{
  "abstract": "Our knowledge of human complex trait architecture across diverse populations remains limited. Estimating SNP heritability and genetic correlation from GWAS summary statistics - successful in revealing genetic architecture in homogeneous cohorts - is challenging in structured and admixed populations due, in part, to the difficulty of representing long-range LD. We present SUMMIT, a statistical framework that combines genome-wide LD scores, efficiently estimated using random projections, with GWAS summary statistics to estimate genome-wide and annotation-specific heritability and genetic correlation. In simulations that explore diverse aspects of genetic architecture across European (EUR), South Asian (SAS), and admixed African-European cohorts (AFR) in the UK Biobank (UKB), SUMMIT had increased accuracy and reduced bias compared to prior methods, with the largest gains in non-European ancestries reflecting improved modeling of long-range LD. Across 40 UKB traits, SUMMIT produced estimates of genome-wide common-SNP heritability (h_g^2) and heritability enrichments in genomic annotations that were broadly concordant across ancestries with the SUMMIT h_g^2 estimates more closely matching recent whole-genome sequencing based estimates. SUMMIT substantially improved genetic correlation analysis recovering more significant findings across ancestries (23 SAS and 3 AFR at FDR < 0.05 compared with none and two for cov-LDSC) with the non-European discoveries showing concordant effects in Europeans suggesting that, like heritability, global patterns of pleiotropy are largely shared across ancestries. By combining accurate genome-wide LD and efficient moment estimation, SUMMIT enables investigation into how heritability and genetic correlation vary across populations and genomic annotations, including in structured and admixed cohorts, at the genome-wide, annotation-specific, and cross-trait levels.",
  "abstract_shown": true,
  "affiliations": [
    "University of California, Los Angeles"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 9,
  "authors": [
    {
      "name": "M. Jeong"
    },
    {
      "name": "Z. Liu"
    },
    {
      "name": "J. Ni"
    },
    {
      "name": "U. An"
    },
    {
      "name": "S. Han"
    },
    {
      "name": "A. Anand"
    },
    {
      "name": "P. Anand"
    },
    {
      "name": "M. Boffelli"
    },
    {
      "affs": [
        0
      ],
      "name": "S. Sankararaman"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9hw0k554rc422.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.20.760508",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.20.760508v1.full",
  "id": "9hw0k554rc422",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.20.760508v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "genomics"
    ],
    [
      "openalex",
      "1311|Genetic Associations and Epidemiology"
    ]
  ],
  "openalex": "W7223187547",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.20.760508v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-20",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/9hw0k554rc422.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:29:07Z",
      "native_id": "10.64898/2026.10.20.760508",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.20.760508v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:genomics",
      "subfield": "genetics-genomics"
    }
  ],
  "title": "Genome-wide LD scores enable robust heritability and genetic correlation estimation from summary statistics across genetic ancestries",
  "title_text": "Genome-wide LD scores enable robust heritability and genetic correlation estimation from summary statistics across genetic ancestries",
  "type": "preprint",
  "updated_at": "2026-10-30T12:29:07Z",
  "url": "https://research.draconitic.com/paper/9hw0k554rc422",
  "venue": "bioRxiv",
  "versions": []
}