Impact of non-linear smoking effects on the identification of gene-by-smoking interactions in COPD genetics studies

Peter J. Castaldi, D. L. Demeo, C. P. Hersh, D. A. Lomas, I. C. Soerheim, A. Gulsvik, P. Bakke, S. Rennard, P. Pare, J. Vestbo, E. K. Silverman, Alvar Agusti, Peter Calverley, Claudio F. Donner, Robert D. Levy, David Lomas, Barry J. Make, Wayne Anderson, Peter Pare, Sreekumar PillaiStephen Rennard, Emiel Wouters, Jørgen Vestbo, Alan Barker, Mark Brantly, Edward J. Campbell, Edward Eden, N. Gerard McElvaney, Robert Sandhaus, James Stocks, James Stoller, Charlie Strange, Gerard Turino

    Research output: Contribution to journalArticlepeer-review


    Background: The identification of gene-by-environment interactions is important for understanding 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 forced expiratory volume in 1 s (FEV1); however, this assumption has not been evaluated empirically in cohorts with a wide spectrum of COPD severity. Methods: The relationship between FEV1 and pack-years of smoking exposure was examined in four large cohorts assembled for the purpose of identifying genetic associations with COPD. Using data from the Alpha-1 Antitrypsin Genetic Modifiers Study, the accuracy and power of two different approaches to model smoking were compared by performing a simulation study of a genetic variant with a range of gene-by-smoking interaction effects. Results: Non-linear relationships between smoking and FEV1 were identified in the four cohorts. It was found that, in most situations where the relationship between pack-years and FEV1 is non-linear, a piecewise linear approach to model smoking and gene-by-smoking interactions is preferable to the commonly used total pack-years approach. The piecewise linear approach was applied to a genetic association analysis of the PI*Z allele in the Norway Case - Control cohort and a potential PI*Z-by-smoking interaction was identified (p=0.03 for FEV1 analysis, p=0.01 for COPD susceptibility analysis). Conclusion: In study samples of subjects with a wide range of COPD severity, a non-linear relationship between pack-years of smoking and FEV1 is likely. In this setting, approaches that account for this non-linearity can be more powerful and less biased than the more common approach of using total pack-years to model the smoking effect.
    Original languageEnglish
    Pages (from-to)903-909
    Number of pages6
    Issue number10
    Publication statusPublished - Oct 2011


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