Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Coding and Non-coding gene expression signatures of granulosa cells from Polycystic Ovary Syndrome Patients

ABSTRACT: Polycystic ovary syndrome (PCOS), one of the most common endocrinal diseases among reproductive-aged women,is characterized by hyperandrogenemia, chronic oligo/anovulation and polycystic ovarian morphology. In this research, we presented microarrays to identify the differential expressed protein-coding genes and lncRNAs expression profile in the luteinized granulosa cells obtained from PCOS and healthy control patients.

ORGANISM(S): Homo sapiens

PROVIDER: GSE114419 | GEO | 2018/10/30

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Coding and Non-coding gene expression signatures of endometrium from Polycystic Ovary Syndrome Patients

Project description:Polycystic ovary syndrome (PCOS), one of the most common endocrinal diseases among reproductive-aged women, is characterized by hyperandrogenemia, chronic oligo/anovulation and polycystic ovarian morphology. In this research, we presented microarrays to identify the differential expressed protein-coding genes and lncRNAs expression profile in the endometrium during the window of implantation between the PCOS and healthy subjects.

2019-09-13 | GSE137354 | GEO

Differential Gene Expression in Granulosa Cells from Polycystic Ovary Syndrome Patients with and without Insulin Resistance: Identification of Susceptibility Gene Sets through Network Analysis

Project description:Polycystic ovary Syndrome (PCOS) is a heterogeneous endocrine disorder that shows evidence of genetic predidposition among affected individuals. We have utilized the Microarray data from granulosa cells of normal and PCOS women for network construction. Human granulosa cells were isolated from ovarian aspirates from normal and PCOS women undergoing IVF and for each sample, RNA was extracted and hybridized to an Affymetrix GeneChip.

2012-11-06 | E-GEOD-34526 | biostudies-arrayexpress

Different gene expression profiles of granulosa cells in Chinese obese patients with or without polycystic ovary syndrome

Project description:Obese or polycystic ovary syndrome (PCOS) women have encountered poor reproductive outcomes in natural as well as assisted conception. Furthermore, pregnancy complications of women with PCOS are profoundly worsened by obesity. Both obesity and PCOS affect function of granulosa cells, which is essential in offering the oocyte with nutrients and growth regulators.

2021-04-14 | GSE80432 | GEO

Differential Gene Expression in Granulosa Cells from Polycystic Ovary Syndrome Patients with and without Insulin Resistance: Identification of Susceptibility Gene Sets through Network Analysis

2012-11-06 | GSE34526 | GEO

Gene Expression Data of Adipose Stem Cells from Normal-Weight Polycystic Ovary Syndrome Women vs. Controls

Project description:In vitro studies of subcutaneous (SC) abdominal adipose stem cells (ASC) from women with polycystic ovary syndrome (PCOS) show altered ASC commitment to preadipocytes and differentiation to mature adipocytes related to hyperandrogenism. The goal of the study is to use microarrays to examine whether SC abdominal ASC gene expression are altered in normal-weight PCOS women and correlated with hyperandrogenemia and/or insulin resistance, which are prevalent clinical pathologies of PCOS.

2019-01-24 | GSE124226 | GEO

Whole genomic DNA methylation analysis across human polycystic ovary syndrome ovary granulosa cells [MBD-seq]

Project description:Aberration in miRNA expression or DNA methylation is a causal factor for numerous pathological conditions including polycystic ovarian syndrome PCOS, a common endocrine disorders and leading cause of infertility. The epigenetic interactions between miRNA and DNA methylation remain unexplored in PCOS. Our study identifies epigenetic alternation in ovarian granulosa cells from PCOS patients and helps to reveal the pathogenesis of PCOS.

2019-10-09 | GSE138573 | GEO

Identification of microRNAs involved in polycystic ovary syndrome based on High-throughput sequencing [miRNA-seq]

Project description:Aberration in miRNA expression or DNA methylation is a causal factor for numerous pathological conditions including polycystic ovarian syndrome PCOS, a common endocrine disorders and leading cause of infertility. The epigenetic interactions between miRNA and DNA methylation remain unexplored in PCOS. Few studies have reported that the regulation of miRNAs in polycystic ovary syndrome(PCOS). Our study helps to understand the molecular pathogenesis of PCOS in human ovarian granulosa cells from the perspective of post-transcriptional level.

2019-10-09 | GSE138572 | GEO

Transcriptome Profiling Reveals the key genes and pathways involved in polycystic ovary syndrome [RNA-seq]

Project description:Aberration in miRNA expression or DNA methylation is a causal factor for numerous pathological conditions including polycystic ovarian syndrome PCOS, a common endocrine disorders and leading cause of infertility. The epigenetic interactions between miRNA and DNA methylation remain unexplored in PCOS. Few studies have reported that the key genes and pathways involved in polycystic ovary syndrome(PCOS). Our study helps to understand the molecular pathogenesis of PCOS in human ovarian granulosa cells and identifiy genes and pathways that may be potential therapeutic targets for PCOS treatment..

2019-10-08 | GSE138518 | GEO

Multiomics analysis reveals molecular abnormalities in granulosa cells of women with polycystic ovary syndrome

Project description:Polycystic ovary syndrome (PCOS) is the most common complex endocrine and metabolic disease in women of reproductive age. It is characterized by anovulatory infertility, hormone disorders, and polycystic ovarian morphology. Regarding the importance of granulosa cells (GCs) in the pathogenesis of PCOS, few studies have investigated the etiology at a single “omics” level, such as with an mRNA expression array or methylation profiling assay, but this can provide only limited insights into the biological mechanisms. Here, genome-wide DNA methylation together with lncRNA-miRNA-mRNA profiles were simultaneously detected in GCs of PCOS cases and controls. A total of 3579 lncRNAs, 49 miRNAs, 669 mRNAs, and 890 differentially methylated regions (DMR)-associated genes were differentially expressed between PCOS cases and controls. Pathway analysis indicated that these differentially expressed genes were commonly associated with steroid biosynthesis and metabolism-related signaling, such as glycolysis/gluconeogenesis. In addition, we constructed ceRNA networks and identified some known ceRNA axes, such as lncRNAs-miR-628-5p-CYP11A1/HSD17B7. We also identified many new ceRNA axes, such as lncRNAs-miR-483-5p-GOT2. Interestingly, most ceRNA axes were also closely related to steroid biosynthesis and metabolic pathways. These findings suggest that it is important to systematically consider the role of reproductive and metabolic genes in the pathogenesis of PCOS.

2021-03-08 | GSE168404 | GEO

High-Fat High-Sugar Diet Induces Polycystic Ovary Syndrome in a Rodent Model

Project description:Obesity has been linked with a host of metabolic and reproductive disorders including polycystic ovary syndrome (PCOS). While a distinct link exists between obesity and PCOS, the exact pathogenesis of the disease remains less understood and limited research has explored the impact of diet on the development of PCOS. With the primary symptoms of PCOS including hyperandrogenism, anovulation, and polycystic ovaries, most animal models utilize androgen treatment to effectively induce PCOS. However, these models fail to address the underlying causes of disease symptoms and do not effectively demonstrate the metabolic features of the disease such as hyperinsulinemia. Here, we present a novel rodent model of diet-induced obesity that recapitulates both the metabolic and reproductive phenotypes of human PCOS. In utilizing a high-fat high-sugar (HFHS) diet, we have created a model of PCOS that allows for the study of metabolic parameters and their impact on ovarian follicle development and reproductive health. Animals on the HFHS diet not only demonstrated signs of metabolic impairment, but they also developed polycystic ovaries and experienced irregular estrous cycling marked by an extended period spent in estrus. Though hyperandrogenism was not characteristic of HFHS diet animals as a group, testosterone levels were predictive of a polycystic ovarian morphology. Importantly, PCOS was induced similarly to the disease etiology in humans, allowing this model to offer the unique opportunity to study PCOS at its genesis rather than following the development of disease symptoms.

2017-06-01 | GSE83220 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data