Supplementary Material for: Smoking-interaction loci affect obesity traits: a gene-smoking stratified meta-analysis of 545,131 Europeans

Introduction: Although many studies have investigated the association between smoking and obesity, very few have analyzed how obesity traits are affected by interactions between genetic factors and smoking. Here, we aimed to identify the loci that affect obesity traits via smoking status-related interactions in European samples. Methods: We performed stratified analysis based on the smoking status using both the UK Biobank (UKB) data (N = 334,808) and the Genetic Investigation of ANthropometric Traits (GIANT) data (N = 210,323) to identify gene-smoking interaction for obesity traits. We divided the UKB subjects into two groups, current smokers and nonsmokers, based on the smoking status, and performed genome-wide association study (GWAS) for body mass index (BMI), waist circumference adjusted for BMI (WCadjBMI), and waist-hip ratio adjusted for BMI (WHRadjBMI) in each group. And then we carried out the meta-analysis using both GWAS summary statistics of UKB and GIANT for BMI, WCadjBMI, and WHRadjBMI, and computed the stratified P-values (Pstratified) based on the differences between meta-analyzed estimated beta coefficients with standard errors in each group. Results: We identified four genome-wide significant loci in interactions with the smoking status (Pstratified < 5×10–8); rs336396 (INPP4B) and rs12899135 (near CHRNB4) for BMI, and rs998584 (near VEGFA) and rs6916318 (near RSPO3) for WHRadjBMI. Moreover, we annotated the biological functions of the SNPs using expression quantitative trait loci (eQTL) and GWAS databases, along with publications, which revealed possible mechanisms underlying the association between the smoking status-related genetic variants and obesity. Conclusions: Our findings suggest that obesity traits can be modified by the smoking status via interactions with genetic variants through various biological pathways.

引言：尽管已有诸多研究探讨了吸烟与肥胖之间的关联，但极少有研究分析遗传因素与吸烟的交互作用如何影响肥胖表型。本研究旨在欧洲人群样本中，鉴定通过与吸烟状态相关的交互作用影响肥胖表型的基因位点。
方法：本研究基于吸烟状态进行分层分析，使用英国生物样本库（UK Biobank, UKB）数据集（样本量N=334808）与人类体格性状遗传研究联盟（Genetic Investigation of ANthropometric Traits, GIANT）数据集（样本量N=210323），以鉴定肥胖表型相关的基因-吸烟交互作用位点。研究人员依据吸烟状态将UKB受试者分为当前吸烟者与非吸烟者两组，并在每组中针对身体质量指数（body mass index, BMI）、校正身体质量指数的腰围（waist circumference adjusted for BMI, WCadjBMI）以及校正身体质量指数的腰臀比（waist-hip ratio adjusted for BMI, WHRadjBMI）开展全基因组关联分析（genome-wide association study, GWAS）。随后，针对BMI、WCadjBMI与WHRadjBMI，研究人员整合UKB与GIANT的GWAS汇总统计量开展荟萃分析，并基于两组间经荟萃分析得到的估计β系数与标准误的差异，计算分层P值（Pstratified）。
结果：本研究共鉴定出4个与吸烟状态存在交互作用的全基因组显著位点（Pstratified < 5×10^-8）：针对BMI的rs336396（INPP4B基因内）与rs12899135（CHRNB4基因附近），以及针对WHRadjBMI的rs998584（VEGFA基因附近）与rs6916318（RSPO3基因附近）。此外，研究人员结合表达数量性状位点（expression quantitative trait loci, eQTL）数据库、GWAS数据库以及已发表文献，对单核苷酸多态性（single nucleotide polymorphisms, SNPs）的生物学功能进行注释，揭示了吸烟状态相关遗传变异与肥胖之间关联的潜在生物学机制。
结论：本研究结果表明，吸烟状态可通过与遗传变异的交互作用，经由多种生物学通路对肥胖表型产生调控作用。