Mendelian randomization for nephrologists

被引:10
|
作者
Dobrijevic, Ellen [1 ,2 ,5 ]
van Zwieten, Anita [1 ,2 ]
Kiryluk, Krzysztof [3 ]
Grant, Andrew J. [1 ]
Wong, Germaine [1 ,2 ,4 ]
Teixeira-Pinto, Armando [1 ,2 ]
机构
[1] Univ Sydney, Fac Med & Hlth, Sydney Sch Publ Hlth, Sydney, NSW, Australia
[2] Childrens Hosp Westmead, Kids Res Inst, Ctr Kidney Res, Westmead, NSW, Australia
[3] Columbia Univ, Vagelos Coll Phys & Surg, Dept Med, Div Nephrol, New York, NY USA
[4] Westmead Hosp, Ctr Transplant & Renal Res, Westmead, NSW, Australia
[5] Childrens Hosp Westmead, Kids Res Inst, Ctr Kidney Res, Sydney, NSW 2145, Australia
基金
英国医学研究理事会;
关键词
causal inference; chronic kidney disease; Mendelian randomization; CHRONIC KIDNEY-DISEASE; GENETIC-VARIANTS; CAUSAL INFERENCE; CANCER; BIAS; ASSOCIATION; INSTRUMENTS; RISK;
D O I
10.1016/j.kint.2023.09.016
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Confounding is a major limitation of observational studies. Mendelian randomization (MR) is a powerful study design that uses genetic variants as instrumental variables to enable examination of the causal effect of an exposure on an outcome in observational data. With the emergence of large-scale genome-wide association studies in nephrology over the past decade, MR has become a popular method to establish causal inferences. However, MR is a complex and challenging methodology that requires careful consideration to ensure robust results. This review article aims to summarize the basic concepts of MR, its application and relevance in nephrology, and the methodological challenges and limitations as well as discuss the current guidelines for design and reporting. With reference to a clinically relevant example of examining the causal relationship between the estimated glomerular filtration rate and cancer, this review outlines the key steps to conducting an MR study, including the key considerations and potential pitfalls at each step. These include defining the clinical question, selecting the data sources, identifying and refining appropriate genetic variants by considering linkage disequilibrium and associations with potential confounders, harmonization of variants across data sets, validation of the genetic instrument by assessing its strength, estimation of the causal effects, confirming the validity of the findings, and interpreting and reporting results.
引用
收藏
页码:1113 / 1123
页数:11
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