Estrobolome dysregulation is associated with altered immunometabolism in a mouse model of endometriosis
Ontology highlight
ABSTRACT:
ORGANISM(S): mouse gut metagenome
PROVIDER: GSE248213 | GEO | 2023/12/08
REPOSITORIES: GEO
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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:Gene expression profiling of hormone treated normal and endometriosis stromal fibroblast cells (eSF). We used Affymetrix Human Gene 1.0 ST arrays. Samples include 4 normal of no uterine pathology (NUP), 4 endometriosis stage I, 4 endometriosis stage IV samples, each treated with Estrogen (E2), Progesterone (P4), E2+P4, or vehicle (veh), for a total of 48 samples on the Affymetrix platform.
2020-02-21 | GSE145701 | GEO
Project description:Genome-wide DNA methylation profiling of hormone treated normal and endometriosis stromal fibroblast cells (eSF). The Illumina Infinium Methylation BeadChip array 450 (HM450) was used. Samples include 4 normal of no uterine pathology (NUP), 4 endometriosis stage I, 4 endometriosis stage IV samples, each treated with Estrogen (E2), Progesterone (P4), E2+P4, or vehicle (veh), for a total of 48 samples analyzed on HM450.
2020-02-22 | GSE130028 | GEO
Project description:Kidney stone disease is influenced by multiple factors, including but not limited to age, gender, genetic background, hydration status, diet and drug. Regarding the gender, epidemiologic data across the world has shown that females at the reproductive age (15-49 years) have lower incidence/prevalence of kidney stone disease approximately 1.5-2.5 folds as compared to males at the same age. However, this gap is narrower in the postmenopausal age, whereas the postmenopausal females with higher serum estrogen levels are less likely to have kidney stones. Furthermore, female stone formers (patients with kidney stones) are associated with lower estrogen levels. Therefore, estrogen has been proposed to serve as the protective hormone against kidney stone disease. However, the precise mechanisms underlying such protective effects of estrogen remain unclear and require further investigations. This study thus investigated the effects of estradiol (which is the most prevalent and potent form of estrogen in females at the reproductive age) on cellular proteome of renal tubular cells using a proteomics approach.
2019-09-09 | PXD014768 | 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:Endometriosis is a complex pathological condition in which multiple components are involved in the disease development and clinical outcome. Endometriosis is mainly an inflammatory codition estrogen-dependent, with unknown pathogenesis, that is characterized by dissemination of edometrium tissue in ectopic position (ovary or pelvic peritoneum). Two main theories rise the pathologic onset: the presence of retrograde menstruation and celomic metaplasia in the pelvic peritoneum, that can occur for development defects. Endometriosis is related not only to genetic or immunological changes and to environmental pollution factors, as the endocrine interferents. The disease phenotype results from multiple events (genetics and enviromental), thus it is difficult to find a single gene as causative while is more probable that a gene network/s might involved in the onset and mantainement of the disease state. The peculiarity of endometriosis rely on the tissue speificity manteinance in the ectopic position, where it responds to the hormone stimuli as the tissue in the eutopic position. In order to identify genes potentially involved in growth and mainteinance of the ectopic endometrium, we have profiled ectopic (8 samples) and eutopic endometrium (8 samples) from several affected woman in the proliferative phase. As control we used endometrium from normal health donors in the same phase (6 samples).
2013-11-30 | E-GEOD-25628 | biostudies-arrayexpress
Project description:Endometriosis is a complex pathological condition in which multiple components are involved in the disease development and clinical outcome. Endometriosis is mainly an inflammatory codition estrogen-dependent, with unknown pathogenesis, that is characterized by dissemination of edometrium tissue in ectopic position (ovary or pelvic peritoneum). Two main theories rise the pathologic onset: the presence of retrograde menstruation and celomic metaplasia in the pelvic peritoneum, that can occur for development defects. Endometriosis is related not only to genetic or immunological changes and to environmental pollution factors, as the endocrine interferents. The disease phenotype results from multiple events (genetics and enviromental), thus it is difficult to find a single gene as causative while is more probable that a gene network/s might involved in the onset and mantainement of the disease state. The peculiarity of endometriosis rely on the tissue speificity manteinance in the ectopic position, where it responds to the hormone stimuli as the tissue in the eutopic position.
2013-11-30 | GSE25628 | GEO
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:<p><strong>INTRODUCTION:</strong> Postmenopausal hormone use is linked to several health outcomes and the risk associated with some may differ depending on whether estrogen is used alone or in combination with progestin.</p><p><strong>OBJECTIVE:</strong> Metabolomic analyses of postmenopausal hormone use and differences between hormone regimes was carried out to identify metabolites associated with each type of hormone treatment.</p><p><strong>METHODS:</strong> Untargeted metabolomics analysis was carried out on serum from 1,336 women enrolled in the Cancer Prevention II Nutrition Cohort. Levels of 781 named metabolites were compared between 667 nonusers with 332 estrogen-only and with 337 estrogen plus progestin users using linear regression. Metabolite levels were also compared between estrogen-only and estrogen plus progestin users.</p><p><strong>RESULTS:</strong> Compared to nonusers, 276 metabolites were statistically significantly (P<6.40 x 10-5) associated with estrogen-only use and 222 were associated with estrogen plus progestin use. The metabolites associated with both types of hormones included numerous lipids, acyl carnitines, and amino acids as well as the thyroid hormone thyroxine and the oncometabolite fumarate. The 65 metabolites that differed significantly between estrogen-only and estrogen plus progestin users included 19 steroids and 12 lipids that contained the bioactive fatty acid arachidonic acid.</p><p><strong>CONCLUSIONS:</strong> These findings suggest that postmenopausal hormone use influences metabolic pathways linked to a variety of cellular processes, including the regulation of metabolism and stress responses, energy production, and inflammation. The differential association of numerous lipids that could influence cellular signaling suggests that differences in signal transduction may contribute to the disparate risks for some diseases between estrogen-only and estrogen plus progestin users.</p>
2019-06-02 | MTBLS136 | MetaboLights
Project description:An in-depth conjoint analysis of transcriptome and proteome abundance atlas on endometrial tissues was generated from 6 control females and 10 patients with endometriosis.
2024-05-12 | GSE212787 | GEO