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dc.contributor.authorWright, CF
dc.contributor.authorSharp, LN
dc.contributor.authorJackson, L
dc.contributor.authorMurray, A
dc.contributor.authorWare, JS
dc.contributor.authorMacArthur, DG
dc.contributor.authorRehm, HL
dc.contributor.authorPatel, KA
dc.contributor.authorWeedon, MN
dc.date.accessioned2024-07-30T12:35:46Z
dc.date.issued2024-07-29
dc.date.updated2024-07-30T09:41:33Z
dc.description.abstractPenetrance 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.sponsorshipDiabetes UKen_GB
dc.description.sponsorshipMedical Research Council (MRC)en_GB
dc.description.sponsorshipWellcome Trusten_GB
dc.description.sponsorshipSir Jules Thorn Charitable Trusten_GB
dc.description.sponsorshipBritish Heart Foundationen_GB
dc.description.sponsorshipNational Institute for Health and Care Research (NIHR)en_GB
dc.identifier.citationPublished online 29 July 2024en_GB
dc.identifier.doihttps://doi.org/10.1038/s41588-024-01842-3
dc.identifier.grantnumber19/0005994en_GB
dc.identifier.grantnumberMR/T00200X/1en_GB
dc.identifier.grantnumber226083/Z/22/Zen_GB
dc.identifier.grantnumber219606/Z/19/Zen_GB
dc.identifier.grantnumber21JTAen_GB
dc.identifier.grantnumberRE/18/4/34215en_GB
dc.identifier.urihttp://hdl.handle.net/10871/136941
dc.identifierORCID: 0000-0003-2958-5076 (Wright, Caroline F)
dc.identifierORCID: 0000-0002-0260-5295 (Jackson, Leigh)
dc.identifierORCID: 0000-0002-2351-2522 (Murray, Anna)
dc.identifierORCID: 0000-0002-9240-8104 (Patel, Kashyap A)
dc.identifierORCID: 0000-0002-6174-6135 (Weedon, Michael N)
dc.language.isoenen_GB
dc.publisherNature Researchen_GB
dc.relation.urlhttps://www.ncbi.nlm.nih.gov/pubmed/39075210en_GB
dc.rights.embargoreasonUnder embargo until 29 January 2025 in compliance with publisher policyen_GB
dc.rights© Springer Nature America, Inc. 2024en_GB
dc.titleGuidance for estimating penetrance of monogenic disease-causing variants in population cohortsen_GB
dc.typeArticleen_GB
dc.date.available2024-07-30T12:35:46Z
dc.identifier.issn1061-4036
exeter.place-of-publicationUnited States
dc.descriptionThis is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recorden_GB
dc.identifier.eissn1546-1718
dc.identifier.journalNature Geneticsen_GB
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserveden_GB
dcterms.dateAccepted2024-06-24
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2024-07-29
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2024-07-30T12:26:42Z
refterms.versionFCDAM
refterms.panelAen_GB
refterms.dateFirstOnline2024-07-29


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