Abnormal genes and pathways that drive muscle contracture from brachial plexus injuries: Towards machine learning approach

SLAS Technol. 2024 Aug;29(4):100166. doi: 10.1016/j.slast.2024.100166. Epub 2024 Jul 20.

Abstract

In order to clarify the pathways closely linked to denervated muscle contracture, this work uses IoMT-enabled healthcare stratergies to examine changes in gene expression patterns inside atrophic muscles following brachial plexus damage. The gene expression Omnibus (GEO) database searching was used to locate the dataset GSE137606, which is connected to brachial plexus injuries. Strict criteria (|logFC|≥2 & adj.p < 0.05) were used to extract differentially expressed genes (DEGs). To identify dysregulated activities and pathways in denervated muscles, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and Gene Set Enrichment Analysis (GSEA) were used. Hub genes were found using Cytoscape software's algorithms, which took into account parameters like as proximity, degree, and MNC. Their expression, enriched pathways, and correlations were then examined. The results showed that 316 DEGs were predominantly concentrated in muscle-related processes such as tissue formation and contraction pathways. Of these, 297 DEGs were highly expressed in denervated muscles, whereas 19 DEGs were weakly expressed. GSEA showed improvements in the contraction of striated and skeletal muscles. In addition, it was shown that in denervated muscles, Myod1, Myog, Myh7, Myl2, Tnnt2, and Tnni1 were elevated hub genes with enriched pathways such adrenergic signaling and tight junction. These results point to possible therapeutic targets for denervated muscular contracture, including Myod1, Myog, Myh7, Myl2, Tnnt2, and Tnni1. This highlights treatment options for this ailment which enhances the mental state of patient.

Keywords: Brachial plexus injuries; Cytoscape; GEO; GSEA; Muscle contracture.

MeSH terms

  • Brachial Plexus* / injuries
  • Computational Biology / methods
  • Contracture* / genetics
  • Contracture* / physiopathology
  • Gene Expression Profiling
  • Gene Regulatory Networks
  • Humans
  • Machine Learning*
  • Muscle, Skeletal / metabolism
  • Signal Transduction