Evidence map›Paper›PMID 29709202›Full record

ReviewAnnual review of genomics and human genetics2018

Inferring Causal Relationships Between Risk Factors and Outcomes from Genome-Wide Association Study Data.

Stephen Burgess, Christopher N Foley, Verena Zuber

Abstract readReview
In one paragraph

Review in Annual review of genomics and human genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 168 papers, 10 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
168citing papers in PubMed, 10 pooled it
–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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

168 citing papers in PubMed, 10 syntheses or guidelines pooled it.

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  12. Exploring the impacts of type 2 diabetes and metformin use on Parkinson's disease: Mendelian randomization analysis and a national cohort study.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026
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108 more citing papers are in PubMed but not listed here.

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

3 authors.

Stephen BurgessMRC Biostatistics Unit, University of Cambridge, Cambridge CB2 0SR, United Kingdom; email: sb452@medschl.cam.ac.uk.
Christopher N FoleyMRC Biostatistics Unit, University of Cambridge, Cambridge CB2 0SR, United Kingdom; email: sb452@medschl.cam.ac.uk.
Verena ZuberMRC Biostatistics Unit, University of Cambridge, Cambridge CB2 0SR, United Kingdom; email: sb452@medschl.cam.ac.uk.

Funding

British Heart Foundation RG/13/13/30194Medical Research Council MC_UU_00002/7Medical Research Council MR/L003120/1Wellcome TrustWellcome Trust 204623/Z/16/Z
6 · The paper itself

Abstract

An observational correlation between a suspected risk factor and an outcome does not necessarily imply that interventions on levels of the risk factor will have a causal impact on the outcome (correlation is not causation). If genetic variants associated with the risk factor are also associated with the outcome, then this increases the plausibility that the risk factor is a causal determinant of the outcome. However, if the genetic variants in the analysis do not have a specific biological link to the risk factor, then causal claims can be spurious. We review the Mendelian randomization paradigm for making causal inferences using genetic variants. We consider monogenic analysis, in which genetic variants are taken from a single gene region, and polygenic analysis, which includes variants from multiple regions. We focus on answering two questions: When can Mendelian randomization be used to make reliable causal inferences, and when can it be used to make relevant causal inferences?

Indexed as

Genome-Wide Association StudyCausalityHumansMendelian Randomization AnalysisRisk Factorscausal inferencedrug discoverygenetic epidemiologyinstrumental variabletarget validation

Identifiers

PMID29709202
PMCPMC6481551

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.