Evidence map›Paper›PMID 42365073›Full record

ArticleNPJ systems biology and applications2026

Gene prioritization across ancestries uncovers distinct molecular pathophysiology and therapeutic landscape in polycystic ovary syndrome.

Sindhuja Rajavelu, Debojyoti De

Abstract read
In one paragraph

Article in NPJ systems biology and applications, 2026. 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

2 authors.

Sindhuja RajaveluDepartment of Biotechnology, National Institute of Technology Durgapur, Durgapur, India.
Debojyoti DeDepartment of Biotechnology, National Institute of Technology Durgapur, Durgapur, India. dde.bt@nitdgp.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Polycystic ovary syndrome (PCOS) is a highly prevalent and heterogeneous endocrine disorder affecting women of reproductive age, with substantial reproductive, metabolic, and long-term health consequences. While genome-wide association studies (GWAS) have identified multiple PCOS-associated loci across diverse populations, the functional interpretation of these predominantly non-coding variants and their translation into clinically actionable targets remain unresolved. Here, we present an integrative population-aware framework that systematically combines regulatory functional genomics, long-range chromatin interactions, genome-wide quantitative trait loci, and protein-protein interaction networks to prioritize effector genes underlying PCOS susceptibility. Applying this framework to East Asian and European populations, we demonstrate robust performance relative to existing approaches and uncover both shared and population-specific functions. Notably, our analyses reveal a predominant enrichment of metabolic dysregulation-associated pathways in East Asian PCOS, whereas European PCOS exhibits a stronger inflammatory and immune-related signature. These population-specific molecular phenotypes were further supported by transcriptomic data from PCOS patient samples. Importantly, integration of genetic evidence with a network-based approach enabled the identification of druggable targets lacking direct genetic cues. Collectively, our study provides mechanistic insight into the ethnic heterogeneity of PCOS and establishes a scalable strategy for genetically informed, population-specific therapeutic prioritization, advancing precision medicine approaches for women's health.

Indexed as

Polycystic Ovary SyndromeFemaleGene Regulatory NetworksGenetic Predisposition to DiseaseGenome-Wide Association StudyGenomicsHumansPhenotypePolymorphism, Single NucleotideProtein Interaction MapsQuantitative Trait Loci

Identifiers

PMID42365073
PMCPMC13677733

What OpenQuestion holds

Textmetadata
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.