Endometrial methylome of patients without endometriosis
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE73949 | GEO | 2016/02/15
SECONDARY ACCESSION(S): PRJNA298577
REPOSITORIES: GEO
Similar Datasets
Project description:Alterations in endometrial DNA methylation profile have been proposed as one potential mechanism initiating the development of endometriosis. However, the normal endometrial methylome is influenced by the cyclic hormonal changes and the menstrual cycle phase-dependent epigenetic signature should be considered when studying endometrial disorders. So far, no studies have been performed to evaluate the menstrual cycle influences and endometriosis-specific endometrial methylation pattern at the same time. Therefore, we used Infinium HumanMethylation 450K BeadChip arrays to explore DNA methylation profiles of endometrial tissues from various menstrual cycle phases. Infinium HumanMethylation 450K BeadChip arrays were used to explore DNA methylation profiles of endometrial tissues from various menstrual cycle phases from 24 patients with endometriosis
2016-02-15 | E-GEOD-73948 | biostudies-arrayexpress
Project description:Alterations in endometrial DNA methylation profile have been proposed as one potential mechanism initiating the development of endometriosis. However, the normal endometrial methylome is influenced by the cyclic hormonal changes and the menstrual cycle phase-dependent epigenetic signature should be considered when studying endometrial disorders. So far, no studies have been performed to evaluate the menstrual cycle influences and endometriosis-specific endometrial methylation pattern at the same time. Therefore, we used Infinium HumanMethylation 450K BeadChip arrays to explore DNA methylation profiles of endometrial tissues from various menstrual cycle phases. Infinium HumanMethylation 450K BeadChip arrays were used to explore DNA methylation profiles of endometrial tissues from mid secretory cycle phase from 17 patients without endometriosis
2016-02-15 | E-GEOD-73949 | biostudies-arrayexpress
Project description:Alterations in endometrial DNA methylation profile have been proposed as one potential mechanism initiating the development of endometriosis. However, the normal endometrial methylome is influenced by the cyclic hormonal changes and the menstrual cycle phase-dependent epigenetic signature should be considered when studying endometrial disorders. So far, no studies have been performed to evaluate the menstrual cycle influences and endometriosis-specific endometrial methylation pattern at the same time. Therefore, we used Infinium HumanMethylation 450K BeadChip arrays to explore DNA methylation profiles of endometrial tissues from various menstrual cycle phases.
2016-02-15 | GSE73948 | GEO
Project description:Endometriosis is a leading cause of pain and infertility affecting millions of women globally. Biological and genetic effects on DNA methylation (DNAm) can influence gene regulation and contribute to complex disease. Herein, we characterize variation in endometrial DNAm and its association with menstrual cycle phase, endometriosis, and genetic variants through analysis of genome-wide genotype data and methylation at 759,345 DNAm sites in endometrial samples from 984 deeply-phenotyped participants. We estimate that 15.4% of the variation in endometriosis is captured by DNAm and identify significant differences in DNAm profiles and DNAm networks, associated with endometriosis, endometriosis sub-phenotypes and menstrual cycle phase, including opening of the window for embryo implantation. DNAm quantitative trait locus (mQTL) analysis identified 118,185 independent cis-mQTLs including 51 associated with risk of endometriosis highlighting candidate genes contributing to disease risk. Our work provides functional evidence for epigenetic targets contributing to endometriosis risk and pathogenesis. Data generated serve as a valuable resource for understanding tissue-specific effects of methylation on endometrial biology in health and disease.
2023-09-12 | GSE223817 | GEO
Project description:Endometriosis, an estrogen-dependent, progesterone-resistant, inflammatory disorder affects 10% of reproductive-age women. It is diagnosed and staged at surgery, resulting in an 11-year latency from symptom onset to diagnosis, underscoring the need for less invasive, less expensive approaches. Since the uterine lining (endometrium) in women with endometriosis has altered molecular profiles, we tested whether molecular classification of this tissue can distinguish and stage disease. We developed classifiers using genomic data from n=148 archived endometrial samples from women with endometriosis or without endometriosis (normal controls or with other common uterine/pelvic pathologies) across the menstrual cycle and evaluated their performance on independent sample sets. Classifiers were trained separately on samples in specific hormonal milieu, using margin tree classification, and accuracies were scored on independent validation samples. Classification of samples from women with endometriosis or no endometriosis involved two binary decisions each based on expression of specific genes. These first distinguished presence or absence of uterine/pelvic pathology and then no endometriosis from endometriosis, with the latter further classified according to severity (minimal/mild or moderate/severe). Best performing classifiers identified endometriosis with 90-100% accuracy, were cycle phase-specific or independent, and utilized relatively few genes to determine disease and severity. Differential gene expression and pathway analyses revealed immune activation, altered steroid and thyroid hormone signaling/metabolism and growth factor signaling in endometrium of women with endometriosis. Similar findings were observed with other disorders versus controls. Thus, classifier analysis of genomic data from endometrium can detect and stage pelvic endometriosis with high accuracy, dependent or independent of hormonal milieu. We propose that limited classifier candidate-genes are of high value in developing diagnostics and identifying therapeutic targets. Discovery of endometrial molecular differences in the presence of endometriosis and other uterine/pelvic pathologies raises the broader biological question of their impact on the steroid hormone response and normal functions of this tissue. We analyzed endometrial samples from n=148 women without or with endometriosis and/or other uterine/pelvic pathologies, using whole genome microarrays.
2014-10-01 | E-GEOD-51981 | biostudies-arrayexpress
Project description:The objectives of the study: 1. Does the phase of the menstrual cycle alter microRNA (miRNA) plasma profiles in healthy women of reproductive age and in women with endometriosis? 2. Does this alter prospects for development of a miRNA-based diagnostic test for endometriosis? Prospectively recruited asymptomatic control women and women with surgically diagnosed endometriosis (n = 8 in each group) were included. Each patient provided blood samples in the early proliferative, late proliferative and mid luteal phases of the menstrual cycle (n = 47 total plasma samples). The cycle phase was verified by hormonal profile. RNA was extracted from each sample and expression of microRNAs was assessed using TaqMan Low Density Human miRNA arrays.
2013-05-09 | E-GEOD-46735 | biostudies-arrayexpress
Project description:This project aims at comparing endometrium from women with and without endometriosis during the secretory phase of menstrual cycle. The present results constitute a first step towards identifying potential diagnosis biomarkers and may provide a better understanding of endometriosis especially the etiology of the disease.
2022-04-01 | PXD012981 | Pride
Project description:The transition of regularly cycling endometrium from the proliferative or Estrogen-dominant phase of the menstrual cycle to the Progesterone-dominant Early and Mid Secretory phases requires wide-spread changes in gene expression that shift the endometrium from a proliferative capacity to a differentiated 'decidual' phenotype in preparation for implantation. This process appears delayed in women with severe endometriosis, suggestive of a progesterone resistant endometrium in this disease. Experiment Overall Design: Endometrial biopsies were obtained from women both with normal endometrial pathologies and no history of endometriosis and from women with laporoscopy proven moderate-severe stage endometriosis. Samples were collected from the Proliferative(PE), Early Secretory (ESE) and Midsecretory (MSE) phases. Samples were then processed for Total RNA isolation and Affymetrix chip hybridization.
2008-04-09 | E-GEOD-6364 | biostudies-arrayexpress
Project description:Endometriosis, an estrogen-dependent, progesterone-resistant, inflammatory disorder affects 10% of reproductive-age women. It is diagnosed and staged at surgery, resulting in an 11-year latency from symptom onset to diagnosis, underscoring the need for less invasive, less expensive approaches. Since the uterine lining (endometrium) in women with endometriosis has altered molecular profiles, we tested whether molecular classification of this tissue can distinguish and stage disease. We developed classifiers using genomic data from n=148 archived endometrial samples from women with endometriosis or without endometriosis (normal controls or with other common uterine/pelvic pathologies) across the menstrual cycle and evaluated their performance on independent sample sets. Classifiers were trained separately on samples in specific hormonal milieu, using margin tree classification, and accuracies were scored on independent validation samples. Classification of samples from women with endometriosis or no endometriosis involved two binary decisions each based on expression of specific genes. These first distinguished presence or absence of uterine/pelvic pathology and then no endometriosis from endometriosis, with the latter further classified according to severity (minimal/mild or moderate/severe). Best performing classifiers identified endometriosis with 90-100% accuracy, were cycle phase-specific or independent, and utilized relatively few genes to determine disease and severity. Differential gene expression and pathway analyses revealed immune activation, altered steroid and thyroid hormone signaling/metabolism and growth factor signaling in endometrium of women with endometriosis. Similar findings were observed with other disorders versus controls. Thus, classifier analysis of genomic data from endometrium can detect and stage pelvic endometriosis with high accuracy, dependent or independent of hormonal milieu. We propose that limited classifier candidate-genes are of high value in developing diagnostics and identifying therapeutic targets. Discovery of endometrial molecular differences in the presence of endometriosis and other uterine/pelvic pathologies raises the broader biological question of their impact on the steroid hormone response and normal functions of this tissue.
2014-10-01 | GSE51981 | GEO
Project description:Whole genome expression analyses of autologous, paired eutopic and ectopic endometrial samples obtained during proliferative and secretory phases of menstrual cycles from eighteen (n=18) fertile women suffering from confirmed stage 3 (moderate) and stage 4 (severe) ovarian endometriosis were performed using whole human genome oligo microarray Agilent paltform (Cat. No. G4112F). In the present study, genome-wide expression analysis of autologous, paired eutopic and ectopic endometrial samples obtained during proliferative (n=13) and secretory (n=5) phases of menstrual cycle from fertile women (n=18) suffering from moderate (stage 3; n=8) or severe (stage 4; n=10) endometrioma was performed by using Agilent single color oligo microarray platform (G4112, 4X44K). Thus eighteen (18) eutopic (shown as EU) and eighteen (18) ectopic (shown as EC) samples from eighteen (18) subjects with confirmed menstrual phase (proliferative and secretory) and severity stages (stage 3 and stage 4) were studied.
2012-09-30 | E-GEOD-37837 | biostudies-arrayexpress