Diagnosis-dependent metabolic reprogramming of follicular fluid

The follicular fluid (FF) microenvironment plays a critical role in oocyte maturation and embryo development, reflecting local ovarian activity and systemic metabolic status. While metabolic alterations in FF have been described in different diseases, comparative analyses across different infertility-related disorders remain limited.

This study aimed to characterize and compare amino acid profiles in FF from patients undergoing in vitro fertilization (IVF) with insulin resistance (IR), endometriosis (EM), thyroid dysfunction (TD) and to identify disease-specific metabolic signatures.

We analyzed 171 FF samples using targeted ultra-high-performance liquid chromatography. The twenty proteogenic amino acids were quantified and analyzed using univariate and multivariate statistical analyses, including Kruskal-Wallis testing with post-hoc correction, generalized linear modeling adjusted for BMI, principal component analysis (PCA) and pathway enrichment analysis.

PCA revealed that the global amino acid composition of FF was largely conserved across all groups. However, disease status had a statistically significant but moderate effect on the overall amino acid profile (PERMANOVA, R²=0.081, p = 0.001). After adjusting for BMI, IR was associated with decreased glycine and arginine levels and TD was associated with lower histidine, tryptophan and lysine concentrations. In contrast, EM was characterized by a selective increase in the histidine content. Pathway analysis revealed alterations in branched-chain amino acid (BCAA) metabolism in IR group and broader disruptions in central amino acid metabolism in TD group. Multivariate and ROC analyses indicated limited discriminative performance of individual amino acids (AUC ≤ 0.71), suggesting that metabolic alterations are subtle and distributed across multiple pathways.

FF amino acid composition is tightly regulated but distinct disease-specific metabolic alterations can be detected in IR, EM and TD. These changes are independent of BMI and reflect coordinated alterations in the metabolism of different amino acids rather than strong individual biomarkers. These results show the sensitivity of the follicular environment to overall metabolic health and support the idea of using multivariable metabolic patterns to better understand reproductive dysfunction.