Evidence map›Paper›PMID 30188969›Full record

ArticleAmerican journal of epidemiology2018

Invited Commentary: Detecting Individual and Global Horizontal Pleiotropy in Mendelian Randomization-A Job for the Humble Heterogeneity Statistic?

Jack Bowden, Gibran Hemani, George Davey Smith

Abstract readComment
In one paragraph

Article in American journal of epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 177 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
177citing papers in PubMed, 8 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

177 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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117 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.

Jack BowdenMRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.
Gibran HemaniMRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.
George Davey SmithMRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.

Funding

Medical Research Council MC_UU_00011/1Medical Research Council MC_UU_00011/2Wellcome Trust 208806/Z/17/Z
6 · The paper itself

Abstract

Mendelian randomization (MR) is gaining in recognition and popularity as a method for strengthening causal inference in epidemiology by utilizing genetic variants as instrumental variables. Concurrently with the explosion in empirical MR studies, there has been the steady production of new approaches for MR analysis. The recently proposed "global and individual tests for direct effects" (GLIDE) approach fits into a family of methods that aim to detect horizontal pleiotropy-at the individual single nucleotide polymorphism level and at the global level-and to adjust the analysis by removing outlying single nucleotide polymorphisms. In this commentary, we explain how existing methods can (and indeed are) being used to detect pleiotropy at the individual and global levels, although not explicitly using this terminology. By doing so, we show that the true comparator for GLIDE is not MR-Egger regression (as Dai et al., the authors of the accompanying article (Am J Epidemiol. 2018;187(12):2672-2680), claim) but rather the humble heterogeneity statistic.

Indexed as

Mendelian Randomization AnalysisPolymorphism, Single Nucleotide

Identifiers

PMID30188969
PMCPMC6269239

What OpenQuestion holds

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LicenceCC BY
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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.