Metabolic profiling putatively identifies plasma biomarkers of male infertility using UPLC-ESI-IT-TOFMS

F J Zeng; H C Ji; Z M Zhang; J K Luo; H M Lu; Y Wang

doi:10.1039/c8ra01897a

Metabolic profiling putatively identifies plasma biomarkers of male infertility using UPLC-ESI-IT-TOFMS

RSC Adv. 2018 Jul 19;8(46):25974-25982. doi: 10.1039/c8ra01897a.

Authors

F J Zeng¹, H C Ji¹, Z M Zhang¹, J K Luo², H M Lu¹, Y Wang²

Affiliations

¹ College of Chemistry and Chemical Engineering, Central South University Changsha China hongmeilu@csu.edu.cn.
² Department of Integrated Traditional Chinese and Western Medicine, Male Department of Integrated Traditional Chinese and Western Medicine, Xiangya Hospital, Central South University Changsha China wangyang_xy87@csu.edu.cn.

Abstract

Male infertility has become a global health problem. Currently, the diagnosis of male infertility depends on the results of semen quality or requires invasive surgical intervention. The process is complex and time-consuming. Metabolomics is an emerging platform with unique advantages in disease diagnosis and pathological mechanism research. In this study, ultra-performance liquid chromatography-electrospray ionization-ion trap-time of flight mass spectrometry (UPLC-ESI-IT-TOFMS) combined with chemometrics methods was used to discover potential biomarkers of male infertility based on non-targeted plasma metabolomics. Plasma samples from healthy controls (HC, n = 43) and various types of infertile patients, i.e., patients having oligozoospermia (OS, n = 36), asthenospermia (AS, n = 56) and erectile dysfunction (ED, n = 45) were analyzed by UPLC-ESI-IT-TOFMS. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed. The results of OPLS-DA showed that HCs could be discriminated from infertile patients including OS (R ² = 0.903, Q ² = 0.617, AUC = 0.992), AS (R ² = 0.985, Q ² = 0.658, AUC = 0.999) or ED (R ² = 0.942, Q ² = 0.500, AUC = 0.998). Some potential biomarkers were successfully discovered by variable selection methods and variable important in the projection (VIP) in combination with the T-test. Statistical significance was set at p < 0.05; the Benjamini-Hochberg false discovery rate was used to reduce type 1 errors resulting from multiple comparisons. The identified biomarkers were associated with energy consumption, hormone regulation and antioxidant defenses in spermatogenesis. To elucidate the pathophysiology of male infertility, relative metabolic pathways were studied. It was found that male infertility is closely related to disturbed phospholipid metabolism, amino acid metabolism, steroid hormone biosynthesis metabolism, metabolism of fatty acids and products of carnitine acylation, and purine and pyrimidine metabolisms. Plasma metabolomics provides a novel strategy for the diagnosis of male infertility and offers a new insight to study pathogenesis mechanism.