Upward bias in odds ratio estimates from genome‐wide association studies
Abstract
Genome‐wide association studies are carried out to identify unknown genes for a complex trait. Polymorphisms showing the most statistically significant associations are reported and followed up in subsequent confirmatory studies. In addition to the test of association, the statistical analysis provides point estimates of the relationship between the genotype and phenotype at each polymorphism, typically an odds ratio in case‐control association studies. The statistical significance of the test and the estimator of the odds ratio are completely correlated. Selecting the most extreme statistics is equivalent to selecting the most extreme odds ratios. The value of the estimator, given the value of the statistical significance depends on the standard error of the estimator and the power of the study. This report shows that when power is low, estimates of the odds ratio from a genome‐wide association study, or any large‐scale association study, will be upwardly biased. Genome‐wide association studies are often underpowered given the low α levels required to declare statistical significance and the small individual genetic effects known to characterize complex traits. Factors such as low allele frequency, inadequate sample size and weak genetic effects contribute to large standard errors in the odds ratio estimates, low power and upwardly biased odds ratios. Studies that have high power to detect an association with the true odds ratio will have little or no bias, regardless of the statistical significance threshold. The results have implications for the interpretation of genome‐wide association analysis and the planning of subsequent confirmatory stages. Genet Epidemiol. 2007. © 2007 Wiley‐Liss, Inc.
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If the authors used the same or similar individuals to estimate the SNP-exposure and SNP-outcome associations, MR estimates could be biased by a form of the winner's curse.
“If the authors used the same or similar individuals to estimate the SNP-exposure and the SNP-outcome associations, MR estimates could be biased by a form of the winner’s curse,94 95 which occurs when the statistically strongest associations—usually using a P value threshold—are selected from the discovery sample.”
From Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomisation (STROBE-MR): explanation and elaboration. (2021) · cites this paper as [95]
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- Authors
- Garner, C.
- Affiliations
- University of California, Irvine (US)
- Corresponding author
- Garner, Chad
- Venue
- Genetic Epidemiology
- Publisher
- Wiley
- Published
- 2007-01-31
- Volume
- 31
- Issue
- 4
- Pages
- 288-295
- ISSN
- 0741-0395 (ISSN-L)
- 1098-2272
- OpenAlex
- W2057289154
- Cited by
- 103
- References
- 23
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 2 · 2022: 1 · 2021: 4 · 2020: 1 · 2019: 3 · 2018: 5 · 2017: 10 · 2016: 5 · 2015: 5 · 2014: 3 · 2013: 6 · 2012: 8
- FWCI
- 6.07
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Genetic Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Cancer Institute (R01CA-74415, R01CA058860, R01 CA 58860-10, R01CA074415)
- 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
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- upward bias, odds ratio estimation, genome-wide association study, statistical significance thresholds, study power, standard errors, complex traits, case-control association, genetic effect size, allele frequency
- MeSH terms
- Computer Simulation, Gene Frequency, Genotype, Humans, Models, Genetic, Phenotype, Polymorphism, Genetic, Models, Statistical, Genome, Human, Odds Ratio, Genetic Predisposition to Disease
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