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Fulltext Construction of a polycystic ovarian syndrome (PCOS) pathway based on the interactions of PCOS-related proteins retrieved from bibliomic data

Mohamed-Hussein ZA, Harun S

Theor Biol Med Model, 2009;6:18.
PMID: 19723303 DOI: 10.1186/1742-4682-6-18

Polycystic ovary syndrome (PCOS) is a complex but frequently occurring endocrine abnormality. PCOS has become one of the leading causes of oligo-ovulatory infertility among premenopausal women. The definition of PCOS remains unclear because of the heterogeneity of this abnormality, but it is associated with insulin resistance, hyperandrogenism, obesity and dyslipidaemia. The main purpose of this study was to identify possible candidate genes involved in PCOS. Several genomic approaches, including linkage analysis and microarray analysis, have been used to look for candidate PCOS genes. To obtain a clearer view of the mechanism of PCOS, we have compiled data from microarray analyses. An extensive literature search identified seven published microarray analyses that utilized PCOS samples. These were published between the year of 2003 and 2007 and included analyses of ovary tissues as well as whole ovaries and theca cells. Although somewhat different methods were used, all the studies employed cDNA microarrays to compare the gene expression patterns of PCOS patients with those of healthy controls. These analyses identified more than a thousand genes whose expression was altered in PCOS patients. Most of the genes were found to be involved in gene and protein expression, cell signaling and metabolism. We have classified all of the 1081 identified genes as coding for either known or unknown proteins. Cytoscape 2.6.1 was used to build a network of protein and then to analyze it. This protein network consists of 504 protein nodes and 1408 interactions among those proteins. One hypothetical protein in the PCOS network was postulated to be involved in the cell cycle. BiNGO was used to identify the three main ontologies in the protein network: molecular functions, biological processes and cellular components. This gene ontology analysis identified a number of ontologies and genes likely to be involved in the complex mechanism of PCOS. These include the insulin receptor signaling pathway, steroid biosynthesis, and the regulation of gonadotropin secretion among others.

Matched MeSH terms: Polycystic Ovary Syndrome/genetics
Reviewing the molecular mechanisms which increase endometrial cancer (EC) risk in women with polycystic ovarian syndrome (PCOS): time for paradigm shift?

Shafiee MN, Chapman C, Barrett D, Abu J, Atiomo W

Gynecol Oncol, 2013 Nov;131(2):489-92.
PMID: 23822891 DOI: 10.1016/j.ygyno.2013.06.032

Endometrial cancer (EC) is the commonest gynaecological cancer in North American and European women. Even though it has been shown that women with polycystic ovary syndrome (PCOS) have a three-fold increase in the risk of developing EC compared to women without PCOS, the precise molecular mechanisms which increase EC risk in women with PCOS remain unclear. Clinical strategies to prevent EC in PCOS are therefore not well researched and understood. Although raised estrogen levels, hyperinsulinaemia and, reduced apoptosis have been suggested as potential mechanisms, there is a lack of clarity about how these factors and other factors may interact to increase EC risk in PCOS. This article reviews the literature, on the potential molecular links between PCOS and EC but argues for a paradigm shift, to a systems biology-based approach in future research into the molecular links between PCOS and EC. The potential challenges of a systems biology-based approach are outlined but not considered insurmountable.

Matched MeSH terms: Polycystic Ovary Syndrome/genetics*
Graph cluster approach in identifying novel proteins and significant pathways involved in polycystic ovary syndrome

Afiqah-Aleng N, Altaf-Ul-Amin M, Kanaya S, Mohamed-Hussein ZA

Reprod Biomed Online, 2020 Feb;40(2):319-330.
PMID: 32001161 DOI: 10.1016/j.rbmo.2019.11.012

RESEARCH QUESTION: Polycystic ovary syndrome (PCOS) is a complex endocrine disorder with diverse clinical implications, such as infertility, metabolic disorders, cardiovascular diseases and psychological problems among others. The heterogeneity of conditions found in PCOS contribute to its various phenotypes, leading to difficulties in identifying proteins involved in this abnormality. Several studies, however, have shown the feasibility in identifying molecular evidence underlying other diseases using graph cluster analysis. Therefore, is it possible to identify proteins and pathways related to PCOS using the same approach?
METHODS: Known PCOS-related proteins (PCOSrp) from PCOSBase and DisGeNET were integrated with protein-protein interactions (PPI) information from Human Integrated Protein-Protein Interaction reference to construct a PCOS PPI network. The network was clustered with DPClusO algorithm to generate clusters, which were evaluated using Fisher's exact test. Pathway enrichment analysis using gProfileR was conducted to identify significant pathways.
RESULTS: The statistical significance of the identified clusters has successfully predicted 138 novel PCOSrp with 61.5% reliability and, based on Cronbach's alpha, this prediction is acceptable. Androgen signalling pathway and leptin signalling pathway were among the significant PCOS-related pathways corroborating the information obtained from the clinical observation, where androgen signalling pathway is responsible in producing male hormones in women with PCOS, whereas leptin signalling pathway is involved in insulin sensitivity.
CONCLUSIONS: These results show that graph cluster analysis can provide additional insight into the pathobiology of PCOS, as the pathways identified as statistically significant correspond to earlier biological studies. Therefore, integrative analysis can reveal unknown mechanisms, which may enable the development of accurate diagnosis and effective treatment in PCOS.

Matched MeSH terms: Polycystic Ovary Syndrome/genetics
Fulltext Subclinical eating disorder, polycystic ovary syndrome- is there any connection between these two conditions through leptin- a twin study

Jahanfar Sh, Maleki H, Mosavi AR

Med J Malaysia, 2005 Oct;60(4):441-6.
PMID: 16570705

The genetic property of subclinical eating behaviour (SEB) and the link between SEB and polycystic ovary syndrome (PCOS) has been studied before but the role of leptin within this connection has never been investigated. The objective of this study was 1). to study the genetic property of SEB. 2). To find a link between leptin, SEB and PCOS. One hundred and fifty four (77 pairs) female-female Iranian twins including 96 MZ individuals (48 pairs) and 58 DZ individuals (29 pairs) participated in the study. Clinical, biochemical and ultrasound tools were used to diagnose polycystic ovary syndrome. BITE questionnaire was filled out for subjects. Eight percent of subjects were diagnosed for subclinical eating disorder. No significant difference was found between intraclass correlation of MZ and DZ (z = 0.57, P = 0.569). Serum leptin level correlated significantly with bulimia score (P < 0.007). The mean (+/-SD) value for bulimia score was found to be higher among PCOS(positive) subjects (3.27 +/- 5.51) in comparison with PCOS(negative) subjects (2.06 +/- 4.48) (P < 0.001). The genetic property of subclinical eating disorder was not confirmed as shared environment might have played a major role in likeliness of DZ twins as well as MZ. Leptin is linked with both subclinical eating disorder and PCOS.

Matched MeSH terms: Polycystic Ovary Syndrome/genetics
Sterol regulatory element binding protein-1 (SREBP1) gene expression is similarly increased in polycystic ovary syndrome and endometrial cancer

Shafiee MN, Mongan N, Seedhouse C, Chapman C, Deen S, Abu J, et al.

Acta Obstet Gynecol Scand, 2017 May;96(5):556-562.
PMID: 28176325 DOI: 10.1111/aogs.13106

INTRODUCTION: Women with polycystic ovary syndrome have a three-fold higher risk of endometrial cancer. Insulin resistance and hyperlipidemia may be pertinent factors in the pathogenesis of both conditions. The aim of this study was to investigate endometrial sterol regulatory element binding protein-1 gene expression in polycystic ovary syndrome and endometrial cancer endometrium, and to correlate endometrial sterol regulatory element binding protein-1 gene expression with serum lipid profiles.
MATERIAL AND METHODS: A cross-sectional study was performed at Nottingham University Hospital, UK. A total of 102 women (polycystic ovary syndrome, endometrial cancer and controls; 34 participants in each group) were recruited. Clinical and biochemical assessments were performed before endometrial biopsies were obtained from all participants. Taqman real-time polymerase chain reaction for endometrial sterol regulatory element binding protein-1 gene and its systemic protein expression were analyzed.
RESULTS: The body mass indices of women with polycystic ovary syndrome (29.28 ± 2.91 kg/m(2) ) and controls (28.58 ± 2.62 kg/m(2) ) were not significantly different. Women with endometrial cancer had a higher mean body mass index (32.22 ± 5.70 kg/m(2) ). Sterol regulatory element binding protein-1 gene expression was significantly increased in polycystic ovary syndrome and endometrial cancer endometrium compared with controls (p

Matched MeSH terms: Polycystic Ovary Syndrome/genetics*