Evidence map›Paper›PMID 35452592›Full record

ReviewAmerican journal of human genetics2022

Combining evidence from Mendelian randomization and colocalization: Review and comparison of approaches.

Verena Zuber, Nastasiya F Grinberg, Dipender Gill, Ichcha Manipur, Eric A W Slob, Ashish Patel, Chris Wallace, Stephen Burgess

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in American journal of human genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 337 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
337citing papers in PubMed, 9 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

337 citing papers in PubMed, 9 syntheses or guidelines pooled it.

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  18. Exploring potential biomarkers of diffuse large B-cell lymphoma through multi-dimensional data.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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277 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

8 authors.

Verena ZuberDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; UK Dementia Research Institute at Imperial College, Imperial College London, London, UK.
Nastasiya F GrinbergNational Institute of Agricultural Botany, Cambridge, UK.
Dipender GillDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; Clinical Pharmacology and Therapeutics Section, Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George's, University of London, London, UK; Clinical Pharmacology Group, Pharmacy and Medicines Directorate, St George's University Hospitals NHS Foundation Trust, London, UK; Genetics Department, Novo Nordisk Research Centre Oxford, Oxford, UK.
Ichcha ManipurCambridge Institute of Therapeutic Immunology & Infectious Disease, University of Cambridge, Cambridge, UK; Department of Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
Eric A W SlobMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
Ashish PatelMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
Chris WallaceCambridge Institute of Therapeutic Immunology & Infectious Disease, University of Cambridge, Cambridge, UK; Department of Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
Stephen BurgessMRC Biostatistics Unit, University of Cambridge, Cambridge, UK; Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. Electronic address: sb452@medschl.cam.ac.uk.

Funding

Medical Research Council MC_PC_17228Medical Research Council MC_QA137853Medical Research Council MC_UU_00002/4Medical Research Council MC_UU_00002/7Medical Research Council MR/S019669/1Medical Research Council MR/W029790/1Wellcome Trust 204623Wellcome Trust 220788
6 · The paper itself

Abstract

Mendelian randomization and colocalization are two statistical approaches that can be applied to summarized data from genome-wide association studies (GWASs) to understand relationships between traits and diseases. However, despite similarities in scope, they are different in their objectives, implementation, and interpretation, in part because they were developed to serve different scientific communities. Mendelian randomization assesses whether genetic predictors of an exposure are associated with the outcome and interprets an association as evidence that the exposure has a causal effect on the outcome, whereas colocalization assesses whether two traits are affected by the same or distinct causal variants. When considering genetic variants in a single genetic region, both approaches can be performed. While a positive colocalization finding typically implies a non-zero Mendelian randomization estimate, the reverse is not generally true: there are several scenarios which would lead to a non-zero Mendelian randomization estimate but lack evidence for colocalization. These include the existence of distinct but correlated causal variants for the exposure and outcome, which would violate the Mendelian randomization assumptions, and a lack of strong associations with the outcome. As colocalization was developed in the GWAS tradition, typically evidence for colocalization is concluded only when there is strong evidence for associations with both traits. In contrast, a non-zero estimate from Mendelian randomization can be obtained despite only nominally significant genetic associations with the outcome at the locus. In this review, we discuss how the two approaches can provide complementary information on potential therapeutic targets.

Indexed as

Genome-Wide Association StudyMendelian Randomization AnalysisCausalityHumansPhenotypeCausal inferenceGenetic epidemiologyphenome-wide association studypost-GWAS investigationsshared heritability

Identifiers

PMID35452592
PMCPMC7612737

What OpenQuestion holds

Textmetadata
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.