Metabolomic Profiling of Poor Ovarian Response Identifies Potential Predictive Biomarkers

OBJECTIVE: To characterize the serum metabolomic profile and its role in the prediction of poor ovarian response (POR). PATIENT(S): Twenty-five women with normal ovarian reserve (24-33 years, antral follicle count [AFC] ≥5, anti-Müllerian hormone [AMH] ≥1.2 ng/ml) as the control group and another twenty-five women with POR (19-35 years, AFC <5, AMH < 1.2 ng/ml) as the study group were collected in our study. The serum levels of the women in both groups were determined from their whole blood by untargeted liquid chromatography–mass spectrometry (LC-MS). Multivariate statistical analysis and cell signal pathways analysis were used to reveal the results. RESULTS: A total of 538 different metabolites were finally identified in the two groups. Tetracosanoic acid, 2-arachidonoylglycerol, lidocaine, cortexolone, prostaglandin H2,1-naphthylamine, 5-hydroxymethyl-2-furancarboxaldehyde, 2,4-dinitrophenol, and D-erythrulose1-phosphate in POR were significantly different from control as were most important metabolites in support vector machines (p <0.05). Metabolomic profiling, together with support vector machines and pathway analysis found that the nicotinate and nicotinamide metabolism pathway, including L-aspartic acid, 6-hydroxynicotinate, maleic acid, and succinic acid semialdehyde, was identified to have significant differences in POR women compared to control women, which may be associated with ovarian reserve. CONCLUSION: This study indicated that LC–MS-based untargeted metabolomics analysis of serum provided biological markers for women with POR. The nicotinate and nicotinamide metabolism pathway may offer new insight into the complementary prediction and therapeutic potential of POR. The functional associations of these metabolites need further investigation.