Exploring the Genetic Link between Irritable Bowel Syndrome and Polycystic Ovary Syndrome: Bidirectional Mendelian Randomization and Machine Learning Approaches

Background: Research has shown a certain correlation between polycystic ovary syndrome (PCOS) and irritable bowel syndrome (IBS). The study aims to determine the directionality and underlying biological processes influencing the relationship between these two disorders. Methods: We explored the causal relationship between IBS and PCOS by conducting a comprehensive bidirectional Mendelian randomization (MR) analysis using five different methods and conducted robustness assessments. We extracted differentially expressed genes from the IBS and PCOS datasets for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Additionally, we developed a protein-protein interaction (PPI) network and applied the Least Absolute Shrinkage and Selection Operator (LASSO) and Support Vector Machine (SVM) methodologies to pinpoint key diagnostic markers. Diagnostic efficacy was further assessed through Receiver Operating Characteristic (ROC) curve analysis for selected genes. Finally, single-sample gene set enrichment analysis (ssGSEA) was carried out to examine immune cell infiltration in IBS and PCOS. Results: MR analysis identified a causal effect of PCOS on IBS (IVW, OR = 1.034, 95% CI: 1.003-1.065, P = 0.029). Conversely, no relationship between IBS and PCOS was observed in the reverse analysis. Furthermore, integrative bioinformatics and machine learning analyses identified CD14 and CASP1 as key diagnostic biomarkers for both IBS and PCOS, which were significantly associated with immune cell infiltration. Conclusion: MR analysis has demonstrated a significant positive causal relationship between PCOS and IBS, though the reverse causality from IBS to PCOS appeared non-significant. The genes CD14 and CASP1 emerged as potential shared diagnostic markers between these two conditions.