Frontiers in Genetics (Feb 2025)

Mendelian randomization and multiomics comprehensively reveal the causal relationship and potential mechanism between atrial fibrillation and gastric cancer

  • Zhao Sicheng,
  • Zhao Sicheng,
  • Zhang Jingcheng,
  • Zhang Jingcheng,
  • Zhang Shuo,
  • Zhang Shuo,
  • Lou Jiaheng,
  • Lou Jiaheng,
  • Cai Yan,
  • Cai Yan,
  • Bai Xing,
  • Bai Xing,
  • Jiang Tao,
  • Jiang Tao,
  • Jiang Tao,
  • Zhang Guangji,
  • Zhang Guangji,
  • Zhang Guangji

DOI
https://doi.org/10.3389/fgene.2025.1446661
Journal volume & issue
Vol. 16

Abstract

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ObjectiveGastric cancer is a harmful disease, the comorbidity mechanism and causality relationship between this disease and other diseases are worth studying.MethodsUsing a two-sample Mendelian Randomization method, this study revealed the potential causal effect of atrial fibrillation (AF) on gastric cancer (GC) risk by constructing a genetic instrument containing 136 AF associated SNPs. Subsequently, analysis identifies 62 AF-GC co-associated genes and constructs a protein-protein interaction network of key genes. High-throughput sequencing data were further used to analyze the association between the two and their impact on the survival outcome of gastric cancer.ResultsThe results showed that AF was negatively associated with gastric cancer, and further analysis revealed that this relationship was independent of GC risk factors such as chronic gastritis, Helicobacter pylori infection, and alcohol consumption. Enrichment analysis reveals associations of key genes with pathways related to cardiovascular disease, inflammatory gastrointestinal diseases, and tumorigenesis. Through single-cell sequencing data analysis, fibroblast subpopulations associated with the key gene set are identified in GC, showing significant correlations with cancer progression and inflammation regulation pathways. Transcription factor analysis and developmental trajectory analysis reveal the potential role of fibroblasts in GC development. Finally, prognosis analysis and gene mutation analysis using TCGA-STAD data indicate an adverse prognosis associated with the key gene set in GC.ConclusionThis study provides new insights into the association between AF and GC and offers novel clues for understanding its impact on the pathogenesis and therapeutic strategies of GC.

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