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Oxford University Press, International Journal of Epidemiology, p. dyw318, 2017

DOI: 10.1093/ije/dyw318

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Evidence for large-scale gene-by-smoking interaction effects on pulmonary function.

Journal article published in 2017 by Hugues Aschard, Martin D. Tobin, Db Hancock, David Skurnik, Akshay Sood, Alan James, Albert Vernon Smith, Aw Manichaikul, Archie Campbell, Bp Prins, Caroline Hayward, Dw Loth, Dj Porteous, Dp Strachan, Eleftheria Zeggini and other authors.
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

BACKGROUND: Smoking is the strongest environmental risk factor for reduced pulmonary function. The genetic component of various pulmonary traits has also been demonstrated, and at least 26 loci have been reproducibly associated with either FEV1 (forced expiratory volume in 1 second) or FEV1/FVC (FEV1/forced vital capacity). Although the main effects of smoking and genetic loci are well established, the question of potential gene-by-smoking interaction effect remains unanswered. The aim of the present study was to assess, using a genetic risk score approach, whether the effect of these 26 loci on pulmonary function is influenced by smoking. METHODS: We evaluated the interaction between smoking exposure, considered as either ever vs never or pack-years, and a 26-single nucleotide polymorphisms (SNPs) genetic risk score in relation to FEV1 or FEV1/FVC in 50 047 participants of European ancestry from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) and SpiroMeta consortia. RESULTS: We identified an interaction (βint = -0.036, 95% confidence interval, -0.040 to -0.032, P = 0.00057) between an unweighted 26 SNP genetic risk score and smoking status (ever/never) on the FEV1/FVC ratio. In interpreting this interaction, we showed that the genetic risk of falling below the FEV 1: /FVC threshold used to diagnose chronic obstructive pulmonary disease is higher among ever smokers than among never smokers. A replication analysis in two independent datasets, although not statistically significant, showed a similar trend in the interaction effect. CONCLUSIONS: This study highlights the benefit of using genetic risk scores for identifying interactions missed when studying individual SNPs and shows, for the first time, that persons with the highest genetic risk for low FEV1/FVC may be more susceptible to the deleterious effects of smoking.