Evidence map›Paper›PMID 38656964›Full record

SynthesisPLoS genetics2024

Better together against genetic heterogeneity: A sex-combined joint main and interaction analysis of 290 quantitative traits in the UK Biobank.

Boxi Lin, Andrew D Paterson, Lei Sun

Abstract readMeta-Analysis
In one paragraph

Synthesis in PLoS genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Sex-Specific Genetic Architecture and Comorbidities of Alcohol Use Behaviors.medRxiv : the preprint server for health sciences · 2025
    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

3 authors.

Boxi LinDivision of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.ORCID 0000-0003-4555-2901
Andrew D PatersonDivision of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
Lei SunDivision of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.ORCID 0000-0002-5640-937X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic effects can be sex-specific, particularly for traits such as testosterone, a sex hormone. While sex-stratified analysis provides easily interpretable sex-specific effect size estimates, the presence of sex-differences in SNP effect implies a SNP×sex interaction. This suggests the usage of the often overlooked joint test, testing for an SNP's main and SNP×sex interaction effects simultaneously. Notably, even without individual-level data, the joint test statistic can be derived from sex-stratified summary statistics through an omnibus meta-analysis. Utilizing the available sex-stratified summary statistics of the UK Biobank, we performed such omnibus meta-analyses for 290 quantitative traits. Results revealed that this approach is robust to genetic effect heterogeneity and can outperform the traditional sex-stratified or sex-combined main effect-only tests. Therefore, we advocate using the omnibus meta-analysis that captures both the main and interaction effects. Subsequent sex-stratified analysis should be conducted for sex-specific effect size estimation and interpretation.

Indexed as

Genetic HeterogeneityPolymorphism, Single NucleotideQuantitative Trait, HeritableFemaleGenome-Wide Association StudyHumansMalePhenotypeQuantitative Trait LociTestosteroneUK BiobankUnited KingdomTestosterone

Identifiers

PMID38656964
PMCPMC11073786

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.