Identification and analysis of individuals who deviate from their genetically-predicted phenotype
dc.contributor.author | Hawkes, G | |
dc.contributor.author | Yengo, L | |
dc.contributor.author | Vedantam, S | |
dc.contributor.author | Marouli, E | |
dc.contributor.author | Beaumont, RN | |
dc.contributor.author | GIANT Consortium | |
dc.contributor.author | Tyrrell, J | |
dc.contributor.author | Weedon, MN | |
dc.contributor.author | Hirschhorn, J | |
dc.contributor.author | Frayling, TM | |
dc.contributor.author | Wood, AR | |
dc.date.accessioned | 2024-01-09T14:13:18Z | |
dc.date.issued | 2023-09-21 | |
dc.date.updated | 2024-01-09T12:51:55Z | |
dc.description.abstract | Findings from genome-wide association studies have facilitated the generation of genetic predictors for many common human phenotypes. Stratifying individuals misaligned to a genetic predictor based on common variants may be important for follow-up studies that aim to identify alternative causal factors. Using genome-wide imputed genetic data, we aimed to classify 158,951 unrelated individuals from the UK Biobank as either concordant or deviating from two well-measured phenotypes. We first applied our methods to standing height: our primary analysis classified 244 individuals (0.15%) as misaligned to their genetically predicted height. We show that these individuals are enriched for self-reporting being shorter or taller than average at age 10, diagnosed congenital malformations, and rare loss-of-function variants in genes previously catalogued as causal for growth disorders. Secondly, we apply our methods to LDL cholesterol (LDL-C). We classified 156 (0.12%) individuals as misaligned to their genetically predicted LDL-C and show that these individuals were enriched for both clinically actionable cardiovascular risk factors and rare genetic variants in genes previously shown to be involved in metabolic processes. Individuals whose LDL-C was higher than expected based on the genetic predictor were also at higher risk of developing coronary artery disease and type-two diabetes, even after adjustment for measured LDL-C, BMI and age, suggesting upward deviation from genetically predicted LDL-C is indicative of generally poor health. Our results remained broadly consistent when performing sensitivity analysis based on a variety of parametric and non-parametric methods to define individuals deviating from polygenic expectation. Our analyses demonstrate the potential importance of quantitatively identifying individuals for further follow-up based on deviation from genetic predictions. | en_GB |
dc.description.sponsorship | Innovative Medicines Initiative 2 Joint Undertaking | en_GB |
dc.description.sponsorship | Academy of Medical Sciences | en_GB |
dc.description.sponsorship | Medical Research Council (MRC) | en_GB |
dc.description.sponsorship | Australian Research Council (ARC) | en_GB |
dc.identifier.citation | Vol. 19, No. 9, article e1010934 | en_GB |
dc.identifier.doi | https://doi.org/10.1371/journal.pgen.1010934 | |
dc.identifier.grantnumber | 875534 | en_GB |
dc.identifier.grantnumber | SBF004\1079 | en_GB |
dc.identifier.grantnumber | SBF006\1134 | en_GB |
dc.identifier.grantnumber | MR/WO14548/1 | en_GB |
dc.identifier.grantnumber | MR/T002239/1 | en_GB |
dc.identifier.grantnumber | DE200100425 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/134955 | |
dc.identifier | ORCID: 0000-0002-3367-789X (Hawkes, Gareth) | |
dc.identifier | ORCID: 0000-0003-0750-8248 (Beaumont, Robin N) | |
dc.identifier | ORCID: 0000-0002-9256-6065 (Tyrrell, Jessica) | |
dc.identifier | ORCID: 0000-0002-6174-6135 (Weedon, Michael N) | |
dc.identifier | ORCID: 0000-0003-1726-948X (Wood, Andrew R) | |
dc.language.iso | en | en_GB |
dc.publisher | Public Library of Science (PLoS) | en_GB |
dc.relation.url | https://www.ncbi.nlm.nih.gov/pubmed/37733769 | en_GB |
dc.relation.url | http://www.ukbiobank.ac.uk | en_GB |
dc.relation.url | https://csg.sph.umich.edu/willer/public/glgc-lipids2021/ | en_GB |
dc.rights | © 2023 Hawkes et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | en_GB |
dc.title | Identification and analysis of individuals who deviate from their genetically-predicted phenotype | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2024-01-09T14:13:18Z | |
dc.contributor.editor | Cordell, HJ | |
dc.identifier.issn | 1553-7390 | |
exeter.place-of-publication | United States | |
dc.description | This is the final version. Available from Public Library of Science via the DOI in this record. | en_GB |
dc.description | Data Availability: The research utilised data from the UK Biobank resource carried out under UK Biobank application number 9072. UK Biobank protocols were approved by the National Research Ethics Service Committee. Individual-level data cannot be shared publicly because of data access policies of the UK Biobank. Data are available from the UK Biobank for researchers who meet the criteria for access to datasets to UK Biobank (http://www.ukbiobank.ac.uk). The weights used to calculate the polygenic score for height is available in Table C in S1 Data. The weights used to calculate the polygenic score for LDL-cholesterol, calculated in a meta-analysis excluding UK Biobank, are available from the Global Lipids Genetics Consortium at https://csg.sph.umich.edu/willer/public/glgc-lipids2021/. | en_GB |
dc.identifier.eissn | 1553-7404 | |
dc.identifier.journal | PLoS Genetics | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2023-08-22 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2023-09-21 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2024-01-09T14:04:18Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2024-01-09T14:13:22Z | |
refterms.panel | A | en_GB |
refterms.dateFirstOnline | 2023-09-21 |
Files in this item
This item appears in the following Collection(s)
Except where otherwise noted, this item's licence is described as © 2023 Hawkes et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.