Next-Generation Endometriosis Diagnostics Through Comprehensive Multi-Dimensional Analysis
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 530
- 试验地点
- 2
- 主要终点
- Identification of epigenetic profile
研究概览
简要总结
This study is a multicentric, observational, case-control, non-profit with additional procedures. It aims to deepen the understanding of the chronic gynecological conditions of endometriosis and adenomyosis, which significantly impact women's reproductive health. Its purpose is to improve early diagnosis and personalized treatment of these conditions using a multi-omic approach, that integrates genetic, epigenetic, imaging, and endometrial receptivity data. The goal is also to refine image-based predictions through recent advancements in artificial intelligence and to study uterine extracellular vesicles to assess fertility non-invasively.
The study targets patients with endometriosis and/or adenomyosis and involves women seeking fertility treatments at assisted reproduction centers, who will serve as a control population.
The study comprises both prospective and retrospective components. The prospective recruitment involves the collection of blood and uterine fluid samples, while the retrospective element utilizes pre-existing biobank samples for comprehensive genetic and epigenetic analysis.
详细描述
Recent research indicates that epigenetic blood analysis could revolutionize the diagnosis of endometriosis, moreover, strong correlations between endometrial and blood methylation have been reported, suggesting significant diagnostic potential. Preliminary data on Polygenic Risk Scores (PRS) also show promise in identifying genetic profiles associated with disease severity.
Advancements in artificial intelligence (AI) offer precise image-based diagnostic predictions, highlighting the transformative potential of integrating AI with genetic analyses. Additionally, our preliminary studies have demonstrated the potential of using gene expression data from uterine fluid extracellular vesicles (UF-EVs) to understand endometrial receptivity, with implications for detecting both endometriosis and adenomyosis.
Through this study, the investigators hypothesize that differential methylation profiles, integrated with genetic, epigenetic, and clinical data, can accurately classify endometriosis and adenomyosis cases. Additionally, it's hypothesized that UF-EVs gene expression profiles differ significantly between endometriosis, adenomyosis, and fertile controls, providing critical insights into endometrial receptivity and potential diagnostic markers for these conditions.
Primary Objective:
To identify specific CpG sites that exhibit differential methylation levels between endometriosis cases and controls. These methylation profiles, combined with polygenic risk scores (PRS) and clinical questionnaire data, will be used to classify cases and controls through machine learning analysis. (Aim 1) In addition to the differential methylation analysis, 'high-resolution SNP genotyping' will be employed. This genotyping will adjust the methylation analysis and aid in deriving polygenic risk scores.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Control
- 时间视角
- Other
入排标准
- 年龄范围
- 18 Years 至 40 Years（Adult）
- 性别
- Female
- 接受健康志愿者
- 是
入选标准
- •Participants eligible for cases with endometriosis and adenomyosis, must meet the following criteria:
- •Able to give informed consent for participation in the study.
- •European descent.
- •Confirmed diagnosis of both endometriosis and adenomyosis through ultrasound screening.
- •Listed for assisted reproductive treatment, specifically within their first or second IVF cycle.
- •Participants eligible for cases with only endometriosis must meet the following criteria:
- •Able to give informed consent for participation in the study.
- •European descent.
- •Confirmed diagnosis of endometriosis with no ultrasound evidence of adenomyosis.
- •Enrolled in an assisted reproductive treatment cycle involving embryo thawing.
- •Participants eligible for cases with only adenomyosis must meet the following criteria:
- •Able to give informed consent for participation in the study.
- •European descent.
- •Confirmed diagnosis of adenomyosis with no ultrasound evidence of endometriosis.
- •Enrolled in an assisted reproductive treatment cycle involving embryo thawing.
- •Participants eligible as controls must meet the following criteria:
- •Able to give informed consent for participation in the study.
- •European descent.
- •Undergone ultrasound screenings that have excluded the presence of endometriosis or adenomyosis.
- •Listed for assisted reproductive treatment, specifically within their first or second IVF cycle.
- •Presence of reduced ovarian reserve or non-severe male factor infertility.
排除标准
- •Patients unable or unwilling to sign the informed consent
- •Individuals who exhibit the presence of sactosalpinx or other uterine pathologies such as fibroids, polyps, or irregular endometrial thickening will be excluded from participation in this study.
- •These exclusion criteria are applicable across all groups to ensure the accuracy and reliability of the study's findings related to endometriosis and adenomyosis.
结局指标
主要结局
Identification of epigenetic profile
时间窗: 2 years
To identify specific CpG sites that exhibit differential methylation levels between endometriosis cases and controls. These methylation profiles, polygenic risk scores (PRS), and clinical questionnaire data will be used to classify cases and controls through machine learning analysis.
Identification of genetic profile
时间窗: 2 years
In addition to the differential methylation analysis, 'high-resolution SNP genotyping' will be employed. This genotyping will adjust the methylation analysis and aid in deriving polygenic risk scores.
次要结局
- Development and validation of a diagnostic model(2 years)
研究者
Candiani Massimo
Principal Investigator
IRCCS San Raffaele