Evidence map›Paper›PMID 28569269›Full record

ReviewNature reviews. Cardiology2017

Mendelian randomization in cardiometabolic disease: challenges in evaluating causality.

Michael V Holmes, Mika Ala-Korpela, George Davey Smith

Open access · greenAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Nature reviews. Cardiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 399 papers, 16 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
399citing papers in PubMed, 16 pooled it
44.7field-weighted citation impact, top 1% of its field
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

399 citing papers in PubMed, 16 syntheses or guidelines pooled it, 734 citations in OpenAlex.

  1. Urate-lowering effects of losartan: a meta-analysis of randomised controlled trials and target trial emulation.Hypertension research : official journal of the Japanese Society of Hypertension · 2026
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339 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 at 2 institutions in 1 country.

Michael V HolmesMedical Research Council Population Health Research Unit, University of Oxford, Roosevelt Drive, Oxford OX3 7LF, UK.
Mika Ala-KorpelaMedical Research Council Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
George Davey SmithMedical Research Council Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
Medical Research Council · GBUniversity of Oxford · GB

Funding

Medical Research Council MC_U137686851Medical Research Council MC_UU_12013/1Medical Research Council MC_UU_12026/2
6 · The paper itself

Abstract

Mendelian randomization (MR) is a burgeoning field that involves the use of genetic variants to assess causal relationships between exposures and outcomes. MR studies can be straightforward; for example, genetic variants within or near the encoding locus that is associated with protein concentrations can help to assess their causal role in disease. However, a more complex relationship between the genetic variants and an exposure can make findings from MR more difficult to interpret. In this Review, we describe some of these challenges in interpreting MR analyses, including those from studies using genetic variants to assess causality of multiple traits (such as branched-chain amino acids and risk of diabetes mellitus); studies describing pleiotropic variants (for example, C-reactive protein and its contribution to coronary heart disease); and those investigating variants that disrupt normal function of an exposure (for example, HDL cholesterol or IL-6 and coronary heart disease). Furthermore, MR studies on variants that encode enzymes responsible for the metabolism of an exposure (such as alcohol) are discussed, in addition to those assessing the effects of variants on time-dependent exposures (extracellular superoxide dismutase), cumulative exposures (LDL cholesterol), and overlapping exposures (triglycerides and non-HDL cholesterol). We elaborate on the molecular features of each relationship, and provide explanations for the likely causal associations. In doing so, we hope to contribute towards more reliable evaluations of MR findings.

Indexed as

BiomarkersCholesterol, HDLCholesterol, LDLCoronary DiseaseGenetic Predisposition to DiseaseGenetic VariationHumansMendelian Randomization AnalysisMultifactorial InheritancePolymorphism, Single NucleotideRisk FactorsBiomarkersCholesterol, HDLCholesterol, LDL

Identifiers

PMID28569269
PMCPMC5600813
OpenAlexW2620908531

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.