{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T05:01:19Z","timestamp":1790398879292,"version":"4.1.0"},"reference-count":48,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T00:00:00Z","timestamp":1788652800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T00:00:00Z","timestamp":1788652800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Genetic Epidemiology"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Although individual traits related to metabolic dysfunction\u2013associated steatotic liver disease (MASLD) have been investigated through large\u2010scale genome\u2010wide association studies (GWASs), the shared genetic susceptibility across these traits remains unclear. We therefore conducted a multivariate GWAS of key MASLD\u2010related traits to elucidate their common genetic architecture. We applied genomic structural equation modeling to model a latent genetic factor (MASLD\u2010F) underlying genetically correlated MASLD\u2010related traits, leveraging their GWAS\u2010derived genetic correlations. We then performed functional annotations, including fine\u2010mapping, transcriptome\u2010wide association study, and cell\u2010 and tissue\u2010type\u2010specific enrichment analyses, and conducted Mendelian randomization analyses to identify modifiable risk factors. Our multivariate MASLD\u2010F GWAS identified 50 independent variants across 48 genomic loci. Transcriptomic imputation identified several MASLD\u2010F\u2013associated genes, including\n                    <jats:italic>ARNTL, NPC1, BTBD10, VDAC2, TSKU, SFMBT1<\/jats:italic>\n                    , and\n                    <jats:italic>ABHD17C<\/jats:italic>\n                    . We observed significant enrichment of MASLD\u2010F\u2013related genetic signals predominantly in brain tissues, pancreatic islets, and the adrenal gland. Additionally, six modifiable risk factors and four modifiable protective factors for MASLD\u2010F were identified. These findings reveal a complex shared genetic architecture underlying MASLD components, thereby expanding our understanding of disease pathogenesis and providing novel insights for precision medicine and public health interventions.\n                  <\/jats:p>","DOI":"10.1002\/gepi.70055","type":"journal-article","created":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T12:46:05Z","timestamp":1788698765000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Revealing the Shared Genetic Architecture of Metabolic Dysfunction\u2013Associated Steatotic Liver Disease\u2013Related Traits Through Genomic Structural Equation Modeling"],"prefix":"10.1002","volume":"50","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8148-0410","authenticated-orcid":false,"given":"Hao","family":"Dong","sequence":"first","affiliation":[{"name":"Department of Gastroenterology, Tongji Hospital of Tongji Medical College Huazhong University 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