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

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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Journal
Advances in Clinical and Experimental Medicine
Published
2026-09-28
DOI
https://doi.org/10.17219/acem/214667
Primary Topic
Ovarian function and disorders
Type
article
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article

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

Keda Zhou, Si Chen, Peijuan WANG, Yu Jing et al.
Advances in Clinical and Experimental Medicine
Ovarian function and disorders
article

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

Keda Zhou, Si Chen, Peijuan WANG, Yu Jing, Tong Chu, Yue Chen
article en

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.

Advances in Clinical and Experimental MedicineVol. 35(9)
Nanjing University of Chinese Medicine (CN), Jiangsu Provincial Academy of Traditional Chinese Medicine (CN)
Reduced inequalities
Openalex Percentile: Top 9%
Ovarian function and disorders
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