{
  "abstract": "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 ~8% 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=8.0x10-7) over linear-only PGS and highlights biologically plausible hypotheses, such as pleiotropic GxS effects of GCKR (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.",
  "abstract_shown": true,
  "affiliations": [
    "UCLA: University of California Los Angeles"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Y. Tanigawa"
    },
    {
      "name": "M. Kellis"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/bzdmwvssyer2g.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.14.751452",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.09.14.751452v1.full",
  "id": "bzdmwvssyer2g",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.09.14.751452v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "genetics"
    ],
    [
      "openalex",
      "1311|Genetic Associations and Epidemiology"
    ]
  ],
  "openalex": "W7213497896",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.09.14.751452v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-14",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/bzdmwvssyer2g.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:22:55Z",
      "native_id": "10.64898/2026.09.14.751452",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.09.14.751452v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:genetics",
      "subfield": "genetics-genomics"
    }
  ],
  "title": "GeneSIS: enhancing transferability of polygenic scores with variant-level gene-by-sex interaction effects",
  "title_text": "GeneSIS: enhancing transferability of polygenic scores with variant-level gene-by-sex interaction effects",
  "type": "preprint",
  "updated_at": "2026-10-30T12:22:55Z",
  "url": "https://research.draconitic.com/paper/bzdmwvssyer2g",
  "venue": "bioRxiv",
  "versions": []
}