Use of Biostatistical Models to Manage Replicate Error in Concussion Biomarker Research.

Importance: Advancing research on fluid biomarkers associated with sport-related concussion (SRC) highlights the importance of detecting low concentrations using ultrasensitive platforms. However, common statistical practices may overlook replicate errors and specimen exclusion, emphasizing the need to explore robust modeling approaches that consider all available replicate data for comprehensive understanding of sample variation and statistical inferences. Objective: To evaluate the impact of replicate error and different biostatistical modeling approaches on SRC biomarker interpretation. Design, Setting, and Participants: This cross-sectional study within the Surveillance in High Schools to Reduce the Risk of Concussions and Their Consequences study used data from healthy youth athletes (ages 11-18 years) collected from 3 sites across Canada between September 2019 and November 2021. Data were analyzed from November 2022 to February 2023. Exposures: Demographic variables included age, sex, and self-reported history of previous concussion. Main Outcomes and Measures: Outcomes of interest were preinjury plasma glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase-L1 (UCH-L1), neurofilament-light (NFL), total tau (t-tau) and phosphorylated-tau-181 (p-tau-181) assayed in duplicate. Bland-Altman analysis determined the 95% limits of agreement (LOAs) for each biomarker. The impact of replicate error was explored using 3 biostatistical modeling approaches assessing the associations of age, sex, and previous concussion on biomarker concentrations: multilevel regression using all available replicate data, single-level regression using the means of replicate data, and single-level regression with replicate means, excluding specimens demonstrating more than 20% coefficient variation (CV). Results: The sample included 149 healthy youth athletes (78 [52%] male; mean [SD] age, 15.74 [1.41] years; 51 participants [34%] reporting ≥1 previous concussions). Wide 95% LOAs were observed for GFAP (-17.74 to 18.20 pg/mL), UCH-L1 (-13.80 to 14.77 pg/mL), and t-tau (65.27% to 150.03%). GFAP and UCH-L1 were significantly associated with sex in multilevel regression (GFAP: effect size, 15.65%; ß = -0.17; 95% CI, -0.30 to -0.04]; P = .02; UCH-L1: effect size, 17.24%; ß = -0.19; 95% CI, -0.36 to -0.02]; P = .03) and single-level regression using the means of replicate data (GFAP: effect size, 15.56%; ß = -0.17; 95% CI, -0.30 to -0.03]; P = .02; UCH-L1: effect size, 18.02%; ß = -0.20; 95% CI, -0.37 to -0.03]; P = .02); however, there was no association for UCH-L1 after excluding specimens demonstrating more than 20% CV. Excluding specimens demonstrating more than 20% CV resulted in decreased differences associated with sex in GFAP (effect size, 12.29%; ß = -0.14; 95% CI, -0.273 to -0.004]; P = .04) and increased sex differences in UCH-L1 (effect size, 23.59%; ß = -0.27; 95% CI, -0.55 to 0.01]; P = .06), with the widest 95% CIs (ie, least precision) found in UCH-L1. Conclusions and Relevance: In this cross-sectional study of healthy youth athletes, varying levels of agreement between SRC biomarker technical replicates suggested that means of measurements may not optimize precision for population values. Multilevel regression modeling demonstrated how incorporating all available biomarker data could capture replicate variation, avoiding challenges associated with means and percentage of CV exclusion thresholds to produce more representative estimates of association.

Role of biomarkers and emerging technologies in defining and assessing neurobiological recovery after sport-related concussion: a systematic review.

OBJECTIVE: Determine the role of fluid-based biomarkers, advanced neuroimaging, genetic testing and emerging technologies in defining and assessing neurobiological recovery after sport-related concussion (SRC). DESIGN: Systematic review. DATA SOURCES: Searches of seven databases from 1 January 2001 through 24 March 2022 using keywords and index terms relevant to concussion, sports and neurobiological recovery. Separate reviews were conducted for studies involving neuroimaging, fluid biomarkers, genetic testing and emerging technologies. A standardised method and data extraction tool was used to document the study design, population, methodology and results. Reviewers also rated the risk of bias and quality of each study. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Studies were included if they: (1) were published in English; (2) represented original research; (3) involved human research; (4) pertained only to SRC; (5) included data involving neuroimaging (including electrophysiological testing), fluid biomarkers or genetic testing or other advanced technologies used to assess neurobiological recovery after SRC; (6) had a minimum of one data collection point within 6 months post-SRC; and (7) contained a minimum sample size of 10 participants. RESULTS: A total of 205 studies met inclusion criteria, including 81 neuroimaging, 50 fluid biomarkers, 5 genetic testing, 73 advanced technologies studies (4 studies overlapped two separate domains). Numerous studies have demonstrated the ability of neuroimaging and fluid-based biomarkers to detect the acute effects of concussion and to track neurobiological recovery after injury. Recent studies have also reported on the diagnostic and prognostic performance of emerging technologies in the assessment of SRC. In sum, the available evidence reinforces the theory that physiological recovery may persist beyond clinical recovery after SRC. The potential role of genetic testing remains unclear based on limited research. CONCLUSIONS: Advanced neuroimaging, fluid-based biomarkers, genetic testing and emerging technologies are valuable research tools for the study of SRC, but there is not sufficient evidence to recommend their use in clinical practice. PROSPERO REGISTRATION NUMBER: CRD42020164558.

Amsterdam 2022 process: A summary of the methodology for the Amsterdam International Consensus on Concussion in Sport.

The purpose of this paper is to summarise the consensus methodology that was used to inform the International Consensus Statement on Concussion in Sport (Amsterdam 2022). Building on a Delphi process to inform the questions and outcomes from the 5th International Conference on Concussion in Sport, the Scientific Committee identified key questions, the answers to which would help encapsulate the current science in sport-related concussion and help guide clinical practice. Over 3½ years, delayed by 2 years due to the pandemic, author groups conducted systematic reviews on each selected topic. The 6th International Conference on Concussion in Sport was held in Amsterdam (27-30 October 2022) and consisted of 2 days of systematic review presentations, panel discussions, question and answer engagement with the 600 attendees, and abstract presentations. This was followed by a closed third day of consensus deliberations by an expert panel of 29 with observers in attendance. The fourth day, also closed, was dedicated to a workshop to discuss and refine the sports concussion tools (Concussion Recognition Tool 6 (CRT6), Sport Concussion Assessment Tool 6 (SCAT6), Child SCAT6, Sport Concussion Office Assessment Tool 6 (SCOAT6) and Child SCOAT6). We include a summary of recommendations for methodological improvements for future research that grew out of the systematic reviews.

Nanoporous Carbon Immunosensor for Highly Accurate and Sensitive Clinical Detection of Glial Fibrillary Acidic Protein in Traumatic Brain Injury, Stroke, and Spinal Cord Injury.

Elevated glial fibrillary acidic protein (GFAP) in the blood serum is one of the promising bodily fluid markers for the diagnosis of central nervous system (CNS) injuries, including traumatic brain injury (TBI), stroke, and spinal cord injury (SCI). However, accurate and point-of-care (POC) quantification of GFAP in clinical blood samples has been challenging and yet to be clinically validated against gold-standard assays and outcome practices. This work engineered and characterized a novel nanoporous carbon screen-printed electrode with significantly increased surface area and conductivity, as well as preserved stability and anti-fouling properties. This nano-decorated electrode was immobilized with the target GFAP antibody to create an ultrasensitive GFAP immunosensor and quantify GFAP levels in spiked samples and the serum of CNS injury patients. The immunosensor presented a dynamic detection range of 100 fg/mL to 10 ng/mL, a limit of detection of 86.6 fg/mL, and a sensitivity of 20.3 Ω mL/pg mm2 for detecting GFAP in the serum. Its clinical utility was demonstrated by the consistent and selective quantification of GFAP comparable to the ultrasensitive single-molecule array technology in 107 serum samples collected from TBI, stroke, and SCI patients. Comparing the diagnostic and prognostic performance of the immunosensor with the existing clinical paradigms confirms the immunosensor's accuracy as a potential complement to the existing imaging diagnostic modalities and presents a potential for rapid, accurate, cost-effective, and near real-time POC diagnosis and prognosis of CNS injuries.

Hiding in Plain Sight: Factors Influencing the Neuroinflammatory Response to Sport-Related Concussion.

Sport-related concussion (SRC) is a major concern among athletes and clinicians around the world. Research into fluid biomarkers of SRC has made significant progress in understanding the complex underlying pathophysiology of concussion. However, little headway has been made toward clinically validating any biomarkers to improve the clinical management of SRC. A major obstacle toward clinical translation of any fluid biomarker is the heterogeneity of SRC overlapping with multiple physiological systems involved in pathology and recovery. Neuroinflammation post-SRC is one such system that may confound fluid biomarker data on many fronts. Neuroinflammatory processes consist of cell mediators, both within the central nervous system and the periphery, that play vital roles in regulating the response to brain injury. Further, neuroinflammation is influenced by many biopsychosocial variables present in most athletic populations. In this commentary, we propose that future fluid biomarker research should take a systems biology approach in the context of the neuroinflammatory response to SRC. We highlight how biological variables, such as age, sex, immune challenges, and hypothalamic-pituitary-adrenal (HPA)-axis responses to stress, may alter neuroinflammation. Further, we underscore the importance of accounting for health and lifestyle variables, such as diet, exercise, sleep, and pre-morbid medical factors, when measuring inflammatory markers of SRC. To successfully move toward clinical translation, fluid biomarker research should take a more holistic approach in study design and data interpretation, collecting information on hidden variables that may be influencing the neuroinflammatory response to SRC.

The Impact of Concussion, Sport, and Time in Season on Saliva Telomere Length in Healthy Athletes.

To date, sport-related concussion diagnosis and management is primarily based on subjective clinical tests in the absence of validated biomarkers. A major obstacle to clinical validation and application is a lack of studies exploring potential biomarkers in non-injured populations. This cross-sectional study examined the associations between saliva telomere length (TL) and multiple confounding variables in a healthy university athlete population. One hundred eighty-three (108 male and 75 female) uninjured varsity athletes were recruited to the study and provided saliva samples at either pre- or mid-season, for TL analysis. Multiple linear regression was used to determine the associations between saliva TL and history of concussion, sport contact type, time in season (pre vs. mid-season collection), age, and sex. Results showed no significant associations between TL and history of concussion, age, or sport contact type. However, TL from samples collected mid-season were longer than those collected pre-season [ß = 231.4, 95% CI (61.9, 401.0), p = 0.008], and males had longer TL than females [ß = 284.8, 95% CI (111.5, 458.2), p = 0.001] when adjusting for all other variables in the model. These findings population suggest that multiple variables may influence TL. Future studies should consider these confounders when evaluating saliva TL as a plausible fluid biomarker for SRC.