Evidence map›Paper›PMID 40626180›Full record

ArticleFrontiers in genetics2025

Shared pathogenesis in polycystic ovaries and rheumatoid arthritis: an analysis of key genes and pathways.

Yingying Ji, Pengcheng Xia, Yan Wang, Yang Liu, Feng Wang, Fenggang Sun, Qiang Feng, Qingbin Ni, Yi Li

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Article in Frontiers in genetics, 2025. 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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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

9 authors.

Yingying Ji *Department of Clinical Laboratory Medicine, The Affiliated Taian City Central Hospital of Qingdao University, Taian, Shandong, China.
Pengcheng Xia *Department of Clinical Laboratory Medicine, The Affiliated Taian City Central Hospital of Qingdao University, Taian, Shandong, China.
Yan WangDepartment of Clinical Laboratory Medicine, The Affiliated Taian City Central Hospital of Qingdao University, Taian, Shandong, China.
Yang LiuDepartment of Clinical Laboratory Medicine, The Affiliated Taian City Central Hospital of Qingdao University, Taian, Shandong, China.
Feng WangDepartment of Clinical Laboratory Medicine, The Affiliated Taian City Central Hospital of Qingdao University, Taian, Shandong, China.
Fenggang SunSchool of Basic Medical Sciences, Shandong First Medical University, Taian, Shandong, China.
Qiang FengDepartment of Clinical Laboratory Medicine, The Affiliated Taian City Central Hospital of Qingdao University, Taian, Shandong, China.
Qingbin Ni *Department of Clinical Laboratory Medicine, The Affiliated Taian City Central Hospital of Qingdao University, Taian, Shandong, China.
Yi Li *Department of Clinical Laboratory Medicine, The Affiliated Taian City Central Hospital of Qingdao University, Taian, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The study aims to explore the potential shared pathogenic processes between PCOS and RA through bioinformatics analysis to identify novel therapeutic targets and biomarkers for disease management. Methods: Microarray datasets for polycystic ovary and RA were obtained from the GEO database. Differential gene expression analysis identified commonly dysregulated genes in both conditions. Gene Ontology (GO) and KEGG pathway enrichment analyses were performed to understand the biological processes and pathways associated with the differentially expressed genes (DEGs). Protein interaction analysis, machine learning algorithms, and validation analyses were employed to identify core genes with potential diagnostic value. Immune cell infiltration analysis and evaluation of hypoxia and angiogenesis scores were conducted to assess the role of the core genes in immune-related disorders. Results: Microarray analysis identified differentially expressed genes (DEGs) commonly dysregulated in PCOS and RA. GO and KEGG enrichment analyses highlighted the involvement of cell death, inflammation, and redox pathways. Ten key genes were identified through protein interaction analysis, and machine learning further narrowed it down to six core genes: CSTA, DPH3, CAPZA2, GLRX, CD58, and IFIT1. The core genes were overexpressed in PCOS and RA tissues, suggesting their potential involvement in disease development. Validation analyses confirmed the diagnostic potential of these genes, especially in RA. Immune cell infiltration analysis correlated the expression of core genes with neutrophil and CD8 Conclusion: The study unveils potential molecular links between PCOS and RA, highlighting the importance of immune dysregulation in their pathogenesis. The identified core genes offer novel therapeutic targets and potential biomarkers for disease management, providing insights into the complex interplay between these two seemingly unrelated conditions.

Indexed as

bioinformatics analysiscore genesimmune dysregulationPCOSRA

Identifiers

PMID40626180
PMCPMC12229850

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