{
  "abstract": "Genome-wide association study (GWAS) summary statistics for training and individual-level cohorts for fine-tuning are essential for constructing predictive polygenic risk score (PRS) models. However, the relatively low representation of admixed populations in both GWAS summary statistics and individual-level datasets hinders the development of PRSs and equitable clinical translation for admixed populations. Prior work indicates that the most informative PRS model for a genetically homogeneous sample varies linearly in an ancestry continuum space. Guided by these observations, we introduce a genetic-distance-assisted PRS combination pipeline for diverse genetic ancestries (DiscoDivas) to interpolate a harmonized PRS for diverse, especially admixed, genetic ancestries. DiscoDivas leverages multiple PRS models fine-tuned within existing samples, which are mostly of single ancestry, and genetic distance. It provides a new approach to generate genetic-ancestry-specific PRSs when a suitably matched individual-level fine-tuning cohort is unavailable or underpowered. DiscoDivas treats genetic ancestry as a continuous variable and does not require shifting across different models when calculating PRSs for different ancestries. We generated PRSs with DiscoDivas and the current conventional method, i.e., fine-tuning multiple GWAS PRSs using the matched or similar genetic-ancestry samples. DiscoDivas generated a harmonized PRS, performing comparable to or better than the conventional approach, with the greatest advantage exhibited in admixed individuals.",
  "abstract_shown": true,
  "affiliations": [
    "Program in Medical and Population, Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA",
    "Program in Medical and Population, Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA",
    "Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA",
    "Program in Medical and Population, Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA; Integrative Research Center for Cerebrovascular and Cardiovascular Diseases, Yonsei University College of Medicine, Seoul, Republic of Korea",
    "Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA",
    "Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA; Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 11,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Yunfeng Ruan",
      "orcid": "0000-0002-3213-8309"
    },
    {
      "affs": [
        0
      ],
      "name": "Rohan Bhukar"
    },
    {
      "affs": [
        1
      ],
      "name": "Aniruddh P. Patel",
      "orcid": "0000-0001-7871-9638"
    },
    {
      "name": "Satoshi Koyama",
      "orcid": "0000-0002-9286-0360"
    },
    {
      "affs": [
        2
      ],
      "name": "Leland E. Hull",
      "orcid": "0000-0002-5736-6543"
    },
    {
      "name": "Buu Minh Thanh Truong",
      "orcid": "0000-0003-0043-0812"
    },
    {
      "affs": [
        3
      ],
      "name": "So Mi Jemma Cho",
      "orcid": "0000-0003-2460-3335"
    },
    {
      "affs": [
        0
      ],
      "name": "Whitney Hornsby",
      "orcid": "0000-0002-0672-0338"
    },
    {
      "affs": [
        4
      ],
      "name": "Haoyu Zhang"
    },
    {
      "affs": [
        5
      ],
      "name": "Nilanjan Chatterjee",
      "orcid": "0000-0002-9060-008X"
    },
    {
      "name": "Pradeep Natarajan",
      "orcid": "0000-0001-8402-7435"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/fk85tve0cbtja.bib",
  "cited_by": 10,
  "doi": "10.1016/j.ajhg.2026.05.006",
  "fulltext_url": null,
  "id": "fk85tve0cbtja",
  "issns": [
    "0002-9297",
    "1537-6605"
  ],
  "landing_url": "https://doi.org/10.1016/j.ajhg.2026.05.006",
  "language": "en",
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1311|Genetic Associations and Epidemiology"
    ]
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  "openalex": "W7163389960",
  "pdf_url": null,
  "pmcid": "PMC11759244",
  "pmid": "39867390",
  "published": "2026-06-03",
  "publisher": "Elsevier BV",
  "ris": "https://research.draconitic.com/paper/fk85tve0cbtja.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:26:46Z",
      "native_id": "W7163389960",
      "source": "openalex",
      "url": "https://doi.org/10.1016/j.ajhg.2026.05.006"
    }
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  "subjects": [
    {
      "field": "biology",
      "origin": "openalex:1311|Genetic Associations and Epidemiology",
      "subfield": "genetics-genomics"
    }
  ],
  "title": "DiscoDivas: Leveraging genetic-ancestry continuum information to interpolate PRS for admixed populations",
  "title_text": "DiscoDivas: Leveraging genetic-ancestry continuum information to interpolate PRS for admixed populations",
  "type": "peer-reviewed",
  "updated_at": "2026-11-07T13:20:49Z",
  "url": "https://research.draconitic.com/paper/fk85tve0cbtja",
  "venue": "The American Journal of Human Genetics",
  "versions": []
}