Evidence map›Paper›PMID 41581046›Full record

ArticleIndian journal of ophthalmology2026

The protein-protein interaction network analysis in idiopathic posterior uveitis.

Mehrdad Motamed Shariati, Zahra Moravvej

Abstract read
In one paragraph

Article in Indian journal of ophthalmology, 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

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Mehrdad Motamed ShariatiEye Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
Zahra Moravvej

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIdiopathic posterior uveitis (IPU) is a vision-threatening inflammatory condition affecting the posterior segment of the eye with poorly understood molecular mechanisms. This study aimed to identify the key molecular actors and functional pathways involved in IPU using protein-protein interaction (PPI) network analysis.

designIn silico bioinformatics study using PPI network analysis to identify key molecular pathways in IPU.

methodsSixteen proteins previously linked to IPU pathogenesis were identified in a comprehensive literature review. These seed proteins were used to query the STRING v12 database to retrieve high-confidence interactions (score ≥ 700). An expanded PPI network was built and analyzed using Python tools, including NetworkX and Louvain community detection algorithm. Topological metrics (degree, betweenness, and eigenvector centrality) were calculated to identify the hub and bottleneck proteins. Functional enrichment analysis was performed to assess the biological significance.

resultsThe resulting PPI network consisted of 260 proteins and 281 interactions. The network exhibited a low density (0.008) but a high modularity (0.8426), which is consistent with typical biological networks. Key hub proteins included PDGFRB, ORM1, IL23A, and TIMP1. Proteins such as IL6, KITLG, and STAT4 emerged as critical bottlenecks based on betweenness centrality. Multimetric centrality analysis highlighted TIMP1, TIMP2, KITLG, and IL6 as potential master regulators.

conclusionThe findings highlight the inflammatory, structural, and neurotrophic pathways as key components of disease pathogenesis, suggesting novel molecular targets for future therapeutic investigations. PPI network analysis offers a robust framework for uncovering the disease mechanisms in complex ocular inflammatory conditions.

Indexed as

Computational BiologyEye ProteinsProtein Interaction MapsUveitis, PosteriorComputer SimulationHumansEye ProteinsBioinformaticshub proteinsidiopathic posterior uveitisinflammationnetwork analysisprotein–protein interactionsystems biology

Identifiers

PMID41581046
PMCPMC12947106

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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.