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Autoimmune disease influence on polycystic ovary syndrome: Insights from Mendelian randomization and multi-omics analysis.

Sep 2026 · Advances in Clinical and Experimental Medicine · 0 citations
Medicine

Abstract

Background

Polycystic ovary syndrome (PCOS) is a common endocrine disorder associated with a substantial health burden.

Objectives

Given the interplay between the immune and endocrine systems, this study aimed to investigate the potential causal relationship between autoimmune diseases and PCOS using Mendelian randomization (MR). MATERIAL AND

Methods

A 2-sample MR analysis was conducted using genome-wide association study (GWAS) data from the FinnGen (n = 118,870) and European Bioinformatics Institute (EBI) (n = 141,355) cohorts. Instrumental variables were selected as single nucleotide polymorphisms (SNPs), and the inverse-variance weighted (IVW), weighted median, and MR-Egger methods were applied. Sensitivity analyses were performed to assess heterogeneity and horizontal pleiotropy. To validate the MR findings, transcriptomic analyses of Gene Expression Omnibus (GEO) datasets (GSE209596 for multiple sclerosis (MS) and GSE277906 for PCOS) were performed to identify shared differentially expressed genes (DEGs), followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Diagnostic nomograms were constructed based on the identified key genes.

Results

Mendelian randomization analysis suggested a potential inverse causal association between MS and PCOS (IVW: odds ratio (OR) = 0.906; 95% confidence interval (95% CI): 0.820-0.999; p = 0.049), which was consistent across both datasets and robust in the sensitivity analyses. No significant causal associations were identified for the other autoimmune diseases. Transcriptomic analysis identified 4 shared DEGs (CD52, ARHGDIB, GCHFR, and S100A9), which were enriched in immune-related pathways. Nomogram models based on these genes accurately discriminated patients from controls in both cohorts, achieving areas under the curve (AUCs) of 82.8% for MS and 81.1% for PCOS.

Conclusions

This integrative analysis suggests a potential protective association between MS and PCOS mediated by immune-related mechanisms. These findings provide new insights into the immunopathology of PCOS and support the future development of diagnostic biomarkers.

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