Using Principal Components of Genetic Variation for Robust and Powerful Detection of Gene-Gene Interactions in Case-Control and Case-Only Studies
Open accessAbstract
Many popular methods for exploring gene-gene interactions, including the case-only approach, rely on the key assumption that physically distant loci are in linkage equilibrium in the underlying population. These methods utilize the presence of correlation between unlinked loci in a disease-enriched sample as evidence of interactions among the loci in the etiology of the disease. We use data from the CGEMS case-control genome-wide association study of breast cancer to demonstrate empirically that the case-only and related methods have the potential to create large-scale false positives because of the presence of population stratification (PS) that creates long-range linkage disequilibrium in the genome. We show that the bias can be removed by considering parametric and nonparametric methods that assume gene-gene independence between unlinked loci, not in the entire population, but only conditional on population substructure that can be uncovered based on the principal components of a suitably large panel of PS markers. Applications in the CGEMS study as well as simulated data show that the proposed methods are robust to the presence of population stratification and are yet much more powerful, relative to standard logistic regression methods that are also commonly used as robust alternatives to the case-only type methods.
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GWAS are generally not powered to detect epistasis or GxE and are not designed to detect epigenetic influences.
“Genome-wide association studies (GWAS) are not generally powered to detect epistasis or G×E121, and they are not designed to detect epigenetic influences122”
From Rare and common variants: twenty arguments (2012) · cites this paper as [121]
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- Authors
- Bhattacharjee, S., Wang, Z., Ciampa, J., Kraft, P., Chanock, S., Yu, K., & Chatterjee, N.
- Affiliations
- National Institutes of Health (US)
- Harvard University (US)
- Corresponding author
- Chatterjee, Nilanjan
- Venue
- The American Journal of Human Genetics
- Publisher
- Elsevier BV
- Published
- 2010-03
- Volume
- 86
- Issue
- 3
- Pages
- 331-342
- ISSN
- 0002-9297 (ISSN-L)
- PMC
- PMC2833365
- OpenAlex
- W1963989728
- Cited by
- 44
- References
- 31
- Citations by year
- 2026: 1 · 2025: 1 · 2021: 1 · 2020: 2 · 2019: 2 · 2018: 3 · 2017: 1 · 2016: 1 · 2014: 4 · 2013: 8 · 2012: 6
- FWCI
- 5.04
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- The American Journal of Human Genetics (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health
- National Cancer Institute (P01CA087969, [P01 CA87969)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- gene-gene interaction, epistasis, case-only design, case-control study, population stratification, linkage disequilibrium, principal components, population substructure, breast cancer, false positives, genetic association
- MeSH terms
- Breast Neoplasms, Epistasis, Genetic, Female, Humans, Models, Genetic, Genetic Variation, Linkage Disequilibrium, Bias, Logistic Models, Case-Control Studies, Databases, Factual, Statistics, Nonparametric, Polymorphism, Single Nucleotide, Principal Component Analysis, Genome-Wide Association Study
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