Status Plus




Serum metabolomic analysis identifies unique signatures in azoospermic men

Zhang, Z1; Yang, Y1; Jiang, H1

1: Peking university Third Hospital, China

Objective: Infertility is considered as a major health problem, and azoospermia cases due to 10% of male factors. Azoospemia is the most challenging task for andrologist, for these patients rarely can father their own genetic offspring. Therefore, it is imperative to investigate the molecular mechanism underlying idiopathic azoospermia and seek a potential treatment.

Methods: The subjects with idiopathic azoospermia were enrolled from Reproductive Center of Peking University Third Hospital (PUTH), and healthy controls form Human Sperm Bank of PUTH. The blood samples from both idiopathic azoospermia and healthy control were used for untargeted metabolites screening by high performance liquid chromatography. All metabolites were introduced to MetaboAnalyst3.0 for data processing, PCA and OPLS-DA was performed to reduce the dimensionality of the data and to reveal any clustering in an unsupervised manner. The significance of variable was quantified by the variable importance in the project (VIP) plot of the established OPLS-DA model. Mann-Whitney U test and chi-square test. Metabolites relative content were analyzed with two-tailed Student’s t-test using.Anydifference with p < 0.05 was considered statistically significant.

Results: A total of 22 idiopathic azoospermic patients and 31 normal controls were enrolled in the case-control sutdy. In the group of azoospermia, infertile men were identified as early/late maturation arrest, Sertoli-cell only. There is an obvious segregation of metabolomic profiles was observed in the group of azoospermic cases in PCA model. The entired data set was identified by a further supervised analysis of PLS-DA, and revealed a clearer separation of azoospermia from the fertile cases. Extracted variables that contributed the most in the case control group differentiation were chosen to be biomarkers for idiopathic azoospermic diagnosis, and acetylcarnitine, citrate, arginine and taurine were identified. The pathways had the top 5 pathway impact are: A. Alanine, aspartate and glutamate metabolism; B. Citrate cycle (TCA cycle); C. Arginine and proline metabolism; D. Butanoate metabolism; E. D-Glutamine and D-glutamate metabolism.

Conclusion: Several potential metabolites were identified that are closely associated to energy production and oxidative stress in spermatogenesis. Biosynthesis and metabolism of these metabolites may contribute to the aetiologies of idiopathic azoospermia. Our findings suggested that metabolomics fingerprinting could provide a promising screening approach to detect possible biomarkers and improve our understanding of mechasnisms underlying male infertility, and eventually aiding to etiological diagnose and therapy intervention.


Work supported by industry: no.

Go Back