Estimation of causal effects of a time-varying exposure at multiple time points through multivariable mendelian randomization

Advanced search
Browse by:

Department | Year

UCL Theses | Latest

Deposit your research

Estimation of causal effects of a time-varying exposure at multiple time points through multivariable mendelian randomization

Sanderson, Eleanor; Richardson, Tom G; Morris, Tim T; Tilling, Kate; Smith, George Davey; (2022) Estimation of causal effects of a time-varying exposure at multiple time points through multivariable mendelian randomization. PLoS Genetics , 18 (7) , Article e1010290. 10.1371/journal.pgen.1010290. Green open access

[thumbnail of Estimation of causal effects of a time-varying exposure at multiple time points through multivariable mendelian randomizatio.pdf]

Preview

Text
Estimation of causal effects of a time-varying exposure at multiple time points through multivariable mendelian randomizatio.pdf - Published Version
Download (956kB) | Preview

Abstract

Mendelian Randomisation (MR) is a powerful tool in epidemiology that can be used to estimate the causal effect of an exposure on an outcome in the presence of unobserved confounding, by utilising genetic variants as instrumental variables (IVs) for the exposure. The effect estimates obtained from MR studies are often interpreted as the lifetime effect of the exposure in question. However, the causal effects of some exposures are thought to vary throughout an individual's lifetime with periods during which an exposure has a greater effect on a particular outcome. Multivariable MR (MVMR) is an extension of MR that allows for multiple, potentially highly related, exposures to be included in an MR estimation. MVMR estimates the direct effect of each exposure on the outcome conditional on all the other exposures included in the estimation. We explore the use of MVMR to estimate the direct effect of a single exposure at different time points in an individual's lifetime on an outcome. We use simulations to illustrate the interpretation of the results from such analyses and the key assumptions required. We show that causal effects at different time periods can be estimated through MVMR when the association between the genetic variants used as instruments and the exposure measured at those time periods varies. However, this estimation will not necessarily identify exact time periods over which an exposure has the most effect on the outcome. Prior knowledge regarding the biological basis of exposure trajectories can help interpretation. We illustrate the method through estimation of the causal effects of childhood and adult BMI on C-Reactive protein and smoking behaviour.

Type:	Article
Title:	Estimation of causal effects of a time-varying exposure at multiple time points through multivariable mendelian randomization
Location:	United States
Open access status:	An open access version is available from UCL Discovery
DOI:	10.1371/journal.pgen.1010290
Publisher version:	https://doi.org/10.1371/journal.pgen.1010290
Language:	English
Additional information:	Copyright: © 2022 Sanderson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Keywords:	Science & Technology, Life Sciences & Biomedicine, Genetics & Heredity, CHILDHOOD, EPIDEMIOLOGY, IMMIGRANTS, SCLEROSIS, VARIANTS, BIAS
UCL classification:	UCL UCL > Provost and Vice Provost Offices > School of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Social Research Institute UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Social Research Institute > IOE - Centre for Longitudinal Studies
URI:	https://discovery.ucl.ac.uk/id/eprint/10171021