» Articles » PMID: 33737984

A General Approach to Sensitivity Analysis for Mendelian Randomization

Overview
Journal Stat Biosci
Date 2021 Mar 19
PMID 33737984
Citations 3
Authors
Affiliations
Soon will be listed here.
Abstract

Mendelian Randomization (MR) represents a class of instrumental variable methods using genetic variants. It has become popular in epidemiological studies to account for the unmeasured confounders when estimating the effect of exposure on outcome. The success of Mendelian Randomization depends on three critical assumptions, which are difficult to verify. Therefore, sensitivity analysis methods are needed for evaluating results and making plausible conclusions. We propose a general and easy to apply approach to conduct sensitivity analysis for Mendelian Randomization studies. Bound et al. (1995) derived a formula for the asymptotic bias of the instrumental variable estimator. Based on their work, we derive a new sensitivity analysis formula. The parameters in the formula include sensitivity parameters such as the correlation between instruments and unmeasured confounder, the direct effect of instruments on outcome and the strength of instruments. In our simulation studies, we examined our approach in various scenarios using either individual SNPs or unweighted allele score as instruments. By using a previously published dataset from researchers involving a bone mineral density study, we demonstrate that our proposed method is a useful tool for MR studies, and that investigators can combine their domain knowledge with our method to obtain bias-corrected results and make informed conclusions on the scientific plausibility of their findings.

Citing Articles

Plasma proteins and coronary atherosclerosis: A Mendelian randomization study.

Pan H, Wu Z, Gao Y, Yao W, Feng G, Wang H Medicine (Baltimore). 2025; 104(8):e41549.

PMID: 39993089 PMC: 11856891. DOI: 10.1097/MD.0000000000041549.


Genetic relationship between ageing and coronary heart disease: a Mendelian randomization study.

Qin S, Sheng Z, Chen C, Cao Y Eur Geriatr Med. 2023; 15(1):159-167.

PMID: 37948032 DOI: 10.1007/s41999-023-00888-6.


Peripheral Inflammatory Factors and Acute Myocardial Infarction Risk: A Mendelian Randomization Study.

Chen Y, Zeng L Glob Heart. 2023; 18(1):55.

PMID: 37811136 PMC: 10558024. DOI: 10.5334/gh.1269.


Exploring the causality between ankylosing spondylitis and atrial fibrillation: A two-sample Mendelian randomization study.

Chen S, Luo X, Zhao J, Liang Z, Gu J Front Genet. 2022; 13:951893.

PMID: 36468019 PMC: 9708899. DOI: 10.3389/fgene.2022.951893.

References
1.
Davey Smith G, Ebrahim S . Mendelian randomization: prospects, potentials, and limitations. Int J Epidemiol. 2004; 33(1):30-42. DOI: 10.1093/ije/dyh132. View

2.
Golding J . Children of the nineties. A longitudinal study of pregnancy and childhood based on the population of Avon (ALSPAC). West Engl Med J. 1990; 105(3):80-2. PMC: 5115048. View

3.
Davey Smith G, Ebrahim S . 'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease?. Int J Epidemiol. 2003; 32(1):1-22. DOI: 10.1093/ije/dyg070. View

4.
Lin D, Psaty B, Kronmal R . Assessing the sensitivity of regression results to unmeasured confounders in observational studies. Biometrics. 1998; 54(3):948-63. View

5.
Cornfield J, Haenszel W, HAMMOND E, LILIENFELD A, SHIMKIN M, Wynder E . Smoking and lung cancer: recent evidence and a discussion of some questions. J Natl Cancer Inst. 1959; 22(1):173-203. View