Dataset Information

Symptomatology and Serum Nuclear Magnetic Resonance Metabolomics; Do They Predict Endometriosis in Fertile Women Undergoing Laparoscopic Sterilisation? A Prospective Cross-sectional Study

ABSTRACT: Endometriosis is a common, chronic inflammatory condition, thought to have a higher incidence in symptomatic women, yet, commonly associated symptoms do not always correlate with the presence or severity of disease and diagnosis requires surgery. We prospectively collected data and assessed symptomology and NMR spectroscopy-based metabolomics of 102 women undergoing laparoscopic sterilisation at a tertiary referral centre in a cross-sectional study. Twelve women were incidentally diagnosed with endometriosis (11.7%). According to the pre-operative questionnaire, presence and absence of many symptoms usually attributed to endometriosis were declared at similar frequencies in women with or without endometriosis. Women with endometriosis reported apparently more persistent heavy periods (50% vs 18.9%), prolonged periods (25% versus 7.8%) and problems conceiving (27.3% versus 9%) than those without endometriosis. NMR could not discern any distinguishable differences in the serum metabolome between those with and without endometriosis. Our paper highlights the complex symptomology experienced by women, regardless of a surgical diagnosis of endometriosis. Previous literature and the current study failed to identify clear, distinguishable symptoms or biomarkers pertinent to surgically confirmed endometriosis in the general population. Therefore, development of effective, non-invasive tests for identifying this heterogenous benign condition, endometriosis, is likely to be challenging.

INSTRUMENT(S): Nuclear Magnetic Resonance (NMR) -

SUBMITTER: Marie Margaret Phelan

PROVIDER: MTBLS2040 | MetaboLights | 2023-05-26

REPOSITORIES: MetaboLights

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Symptomatology and Serum Nuclear Magnetic Resonance Metabolomics; Do They Predict Endometriosis in Fertile Women Undergoing Laparoscopic Sterilisation? A Prospective Cross-sectional Study.

Tempest Nicola N Hill C J CJ Whelan A A De Silva A A Drakeley A J AJ Phelan M M MM Hapangama D K DK

Reproductive sciences (Thousand Oaks, Calif.) 20210915 12

Endometriosis is a common, chronic inflammatory condition, thought to have a higher incidence in symptomatic women, yet, commonly associated symptoms do not always correlate with the presence or severity of disease and diagnosis requires surgery. We prospectively collected data and assessed symptomology and NMR spectroscopy-based metabolomics of 102 women undergoing laparoscopic sterilisation at a tertiary referral centre in a cross-sectional study. Twelve women were incidentally diagnosed with ...[more]

PMID: 34524640

Similar Datasets

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.

			Action	DRS
	MTBLS2040	Other
	FILES	Other
	a_MTBLS2040_NMR___metabolite_profiling.txt	Txt
	files-all.json	Other
	i_Investigation.txt	Txt