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Despite the established genetic contribution to AUD, sex as a biological variable and the interplay with genetic factors in the disorder remain largely unexplored. This study aimed to address the key question as to how genetic variations interact with biological sex to influence the AUD risk.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted genome\u2010wide genotype\u2010by\u2010sex (G\u2009\u00d7\u2009S) interaction analyses using multiancestry datasets from the Million Veteran Program (MVP) and UK Biobank (UKB). In total, 1,039,476 participants were analyzed, comprising 150,429 AUD cases and 889,046 controls. AUD cases were defined using ICD\u20109\/10 codes in the MVP and using ICD\u201010 codes (field ID 41270) along with self\u2010reported history of alcohol addiction (field ID 20406) in the UKB.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      In single\u2010ancestry analyses, we identified two loci in African ancestry samples with lead single\u2010nucleotide polymorphisms (SNPs) rs2183020 (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20091.82\u2009\u00d7\u200910\n                      <jats:sup>\u22128<\/jats:sup>\n                      ) and rs9304803 (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20094.66\u2009\u00d7\u200910\n                      <jats:sup>\u22128<\/jats:sup>\n                      ), and one locus in Admixed American ancestry samples with lead SNP rs9527196 (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20092.83\u2009\u00d7\u200910\n                      <jats:sup>\u22128<\/jats:sup>\n                      ). The cross\u2010ancestry meta\u2010analysis identified one additional locus with lead SNP rs62446539 (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20093.95\u2009\u00d7\u200910\n                      <jats:sup>\u22128<\/jats:sup>\n                      ). The deep learning method predicted that rs9304803 has B\u2010cell type\u2010specific enhancer activity. Rs2183020 and rs9304803 exhibited expression quantitative trait locus (eQTL) effects on multiple genes across various tissues, including the brain. Further experiments in ethanol\u2010exposed human neurons confirmed expression changes in several of these genes. Phenome\u2010wide association analyses revealed significant associations between rs2183020 and weight\/body mass index, and between rs9304803 and prothrombin time (measured as international normalized ratio).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>We believe this is the first genome\u2010wide G\u2009\u00d7\u2009S study of AUD, providing novel insights into the genetic basis of sex differences in AUD and advancing our understanding of its biological underpinnings.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/acer.70173","type":"journal-article","created":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T07:45:05Z","timestamp":1759131905000},"page":"2485-2493","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Genotype\u2010by\u2010sex interaction analyses for alcohol use disorder across biobanks"],"prefix":"10.1111","volume":"49","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7694-6391","authenticated-orcid":false,"given":"Hang","family":"Zhou","sequence":"first","affiliation":[{"name":"Department of Psychiatry Yale School of Medicine  New Haven Connecticut USA"},{"name":"Veterans Affairs Connecticut Healthcare System  West Haven Connecticut USA"},{"name":"Department of Biomedical Informatics and Data Science Yale School of Medicine  New Haven Connecticut USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lu","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Psychiatry Yale School of Medicine  New Haven Connecticut USA"},{"name":"Veterans Affairs Connecticut Healthcare System  West Haven Connecticut USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-0800-380X","authenticated-orcid":false,"given":"Zhongzheng","family":"Mao","sequence":"additional","affiliation":[{"name":"Graduate School of Arts and Sciences Yale University  New Haven Connecticut USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"P. 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Michael","family":"Deans","sequence":"additional","affiliation":[{"name":"Department of Psychiatry Yale School of Medicine  New Haven Connecticut USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8820-2659","authenticated-orcid":false,"given":"Rachel L.","family":"Kember","sequence":"additional","affiliation":[{"name":"Crescenz Veterans Affairs Medical Center  Philadelphia Pennsylvania USA"},{"name":"Department of Psychiatry University of Pennsylvania Perelman School of Medicine  Philadelphia Pennsylvania USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingyu","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics and Data Science Yale School of Medicine  New Haven Connecticut USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yasmin","family":"Zakiniaeiz","sequence":"additional","affiliation":[{"name":"Department of Psychiatry Yale School of Medicine  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