To assess the accuracy and physiological relevance of circulating microRNA (miRNA) as a biomarker of pediatric concussion, we compared changes in salivary miRNA and cerebrospinal fluid (CSF) miRNA concentrations after childhood traumatic brain injury (TBI). A case-cohort design was used to compare longitudinal miRNA concentrations in CSF of seven children with severe TBI against three controls without TBI. The miRNAs "altered" in CSF were interrogated in saliva of 60 children with mild TBI and compared with 18 age- and sex-matched controls. The miRNAs with parallel changes (Wilcoxon rank sum test) in CSF and saliva were interrogated for predictive accuracy of TBI status using a multivariate regression technique. Spearman rank correlation identified relationships between miRNAs of interest and clinical features. Functional analysis with DIANA mirPath identified related mRNA pathways. There were 214 miRNAs detected in CSF, and 135 (63%) were also present in saliva. Six miRNAs had parallel changes in both CSF and saliva (miR-182-5p, miR-221-3p, mir-26b-5p, miR-320c, miR-29c-3p, miR-30e-5p). These miRNAs demonstrated an area under the curve of 0.852 for identifying mild TBI status. Three of the miRNAs exhibited longitudinal trends in CSF and/or saliva after TBI, and all three targeted mRNAs related to neuronal development. Concentrations of miR-320c were directly correlated with child and parent reports of attention difficulty. Salivary miRNA represents an easily measured, physiologically relevant, and accurate potential biomarker for TBI. Further studies assessing the influence of orthopedic injury and exercise on peripheral miRNA patterns are needed.

IMPORTANCE Approximately one-third of children who experience a concussion develop prolonged concussion symptoms. To our knowledge, there are currently no objective or easily administered tests for predicting prolonged concussion symptoms. Several studies have identified alterations in epigenetic molecules known as microRNAs (miRNAs) following traumatic brain injury. No studies have examined whether miRNA expression can detect prolonged concussion symptoms. OBJECTIVE To evaluate the efficacy of salivary miRNAs for identifying children with concussion who are at risk for prolonged symptoms. DESIGN, SETTING, AND PARTICIPANTS This prospective cohort study at the Penn State Medical Center observed 52 patients aged 7 to 21 years presenting for evaluation of concussion within 14 days of initial head injury, with follow-up at 4 and 8 weeks. EXPOSURES All patients had a clinical diagnosis of concussion. MAIN OUTCOMES AND MEASURES Salivary miRNA expression was measured at the time of initial clinical presentation in all patients. Patients with a Sport Concussion Assessment Tool (SCAT3) symptom score of 5 or greater on self-report or parent report 4 weeks after injury were designated as having prolonged symptoms. RESULTS Of the 52 included participants, 22 (42%) were female, and the mean (SD) age was 14 (3) years. Participants were split into the prolonged symptom group (n = 30) and acute symptom group (n = 22). Concentrations of 15 salivary miRNAs spatially differentiated prolonged and acute symptom groups on partial least squares discriminant analysis and demonstrated functional relationships with neuronal regulatory pathways. Levels of 5 miRNAs (miR-320c-1, miR-133a-5p, miR-769-5p, let-7a-3p, and miR-1307-3p) accurately identified patients with prolonged symptoms on logistic regression (area under the curve, 0.856; 95% CI, 0.822-0.890). This accuracy exceeded accuracy of symptom burden on child (area under the curve, 0.649; 95% CI, 0.388-0.887) or parent (area under the curve, 0.562; 95% CI, 0.219-0.734) SCAT3 score. Levels of 3 miRNAs were associated with specific symptoms 4 weeks after injury; miR-320c-1 was associated with memory difficulty (R, 0.55; false detection rate, 0.02), miR-629 was associated with headaches (R, 0.47; false detection rate, 0.04), and let-7b-5p was associated with fatigue (R, 0.45; false detection rate, 0.04). CONCLUSIONS AND RELEVANCE Salivary miRNA levels may identify the duration and character of concussion symptoms. This could reduce parental anxiety and improve care by providing a tool for concussion management. Further validation of this approach is needed.

Background: Early, accurate diagnosis of mild traumatic brain injury (mTBI) can improve clinical outcomes for patients, but mTBI remains difficult to This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Objective The goals of this study were to assess the ability of salivary non-coding RNA (ncRNA) levels to predict post-concussion symptoms lasting ≥ 21 days, and to examine the ability of ncRNAs to identify recovery compared to cognition and balance. Methods RNA sequencing was performed on 505 saliva samples obtained longitudinally from 112 individuals (8–24-years-old) with mild traumatic brain injury (mTBI). Initial samples were obtained ≤ 14 days post-injury, and follow-up samples were obtained ≥ 21 days post-injury. Computerized balance and cognitive test performance were assessed at initial and follow-up time-points. Machine learning was used to define: (1) a model employing initial ncRNA levels to predict persistent post-concussion symptoms (PPCS) ≥ 21 days post-injury; and (2) a model employing follow-up ncRNA levels to identify symptom recovery. Performance of the models was compared against a validated clinical prediction rule, and balance/cognitive test performance, respectively. Results An algorithm using age and 16 ncRNAs predicted PPCS with greater accuracy than the validated clinical tool and demonstrated additive combined utility (area under the curve (AUC) 0.86; 95% CI 0.84–0.88). Initial balance and cognitive test performance did not differ between PPCS and non-PPCS groups (p > 0.05). Follow-up balance and cognitive test performance identified symptom recovery with similar accuracy to a model using 11 ncRNAs and age. A combined model (ncRNAs, balance, cognition) most accurately identified recovery (AUC 0.86; 95% CI 0.83–0.89). Conclusions ncRNA biomarkers show promise for tracking recovery from mTBI, and for predicting who will have prolonged symptoms. They could provide accurate expectations for recovery, stratify need for intervention, and guide safe return-to-activities.

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Concussion is a heterogeneous injury that relies predominantly on subjective symptom reports for patient assessment and treatment. Developing an objective, biological test could aid phenotypic categorization of concussion patients, leading to advances in personalized treatment. This prospective multi-center study employed saliva micro-ribonucleic acid (miRNA) levels to stratify 251 individuals with concussion into biological subgroups. Using miRNA biological clusters, our objective was to assess for differences in medical/demographic characteristics, symptoms, and functional measures of balance and cognition. The miRNAs that best defined each cluster were used to identify physiological pathways that characterized each cluster. The 251 participants (mean age: 18 ± 7 years; 57% male) were optimally grouped into 10 clusters based on 22 miRNA levels. The clusters differed in age (χ 2 = 19.1, p = 0.024), days post-injury at the time of saliva collection (χ 2 = 22.6; p = 0.007), and number of prior concussions (χ 2 = 17.6, p = 0.040). The clusters also differed in symptom reports for fatigue (χ 2 = 17.7; p = 0.039), confusion (χ 2 = 22.3; p = 0.008), difficulty remembering (χ 2 = 22.0; p = 0.009), and trouble falling asleep (χ 2 = 17.2; p = 0.046), but not objective balance or cognitive performance ( p > 0.05). The miRNAs that defined concussion clusters regulate 16 physiological pathways, including adrenergic signaling, estrogen signaling, fatty acid metabolism, GABAergic signaling, synaptic vesicle cycling, and transforming growth factor (TGF)-β signaling. These results show that saliva miRNA levels may stratify individuals with concussion based on underlying biological perturbations that are relevant to both symptomology and pharmacological targets. If validated in a larger cohort, miRNA assessment could aid individualized, biology-driven concussion treatment.

OBJECTIVES/GOALS: There is no objective, biologic tool to detect concussion or guide clinical management. We previously showed that saliva microRNA (miRNA) levels differ in children with concussion and may predict symptom duration. The purpose of this study was to validate the utility of saliva miRNA and define longitudinal trends during the recovery period. METHODS/STUDY POPULATION: We collected concussion symptom burden (SCAT-5), cognitive performance (DANA), balance measures (ClearEdge), and saliva from 150 children (7-21 years) with concussion over 5 time-points: 0-2, 3-6, 7-14, 15-29, and 30-60 days post-injury. Saliva miRNA levels within the 443 concussion samples were quantified with RNA sequencing and compared to 218 samples from age- and sex-matched controls (healthy and post-exercise participants). Non-parametric ANOVA assessed RNA levels across time-points, and between concussions/controls. Machine learning was used to build logistic regression algorithms differentiating concussions/controls, and symptomatic/recovered concussion participants. Relationships between miRNAs and concussion phenotypes were explored with Spearman’s Rank correlations. RESULTS/ANTICIPATED RESULTS: Fifteen miRNAs differed across control and concussion participants (FDR < 0.05). Within concussion participants, all 15 miRNAs trended back toward control levels by 30-60 days post injury. A regression algorithm employing 6 of the 15 miRNAs differentiated control and concussion participants with an area under the curve (AUC) of 0.78 in a training set (n = 244) and 0.84 in a naïve test set (n = 24). Similarly, 6 miRNAs were able to differentiate symptomatic (SCAT-5 symptom score > 7) and asymptomatic concussion participants with an AUC of 0.73 in a training set (n = 219) and 0.76 in a naïve test set (n = 44). Furthermore, 5 miRNAs showed significant (R > 0.3; FDR < 0.05) associations with subjective and/or objective measures of concussion-related symptoms. DISCUSSION/SIGNIFICANCE OF IMPACT: Saliva miRNAs levels are altered in children with concussion, and display predictable longitudinal trends following injury. Saliva miRNA measurement represents a non-invasive, objective tool that could be rapidly assessed to provide biologic evidence for clinicians managing pediatric concussion. CONFLICT OF INTEREST DESCRIPTION: I serve as a paid consultant and scientific advisory board member for Quadrant Biosciences, who has funded a portion of this work and licensed the findings from the Penn State College of Medicine.

Objectives: To determine whether adolescents with persistent postconcussion symptoms (PPCS) differ from healthy peers in their personality traits and social supports. Setting: Specialty Concussion Clinic and Primary Care Clinic affiliated with an academic medical center. Participants: Ninety-seven adolescents (42 with PPCS, 55 healthy peers; age: 15 ± 2 years). Design: Participants completed a web-based survey that included medical and demographic characteristics, mechanisms of concussion, 10-item Big Five Inventory, and Child and Adolescent Social Support Scale. A Student's 2-tailed t test with multiple testing corrections was used to compare the youths with PPCS to healthy peers. Main Measures: The primary outcome was PPCS, defined by the presence of 2 or more concussionrelated symptoms on the Post-Concussion Symptom Scale (PCSS), lasting for more than 4 weeks after initial injury. The secondary outcome was perceived personality traits and social support, based on the 10-item Big Five Inventory and the Child and Adolescent Social Support Scale, respectively. Results: The PPCS group had higher neuroticism scores on their Big Five Inventory than healthy peers. They also reported less social support from teachers and classmates than healthy peers. Conclusion: Youths with PPCS report specific personality and social support characteristics that differ from their peers. These findings suggest that individual personality and schoolbased social supports may influence concussion recovery.