Evidence map›Paper›PMID 29149188›Full record

ArticlePLoS genetics2017

Orienting the causal relationship between imprecisely measured traits using GWAS summary data.

Gibran Hemani, Kate Tilling, George Davey Smith

Erratum issuedAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PLoS genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1,705 papers, 11 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1,705citing papers in PubMed, 11 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

1,705 citing papers in PubMed, 11 syntheses or guidelines pooled it.

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  10. The genetics of cannabis lifetime use.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026
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1,645 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Gibran HemaniMRC Integrative Epidemiology Unit (IEU) at the University of Bristol, School of Social and Community Medicine, Bristol, United Kingdom.ORCID http://orcid.org/0000-0003-0920-1055
Kate TillingMRC Integrative Epidemiology Unit (IEU) at the University of Bristol, School of Social and Community Medicine, Bristol, United Kingdom.
George Davey SmithMRC Integrative Epidemiology Unit (IEU) at the University of Bristol, School of Social and Community Medicine, Bristol, United Kingdom.ORCID http://orcid.org/0000-0002-1407-8314

Funding

Medical Research Council MC_UU_12013/1Medical Research Council MC_UU_12013/9
6 · The paper itself

Abstract

Inference about the causal structure that induces correlations between two traits can be achieved by combining genetic associations with a mediation-based approach, as is done in the causal inference test (CIT). However, we show that measurement error in the phenotypes can lead to the CIT inferring the wrong causal direction, and that increasing sample sizes has the adverse effect of increasing confidence in the wrong answer. This problem is likely to be general to other mediation-based approaches. Here we introduce an extension to Mendelian randomisation, a method that uses genetic associations in an instrumentation framework, that enables inference of the causal direction between traits, with some advantages. First, it can be performed using only summary level data from genome-wide association studies; second, it is less susceptible to bias in the presence of measurement error or unmeasured confounding. We apply the method to infer the causal direction between DNA methylation and gene expression levels. Our results demonstrate that, in general, DNA methylation is more likely to be the causal factor, but this result is highly susceptible to bias induced by systematic differences in measurement error between the platforms, and by horizontal pleiotropy. We emphasise that, where possible, implementing MR and appropriate sensitivity analyses alongside other approaches such as CIT is important to triangulate reliable conclusions about causality.

Indexed as

BiasDNA MethylationGene Expression RegulationGenetic Association StudiesGenome-Wide Association StudyMendelian Randomization AnalysisPhenotypeSample Size

Identifiers

PMID29149188
PMCPMC5711033

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Registered trials

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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.