Next-Generation Endometriosis Diagnostics Through Comprehensive Multi-Dimensional Analysis (AdEnd)

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.

Study Overview

• Status: Recruiting
• Conditions: Endometriosis; Adenomyosis
• Intervention / Treatment: Other: No intervention

Detailed Description

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.

Secondary Objectives:

To develop and validate a diagnostic model integrating ultrasound imaging with genetic, epigenetic, and clinical data to accurately identify and differentiate adenomyosis as an extension of endometriosis, and to predict pregnancy outcomes in women undergoing IVF. (Aim 2)

Tertiary Objectives:

To characterize the gene expression profiles of uterine fluid extracellular vesicles (UF-EVs) specific to endometriosis and adenomyosis will be analyzed samples at two critical time points: LH+2 (non-receptive) and LH+7 (receptive). The obtained gene expression data will be compared against previously collected data from fertile and infertile patients. By comparing these profiles, the investigators aim to identify distinct molecular signatures associated with each condition, enhancing our understanding of their impact on fertility and endometrial receptivity. Also, this comparison will allow us to refine diagnostic markers and potentially develop targeted interventions for affected women. (Aim 3)

This study is conducted as a multicenter project, involving two Assisted Reproduction Centers, it will include a diverse cohort of 800 women. The study involves 530 participants and three distinct groups: women diagnosed with endometriosis, women diagnosed with both endometriosis and adenomyosis, and a control group of infertile women without these conditions. Each group will participate in the study, it is planned to last 24 months from the onset of recruitment to the final analysis of collected data. An additional group will consist of 300 DNA biobanked samples from women diagnosed with endometriosis.

• Study Type: Observational
• Enrollment (Estimated): 530

Contacts and Locations

• Study Contact: Name: LUCA PAGLIARDINI; Phone Number: 0039 0226434834; Email: pagliardini.luca@hsr.it
• Study Contact Backup: Name: ENRICO PAPALEO; Phone Number: 0039 0226434310; Email: papaleo.enrico@hsr.it

Study Locations

• Italy
  • Catanzaro
    • Catanzaro, Catanzaro, Italy, 88100
      • Active, not recruiting
      • Azienda Ospedaliero Universitaria Renato Dulbecco di Catanzaro
  • Milano
    • Milan, Milano, Italy, 20132
      • Recruiting
      • IRCCS San Raffaele Hospital
      • Contact: LUCA PAGLIARDINI; Phone Number: +39 02 2643 4834; Email: pagliardini.luca@hsr.it
      • Principal Investigator: Massimo Candiani, MD
      • Sub-Investigator: Enrico Papaleo, MD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

The study will involve a total of 530 participants selected from two Assisted Reproduction Centers. The participant population includes:

• Group A: 100 women diagnosed with both endometriosis and adenomyosis (cases).
• Group B: 15 women diagnosed exclusively with endometriosis (cases).
• Group C: 15 women diagnosed exclusively with adenomyosis (cases).
• 400 women from couples seeking fertility treatment at infertility clinics (controls).

Additionally, Group D will consist of 300 DNA biobank samples from women diagnosed with endometriosis.

Description

Inclusion Criteria:

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.

Exclusion Criteria:

• 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.

Study Plan

How is the study designed?

Number of groups / cohorts

5

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Cases with both endometriosis and adenomyosis; 100 women diagnosed with both endometriosis and adenomyosis (cases). These participants are part of couples seeking fertility treatment at Assisted Reproduction Centers. The diagnosis of both endometriosis and adenomyosis will be made through ultrasound imaging at the IVF centers. The recruitment involves the collection of blood for genetic and epigenetic analysis, and acquiring ultrasound images for machine learning analysis.	Other: No intervention; No intervention
Cases with only endometriosis; 15 women diagnosed exclusively with endometriosis (cases): This subgroup consists of women who have been diagnosed with endometriosis but show no ultrasound evidence of adenomyosis. The recruitment involves the collection of blood for genetic and epigenetic analysis, acquiring ultrasound images for machine learning analysis, and collecting uterine fluid samples to study gene expression profiles through uterine fluid extracellular vesicles (UF-EVs).	Other: No intervention; No intervention
Cases with only adenomyosis; 15 women diagnosed exclusively with adenomyosis (cases): This subgroup includes women diagnosed solely with adenomyosis, without any ultrasonographic signs of endometriosis. The recruitment involves the collection of blood for genetic and epigenetic analysis, acquiring ultrasound images for machine learning analysis, and collecting uterine fluid samples to study gene expression profiles through uterine fluid extracellular vesicles (UF-EVs).	Other: No intervention; No intervention
Controls; 400 women from couples seeking fertility treatment at infertility clinics (controls): These participants, who will be part of couples attempting to conceive, will be actively seeking treatment for infertility or other gynecological symptoms. Crucially, these individuals will have undergone ultrasound screenings that have excluded the presence of endometriosis or adenomyosis. The recruitment involves the collection of blood for genetic and epigenetic analysis, and acquiring ultrasound images for machine learning analysis.	Other: No intervention; No intervention
Cases of endometriosis with pre-existing genotyping data; This group will consist of 300 DNA biobanked samples from women diagnosed with endometriosis. These samples come with pre-existing genotyping data, which will be integrated into the study to provide a robust genetic baseline for comparative analyses.	Other: No intervention; No intervention

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Identification of epigenetic profile	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.	2 years
Identification of genetic profile	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.	2 years

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Development and validation of a diagnostic model	To develop and validate a diagnostic model integrating ultrasound imaging with genetic, epigenetic, and clinical data to accurately identify and differentiate adenomyosis as an extension of endometriosis, and to predict pregnancy outcomes in women undergoing IVF.	2 years

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Characterization of uterine fluid extracellular vesicles (UF-EVs)	To characterize the gene expression profiles of uterine fluid extracellular vesicles (UF-EVs) specific to endometriosis and adenomyosis, we will analyze samples at two critical time points: LH+2 (non-receptive) and LH+7 (receptive). We will compare the obtained gene expression data against previously collected data from fertile and infertile patients. By comparing these profiles, we aim to identify distinct molecular signatures associated with each condition, enhancing our understanding of their impact on fertility and endometrial receptivity. Also, this comparison will allow us to refine diagnostic markers and potentially develop targeted interventions for affected women.	2 years

Collaborators and Investigators

• Sponsor: IRCCS San Raffaele
• Collaborators: AUO Renato Dulbecco
• Investigators: Principal Investigator: MASSIMO CANDIANI, IRCCS San Raffaele

Publications and helpful links

General Publications

• Giacomini E, Scotti GM, Vanni VS, Lazarevic D, Makieva S, Privitera L, Signorelli S, Cantone L, Bollati V, Murdica V, Tonon G, Papaleo E, Candiani M, Vigano P. Global transcriptomic changes occur in uterine fluid-derived extracellular vesicles during the endometrial window for embryo implantation. Hum Reprod. 2021 Jul 19;36(8):2249-2274. doi: 10.1093/humrep/deab123.
• Vercellini P, Vigano P, Bandini V, Buggio L, Berlanda N, Somigliana E. Association of endometriosis and adenomyosis with pregnancy and infertility. Fertil Steril. 2023 May;119(5):727-740. doi: 10.1016/j.fertnstert.2023.03.018. Epub 2023 Mar 21.

Study record dates

Study Major Dates

• Study Start (Actual): November 7, 2024
• Primary Completion (Estimated): February 28, 2026
• Study Completion (Estimated): August 30, 2026

Study Registration Dates

• First Submitted: August 23, 2024
• First Submitted That Met QC Criteria: August 23, 2024
• First Posted (Actual): August 27, 2024

Study Record Updates

• Last Update Posted (Estimated): October 7, 2025
• Last Update Submitted That Met QC Criteria: October 2, 2025
• Last Verified: October 1, 2025

More Information

Terms related to this study

• Keywords: Genetic; Endometriosis; Adenomyosis; Prospective; Retrospective; Case-control; Epigenetic; Machine learning
• Additional Relevant MeSH Terms: Urogenital Diseases; Genital Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Uterine Diseases; Genital Diseases, Female; Adenomyosis; Endometriosis
• Other Study ID Numbers: PNRR-MCNT2-2023-12378346

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No