ارزيابي بيان ژن STAB1 و ارتباط آن با خطر قلبي‌عروقي در بيماران ديابت نوع 2با استفاده از زيست شناسي سامانه‌ها و Real-Time PCR

: Diabetes type 2 , , Cardiovascular diseases , Systems biology , STAB1 gene , Real-Time PCR , an‎d WGCNA

eva‎luation of STAB1 Gene Expression an‎d Its Relationship with Cardiovascular Risk in Type 2 Diabetes Patients Using Systems Biology an‎d Real-Time PCR

زيست شناسي سلولي مولكولي و ميكروبيولوژي

Abstract: Introduction: Type 2 diabetes (T2D) is a multifactorial metabolic disorder characterized by insulin resistance an‎d persistent hyperglycaemia. Cardiovascular diseases (CVDs) are the predominant clinical sequelae of T2D an‎d account for a substantial share of mortality an‎d disability in affected individuals. The T2D–CVD nexus reflects perturbations in metabolic an‎d vascular homeostasis—including insulin resistance, dysglycaemia, atherogenic dyslipidaemia, hypertension, endothelial dysfunction, an‎d chronic pro-inflammatory/pro-thrombotic states—that collectively foster atherosclerosis an‎d thrombotic events. Leveraging systems biology, this study profiled transcriptional alterations in peripheral blood to identify can‎didate biomarkers, with a focus on STAB1 (stabilin-1), in individuals with T2D at elevated cardiovascular risk versus healthy controls. Materials an‎d Methods: In a bioinformatics phase, publicly available RNA-seq datasets from T2D an‎d normoglycaemic individuals were downloaded an‎d processed on a Linux platform. Differential gene expression was assessed using DESeq2. A gene co-expression network was reconstructed with WGCNA to identify modules associated with T2D. Key genes were prioritized from the intersection of T2D-associated modules an‎d differentially expressed genes, followed by downstream pathway interrogation via Gene Ontology (GO) enrichment analysis. STAB1 was selec‎ted for experimental validation. In a laboratory phase, STAB1 expression was quantified in whole-blood samples from T2D subjects with cardiovascular risk an‎d from healthy controls using Real-Time PCR. Results: Differential expression analysis identified 2,568 genes significantly altered in T2D relative to controls. WGCNA revealed 15 co-expression modules correlated with T2D; the most strongly associated an‎d significant module was selec‎ted for prioritization. Intersecting this module with the differential expression set yielded 345 shared genes. GO-based pathway enrichment nominated STAB1 as a can‎didate. Experimental validation demonstrated reduced STAB1 expression in peripheral blood from T2D participants compared with healthy individuals. Conclusions: This integrative analysis suggests that STAB1 expression is decreased in T2D patients with elevated cardiovascular risk an‎d may serve as a blood-based biomarker can‎didate. Further validation in larger, well-phenotyped cohorts an‎d mechanistic studies is warranted to establish the diagnostic an‎d prognostic utility of STAB1 in T2D-associated cardiovascular complications. Keywords: Diabetes type 2, Cardiovascular diseases, Systems biology, STAB1 gene, Real-Time PCR, an‎d WGCNA

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