Evidence map›Paper›PMID 40766617›Full record

ArticlebioRxiv : the preprint server for biology2025

Escape from X inactivation drives sex differences and female trait variation.

Carrie Zhu, Liaoyi Xu, Arbel Harpak

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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

5 · Who and what money

Authors and funding

3 authors.

Carrie ZhuDepartment of Integrative Biology, University of Texas at Austin, Austin, TX, USA.
Liaoyi XuDepartment of Integrative Biology, University of Texas at Austin, Austin, TX, USA.ORCID 0000-0002-7198-3353
Arbel HarpakDepartment of Integrative Biology, University of Texas at Austin, Austin, TX, USA.ORCID 0000-0002-3655-748X

Funding

Making Genomic Prediction of Complex Disease EquitableR35GM151108 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI Arbel Harpak · 2023 to 2026
$1.6M
NIGMS NIH HHS R35 GM151108
6 · The paper itself

Abstract

X chromosome inactivation (XCI) partially balances gene dosage between sexes, yet expression from the inactive X (Xi) is variable across genes. In this study, we investigate whether gene-level Xi expression predicts transcriptional and phenotypic consequences of X-linked variation. We find that Xi expression levels are a strong linear predictor of female-male expression differences, suggesting that other compensatory or regulatory mechanisms play a more minor role in sex differences in X-linked gene expression. Among females, we identify three traits-lymphocyte percentage, HbA1c, and schizophrenia-for which higher Xi expression correlates with the strength of evidence for dominance effects. We hypothesize that an underappreciated mechanism could generate dominance effects of X-linked variants on a trait-specifically when the variant influences skew in X inactivation. This work establishes Xi expression as essential for understanding sex differences and the female-specific genetic basis of disease.

Identifiers

PMID40766617
PMCPMC12324440

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.