Metabolomic Profiling of Poor Ovarian Response Identifies Potential Predictive Biomarkers - Song, Haixia; Qin, Qin; Yuan, Caixia; Li, Hong; Zhang, Fang; Fan, Lingling (Frontiers in Endocrinology, 2021)
Abstract Objective: To characterize the serum metabolomic profile and its role in the prediction of poor ovarian response (POR). Patient(s): 25 women with normal ovarian reserve (24-33 years,antral follicle count[AFC] ≥5, antimmüllerian hormone [AMH]≥1.2ng/ml) as the control group and the other 25 women with POR (19-35 years, AFC <5, AMH < 1.2 ng/ml) as the study group were collected in our study. The serums of the women in both groups from their whole blood were determined by untargeted liquid chromatography–mass spectrometry (LC-MS). Multivariate statistical analysis and cell signal pathways analysis were used to reveal the results. Results: 538 metabolites were finally identified differently 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 and also most important metabolites in support vector machines(p <0.05). Metabolomic profiling, together with support vector machines and pathway analysis, 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. Nicotinate and nicotinamide metabolism pathway may be a new insight for complementary prediction and therapeutic potential of POR. The functional associations of these metabolites need further to be investigated.