Evidence map›Paper›PMID 42458269›Full record

ArticleBMC genomics2026

Identifying sex-specific genetic effects across 733 traits in UK biobank.

Wei Jiang, Yueqian Jing, James Han, Yixuan Ye, Hongyu Zhao

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PubMed Full text at PMC Publisher
In one paragraph

Article in BMC genomics, 2026. 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

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

5 authors.

Wei Jiang *Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
Yueqian Jing *Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
James Han *Department of Statistics and Data Science, Yale University, New Haven, CT, USA.
Yixuan YeProgram of Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA.
Hongyu ZhaoDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA. hongyu.zhao@yale.edu.

Funding

Novel statistical methods and tools to integrate multiple endophenotypes and functional annotation data to study the roles of rare variants in complex human diseases using sequencing dataR01GM134005 · NIGMS · YALE UNIVERSITY · PI WU, BAOLIN, ZHAO, HONGYU · 2020 to 2023
$1.6M
NIGMS NIH HHS R01 GM134005NIH HHS R01 GM134005
6 · The paper itself

Abstract

Sex-specificity has been reported in a wide range of diseases and complex traits. While sex-specific genetic effects have been documented for certain traits, the genetic mechanisms underlying sex differences in most traits remain largely unexplored. With its large sample size and wide range of diseases and traits, the UK Biobank-a large, prospective cohort study containing health history, phenotypic measurements, and genetic data for over 500,000 individuals-provides an opportunity to explore sexually dimorphic genetic architectures in a large number of traits and diseases. Here, we present a sex-specific analysis of 733 sex-stratified complex trait GWAS for 361,194 white British individuals in the UK Biobank. Among these 733 traits, we detected sex-specific locus in 520 of them. These 520 candidate traits with sex-specific genetic effects were classified to 270 distinct groups. Using a systematic sex-specific discovery-replication analysis, we identify 489 loci showing sex-specific effects on 127 of the candidate trait groups, among which three of them having the most numbers of traits showing replicable signals were further investigated, including fat mass related traits (12 traits), heart disease related traits (7 traits) and body impedance related traits (6 traits). We identify pathways with sex-biased enrichment patterns from exploratory enrichment analyses based on QTL-associated genes. In addition, we present further evidence for significant sex-specific genetic effects in 25 traits by comparing the prediction performance of sex-specific polygenic risk scores (PRS).

Indexed as

Biological Specimen BanksSex CharacteristicsFemaleGenetic Risk ScoreGenome-Wide Association StudyHumansMaleMultifactorial InheritancePhenotypePolymorphism, Single NucleotideQuantitative Trait LociUK BiobankUnited KingdomComplex traitsPathway analysisPolygenic risk scoreSex specific effectsSex-stratified GWASSexual dimorphismUK Biobank

Identifiers

PMID42458269
PMCPMC13647673

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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.