Background
The identification of gene-by-environment interactions is important to understand the genetic basis of chronic obstructive pulmonary disease (COPD). Many COPD genetic association analyses assume a linear relationship between pack-years of smoking exposure and FEV1; however, this assumption has not been evaluated empirically in cohorts with a wide spectrum of COPD severity.
Methods
We examined the relationship between FEV1 and pack-years of smoking exposure in 4 large cohorts assembled for the purpose of identifying genetic associations with COPD. Using data from the Alpha-1 Antitrypsin Genetic Modifiers Study, we compared the accuracy and power of two different approaches to model smoking by performing a simulation study of a genetic variant with a range of gene-by-smoking interaction effects.
Results
We identified nonlinear relationships between smoking and FEV1 in 4 large cohorts. We demonstrated that in most situations where the relationship between pack-years and FEV1 is nonlinear, a piecewise-linear approach to model smoking and gene-by-smoking interactions is preferable to the commonly used total pack-years approach. We applied the piecewise linear approach to a genetic association analysis of the PI*Z allele in the Norway case-control cohort and identified a potential PI*Z-by-smoking interaction (p=0.03 for FEV1 analysis, p= 0.01 for COPD susceptibility analysis).
Conclusion
In study samples with subjects having a wide range of COPD severity, a nonlinear relationship between pack-years of smoking and FEV1 is likely. In this setting, approaches that account for this nonlinearity can be more powerful and less-biased than the commonly-used approach of using total pack-years to model the smoking effect.
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