Abstract Background& Aims: Multiple epidemiological studies have suggested an association between Metabolic dysfunction-associated fatty liver disease (MAFLD) and cardiovascular diseases (CVDs). However, the genetic components that are shared between the two remain unclear. Methods: This genome-wide pleiotropic association study integrated comprehensive genome-wide association studies (GWAS) summary data from publicly available sources within European populations. It employed a range of genetic approaches to analyze the shared genetic architectures between MAFLD and six CVDs: atrial fibrillation (AF), coronary artery disease (CAD), venous thromboembolism (VTE), heart failure (HF), peripheral artery disease (PAD), and stroke. Initially, we examined the genetic correlation and overlap between these conditions. Subsequently, Mendelian Randomization (MR) analysis was conducted to investigate potential causal relationships. Finally, we explored horizontal pleiotropy at the levels of single nucleotide polymorphisms (SNPs), genes, and biological pathways to further elucidate the shared genetic mechanisms underlying. Results: We observed significant genetic associations between MAFLD and four CVDs, including CAD, HF, PAD, and VTE. However, we noted extensive genetic overlap in all but MAFLD-AF. MR analysis established causal relationships from MAFLD to both AF and PAD. Regarding horizontal pleiotropy, 49 pleiotropic loci were identified at the SNP level with functional annotations, 13 demonstrating strong evidence of colocalization. At the gene level, 14 unique pleiotropic genes were found , with SAMM50 (located at 22q13.31) being particularly notable. Further pathway enrichment analysis indicated that these genes significantly contribute to the pathway of establishment of protein localization to membrane, highlighting their pivotal role in the pathophysiology of both MAFLD and CVD. Conclusions：In all, our research proved the shared genetic architectures and mechanisms between MAFLD and CVD and elucidated their shared genetic etiology and biological mechanisms.

The authors have declared no competing interest.

Financial support statement This study was supported by the Natural Science Foundation of China Excellent Young Scientists Fund (Overseas) (Grant no. K241141101), Guangdong Basic and Applied Basic Research Foundation for Distinguished Young Scholars (Grant no. 2024B1515020047), Shenzhen Pengcheng Peacock Plan, Shenzhen Basic Research General Projects of Shenzhen Science and Technology Innovation Commission (Grant no. JCYJ20230807093514029) (To Y.F.), Shenzhen University 2035 Program for Excellent Research 8690200000314, the Shenzhen Science and Technology Fund for Distinguished Young Scholars (RCYX20231211090127031) (to W. S.), National Natural Science Foundation of China (Grant no. 82230067, 82272103), the Guangdong Provincial Key Laboratory of Tumor Interventional Diagnosis and Treatment (Grant no. 2021B1212040004), and the Natural Science Foundation of Guangdong Province of China (Grant no. 2022B1515020010) (To M.Z.), Shenzhen Science and Technology Program (Grant No. GJHZ20240218111401002 to J.B.), and Center for Computational Science and Engineering at Southern University of Science and Technology. The funder had no role in the design, implementation, analysis, interpretation of the data, approval of the manuscript, and decision to submit the manuscript for publication.

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The datasets used in this study are publicly available from the following sources: atrial fibrillation data can be accessed at the GWAS Catalog (GCST006414) through https://www.ebi.ac.uk/gwas/studies/GCST006414; coronary artery disease data are available at https://cvd.hugeamp.org/datasets.html; venous thromboembolism data are accessible at https://www.decode.com/summarydata/; heart failure data can be found at the GWAS Catalog (GCST009541) via https://www.ebi.ac.uk/gwas/studies/GCST009541; peripheral artery disease data are provided at https://cvd.hugeamp.org/datasets.html; stroke data can be obtained at https://www.ebi.ac.uk/gwas/studies/GCST90104539; and metabolic dysfunction-associated fatty liver disease data are available at https://www.ebi.ac.uk/gwas/publications/34841290.

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