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

## TL;DR

This study uses genetic and multiomics data to show that atrial fibrillation may have a causal link to gastric cancer, independent of known risk factors.

## Contribution

The study identifies 62 co-associated genes and reveals a novel causal relationship between atrial fibrillation and gastric cancer.

## Key findings

- Atrial fibrillation is negatively associated with gastric cancer risk, independent of common risk factors.
- Key genes are linked to cardiovascular, inflammatory, and tumorigenic pathways in gastric cancer.
- Fibroblast subpopulations associated with key genes correlate with cancer progression and inflammation.

## Abstract

Gastric cancer is a harmful disease, the comorbidity mechanism and causality relationship between this disease and other diseases are worth studying.

Using 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.

The 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.

This 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.