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Cited by 243Genetic Associations and EpidemiologyPharmacogenetics and Drug MetabolismGenetic Mapping and Diversity in Plants and Animals

Genome-wide association study of medication-use and associated disease in the UK Biobank

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Wu, Yeda, Byrne, Enda M., Zheng, Zhili, Kemper, Kathryn E., Yengo, Loic, Mallett, Andrew J., Yang, Jian, Visscher, Peter M. +1 more·2019·Nature Communications
DOI 10.1038/s41467-019-09572-5PMC PMC6478889

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Abstract

Genome-wide association studies (GWASs) of medication use may contribute to understanding of disease etiology, could generate new leads relevant for drug discovery and can be used to quantify future risk of medication taking. Here, we conduct GWASs of self-reported medication use from 23 medication categories in approximately 320,000 individuals from the UK Biobank. A total of 505 independent genetic loci that meet stringent criteria ( P < 10 −8 /23) for statistical significance are identified. We investigate the implications of these GWAS findings in relation to biological mechanism, potential drug target identification and genetic risk stratification of disease. Amongst the medication-associated genes are 16 known therapeutic-effect target genes for medications from 9 categories. Two of the medication classes studied are for disorders that have not previously been subject to large GWAS (hypothyroidism and gastro-oesophageal reflux disease).

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  • Statin adjustment may be incomplete because not all individuals report medication use, and confounders assessed by self-report may be sub-optimally controlled.

    “Statin adjustment may be incomplete because not all individuals report medication use; confounders assessed by self-report may be sub-optimally controlled depending on the outcome of interest [16].”

    From Characterization of APOE Christchurch carriers in 455,306 UK Biobank participants (2023) · cites this paper as [16]

    The Discussion (page unavailable) says self-reported medication use may limit the accuracy of the data, and the Results report that about 73% of participants had non-blank medication information. These passages support concern about incomplete medication data, but the paper does not assess whether statin adjustment or control of self-reported confounders is inadequate for particular outcomes. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • JAKMIP1 is associated with type 2 diabetes and medications used to treat it.

    “associated with type 2 diabetes and medications used to treat it82–84.”

    From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [83]

    The Results section reports associations involving diabetes medications (A10), and the drug-target analysis names IDE as a gene meriting further study for type 2 diabetes. A search for JAKMIP1 in our copy found no passage linking that gene to type 2 diabetes or its medications, so the specific claim cannot be verified. (LLM, conf=0.75)

    Experimental — accuracy not yet measured

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Cited by

Sorted by citations

Authors
Wu, Y., Byrne, E. M., Zheng, Z., Kemper, K. E., Yengo, L., Mallett, A. J., Yang, J., Visscher, P. M., & Wray, N. R.
Affiliations
The University of Queensland (AU)
Corresponding author
  • Visscher, Peter M.
  • Wray, Naomi R.
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2019-04-23
Volume
10
Issue
1
Pages
1891-1891
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-019-09572-5
PMC
PMC6478889
OpenAlex
W2942053120
Cited by
243
References
13
Citations by year
2026: 22 · 2025: 43 · 2024: 51 · 2023: 51 · 2022: 29 · 2021: 31 · 2020: 14 · 2019: 2
FWCI
11.45
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • ResearchOnline - JCU (James Cook University) (submittedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • University of Queensland
  • Medical Research Council (1113400, 1078037, 1078901)
  • National Health and Medical Research Council (1113400, 1078901, 1078037)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacogenetics and Drug Metabolism
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
Keywords
medication use, genetic loci, drug target genes, genetic risk stratification, hypothyroidism, gastroesophageal reflux disease, etiology, drug discovery
MeSH terms
Pharmacogenomic Testing, Aged, Mental Disorders, Cardiovascular Diseases, Drug Utilization, Female, Gastrointestinal Diseases, United Kingdom, Humans, Male, Middle Aged, Musculoskeletal Diseases, Self Administration, Genome, Human, Databases, Factual, Biological Specimen Banks, Genome-Wide Association Study, Prescription Drugs, Genetic Loci, Self Report

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