Sample size determination for studies of gene-environment interaction
Abstract
Background The search for interaction effects is common in epidemiological studies, but the power of such studies is a major concern. This is a practical issue as many future studies will wish to investigate potential gene-gene and gene-environment interactions and therefore need to be planned on the basis of appropriate sample size calculations. Methods The underlying model considered in this paper is a simple linear regression and relating a continuous outcome to a continuously distributed exposure variable. Results The slope of the regression line is taken to be dependent on genotype, and the ratio of the slopes for each genotype is considered as the interaction parameter. Sample size is affected by the allele frequency and whether the genetic model is dominant or recessive. It is also critically dependent upon the size of the association between exposure and outcome, and the strength of the interaction term. The link between these determinants is graphically displayed to allow sample size and power to be estimated. An example of the analysis of the association between physical activity and glucose intolerance demonstrates how information from previous studies can be used to determine the sample size required to examine gene-environment interactions. Conclusions The formulae allowing the computation of the sample size required to study the interaction between a continuous environmental exposure and a genetic factor on a continuous outcome variable should have a practical u…
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Interaction effects require larger sample sizes for adequate power, and power depends on allele frequencies and exposure to early life stress.
“Achieving sufficient statistical power presents a special challenge because interaction effects require larger numbers of subjects for adequate power (Brookes et al. 2001; Luan et al. 2001; Uher 2008), and power depends on allele frequencies in addition to exposure to ELS (Munafo et al. 2009).”
From Gene–environment interactions: early life stress and risk for depressive and anxiety disorders (2011) · cites this paper as Luan et al. 2001
Cites
ROTHMAN, K. J., GREENLAND, S., & WALKER, A. M. (1980) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a113015 · Cited by 851 · see citing works
Genetic and environmental determinants of non‐insulin‐dependent diabetes mellitus (NIDDM)
Hamman, R. F. (1992) · Diabetes/Metabolism Reviews · doi:10.1002/dmr.5610080402 · Cited by 256 · see citing works
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Duncan, L. E., & Keller, M. C. (2011) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2011.11020191 · Cited by 1,032 · see citing works
Genomics, type 2 diabetes, and obesity
McCarthy, M. I. (2010) · New England Journal of Medicine · doi:10.1056/nejmra0906948 · Cited by 938 · see citing works
Strategy for Investigating Interactions Between Measured Genes and Measured Environments
Moffitt, T. E., Caspi, A., & Rutter, M. (2005) · Archives of General Psychiatry · doi:10.1001/archpsyc.62.5.473 · Cited by 784 · see citing works
Statistical power and significance testing in large-scale genetic studies
Sham, P. C., & Purcell, S. M. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3706 · Cited by 573 · see citing works
Brage, S., Brage, N., Franks, P. W., Ekelund, U., Wong, M.-Y., Andersen, L. B., Froberg, K., & Wareham, N. J. (2004) · Journal of Applied Physiology · doi:10.1152/japplphysiol.00703.2003 · Cited by 473 · see citing works
Self-citationGene–environment interactions: early life stress and risk for depressive and anxiety disorders
Nugent, N. R., Tyrka, A. R., Carpenter, L. L., & Price, L. H. (2011) · Psychopharmacology · doi:10.1007/s00213-010-2151-x · Cited by 269 · see citing works
“Achieving sufficient statistical power presents a special challenge because interaction effects require larger numbers of subjects for adequate power (Brookes et al. 2001; Luan et al. 2001; Uher 2008), and power depends on allele frequencies in addition to exposure to ELS (Munafo et al.”
BackgroundMacdonald, H. M., McGuigan, F. E., Lanham-New, S. A., Fraser, W. D., Ralston, S. H., & Reid, D. M. (2008) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/87.5.1513 · Cited by 63 · see citing works
- Authors
- Luan, J., Wong, M., Day, N., & Wareham, N.
- Venue
- International Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2001-10
- Volume
- 30
- Issue
- 5
- Pages
- 1035-1040
- ISSN
- 0300-5771 (ISSN-L)
- 1464-3685
- OpenAlex
- W2153848537
- Cited by
- 123
- References
- 4
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 5 · 2023: 3 · 2022: 3 · 2020: 2 · 2019: 5 · 2018: 2 · 2017: 4 · 2016: 8 · 2015: 2 · 2014: 7 · 2013: 8 · 2012: 8
- FWCI
- 2.73
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
- Keywords
- sample size determination, gene-environment interaction, statistical power, gene-gene interaction, continuous exposure, continuous outcomes, allele frequency, physical activity, impaired glucose tolerance
- MeSH terms
- Environmental Exposure, Genotype, Humans, Effect Modifier, Epidemiologic, Linear Models, Glucose Intolerance, Sample Size
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