Evaluation of Genetic Signature in Endometriosis Disease by Non Invasive Sampling

NCT06100471 | Enrolling By Invitation

• 1 other identifier: 01-23
• Study Type: observational
• Target: 150
• Locations: 1 country
• Sites: 1

Brief Summary

Endometriosis is a disease that affects 10-15% of the general population and 50% of infertile women. It is characterized by the presence of endometrial tissue outside the uterine cavity. Endometriosis can lead to infertility by interfering through endocrine and mechanical alterations on the function of the ovaries, fallopian tubes, and uterus. The aim of the study is to define the differential expression of a cluster of RNAs tissue driven for the identification of an RNA profile in saliva, specific for endometriosis. This study focuses on the expression of genes involved in the control and regulation of apoptosis, cell survival, metabolism, cell adhesion and invasion, angiogenesis, inflammation, and estrogen receptor expression levels.

Conditions

Endometriosis; Hypofertility

Keywords

endo

Outcome Measures

Primary Outcomes (2)

• Next Generation Sequencing technical validation

  Assessing the quality of Next Generation Sequencing via the FASTQC tool. Following benchmarks will be considered: 1.1 Per base sequence quality \[Phred score: positive real number, the higher the better\] 1.2 Total number of sequenced reads \[integer: positiver integer number, the higher the better\]

  1 month

• Wet lab kit validation

  Assessing the quality of the kit by mapping the reads against public miRNA databases. Following benchmark will be considered: Total reads mapped \[integer\]

  1 month

Secondary Outcomes (3)

• Tissue validation

  2 months

• Clinical validation

  4 months

• Biomarkers identification

  7 months

Study Arms (3)

case

Patients with endometriotic adnexal pathology

Other: Observational study

control

Patients with non endometriotic adnexal pathology

Other: Observational study

analytical control

Patients with no gynecological pathology, not undergoing surgery

Other: Observational study

Interventions

Observational study OTHER

Observational study in different tissues in identifing new genetic markers related to endometriosis disease

analytical control; case; control

Eligibility Criteria

• Age: 18 Years - 45 Years
• Sex: female
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

Groups of study: * patients with diagnosed endometriotic adnexal pathology (case, CA) * patients with non-endometriotic adnexal pathology (control, CO) * patients with no gynecological pathology, not undergoing surgery (analytical control)

You may qualify if:

• Case population (CA), patients with endometriotic adnexal pathology
• Control population (CO), patients with non-endometriotic adnexal pathology
• Analytical control population (C-), patients with no gynecologic pathology, not undergoing surgery

You may not qualify if:

• Pregnant patient
• Patient with a personal history of cancer
• Patient infected with HIV

Sponsors & Collaborators

• Eurofins Genoma: lead

Study Sites (1)

Eurofins Genoma

Rome, 00138, Italy

Location

Related Publications (6)

• Dabi Y, Suisse S, Puchar A, Delbos L, Poilblanc M, Descamps P, Haury J, Golfier F, Jornea L, Bouteiller D, Touboul C, Darai E, Bendifallah S. Endometriosis-associated infertility diagnosis based on saliva microRNA signatures. Reprod Biomed Online. 2023 Jan;46(1):138-149. doi: 10.1016/j.rbmo.2022.09.019. Epub 2022 Sep 27.

  PMID: 36411203 BACKGROUND

• Bendifallah S, Dabi Y, Suisse S, Jornea L, Bouteiller D, Touboul C, Puchar A, Darai E. A Bioinformatics Approach to MicroRNA-Sequencing Analysis Based on Human Saliva Samples of Patients with Endometriosis. Int J Mol Sci. 2022 Jul 21;23(14):8045. doi: 10.3390/ijms23148045.

  PMID: 35887388 BACKGROUND

• Bendifallah S, Suisse S, Puchar A, Delbos L, Poilblanc M, Descamps P, Golfier F, Jornea L, Bouteiller D, Touboul C, Dabi Y, Darai E. Salivary MicroRNA Signature for Diagnosis of Endometriosis. J Clin Med. 2022 Jan 26;11(3):612. doi: 10.3390/jcm11030612.

  PMID: 35160066 BACKGROUND

• Bendifallah S, Dabi Y, Suisse S, Jornea L, Bouteiller D, Touboul C, Puchar A, Darai E. MicroRNome analysis generates a blood-based signature for endometriosis. Sci Rep. 2022 Mar 8;12(1):4051. doi: 10.1038/s41598-022-07771-7.

  PMID: 35260677 BACKGROUND

• Dabi Y, Suisse S, Jornea L, Bouteiller D, Touboul C, Puchar A, Darai E, Bendifallah S. Clues for Improving the Pathophysiology Knowledge for Endometriosis Using Plasma Micro-RNA Expression. Diagnostics (Basel). 2022 Jan 12;12(1):175. doi: 10.3390/diagnostics12010175.

  PMID: 35054341 BACKGROUND

• Bendifallah S, Puchar A, Suisse S, Delbos L, Poilblanc M, Descamps P, Golfier F, Touboul C, Dabi Y, Darai E. Machine learning algorithms as new screening approach for patients with endometriosis. Sci Rep. 2022 Jan 12;12(1):639. doi: 10.1038/s41598-021-04637-2.

  PMID: 35022502 BACKGROUND

Biospecimen

Retention: SAMPLES WITH DNA

tissue biopsy and saliva

MeSH Terms

Conditions

Endometriosis

Interventions

Observation

Condition Hierarchy (Ancestors)

Genital Diseases, Female; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Genital Diseases

Intervention Hierarchy (Ancestors)

Methods; Investigative Techniques

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: October 13, 2023
• First Posted: October 25, 2023
• Study Start: May 1, 2023
• Primary Completion: July 31, 2024
• Study Completion: December 31, 2024
• Last Updated: February 20, 2024

Record last verified: 2024-02

Data Sharing

• IPD Sharing: Will not share

Locations

IT (1)