dc.contributor.author | Wright, CF | |
dc.contributor.author | Sharp, LN | |
dc.contributor.author | Jackson, L | |
dc.contributor.author | Murray, A | |
dc.contributor.author | Ware, JS | |
dc.contributor.author | MacArthur, DG | |
dc.contributor.author | Rehm, HL | |
dc.contributor.author | Patel, KA | |
dc.contributor.author | Weedon, MN | |
dc.date.accessioned | 2024-07-30T12:35:46Z | |
dc.date.issued | 2024-07-29 | |
dc.date.updated | 2024-07-30T09:41:33Z | |
dc.description.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. | en_GB |
dc.description.sponsorship | Diabetes UK | en_GB |
dc.description.sponsorship | Medical Research Council (MRC) | en_GB |
dc.description.sponsorship | Wellcome Trust | en_GB |
dc.description.sponsorship | Sir Jules Thorn Charitable Trust | en_GB |
dc.description.sponsorship | British Heart Foundation | en_GB |
dc.description.sponsorship | National Institute for Health and Care Research (NIHR) | en_GB |
dc.identifier.citation | Published online 29 July 2024 | en_GB |
dc.identifier.doi | https://doi.org/10.1038/s41588-024-01842-3 | |
dc.identifier.grantnumber | 19/0005994 | en_GB |
dc.identifier.grantnumber | MR/T00200X/1 | en_GB |
dc.identifier.grantnumber | 226083/Z/22/Z | en_GB |
dc.identifier.grantnumber | 219606/Z/19/Z | en_GB |
dc.identifier.grantnumber | 21JTA | en_GB |
dc.identifier.grantnumber | RE/18/4/34215 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/136941 | |
dc.identifier | ORCID: 0000-0003-2958-5076 (Wright, Caroline F) | |
dc.identifier | ORCID: 0000-0002-0260-5295 (Jackson, Leigh) | |
dc.identifier | ORCID: 0000-0002-2351-2522 (Murray, Anna) | |
dc.identifier | ORCID: 0000-0002-9240-8104 (Patel, Kashyap A) | |
dc.identifier | ORCID: 0000-0002-6174-6135 (Weedon, Michael N) | |
dc.language.iso | en | en_GB |
dc.publisher | Nature Research | en_GB |
dc.relation.url | https://www.ncbi.nlm.nih.gov/pubmed/39075210 | en_GB |
dc.rights.embargoreason | Under embargo until 29 January 2025 in compliance with publisher policy | en_GB |
dc.rights | © Springer Nature America, Inc. 2024 | en_GB |
dc.title | Guidance for estimating penetrance of monogenic disease-causing variants in population cohorts | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2024-07-30T12:35:46Z | |
dc.identifier.issn | 1061-4036 | |
exeter.place-of-publication | United States | |
dc.description | This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this record | en_GB |
dc.identifier.eissn | 1546-1718 | |
dc.identifier.journal | Nature Genetics | en_GB |
dc.rights.uri | http://www.rioxx.net/licenses/all-rights-reserved | en_GB |
dcterms.dateAccepted | 2024-06-24 | |
rioxxterms.version | AM | en_GB |
rioxxterms.licenseref.startdate | 2024-07-29 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2024-07-30T12:26:42Z | |
refterms.versionFCD | AM | |
refterms.panel | A | en_GB |
refterms.dateFirstOnline | 2024-07-29 | |