Mixed model association for biobank-scale data sets
Open accessPreprint — published as 10.1038/s41588-018-0144-6 · Paper page
Abstract
Biobank-based genome-wide association studies are enabling exciting insights in complex trait genetics, but much uncertainty remains over best practices for optimizing statistical power and computational efficiency in GWAS while controlling confounders. Here, we introduce a much faster version of our BOLT-LMM Bayesian mixed model association method— capable of running analyses of the full UK Biobank cohort in a few days on a single compute node—and show that it produces highly powered, robust test statistics when run on all 459K European samples (retaining related individuals). When used to conduct a GWAS for height in UK Biobank, BOLT-LMM achieved power equivalent to linear regression on 650K samples—a 93% increase in effective sample size versus the common practice of analyzing unrelated British samples using linear regression (UK Biobank documentation; Bycroft et al. bioRxiv). Across a broader set of 23 highly heritable traits, the total number of independent GWAS loci detected increased from 5,839 to 10,759, an 84% increase. We recommend the use of BOLT-LMM (retaining related individuals) for biobank-scale analyses, and we have publicly released BOLT-LMM summary association statistics for the 23 traits analyzed as a resource for all researchers.
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In cases of a large product of sample size and SNP heritability, a normalization of the LDSC intercept called the 'ratio' has been proposed as a more appropriate measure of confounding.
“In cases of a large product of sample size and SNP heritability, a normalization of the LDSC intercept called the ‘ratio’ has been proposed as a more appropriate measure of confounding49.”
From Family-GWAS reveals effects of environment and mating on genetic associations (2024) · cites this paper as [49]
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References 11 · Cited by 788
Research works printed but not linked: 3
- Bycroft, C. et al. Genome-wide genetic data on ∼500,000 UK Biobank participants. bioRxiv (2017).
- Canela-Xandri, O., Rawlik, K. & Tenesa, A. An atlas of genetic associations in UK Biobank. bioRxiv 176834 (2017).
- Zhou, W. et al. Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies. bioRxiv 212357 (2017).
- Authors
- Loh, P.-R., Kichaev, G., Gazal, S., Schoech, A. P., & Price, A. L.
- Affiliations
- Broad Institute (US)
- University of California, Los Angeles (US)
- Corresponding author
- Loh, Po-Ru
- Price, Alkes L
- Venue
- Nature Genetics
- Publisher
- openRxiv
- Published
- 2017-09-27
- Volume
- 50
- Issue
- 7
- Pages
- 906-908
- ISSN
- 1061-4036 (ISSN-L)
- PMC
- PMC6309610
- OpenAlex
- W2950598813
- Cited by
- 788
- References
- 11
- Citations by year
- 2026: 58 · 2025: 129 · 2024: 148 · 2023: 85 · 2022: 94 · 2021: 107 · 2020: 76 · 2019: 58 · 2018: 31 · 2017: 2
- FWCI
- 42.17
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Nature Genetics (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Boehringer Ingelheim Fonds
- National Institutes of Health (1s10rr028832-01, MH107649)
- National Institute of Mental Health (R01MH107649)
- National Human Genome Research Institute (R01HG006399, U01HG009379)
- National Institute of General Medical Sciences (R01GM105857)
- National Center for Research Resources (S10 RR028832, 1S10RR028832, 1S10RR028832-01)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Keywords
- biobank-scale data, genome-wide association study, genetic association, primary sclerosing cholangitis, genetic susceptibility loci
- MeSH terms
- United Kingdom, Humans, Genome, Human, Linear Models, Biological Specimen Banks, Genome-Wide Association Study, Datasets as Topic
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