Evidence map›Paper›PMID 42213658›Full record

ArticlePloS one2026

GSEA and the coexpression network approach identify novel pathway connections of molecular processes affected in Porto-sinusoidal vascular disease.

Aishwarya Iyer, Cenna Doornbos, Chris Evelo, Martina Kutmon, Friederike Ehrhart

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

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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

5 authors.

Aishwarya IyerDepartment of Translational Genomics NUTRIM/MHeNs, Maastricht University, Maastricht, The Netherlands.ORCID https://orcid.org/0000-0003-2878-4049
Cenna DoornbosMedical BioSciences Department, Radboud University, Nijmegen, The Netherlands.ORCID https://orcid.org/0000-0002-0613-3651
Chris EveloDepartment of Translational Genomics NUTRIM/MHeNs, Maastricht University, Maastricht, The Netherlands.
Martina KutmonMaastricht Centre for Systems Biology and Bioinformatics(MaCSBio), Maastricht University, Maastricht, The Netherlands.
Friederike EhrhartDepartment of Translational Genomics NUTRIM/MHeNs, Maastricht University, Maastricht, The Netherlands.ORCID https://orcid.org/0000-0002-7770-620X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPorto-sinusoidal vascular disease (PSVD) is a complex, rare liver disease characterized by the absence of cirrhosis, with or without the presence of portal hypertension or histological lesions. Given the knowledge gaps in the mechanisms involved in this disease with unknown etiology, we used omics-based approaches to further elucidate the pathways affected by PSVD, facilitating improvements in the prognosis, diagnosis, and treatment options for these patients.

methodsWe applied gene set enrichment analysis (GSEA) and weighted gene coexpression network analysis (WGCNA) to identify pathways dysregulated in PSVD. Network construction and visualization were performed in Cytoscape to explore interconnectivity among enriched processes. Within key modules, candidate genes were prioritized by ranking approaches and cross-referenced with findings from previous studies. RESULTS AND

conclusionIn this study using both module eigengene correlation network analysis and GSEA, a novel coordinated dysregulation in PSVD was identified characterized by the simultaneous activation of immune and signaling pathways alongside the suppression of metabolic, ribosomal, and mitochondrial programs, highlighting a critical antagonistic interplay between these systems. Alterations in ribosomal proteins, ATP synthase subunits, and serpin family members highlight translational, bioenergetic, and anticoagulant dysfunction as core mechanisms. Together, these findings define PSVD as a disorder of integrated immune, vascular, and metabolic imbalance.

Indexed as

Gene Regulatory NetworksVascular DiseasesGene Expression ProfilingHumansIdiopathic Noncirrhotic Portal HypertensionSignal Transduction

Identifiers

PMID42213658
PMCPMC13220999

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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 Socratic graph.