{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T15:05:38Z","timestamp":1773414338740,"version":"3.50.1"},"posted":{"date-parts":[[2025,12,2]]},"group-title":"Genetic and Genomic Medicine","reference-count":88,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T00:00:00Z","timestamp":1764633600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,3,11]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                <jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Sex differences in alcohol use behaviors are well-established: males typically engage in heavier and more frequent drinking and exhibit more externalizing behaviors (e.g., other substance use), while females often transition to dependence more rapidly and present more internalizing psychopathology (e.g., depression). The biological mechanisms underpinning these differences are relatively unknown.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>\n                    In this study, we investigated the sex-differentiated genetic architecture of 11 alcohol use phenotypes pertaining to frequency, quantity and problematic use by leveraging sex-stratified genome-wide association studies (Ns 40,335 to 613,148). Specifically, we compared SNP-based heritability (\n                    <jats:bold>\n                      <jats:italic>\n                        h\n                        <jats:sup>2<\/jats:sup>\n                        <jats:sub>SNP<\/jats:sub>\n                      <\/jats:italic>\n                    <\/jats:bold>\n                    ) estimates, individual genetic locus effects, genetic correlations (\n                    <jats:bold>\n                      <jats:italic>\n                        r\n                        <jats:sub>g<\/jats:sub>\n                      <\/jats:italic>\n                    <\/jats:bold>\n                    ) across alcohol phenotypes and with comorbid traits from independent GWAS, and polygenic score (\n                    <jats:bold>PGS<\/jats:bold>\n                    ) associations with medical outcomes from clinical populations.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>\n                    <jats:italic>\n                      h\n                      <jats:sup>2<\/jats:sup>\n                      <jats:sub>SNP<\/jats:sub>\n                    <\/jats:italic>\n                    was broadly similar between sexes, except for higher estimates in males for\n                    <jats:italic>beer quantity<\/jats:italic>\n                    and\n                    <jats:italic>problematic alcohol use<\/jats:italic>\n                    (\n                    <jats:bold>PAU<\/jats:bold>\n                    ). We identified four sex-differentiated top loci (\n                    <jats:italic>\n                      p\n                      <jats:sub>sex-diff<\/jats:sub>\n                    <\/jats:italic>\n                    &lt; 5 x 10\n                    <jats:sup>-8<\/jats:sup>\n                    ), including a female-specific association in\n                    <jats:italic>IZUMO1<\/jats:italic>\n                    for\n                    <jats:italic>drinking frequency<\/jats:italic>\n                    and\n                    <jats:italic>quantity<\/jats:italic>\n                    , and three male-specific associations in\n                    <jats:italic>ADH1B<\/jats:italic>\n                    ,\n                    <jats:italic>KLB<\/jats:italic>\n                    and\n                    <jats:italic>FTO<\/jats:italic>\n                    for\n                    <jats:italic>beer quantity<\/jats:italic>\n                    and\/or\n                    <jats:italic>PAU<\/jats:italic>\n                    . Between-sex genetic correlations ranged from 0.68\u00b10.07 to 0.89\u00b10.04, these estimates were lowest for quantity measures and varied by beverage type, indicating partially distinct polygenic architecture. In males, we identified stronger positive genetic correlations with several externalizing traits (e.g., general addiction) compared to females. In females, we identified a specific positive genetic correlation with a single internalizing trait, self-harm. PGS analyses revealed sex-specific medical associations (e.g., bone\/musculoskeletal conditions in females; hepatic\/respiratory\/infectious sequelae in males) that were obscured in sex-combined analyses; however, sex-specific PGS did not outperform combined-sex PGS for predicting alcohol use disorder diagnosis.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>Sex-aware analyses of alcohol use behaviors can improve our understanding of the genetic etiology of alcohol use and related health outcomes, and future studies should consider cultural variation (e.g., drinking attitudes, social norms) in the relationship between behavior and genetics.<\/jats:p>\n                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