Deciphering transcriptomic signatures in myotonic dystrophy: a bioinformatics casecontrol study

Myotonic dystrophy (DM), characterized by its intricate multi-system involvement anddiverse subtypes, poses significant challenges in therapeutic strategies and interdisciplinary research.Among the pivotal genes associated with myotonia dystrophy, the MEF۲ gene assumes a central role[۱]. This study employs bioinformatics analysis to explore a microarray dataset (GSE۱۳۶۰۸; AffymetrixHuman Genome U۱۳۳ Plus ۲.۰ Array) sourced from the NCBI's GEO database [۲]. Focusing on skeletalmuscle biopsies from DM۱ (۱۰ samples) and DM۲ patients (۲۰ samples), the analysis compares theseprofiles with those of normal individuals (n = ۶). Transcriptome profiling serves as a pivotal tool indeciphering the molecular intricacies underlying neuromuscular disorders, offering insights into theregulatory mechanisms that underlie the complexities of myotonic dystrophy.The analysis pipeline involved loading the data using GEOquery, quality control, log۲ transformation,and generating descriptive plots (e.g., box-and-whisker plots, expression value distribution plots, andmean-variance trends) using R programming [۳]. Notably, our focus centered on the dysregulation ofMEF۲ and MEF۲-related genes. Out of ۳۶ samples, seven genes displayed significant (adj.P.val < ۰.۰۱and |log۲ FC| > ۱) dysregulation including, COL۴A۳, nebulin, MTUS۱, COPE, TTN, AMPD۱, andGRAPL, proposing as significant biomarkers. In the context of myotonic dystrophy, our analysis revealsdistinct expression patterns, illustrated through box-and-whisker plots showcasing variability in geneexpression across the case and control conditions. The GeneCards, Reactome and KEGG pathwaydatabases showed that these genes exert regulatory control over various crucial biological processesand pathways, including Tibial muscular dystrophy, Metabolic pathways, and ECM-receptorinteraction, extracellular matrix organization, collagen formation, signal transduction, striated musclecontraction pathway, and collagen biosynthesis. Our study not only contributes valuable insights intothe molecular signatures associated with myotonic dystrophy but also suggests potential therapeuticinterventions targeting these dysregulated pathways.

کلیدواژه ها:

Bioinformatics analysis ، Microarray ، Myotonic dystrophy ، Transcriptome profiling