International Journal of Epidemiology 2001;30:1035-1040
© International Epidemiological Association 2001
Methodology |
Sample size determination for studies of gene-environment interaction
a Department of Public Health and Primary Care, Institute of Public Health, University of Cambridge, Cambridge CB2 2SR, UK.
b Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong.
Dr Nicholas J Wareham, Department of Public Health and Primary Care, Institute of Public Health, University Forvie Site, Robinson Way, Cambridge CB2 2SR, UK. E-mail: njw1004{at}medschl.cam.ac.uk
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 graphiscally 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 utility in assisting the design of studies of appropriate power.
Keywords Genotype, environmental exposure, gene-environment interaction, sample size, quantitative trait
Accepted 7 February 2001
![]()
CiteULike
Connotea
Del.icio.us What's this?
This article has been cited by other articles:
![]() |
D. Corella, G. Peloso, D. K. Arnett, S. Demissie, L. A. Cupples, K. Tucker, C.-Q. Lai, L. D. Parnell, O. Coltell, Y.-C. Lee, et al. APOA2, Dietary Fat, and Body Mass Index: Replication of a Gene-Diet Interaction in 3 Independent Populations Arch Intern Med, November 9, 2009; 169(20): 1897 - 1906. [Abstract] [Full Text] [PDF] |
||||
![]() |
Q.-H. Yang, L. D Botto, M. Gallagher, J. Friedman, C. L Sanders, D. Koontz, S. Nikolova, J D. Erickson, and K. Steinberg Prevalence and effects of gene-gene and gene-nutrient interactions on serum folate and serum total homocysteine concentrations in the United States: findings from the third National Health and Nutrition Examination Survey DNA Bank Am. J. Clinical Nutrition, July 1, 2008; 88(1): 232 - 246. [Abstract] [Full Text] [PDF] |
||||
![]() |
H. M Macdonald, F. E McGuigan, S. A Lanham-New, W. D Fraser, S. H Ralston, and D. M Reid Vitamin K1 intake is associated with higher bone mineral density and reduced bone resorption in early postmenopausal Scottish women: no evidence of gene-nutrient interaction with apolipoprotein E polymorphisms Am. J. Clinical Nutrition, May 1, 2008; 87(5): 1513 - 1520. [Abstract] [Full Text] [PDF] |
||||
![]() |
F Zhang, M Lewis, G Yang, J Iriondo-Perez, Y Zeng, and J Liu Apolipoprotein E polymorphism, life stress and self-reported health among older adults J Epidemiol Community Health, April 1, 2008; 62(4): e3 - e3. [Abstract] [Full Text] [PDF] |
||||
![]() |
M P M Boks, M Schipper, C D Schubart, I E Sommer, R S Kahn, and R A Ophoff Investigating gene environment interaction in complex diseases: increasing power by selective sampling for environmental exposure Int. J. Epidemiol., December 1, 2007; 36(6): 1363 - 1369. [Abstract] [Full Text] [PDF] |
||||
![]() |
T. E. Moffitt, A. Caspi, and M. Rutter Strategy for Investigating Interactions Between Measured Genes and Measured Environments Arch Gen Psychiatry, May 1, 2005; 62(5): 473 - 481. [Abstract] [Full Text] [PDF] |
||||
![]() |
P. W. Franks, S. Bhattacharyya, J.'a. Luan, C. Montague, J. Brennand, B. Challis, S. Brage, U. Ekelund, R. P.S. Middelberg, S. O'Rahilly, et al. Association Between Physical Activity and Blood Pressure Is Modified by Variants in the G-Protein Coupled Receptor 10 Hypertension, February 1, 2004; 43(2): 224 - 228. [Abstract] [Full Text] [PDF] |
||||
![]() |
S. Brage, N. Brage, P. W. Franks, U. Ekelund, M.-Y. Wong, L. B. Andersen, K. Froberg, and N. J. Wareham Branched equation modeling of simultaneous accelerometry and heart rate monitoring improves estimate of directly measured physical activity energy expenditure J Appl Physiol, January 1, 2004; 96(1): 343 - 351. [Abstract] [Full Text] [PDF] |
||||
![]() |
M. Wong, N. Day, J. Luan, K. Chan, and N. Wareham The detection of gene-environment interaction for continuous traits: should we deal with measurement error by bigger studies or better measurement? Int. J. Epidemiol., February 1, 2003; 32(1): 51 - 57. [Abstract] [Full Text] [PDF] |
||||
![]() |
A. Dawid Commentary: Counterfactuals: help or hindrance? Int. J. Epidemiol., April 1, 2002; 31(2): 429 - 430. [Full Text] [PDF] |
||||
![]() |
J. S Kaufman and S. Kaufman Commentary: Estimating causal effects Int. J. Epidemiol., April 1, 2002; 31(2): 431 - 432. [Full Text] [PDF] |
||||
![]() |
F. Elwert and C. Winship Commentary: Population versus individual level causal effects Int. J. Epidemiol., April 1, 2002; 31(2): 432 - 434. [Full Text] [PDF] |
||||
![]() |
G. Shafer Commentary: Estimating causal effects Int. J. Epidemiol., April 1, 2002; 31(2): 434 - 435. [Full Text] [PDF] |
||||
![]() |
A. Meirhaeghe, J.'a. Luan, P. Selberg-Franks, S. Hennings, J. Mitchell, D. Halsall, S. O'Rahilly, and N. J. Wareham The Effect of the Gly16Arg Polymorphism of the {beta}2-Adrenergic Receptor Gene on Plasma Free Fatty Acid Levels Is Modulated by Physical Activity J. Clin. Endocrinol. Metab., December 1, 2001; 86(12): 5881 - 5887. [Abstract] [Full Text] [PDF] |
||||







