Identification of immune feature genes and intercellular profiles in diabetic cardiomyopathy.

backgroundDiabetic cardiomyopathy (DCM) is a multifaceted cardiovascular disorder in which immune dysregulation plays a pivotal role. The immunological molecular mechanisms underlying DCM are poorly understood.

aimTo examine the immunological molecular mechanisms of DCM and construct diagnostic and prognostic models of DCM based on immune feature genes (IFGs).

methodsWeighted gene co-expression network analysis along with machine learning methods were employed to pinpoint IFGs within bulk RNA sequencing (RNA-seq) datasets. Single-sample gene set enrichment analysis (ssGSEA) facilitated the analysis of immune cell infiltration. Diagnostic and prognostic models for these IFGs were developed and assessed in a validation cohort. Gene expression in the DCM cell model was confirmed through real time-quantitative polymerase chain reaction and western blotting techniques. Additionally, single-cell RNA-seq data provided deeper insights into cellular profiles and interactions.

resultsThe overlap between 69 differentially expressed genes in the DCM-associated module and 2483 immune genes yielded 7 differentially expressed immune-related genes. Four IFGs showed good diagnostic and prognostic values in the validation cohort: Proenkephalin (Penk) and retinol binding protein 7 (Rbp7), which were highly expressed, and glucagon receptor and inhibin subunit alpha, which were expressed at low levels in DCM patients (all area under the curves > 0.9). SsGSEA revealed that IFG-related immune cell infiltration primarily involved type 2 T helper cells. High expression of Penk (

conclusionThe present study identified Penk and Rbp7 as potential DCM biomarkers, and aberrant mesenchymal-immune cell phenotype communication may be an important aspect of DCM pathogenesis.