Dissecting Causal Pathways Using Mendelian Randomization with Summarized Genetic Data: Application to Age at Menarche and Risk of Breast Cancer

被引:149
作者
Burgess, Stephen [1 ,2 ]
Thompson, Deborah J. [3 ]
Rees, Jessica M. B. [2 ]
Day, Felix R. [4 ]
Perry, John R. [4 ]
Ong, Ken K. [4 ]
机构
[1] Univ Cambridge, MRC, Biostat Unit, Cambridge CB2 0QQ, Cambs, England
[2] Univ Cambridge, Cardiovasc Epidemiol Unit, Cambridge CB2 0QQ, Cambs, England
[3] Univ Cambridge, Cambridge Ctr Genet Epidemiol, Cambridge CB2 0QQ, Cambs, England
[4] Univ Cambridge, MRC, Epidemiol Unit, Cambridge CB2 0QQ, Cambs, England
基金
加拿大健康研究院; 英国惠康基金; 英国医学研究理事会; 美国国家卫生研究院;
关键词
Mendelian randomization; instrumental variable; mediation analysis; direct effect; causal inference; INSTRUMENTAL VARIABLE ANALYSIS; VARIANTS; IDENTIFICATION; MEDIATION; DESIGN; LOCI; BIAS;
D O I
10.1534/genetics.117.300191
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Mendelian randomization is the use of genetic variants as instrumental variables to estimate causal effects of risk factors on outcomes. The total causal effect of a risk factor is the change in the outcome resulting from intervening on the risk factor. This total causal effect may potentially encompass multiple mediating mechanisms. For a proposed mediator, the direct effect of the risk factor is the change in the outcome resulting from a change in the risk factor, keeping the mediator constant. A difference between the total effect and the direct effect indicates that the causal pathway from the risk factor to the outcome acts at least in part via the mediator (an indirect effect). Here, we show that Mendelian randomization estimates of total and direct effects can be obtained using summarized data on genetic associations with the risk factor, mediator, and outcome, potentially from different data sources. We perform simulations to test the validity of this approach when there is unmeasured confounding and/or bidirectional effects between the risk factor and mediator. We illustrate this method using the relationship between age at menarche and risk of breast cancer, with body mass index (BMI) as a potential mediator. We show an inverse direct causal effect of age at menarche on risk of breast cancer (independent of BMI), and a positive indirect effect via BMI. In conclusion, multivariable Mendelian randomization using summarized genetic data provides a rapid and accessible analytic strategy that can be undertaken using publicly available data to better understand causal mechanisms.
引用
收藏
页码:481 / 487
页数:7
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