Integrated transcriptomic and Mendelian randomization analysis identifies novel biomarkers for type 2 diabetes-associated cardiac dysfunction: cynaropicrin as a candidate intervention.

Abstract

The objective of this study is to identify T2DM-associated biomarkers linked to diabetic cardiac dysfunction-related transcriptomic signatures through integrated transcriptomic and Mendelian randomization analysis and evaluate cynaropicrin as a candidate cardiometabolic intervention. Transcriptomic datasets from the GEO database related to diabetic cardiac dysfunction, heart failure, and cardiomyopathy-associated phenotypes were processed for differential expression analysis and WGCNA, with consideration of disease-definition and tissue-source heterogeneity. A two-sample Mendelian randomization analysis was used to evaluate genetically predicted associations between candidate gene expression and T2DM risk. External validation assessed diagnostic performance via ROC analysis. Multi-database screening and molecular docking identified candidate compounds. Streptozotocin-induced diabetic rats were treated with cynaropicrin for 8 weeks, with comprehensive cardiac and metabolic assessment. Analysis identified 30 candidate genes with functional enrichment in proteostasis and metabolism. Mendelian randomization prioritized three T2DM-associated genetically supported genes: PPIP5K2, RBM23, and IGF2BP2. Cynaropicrin significantly improved cardiac function, reduced fibrosis, and enhanced glycemic control in diabetic rats while suppressing pro-fibrotic signaling. PPIP5K2, RBM23, and IGF2BP2 represent T2DM-associated genetically supported biomarkers dysregulated in diabetic cardiac dysfunction-related datasets with diagnostic potential. Cynaropicrin demonstrates candidate cardioprotective and metabolic benefits in diabetic rats; however, its direct molecular targets and mechanism of action require further validation.