Evaluation of Genetic Signature in Endometriosis Disease by Non Invasive Sampling
NCT ID: NCT06100471
Last Updated: 2024-02-20
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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ENROLLING_BY_INVITATION
150 participants
OBSERVATIONAL
2023-05-01
2024-12-31
Brief Summary
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Detailed Description
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The study involves collecting a saliva sample from all patients involved in the study, and performing a biopsy from both patients with endometriotic adnexal pathology (CA) and patients with non-endometriotic adnexal pathology (CO).
Conditions
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Study Design
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CASE_CONTROL
CROSS_SECTIONAL
Study Groups
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case
Patients with endometriotic adnexal pathology
Observational study
Observational study in different tissues in identifing new genetic markers related to endometriosis disease
control
Patients with non endometriotic adnexal pathology
Observational study
Observational study in different tissues in identifing new genetic markers related to endometriosis disease
analytical control
Patients with no gynecological pathology, not undergoing surgery
Observational study
Observational study in different tissues in identifing new genetic markers related to endometriosis disease
Interventions
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Observational study
Observational study in different tissues in identifing new genetic markers related to endometriosis disease
Eligibility Criteria
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Inclusion Criteria
* Control population (CO), patients with non-endometriotic adnexal pathology
* Analytical control population (C-), patients with no gynecologic pathology, not undergoing surgery
Exclusion Criteria
* Pregnant patient
* Patient with a personal history of cancer
* Patient infected with HIV
18 Years
45 Years
FEMALE
Yes
Sponsors
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Eurofins Genoma
INDUSTRY
Responsible Party
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Locations
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Eurofins Genoma
Rome, , Italy
Countries
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References
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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.
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.
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.
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.
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.
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.
Other Identifiers
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01-23
Identifier Type: -
Identifier Source: org_study_id
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