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Exploring penetrance of clinically relevant variants in over 800,000 humans from the Genome Aggregation Database

Author

Listed:
  • Sanna Gudmundsson

    (Broad Institute of MIT and Harvard
    Massachusetts General Hospital
    Harvard Medical School
    KTH Royal Institute of Technology)

  • Moriel Singer-Berk

    (Broad Institute of MIT and Harvard)

  • Sarah L. Stenton

    (Broad Institute of MIT and Harvard
    Massachusetts General Hospital
    Harvard Medical School)

  • Julia K. Goodrich

    (Broad Institute of MIT and Harvard)

  • Michael W. Wilson

    (Broad Institute of MIT and Harvard)

  • Jonah Einson

    (New York Genome Center)

  • Nicholas A. Watts

    (Broad Institute of MIT and Harvard)

  • Tuuli Lappalainen

    (KTH Royal Institute of Technology
    New York Genome Center)

  • Heidi L. Rehm

    (Broad Institute of MIT and Harvard
    Massachusetts General Hospital)

  • Daniel G. MacArthur

    (Broad Institute of MIT and Harvard
    Garvan Institute of Medical Research and UNSW Sydney
    Murdoch Children’s Research Institute)

  • Anne O’Donnell-Luria

    (Broad Institute of MIT and Harvard
    Massachusetts General Hospital
    Harvard Medical School)

Abstract

Incomplete penetrance, or absence of disease phenotype in an individual with a disease-associated variant, is a major challenge in variant interpretation. Studying individuals with apparent incomplete penetrance can shed light on underlying drivers of altered phenotype penetrance. Here, we investigate clinically relevant variants from ClinVar in 807,162 individuals from the Genome Aggregation Database (gnomAD), demonstrating improved representation in gnomAD version 4. We then conduct a comprehensive case-by-case assessment of 734 predicted loss of function variants in 77 genes associated with severe, early-onset, highly penetrant haploinsufficient disease. Here, we identify explanations for the presumed lack of disease manifestation in 701 of 734 variants (95%). Individuals with unexplained lack of disease manifestation in this set of disorders are rare, underscoring the need and power of deep case-by-case assessment presented here to minimize false assignments of disease risk, particularly in unaffected individuals with higher rates of secondary properties that result in rescue.

Suggested Citation

  • Sanna Gudmundsson & Moriel Singer-Berk & Sarah L. Stenton & Julia K. Goodrich & Michael W. Wilson & Jonah Einson & Nicholas A. Watts & Tuuli Lappalainen & Heidi L. Rehm & Daniel G. MacArthur & Anne O’, 2025. "Exploring penetrance of clinically relevant variants in over 800,000 humans from the Genome Aggregation Database," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-61698-x
    DOI: 10.1038/s41467-025-61698-x
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    References listed on IDEAS

    as
    1. Monkol Lek & Konrad J. Karczewski & Eric V. Minikel & Kaitlin E. Samocha & Eric Banks & Timothy Fennell & Anne H. O’Donnell-Luria & James S. Ware & Andrew J. Hill & Beryl B. Cummings & Taru Tukiainen , 2016. "Analysis of protein-coding genetic variation in 60,706 humans," Nature, Nature, vol. 536(7616), pages 285-291, August.
    2. Julia K. Goodrich & Moriel Singer-Berk & Rachel Son & Abigail Sveden & Jordan Wood & Eleina England & Joanne B. Cole & Ben Weisburd & Nick Watts & Lizz Caulkins & Peter Dornbos & Ryan Koesterer & Zach, 2021. "Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
    3. Konrad J. Karczewski & Laurent C. Francioli & Grace Tiao & Beryl B. Cummings & Jessica Alföldi & Qingbo Wang & Ryan L. Collins & Kristen M. Laricchia & Andrea Ganna & Daniel P. Birnbaum & Laura D. Gau, 2020. "The mutational constraint spectrum quantified from variation in 141,456 humans," Nature, Nature, vol. 581(7809), pages 434-443, May.
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