Bioinformatics combining machine learning and single-cell sequencing analysis to identify common mechanisms and biomarkers of rheumatoid arthritis and ischemic heart failure.

ABSTRACT: Patients with rheumatoid arthritis (RA) have an increased risk of ischemic heart failure (IHF), but the shared mechanisms are unclear. This study analyzed RNA sequencing data from five RA and IHF datasets to identify common biological mechanisms and significant biomarkers. One hundred and seventy-seven common differentially expressed genes (CDEGs) were identified, with enrichment analysis highlighting pathways related to sarcomere organization, ventricular myocardial tissue morphogenesis, chondrocyte differentiation, prolactin signaling, hematopoietic cell lineage, and protein methyltransferases. Five hub genes (CD2, CD3D, CCL5, IL7R, and SPATA18) were identified through protein-protein interaction (PPI) network analysis and machine learning. Co-expression and immune cell infiltration anal

SUBMITTER: Sun Z 

PROVIDER: S-EPMC11783397 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature