 2. Biomarker values across groups.
Multivariate analysis
depicts the PLS-DA analysis used to identify salient biomarkers which discriminated athletes with SRC from healthy athletes in the subacute period ( and at medical clearance (. Similar to the univariate analysis, in the subacute period after injury, higher PRDX-6 levels were associated with concussion (. At medical clearance, the weighted contribution of higher levels of PRDX-6 and T-tau were associated with concussion (.
Figure 1. Biomarker variance between concussed and healthy athletes. s100 calcium binding protein beta (s100B); glial fibrillary acidic protein (GFAP); neuron specific enolase (NSE); neurogranin (NRGN); creatine kinase-BB isoenzyme (CKBB); visinin-like protein (VILIP-1); von Willebran factor (vWF); brain derived neurotrophic factor (BDNF); peroxiredoxin (PRDX) − 6; monocyte chemoattractant protein (MCP) −1. Plots show the contributions of individual biomarkers towards class separation between concussed and healthy athletes at (a) the subacute period after injury, and (b) medical clearance, by PLS-DA analysis. Bars represent biomarker loadings and the standard error derived from bootstrapped resampling (1000 samples). red bars = FDR < 0.05.
Discussion
The main findings of this study were the significant elevation in blood PRDX-6 levels observed in athletes with SRC in the subacute phase, as well as the contribution of elevations in both PRDX-6 and T-tau in classifying athletes with SRC compared to controls at medical clearance.
We found elevated PRDX-6 levels in concussed athletes compared to healthy athletes sub-acutely. PRDX-6 is an antioxidant enzyme found primarily in astrocytes that may protect neuronal membranes and mitochondria from damage due to lipid peroxidation Citation(38). PRDX-6 has been targeted in TBI due to the vulnerability of the brain to lipid peroxidation Citation(38), and was recently uncovered as a candidate TBI biomarker in a rodent model using unsupervised autoimmune screening Citation(39). Elevated PRDX-6 levels have been observed acutely across the spectrum of TBI in humans Citation(40), and the restitution of PRDX-6 levels within 24 h of severe TBI in humans has been associated with improved recovery Citation(38). While the mechanism remains elusive in human injury, these findings generally support the metabolic dysfunction noted in experimental brain injury models Citation(6) and human advanced neuroimaging (Citation9–Citation11,Citation41). Furthermore, although the scope of the current study was to characterise blood biomarkers for the purpose of advancing our understanding of human secondary injury pathophysiology, the findings of the current study warrant future investigations to evaluate the clinical potential of PRDX-6 in SRC diagnosis and prognosis; competitively evaluating the statistical performance of this marker against other well-studied indices of brain injury such as s100B and GFAP may be useful.
Recent evidence suggests that peripherally measured Tau in the systemic circulation may reflect CNS tauopathy (Citation42,Citation43) or axonal damage Citation(44). While we did not observe differences in T-tau levels between athletes with SRC and controls in the subacute time period, higher blood concentrations were associated with SRC at medical clearance. Our findings are aligned with similar null findings for T-tau found within 24 h after mTBI Citation(45). However, Shahim and colleagues identified elevations in serum T-tau both immediately and in the subacute period after SRC, with levels returning to baseline by return-to-play Citation(22). Furthermore, Neselius et al. found elevated blood T-tau levels in boxers at 1–6 days after a bout, compared to control subjects Citation(46). Study design may partly account for the discrepancy between our findings and those of Shahim et al., as they compared T-tau levels in concussed athletes against pre-season baseline levels in males playing a single sport (ice hockey) Citation(22), while we utilised in-season matched controls in males and females across several sports. Likewise, T-tau may have a biphasic secretion pattern, and it is possible that our chosen sampling times did not coincide with peak secretion periods Citation(22). Regarding the findings of Neselius et al., it is possible that the discrepancy may be attributed to the different T-tau assay used by their group, or to their use of control subjects purposely screened to exclude any potential history of head impacts Citation(46); the current study utilized athletes matched for concussion history.
In agreement with our findings, chronically elevated T-tau has been found in soldiers with a history of reported or medically documented concussion up to 18 months post-deployment Citation(47), and elevated levels have also been observed at one month post-severe TBI Citation(44). Regarding the former, there are a number of similarities between SRC and military concussion; both populations are typically young, athletic, have the same physical and mental requirements for success in their fields, and are at risk for repetitive trauma. In addition, despite some reported differences in acute concussive symptoms and neurocognitive performance between military-related mTBI and SRC Citation(48), a recent retrospective case series demonstrated that the natural history of recovery in blast-induced mild brain injury mirrors the pattern of recovery in SRC Citation(49). In addition, the current findings are also in agreement with recent work from our group which demonstrated that collision sport participation was associated with increased T-tau levels in the plasma of uninjured athletes Citation(14). Yet, Neselius et al. found that while plasma T-tau was elevated in boxers within a week after a bout, levels returned to baseline at approximately 14 days Citation(46). The discrepancy between the current studies’ findings and those of Nesilus and colleagues are unclear, warranting future research on the potential dysregulation of plasma T-tau chronically after brain injury. Understanding the relationship between peripheral blood T-tau levels and axonal injury or the accumulation of tau in the brain is important, as peripheral tau has been linked to chronic neurodegenerative disorders such as chronic traumatic encephalopathy and Alzheimer’s disease (Citation42,Citation47,Citation50–Citation54).
That we found perturbations in systemic biomarker levels at the time of medical clearance is consistent with a number of previous investigations that have identified physiological disturbances at clinical recovery (Citation27,Citation28,Citation30). Our group also recently showed that heart rate variability – an index of neuroendocrine function – was perturbed at clinical recovery post-SRC Citation(29). It is unclear if these prolonged physiological observations are a risk factor for future injury, or a by-product of brain restitution. However, our current findings are supportive of further investigation into the potential utility of employing blood biomarkers to evaluate physiological recovery in asymptomatic individuals, and suggest that biological perturbations may persist at return-to-play.
The continued use of blood biomarkers to characterise concussion pathophysiology will require directed investigations on the mechanistic links to brain injury/repair. An important component of this is identifying how and why certain molecules appear in the peripheral blood after injury. This requires a greater understanding of mechanisms involved in glymphatic clearance (Citation18,Citation55–Citation57), BBB disruption, and neuroendocrine dysfunction (Citation17,Citation19,Citation21). In view of the latter, injury-induced alterations to hormones produced by both the sympathetic nervous system and hypothalamic–pituitary–adrenal (HPA)-axis can modulate peripheral immune function, altering blood levels of cytokines and chemokines (Citation58–Citation60). While we did not find differences in blood concentrations of the inflammatory chemokine MCP-1 between concussed and healthy athletes in either the subacute period or at medical clearance, Merchant-Borna et al. observed that at 7 days after SRC, gene transcription profiles in peripheral blood leukocytes were perturbed, reflecting potential dysregulation of the HPA-axis Citation(25). In addition, we recently demonstrated that acutely elevated levels of peripheral catecholamines after moderate and severe TBI were highly correlated with elevated circulating concentrations of inflammatory cytokines and chemokines Citation(19). Hence, future studies are required to evaluate the potential contribution of the peripheral immune system to concussion, and will need to assess a breadth of markers to encompass the scope of this response.
While it is possible that academic-related stress and/or the chronic effects of exercise over a competitive season may alter systemic biomarker levels, this has not been clearly demonstrated in humans to date. In fact, Shahim and colleagues found that a “friendly” hockey game without any concussive injuries resulted in increased peripheral blood levels of the neuroinjury markers s100B and NSE, but not T-tau Citation(22). Similar conclusions were reached by Oliver and colleagues Citation(61), who recently found that peripheral blood T-tau levels did not differ in football players over the course of a college season. In addition, while PRDX-6 is found in platelets and may be subject to post-processing effects Citation(39), changes in peripheral concentrations due to exercise have not been demonstrated in humans. However, it is still possible that psychological and physical stressors unrelated to concussion may significantly impact peripheral biomarker concentrations, and thus more definitive studies are required.
Future biomarker studies in SRC will need to be cognizant of which statistical strategies to employ when examining potentially small perturbations in molecular targets that are easily confounded by biological noise. In view of this, although the current study did not find FDR-adjusted significance for PRDX-6 or T-tau at medical clearance using a univariate approach, our multivariate PLSDA analysis identified that both markers significantly contributed to class separation between athletes with SRC and healthy athletes. It is important to note that multivariate statistical approaches such as the PLSDA, as opposed to more conservative univariate alternatives, can be more sensitive in identifying variance patterns across numerous variables in relatively small sample sizes, and hence can be used to identify subtle, yet meaningful differences (Citation62,Citation63). Indeed, this is evident in the current findings, as it was the weighted combination of PRDX-6 and T-tau that significantly co-varied with SRC at medical clearance. Furthermore, the increased sensitivity of a multivariate approach does not come at the cost of stability; the results of the PLSDA in the current study were derived after 1000 bootstrap iterations, and adjusted for multiple comparisons.
Limitations
This study was limited by a relatively small sample size. A greater number of participants would have allowed for sex stratification, as well as the ability to dichotomise collision vs. non-collision sport athletes. In view of this, we previously identified perturbations to blood biomarkers in athletes with a history of concussion that varied according to sex and sport participation Citation(14). Furthermore, despite our novel findings of physiological perturbations in blood biomarkers at medical clearance, the addition of earlier sample times would have further added to the temporal dimension of our results. However, despite these limitations, we were able to identify significant differences in peripheral blood biomarkers in athletes with SRC compared to healthy athletes.
Conclusion
Our findings support the continued application of blood biomarkers to help elucidate the pathophysiology of secondary injury after SRC. We observed higher circulating levels of PRDX-6 in athletes with SRC compared to control athletes in the subacute phase after injury, and identified a relationship between SRC and higher PRDX-6 and T-tau levels at medical clearance. Future biomarker investigations in sport concussion should consider the complexity and heterogeneity of sampling populations, the potential confounds of physical and psychological stressors unrelated to SRC, and the application of statistical tests that are sensitive to small, but meaningful differences observed in multivariate datasets.
Disclaimer
Opinions expressed or implied in this publication are those of the authors and do not represent the views or policy of the Department of National Defence or the Canadian Armed Forces.
Declaration of interest
The authors declare that they have no competing interests. This research was funded by Defence Research & Development Canada (DRDC) and the Canadian Institutes of Military and Veterans Health (CIMVHR). This study was approved by the Canadian Forces Surgeon General’s Health Research Program. In accordance with the Department of National Defence policy, the paper was reviewed and approved for submission without modification by the DRDC Publications Office.
Acknowledgements
We thank Maria Shiu and Ingrid Smith for their technical assistance.
Supplementary material
The supplemental data for this article can be accessed here.
References
- Voss JD, Connolly J, Schwab KA, Scher AI. Update on the epidemiology of concussion/mild traumatic brain injury. Curr Pain Headache Rep. 2015;19(7):32.
- Garber BG, Rusu C, Zamorski MA, Boulos D. Occupational outcomes following mild traumatic brain injury in Canadian military personnel deployed in support of the mission in Afghanistan: a retrospective cohort study. BMJ Open. 2016;6(5):e010780.
- Barkhoudarian G, Hovda DA, Giza CC. The molecular pathophysiology of concussive brain injury - an update. Phys Med Rehabil Clin N Am. 2016;27(2):373–93.
- Levin HS, Diaz-Arrastia RR. Diagnosis, prognosis, and clinical management of mild traumatic brain injury. Lancet Neurol. 2015;14(5):506–17.
- Papa L. Potential blood-based biomarkers for concussion. Sports Med Arthrosc. 2016;24(3):108–15.
- Giza CC, Hovda DA. The new neurometabolic cascade of concussion. Neurosurgery. 2014;75(Suppl 4):S24–33.
- Blaylock RL, Maroon J. Immunoexcitotoxicity as a central mechanism in chronic traumatic encephalopathy-a unifying hypothesis. Surg Neurol Int. 2011;2:107.
- Wright DK, Trezise J, Kamnaksh A, Bekdash R, Johnston LA, Ordidge R, Semple BD, Gardner AJ, Stanwell P, O’Brien TJ, and others. Behavioral, blood, and magnetic resonance imaging biomarkers of experimental mild traumatic brain injury. Sci Rep. 2016;6:28713.
- Jalloh I, Carpenter KL, Grice P, Howe DJ, Mason A, Gallagher CN, Helmy A, Murphy MP, Menon DK, Carpenter TA, and others. Glycolysis and the pentose phosphate pathway after human traumatic brain injury: microdialysis studies using 1,2-(13)C2 glucose. J Cereb Blood Flow Metab. 2015;35(1):111–20.
- Bergsneider M, Hovda DA, Shalmon E, Kelly DF, Vespa PM, Martin NA, Phelps ME, McArthur DL, Caron MJ, Kraus JF, and others. Cerebral hyperglycolysis following severe traumatic brain injury in humans: a positron emission tomography study. J Neurosurg. 1997;86(2):241–51.
- Bergsneider M, Hovda DA, Lee SM, Kelly DF, McArthur DL, Vespa PM, Lee JH, Huang SC, Martin NA, Phelps ME, and others. Dissociation of cerebral glucose metabolism and level of consciousness during the period of metabolic depression following human traumatic brain injury. J Neurotrauma. 2000;17(5):389–401.
- Wilson L, Stewart W, Dams-O’Connor K, Diaz-Arrastia R, Horton L, Menon DK, Polinder S. The chronic and evolving neurological consequences of traumatic brain injury. Lancet Neurol. 2017;16(10):813–25.
- Di Battista AP, Rhind SG, Baker AJ. Application of blood-based biomarkers in human mild traumatic brain injury. Front Neurol. 2013;4:44.
- Di Battista AP, Rhind SG, Richards D, Churchill N, Baker AJ, Hutchison MG. Altered blood biomarker profiles in athletes with a history of repetitive head impacts. PLoS One. 2016;11(7):e0159929.
- Woodcock T, Morganti-Kossmann MC. The role of markers of inflammation in traumatic brain injury. Front Neurol. 2013;4:18.
- Alves JL. Blood-brain barrier and traumatic brain injury. J Neurosci Res. 2014;92(2):141–47.
- Chodobski A, Zink BJ, Szmydynger-Chodobska J. Blood-brain barrier pathophysiology in traumatic brain injury. Transl Stroke Res. 2011;2(4):492–516.
- Plog BA, Dashnaw ML, Hitomi E, Peng W, Liao Y, Lou N, Deane R, Nedergaard M. Biomarkers of traumatic injury are transported from brain to blood via the glymphatic system. J Neurosci. 2015;35(2):518–26.
- Di Battista AP, Rhind SG, Hutchison MG, Hassan S, Shiu MY, Inaba K, Topolovec-Vranic J, Neto AC, Rizoli SB, Baker AJ. Inflammatory cytokine and chemokine profiles are associated with patient outcome and the hyperadrenergic state following acute brain injury. J Neuroinflammation. 2016;13:40.
- Catania A, Lonati C, Sordi A, Gatti S. Detrimental consequences of brain injury on peripheral cells. Brain Behav Immun. 2009;23(7):877–84.
- Santarsieri M, Kumar RG, Kochanek PM, Berga S, Wagner AK. Variable neuroendocrine-immune dysfunction in individuals with unfavorable outcome after severe traumatic brain injury. Brain Behav Immun. 2015;45:15–27.
- Shahim P, Tegner Y, Wilson DH, Randall J, Skillback T, Pazooki D, Kallberg B, Blennow K, Zetterberg H. Blood biomarkers for brain injury in concussed professional ice hockey players. JAMA Neurol. 2014;71(6):684–92.
- Siman R, Shahim P, Tegner Y, Blennow K, Zetterberg H, Smith DH. Serum SNTF increases in concussed professional ice hockey players and relates to the severity of postconcussion symptoms. J Neurotrauma. 2015;32(17):1294–300.
- Papa L, Brophy GM, Welch RD, Lewis LM, Braga CF, Tan CN, Ameli NJ, Lopez MA, Haeussler CA, Mendez Giordano DI, and others. Time course and diagnostic accuracy of glial and neuronal blood biomarkers GFAP and UCH-L1 in a large cohort of trauma patients with and without mild traumatic brain injury. JAMA Neurol. 2016;73(5):551–60.
- Merchant-Borna K, Lee H, Wang D, Bogner V, Van Griensven M, Gill J, Bazarian JJ. Genome-wide changes in peripheral gene expression following sports-related concussion. J Neurotrauma. 2016;33(17):1576–85.
- Gill J, Merchant-Borna K, Lee H, Livingston WS, Olivera A, Cashion A, Wang D, Bazarian JJ. Sports-related concussion results in differential expression of nuclear factor-kappab pathway genes in peripheral blood during the acute and subacute periods. J Head Trauma Rehabil. 2016;31(4):269–76.
- Zhu DC, Covassin T, Nogle S, Doyle S, Russell D, Pearson RL, Monroe J, Liszewski CM, DeMarco JK, Kaufman DI. A potential biomarker in sports-related concussion: brain functional connectivity alteration of the default-mode network measured with longitudinal resting-state fMRI over thirty days. J Neurotrauma. 2015;32(5):327–41.
- Chamard E, Lassonde M, Henry L, Tremblay J, Boulanger Y, De Beaumont L, Theoret H. Neurometabolic and microstructural alterations following a sports-related concussion in female athletes. Brain Inj. 2013;27(9):1038–46.
- Hutchison MG, Mainwaring L, Senthinathan A, Churchill N, Thomas S, Richards D. Psychological and physiological markers of stress in concussed athletes across recovery milestones. J Head Trauma Rehabil. 2016;32(3):E38–E48.
- McCrea M, Prichep L, Powell MR, Chabot R, Barr WB. Acute effects and recovery after sport-related concussion: a neurocognitive and quantitative brain electrical activity study. J Head Trauma Rehabil. 2010;25(4):283–92.
- McCrory P, Meeuwisse W, Dvorak J, Aubry M, Bailes J, Broglio S, Cantu RC, Cassidy D, Echemendia RJ, Castellani RJ, and others. Consensus statement on concussion in sport-the 5th international conference on concussion in sport held in Berlin, October 2016. Br J Sports Med. 2017;51(11):838–47.
- Shahim P, Linemann T, Inekci D, Karsdal MA, Blennow K, Tegner Y, Zetterberg H, Henriksen K. Serum tau fragments predict return to play in concussed professional ice hockey players. J Neurotrauma. 2016;33(22):1995–99.
- McCrory P, Meeuwisse W, Johnston K, Dvorak J, Aubry M, Molloy M, Cantu R. Consensus statement on concussion in sport: the 3rd international conference on concussion in sport held in Zurich, November 2008. Br J Sports Med. 2009;43(Suppl 1):i76–90.
- McCrory P, Meeuwisse WH, Aubry M, Cantu B, Dvorak J, Echemendia RJ, Engebretsen L, Johnston K, Kutcher JS, Raftery M, and others. Consensus statement on concussion in sport: the 4th international conference on concussion in sport held in Zurich, November 2012. Br J Sports Med. 2013;47(5):250–58.
- Brown DA, Elsass JA, Miller AJ, Reed LE, Reneker JC. Differences in symptom reporting between males and females at baseline and after a sports-related concussion: a systematic review and meta-analysis. Sports Med. 2015;45(7):1027–40.
- Guskiewicz KM, Register-Mihalik J, McCrory P, McCrea M, Johnston K, Makdissi M, Dvorak J, Davis G, Meeuwisse W. Evidence-based approach to revising the SCAT2: introducing the SCAT3. Br J Sports Med. 2013;47(5):289–93.
- Galetta MS, Galetta KM, McCrossin J, Wilson JA, Moster S, Galetta SL, Balcer LJ, Dorshimer GW, Master CL. Saccades and memory: baseline associations of the King-Devick and SCAT2 SAC tests in professional ice hockey players. J Neurol Sci. 2013;328(1–2):28–31.
- Manevich Y, Hutchens S, Halushka PV, Tew KD, Townsend DM, Jauch EC, Borg K. Peroxiredoxin VI oxidation in cerebrospinal fluid correlates with traumatic brain injury outcome. Free Radic Biol Med. 2014;72:210–21.
- Buonora JE, Mousseau M, Jacobowitz DM, Lazarus RC, Yarnell AM, Olsen CH, Pollard HB, Diaz-Arrastia R, Latour L, Mueller GP. Autoimmune profiling reveals peroxiredoxin 6 as a candidate traumatic brain injury biomarker. J Neurotrauma. 2015;32(22):1805–14.
- Buonora JE, Yarnell AM, Lazarus RC, Mousseau M, Latour LL, Rizoli SB, Baker AJ, Rhind SG, Diaz-Arrastia R, Mueller GP. Multivariate analysis of traumatic brain injury: development of an assessment score. Front Neurol. 2015;6:68.
- Jalloh I, Carpenter KL, Helmy A, Carpenter TA, Menon DK, Hutchinson PJ. Glucose metabolism following human traumatic brain injury: methods of assessment and pathophysiological findings. Metab Brain Dis. 2015;30(3):615–32.
- Zetterberg H, Wilson D, Andreasson U, Minthon L, Blennow K, Randall J, Hansson O. Plasma tau levels in Alzheimer’s disease. Alzheimers Res Ther. 2013;5(2):9.
- Stern RA, Tripodis Y, Baugh CM, Fritts NG, Martin BM, Chaisson C, Cantu RC, Joyce JA, Shah S, Ikezu T, and others. Preliminary study of plasma exosomal tau as a potential biomarker for chronic traumatic encephalopathy. J Alzheimers Dis. 2016;51(4):1099–109.
- Rubenstein R, Chang B, Davies P, Wagner AK, Robertson CS, Wang KK. A novel, ultrasensitive assay for tau: potential for assessing traumatic brain injury in tissues and biofluids. J Neurotrauma. 2015;32(5):342–52.
- Bulut M, Koksal O, Dogan S, Bolca N, Ozguc H, Korfali E, Ilcol YO, Parklak M. Tau protein as a serum marker of brain damage in mild traumatic brain injury: preliminary results. Adv Ther. 2006;23(1):12–22.
- Neselius S, Zetterberg H, Blennow K, Randall J, Wilson D, Marcusson J, Brisby H. Olympic boxing is associated with elevated levels of the neuronal protein tau in plasma. Brain Inj. 2013;27(4):425–33.
- Olivera A, Lejbman N, Jeromin A, French LM, Kim HS, Cashion A, Mysliwiec V, Diaz-Arrastia R, Gill J. Peripheral total tau in military personnel who sustain traumatic brain injuries during deployment. JAMA Neurol. 2015;72(10):1109–16.
- Luethcke CA, Bryan CJ, Morrow CE, Isler WC. Comparison of concussive symptoms, cognitive performance, and psychological symptoms between acute blast-versus nonblast-induced mild traumatic brain injury. J Int Neuropsychol Soc. 2011;17(1):36–45.
- Larres DT, Carr W, Gonzales EG, Hawley JS. The natural history of acute recovery of blast-induced mild traumatic brain injury: a case series during war. Mil Med. 2016;181(5 Suppl):23–27.
- Omalu B, Bailes J, Hamilton RL, Kamboh MI, Hammers J, Case M, Fitzsimmons R. Emerging histomorphologic phenotypes of chronic traumatic encephalopathy in American athletes. Neurosurgery. 2011;69(1):173–83; discussion 183.
- Barrio JR, Small GW, Wong KP, Huang SC, Liu J, Merrill DA, Giza CC, Fitzsimmons RP, Omalu B, Bailes J, and others. In vivo characterization of chronic traumatic encephalopathy using [F-18]FDDNP PET brain imaging. Proc Natl Acad Sci U S A. 2015;112(16):E2039–47.
- Small GW, Kepe V, Siddarth P, Ercoli LM, Merrill DA, Donoghue N, Bookheimer SY, Martinez J, Omalu B, Bailes J, and others. PET scanning of brain tau in retired national football league players: preliminary findings. Am J Geriatr Psychiatry. 2013;21(2):138–44.
- McKee AC, Cantu RC, Nowinski CJ, Hedley-Whyte ET, Gavett BE, Budson AE, Santini VE, Lee HS, Kubilus CA, Stern RA. Chronic traumatic encephalopathy in athletes: progressive tauopathy after repetitive head injury. J Neuropathol Exp Neurol. 2009;68(7):709–35.
- Bogoslovsky T, Wilson D, Chen Y, Hanlon D, Gill J, Jeromin A, Song L, Moore C, Gong Y, Kenney K, and others. Increases of plasma levels of glial fibrillary acidic protein, tau, and amyloid beta up to 90 days after traumatic brain injury. J Neurotrauma. 2017;34(1):66–73.
- Plog BA, Nedergaard M. Why have we not yet developed a simple blood test for TBI? Expert Rev Neurother. 2015;15(5):465–68.
- Iliff JJ, Chen MJ, Plog BA, Zeppenfeld DM, Soltero M, Yang L, Singh I, Deane R, Nedergaard M. Impairment of glymphatic pathway function promotes tau pathology after traumatic brain injury. J Neurosci. 2014;34(49):16180–93.
- Iliff JJ, Wang M, Liao Y, Plogg BA, Peng W, Gundersen GA, Benveniste H, Vates GE, Deane R, Goldman SA, and others. A paravascular pathway facilitates CSF flow through the brain parenchyma and the clearance of interstitial solutes, including amyloid beta. Sci Transl Med. 2012;4(147):147ra111.
- Elenkov IJ, Wilder RL, Chrousos GP, Vizi ES. The sympathetic nerve–an integrative interface between two supersystems: the brain and the immune system. Pharmacol Rev. 2000;52(4):595–638.
- Pavlov VA, Tracey KJ. Neural regulators of innate immune responses and inflammation. Cell Mol Life Sci. 2004;61(18):2322–31.
- Bellavance MA, Rivest S. The HPA - Immune axis and the immunomodulatory actions of glucocorticoids in the brain. Front Immunol. 2014;5:136.
- Oliver JM, Jones MT, Anzalone AJ, Kirk KM, Gable DA, Repshas JT, Johnson TA, Hoglund K, Blennow K, Zetterberg H. A season of American football is not associated with changes in plasma tau. J Neurotrauma. 2017;34(23):3295–300.
- Krishnan A, Williams LJ, McIntosh AR, Abdi H. Partial Least Squares (PLS) methods for neuroimaging: a tutorial and review. Neuroimage. 2011;56(2):455–75.
- Wold S, Sjostrom M, Eriksson L. PLS-regression: a basic tool of chemometrics. Chemom Intell Lab Syst. 2001;58:109–30.