{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T19:00:24Z","timestamp":1790017224728,"version":"4.0.1"},"posted":{"date-parts":[[2026,9,17]]},"group-title":"Genetics","reference-count":89,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T00:00:00Z","timestamp":1789603200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,9,17]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>\n                  Advancing precision medicine requires accurate prediction of disease liability across populations and contexts. A major challenge is the limited transferability of polygenic scores (PGS) across genetic ancestry groups. We present GeneSIS (GENE and Sex Interaction Score), a supervised statistical learning framework for jointly modeling additive and context-dependent genetic effects at single-variant resolution directly from individual-level data. We analyze 406,659 individuals, including admixed individuals, in the UK Biobank and 1.3 million variants to develop predictive models for 99 complex traits. We report that \u223c8% of selected variables capture gene-by-sex (GxS) effects, validated by sex-stratified analyses. Modeling GxS effects improves prediction across 32 traits in non-European individuals. For predicting hip circumference in Africans, GeneSIS achieves a 3.7-fold improvement (p=8.0\u00d710-7) over linear-only PGS and highlights biologically plausible hypotheses, such as pleiotropic GxS effects of\n                  <jats:italic>GCKR<\/jats:italic>\n                  (rs1260326) on anthropometry and menopause, as well as GxS pathway enrichments for interleukin-4 regulation. Overall, our results highlight the benefits of integrating context-dependent effects in human genetics studies.\n                <\/jats:p>","DOI":"10.64898\/2026.09.14.751452","type":"posted-content","created":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T20:40:15Z","timestamp":1789677615000},"source":"Crossref","is-referenced-by-count":0,"title":["GeneSIS: enhancing transferability of polygenic scores with variant-level gene-by-sex interaction effects"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9759-157X","authenticated-orcid":false,"given":"Yosuke","family":"Tanigawa","sequence":"first","affiliation":[{"name":"Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"name":"Broad Institute of MIT and Harvard, Cambridge, MA, USA"},{"name":"Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7113-9630","authenticated-orcid":false,"given":"Manolis","family":"Kellis","sequence":"additional","affiliation":[{"name":"Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"name":"Broad Institute of MIT and Harvard, Cambridge, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","reference":[{"key":"2026092111051177000_2026.09.14.751452v1.1","doi-asserted-by":"publisher","DOI":"10.1038\/nrg.2016.27"},{"key":"2026092111051177000_2026.09.14.751452v1.2","doi-asserted-by":"publisher","DOI":"10.1186\/s13073-020-00742-5"},{"key":"2026092111051177000_2026.09.14.751452v1.3","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-03243-6"},{"key":"2026092111051177000_2026.09.14.751452v1.4","doi-asserted-by":"publisher","DOI":"10.1161\/CIR.0000000000001077"},{"key":"2026092111051177000_2026.09.14.751452v1.5","doi-asserted-by":"publisher","DOI":"10.1038\/s41588-019-0379-x"},{"key":"2026092111051177000_2026.09.14.751452v1.6","doi-asserted-by":"publisher","DOI":"10.1038\/s41588-022-01095-y"},{"key":"2026092111051177000_2026.09.14.751452v1.7","doi-asserted-by":"publisher","DOI":"10.1038\/s41576-023-00637-2"},{"key":"2026092111051177000_2026.09.14.751452v1.8","doi-asserted-by":"publisher","DOI":"10.1038\/s41588-024-01711-z"},{"key":"2026092111051177000_2026.09.14.751452v1.9","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajhg.2023.09.013"},{"key":"2026092111051177000_2026.09.14.751452v1.10","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajhg.2022.04.015"},{"key":"2026092111051177000_2026.09.14.751452v1.11","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-022-02697-9"},{"key":"2026092111051177000_2026.09.14.751452v1.12","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-biodatasci-102022-120818"},{"key":"2026092111051177000_2026.09.14.751452v1.13","doi-asserted-by":"publisher","DOI":"10.1038\/s41588-024-01731-9"},{"key":"2026092111051177000_2026.09.14.751452v1.14","doi-asserted-by":"publisher","DOI":"10.1101\/2022.07.21.501001"},{"key":"2026092111051177000_2026.09.14.751452v1.15","doi-asserted-by":"publisher","DOI":"10.1126\/science.abn8455"},{"key":"2026092111051177000_2026.09.14.751452v1.16","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-022-31625-5"},{"key":"2026092111051177000_2026.09.14.751452v1.17","doi-asserted-by":"publisher","DOI":"10.1038\/s41588-021-00912-0"},{"key":"2026092111051177000_2026.09.14.751452v1.18","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1011221"},{"key":"2026092111051177000_2026.09.14.751452v1.19","doi-asserted-by":"publisher","DOI":"10.7554\/eLife.48376"},{"key":"2026092111051177000_2026.09.14.751452v1.20","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajhg.2022.05.014"},{"key":"2026092111051177000_2026.09.14.751452v1.21","doi-asserted-by":"publisher","DOI":"10.1101\/2024.03.29.24305093"},{"key":"2026092111051177000_2026.09.14.751452v1.22","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-020-0751-5"},{"key":"2026092111051177000_2026.09.14.751452v1.23","doi-asserted-by":"publisher","DOI":"10.1038\/s41431-020-00712-w"},{"key":"2026092111051177000_2026.09.14.751452v1.24","doi-asserted-by":"publisher","DOI":"10.1016\/j.xgen.2023.100297"},{"key":"2026092111051177000_2026.09.14.751452v1.25","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-024-02858-2"},{"key":"2026092111051177000_2026.09.14.751452v1.26","doi-asserted-by":"publisher","DOI":"10.1038\/s41588-024-01776-w"},{"key":"2026092111051177000_2026.09.14.751452v1.27","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajhg.2025.01.014"},{"key":"2026092111051177000_2026.09.14.751452v1.28","doi-asserted-by":"publisher","DOI":"10.1038\/ng.685"},{"key":"2026092111051177000_2026.09.14.751452v1.29","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1003500"},{"key":"2026092111051177000_2026.09.14.751452v1.30","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1000360"},{"key":"2026092111051177000_2026.09.14.751452v1.31","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1008682"},{"key":"2026092111051177000_2026.09.14.751452v1.32","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-023-06957-x"},{"key":"2026092111051177000_2026.09.14.751452v1.33","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-024-48654-x"},{"key":"2026092111051177000_2026.09.14.751452v1.34","doi-asserted-by":"publisher","DOI":"10.1016\/j.xgen.2021.100086"},{"key":"2026092111051177000_2026.09.14.751452v1.35","doi-asserted-by":"publisher","DOI":"10.1038\/s41588-024-01792-w"},{"key":"2026092111051177000_2026.09.14.751452v1.36","doi-asserted-by":"publisher","DOI":"10.1101\/2024.06.05.597631"},{"key":"2026092111051177000_2026.09.14.751452v1.37","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-018-0579-z"},{"key":"2026092111051177000_2026.09.14.751452v1.38","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1009141"},{"key":"2026092111051177000_2026.09.14.751452v1.39","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btab452"},{"key":"2026092111051177000_2026.09.14.751452v1.40","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2005.00503.x"},{"key":"2026092111051177000_2026.09.14.751452v1.41","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1004754"},{"key":"2026092111051177000_2026.09.14.751452v1.42","doi-asserted-by":"publisher","DOI":"10.1038\/nbt.1630"},{"key":"2026092111051177000_2026.09.14.751452v1.43","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1010378"},{"key":"2026092111051177000_2026.09.14.751452v1.44","doi-asserted-by":"publisher","DOI":"10.1101\/2024.05.29.24307783"},{"key":"2026092111051177000_2026.09.14.751452v1.45","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1010105"},{"key":"2026092111051177000_2026.09.14.751452v1.46","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajhg.2021.11.008"},{"key":"2026092111051177000_2026.09.14.751452v1.47","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-023-06079-4"},{"key":"2026092111051177000_2026.09.14.751452v1.48","doi-asserted-by":"publisher","DOI":"10.1038\/nn.4202"},{"key":"2026092111051177000_2026.09.14.751452v1.49","doi-asserted-by":"publisher","DOI":"10.1038\/ng.521"},{"key":"2026092111051177000_2026.09.14.751452v1.50","doi-asserted-by":"publisher","DOI":"10.1093\/hmg\/ddp357"},{"key":"2026092111051177000_2026.09.14.751452v1.51","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bty999"},{"key":"2026092111051177000_2026.09.14.751452v1.52","doi-asserted-by":"publisher","DOI":"10.1038\/s41588-020-00757-z"},{"key":"2026092111051177000_2026.09.14.751452v1.53","doi-asserted-by":"publisher","DOI":"10.1038\/s41588-021-00892-1"},{"key":"2026092111051177000_2026.09.14.751452v1.54","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkaa840"},{"key":"2026092111051177000_2026.09.14.751452v1.55","doi-asserted-by":"publisher","DOI":"10.1194\/jlr.M041392"},{"key":"2026092111051177000_2026.09.14.751452v1.56","doi-asserted-by":"publisher","DOI":"10.1038\/s41588-022-01036-9"},{"key":"2026092111051177000_2026.09.14.751452v1.57","doi-asserted-by":"publisher","DOI":"10.1038\/s41588-022-01054-7"},{"key":"2026092111051177000_2026.09.14.751452v1.58","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbag164"},{"key":"2026092111051177000_2026.09.14.751452v1.59","doi-asserted-by":"publisher","DOI":"10.64898\/2026.08.26.746823"},{"key":"2026092111051177000_2026.09.14.751452v1.60","doi-asserted-by":"publisher","DOI":"10.3389\/fgene.2022.1076440"},{"key":"2026092111051177000_2026.09.14.751452v1.61","doi-asserted-by":"publisher","DOI":"10.1002\/gepi.22495"},{"key":"2026092111051177000_2026.09.14.751452v1.62","doi-asserted-by":"crossref","unstructured":"Stasinopoulos MD , Kneib T , Klein N , Mayr A , Heller GZ . Generalized additive models for location, scale and shape. Cambridge, England: Cambridge University Press; 2024.","DOI":"10.1017\/9781009410076"},{"key":"2026092111051177000_2026.09.14.751452v1.63","doi-asserted-by":"publisher","DOI":"10.7554\/eLife.74970"},{"key":"2026092111051177000_2026.09.14.751452v1.64","doi-asserted-by":"publisher","DOI":"10.1038\/s41588-024-01782-y"},{"key":"2026092111051177000_2026.09.14.751452v1.65","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2011.01004.x"},{"key":"2026092111051177000_2026.09.14.751452v1.66","doi-asserted-by":"publisher","DOI":"10.1093\/biostatistics\/kxaa038"},{"key":"2026092111051177000_2026.09.14.751452v1.67","doi-asserted-by":"publisher","DOI":"10.1214\/21-aoas1575"},{"key":"2026092111051177000_2026.09.14.751452v1.68","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btab095"},{"key":"2026092111051177000_2026.09.14.751452v1.69","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1001779"},{"key":"2026092111051177000_2026.09.14.751452v1.70","doi-asserted-by":"publisher","DOI":"10.1126\/scitranslmed.adf4428"},{"key":"2026092111051177000_2026.09.14.751452v1.71","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkz966"},{"key":"2026092111051177000_2026.09.14.751452v1.72","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-016-0974-4"},{"key":"2026092111051177000_2026.09.14.751452v1.73","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-020-2308-7"},{"key":"2026092111051177000_2026.09.14.751452v1.74","doi-asserted-by":"publisher","DOI":"10.1038\/ng.998"},{"key":"2026092111051177000_2026.09.14.751452v1.75","doi-asserted-by":"publisher","DOI":"10.1101\/2020.05.28.119669"},{"key":"2026092111051177000_2026.09.14.751452v1.76","doi-asserted-by":"publisher","DOI":"10.1186\/s13742-015-0047-8"},{"key":"2026092111051177000_2026.09.14.751452v1.77","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-019-11953-9"},{"key":"2026092111051177000_2026.09.14.751452v1.78","doi-asserted-by":"publisher","DOI":"10.1038\/s41588-021-00870-7"},{"key":"2026092111051177000_2026.09.14.751452v1.79","doi-asserted-by":"publisher","DOI":"10.1037\/0033-2909.118.1.155"},{"key":"2026092111051177000_2026.09.14.751452v1.80","doi-asserted-by":"publisher","DOI":"10.4324\/9780203774441"},{"key":"2026092111051177000_2026.09.14.751452v1.81","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajhg.2023.01.004"},{"key":"2026092111051177000_2026.09.14.751452v1.82","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btac830"},{"key":"2026092111051177000_2026.09.14.751452v1.83","doi-asserted-by":"publisher","DOI":"10.3233\/978-1-61499-649-1-87"},{"key":"2026092111051177000_2026.09.14.751452v1.84","unstructured":"R Core Team. R: A language and environment for statistical computing. 2019. Available: https:\/\/www.R-project.org\/"},{"key":"2026092111051177000_2026.09.14.751452v1.85","doi-asserted-by":"publisher","DOI":"10.21105\/joss.01686"},{"key":"2026092111051177000_2026.09.14.751452v1.86","doi-asserted-by":"publisher","DOI":"10.5281\/zenodo.1146014"},{"key":"2026092111051177000_2026.09.14.751452v1.87","doi-asserted-by":"crossref","unstructured":"Wickham H. ggplot2: Elegant Graphics for Data Analysis. Springer; 2016. Available: https:\/\/ggplot2.tidyverse.org","DOI":"10.1007\/978-3-319-24277-4_9"},{"key":"2026092111051177000_2026.09.14.751452v1.88","doi-asserted-by":"crossref","unstructured":"Slowikowski K , Schep A , Hughes S , Dang TK , Lukauskas S , Irisson J-O , et al. ggrepel: Automatically position non-overlapping text labels with \u201cggplot2.\u201d 2016. Available: https:\/\/github.com\/slowkow\/ggrepel","DOI":"10.32614\/CRAN.package.ggrepel"},{"key":"2026092111051177000_2026.09.14.751452v1.89","doi-asserted-by":"crossref","unstructured":"Petukhov V , van den Brand T , Biederstedt E. ggrastr: Raster Layers for \u201cggplot2.\u201d 2021. Available: https:\/\/CRAN.R-project.org\/package=ggrastr","DOI":"10.32614\/CRAN.package.ggrastr"}],"container-title":[],"original-title":[],"link":[{"URL":"https:\/\/syndication.highwire.org\/content\/doi\/10.64898\/2026.09.14.751452","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T18:05:24Z","timestamp":1790013924000},"score":1,"resource":{"primary":{"URL":"http:\/\/biorxiv.org\/lookup\/doi\/10.64898\/2026.09.14.751452"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,17]]},"references-count":89,"URL":"https:\/\/doi.org\/10.64898\/2026.09.14.751452","relation":{},"subject":[],"published":{"date-parts":[[2026,9,17]]},"subtype":"preprint"}}