Evidence map›Paper›PMID 37253997›Full record

ArticleEuropean journal of epidemiology2023

Falsification of the instrumental variable conditions in Mendelian randomization studies in the UK Biobank.

Kelly Guo, Elizabeth W Diemer, Jeremy A Labrecque, Sonja A Swanson

Open access · hybridAbstract read
In one paragraph

Article in European journal of epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.5field-weighted citation impact, top 10% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

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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

4 authors at 2 institutions in 2 countries.

Kelly GuoDepartment of Epidemiology, Erasmus MC, Rotterdam, the Netherlands. k.guo@erasmusmc.nl.ORCID http://orcid.org/0000-0002-7474-7663
Elizabeth W DiemerDepartment of Child and Adolescent Psychiatry, Erasmus MC, Rotterdam, the Netherlands.
Jeremy A LabrecqueDepartment of Epidemiology, Erasmus MC, Rotterdam, the Netherlands.
Sonja A SwansonDepartment of Epidemiology, Erasmus MC, Rotterdam, the Netherlands.
Erasmus MC · NLHarvard University · US

Funding

ZonMw 91617066
6 · The paper itself

Abstract

Mendelian randomization (MR) is an increasingly popular approach to estimating causal effects. Although the assumptions underlying MR cannot be verified, they imply certain constraints, the instrumental inequalities, which can be used to falsify the MR conditions. However, the instrumental inequalities are rarely applied in MR. We aimed to explore whether the instrumental inequalities could detect violations of the MR conditions in case studies analyzing the effect of commonly studied exposures on coronary artery disease risk.Using 1077 single nucleotide polymorphisms (SNPs), we applied the instrumental inequalities to MR models for the effects of vitamin D concentration, alcohol consumption, C-reactive protein (CRP), triglycerides, high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol on coronary artery disease in the UK Biobank. For their relevant exposure, we applied the instrumental inequalities to MR models proposing each SNP as an instrument individually, and to MR models proposing unweighted allele scores as an instrument. We did not identify any violations of the MR assumptions when proposing each SNP as an instrument individually. When proposing allele scores as instruments, we detected violations of the MR assumptions for 5 of 6 exposures.Within our setting, this suggests the instrumental inequalities can be useful for identifying violations of the MR conditions when proposing multiple SNPs as instruments, but may be less useful in determining which SNPs are not instruments. This work demonstrates how incorporating the instrumental inequalities into MR analyses can help researchers to identify and mitigate potential bias.

Indexed as

Coronary Artery DiseaseBiological Specimen BanksCholesterolCholesterol, HDLGenome-Wide Association StudyHumansMendelian Randomization AnalysisPolymorphism, Single NucleotideUnited KingdomCholesterolCholesterol, HDLCausal inferenceCoronary artery diseaseFalsificationInstrumental inequalitiesMendelian randomizationUK Biobank

Identifiers

PMID37253997
PMCPMC10501946
OpenAlexW4378781768

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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.