Seminal plasma metabolomics approach for the diagnosis of unexplained male infertility

We used a gas chromatography-mass spectrometry (GC-MS) based metabolomics approach to obtain the metabolic profiling of unexplained male infertility (UMI), and identified seminal plasma biomarkers associated with UMI by a two-stage population study. A robust OPLS-DA model based on these identified m...

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Detalles Bibliográficos
Autores principales: Qiao, Shanlei, Wu, Wei, Chen, Minjian, Tang, Qiuqin, Xia, Yankai, Jia, Wei, Wang, Xinru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5552325/
https://www.ncbi.nlm.nih.gov/pubmed/28797078
http://dx.doi.org/10.1371/journal.pone.0181115
Descripción
Sumario:We used a gas chromatography-mass spectrometry (GC-MS) based metabolomics approach to obtain the metabolic profiling of unexplained male infertility (UMI), and identified seminal plasma biomarkers associated with UMI by a two-stage population study. A robust OPLS-DA model based on these identified metabolites was able to distinguish 82% of the UMI patients from health controls with a specificity of 92%. In this model, 44 metabolites were found differentially expressed in UMI subjects compared with health controls. By pathway enrichment analysis, we identified several major changed metabolic pathways related to UMI. Our findings provide new perspective for the diagnosis of UMI.

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