A case-only study of gene-environment interaction between genetic susceptibility variants in NOD2 and cigarette smoking in Crohn's disease aetiology

Abstract

BackgroundGenetic variation in NOD2 and cigarette smoking are well-established risk factors for the development of Crohn's disease (CD). However, little is known about a potential interaction between these risk factors. We investigated gene-environment interactions between CD-associated NOD2 alleles and cigarette smoking in a large sample of patients with CD.MethodsThree previously reported CD-associated variants in NOD2 (R702W, G908R, 1007fs) were genotyped in 1636 patients with CD continuously recruited between 1995 and 2010 based on physician referral. Data on history of smoking behaviour was obtained for all participants through a written questionnaire. Using a case-only design, we performed logistic regression analyses to investigate statistical interactions between NOD2 risk alleles and smoking status.ResultsWe detected a significant negative interaction between carriership of at least one of the NOD2 risk alleles and history of ever having smoked (OR = 0.71; p = 0.005) as well as smoking at the time of CD diagnosis (OR = 0.68; p = 0.005). Subsequent separate analyses of the three variants revealed a significant negative interaction between the 1007fs variant and history of ever having smoked (OR = 0.64; p = 9 × 10-4) and smoking at the time of CD diagnosis (OR = 0.53; p = 7 × 10-5).ConclusionsThe observed significant negative gene-environment interaction suggests that the risk increase for CD conferred simultaneously by cigarette smoking and the 1007fs NOD2 polymorphism is smaller than expected and may point to a biological interaction. Our findings warrant further investigation in epidemiological and functional studies to elucidate pathophysiology as well as to aid in the development of recommendations for disease prevention.

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“…Expanded approaches that include analyses to assess geneenvironment interactions using GWAS data are referred to as gene-environment wide interaction studies (GEWIS; Khoury & Wacholder, 2009) or genome-wide environmental interactions (GWEI; Aschard et al, 2012). Methods that improve limitations inherent in these early designs have been developed and include approaches that can account for the complex correlations between individuals in admixed populations (Chen et al, 2019), assess the impact of exposure misclassification (Boonstra et al, 2016), evaluate interactions using case subjects only (vs. the traditional method using case and control subjects) (Cornelis et al, 2012;Helbig et al, 2012), and assess interactions using exposed subjects only (Zhao, Fan, et al, 2015).…”