Evidence map›Paper›PMID 38379245›Full record

ArticleGenetic epidemiology2024

Robust use of phenotypic heterogeneity at drug target genes for mechanistic insights: Application of cis-multivariable Mendelian randomization to GLP1R gene region.

Ashish Patel, Dipender Gill, Dmitry Shungin, Christos S Mantzoros, Lotte Bjerre Knudsen, Jack Bowden, Stephen Burgess

Abstract read
In one paragraph

Article in Genetic epidemiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–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

23 citing papers in PubMed.

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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

7 authors.

Ashish PatelMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.ORCID 0000-0002-0350-4365
Dipender GillDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
Dmitry ShunginHuman Genetics Centre of Excellence, AI and Digital Research, Novo Nordisk, Bagsværd, Denmark.
Christos S MantzorosDepartment of Internal Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.
Lotte Bjerre KnudsenChief Scientific Advisor Office, Research and Early Development, Novo Nordisk, Bagsværd, Denmark.
Jack BowdenDepartment of Clinical and Biomedical Sciences, University of Exeter, Exeter, UK.
Stephen BurgessMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.ORCID 0000-0001-5365-8760

Funding

Department of Health IS-BRC-1215-20014Medical Research Council MC-UU-00002/7National Institute for Health Research Cambridge Biomedical Research CentreUnited Kingdom Research and Innovation Medical Research CouncilWellcome Trust 204623Wellcome Trust 204623/Z/16/ZWellcome Trust 225790Wellcome Trust 225790/Z/22/ZWellcome Trust and Royal Society
6 · The paper itself

Abstract

Phenotypic heterogeneity at genomic loci encoding drug targets can be exploited by multivariable Mendelian randomization to provide insight into the pathways by which pharmacological interventions may affect disease risk. However, statistical inference in such investigations may be poor if overdispersion heterogeneity in measured genetic associations is unaccounted for. In this work, we first develop conditional F statistics for dimension-reduced genetic associations that enable more accurate measurement of phenotypic heterogeneity. We then develop a novel extension for two-sample multivariable Mendelian randomization that accounts for overdispersion heterogeneity in dimension-reduced genetic associations. Our empirical focus is to use genetic variants in the GLP1R gene region to understand the mechanism by which GLP1R agonism affects coronary artery disease (CAD) risk. Colocalization analyses indicate that distinct variants in the GLP1R gene region are associated with body mass index and type 2 diabetes (T2D). Multivariable Mendelian randomization analyses that were corrected for overdispersion heterogeneity suggest that bodyweight lowering rather than T2D liability lowering effects of GLP1R agonism are more likely contributing to reduced CAD risk. Tissue-specific analyses prioritized brain tissue as the most likely to be relevant for CAD risk, of the tissues considered. We hope the multivariable Mendelian randomization approach illustrated here is widely applicable to better understand mechanisms linking drug targets to diseases outcomes, and hence to guide drug development efforts.

Indexed as

Body Mass IndexCoronary Artery DiseaseDiabetes Mellitus, Type 2Glucagon-Like Peptide-1 ReceptorMendelian Randomization AnalysisPhenotypeGenetic Predisposition to DiseaseHumansPolymorphism, Single NucleotideGlucagon-Like Peptide-1 Receptordrug target Mendelian randomizationGLP1R agonistsoverdispersion heterogeneityphenotypic heterogeneity

Identifiers

PMID38379245
PMCPMC7616158

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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.