Assessing Digital Phenotyping to Enhance Genetic Studies of Human Diseases.
GWAS
UK Biobank
digital phenotyping
genetic correlation
genetics
genome-wide association study
mixture models
phenotyping
population cohorts
Journal
American journal of human genetics
ISSN: 1537-6605
Titre abrégé: Am J Hum Genet
Pays: United States
ID NLM: 0370475
Informations de publication
Date de publication:
07 05 2020
07 05 2020
Historique:
received:
30
08
2019
accepted:
11
03
2020
pubmed:
11
4
2020
medline:
28
7
2020
entrez:
11
4
2020
Statut:
ppublish
Résumé
Population-scale biobanks that combine genetic data and high-dimensional phenotyping for a large number of participants provide an exciting opportunity to perform genome-wide association studies (GWAS) to identify genetic variants associated with diverse quantitative traits and diseases. A major challenge for GWAS in population biobanks is ascertaining disease cases from heterogeneous data sources such as hospital records, digital questionnaire responses, or interviews. In this study, we use genetic parameters, including genetic correlation, to evaluate whether GWAS performed using cases in the UK Biobank ascertained from hospital records, questionnaire responses, and family history of disease implicate similar disease genetics across a range of effect sizes. We find that hospital record and questionnaire GWAS largely identify similar genetic effects for many complex phenotypes and that combining together both phenotyping methods improves power to detect genetic associations. We also show that family history GWAS using cases ascertained on family history of disease agrees with combined hospital record and questionnaire GWAS and that family history GWAS has better power to detect genetic associations for some phenotypes. Overall, this work demonstrates that digital phenotyping and unstructured phenotype data can be combined with structured data such as hospital records to identify cases for GWAS in biobanks and improve the ability of such studies to identify genetic associations.
Identifiants
pubmed: 32275883
pii: S0002-9297(20)30083-5
doi: 10.1016/j.ajhg.2020.03.007
pmc: PMC7212271
pii:
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
611-622Subventions
Organisme : Medical Research Council
ID : MC_QA137853
Pays : United Kingdom
Organisme : NHGRI NIH HHS
ID : U01 HG009080
Pays : United States
Organisme : Medical Research Council
ID : MC_PC_17228
Pays : United Kingdom
Organisme : NLM NIH HHS
ID : T32 LM012409
Pays : United States
Organisme : NLM NIH HHS
ID : T15 LM007033
Pays : United States
Organisme : NHGRI NIH HHS
ID : R01 HG010140
Pays : United States
Informations de copyright
Copyright © 2020 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
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