Evidence map›Paper›PMID 36388766›Full record

ArticleCell genomics2022

Proteome-wide Mendelian randomization in global biobank meta-analysis reveals multi-ancestry drug targets for common diseases.

Huiling Zhao, Humaria Rasheed, Therese Haugdahl Nøst, Yoonsu Cho, Yi Liu, Laxmi Bhatta, Arjun Bhattacharya, Global Biobank Meta-analysis Initiative, Gibran Hemani, George Davey Smith and 5 more

Open access · goldAbstract read
In one paragraph

Article in Cell genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 2 pooled it
13.3field-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

55 citing papers in PubMed, 2 syntheses or guidelines pooled it, 79 citations in OpenAlex.

  1. Pooled it
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  3. Proteogenomics in human populations.Nature reviews. Genetics · 2026
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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

15 authors at 6 institutions in 4 countries.

Huiling ZhaoMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
Humaria RasheedMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
Therese Haugdahl NøstK.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.
Yoonsu ChoMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
Yi LiuMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
Laxmi BhattaK.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.
Arjun BhattacharyaDepartment of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
Global Biobank Meta-analysis Initiative
Gibran HemaniMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
George Davey SmithMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
Ben Michael BrumptonDivision of Medicine and Laboratory Sciences, University of Oslo, Oslo, Norway.
Wei ZhouDepartment of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI 48109, USA.
Benjamin M NealeAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA.
Tom R GauntMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
Jie ZhengMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
University of Bristol · GBBroad Institute · USNorwegian University of Science and Technology · NOUniversity of Oslo · NOQB3 · USShanghai Jiao Tong University · CN

Funding

Cancer Research UK 29019Medical Research Council MC_PC_17228Medical Research Council MC_QA137853Medical Research Council MC_UU_00011/1Medical Research Council MC_UU_00011/4Wellcome Trust
6 · The paper itself

Abstract

Proteome-wide Mendelian randomization (MR) shows value in prioritizing drug targets in Europeans but with limited evidence in other ancestries. Here, we present a multi-ancestry proteome-wide MR analysis based on cross-population data from the Global Biobank Meta-analysis Initiative (GBMI). We estimated the putative causal effects of 1,545 proteins on eight diseases in African (32,658) and European (1,219,993) ancestries and identified 45 and 7 protein-disease pairs with MR and genetic colocalization evidence in the two ancestries, respectively. A multi-ancestry MR comparison identified two protein-disease pairs with MR evidence in both ancestries and seven pairs with specific effects in the two ancestries separately. Integrating these MR signals with clinical trial evidence, we prioritized 16 pairs for investigation in future drug trials. Our results highlight the value of proteome-wide MR in informing the generalizability of drug targets for disease prevention across ancestries and illustrate the value of meta-analysis of biobanks in drug development.

Indexed as

complex diseasesdrug target prioritizationmulti-ancestry Mendelian randomizationplasma proteome

Identifiers

PMID36388766
PMCPMC9646482
OpenAlexW4304777503

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.