Validation of a Salivary miRNA Signature of Endometriosis - Interim Data

Sofiane Bendifallah ^1,2,3, Yohann Dabi ^1,2,3, Stéphane Suisse ⁴

¹Department of Obstetrics and Reproductive Medicine, Tenon Hospital, Paris.
²Clinical Research Group Paris 6: Endometriosis Expert Center, Sorbonne University, Sorbonne, France.
³INSERM UMR S 938, Centre De Recherche scientifique Saint-Antoine (CRSA), Sorbonne University, Paris.
⁴Ziwig, Lyon, France.
⁵Department of Obstetrics and Reproductive Medicine-Angers University Hospital, Angers, France.
⁶Endometriosis Expert Center-Pays de la Loire, Angers, France.
⁷Department of Obstetrics and Reproductive Medicine, Lyon South University Hospital, Lyon Civil Hospices, Lyon, France.
⁸Endometriosis Expert Center-Steering Committee of the EndAURA Network, Lyon, France.
⁹Sorbonne Université, Paris Brain and Spinal Cord Institute (ICM), Institut national de la santé et de la recherche médicale U1127, CNRS UMR 7225, Assistance publique-Hôpitaux de Paris (APHP)-Pitié-Salpêtrière Hospital, Paris.
¹⁰Genotyping and Sequencing Core Facility, iGenSeq, Paris Brain and Spinal Cord Institute (ICM), Pitié-Salpêtrière Hospital, Paris.
¹¹Department of Obstetrics and Reproductive Medicine, University Hospital (HU) Paris Sud, Kremlin Bicetre APHP, Le Kremlin Bicetre, France.
¹²Department of Obstetrics and Reproductive Medicine, Paris Saint Joseph Hospital, Paris.
¹³Department of Obstetrics and Reproductive Medicine, Côte De Nacre University Hospital, Caen, France.
¹⁴Radiological Center Manin Crimée, Paris.
¹⁵Department of Obstetrics and Reproductive Medicine, Strasbourg University Hospital, Strasbourg, France.
¹⁶Department of Obstetrics, Gynecology and Human Reproduction, University of Rennes, Rennes, France.
¹⁷Bastia Hospital Center, Department of Specialised Surgery and Clinical Research, Bastia, France.
¹⁸Endometriosis Center, Tivoli-Ducos Clinic, Bordeaux, France.

⁰Department of Obstetrics and Reproductive Medicine, Tenon Hospital, Paris.

Nejm Evidence +

|

February 6, 2024

View abstract on PubMed

Summary

A new saliva test using micro-ribonucleic acid (miRNA) signatures and artificial intelligence (AI) shows high accuracy for diagnosing endometriosis. This noninvasive method offers a promising tool for early disease detection in women.

Area Of Science

Genomics and Bioinformatics
Biomarker Discovery
Medical Diagnostics

Background

Endometriosis diagnosis remains challenging, often requiring invasive procedures.
A 2022 discovery identified a 109-microRNA (miRNA) signature in saliva as a potential noninvasive diagnostic marker.
Artificial intelligence (AI) modeling was integral to developing this miRNA signature.

Purpose Of The Study

To externally validate the diagnostic accuracy of the 109-miRNA saliva signature for endometriosis.
To assess the performance of this noninvasive diagnostic tool in a multicenter prospective study.
To present interim analysis results from the ENDOmiRNA Saliva Test study.

Main Methods

Inclusion of 200 patients (ages 18-43) with confirmed or suspected endometriosis in the interim analysis.
Collection of epidemiological, clinical, and saliva sequencing data.
Genome-wide miRNA expression profiling via next-generation sequencing (NGS) and random forest algorithm analysis for diagnostic accuracy assessment.

Main Results

The 109-miRNA saliva signature demonstrated high diagnostic accuracy in the interim cohort (population prevalence 79.5%).
Key performance metrics included: sensitivity 96.2%, specificity 95.1%, positive predictive value 95.1%, and negative predictive value 86.7%.
The area under the receiver operating characteristic curve was 0.96, indicating excellent diagnostic performance.

Conclusions

Next-generation sequencing (NGS) and AI-driven analysis of saliva miRNAs can identify a diagnostic signature for endometriosis.
Interim results from this multicenter validation study support the continued investigation of this saliva-based test.
The findings suggest a promising noninvasive approach for early endometriosis detection.