Gut Microbiome in Patients With Polycystic Ovary Syndrome

Study Overview
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Brief Summary
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The polycystic ovary syndrome is intimately associated with body weight and nutrition.The genomic era did not bring a breakthrough to the understanding of the syndrome. The recent surge of studies on gut microbiome has raised the possibility that the specific diet, which often affect these women favorably, would change their gut microbiome. Hence, the investigators will examine their gut microbial population in comparison to normal ovulatory women and then examine whether a low carbohydrate diet causes favorable change in their gut microbial population.

Detailed Description
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- Scientific Background Infertility is a major health problem that affects up to 15% of married couples. About half of these cases are attributable to female factors, among which anovulation is the leading cause. About 5% of all women of reproductive age are anovulatory due to the polycystic ovarian syndrome (PCOS). In addition to its effect on fertility, PCOS causes major health and cosmetic problems and significantly affects quality of life in women. 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. PCOS The clinical picture: The polycystic ovary syndrome consists of anovulation, acne, hirsutism (resulting from hyperandrogenism), and reversed serum LH to FSH ratio. A large proportion of women with PCOS are overweight, and a significant proportion of women with PCOS have decreased peripheral insulin sensitivity. The direct cause to this insulin resistance is still enigmatic. All these features place women with PCOS as a group of patients related to the metabolic syndrome. Baranova et al. (2011) even stated that it seems appropriate to consider polycystic ovary syndrome as the ovarian manifestation of metabolic syndrome. - Genetics Not all women with PCOS have affected relatives but familial clusters are common, and brothers of women with PCOS have high serum levels of the androgen dehydroepiandrosterone sulfate. The eventual clinical expression of PCOS results not only from genetic predisposition but also from nutritional factors. Family studies using several approaches of analysis suggested up to 40 candidate genes, possibly responsible to the syndrome. Among these were genes from the steroidogenic pathways, the gonadotrophin receptors signal transduction pathways, the insulin signal transduction pathway and growth factor signal transduction pathways. Except for some association of polymorphism in CYP11 with hyperandrogenism none of these candidate genes were definitively associated with PCOS. The inheritance pattern of PCOS is not clear, some evidence favor autosomal dominant mode while others do not support it. Recently the methionine 196 arginine polymorphism in exon 6 of the TNF receptor 2 gene (676 T-->G) was shown to be associated with hyperandrogenism and PCOS, but the genotype did not influence any clinical or biochemical variable related to hyperandrogenism or insulin sensitivity and was not associated with obesity. A role of Calpain 10 gene in PCOS susceptibility was also suggested, as was that of a variant LH receptor. The sex hormone binding gene also showed promise but disappointed. The mode of X-chromosome inactivation appears to be associated with the risk of sisters for discordancy to PCOD, but no specific genes are implicated in this respect. As with many complex disorders, the heritability of polycystic ovarian syndrome has eluded investigators. Although familial aggregation studies have demonstrated clearly a genetic component to the syndrome, simple Mendelian models do not characterize its mode of inheritance. Instead, multiple loci and epigenetic modification may play a role in the phenotype. The candidate gene approach relies upon improved statistical and technological methods to analyze potential genes based on biologic plausibility. Pathways that affect steroidogenesis, insulin resistance, gonadotropin function, and obesity provide potential genes for investigation. Obstacles such as phenotypic variability, lack of a male phenotype, multiple attempts at analysis, and small sample sizes hamper these efforts. Genome wide Analysis has become the gold standard for the elucidation of the genetic background for many diseases. The most recent and comprehensive such analysis of PCOD vs. controls was conducted by Chen et al (2011), and some candidate gens were defined, but a mechanistic understanding of possible causality is still far away. Gut Microbiota General: The post genomic era led to several breakthroughs in our understanding of human physiology. One of the more prominent is the realization that our alimentary tract harbors 100-fold more living (bacterial) cells than our own body has. This discovery was made possible by the ability to define the presence of a bacterial strain by its DNA signature, without the need to culture it. Furthermore, the definition of these strains allows their allocation to major taxonomic divisions, in turn enabling what is legitimately called profiling of gut bacterial population diversity. Thus a new term has been coined microbiota to designate the total population of our gut microbes. In addition, it is now also possible to define the presence of specified enzymes and enzyme families in the gut microbiota, enabling in turn an outline of overall gut microbial metabolic capacity. It is of major interest now to characterize the varying taxonomic and metabolic profiles, as they pertain to specified human pathologies and physiological states. Once microbiota profile that is associated with specific human pathology is characterized, a key question arises as to which is the egg and which is the hen. Namely, which is causative, the pathological state or the microbiota that has been shown to be associated with it? On several issues recent studies proven the microbiota to be most likely causative, as experimental transplantation of microbiota to mice led to the development of a state which was reminiscent of the human disease. Yet the differences between microbiotas of human populations on various locations across the globe raises the likely possibility that ethnicity, diet and other environmental factors have a meaningful effect on gut microbiota. All told, the study of the association of gut microbiota with many human conditions could reveal major subjects of interest, mostly towards possible understanding of causality as well as suggestions as to future corrective measures. - Women Women go through several major physiological transitions during their lifetime. The first is puberty, followed by conception and pregnancy, usually more than once in life, and the last is menopause. It is likely that these would be associated with dynamic changes in gut microbiota, as a pioneering study shown recently that pregnant women's gut microbiota is profoundly altered as compared to that in non-pregnant women. Furthermore, as evidence is accumulating regarding specific alteration of gut microbiota in several morbid states, it is likely that woman's pathologies, such as anovulatory infertility associated with PCOS, could be associated with specific alterations in gut microbiota profile. Naturally, the egg vs. hen question is of importance should differences between anovulatory and ovulatory women will be found, and should be tackled almost at the outset. - Overall Study Objective Is there a difference in gut microbial population between normal ovulatory women and women who suffer from PCOS, and if there is, what is its role in the causation of the syndrome? Specific Aims Is there a difference in microbial population profile between women with PCOS and normal ovulatory women? Can a carbohydrate-poor diet and physical activity induce a change in the gut microbial population of women with PCOS? Detailed Study Design Specific Aim I: Is there a difference in microbial population profile between women with PCOS and normal ovulatory women? A group of 30 women who will be diagnosed with PCOS by the standard Rotterdam consensus criteria and 30 normal ovulatory women will provide stool samples during the 3-5 initial days of their menstrual bleeding. Serum hormone and metabolic profile will be obtained concomitantly. Samples will be submitted to DNA sequencing in GGA laboratories (Prof. Dani Bercovich), using the technique described previously in. The resulting datasets will be analyzed in the laboratory of Dr. Omry Koren, the Faculty of Medicine in the Galil, using the method he previously used. Caveats and Potential Pitfalls It is possible that gut microbita of the two groups will not show either a taxonomic difference or a difference in putative metabolic enzyme profile. Nevertheless, we assume that at least one of these two arms will yield a positive product, since the polycystic ovary shares characters with the metabolic syndrome, amply documented to portray a distinct microbial population profile in comparison to healthy individuals. Specific Aim II: Can a carbohydrate-poor diet and physical activity induce a change in the gut microbial population of women with PCOS? A change in diet has been known for many years to favorably affect the ovulatory function of patients with PCOS, as well as alleviating some of the associated cosmetic concerns. Most significantly, it is the carbohydrate element of this diet which is central to this change, alongside with the addition of physical activity. We will prescribe a carbohydrate-poor diet (appended table) to the study group and a concomitant physical activity program (45 minutes brisk walk, 4-5 times a week). After two months of this change of lifestyle we will repeat hormonal and metabolic profile, as well as obtain a second stool sample. A secondary interest would be to examine whether there exists a difference in the microbiome between women who would succeed in the diet and those who would not, whether in the initial bacterial population profile or that which will result from the diet.

Official Title
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The Effect of Diet on the Microbiome of Women With Polycystic Ovary Syndrome

Conditions
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Polycystic Ovary Syndrome

Intervention / Treatment
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* Behavioral: diet


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Study group - no other etiologies for infertility Exclusion Criteria: Other etiologies for infertility

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 35 Years

Sexes Eligible for Study
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Female

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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Design Details

Primary Purpose: Treatment
Allocation: Non-Randomized
Intervention Model: Single Group Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: PCOS after diet<br>Patients after 2 months of diet | Behavioral: diet<br>* Carbohydrate poor diet<br>|
| No Intervention: control<br>Ovulatory women | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| change in microbial population of the colon |  | 2 months of diet | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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polycystic ovary syndrome, gut microbiome, Change in gut microbial population, diet