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We sought to identify genetic modifiers of age at onset (AAO) of AD while probing the influence of sex and\n                      <jats:italic>APOE<\/jats:italic>\n                      among those with diverse ancestry.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>\n                      We performed genome\u2010wide association studies (GWASs) of AAO in two diverse samples followed by meta\u2010analysis, contrasting results with and without adjustment for sex and\n                      <jats:italic>APOE<\/jats:italic>\n                      . Genome\u2010wide significance was set to\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0&lt;\u00a05\u00d710\n                      <jats:sup>\u22128<\/jats:sup>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>\n                      GWASs adjusting for sex,\n                      <jats:italic>APOE<\/jats:italic>\n                      , population structure, and relatedness revealed 17 significant loci including independent associations at AD risk loci and four novel signals.\n                      <jats:italic>APOE<\/jats:italic>\n                      adjustment influenced GWAS effect sizes across the genome while sex adjustment had minimal effect.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>DISCUSSION<\/jats:title>\n                    <jats:p>We identified association signals within a diverse but relatively small sample, replicating loci recently discovered in large European ancestry\u2010only GWASs, and illustrated the power of using a quantitative trait like AAO over a binary diagnosis trait.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Highlights<\/jats:title>\n                    <jats:p>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>Survival analysis approach identified known and novel genetic modifiers of Alzheimer's disease (AD).<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Multi\u2010ancestry analyses revealed independent signals at known AD loci.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Apolipoprotein E adjustment influenced variant effects across the genome.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/alz.70489","type":"journal-article","created":{"date-parts":[[2025,8,30]],"date-time":"2025-08-30T04:58:50Z","timestamp":1756529930000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Multi\u2010ancestry meta\u2010analysis identifies genetic modifiers of age\u2010at\u2010onset of Alzheimer's disease at known and novel loci"],"prefix":"10.1002","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0633-0305","authenticated-orcid":false,"given":"Elizabeth E.","family":"Blue","sequence":"first","affiliation":[{"name":"Department of Medicine, Division of Medical Genetics University of Washington  Seattle 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