Evidence map›Paper›PMID 38233927›Full record

ArticleBMC research notes2024

MRSamePopTest: introducing a simple falsification test for the two-sample mendelian randomisation 'same population' assumption.

Benjamin Woolf, Amy Mason, Loukas Zagkos, Hannah Sallis, Marcus R Munafò, Dipender Gill

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In one paragraph

Article in BMC research notes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Benjamin WoolfSchool of Psychological Science, University of Bristol, Bristol, UK. benjamin.woolf@bristol.ac.uk.
Amy MasonVictor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK.
Loukas ZagkosDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
Hannah Sallis *MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
Marcus R Munafò *School of Psychological Science, University of Bristol, Bristol, UK.
Dipender Gill *Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK.

Funding

Medical Research Council MC_UU_00002/7Medical Research Council MC_UU_00032/7
6 · The paper itself

Abstract

Two-sample MR is an increasingly popular method for strengthening causal inference in epidemiological studies. For the effect estimates to be meaningful, variant-exposure and variant-outcome associations must come from comparable populations. A recent systematic review of two-sample MR studies found that, if assessed at all, MR studies evaluated this assumption by checking that the genetic association studies had similar demographics. However, it is unclear if this is sufficient because less easily accessible factors may also be important. Here we propose an easy-to-implement falsification test. Since recent theoretical developments in causal inference suggest that a causal effect estimate can generalise from one study to another if there is exchangeability of effect modifiers, we suggest testing the homogeneity of variant-phenotype associations for a phenotype which has been measured in both genetic association studies as a method of exploring the 'same-population' test. This test could be used to facilitate designing MR studies with diverse populations. We developed a simple R package to facilitate the implementation of our proposed test. We hope that this research note will result in increased attention to the same-population assumption, and the development of better sensitivity analyses.

Indexed as

Genome-Wide Association StudyMendelian Randomization AnalysisCausalityGenetic Association StudiesPhenotypePopulation homogeneitySensitivity analysisTwo-sample Mendelian randomisation

Identifiers

PMID38233927
PMCPMC10795421

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