Integrated Genomic and Transcriptomic Analysis Reveals the Genetic Basis and Causal Association Between Obesity and Atrial Fibrillation

ABSTRACT Background Observational studies have shown that obesity is associated with an increased risk of atrial fibrillation (AF), but the underlying genetic mechanisms and direction of causality remain unclear. This study aims to systematically investigate the genetic associations, direction of causality and key pleiotropic genes linking obesity and AF by integrating large‐scale genome‐wide association study (GWAS) data and employing various genetic methods. Methods This study utilised pooled GWAS data on obesity (FinnGen R12) and AF (a large‐scale GWAS meta‐analysis). First, linkage disequilibrium score regression (LDSC) and high‐definition likelihood inference (HDL) were employed to assess heritability and genetic correlation, while bidirectional Mendelian randomisation (MR) was used to infer the direction of causality. Secondly, multi‐trait analysis of GWAS (MTAG) was applied to the AF GWAS by integrating the obesity dataset to generate an enhanced MTAG‐AF dataset. Independent genetic loci were identified using functional mapping and annotation (FUMA) and GCTA conditional and joint analysis (GCTA‐COJO) and gene‐based association analyses were conducted using multi‐marker analysis of genomic annotation (MAGMA) and GCTA‐fast set‐based association test (GCTA‐fastBAT). Subsequently, tissue‐specific enrichment analysis using LDSC applied to specifically expressed genes (LDSC‐SEG), transcriptome‐wide association studies (TWAS) and summary‐data‐based Mendelian randomisation (SMR) were utilised to investigate the tissue‐specific expression of pleiotropic genes. Finally, the causal relationships between key pleiotropic genes and traits were assessed using bidirectional gene‐trait MR. Results Both LDSC (rg = 0.2285, SE = 0.0257, p = 7.00 × 10 −19 ) and HDL (rg = 0.2885, SE = 0.0418, p = 4.83 × 10 −12 ) analyses confirmed a significant genetic correlation between obesity and AF. Bidirectional MR analysis revealed that obesity had a significant positive causal effect on AF (IVW: 1.160, 95% CI: 1.115–1.208, p = 3.14 × 10 −13 ), while no evidence of reverse causality was found (IVW: OR = 1.004, p = 0.810). A total of 216 overlapping genes from FUMA and GCTA‐COJO and 240 shared pleiotropic genes from gene‐based analyses were identified, with 62 pleiotropic genes further obtained through intersection analysis. These pleiotropic genes were primarily enriched in transcriptional regulation, pathways related to myocardial action potentials and the PI3K/AKT signalling pathway. NFATC2IP, NUCKS1 and PCCB were found to exhibit both tissue‐specific expression and genetic regulatory associations in adipose and cardiac tissues. Genetically predicted higher expression of NFATC2IP, NUCKS1 and PCCB was associated with increased AF risk. Higher NFATC2IP and NUCKS1 expression also increased obesity risk. Reverse MR revealed that obesity upregulated NFATC2IP expression and AF upregulated PCCB expression. Conclusions This study provides genetic evidence supporting a shared genetic basis and a likely unidirectional causal relationship from obesity to AF. NFATC2IP, NUCKS1 and PCCB are identified as key pleiotropic genes, offering new genetic insights and potential therapeutic targets for obesity‐related AF.