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Related Concept Videos

Traumatic Brain Injury l: Introduction01:28

Traumatic Brain Injury l: Introduction

DefinitionTraumatic brain injury, or TBI, is a disturbance of normal brain function induced by an external mechanical force, such as a direct blow to the head or a penetrating injury. It can affect both brain structure and function, producing a wide range of clinical outcomes. TBI is a heterogeneous condition, meaning its effects may differ based on the type, location, and severity of the injury.Basis of ClassificationTBI is classified based on severity, injury mechanism, or pathophysiology. In...

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A Bioinformatic Study of Genetics Involved in Determining Mild Traumatic Brain Injury Severity and Recovery.

Mahnaz Tajik1,2,3, Michael D Noseworthy1,2,4,5

  • 1School of Biomedical Engineering, McMaster University, 1280 Main St W, Hamilton, ON L8S 4L8, Canada.

Biomedicines
|November 27, 2025
PubMed
Summary

This study identified key genes and microRNAs (miRNAs) as potential biomarkers for mild traumatic brain injury (mTBI). These findings could advance mTBI diagnostics by tracking specific molecular indicators for better patient outcomes.

Keywords:
RNA sequencing analysisbioinformaticsgenomicsmicroRNAmild traumatic brain injury (mTBI)

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Area of Science:

  • Biomolecular research
  • Neuroscience
  • Bioinformatics

Background:

  • Mild traumatic brain injury (mTBI) poses significant challenges in diagnosis and prognosis.
  • Identifying reliable biomarkers is crucial for understanding mTBI pathophysiology and improving patient management.

Purpose of the Study:

  • To identify specific gene and microRNA (miRNA) biomarkers for mild traumatic brain injury (mTBI) using bioinformatics approaches.
  • To investigate the role of these biomarkers in neuronal structure, axonal integrity, and regeneration following mTBI.

Main Methods:

  • In silico analysis of publicly available gene and miRNA databases (Gene, MalaCard).
  • Functional annotation (GO, KEGG), hub gene identification (Cytoscape), protein-protein interaction mapping (DAVID, STRING), and miRNA target prediction (miRSystem, miRWalk2.0, mirDIP).
  • RNA-sequencing analysis of the mTBI dataset GSE123336.

Main Results:

  • Eleven candidate hub genes (e.g., APOE, S100B, GFAP, BDNF) associated with mTBI outcomes were identified.
  • Enrichment analysis linked these genes to neuronal regeneration and synaptic plasticity.
  • Several miRNAs, including hsa-miR-10a-5p, were identified and correlated with mTBI, with two miRNAs showing positive correlation with head impacts.

Conclusions:

  • Bioinformatic analysis highlights specific genes and miRNAs, notably hsa-miR-10a-5p, as potential molecular players in mTBI.
  • These findings may inform the development of novel diagnostic tools for mTBI.
  • Further research is needed to validate these biomarkers in diverse patient cohorts.