A Bioinformatic Study of Genetics Involved in Determining Mild Traumatic Brain Injury Severity and Recovery
Mahnaz Tajik, Michael D Noseworthy

TL;DR
This bioinformatic study identified key genes and miRNAs associated with mild traumatic brain injury (mTBI) outcomes, providing potential biomarkers for diagnosis and understanding recovery mechanisms.
Contribution
The study introduces a comprehensive in silico approach combining gene, miRNA analysis, and RNA-sequencing to identify novel biomarkers for mTBI.
Findings
Identified 11 hub genes linked to mTBI recovery.
Linked specific miRNAs to mTBI-related gene regulation.
Discovered 2664 differentially expressed miRNAs post-injury.
Abstract
Aim: This in silico study sought to identify specific biomarkers for mild traumatic brain injury (mTBI) through the analysis of publicly available gene and miRNA databases, hypothesizing their influence on neuronal structure, axonal integrity, and regeneration. Methods: This study implemented a three-step process: (1) Data searching for mTBI-related genes in Gene and MalaCard databases and literature review ; (2) Data analysis involved performing functional annotation through GO and KEGG, identifying hub genes using Cytoscape, mapping protein-protein interactions via DAVID and STRING, and predicting miRNA targets using miRSystem, miRWalk2.0, and mirDIP (3) RNA-sequencing analysis applied to the mTBI dataset GSE123336. Results: Eleven candidate hub genes associated with mTBI outcome were identified: APOE, S100B, GFAP, BDNF, AQP4, COMT, MBP, UCHL1, DRD2, ASIC1, and CACNA1A. Enrichment…
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