Salivary MicroRNAs as Biomarkers for Identification and Prognosis in Adolescents Following Concussion

Abstract

MicroRNAs (miRNAs), which are small noncoding RNAs involved in gene regulation that can be measured reliably in saliva, have emerged as promising biomarker candidates for identifying concussion. However, research thus far is limited, and the role of miRNAs in prognosis following concussion in adolescents remains largely unexplored. This case-cohort study investigated whether salivary miRNAs collected within 10 days of injury could identify concussed adolescents from age- and sex-matched, healthy, uninjured controls, and predict symptom burden at 3-weeks post injury. Saliva samples were collected from 58 concussed adolescents (mean age [SD] = 15.4 [1.6] years; 25 females) within 10 days of injury, and 35 age- and sex-matched, healthy, uninjured controls. Using a neurodegenerative panel of 798 miRNAs, we applied feature selection to identify miRNAs that best identified concussed from healthy, uninjured adolescents. Additional analysis investigated whether these miRNAs were able to predict concussion symptom burden 3-weeks post injury. Results indicated that two miRNAs were significantly upregulated in concussed participants: (1) hsa-miR-26a-5p (F = 8.2, p = 0.005, False Discovery Rate [FDR]-corrected p = 0.008) and (2) hsa-miR-4286 (F = 9.6, p = 0.002, FDR-corrected p = 0.008). Higher hsa-miR-4286 levels predicted lower symptom burden at 3-weeks (β = −0.41, p = 0.001, FDR-corrected p = 0.002). The findings indicated that two salivary miRNAs demonstrated promise as clinically feasible biomarkers for identifying concussion in adolescents, one of which, was also useful for prognosis of symptom burden. The observed miRNA alterations may reflect injury-induced changes in neuroinflammatory and repair pathways, but larger, longitudinal studies are needed to validate these candidates and establish their sensitivity and specificity in this population.

Keywords

adolescents biomarkers biospecimen concussion mTBI microRNA

Introduction

Concussion, or mild traumatic brain injury (mTBI), is a major public health concern, with high incidence among adolescents worldwide.¹ Just between 2016 and 2020, the percentage of the U.S. adolescents reporting at least one lifetime concussion has increased from 19.5% to 24.6%.¹ This is concerning, as adolescent concussion has been linked to short- and long-term adverse outcomes such as cognitive impairment, emotional dysregulation, and academic difficulties. Although most adolescents recover within 2–4 weeks,² a significant subset experiences prolonged symptoms with developmental, educational, and psychosocial consequences.^3–5 Current clinical assessments rely largely on self-reported symptoms, which are often subjective and may not accurately capture underlying neurobiological processes.⁶ Therefore, identifying objective and reliable predictors of recovery is critical for improving clinical management. MicroRNAs (miRNAs) have emerged as promising biomarkers that may provide insights beyond current clinical assessments.⁷

MiRNAs are small, noncoding RNAs that regulate gene expression by binding to messenger RNAs and either blocking translation or promoting degradation.^7,8 In the brain, miRNAs are critical for neurodevelopment, synaptic plasticity, and neuronal signaling⁸ and their dysregulation has been linked to key injury-related processes such as inflammation and neuronal stress.^7,9,10 A major advantage of miRNA-based biomarkers is their stability in biofluids, which allows for consistent measurements.⁷ Saliva, in particular, offers a noninvasive method for biomarker assessment, making it well-suited for pediatric and adolescent populations compared with blood.^7,10,11 Recent studies support their potential in concussion, with higher levels of salivary miRNAs predicting concussion duration, tracking symptom recovery, and, in some cases, outperforming traditional cognitive and balance assessments.^6,9–13 Yet, heterogeneity across reports and the use of broad age ranges limit their clinical utility in adolescent concussion. Given that adolescence is a time of high susceptibility to concussion,^14,15 identifying specific miRNA profiles that can capture individual differences in symptom recovery during this developmental window may open opportunities for early identification of risk for prolonged recovery.

The primary purpose of this study was to determine which salivary miRNAs can reliably identify concussed from healthy, uninjured adolescent controls. A secondary purpose was to evaluate the association of miRNAs with concussion symptom burden (total symptom severity) 3 weeks after injury. To this end, we used a panel of 798 miRNAs informed by prior neurodegenerative and brain injury research to enable comprehensive profiling. We hypothesized that concussed adolescents would demonstrate higher miRNA levels relative to controls. We also hypothesized that higher levels of these miRNAs would be associated with higher symptom burden 3 weeks after injury.

Methods

Study design

This work is part of a longitudinal neuroimaging study (Investigating Concussion in Adolescents at Risk for Emotional Dysregulation—iCARE) conducted at the University of Pittsburgh and that enrolled participants between 2019 and 2024.^16–20 Adolescents aged 12–17.9 years who sustained a concussion within the previous 10 days (mean time [SD] from injury to study-entry visit = 3.7 [2.5] days) were recruited. Concussions were diagnosed according to current consensus guidelines.^2,21 Age- and sex-matched healthy controls (HC) were also recruited.

Participants

Participants with concussion were recruited from the UPMC Sports Medicine Concussion Program and the UPMC Children’s Hospital of Pittsburgh Emergency Department. HC were recruited through a voluntary community-based registry (https://pittplusme.org). A total of 60 adolescents with concussion and 39 HCs completed the salivary miRNA protocol. See Supplementary Data for exclusion criteria and more details about the parent study.

Assessments

Saliva collection

Participants were instructed to abstain from eating, drinking, or oral hygiene for at least 30 minutes before collection. Saliva samples were collected using Oragene® CP-190 kits following the manufacturer instructions. After collection, samples were stabilized in Oragene solution and stored at −80°C until RNA extraction. See additional details in the Supplementary Data.

Post-concussive symptoms

The Post-Concussion Symptom Scale (PCSS)²² was used to assess post-concussive symptoms. The PCSS ask patients to rate on a 0 (none) to 6 (severe) scale 22 concussion symptom items, resulting in a total symptom severity (i.e., symptom burden) score ranging from 0 to 132.

Additional information

A standard-of-care intake form, interview, and clinical examination collected demographic information (e.g., age, sex). Causes of current concussion and history of previous concussion and migraine were also assessed.

Procedures

Study visits and assessments

This study was approved by the Institutional Review Board at the University of Pittsburgh (STUDY19030360). At the study-entry visit, parents/guardians and participants provided written informed consent and assent, respectively. Participants with concussion completed PCSS assessment at study-entry (first 10 days post injury) and follow-up (3-weeks post-concussion) visits. Saliva samples were collected at study-entry visit.

MiRNA quantification

Figure 1–Panel A displays processing and analysis steps. Overall, saliva-derived miRNA was first extracted and hybridized with fluorescently barcoded probes (NanoString Technologies). Then, after a standardized preparation (removal of excessive probes and probe-target fixation into a cartridge surface), fluorescently barcoded probes were quantified using the nCounter Digital Analyzer, subjected to comprehensive quality control procedures, and normalized with ligation and positive controls alongside outlier detection. MiRNA expression was quantified using the nCounter Human v3 miRNA Expression Assay, which profiles 798 unique human miRNAs via direct digital barcoding without amplification²³ (Supplementary Table S1). Levels of each miRNA were extracted for statistical analysis. Additional details are provided in the Supplementary Data.

FIG. 1.

Overview of saliva miRNA processing and main findings. (A) shows the step-by-step workflow used to quantify salivary miRNAs in concussed and control adolescents. For more specific details, see Supplementary Data. (B) shows a bar plot of the mean expression levels (log-transformed) for each miRNA, highlighting significant between-group differences. p-Values for each comparison are indicated, and the legend identifies concussed adolescents (red) and controls (blue). (C) displays a scatter plot depicting the linear relationship between hsa-miR-4286 expression and post-concussive symptoms at 3-week follow-up.

Statistical approach

Feature selection methods

The contribution of 798 extracted miRNAs in differentiating concussed from HC participants was assessed using Least Absolute Shrinkage and Selection Operator (LASSO) regression within the GLMNET package.^24–26 GLMNET fits generalized linear models using a penalty (α = 1; LASSO), shrinking non-informative coefficients to zero, which is advantageous for biomarker identification and interpretability in small samples. The optimal tuning parameter (λ) was selected via cross-validation, and miRNAs with non-zero coefficients were retained as meaningful contributors, with larger absolute coefficients indicating greater influence in the model.^25,26

Between-group differences methods

Because LASSO does not provide conventional test statistics (e.g., F- or p-values), analysis of covariance (ANCOVA) models compared the levels of the miRNAs selected with LASSO between concussed and HC participants. The distribution of each miRNA was assessed using the Shapiro–Wilk test; miRNAs with non-normal distributions were log-transformed prior to analysis. Age and sex were included as covariates. False discovery rate (FDR²⁷) was used to account for multiple comparisons.

Predicting follow-up post-concussive symptoms' methods

Linear regression models investigated whether the levels of the miRNAs selected by LASSO were associated with PCSS scores at 3-week follow-up. Age and sex were included as covariates. In addition, PCSS scores at study-entry and time between injury and study-entry were included as covariates to account for study-entry levels. FDR was used to account for multiple comparisons.

Results

Sample

After QC, a total of 58 adolescents with concussion (mean age [SD] = 15.4 [1.6] years; 25 females) and 35 HCs had usable miRNA data. There were no between-group differences in age or sex distribution (Table 1). At the 3-week follow-up, PCSS scores were available for 50 adolescents with concussion (mean age [SD] = 15.5 [1.6] years; 23 females).

Table 1.

Demographic Characteristics

Variable	HC (N = 35)	Concussed (N = 58)	Statistic	p
Age mean [SD]	15.26 [1.52]	15.44 [1.62]	0.29	0.592
Sex at birth
Male N(%)	16 (46%)	33 (57%)	0.69	0.405
Female N(%)	19 (54%)	25 (43%)	0.69	0.405
Causes of current concussion
Sports N(%)	—	45 (78%)	—	—
Fall/accident N(%)	—	9 (16%)
Other N(%)	—	4 (7%)
History of previous concussion
Yes N(%)	0 (0%)	15 (26%)	—	—
No N(%)	35 (100%)	43 (74%)	—	—
History of migraine
Yes N(%)	0 (0%)	9 (16%)	—	—
No N(%)	35 (100%)	49 (84%)	—	—
Post-Concussive Symptom Scale-total score mean [SD]	2.5 [3.84]	27.47 [18.67]	55.6	<0.001

Feature selection results

Among the 798 miRNAs, only three were identified as differentiating features between concussed and HC participants: hsa-miR-26a-5p, hsa-miR-4286, and hsa-miR-16-5p (Supplementary Table S2).

Between-group differences results

Using log-transformed outcomes, ANCOVAs revealed statistically significant differences in two of the three miRNAs: hsa-miR-26a-5p (F = 8.2, p = 0.005, FDR-corrected p = 0.008) and hsa-miR-4286 (F = 9.6, p = 0.002, FDR-corrected p = 0.008; Fig. 1–Panel B). ANCOVA revealed a trend toward significance for hsa-miR-16-5p (F = 3.8, p = 0.054, FDR-corrected p = 0.054; Fig. 1–Panel B). Concussed participants showed higher levels of miRNA than HC (Supplementary Table S3).

Predicting follow-up post-concussive symptoms' results

Linear regression models revealed that higher levels of hsa-miR-4286 at study-entry were associated with lower post-concussive symptoms at 3-week follow-up (β = −0.41, p = 0.001, FDR-corrected p = 0.002; Fig. 1–Panel C). Levels of hsa-miR-26a-5p (β = −0.17, p = 0.138, FDR-corrected p = 0.138) and hsa-miR-16-5p (β = −0.21, p = 0.071, FDR-corrected p = 0.107) were not associated with post-concussive symptoms at 3-week follow-up.

Discussion

This study aimed to determine whether distinct salivary miRNAs could differentiate concussed adolescents from controls and serve as predictors of post-concussive symptoms at 3 weeks post-injury. Our findings indicated that the levels of salivary miRNAs were significantly elevated in concussed adolescents versus HCs, specifically hsa-miR-26a-5p and hsa-miR-4286, and that higher levels of hsa-miR-4286 were associated with fewer post-concussive symptoms at the 3-week follow-up. Overall, our findings supported our hypothesis that salivary miRNAs could differentiate concussed adolescents from controls and relate to short-term symptom outcomes.

Regarding hsa-miR-4286, our findings indicate that it was not only a marker of acute injury, differentiating concussed adolescents from controls, but may also reflect early adaptive biological responses that support recovery rather than merely signaling injury severity. Elevated levels shortly after injury were associated with fewer post-concussive symptoms weeks later, indicating that early engagement of hsa-miR-4286-related pathways may support recovery. Although this miRNA has not previously been studied in the context of TBI, prior work indicates that hsa-miR-4286 can attenuate stress- and inflammation-related responses,²⁸ consistent with a model in which early regulatory engagement may support symptom resolution. Importantly, this pattern contrasts with biomarkers linked to prolonged or dysregulated inflammation, which are often associated with poorer outcomes. Together, these findings raise the possibility that hsa-miR-4286 differentiates recovery-supportive biological processes from maladaptive post-injury responses, highlighting its potential relevance for early prognosis following concussion.

Along with hsa-miR-4286, hsa-miR-26a-5p was also elevated in concussed adolescents relative to controls. This miRNA has been implicated in neuroplasticity in animal models, promoting axonal regeneration by suppressing Phosphatase and Tensin Homolog (PTEN), a negative regulator of neuronal growth, and suggesting a potential role in supporting neural repair.²⁹ Administration of mesenchymal stem cell–derived exosomes enriched with miR-26a-5p has also been shown to reduce neuronal injury, modulate microglial activation, and attenuate inflammatory responses following brain injury in animal models.³⁰ To the best of our knowledge, this is the first study to identify abnormal levels of hsa-miR-26a-5p in concussion; we speculate that its increased expression may reflect engagement of repair and neuroplasticity mechanisms in adolescents following injury. Notably, however, hsa-miR-26a-5p levels were not associated with symptom severity at 3 weeks, suggesting that its role may be more closely tied to underlying neurobiological recovery processes rather than short-term clinical outcomes.

While hsa-miR-16-5p was selected in our feature selection model and showed a trend toward higher expression in concussed adolescents, this did not reach statistical significance, potentially due to limited power from our modest sample size. This miRNA has been linked to inflammation, apoptosis, and stress-response pathways, and prior studies have reported dysregulation in TBI and neurodegenerative conditions.^10,31,32 Although we cannot draw definitive conclusions, the trend observed here may reflect a subtle neuroimmune response following concussion.

Notably, our findings identify miRNAs that differ from those reported in prior studies,^6,9–13 which have largely examined broader age ranges. This may reflect our developmental focus, as adolescence is characterized by neurodevelopment and heightened plasticity, and age-heterogeneous samples may obscure recovery-relevant miRNA patterns. Future studies should use developmentally stratified, longitudinal designs to clarify the prognostic relevance of miRNA dynamics following concussion.

Despite the potential of miRNAs in adolescent concussion, this study has several limitations. The sample was modest (58 concussed adolescents), limiting generalizability and reducing power to detect smaller effects. Our feature selection and statistical models did not account for potential non-linear relationships. The cross-sectional design, with saliva collected within 10 days of injury, prevented temporal sequencing, which is critical given that some models suggest expression patterns change over days to weeks post injury.⁶ Additionally, salivary miRNA measurements may be influenced by local oral factors (e.g., circadian variation), and the low abundance and generally low concentration of miRNAs in biofluids can present challenges for reliable measurement, potentially contributing to variability in observed levels.³³ Finally, potential confounders such as activity level and stress were also not fully controlled. Future studies with larger samples should employ longitudinal sampling, control for confounding and local oral factors, and explore nonlinear relationships to better characterize miRNA dynamics and their prognostic utility in concussion.

Conclusion

The findings indicated that three salivary miRNAs (hsa-miR-26a-5p, hsa-miR-4286, hsa-miR-16-5p) demonstrated promise as clinically feasible biomarkers for identifying concussion in adolescents. Among these, hsa-miR-26a-5p and hsa-miR-4286 demonstrated significant elevations in concussed adolescents, with hsa-miR-4286 also showing potential for predicting symptom burden. Importantly, salivary miRNAs are easily obtainable, repeatable, and more suitable for adolescents than methods requiring plasma or serum samples, which may support early detection and longitudinal tracking of concussion recovery. The observed miRNA alterations may reflect injury-induced changes in neuroinflammatory and repair pathways, but larger, longitudinal studies are needed to validate these candidates and establish their sensitivity and specificity in this population.

Transparency, Rigor, and Reproducibility Summary

This study is part of the longitudinal Investigating Concussion in Adolescents at Risk for Emotional Dysregulation (iCARE) study. The analysis plan for this work was not preregistered, but the analysis plan was formulated before beginning the collection of saliva data. In total, 197 participants (141 concussed and 56 healthy controls) were recruited in the study. By the time the saliva collection was included in the study, 60 concussions and 39 HC had saliva samples collected. Extracted metrics related to miRNA may be made available from the corresponding author (A.V.) and ethics board approval.

Authors’ Contributions

J.P.L.S.: conceptualization, methodology, formal analysis, writing—original draft, writing—review and editing. L.K.: Writing—original draft. B.H., S.B., R.W.H., M.W.C., and C.L.H.: writing—review & editing. Anthony P. Kontos & Amelia Versace: conceptualization, Methodology, writing—review and editing, supervision, and funding acquisition.

Supplemental Material

sj-docx-1-ntr-10.1177_2689288X261454326 — Supplemental material for Salivary MicroRNAs as Biomarkers for Identification and Prognosis in Adolescents Following Concussion

Supplemental material, sj-docx-1-ntr-10.1177_2689288X261454326 for Salivary MicroRNAs as Biomarkers for Identification and Prognosis in Adolescents Following Concussion by João Paulo Lima Santos, Lochan Karthikeyan, Blair Harvie, Sayani Bhattacharjee, Robert W. Hickey, Michael W. Collins, Cyndi L. Holland, Anthony P. Kontos, and Amelia Versace

Footnotes

Acknowledgments

The authors thank the Health Sciences Sequencing Core at UPMC Children’s Hospital of Pittsburgh (RRID:SCR_023116), the UPMC Hillman Cancer Center Cytometry Facility (RRID:SCR_025361), and the National Institutes of Health (P30CA047904) for services and instruments related to the miRNA analyses used in this project. These services and instruments were graciously supported, in part, by the University of Pittsburgh, the Office of the Senior Vice Chancellor for Health Sciences, the Department of Pediatrics, the Institute for Precision Medicine, and the Richard K Mellon Foundation for Pediatric Research.

Author Disclosure Statement

A.P.K. and M.W.C. receive book royalties from APA Books, and funding for their research through the University of Pittsburgh from the Centers for Disease Control and Prevention, Chuck Noll Foundation for Brain Injury Research, Department of Defense (CDMRP, USAMRAA, USUHS), National Football League, National Institutes of Health (NICHD, NIMH, NINDS), and private donors. Other authors declare no conflict of interest.

Funding Information

This work was supported by the National Institute of Mental Health grant R01MH114881 (PIs: Versace, Kontos) and by the Chuck Noll Foundation (PI: Versace). These funding agencies were not involved in the design, analysis, and interpretation of the data, or the preparation, review, or approval of the article.

Abbreviations used

References

Bryan

, Rowhani-Rahbar

, Comstock

, et al.; Seattle Sports Concussion Research Collaborative. Sports-and recreation-related concussions in US youth. Pediatrics, 2016; 138(1):e20154635.

McCrory

, Meeuwisse

, Dvorak

, et al. 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):838–847.

Halstead

, Walter

, COUNCIL ON SPORTS MEDICINE AND FITNESS. Sport-related concussion in children and adolescents. Pediatrics, 2010; 126(3):597–615.

Hicks

, Onks

, Kim

, et al. Diagnosing mild traumatic brain injury using saliva RNA compared to cognitive and balance testing. Clin Transl Med, 2020; 10(6):e197.

Veliz

, McCabe

, Eckner

, et al. Trends in the prevalence of concussion reported by US adolescents, 2016-2020. JAMA, 2021; 325(17):1789–1791.

Vaughn

, Winston

, Levin

, et al. Developing biomarkers of mild traumatic brain injury: Promise and progress of CNS-derived exosomes. Front Neurol, 2021; 12:698206.

Qin

, Li

, Lv

, et al. Expression profile of plasma microRNAs and their roles in diagnosis of mild to severe traumatic brain injury. PLoS One, 2018; 13(9):e0204051.

, Li

. miRNAs in synapse development and synaptic plasticity. Curr Opin Neurobiol, 2017; 45:24–31.

Johnson

, Loeffert

, Stokes

, et al. Association of salivary microRNA changes with prolonged concussion symptoms. JAMA Pediatr, 2018; 172(1):65–73.

10.

Bhomia

, Balakathiresan

, Wang

, et al. A panel of serum MiRNA biomarkers for the diagnosis of severe to mild traumatic brain injury in humans. Sci Rep, 2016; 6(1):28148.

11.

Hicks

, Onks

, Kim

, et al. Refinement of saliva microRNA biomarkers for sports-related concussion. J Sport Health Sci, 2023; 12(3):369–378.

12.

, Sullivan

, Zhu

, et al. Putting the “mi” in omics: Discovering miRNA biomarkers for pediatric precision care. Pediatr Res, 2023; 93(2):316–323.

13.

LaRocca

, Barns

, Hicks

, et al. Comparison of serum and saliva miRNAs for identification and characterization of mTBI in adult mixed martial arts fighters. PLoS One, 2019; 14(1):e0207785.

14.

Lima Santos

, Jia-Richards

, Kontos

, et al. Emotional regulation and adolescent concussion: Overview and role of neuroimaging. Int J Environ Res Public Health, 2023; 20(13):6274.

15.

Ledoux

A-A

, Webster

, Clarke

, et al. Risk of mental health problems in children and youths following concussion. JAMA Netw Open, 2022; 5(3):e221235.

16.

Lima Santos

, Kontos

, Mailliard

, et al. White matter abnormalities associated with prolonged recovery in adolescents following concussion. Front Neurol, 2021; 12:681467.

17.

Lima Santos

, Zynda

, Perry

, et al. Effects of screen time use on psychological symptoms in adolescents following concussion. J Neurotrauma, 2026; 43(5–6):501–506.

18.

Gomes

, Eagle

, Mehmel

, et al. Impact of sex and pubertal development on anxiety in adolescents after concussion. J Neurotrauma, 2024; 41(21–22):2385–2394; doi: 10.1089/neu.2023.0132

19.

Lima Santos

, Kontos

, Holland

, et al. The role of sleep quality on white matter integrity and concussion symptom severity in adolescents. Neuroimage Clin, 2022; 35:103130; doi: 10.1016/j.nicl.2022.103130

20.

Lima Santos

, Kontos

, Holland

, et al. The role of puberty and sex on brain structure in adolescents with anxiety following concussion. Biol Psychiatry Cogn Neurosci Neuroimaging, 2024; 9(3):285–297; doi: 10.1016/j.bpsc.2022.09.013

21.

Patricios

, Schneider

, Dvorak

, et al. Consensus statement on concussion in sport: The 6th international conference on concussion in sport–Amsterdam, October 2022. Br J Sports Med, 2023; 57(11):695–711; doi: 10.1136/bjsports-2023-106898

22.

Lovell

, Iverson

, Collins

, et al. Measurement of symptoms following sports-related concussion: Reliability and normative data for the post-concussion scale. Appl Neuropsychol, 2006; 13(3):166–174; doi: 10.1207/s15324826an1303_4

23.

Crossland

, Albiero

, Sanjurjo‐Rodríguez

, et al. MicroRNA profiling of low concentration extracellular vesicle RNA utilizing NanoString nCounter technology. J Extracell Biol, 2023; 2(1):e72.

24.

Core Team R. R: A language and environment for statistical computing. R Foundation for Statistical Computing: Vienna, Austria; 2017. Available from: https://www.R-projectorg/

25.

Friedman

, Hastie

, Tibshirani

. Regularization paths for generalized linear models via coordinate descent. J Stat Softw, 2010; 33(1):1–22.

26.

Hastie

, Qian

. Glmnet vignette. 2016. Available from: http://www.web.Stanford.edu/∼hastie/Papers/Glmnet_Vignette.pdf [Last accessed: September 20, 2014].

27.

Benjamini

, Hochberg

. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J R Stat Soc B (Methodological), 1995; 57(1):289–300.

28.

, Xue

, Liu

, et al. miR-4286/TGF-β1/Smad3-negative feedback loop ameliorated vascular endothelial cell damage by attenuating apoptosis and inflammatory response. J Cardiovasc Pharmacol, 2020; 75(5):446–454.

29.

Zhang

, Ma

Y-X

, Zeng

Y-Q

, et al. miR-26a promotes axon regeneration in the mammalian central nervous system by suppressing PTEN expression. Acta Biochim Biophys Sin (Shanghai), 2021; 53(6):758–765.

30.

, Hou

, Sang

, et al. Intravenous administration of mesenchymal stem cell-derived exosomes mitigates traumatic brain injury by inhibiting neutrophil extracellular trap formation via miR-26a-5p. Neuroreport, 2025; 36(12):651–668.

31.

Redell

, Moore

, Ward

III , et al. Human traumatic brain injury alters plasma microRNA levels. J Neurotrauma, 2010; 27(12):2147–2156.

32.

Kim

Y-J

, Kim

, Park

, et al. miR-16-5p is upregulated by amyloid β deposition in Alzheimer’s disease models and induces neuronal cell apoptosis through direct targeting and suppression of BCL-2. Exp Gerontol, 2020; 136:110954.

33.

Chilimoniuk

, Erol

, Rödiger

, et al. Challenges and opportunities in processing NanoString nCounter data. Comput Struct Biotechnol J, 2024; 23:1951–1958.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.06 MB