Study of Sperm Molecular Factors Implicated in Male Fertility

Study Overview
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Brief Summary
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Sperm analysis following World Health Organization guidelines is unable to explain the molecular causes of male infertility when basic sperm parameters are within a normal range and women do not present gynaecological pathology. Subsequently, there is a need for accurate diagnostic tools in this sense and microarray technology applied to sperm analysis emerges as a promising field

Detailed Description
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Sperm analysis based in sperm count and motility has been employed for the diagnosis of male fertility for several decades. It is an easy, inexpensive and useful tool to determine the fertile status of a male but there is still a significant number of infertile males with normal sperm features, as determined by the basic sperm analysis, while they remain unable to reach a full-term pregnancy (1). This fact clearly indicates the need to develop new male infertility tests and accurately diagnose the sperm samples from these individuals. Recent investigations about sperm mRNA contents have described the relevance of the sperm mRNA stock in fertilization and early embryo development in several species. (2) Although sperm is a quiescent cell from the translational point of view, several functional mRNAs that will be delivered into the oocyte after fertilization, that were synthesized in an earlier phase of the spermatogenesis process can be found (3, 4). The fertile male transcriptome (stock of mRNAs within the sperm of a male able to have progeny) has been already described (5, 6), confirming the expression of thousands of sequence tags with different intensity of expression. Moreover, several investigations have demonstrated that a differential expression of some key mRNAs is found in infertile males in comparison with fertile males (1, 7). Nevertheless, there is no information available neither about the characteristics of the stock sperm mRNAs on infertile males or the differences between fertile and infertile men, although several authors have hypothesized that sperm microarray analysis will be the future in the male infertility diagnosis (2, 8-11). Microarray technology provides information about a wide range of mRNAs expression within a single experiment, permitting to analyze complete sperm expression profiles (SEP) in cells or tissues. Bioinformatics can help in the organization of such amount of results by following logical processes of gene expression grouping, and analyzing statistically these findings. Our aim with this work was to compare the SEP in spermatozoa obtained from males with idiopathic infertility versus those from sperm donors of proven fertility by employing microarray technology followed by a functional analysis, in order to determine the genes, sequences and biological processes involved in the sperm physiology that are different in infertile vs. fertile males.

Official Title
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Microarray Analysis in Sperm From Fertile and Infertile Males Without Basic Sperm Analysis Abnormalities

Conditions
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Male Infertility

Intervention / Treatment
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* Behavioral: Microarray analysis
* Behavioral: Microarray


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Fertile (controls) or infertile males, with sperm parameters above the WHO criteria values Exclusion Criteria: Well established infertility causes

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 50 Years

Sexes Eligible for Study
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Male

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Arms and Interventions

| Intervention/Treatment |
| --- |
|Behavioral: Microarray analysis|Microarray analysis|
|Behavioral: Microarray|Microarray|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Sperm mRNAs expression profile in samples achieving pregnancy vs those who failed in different assisted reproduction techniques |  | 10 months | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Sperm, male fertility, microarrays