Evidence map›Paper›PMID 39119976›Full record

ArticleJournal of the American Heart Association2024

Mendelian Randomization and Bayesian Colocalization Analysis Implicate Glycoprotein VI as a Potential Drug Target for Cardioembolic Stroke in South Asian Populations.

Siwei Wu, Devendra Meena, James Yarmolinsky, Dipender Gill, Alexander Smith, Marie-Joe Dib, Ganesh Chauhan, Anand Rohatgi, Abbas Dehghan, Ioanna Tzoulaki

Abstract read
In one paragraph

Article in Journal of the American Heart Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

10 authors.

Siwei WuDepartment of Epidemiology and Biostatistics School of Public Health, Imperial College London London United Kingdom.
Devendra MeenaDepartment of Epidemiology and Biostatistics School of Public Health, Imperial College London London United Kingdom.
James YarmolinskyDepartment of Epidemiology and Biostatistics School of Public Health, Imperial College London London United Kingdom.
Dipender GillDepartment of Epidemiology and Biostatistics School of Public Health, Imperial College London London United Kingdom.ORCID 0000-0001-7312-7078
Alexander SmithDepartment of Epidemiology and Biostatistics School of Public Health, Imperial College London London United Kingdom.ORCID 0000-0001-6418-613X
Marie-Joe DibDivision of Cardiovascular Medicine Hospital of the University of Pennsylvania Philadelphia PA USA.ORCID 0000-0001-7591-5684
Ganesh ChauhanDepartment of Genetics & Genomics Rajendra Institute of Medical Sciences (RIMS) Ranchi India.ORCID 0000-0002-8564-5021
Anand RohatgiDepartment of Medicine, Division of Cardiology University of Texas Southwestern Medical Center Dallas TX USA.ORCID 0000-0003-0164-2382
Abbas DehghanDepartment of Epidemiology and Biostatistics School of Public Health, Imperial College London London United Kingdom.ORCID 0000-0001-6403-016X
Ioanna TzoulakiDepartment of Epidemiology and Biostatistics School of Public Health, Imperial College London London United Kingdom.ORCID 0000-0002-4275-9328

Funding

Lipoprotein Metabolism and Excess Cardiometabolic Risk in South AsiansR01HL162300 · NHLBI · UT SOUTHWESTERN MEDICAL CENTER · PI Anand Kumar Rohatgi · 2022 to 2026
$2.9M
Mentoring Patient-Oriented Research in Deep Lipid Phenotyping for Cardiovascular DiseaseK24HL146838 · NHLBI · UT SOUTHWESTERN MEDICAL CENTER · PI Anand Kumar Rohatgi · 2019 to 2026
$945k
NHLBI NIH HHS K24 HL146838NHLBI NIH HHS R01 HL162300
6 · The paper itself

Abstract

backgroundCirculating plasma proteins are clinically useful biomarkers for stroke risk. We examined the causal links between plasma proteins and stroke risk in individuals of South Asian ancestry. METHODS AND

resultsWe applied proteome-wide Mendelian randomization and colocalization approaches to understand causality of 2922 plasma proteins on stroke risk in individuals of South Asian ancestry. We obtained genetic instruments (proxies) for plasma proteins from the UK Biobank (N=920). Genome-wide association studies summary data for strokes (N≤11 312) were sourced from GIGASTROKE consortium. Our primary approach involved the Wald ratio or inverse-variance-weighted methods, with statistical significance set at false discovery rate <0.1. Additionally, a Bayesian colocalization approach assessed shared causal variants among proteome, transcriptome, and stroke phenotypes to minimize bias from linkage disequilibrium. We found evidence of a potential causal effect of plasma GP6 (glycoprotein VI) levels on cardioembolic stroke (odds ratio [OR]

conclusionsOur joint Mendelian randomization and colocalization analyses suggest that genetically predicted GP6 is potentially causally associated with cardioembolic stroke risk in individuals of South Asian ancestry. As genetic data on individuals of South Asian ancestry increase, future Mendelian randomization studies with larger sample size for plasma GP6 levels should be implemented to further validate our findings. Additionally, clinical studies will be necessary to verify GP6 as a therapeutic target for cardioembolic stroke in South Asians.

Indexed as

Embolic StrokePlatelet Membrane GlycoproteinsSouth Asian PeopleAgedBayes TheoremBiomarkersFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMaleMendelian Randomization AnalysisMiddle AgedPolymorphism, Single NucleotideRisk AssessmentRisk FactorsBiomarkersPlatelet Membrane Glycoproteinsplatelet membrane glycoprotein VIcardioembolicGP6Mendelian randomizationSouth Asian ancestrystroke

Identifiers

PMID39119976
PMCPMC11963915

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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.