Evidence map›Paper›PMID 39072021›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Genome-wide fine-mapping improves identification of causal variants.

Yang Wu, Zhili Zheng, Loic Thibaut, Tian Lin, Qian Feng, Hao Cheng, Loic Yengo, Michael E Goddard, Naomi R Wray, Peter M Visscher and 1 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Yang WuInstitute of Rare Diseases, West China Hospital of Sichuan University, Chengdu, China.
Zhili ZhengInstitute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
Loic ThibautInstitute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
Tian LinInstitute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
Qian FengInstitute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
Hao ChengDepartment of Animal Science, University of California, Davis, CA, USA.
Loic YengoInstitute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
Michael E GoddardFaculty of Veterinary and Agricultural Science, University of Melbourne, Parkville, Victoria, Australia.
Naomi R WrayInstitute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.ORCID 0000-0001-7421-3357
Peter M VisscherInstitute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
Jian ZengInstitute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.

Funding

2/2 Genetics at an extreme: an efficient genomic study of individuals with clinically severe major depression receiving ECTR01MH121545 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SULLIVAN, PATRICK F · 2019 to 2023
$2.9M
NIMH NIH HHS R01 MH121545
6 · The paper itself

Abstract

Fine-mapping refines genotype-phenotype association signals to identify causal variants underlying complex traits. However, current methods typically focus on individual genomic loci and do not account for the global genetic architecture. Here, we demonstrate the advantages of performing genome-wide fine-mapping (GWFM) with functional annotations and develop methods to facilitate GWFM. In simulations and real data analyses, GWFM outperforms current methods across multiple metrics, including error control, mapping power, resolution, precision, replication rate, and trans-ancestry phenotype prediction. Across 48 complex traits, we identify credible sets that collectively explain 18% of the SNP-based heritability (

Identifiers

PMID39072021
PMCPMC11275676

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.