Abstract
BACKGROUND: Infertility affects 70-80% of women with polycystic ovary syndrome (PCOS). However, the clinical, microbial, and metabolic factors that distinguish infertile PCOS patients from those who conceive remain poorly defined. METHODS: This cross-sectional study enrolled 80 PCOS patients (35 with prior spontaneous conception [PCOS-Control] and 45 infertile [PCOS-Infertile]). Clinical characteristics, reproductive hormones, and metabolic parameters were assessed. Gut microbiota composition was analyzed by 16S rRNA sequencing, and serum metabolomic profiling was performed using UPLC-QTOF-MS. Multi-omics integration and machine learning were applied to identify discriminative features. RESULTS: Infertile patients exhibited significantly higher testosterone levels and LH/FSH ratios. While overall gut microbial diversity was similar, taxon-specific analysis revealed enrichment of Turicibacter and Prevotella and depletion of beneficial taxa such as Alistipes finegoldii in the infertile group. Serum metabolomics identified seven differential metabolites, with elevated pro-inflammatory metabolites (e.g., phosphatidic acid, trichostachine) in infertile patients and reduced levels of potentially protective metabolites (e.g., L,L-Cyclo(leucylprolyl)). A multi-omics predictive model achieved strong diagnostic performance (AUC = 0.833) for identifying infertility. CONCLUSION: Infertility in PCOS is associated with distinct gut microbiota and serum metabolite signatures, characterized by specific microbial taxa shifts and metabolic dysregulation. These findings provide potential biomarkers for clinical stratification and offer insights into the microbiota-metabolite-fertility axis in PCOS.