Objective
End-stage renal disease (ESRD) can increase the risk of cardiovascular disease (CV). We aimed to investigate the pathways and mechanisms associated with potential protective genes linked to CV (CVP).
Methods
We conducted a systematic bioinformatics analysis using publicly available datasets from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified in patients with ESRD with and without arrhythmia using stringent statistical criteria. Functional enrichment analyses were performed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways to elucidate the biological roles of these DEGs. Receiver Operating Characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of the identified biomarkers for CV risk prediction.
Results
Our analysis revealed a distinct set of DEGs in ESRD patients with arrhythmia compared to those without arrhythmia. GO and KEGG pathway analyses indicated that these DEGs were involved in key biological processes and pathways relevant to cardiovascular disorders and renal function, including wound healing, platelet activation, and fluid-level regulation. Moreover, this study identified four downregulated genes (ABLIM3, TREML1, VCL, and AVPR1A) and two upregulated genes (BHLHA15 and FZD8), which exhibited significant alterations in expression levels, with some showing robust discriminatory power, as evidenced by high Area Under the Curve (AUC) values in ROC analysis for predicting patients without CV risks.
Conclusion
This study identified a panel of genes (including a miRNA and an unknown gene) in the plasma that may serve as promising biomarkers for predicting arrhythmia risk in ESRD patients. These findings provide a foundation for future validation studies aimed at integrating plasma biomarkers into clinical practice to improve risk stratification and management of CV in patients with ESRD.