Genetic Obesity and the Risk of Atrial Fibrillation

医学 孟德尔随机化 危险系数 体质指数 内科学 置信区间 人口 混淆 队列研究 队列 心房颤动 人口学 遗传学 基因型 遗传变异 社会学 基因 环境卫生 生物
作者
Neal A. Chatterjee,Franco Giulianini,Bastiaan Geelhoed,Kathryn L. Lunetta,Jeffrey R. Misialek,Maartje N. Niemeijer,Michiel Rienstra,Lynda M. Rose,Albert V. Smith,Dan E. Arking,Patrick T. Ellinor,Jan Heeringa,Honghuang Lin,Catherine M Otto,Elsayed Z. Soliman,Niek Verweij,Alvaro Alonso,Emelia J. Benjamin,Vilmundur Gudnason,Bruno H. Stricker,Pim van der Harst,Daniel I. Chasman,Christine M. Albert
出处
期刊:Circulation [Lippincott Williams & Wilkins]
卷期号:135 (8): 741-754 被引量:79
标识
DOI:10.1161/circulationaha.116.024921
摘要

Background: Observational studies have identified an association between body mass index (BMI) and incident atrial fibrillation (AF). Inferring causality from observational studies, however, is subject to residual confounding, reverse causation, and bias. The primary objective of this study was to evaluate the causal association between BMI and AF by using genetic predictors of BMI. Methods: We identified 51 646 individuals of European ancestry without AF at baseline from 7 prospective population-based cohorts initiated between 1987 and 2002 in the United States, Iceland, and the Netherlands with incident AF ascertained between 1987 and 2012. Cohort-specific mean follow-up ranged from 7.4 to 19.2 years, over which period there was a total of 4178 cases of incident AF. We performed a Mendelian randomization with instrumental variable analysis to estimate a cohort-specific causal hazard ratio for the association between BMI and AF. Two genetic instruments for BMI were used: FTO genotype (rs1558902) and a BMI gene score comprising 39 single-nucleotide polymorphisms identified by genome-wide association studies to be associated with BMI. Cohort-specific estimates were combined by random-effects, inverse variance–weighted meta-analysis. Results: In age- and sex-adjusted meta-analysis, both genetic instruments were significantly associated with BMI ( FTO : 0.43 [95% confidence interval, 0.32–0.54] kg/m 2 per A-allele, P <0.001; BMI gene score: 1.05 [95% confidence interval, 0.90–1.20] kg/m 2 per 1-U increase, P <0.001) and incident AF ( FTO , hazard ratio, 1.07 [1.02–1.11] per A-allele, P =0.004; BMI gene score, hazard ratio, 1.11 [1.05–1.18] per 1-U increase, P <0.001). Age- and sex-adjusted instrumental variable estimates for the causal association between BMI and incident AF were hazard ratio, 1.15 (1.04–1.26) per kg/m 2 , P =0.005 ( FTO ) and 1.11 (1.05–1.17) per kg/m 2 , P <0.001 (BMI gene score). Both of these estimates were consistent with the meta-analyzed estimate between observed BMI and AF (age- and sex-adjusted hazard ratio 1.05 [1.04–1.06] per kg/m 2 , P <0.001). Multivariable adjustment did not significantly change findings. Conclusions: Our data are consistent with a causal relationship between BMI and incident AF. These data support the possibility that public health initiatives targeting primordial prevention of obesity may reduce the incidence of AF.
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