Evidence map›Paper›PMID 38969939›Full record

ArticleHuman genetics2024

Fine mapping of candidate effector genes for heart rate.

Julia Ramírez, Stefan van Duijvenboden, William J Young, Yutang Chen, Tania Usman, Michele Orini, Pier D Lambiase, Andrew Tinker, Christopher G Bell, Andrew P Morris and 1 more

Abstract read
In one paragraph

Article in Human genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Julia Ramírez *Aragon Institute of Engineering Research, University of Zaragoza, Zaragoza, Spain. Julia.Ramirez@unizar.es.
Stefan van Duijvenboden *William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK. stefan.vanduijvenboden@ndph.ox.ac.uk.
William J YoungWilliam Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.
Yutang ChenWilliam Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.
Tania UsmanKings College London, London, UK.
Michele OriniInstitute of Cardiovascular Science, University College London, London, UK.
Pier D LambiaseInstitute of Cardiovascular Science, University College London, London, UK.
Andrew TinkerWilliam Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.
Christopher G BellWilliam Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.
Andrew P MorrisCentre for Musculoskeletal Research, The University of Manchester, Manchester, UK.
Patricia B MunroeWilliam Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK. p.b.munroe@qmul.ac.uk.

Funding

Medical Research Council MR/N025083/1
6 · The paper itself

Abstract

An elevated resting heart rate (RHR) is associated with increased cardiovascular mortality. Genome-wide association studies (GWAS) have identified > 350 loci. Uniquely, in this study we applied genetic fine-mapping leveraging tissue specific chromatin segmentation and colocalization analyses to identify causal variants and candidate effector genes for RHR. We used RHR GWAS summary statistics from 388,237 individuals of European ancestry from UK Biobank and performed fine mapping using publicly available genomic annotation datasets. High-confidence causal variants (accounting for > 75% posterior probability) were identified, and we collated candidate effector genes using a multi-omics approach that combined evidence from colocalisation with molecular quantitative trait loci (QTLs), and long-range chromatin interaction analyses. Finally, we performed druggability analyses to investigate drug repurposing opportunities. The fine mapping pipeline indicated 442 distinct RHR signals. For 90 signals, a single variant was identified as a high-confidence causal variant, of which 22 were annotated as missense. In trait-relevant tissues, 39 signals colocalised with cis-expression QTLs (eQTLs), 3 with cis-protein QTLs (pQTLs), and 75 had promoter interactions via Hi-C. In total, 262 candidate genes were highlighted (79% had promoter interactions, 15% had a colocalised eQTL, 8% had a missense variant and 1% had a colocalised pQTL), and, for the first time, enrichment in nervous system pathways. Druggability analyses highlighted ACHE, CALCRL, MYT1 and TDP1 as potential targets. Our genetic fine-mapping pipeline prioritised 262 candidate genes for RHR that warrant further investigation in functional studies, and we provide potential therapeutic targets to reduce RHR and cardiovascular mortality.

Indexed as

Chromosome MappingGenome-Wide Association StudyHeart RatePolymorphism, Single NucleotideQuantitative Trait LociFemaleHumansMale

Identifiers

PMID38969939
PMCPMC11485034

What Socratic holds

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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 Socratic graph.