Plasma Biomarkers of Traumatic Brain Injury in Adolescents With Sport-Related Concussion

Jason B Tabor; Linden C Penner; Jean-Michel Galarneau; Nik Josafatow; Jennifer Cooper; Mohammad Ghodsi; Johnny Huang; Douglas D Fraser; Jonathan Smirl; Michael J Esser; Keith Owen Yeates; Cheryl L Wellington; Chantel T Debert; Carolyn A Emery

doi:10.1001/jamanetworkopen.2024.31959

. 2024 Sep 5;7(9):e2431959. doi: 10.1001/jamanetworkopen.2024.31959

Plasma Biomarkers of Traumatic Brain Injury in Adolescents With Sport-Related Concussion

Jason B Tabor ^1,^2,^3,^✉, Linden C Penner ^1,^2,³, Jean-Michel Galarneau ¹, Nik Josafatow ^1,^2,³, Jennifer Cooper ⁴, Mohammad Ghodsi ⁴, Johnny Huang ⁴, Douglas D Fraser ⁵, Jonathan Smirl ^1,^2,³, Michael J Esser ^2,³, Keith Owen Yeates ^2,^3,⁶, Cheryl L Wellington ⁴, Chantel T Debert ^1,^2,^3,⁷, Carolyn A Emery ^1,^2,^3,⁸

¹Sport Injury Prevention Research Centre, Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada

²Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada

³Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada

⁴Department of Pathology and Laboratory Medicine, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada

⁵Department of Pediatrics and Clinical Neurological Sciences, Western University, London, Ontario, Canada

⁶Department of Psychology, University of Calgary, Calgary, Alberta, Canada

⁷Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada

⁸Departments of Pediatrics and Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada

Accepted for Publication: July 11, 2024.

Published: September 5, 2024. doi:10.1001/jamanetworkopen.2024.31959

^✉

Corresponding Author: Jason B. Tabor, PhD, Foothills Medical Centre, 1403 29 St NW, South Tower, Room 912, Calgary, AB, Canada T2N 2T9 (jbtabor@ucalgary.ca).

Author Contributions: Drs Emery and Galarneau had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Wellington, Debert, and Emery are co–senior authors.

Concept and design: Tabor, Smirl, Esser, Wellington, Debert, Emery.

Acquisition, analysis, or interpretation of data: Tabor, Penner, Galarneau, Josafatow, Cooper, Ghodsi, Huang, Fraser, Smirl, Esser, Yeates, Debert, Emery.

Drafting of the manuscript: Tabor, Galarneau, Debert, Emery.

Critical review of the manuscript for important intellectual content: Tabor, Penner, Josafatow, Cooper, Ghodsi, Huang, Fraser, Smirl, Esser, Yeates, Wellington, Debert, Emery.

Statistical analysis: Tabor, Galarneau, Emery.

Obtained funding: Wellington, Debert, Emery.

Administrative, technical, or material support: Penner, Josafatow, Cooper, Ghodsi, Smirl, Wellington, Debert, Emery.

Supervision: Fraser, Smirl, Esser, Wellington, Debert, Emery.

Conflict of Interest Disclosures: Dr Tabor reported receiving doctoral funding from the Canadian Institutes of Health during the conduct of the study. Dr Smirl reported receiving grants from Brain Canada, Branch Out Neurological Foundation, and Natural Sciences and Engineering Research Council of Canada outside the submitted work. Ms Cooper reported receiving an Alzheimer’s Society of Canada doctoral award. No other disclosures were reported.

Funding/Support: This work is aligned with the Surveillance in High Schools and Community Sports to Reduce Concussions and Their Consequences study, which is supported by the National Football League’s Play Smart Play Safe Program.

Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2.

Additional Contributions: The Sport Injury Prevention Research Centre is one of the International Research Centres for Prevention of Injury and Protection of Athlete Health supported by the International Olympic Committee. We acknowledge the support of SHRed Concussions (National Football League Play Smart Play Safe Program) and the Integrated Concussion Research Program (University of Calgary). We acknowledge the support of the SHRed research team and the SHRed participants for their engagement in this study.

^✉

Corresponding author.

PMCID: PMC11378000 PMID: 39235809

This cohort study evaluates the association between sport-related concussion and plasma biomarkers in Canadian adolescents.

Key Points

Question

Are blood-based levels of neurological biomarkers different between adolescents with sport-related concussion (SRC) and uninjured peers?

Findings

This cohort study included 1023 plasma samples from 695 uninjured adolescents and 154 adolescents with concussion. Sex-specific post-SRC differences were found in multiple traumatic brain injury biomarkers at acute and subacute time points relative to healthy uninjured youths.

Meaning

These findings highlight variations in biomarker levels in adolescents with SRC, suggesting their continued use in investigating concussion pathology in this understudied population.

Abstract

Importance

Blood-based biomarkers may clarify underlying neuropathology and potentially assist in clinical management of adolescents with sport-related concussion (SRC).

Objective

To investigate the association between SRC and plasma biomarkers in adolescents.

Design, Setting, and Participants

Prospective cohort study in Canadian sport and clinic settings (Surveillance in High Schools and Community Sport to Reduce Concussions and Their Consequences study; September 2019 to November 2022). Participants were a convenience sample of 849 adolescent (ages 10-18 years) sport participants with blood samples. Data were analyzed from February to September 2023.

Exposures

Blood collection and clinical testing preseason (uninjured) and post-SRC follow-ups (ie, ≤72 hours, 1 week, and biweekly until medical clearance to return to play [RTP]).

Main Outcomes and Measures

Plasma glial fibrillary acidic protein (GFAP), ubiquitin c-terminal hydrolase-L1 (UCH-L1), neurofilament light (NfL), and total tau (t-tau) were assayed. Group-level comparisons of biomarker levels were conducted between uninjured and post-SRC intervals (postinjury day [PID] 0-3, 4-10, 11-28, and >28) considering age and sex as modifiers. Secondary analyses explored associations between biomarker concentrations and clinical outcomes (Sport Concussion Assessment Tool, Fifth Edition [SCAT5] symptom scores and time to RTP).

Results

This study included 1023 plasma specimens from 695 uninjured participants (467 male participants [67.2%]; median [IQR] age, 15.90 [15.13-16.84] years) and 154 participants with concussion (78 male participants [51.0%]; median [IQR] age, 16.12 [15.31-17.11] years). Acute (PID 0-3) differences relative to uninjured levels were found for GFAP (female participants: 17.8% increase; β = 0.164; 95% CI, 0.064 to 0.263; P = .001; male participants: 17.1% increase; β = 0.157; 95% CI, 0.086 to 0.229; P < .001), UCH-L1 (female participants: 43.4% increase; β = 0.361; 95% CI, 0.125 to 0.596; P = .003), NfL (male participants: 19.0% increase; β = 0.174; 95% CI, 0.087 to 0.261; P < .001), and t-tau (female participants: −22.9%; β = −0.260; 95% CI, −0.391 to −0.130; P < .001; male participants: −18.4%; β = −0.203; 95% CI, −0.300 to −0.106; P < .001). Differences were observed for all biomarkers at PID 4 to 10, 11 to 28, and greater than 28 compared with uninjured groups. GFAP, NfL, and t-tau were associated with SCAT5 symptom scores across several PID intervals. Higher GFAP after 28 days post-SRC was associated with earlier clearance to RTP (hazard ratio, 4.78; 95% CI, 1.59 to 14.31; P = .01). Male participants exhibited lower GFAP (−9.7%), but higher UCH-L1 (21.3%) compared with female participants. Age was associated with lower GFAP (−5.4% per year) and t-tau (−5.3% per year).

Conclusions and Relevance

In this cohort study of 849 adolescents, plasma biomarkers differed between uninjured participants and those with concussions, supporting their continued use to understand concussion neuropathology. Age and sex are critical considerations as these biomarkers progress toward clinical validation.

Introduction

Sport-related concussion (SRC) is a pressing public health concern; however, research has lagged with respect to adolescents. Recent years have witnessed a significant rise in adolescent SRC rates, with substantial impact of prolonged symptoms and recovery on daily life.^1,2,3,4 The developing brain may be more vulnerable to insult, potentially affecting healthy biopsychosocial development.^5,6,7 The 6th Consensus Statement on Concussion in Sport has stressed the necessity for further research into child and adolescent SRC as youths experience concussion differently than adults.^7,8,9,10 Given these concerns, rapid SRC detection, diagnosis, and prognosis is essential to avoid misdiagnoses and direct appropriate interventions. Diagnosis of SRC in adolescents lacks a gold standard, relying on subjective clinical examination and interpretation of nonspecific symptoms. These limitations highlight the need for objective measures to assist clinical decision-making in young athletes.

Blood-based biomarkers of SRC have garnered significant interest for their relatively noninvasive and cost-effective potential in on-field and in-office and/or hospital assessment. Recent research suggests that biomarkers including glial fibrillary acidic protein (GFAP), ubiquitin c-terminal hydrolase-L1 (UCH-L1), neurofilament light (NfL), and possibly total tau (t-tau) may reflect central nervous system (CNS) injury following SRC.^11,12 However, most SRC biomarker data originate from adults, with limited studies in children and adolescents with longitudinal sampling beyond the acute injury period.^13,14,15

Despite substantial data in adults, commensurate progress has yet to be made in youths, with few studies sufficiently powered to confirm post-SRC biomarker changes while considering sex and age differences.¹⁶ The pan-Canadian Surveillance in High Schools and Community Sport to Reduce Concussions and Their Consequences (SHRed Concussions) multicenter longitudinal cohort study aims to address these major limitations in adolescent SRC. This project had 2 main objectives: (1) to examine whether SRC is associated with differences in plasma biomarker concentrations in adolescents at various postinjury time points compared with uninjured samples; and (2) to explore whether post-SRC biomarker levels are associated with clinical symptoms and medical clearance to return to play (RTP). We hypothesized that biomarker levels would differ in adolescents with SRC compared with uninjured peers, would potentially vary by sex and age, and would potentially be associated with clinical outcomes.

Methods

Participants

This prospective cohort study included a subset of adolescents from the SHRed Concussions study. SHRed Concussions enrolled adolescents (ages 10-18 years) participating in high-risk sports (eg, ice hockey, football, and rugby) across Canada. Participants provided written consent (mature minor consent ≥14 years) or parental consent with adolescent assent (<14 years). Exclusion criteria encompassed medical conditions affecting anticipated sports participation (eg, systemic disease, severe and/or chronic neurological conditions, or recent surgery and/or fractures [<12 months]).

Following the SHRed Concussions protocol and previously validated injury surveillance methods,^17,18,19 participants completed baseline assessments including the collection of demographic information (age, sex, and medical history) and Sport Concussion Assessment Tool, Fifth Edition (SCAT5) administration by trained research staff. Participants with SRC completed follow-up visits at approximately 72 or fewer hours, 1 week, and every 2 weeks until medically cleared to RTP. Diagnosis of SRC and clearance to RTP was confirmed by a study physician in accordance with the Berlin 2016 Concussion in Sport Group (CISG) Fifth Consensus Statement.^20,21 SCAT5 evaluations were completed at each clinical follow-up. Symptom burden was assessed using total symptom number and severity scores on the SCAT5 graded symptom checklist.²² Symptom scores were only included in the analysis if obtained on the same day as blood draws. This study was approved by the University of Calgary conjoint research ethics board and followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies.²³

Blood Collection

Blood collection occurred at baseline assessments and each post-SRC follow-up whenever possible. Participation in blood collection was limited by logistical constraints like participant refusal and maximum venipuncture attempts but not underlying participant conditions. Participants providing baseline samples may have differed from those providing post-SRC samples. Plasma was collected via standard venipuncture using K2-EDTA vacutainer tubes. Specimens were centrifuged for 10 minutes at 1300g, then aliquoted into cryovials for immediate freezing and storage at −80 °C (total processing time was <2 hours per specimen). Freeze-thaw cycles were avoided.

Biomarker Analysis

Plasma samples were analyzed using the Neurology-4 Plex B (N4PB) assay (Quanterix; catalog No. 103670) and Simoa HD-X analyzer (Quanterix). The N4PB assay measured GFAP, UCH-L1, NfL, and t-tau following manufacturer protocols with an 8-point standard curve. Participants were randomized into multiple runs, keeping participants with multiple samples on the same run. Specimens were diluted on board at a 4-fold dilution and run in duplicate. To track accuracy and interassay reliability, 2 manufacturer-provided controls and 3 internally-provided plasma controls were included in each run. The average intra-assay coefficient of variance (CV) was 6% to 9% for GFAP, NfL, and t-tau and 26% for UCH-L1. Interassay CVs ranged from 8% to 17% for GFAP, NfL, and t-tau and up to 56% for UCH-L1. The intra-assay and interassay variability in this study were within expected ranges observed in previous works.^24,25,26,27 Two different lots of N4PB were used (149 uninjured samples collected up to November 2021 in 1 lot, all subsequent uninjured and post-SRC samples in the second lot. Cross-lot and sensitivity analyses–confirmed lot differences did not influence results (detailed in eFigure 2 and eTable 5 in Supplement 1).

Statistical Analysis

Biomarker data underwent natural log (ln) transformation to better satisfy model assumptions. Post-SRC groups were binned into 4 postinjury day (PID) intervals: PID 0 to 3, PID 4 to 10, PID 11 to 28, and PID greater than 28. This categorization reflects both biological and clinical factors. Growing evidence indicates rapid CNS biomarker changes over the acute and/or subacute period,^11,28 suggesting a need to monitor possible signal changes between acute (≤ 72 hours) and subacute (up to 10 days) visits. The PID 11 to 28 interval reflects biomarker levels before typical clinical recovery in youths.²⁰ The final interval is composed of samples from more than 28 days, reflecting biomarker levels in individuals demonstrating prolonged recoveries.

Multilevel multivariable linear regression models using all available replicates per specimen were employed for all analyses, considering clustering by individual where the same participant had multiple samples.²⁹ The primary analysis assessed group-level differences between uninjured and post-SRC biomarker levels at each postinjury interval, adjusting for age and forcing sex as an effect modifier of PID interval to examine sex-specific differences. This approach was chosen given the limited availability of preseason (uninjured) and post-SRC blood samples collected from the same individual due to data collection interruptions during the COVID-19 pandemic (March 2020). Wald tests assessed the significance of interaction terms, which were retained irrespective of significance to explore sex-specific biomarker differences post-SRC. A subanalysis of post-SRC samples explored the associations between biomarker levels and symptom totals and severity scores, adjusting for age and sex at each interval. Lastly, an exploratory time point–stratified, time-to-event analysis was performed to determine whether post-SRC biomarker concentrations taken from the first blood draw postconcussion were associated with time to RTP using bootstrapped (1000 repetitions) age- and sex-adjusted Cox regressions where biomarker concentrations were dichotomized on median concentration within PID interval. Bootstrapping ensured robustness of interval-specific inferences by mitigating the influence of individual observations. Estimates and 95% CIs are reported for each analysis. For clinical translation, effect sizes of estimates were reported as percentage difference in raw biomarker concentrations. Biomarker data below the lower limit of detection (LLOD) were excluded. Statistical analyses were performed using Stata software version 16.1 (StataCorp) with an α level of .05. Data were analyzed from February to September 2023.

Results

Participant Characteristics

A total of 8124 adolescents were enrolled in the SHRed Concussions study (September 2019 to November 2022), of which 849 individual participants (695 uninjured participants; 467 male participants [67.2%]; 154 SRC participants; 78 male participants [51.0%]) contributed 1023 blood samples for biomarker analysis (695 uninjured participants; 328 SRC participants). See Table 1 for participant characteristics and Figure 1 for the study flow diagram. Uninjured samples were from 467 male participants (median [IQR] age, 15.90 [15.16-16.82] years) and 222 female participants (median [IQR] age, 15.87 [14.99-16.85] years), with 6 individuals not disclosing sex. Post-SRC samples were from 78 male participants (median [IQR] age, 15.95 [15.20-16.89] years) and 75 female participants (median [IQR] age, 16.30 [15.20-17.34] years), with 1 participant not disclosing sex. Both baseline uninjured and post-SRC samples were acquired for 20 participants (included in group-level analyses). Overall, 216 members of the uninjured group (31.1%; median [IQR] time since most recent concussion, 478.5 [176-1252] days) and 80 members of the post-SRC group (52.2%; median [IQR] time since most recent concussion, 530.5 [282-1470] days) reported a history of at least 1 previous concussion. Median (IQR) time to RTP was 29 (17-58) days for male participants and 38 (23-60) days for female participants. Post-SRC, the total plasma samples at each time point were 35 specimens (35 participants) for PID 0 to 3, 91 specimens (89 participants) for PID 4 to 10, 118 specimens (98 participants) for PID 11 to 28, and 84 specimens (54 participants) for PID greater than 28. Subacute time points included multiple samples from the same participants drawn on separate days: 2 for PID 4 to 10, 17 for PID 11 to 28, and 20 for PID greater than 28. Total sample sizes, demographic information, and SCAT5 symptom scores are reported in Table 1. Some measures were incomplete (ie, concussion history and SCAT5 symptom scores; variables not included in the primary analysis), and missing data are reported in Table 1.

Table 1. Participant Characteristics.

Characteristic	Participants, No. (%)
	Uninjured total		Postinjury total		PID 0-3		PID 4-10		PID 11-28		PID>28
	Male	Female	Male	Female	Male	Female	Male	Female	Male	Female	Male	Female
Total participants, No.^a	467	222	78	75	19	16	48	41	47	51	19	35
Total samples, No.	467	222	158	169	19	16	50	41	56	62	33	50
Age, mean (SD), y	15.91 (1.10)	15.71 (1.60)	15.92 (1.22)	16.15 (1.38)	15.73 (1.23)	16.18 (1.66)	15.91 (1.21)	16.20 (1.34)	15.99 (1.20)	16.18 (1.43)	16.10 (0.87)	16.31 (1.27)
Previous concussion
Any	153 (33)	63 (28)	40 (51)	40 (53)	8 (42)	10 (63)	25 (50)	19 (46)	28 (50)	35 (57)	21 (64)	37 (74)
Missing	24 (5)	9 (4)	3 (4)	2 (3)	0	0	1 (2)	0	1 (2)	2 (3)	1 (3)	1 (2)
No. of previous concussions
1	91 (20)	38 (17)	20 (26)	24 (32)	2 (10)	7 (43)	10 (20)	11 (27)	12 (21)	19 (31)	18 (55)	26 (52)
2	42 (9)	11 (5)	9 (12)	12 (16)	3 (16)	2 (13)	8 (16)	5 (12)	6 (11)	12 (19)	3 (9)	7 (14)
3	12 (3)	11(5)	6 (8)	3 (4)	2 (10)	1 (6)	3 (6)	3 (7)	6 (11)	4 (6)	0	3 (6)
4	1 (<1)	0	1 (1)	0	0	0	2 (4)	3 (7)	3 (5)	0	0	3 (6)
≥5	2 (<1)	2 (1)	4 (5)	1 (1)	1 (5)	0	2 (4)	0	1 (2)	0	0	0
Missing	8 (2)	2 (1)	3 (4)	2 (3)	0	0	1 (2)	0	1 (2)	2 (3)	1 (3)	1 (2)
Time since most recent previous concussion, median (IQR), months	19.86 (6.12-45.70)	11.34 (3.72-30.90)	26.22 (9.53-54.86)	16.47 (9.27-39.22)	44.84 (11.93-54.61)	12.13 (8.98-31.56)	19.49 (7.54-44.48)	22.51 (12.23-46.52)	35.64 (8.68-56.21)	28.04 (12.86-39.22)	57.67 (35.08-57.67)	12.33 (4.34-46.52)
Baseline SCAT5 symptom total^b
Mean (SD)	5.29 (5.02)	8.21 (6.00)	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Missing, No.	79	48	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Baseline SCAT5 Symptom Severity Score^c
Mean (SD)	8.83 (11.54)	15.62 (16.52)	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Missing	86 (12.5)	55 (7.98)	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Postinjury SCAT5 Symptom Total^b
Mean (SD)	NA	NA	11.68 (6.56)	13.59 (6.18)	5.96 (6.51)	8.21 (7.25)	8.91 (7.11)	12 (7.26)	5.96 (6.51)	8.21 (7.25)	4.88 (6.02)	6.45 (5.79)
Missing, No.	NA	NA	3	4	1	0	4	3	6	5	9	8
Postinjury SCAT5 Symptom Severity score^c
Mean (SD)	NA	NA	27.89 (25.38)	34.73 (23.59)	12.48 (20.23)	17.43 (19.64)	19.37 (22.78)	29.66 (25.89)	12.48 (20.23)	17.44 (19.64)	7.875 (12.31)	9.45 (10.95)
Missing, No.	NA	NA	3	4	1	0	4	3	6	5	9	8
Time to return to play, median (IQR), d	NA	NA	25 (15-53)	35 (20-58)	NA	NA	NA	NA	NA	NA	NA	NA

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Abbreviations: NA, not applicable; PID, postinjury days; SCAT5, Sport Concussion Assessment Tool 5.

^{^a}

Seven individuals (6 uninjured, 1 post–sport-related concussion [1 sample in postinjury day>28 only]) reported “prefer not to respond” for sex and are not included in the calculated values presented.

^{^b}

Maximum score is 22.

^{^c}

Maximum score is 132.

Figure 1. — PID indicates postinjury day; SRC, sport-related concussion.

Post-SRC Biomarker Levels

Aggregate raw and ln-transformed biomarker data are presented in eTable 1 in Supplement 1. Results from multilevel multivariable modeling displaying sex-specific group differences between uninjured and post-SRC biomarker levels are reported in Table 2 and Figure 2. Twenty-three replicates (17 uninjured and 6 post-SRC) for UCH-L1 fell below the LLOD and were excluded.

Table 2. Age-Adjusted, Sex-Specific, Post–Sport-Related Concussion Differences in Biomarker Concentrations.

Biomarker	Main effect of age			Average marginal effect of sex			Time point, PID	Female Participants			Male Participants
Biomarker	Effect, %	Coefficient (95% CI)	P value	Effect, %	Coefficient (95% CI)	P value	Time point, PID	Effect, %^a	Coefficient (95% CI)	P value	Effect, %^a	Coefficient (95% CI)	P value
lnGFAP	−5.41	−0.056 (−0.078 to −0.033)	<.001	−9.73	−0.102 (−0.165 to −0.040)	.001	0-3	17.76	0.164 (0.064 to 0.263)	.001	17.05	0.157 (0.086 to 0.229)	<.001
							4-10	10.72	0.102 (0.016 to 0.188)	.02	12.07	0.114 (0.058 to 0.169)	<.001
							11-28	15.13	0.141 (0.057 to 0.225)	.001	14.47	0.135 (0.078 to 0.192)	<.001
							>28	7.40	0.071 (−0.012 to 0.155)	.09	10.57	0.100 (0.029 to 0.172)	.006
lnUCH-L1	−0.98	−0.010 (−0.047 to 0.027)	.61	21.25	0.193 (0.088 to 0.297)	<.001	0-3	43.43	0.361 (0.125 to 0.596)	.003	11.66	0.110 (−0.083 to 0.304)	.26
							4-10	23.78	0.213 (0.026 to 0.401)	.03	11.19	0.106 (−0.04 to 0.252)	.15
							11-28	33.16	0.286 (0.107 to 0.466)	.002	2.10	0.021 (−0.127 to 0.169)	.78
							>28	52.84	0.424 (0.235 to 0.613)	<.001	19.36	0.177 (−0.01 to 0.364)	.06
lnNfL	0.97	0.010 (−0.014 to 0.033)	.42	−1.90	−0.001 (−0.066 to 0.064)	.98	0-3	4.38	0.043 (−0.073 to 0.159)	.47	18.97	0.174 (0.087 to 0.261)	<.001
							4-10	4.98	0.049 (−0.05 to 0.147)	.33	11.58	0.110 (0.043 to 0.176)	.001
							11-28	5.47	0.053 (−0.042 to 0.149)	.27	6.32	0.061 (−0.007 to 0.13)	.08
							>28	−2.73	−0.028 (−0.123 to 0.068)	.57	6.26	0.061 (−0.025 to 0.146)	.17
lnt-tau	−5.32	−0.055 (−0.082 to −0.028)	<.001	−9.89	−0.039 (−0.114 to 0.037)	.32	0-3	−22.90	−0.260 (−0.391 to −0.13)	<.001	−18.38	−0.203 (−0.3 to −0.106)	<.001
							4-10	−21.18	−0.238 (−0.349 to −0.127)	<.001	−8.01	−0.083 (−0.158 to −0.009)	.03
							11-28	−14.65	−0.158 (−0.267 to −0.05)	.004	9.13	0.087 (0.011 to 0.164)	.03
							>28	−17.72	−0.195 (−0.303 to −0.087)	<.001	5.91	0.057 (−0.038 to 0.153)	.24

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Abbreviations: lnGFAP, natural log glial fibrillary acidic protein; lnNfL, natural log neurofilament light; lnt-tau, natural log total tau; lnUCH-L1, natural log ubiquitin-c-hydrolase-L1; PID, postinjury day.

^{^a}

Time point effect sizes represent post–sport-related concussion group-level percentage difference in raw biomarker concentration at the specific time point compared with the uninjured group concentration.

Figure 2. — Mean natural log-transformed uninjured and post–sport-related concussion plasma biomarker levels across postinjury time intervals for A, GFAP; B, UCH-L1; C, NfL; and D, t-tau separated by sex. Error bars represent SEs. Samples beyond 28 days only consist of participants demonstrating prolonged recovery per Concussion in Sport Group definitions of typical recovery.

GFAP indicates glial fibrillary acidic protein; NfL, neurofilament light; t-tau, total tau; UCH-L1, ubiquitin-c-hydrolase-L1.

GFAP

Our primary analyses revealed sex-specific differences in post-SRC GFAP compared with uninjured levels at some time points. Relative to uninjured female participants, those post-SRC had significantly higher GFAP in the acute and subacute phases of recovery (PID 0-3: 17.8% increase; β = 0.164; 95% CI, 0.064 to 0.263; P = .001; PID 4-10: β = 0.102; 95% CI, 0.016 to 0.188; P = .02; PID 11-28: β = 0.141; 95% CI, 0.057 to 0.225; P = .001), but not at PID greater than 28. Relative to uninjured male participants, male participants post-SRC had higher GFAP at all time points (PID 0-3: 17.1% increase; β = 0.157; 95% CI, 0.086 to 0.229; P < .001; PID 4-10: β = 0.114; 95% CI, 0.058 to 0.169; P < .001; PID 11-28: β = 0.135; 95% CI, 0.078 to 0.192; P < .001; and PID > 28: β = 0.100; 95% CI, 0.029 to 0.172; P = .001). Main effects of age for GFAP (−5.4% per year; β = −0.056; 95% CI, −0.078 to −0.033; P < .001) and average marginal sex effects (9.7% lower GFAP in males; β = −0.102; 95% CI, −0.165 to −0.040; P = .001) were also found.

UCH-L1

Female participants post-SRC displayed higher levels of UCH-L1 compared with uninjured female participants at all time points (PID 0-3: 43.4% increase; β = 0.361; 95% CI, 0.125 to 0.596; P = .003; PID 4-10: β = 0.213; 95% CI, 0.026 to 0.401; P = .03; PID 11-28: β = 0.286; 95% CI, 0.107 to 0.466; P = .002; and PID > 28: β = 0.424; 95% CI, 0.235 to 0.613; P < .001). No significant differences were found in male participants. However, when comparing across sexes, at PID 11 to 28, female participants displayed 23.3% higher post-SRC differences than male participants (β = −0.266; 95% CI, −0.498 to −0.033; P = .03). An average marginal sex effect was found where male participants had 21.3% higher UCH-L1 levels than female participants (β = 0.193; 95% CI, 0.088 to 0.297; P < .001).

NfL

Differences in NfL were the least common of all biomarkers. The only uninjured vs post-SRC group-level differences were in male participants at PID 0 to 3 (19.0% increase; β = 0.174; 95% CI, 0.087-0.261; P < .001) and PID 4 to 10 (β = 0.110; 95% CI, 0.043-0.176; P = .001). There were no significant age or sex effects.

t-tau

A significant sex by PID interval interaction was found for t-tau (χ²₄ = 20.08; P < .001). In female participants, t-tau was lower at all post-SRC time points compared with uninjured levels (PID 0-3: −22.9%; β = −0.260; 95% CI, −0.391 to −0.130; P < .00; 1 PID 4-10: β = −0.238; 95% CI, −0.349 to −0.127; P < .001; PID 11-28: β = −0.158; 95% CI, −0.267 to −0.050; P = .004; and PID > 28: β = −0.195; 95% CI, −0.303 to −0.087; P < .001). In male participants, post-SRC t-tau was lower at PID 0 to 3 (−18.4%; β = −0.203; 95% CI, −0.300 to −0.106; P < .001) and PID 4 to 10 (β = −0.083; 95% CI, −0.158 to −0.009; P = .03), but higher at PID 11 to 28 (β = 0.087; 95% CI, 0.011 to 0.164; P = .03) relative to uninjured participants. Additionally, male participants displayed larger post-SRC vs uninjured differences compared with female participants at PID 4 to 10 (β = 0.154; 95% CI, 0.021 to 0.288; P = .02), PID 11 to 28 (β = 0.246; 95% CI, 0.113 to 0.378; P < .001) and PID greater than 28 (β = 0.252; 95% CI, 0.108 to 0.396; P = .001). Main effects were also observed for age (−5.3% t-tau per year; β = −0.055; 95% CI, −0.082 to −0.028; P < .001).

SCAT5 Symptom Burden, Recovery Time, and Biomarker Levels

Table 1 displays mean post-SRC and postinjury interval SCAT5 symptom totals and severity scores. Results from exploratory analyses investigating biomarker associations with post-SRC symptom burden are presented in eTable 2 and eTable 3 in Supplement 1. GFAP was positively associated with symptom total (β = 0.004; 95% CI, 0.000 to 0.008; P = .04) and severity score (β =0.002; 95% CI, 0.000 to 0.003; P = .02) at PID 0 to 3. NfL was positively associated with symptom total (PID 0-3: β = 0.007; 95% CI, 0.002 to 0.012; P = .003; PID 4-10: β = 0.006; 95% CI, 0.003 to 0.010; P = .001; and PID > 28: β = 0.008; 95% CI, 0.001 to 0.015; P = .03) and severity score (PID 0-3: β = 0.002; 95% CI, 0.001 to 0.004; P = .002; PID 4-10: β = 0.002; 95% CI, 0.001 to 0.003; P = .002). Lastly, t-tau was negatively associated with symptom total (PID 0-3: β = −0.011; 95% CI, −0.016 to −0.006; P < .001; PID 4-10: β = −0.004; 95% CI, −0.009 to 0.000; P = .03) and severity score at the first 2 time points (PID 0-3: β = −0.003; 95% CI, −0.005 to −0.002; P < .001; PID 4-10: β = −0.002; 95% CI, −0.003 to 0.000; P = .01), but then positively associated at PID more than 28 (symptom total: β = 0.013; 95% CI, 0.005 to 0.021; P = .001; severity score: β = 0.008; 95% CI, 0.003 to 0.012; P = .001).

Results from time-to-event analyses of the association between post-SRC biomarker levels and days to RTP are displayed in Figure 3, eFigure 1, and eTable 4 in Supplement 1. Pronounced separations in survival curves were observed at the PID greater than 28 interval in each biomarker, but the only significant association occurred with GFAP (hazard ratio, 4.78; 95% CI, 1.59-14.31; P = .01), whereby higher GFAP levels after 28 days were associated with a faster recovery.

Discussion

This prospective cohort study investigated plasma concentrations of GFAP, UCH-L1, NfL, and t-tau in adolescent sport participants at uninjured and post-SRC time points throughout recovery. We demonstrated differences in uninjured vs adolescents post-SRC for all 4 biomarkers that may be associated with age and sex. Exploratory analyses also revealed GFAP, t-tau, and NfL may be associated with post-SRC symptom burden and time to RTP.

SRC, Age, and Sex Associations With Biomarkers in Adolescents

Blood sampled at different PID intervals post-SRC revealed notable biomarker differences, with both GFAP and UCH-L1 exhibiting persistent elevations after injury. Prior work in adult concussion has reported UCH-L1 and GFAP peaks within 24 hours of injury.^11,30 We may have missed the true peak for these biomarkers given the limited samples obtained in this time frame (4 samples). However, elevated GFAP levels at subsequent intervals align with reports in the adult literature at later time points. Interestingly, postinjury UCH-L1 levels seen in our study are unique in the SRC context. This discrepancy may be due to our statistical approach, which accommodates the high analytical variation in UCH-L1 commonly found in SRC studies, perhaps capturing differences that would otherwise have been lost if variable replicate data were excluded.²⁹

Post-SRC t-tau levels align with prior reports in adolescents and adults,^11,13,31 but a sex by PID interval effect was evident. Both sexes exhibited decreased t-tau until PID 4 to 10; however, female participants with SRC remained below the uninjured group mean at each postinjury time point, while male participants’ t-tau significantly increased at PID 11 to 28 and PID greater than 28. Male-specific changes in NfL have also been documented in other SRC research,¹² reinforcing the importance of analyzing sex differences following concussion. These variations may be influenced by various sexual dimorphisms in the brain, including distinctions in neurodevelopment, sex hormones, or neuroinflammatory responses.^{32,33,34,35,36}

Age was negatively associated with both GFAP and t-tau, suggesting higher levels in younger individuals, consistent with previous studies and recently published normative data in Canadian youths.^26,27,37,38 Age-dependent diagnostic utility of these biomarkers has been demonstrated for detection of intracranial trauma after adult mild traumatic brain injury,³⁹ but age-related investigations in SRC in adolescents will require comparisons with reference intervals from large representative adolescent samples as few of our participants had biomarker levels above reported upper ranges of normal.^26,27 However, studies of potential biomarker differences between athletic and general adolescent populations are warranted.^38,40,41,42 Lastly, available evidence on biomarker sex differences is limited despite clinical evidence of divergent female experiences and symptom reporting following SRC.^43,44,45 Sex differences in GFAP, UCH-L1, and NfL underscore the importance of including sex in future clinical validation studies.

Biomarkers and Symptom Burden and Recovery Time

Historically, the clinical applicability of SRC fluid biomarkers in adolescents has not been examined.⁴⁶ Our study aimed to bridge the gap between biochemistry and clinical utility by exploring post-SRC biomarker associations with SCAT5 symptom reporting. All biomarkers except UCH-L1 were significantly associated with symptom burden. However, the clinical significance of these associations is limited as effect sizes rarely exceeded a 1% change in biomarker concentration per unit increase in symptom score. Overall, our data suggest these biomarkers are sensitive to adolescent SRC, but they may not enhance typical recovery monitoring over established clinical protocols. However, biomarker elevations beyond 28 days were specific to adolescents with prolonged time to medical clearance, suggesting potential utility in studies exploring treatment interventions for this clinical population. Results from our exploratory time-to-event analyses support investigation of these biomarkers at extended time points, particularly for GFAP, where elevated concentrations were, counterintuitively, associated with faster recovery times in blood sampled after 28 days. This suggests that dynamic astrocytic processes may have beneficial roles in prolonged recovery. Overall, the biomarker differences mirror many trends observed in adults, suggesting consistent neurophysiological processes (eg, axonal injury, glial activation) occur following adolescent SRC. However, the variations due to age and sex highlight unique considerations for developmental and/or pubertal factors in this age group, possibly explained by neuropathological mechanisms unique to the developing brain. For instance, the neuroinflammatory response to concussion may differ due to age-specific immune- or hormone-mediated influences, resulting in altered production and/or release of biomarkers into general circulation.^6,37,47 Although these processes are speculative here, our work provides a foundation for future studies to fully investigate SRC pathology in the developing brain.

Strengths and Limitations

To our knowledge, this study features the largest adolescent SRC blood biomarker sample to date. Key methodological strengths increase the generalizability of our findings. This includes the collection of a large sample of uninjured specimens from community sport sites across Canada, providing a representative estimate of healthy biomarker concentrations in adolescents for comparison, and the sizable post-SRC sample from community sport-medicine clinics, enabling the characterization of biomarker differences at various intervals since injury. Additionally, our post-SRC sample included a relatively balanced representation of sex, allowing for an investigation of sex differences that have been inadequately explored thus far.

The study also has limitations. Statistical analyses were restricted to group-level comparisons between uninjured and post-SRC samples. The original study design aimed to acquire more blood samples from uninjured individuals who later experienced SRC, along with serial post-SRC specimen collection throughout clinical recovery, to better capture biomarker trajectories. However, pandemic-related disruptions limited our within-participant pre-post data. In addition, many initial post-SRC samples were acquired beyond the possible 24- to 48-hour peak in biomarkers. Future adolescent studies aiming to collect earlier post-SRC data may require sideline or mobile blood collection to increase generalizability to acute-care settings. Furthermore, while this study enrolled participants aged 10 to 18 years, most were between 15 to 17 years which may not fully reflect biomarker differences across broader developmental stages. Future research should investigate a wider age distribution to better understand variations in pediatric SRC. Additionally, our t-tau data should be interpreted with caution given blood and cerebrospinal fluid t-tau are poorly correlated, and results may reflect peripheral tau metabolism.^48,49,50,51 Future SRC studies may instead benefit from brain-derived tau assays.⁵⁰ Lastly, while we reported group-level biomarker differences to healthy participants, future directions should include comparisons of post-SRC concentrations to established normative ranges to determine clinical utility.^26,27

Conclusions

In this cohort study of 849 adolescents, significant differences in plasma GFAP, UCH-L1, t-tau, and NfL were demonstrated at multiple time points in adolescents with SRC compared with uninjured samples in group-level analyses, adding to the growing literature that these biomarkers are sensitive to SRC in this population. These results support the use of these biomarkers to investigate adolescent SRC pathophysiology. Future studies should consider biomarker associations with age and sex as they may have implications for potential clinical validation.

Supplement 1.

eFigure 1. Time to RTP Clearance by Acute (PID 0-3) Median Biomarker Concentration Produced by Age- and Sex-Adjusted Cox Regression

eFigure 2. Cross-Lot Analysis for t-tau, NfL, GFAP, and UCH-L1

eTable 1. Biomarker Levels Across Time Intervals

eTable 2. Age and Sex-Adjusted Associations Between Total Number of Symptoms and Post-SRC Biomarker Concentrations

eTable 3. Age and Sex-Adjusted Associations Between Symptom Severity Scores and Post-SRC Biomarker Concentrations

eTable 4. Time-to-Event Analysis of Biomarkers Post-SRC

eTable 5. Age-Adjusted Sex-Specific Post-SRC Differences in UCH-L1

jamanetwopen-e2431959-s001.pdf^{(780.9KB, pdf)}

Supplement 2.

Data Sharing Statement

jamanetwopen-e2431959-s002.pdf^{(13.3KB, pdf)}

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement 1.

eFigure 1. Time to RTP Clearance by Acute (PID 0-3) Median Biomarker Concentration Produced by Age- and Sex-Adjusted Cox Regression

eFigure 2. Cross-Lot Analysis for t-tau, NfL, GFAP, and UCH-L1

eTable 1. Biomarker Levels Across Time Intervals

eTable 2. Age and Sex-Adjusted Associations Between Total Number of Symptoms and Post-SRC Biomarker Concentrations

eTable 3. Age and Sex-Adjusted Associations Between Symptom Severity Scores and Post-SRC Biomarker Concentrations

eTable 4. Time-to-Event Analysis of Biomarkers Post-SRC

eTable 5. Age-Adjusted Sex-Specific Post-SRC Differences in UCH-L1

jamanetwopen-e2431959-s001.pdf^{(780.9KB, pdf)}

Supplement 2.

Data Sharing Statement

jamanetwopen-e2431959-s002.pdf^{(13.3KB, pdf)}

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PERMALINK

Plasma Biomarkers of Traumatic Brain Injury in Adolescents With Sport-Related Concussion

Jason B Tabor, PhD

Linden C Penner, MSc

Jean-Michel Galarneau, PhD

Nik Josafatow, MSc

Jennifer Cooper, BMLSc

Mohammad Ghodsi, BSc

Johnny Huang, BSc

Douglas D Fraser, MD, PhD

Jonathan Smirl, PhD

Michael J Esser, MD, PhD

Keith Owen Yeates, PhD

Cheryl L Wellington, PhD

Chantel T Debert, MD, MSc

Carolyn A Emery, PhD

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Exposures

Main Outcomes and Measures

Results

Conclusions and Relevance

Introduction

Methods

Participants

Blood Collection

Biomarker Analysis

Statistical Analysis

Results

Participant Characteristics

Table 1. Participant Characteristics.

Figure 1. Participant Flowchart.

Post-SRC Biomarker Levels

Table 2. Age-Adjusted, Sex-Specific, Post–Sport-Related Concussion Differences in Biomarker Concentrations.

Figure 2. Mean Natural Log-Transformed Uninjured and Post–Sport-Related Concussion Plasma Biomarker Levels Across Postinjury Time Intervals.

GFAP

UCH-L1

NfL

t-tau

SCAT5 Symptom Burden, Recovery Time, and Biomarker Levels

Figure 3. Time to Return to Play (RTP) Clearance by Prolonged Recovery (Postinjury Day >28) Median Biomarker Concentration Produced by Age- and Sex-Adjusted Cox Regression.

Discussion

SRC, Age, and Sex Associations With Biomarkers in Adolescents

Biomarkers and Symptom Burden and Recovery Time

Strengths and Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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