Multi-omics integration to identify the genetic expression and protein signature of dilated and ischemic cardiomyopathy

INTRODUCTION: Heart failure (HF) is a complex clinical syndrome leading to high morbidity. In this study, we aimed to identify the gene expression and protein signature of HF main causes, namely dilated cardiomyopathy (DCM) and ischemic cardiomyopathy (ICM). METHODS: Omics data were accessed through GEO repository for transcriptomic and PRIDE repository for proteomic datasets. Sets of differentially expressed genes and proteins comprising DCM (DiSig) and ICM (IsSig) signatures were analyzed by a multilayered bioinformatics approach. Enrichment analysis via the Gene Ontology was performed through the Metascape platform to explore biological pathways. Protein-protein interaction networks were analyzed via STRING db and Network Analyst. RESULTS: Intersection of transcriptomic and proteomic analysis showed 10 differentially expressed genes/proteins in DiSig (AEBP1, CA3, HBA2, HBB, HSPA2, MYH6, SERPINA3, SOD3, THBS4, UCHL1) and 15 differentially expressed genes/proteins in IsSig (AEBP1, APOA1, BGN, CA3, CFH, COL14A1, HBA2, HBB, HSPA2, LTBP2, LUM, MFAP4, SOD3, THBS4, UCHL1). Common and distinct biological pathways between DiSig and IsSig were retrieved, allowing for their molecular characterization. Extracellular matrix organization, cellular response to stress and transforming growth factor-beta were common between two subphenotypes. Muscle tissue development was dysregulated solely in DiSig, while immune cells activation and migration in IsSig. DISCUSSION: Our bioinformatics approach sheds light on the molecular background of HF etiopathology showing molecular similarities as well as distinct expression differences between DCM and ICM. DiSig and IsSig encompass an array of “cross-validated” genes at both transcriptomic and proteomic level, which can serve as novel pharmacological targets and possible diagnostic biomarkers.