Whole Genome Analysis for the Detection of Key Genes in the Polycystic Ovary Syndrome

Study Overview
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Brief Summary
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Background: Infertility affects up to 15% of married couples. About half are attributable to female factors, among which anovulation is the leading cause. Some 5% of all women of reproductive age are anovulatory due to the polycystic ovarian syndrome (PCOS). PCOS causes also major health and cosmetic problems and significantly affects quality of life. PCOS is associated with cardiovascular morbidity and Type 2 diabetes mellitus, but it is unclear whether these are caused by the ovarian dysfunction or result from a common denominator. Working hypothesis and aims: Whole genome analysis of multigenerational families in which at least one woman is affected by PCOS may significantly reduce the numbers needed to verify the specific genes, involved in the causation of PCOS. Methods: Registration of multigenerational families and production of personal files with full workup for the presence of PCOS or its absence (in the women participants). Drawing of blood, extraction and preservation of DNA. Analysis of all informative SNPs in the genomes of the participants on a specific microarray chip. Statistical analysis of the results. Expected results: Verification of the loci and putative genes, associated with the appearance of PCOS. Importance: Elucidation of the specific genes underlying the pathology of PCOS. Probable implications to Medicine: Paving the way for targeted treatment of the problems, associated with PCOS, based on the clear knowledge of its underlying cause(s).

Detailed Description
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Working Hypothesis The recent trend in GWA has been the comparison of large numbers of DNA samples from affected individuals and large pools of unrelated individuals (Wellcome Trust Case Control Consortium). Whenever the control group came from family members, the number of patients needed to be sampled has been consistently smaller (Dempfle a et al 2006; The Japanese Schizophrenia Sib-Pair Linkage Group 2005), due to less degrees of freedom in the statistical analysis (Chen WM & Abecasis GR 2007). Specific Aims What are the specific informative SNPs, associated with PCOD? What are the specific genes located in the vicinity of these SNPs, which could contribute to the development of the clinical syndrome? Detailed description of the proposed research Clinical data collection and patient recruitment Patients Women will be diagnosed as suffering from PCOD based on the Rotterdam criteria (): Oligo- and/or anovulation Clinical and/or biochemical signs of hyperandrogenism Polycystic ovaries, and exclusion of other aetiologies (congenital adrenal hyperplasias, androgen-secreting tumours, Cushing's syndrome) Routine testing of serum levels for the relevant sex hormones will be performed at the 3rd day of the menstrual cycle. Glucose and insulin levels will be measured at the fasting state. The individual data collection page is presented as Appendix 1. Controls Sisters, mothers, fathers, aunts and grandmothers of affected women will be asked to disclose their relevant clinical history and donate a single blood test for both DNA extraction and hormonal tests, which will be taken at the 3rd day of menstruation, where applicable. The population that is served by Mayanei Hayeshua hospital is characterized by a short generation interval, due to the mean early age at marriage and the desire to bear children right after marriage. This should allow the formation of genealogy trees that are very informative. Data security and terms of use of samples Recruitment of family members will be only through the index cases, and each participant will receive a complete explanation of possible personal implication of the study results to herself and family (none). Overall, all included women, patients and family members alike, will be notified as to the secrecy of the data and its use only for the declared purpose of research. They will also be made aware that no personal benefit or harm can be derived from this data to them. In addition, all participants will be informed that if in the future there will arise a new reason to re-analyze their samples, a specific address will be made to each and every one of them to obtain a new permission for this use. Upon request each participant will receive a full explanation of the storage system and the hierarchy of responsibility for the samples and data security. Compliance to the definition of a feasibility study The funds requested herein are meant to enable the formation of DNA bank and family trees, which in turn will serve as the basis for an application to receive the full funding for whole genome analysis, from larger funding resources. Towards this we have teamed up with the future participants of a worldwide consortium on this topic (letter of intention from Bart Fauser, the leading person of this consortium, is attached). Our most pronounced advantage within the consortium, is the availability of multigenerational families, members of which we treat in Bnei Brak. Potential Implications to Medicine and contribution of the expected outcome to society Paving the way for targeted treatment of the problems, associated with PCOS, based on the clear knowledge of its underlying cause(s).

Official Title
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Whole Genome Analysis for the Detection of Key Genes in the Polycystic Ovary Syndrome - a Study on Multigenerational Families

Conditions
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Anovulation, Hyperandrogenism, Polycystic Ovary Syndrome, Single Nucleotide Polymorphism

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: A clinical and laboratory diagnosis of the polycystic ovary syndrome (cases). Female family members of index cases, up to a great grandmother and fathers of index cases. Exclusion Criteria: None.
Sexes Eligible for Study
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All

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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What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Polycystic ovary syndrome, Single nucleotide polymorphism, Whole genome analysis, Multigenerational family study