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Understanding the assumptions underlying Mendelian randomization.

ABSTRACT: With the rapidly increasing availability of large genetic data sets in recent years, Mendelian Randomization (MR) has quickly gained popularity as a novel secondary analysis method. Leveraging genetic variants as instrumental variables, MR can be used to estimate the causal effects of one phenotype on another even when experimental research is not feasible, and therefore has the potential to be highly informative. It is dependent on strong assumptions however, often producing biased results if these are not met. It is therefore imperative that these assumptions are well-understood by researchers aiming to use MR, in order to evaluate their validity in the context of their analyses and data. The aim of this perspective is therefore to further elucidate these assumptions and the role they play in MR, as well as how different kinds of data can be used to further support them.

SUBMITTER: de Leeuw C

PROVIDER: S-EPMC9177700 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Understanding the assumptions underlying Mendelian randomization.

de Leeuw Christiaan C Savage Jeanne J Bucur Ioan Gabriel IG Heskes Tom T Posthuma Danielle D

European journal of human genetics : EJHG 20220126 6

With the rapidly increasing availability of large genetic data sets in recent years, Mendelian Randomization (MR) has quickly gained popularity as a novel secondary analysis method. Leveraging genetic variants as instrumental variables, MR can be used to estimate the causal effects of one phenotype on another even when experimental research is not feasible, and therefore has the potential to be highly informative. It is dependent on strong assumptions however, often producing biased results if t ...[more]

PMID: 35082398

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