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Clinical Trial Summary

The pathogenesis of endometriosis is very complex as several factors, including genetic, environmental and lifestyle-related factors, are involved in the development, progression and maintenance of the disease. In particular, there are emerging evidences that prostaglandin metabolism, chronic inflammatory processes and circulating estrogen levels are involved in the pathogenesis of endometriosis. Pelvic pain, in particular dysmenorrhea, is the most typical symptom caused by the production of prostaglandins and pain mediators associated with the peritoneal inflammatory state. Metabolomics strives to measure all metabolites, such as sugars, amino acids, acylcarnitines, organic acids, and lipids, present in a given biological sample. Thus, metabolomics represents a reflection of phenotypic changes in an organism in response to the presence of a certain disease, genetic changes, and nutritional, toxicological, environmental, and pharmacological influences, providing a means to more accurately capture exogenous exposures and evaluate endogenous biomarkers. Regarding endometriosis, the targeted metabolomics studies focused mainly on lipids, and the non-targeted studies also identified mainly lipids, amino acids, and intermediary metabolites as the most important variables. The combinations of metabolomics data together with clinical ones are of utmost importance in endometriosis research. This approach might lead to the construction of models/algorithms useful to better define diagnostic/prognostic characteristics of women who have endometriosis, identify environmental and modifiable risk factors, elucidate pathogenetic mechanisms, and contribute to better tailor medical treatments. In particular, metabolomics may provide a means to capture exogenous exposures and evaluate endogenous biomarkers more accurately. The main objective of the present research project is to evaluate potential variations in the plasma metabolomic profile of women affected by endometriosis (as compared with a control group) as a consequence of pathophysiologic alterations associated with this disorder. Secondary objectives are: 1. to evaluate potential variations in the plasma metabolomic profile of endometriosis patients with different phenotypes of the disease: peritoneal endometriosis, ovarian endometriosis, deep infiltrating endometriosis; 2. to evaluate potential variations in the plasma metabolomic profile of endometriosis patients in relation to the presence of endometriosis-related painful symptoms and/or infertility. There is strong evidence that endometriosis has a negative impact on women's quality of life, with severe long-term consequences and substantial social costs. Our findings might lead to the construction of models/algorithms useful to better define diagnostic/prognostic characteristics of women who have endometriosis, identify environmental and modifiable risk factors, elucidate pathogenetic mechanisms, and contribute to better tailoring medical treatments.


Clinical Trial Description

Endometriosis is defined as the presence of endometrial glands and stroma outside the uterine cavity. It is an estrogen-dependent chronic inflammatory disease, in which the ectopic endometrium grows and proliferate under the action of estradiol, which plays a pro-inflammatory and anti-apoptotic role. Ectopic endometrium can be found on the ovaries in the pelvic peritoneum, rectovaginal septum, and other pelvic sites; this thus defines at least three different entities: peritoneal, ovarian, and deep infiltrating endometriosis. Estimates show that up to 10% of premenopausal women and 35% to 50% of women with infertility, pelvic pain or both have endometriosis. Pelvic pain, in particular dysmenorrhea, is the most typical symptom of endometriosis, caused by the production of prostaglandins and pain mediators associated with the peritoneal inflammatory state. Thus, endometriosis significantly impairs the quality of life of women, with substantial social costs. The pathogenesis of endometriosis is very complex as several factors, including genetic, environmental and lifestyle-related factors, are involved in the development, progression and maintenance of the disease. In particular, there are emerging evidences that prostaglandin metabolism, chronic inflammatory processes and circulating estrogen levels are involved in the pathogenesis of endometriosis. Metabolomics strives to measure all metabolites, such as sugars, amino acids, acylcarnitines, organic acids, and lipids, present in a given biological sample. Metabolomics represents a reflection of phenotypic changes in an organism in response to the presence of a certain disease, genetic changes, and nutritional, toxicological, environmental, and pharmacological influences. In particular, metabolomics may provide a means to capture exogenous exposures and evaluate endogenous biomarkers more accurately. For example, a study on nutritional metabolomics and breast cancer risk- an estrogen-dependent disease as endometriosis and that shares similar diet-related risk factors such as high intake of alcohol, red meat and low intake of fruits and vegetables - found that pre-diagnostic serum concentrations of metabolites related to alcohol, vitamin E, and animal fats were associated with estrogen receptor positive (ER+) breast cancer risk. Regarding endometriosis, the targeted metabolomics studies focused mainly on lipids, and the non-targeted studies also identified mainly lipids, amino acids, and intermediary metabolites as the most important variables. The combinations of metabolomics data together with clinical ones are of utmost importance in endometriosis research. This approach might lead to the construction of models/algorithms useful to better define diagnostic/prognostic characteristics of women who have endometriosis, identify environmental and modifiable risk factors, elucidate pathogenetic mechanisms, and contribute to better tailoring medical treatments. As preliminary evidence suggests that endometriosis causes metabolic dysregulation, the investigators hypothesize that metabolomics could represent a promising method to diagnose women with endometriosis and women without endometriosis early. Moreover, the investigators hypothesized that the metabolic approach could represent a possible diagnostic tool that allows a better description of the disease phenotype (peritoneal, ovarian or deep infiltrating endometriosis), identifying new biomarkers and clarifying the metabolic pathways involved in the disease. In addition, this approach could represent a valuable tool to early identify women with endometriosis at risk to develop painful symptoms and/or infertility. There is strong evidence that endometriosis has a negative impact on women's quality of life, with severe long-term consequences that should be carefully addressed in developing national healthcare programs. Our findings may lead to the implementation of more effective instruments for early diagnosis and tools for identifying environmental and modifiable risk factors, particularly in relation to nutrition, elucidating the underlying pathogenetic mechanisms. Preliminary data: The first metabolomics study to identify novel biomarkers of endometriosis was published in 2012. In addition, a systematic review was recently published about the contribution of metabolomics to the identification of diagnostic and prognostic biomarkers for uterine diseases, including 17 studies on endometriosis. The targeted metabolomics studies focused mainly on lipids, and the non-targeted studies also identified mainly lipids, amino acids, and intermediary metabolites as the most important variables. The highest diagnostic accuracies were reported for the plasma/serum metabolic signatures that separated healthy women from endometriosis patients. For stratification between infertile women and endometriosis patients, a panel of serum metabolites was identified in a small case/control discovery study, with a high AUC of 0.99: lactate, 2-hydroxybutyrate, succinate, and lysine, the data on this issue are however very limited. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT05496218
Study type Interventional
Source Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico
Contact Paolo Vercellini, Prof.
Phone 0255032318
Email paolo.vercellini@unimi.it
Status Recruiting
Phase N/A
Start date April 9, 2022
Completion date February 28, 2024

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