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


Journal

PLoS genetics
ISSN: 1553-7404
Titre abrégé: PLoS Genet
Pays: United States
ID NLM: 101239074

Informations de publication

Date de publication:
07 2022
Historique:
received: 12 01 2022
accepted: 09 06 2022
revised: 03 08 2022
pubmed: 19 7 2022
medline: 6 8 2022
entrez: 18 7 2022
Statut: epublish

Résumé

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.

Identifiants

pubmed: 35849575
doi: 10.1371/journal.pgen.1010290
pii: PGENETICS-D-22-00043
pmc: PMC9348730
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1010290

Subventions

Organisme : Medical Research Council
ID : MC_PC_17228
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_QA137853
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_UU_00011/3
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_UU_00011/1
Pays : United Kingdom

Déclaration de conflit d'intérêts

I have read the journals policy and the authors of this manuscripts have the following competing interests: TGR is employed part-time by Novo Nordisk outside of this work. KT has undertaken paid consultancy work for CHDI unrelated to this work. All other authors declare no conflicts of interest.

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Auteurs

Eleanor Sanderson (E)

MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom.
Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.

Tom G Richardson (TG)

MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom.
Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
Novo Nordisk Research Centre, Headington, Oxford, United Kingdom.

Tim T Morris (TT)

MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom.
Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.

Kate Tilling (K)

MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom.
Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.

George Davey Smith (G)

MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom.
Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.

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Classifications MeSH