Unknown,Transcriptomics,Genomics,Proteomics

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CNVs in spermatogenic failure

ABSTRACT: To determine the involvement of Copy Number Variants (CNVs) in the origin of male infertility, patients with idiopathic severe oligozoospermia, Sertoli-cell-only syndrome and controls with normozoospermia were analysed by array CGH using the 244A/400K array sets (Agilent Technologies). Comparison of 89 infertile male patients with severe oligozoospermia (≤5 x Mill./ml sperm concentration and ≤10 Mill. total sperm count) and 37 with azoospermia due to complete, bilateral Sertoli-cell-only syndrome (SCOS) with 100 healthy controls with normal semen parameters (≥20 Mill./ml sperm concentration, ≥40 Mill. total sperm count, ≥2 ml semen volume, ≥50% of a+b or ≥25% a motility, high percentage of normal forms (≥10%)). Patients with recurring, patient-specific and mostly private, sex-chromosomal CNVs (29 with OAT and 17 with SCOS) are reported as possibly causing spermatogenic failure.

ORGANISM(S): Homo sapiens

SUBMITTER: Frank Tüttelmann

PROVIDER: E-GEOD-27965 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:<h4><strong>BACKGROUND: </strong>Semen quality is negatively correlated with male age and is mainly quantified by a routine semen analysis, which is descriptive and inconclusive. Sperm proteins or semen metabolites are used as the intermediate or end-products, reflecting changes in semen quality, and hold much promise as a new biomarker to predict fertility in advanced-aged males.</h4><h4><strong>OBJECTIVES: </strong>In this study, we sought to assess whether the semen metabolome and proteome of aged males can affect semen quality and serve as biomarkers for predicting semen quality.</h4><p><strong>MATERIALS AND METHODS: </strong>We retrospectively analyzed 12825 males that underwent semen routine analysis to understand the age-dependent changes in sperm quality. To identify the difference between aged and young adults, metabolomics (n=60) analyses of semen and proteomics (n=12) analyses of sperm were conducted. Finally, integrated machine learning of metabolomics was conducted to screen biomarkers to identify aging semen.</p><p><strong>RESULTS:</strong> We discovered that male age was positively correlated with sperm concentration as well as DNA fragmentation index(DFI), and negatively with progressive motile sperm count, total sperm count, sperm volume and progressive sperm motility. The differential metabolites were significantly enriched in various metabolic pathways, and four of these differential metabolites (Pipamperone, 2,2-Bis(hydroxymethyl)-2,2',2''-nitrilotriethanol, Arg-Pro and Triethyl phosphate) were utilized to establish a biomarker panel to identify aging semen. Proteomic analysis showed that differential proteins were significantly enriched in protein digestion and absorption and some energy-related pathways. An integrated analysis of the metabolome and proteome identified differential energy metabolism and oxidative stress-related proteins, which could explain the decreased motility and the increased DFI of aging sperm.</p><p><strong>DISCUSSION AND CONCLUSION:</strong> We provide compelling evidence that the changes in semen metabolome and sperm proteome are related to the decline of semen quality in aged males. Moreover, a biomarker panel based on four metabolites was established to identify aging semen.</p>

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CNVs in spermatogenic failure

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