Biochemistry and Biophysics Reports (Mar 2025)

Screening of biomarkers for diagnosing chronic kidney disease and heart failure with preserved ejection fraction through bioinformatics analysis

  • Can Hou,
  • Jiayi Xu,
  • Min Zhou,
  • Junyu Huo,
  • Xiaofei Wang,
  • Wanying Jiang,
  • Tong Su,
  • Hui Wang,
  • Fang Jia

Journal volume & issue
Vol. 41
p. 101911

Abstract

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Background: Previous research has established that chronic kidney disease (CKD) and heart failure with preserved ejection fraction (HFpEF) often coexist. Although we have a preliminary understanding of the potential correlation between HFpEF and CKD, the underlying pathophysiological mechanisms remain unclear. This study aimed to elucidate the molecular mechanisms associated with CKD and HFpEF through bioinformatics analysis. Methods: Datasets for HFpEF and CKD were obtained from the Gene Expression Omnibus (GEO) database. The R software package “limma” was employed to conduct differential expression analysis. Functional annotation was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). We conducted weighted gene co-expression network analysis (WGCNA), correlation analysis with autophagy, ferroptosis, and immune-related processes, as well as transcriptional regulation analysis, immune infiltration analysis, and diagnostic performance evaluation. Finally, the diagnostic potential of the identified hub genes for CKD and HFpEF was assessed using ROC curve analysis (GSE37171). Results: Differential expression analysis revealed 58 overlapping genes, comprised of 40 up-regulated and 18 down-regulated genes. Both GO and KEGG analyses indicated enriched pathways relevant to both disorders. WGCNA identified 4086 genes associated with CKD. Further comparison with differentially expressed genes (DEGs) identified three hub genes (KLF4, SCD, and SEL1L3) that were linked to autophagy, ferroptosis, and immune processes in both conditions. Additionally, a miRNA-mRNA regulatory network involving 376 miRNAs and 12 transcription factors (TFs) was constructed. ROC curve analysis was performed to evaluate the diagnostic utility of the hub genes for CKD and HFpEF. Conclusion: This study elucidated shared pathogenic mechanisms and identified diagnostic markers common to both HFpEF and CKD. The identified hub genes show promise as potential tools for early diagnosis and treatment strategies for these conditions.

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