A Metabolomic Profile of Seminal Fluid in Extremely Severe Oligozoopermia Suggesting an Epididymal Involvement.
Orianne SerriMagalie BoguenetJuan Manuel Chao de la BarcaPierre-Emmanuel BouetHady El HachemOdile BlanchetPascal ReynierPascale May-PanloupPublished in: Metabolites (2022)
Male infertility has increased in the last decade. Pathophysiologic mechanisms behind extreme oligospermia (EO) are not yet fully understood. In new "omics" approaches, metabolomic can offer new information and help elucidate these mechanisms. We performed a metabolomics study of the seminal fluid (SF) in order to understand the mechanisms implicated in EO. We realized a targeted quantitative analysis using high performance liquid chromatography and mass spectrometry to compare the SF metabolomic profile of 19 men with EO with that of 22 men with a history of vasectomy (V) and 20 men with normal semen parameters (C). A total of 114 metabolites were identified. We obtained a multivariate OPLS-DA model discriminating the three groups. Signatures show significantly higher levels of amino acids and polyamines in C group. The sum of polyunsaturated fatty acids and free carnitine progressively decrease between the three groups (C > EO > V) and sphingomyelins are significantly lower in V group. Our signature characterizing EO includes metabolites already linked to infertility in previous studies. The similarities between the signatures of the EO and V groups are clear evidence of epididymal dysfunction in the case of testicular damage. This study shows the complexity of the metabolomic dysfunction occurring in the SF of EO men and underlines the importance of metabolomics in understanding male infertility.
Keyphrases
- mass spectrometry
- high performance liquid chromatography
- middle aged
- oxidative stress
- liquid chromatography
- ms ms
- tandem mass spectrometry
- healthcare
- type diabetes
- simultaneous determination
- polycystic ovary syndrome
- gene expression
- climate change
- gas chromatography
- early onset
- skeletal muscle
- dna methylation
- cancer therapy
- case control
- health information
- data analysis