Chatterjee Neal A, Giulianini Franco, Geelhoed Bastiaan, Lunetta Kathryn L, Misialek Jeffrey R, Niemeijer Maartje N, Rienstra Michiel, Rose Lynda M, Smith Albert V, Arking Dan E, Ellinor Patrick T, Heeringa Jan, Lin Honghuang, Lubitz Steven A, Soliman Elsayed Z, Verweij Niek, Alonso Alvaro, Benjamin Emelia J, Gudnason Vilmundur, Stricker Bruno H C, Van Der Harst Pim, Chasman Daniel I, Albert Christine M
Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.
Circulation. 2017 Feb 21;135(8):741-754. doi: 10.1161/CIRCULATIONAHA.116.024921. Epub 2016 Dec 14.
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.
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: 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.
In age- and sex-adjusted meta-analysis, both genetic instruments were significantly associated with BMI (: 0.43 [95% confidence interval, 0.32-0.54] kg/m per A-allele, <0.001; BMI gene score: 1.05 [95% confidence interval, 0.90-1.20] kg/m per 1-U increase, <0.001) and incident AF (, hazard ratio, 1.07 [1.02-1.11] per A-allele, =0.004; BMI gene score, hazard ratio, 1.11 [1.05-1.18] per 1-U increase, <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, =0.005 () and 1.11 (1.05-1.17) per kg/m, <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, <0.001). Multivariable adjustment did not significantly change findings.
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.
观察性研究已确定体重指数(BMI)与新发房颤(AF)之间存在关联。然而,从观察性研究中推断因果关系容易受到残余混杂因素、反向因果关系和偏差的影响。本研究的主要目的是通过使用BMI的基因预测指标来评估BMI与AF之间的因果关联。
我们从1987年至2002年在美国、冰岛和荷兰启动的7个基于人群的前瞻性队列中,确定了51646名基线时无AF的欧洲血统个体,并在1987年至2012年期间确定了新发AF情况。各队列的平均随访时间为7.4至19.2年,在此期间共有4178例新发AF病例。我们进行了孟德尔随机化和工具变量分析,以估计BMI与AF关联的特定队列因果风险比。使用了两种BMI的基因工具:基因型(rs1558902)和一个由全基因组关联研究确定的与BMI相关的包含39个单核苷酸多态性的BMI基因评分。通过随机效应、逆方差加权荟萃分析合并特定队列的估计值。
在年龄和性别调整的荟萃分析中,两种基因工具均与BMI显著相关(rs1558902:每A等位基因0.43[95%置信区间,0.32 - 0.54]kg/m²,P<0.001;BMI基因评分:每1单位增加1.05[95%置信区间,0.90 - 1.20]kg/m²,P<0.001)以及新发AF(rs1558902,风险比,每A等位基因1.07[1.02 - 1.11],P = 0.004;BMI基因评分,风险比,每1单位增加1.11[1.05 - 1.18],P<0.001)。BMI与新发AF之间因果关联的年龄和性别调整工具变量估计值为每kg/m²风险比1.15(1.04 - 1.26),P = 0.005(rs1558902)和每kg/m² 1.11(1.05 - 1.17),P<0.001(BMI基因评分)。这两个估计值均与观察到的BMI和AF之间的荟萃分析估计值一致(年龄和性别调整风险比每kg/m² 1.05[1.04 - 1.06],P<0.001)。多变量调整未显著改变研究结果。
我们的数据与BMI和新发AF之间存在因果关系一致。这些数据支持了针对肥胖的初级预防的公共卫生举措可能降低AF发病率的可能性。