Microbiota endometriosis
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB26800 | ENA |
REPOSITORIES: ENA
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Project description:Endometriosis is a chronic, estrogen-dependent gynecological condition that affects approximately 10% of women of reproductive age. The most widely accepted theory of the etiology of endometriosis includes the process of retrograde menstruation, where menstrual effluent travels up the Fallopian tubes, accesses the peritoneal cavity, and in some people is able to establish endometriotic lesions. Recent reports suggest the uterus is not devoid of bacteria, as was once believed. Thus, the refluxed menstrual effluent may also carry bacteria along with it, and this bacteria has been suggested to contribute to inflammation, and establishment and growth of endometriotic lesions. Here, we sought to compare and contrast the uterine bacteria (endometrial microbiota) in women with surgically confirmed presence or absence of endometriosis using next-generation 16S rRNA gene sequencing. We obtained an average of more than 9000 sequence reads per endometrial biopsy, and found that the endometrial microbiota of women with endometriosis was more diverse (greater Shannon Diversity Index and greater proportion of ‘Other’ taxa) than that of symptomatic controls (women with pelvic pain, but with surgically confirmed absence of endometriosis; diagnosed with other benign gynecological conditions at surgery). The difference in endometrial microbiotas was supported in unsupervised cluster analyses where some clustering of endometrial microbiota by disease status (endometriosis vs. controls) was observed. The bacterial taxa enriched in the endometrial microbiota of women with endometriosis belonged to the Actinobacteria phylum, Oxalobacteraceae and Streptococcaceae families, and Tepidimonas genus, while those enriched in the symptomatic controls (without endometriosis) belonged to the Burkholderiaceae family, and Ralstonia genus. Taken together, our findings suggest the endometrial microbiota is perturbed in people with endometriosis.
2021-04-16 | GSE172172 | 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:Purpose- To identify the pathways and processes that are dysregulated in the eutopic endometrium of women with endometriosis Methods-RNA sequencing was used to detect and quantify the transcripts encoded by the whole genome in the eutopic endometrium. Mid-secretory phase eutopic endometrial samples from women with (n=4) and without endometriosis (n=4) were processed for RNA sequencing and the data were compared to identify the transcripts displaying differential abundance in women with endometriosis, compared to those without endometriosis (controls)
2021-03-28 | GSE153740 | GEO
Project description:Purpose- To identify the pathways and processes that are dysregulated in the eutopic endometrium of women with endometriosis Methods- RNA sequencing was used to detect and quantify the transcripts encoded by the whole genome in the eutopic endometrium. Mid-proliferative phase eutopic endometrial samples from women with (n=4) and without endometriosis (n=3) were processed for RNA sequencing and the data were compared to identify the transcripts displaying differential abundance in women with endometriosis, compared to those without endometriosis (controls)
2021-03-28 | GSE153739 | GEO
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: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:The objective of the study was to compare the transcriptome of the primary eutopic and ectopic endometrial stromal cells isolated from paired eutopic endometrium and peritoneal lesions from women with endometriosis (N = 5) exposed to normoxic (20% O2) or hypoxic (1% O2) conditions for 48 hours. Induced expression of TGFBI was found in ectopic cells and ectopic & eutopic cells exposed to hypoxia at both RNA and protein (secreted to the culture media) levels. TGFBI gene and protein expression ex vivo in euoptic endometrium of women with endometriosis and controls (women without endometriosis) was found to be increased in the proliferative phase of menstrual cycle compared to secretory phase.
2024-12-07 | GSE269530 | GEO
Project description:Uterine Atlas Endometriosis
Endometriosis is a chronic inflammatory disease driven by oestrogen, affecting around 10% of women of child-bearing again world-wide. It is described by the presence of endometrium-like tissue outside of the uterus (ectopic endometriosis tissue) and debilitating chronic pain. There is a lack of understanding of endometriosis pathogenesis, as well as cellular composition of both the eutopic endometrium and ectopic endometriosis tissue of endometriosis patients.There are therefore two main aims for this study. Using single cell genomics and spatial methods we aim to:
I) characterise endometrial cellular census in women with and without endometriosis
II) characterise cellular census of ectopic endometriosis tissue
Furthermore, we aim to establish endometrial organoids and endometriosis organoids from the samples collected and characterise these using single cell genomics and spatial methods.
This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/
| EGAS00001004725 | EGA
Project description:Endometrial Microbiota is More Diverse in Women with Endometriosis than Symptomatic Controls
| PRJNA722289 | ENA
Project description:Comparison of macrophages M1 (M1) and M2 (M2) from eutopic endometrium from women with and without endometriosis
2020-01-22 | GSE130435 | GEO