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A method to estimate the contribution of rare coding variants to complex trait heritability

Author

Listed:
  • Nazia Pathan

    (Hamilton Health Sciences and McMaster University
    Michael G. DeGroote School of Medicine)

  • Wei Q. Deng

    (St. Joseph’s Healthcare Hamilton
    McMaster University)

  • Matteo Di Scipio

    (Hamilton Health Sciences and McMaster University
    McMaster University)

  • Mohammad Khan

    (Hamilton Health Sciences and McMaster University
    McMaster University)

  • Shihong Mao

    (Hamilton Health Sciences and McMaster University)

  • Robert W. Morton

    (Hamilton Health Sciences and McMaster University
    Michael G. DeGroote School of Medicine)

  • Ricky Lali

    (Hamilton Health Sciences and McMaster University
    McMaster University)

  • Marie Pigeyre

    (Hamilton Health Sciences and McMaster University
    McMaster University)

  • Michael R. Chong

    (Hamilton Health Sciences and McMaster University
    Michael G. DeGroote School of Medicine
    Vascular and Stroke Research Institute)

  • Guillaume Paré

    (Hamilton Health Sciences and McMaster University
    Michael G. DeGroote School of Medicine
    McMaster University
    Vascular and Stroke Research Institute)

Abstract

It has been postulated that rare coding variants (RVs; MAF 5%, with height having the highest h2RV at 21.9% (95% CI: 19.0-24.8%). The total heritability, including common and rare variants, recovered pedigree-based estimates for 11 traits. RARity can estimate gene-level h2RV, enabling the assessment of gene-level characteristics and revealing 11, previously unreported, gene-phenotype relationships. Finally, we demonstrated that in silico pathogenicity prediction (variant-level) and gene-level annotations do not generally enrich for RVs that over-contribute to complex trait variance, and thus, innovative methods are needed to predict RV functionality.

Suggested Citation

  • Nazia Pathan & Wei Q. Deng & Matteo Di Scipio & Mohammad Khan & Shihong Mao & Robert W. Morton & Ricky Lali & Marie Pigeyre & Michael R. Chong & Guillaume Paré, 2024. "A method to estimate the contribution of rare coding variants to complex trait heritability," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-45407-8
    DOI: 10.1038/s41467-024-45407-8
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