Mendelian Randomization With Repeated Measures of a Time-varying Exposure: An Application of Structural Mean Models.

ABSTRACT: Mendelian randomization (MR) is often used to estimate effects of time-varying exposures on health outcomes using observational data. However, MR studies typically use a single measurement of exposure and apply conventional instrumental variable (IV) methods designed to handle time-fixed exposures. As such, MR effect estimates for time-varying exposures are often biased, and interpretations are unclear. We describe the instrumental conditions required for IV estimation with a time-varying exposure, and the additional conditions required to causally interpret MR estimates as a point effect, a period effect or a lifetime effect depending on whether researchers have measurements at a single or multiple time points. We propose methods to incorporate time-varying exposures in MR analyses based

SUBMITTER: Shi J 

PROVIDER: S-EPMC9067358 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature