Evidence map›Paper›PMID 41173899›Full record

ArticleNature communications2025

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

Sanna Gudmundsson, Moriel Singer-Berk, Sarah L Stenton, Julia K Goodrich, Michael W Wilson, Jonah Einson, Nicholas A Watts, Genome Aggregation Database Consortium, Tuuli Lappalainen, Heidi L Rehm and 2 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Genetic background shapes AI-predicted variant effects.bioRxiv : the preprint server for biology · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. A scalable approach to resolving variants of uncertain significance.bioRxiv : the preprint server for biology · 2026
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Sanna GudmundssonProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. sgudmund@broadinstitute.org.ORCID http://orcid.org/0000-0002-2332-074X
Moriel Singer-BerkProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Sarah L StentonProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID http://orcid.org/0000-0003-4071-449X
Julia K GoodrichProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Michael W WilsonProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Jonah EinsonNew York Genome Center, New York, NY, USA.
Nicholas A WattsProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Genome Aggregation Database Consortium
Tuuli LappalainenScience for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden.ORCID http://orcid.org/0000-0002-7746-8109
Heidi L RehmProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Daniel G MacArthurProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Anne O'Donnell-LuriaProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. odonnell@broadinstitute.org.ORCID http://orcid.org/0000-0001-6418-9592

Funding

The Genome Aggregation Database (gnomAD)U24HG011450 · NHGRI · BROAD INSTITUTE, INC. · PI Mark Joseph Daly, Konrad Karczewski · 2021 to 2026
$22.3M
Department of Health | National Health and Medical Research Council (NHMRC) 2009982G. Harold and Leila Y. Mathers Foundation (G. Harold & Leila Y. Mathers Foundation) MF-2204-02659NHGRI NIH HHS U24 HG011450U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI) U24HG011450
6 · The paper itself

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.

Indexed as

Genetic VariationGenome, HumanPenetranceDatabases, GeneticGenetic Predisposition to DiseaseHaploinsufficiencyHumansPhenotype

Identifiers

PMID41173899
PMCPMC12579199

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.