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.