Screening of CAD-related secretory genes associated with type II diabetes based on comprehensive bioinformatics analysis and machine learning

Abstract

Background

Type II diabetes mellitus (T2DM) is strongly linked with a heightened risk of coronary artery disease (CAD). Exploring biological targets common to T2DM and CAD is essential for CAD intervention strategies.

Methods

RNA transcriptome data from CAD and T2DM patients and single-cell transcriptional data from myocardial tissue of CAD patients were used for bioinformatics analysis. Differential analysis and Weighted Gene Co-expression Network Analysis (WGCNA) were conducted to identify hub genes associated with the CAD Index (CADi) in these cells. We then intersected these genes with differentially expressed genes in the T2DM dataset to validate the key gene FGF7. Additional analyses included immune analysis, drug sensitivity, competing endogenous RNA (ceRNA) networks, and smooth muscle cell -related functional analysis.

Results

An abnormally high proportion of smooth muscle cells was observed in CAD tissues compared to normal cardiomyocytes. The gene FGF7, which encodes the keratinocyte growth factor 7 protein, showed increased expression in both CAD and T2DM and was significantly positively correlated with the CADi (correlation = 0.24, p < 0.05). FGF7 expression was inversely correlated with CD4⁺ and CD8⁺ T-cell immune infiltration and correlated with the cardiovascular drugs. Overexpression of FGF7 in CAD samples enhanced interactions with mononuclear macrophages and influenced the metabolism of alanine, glutamate, nicotinamide, and retinol. We also identified that hsa-miR-15a-5p, hsa-miR-373-3p, hsa-miR-20a-5p, and hsa-miR-372-3p could regulate FGF7 expression.

Conclusion

FGF7 serves as a critical shared biological target for T2DM and CAD, playing a significant role in CAD progression with potential therapeutic implications.