Evidence map›Paper›PMID 39075210›Full record

ReviewNature genetics2024

Guidance for estimating penetrance of monogenic disease-causing variants in population cohorts.

Caroline F Wright, Luke N Sharp, Leigh Jackson, Anna Murray, James S Ware, Daniel G MacArthur, Heidi L Rehm, Kashyap A Patel, Michael N Weedon

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
–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

30 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Guideline
  2. Trial
  3. Article
  4. Article
  5. [Genetic diagnostics].Pathologie (Heidelberg, Germany) · 2026
    Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Cancer risk in adults with pathogenic germline variants in RAS/MAPK genes using genomic ascertainment.Genetics in medicine : official journal of the American College of Medical Genetics · 2026
    Article
  11. Article
  12. Measuring disease likelihood in genomic ascertainment.American journal of human genetics · 2026
    Article
  13. Population Prevalence, Penetrance, and Mortality for Genetically Confirmed MODY.The Journal of clinical endocrinology and metabolism · 2026
    Article
  14. Revisiting penetrance in an era of genomic screening.European journal of human genetics : EJHG · 2026
    Article
  15. Structural Evaluation ofCirculation. Genomic and precision medicine · 2026
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Caroline F Wright *Department of Clinical and Biomedical Sciences, Medical School, University of Exeter, Exeter, UK. caroline.wright@exeter.ac.uk.ORCID http://orcid.org/0000-0003-2958-5076
Luke N Sharp *Department of Clinical and Biomedical Sciences, Medical School, University of Exeter, Exeter, UK.ORCID http://orcid.org/0009-0001-3657-5493
Leigh JacksonDepartment of Clinical and Biomedical Sciences, Medical School, University of Exeter, Exeter, UK.ORCID http://orcid.org/0000-0002-0260-5295
Anna MurrayDepartment of Clinical and Biomedical Sciences, Medical School, University of Exeter, Exeter, UK.ORCID http://orcid.org/0000-0002-2351-2522
James S WareNational Heart and Lung Institute and MRC Laboratory of Medical Sciences, Imperial College London, London, UK.ORCID http://orcid.org/0000-0002-6110-5880
Daniel G MacArthurCentre for Population Genomics, Garvan Institute of Medical Research and UNSW Sydney, Sydney, New South Wales, Australia.
Heidi L RehmMedical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-6025-0015
Kashyap A Patel *Department of Clinical and Biomedical Sciences, Medical School, University of Exeter, Exeter, UK.ORCID http://orcid.org/0000-0002-9240-8104
Michael N Weedon *Department of Clinical and Biomedical Sciences, Medical School, University of Exeter, Exeter, UK. m.n.weedon@exeter.ac.uk.ORCID http://orcid.org/0000-0002-6174-6135

Funding

Diabetes UK 19/0005994RCUK | Medical Research Council (MRC) MR/T00200X/1RCUK | MRC | Medical Research Foundation MR/T00200X/1Wellcome Trust (Wellcome) 226083/Z/22/Z
6 · The paper itself

Abstract

Penetrance is the probability that an individual with a pathogenic genetic variant develops a specific disease. Knowing the penetrance of variants for monogenic disorders is important for counseling of individuals. Until recently, estimates of penetrance have largely relied on affected individuals and their at-risk family members being clinically referred for genetic testing, a 'phenotype-first' approach. This approach substantially overestimates the penetrance of variants because of ascertainment bias. The recent availability of whole-genome sequencing data in individuals from very-large-scale population-based cohorts now allows 'genotype-first' estimates of penetrance for many conditions. Although this type of population-based study can underestimate penetrance owing to recruitment biases, it provides more accurate estimates of penetrance for secondary or incidental findings. Here, we provide guidance for the conduct of penetrance studies to ensure that robust genotypes and phenotypes are used to accurately estimate penetrance of variants and groups of similarly annotated variants from population-based studies.

Indexed as

Genetic Predisposition to DiseasePenetrancePhenotypeCohort StudiesGenetic Diseases, InbornGenetic TestingGenetic VariationGenotypeHumansWhole Genome Sequencing

Identifiers

What OpenQuestion holds

Textmetadata
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.