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Endometriosis-associated infertility diagnosis based on saliva microRNA signatures

  • Yohann Dabi
    Affiliations
    Sorbonne University, Department of Obstetrics and Reproductive Medicine, Hôpital Tenon, 4 rue de la Chine, Paris 75020

    Clinical Research Group (GRC) Paris 6, Centre Expert Endométriose (C3E), Sorbonne University (GRC6 C3E SU)

    Cancer Biology and Therapeutics, Centre de Recherche Saint-Antoine (CRSA), Sorbonne University, INSERM UMR_S_938, Paris 75020, France
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  • Stéphane Suisse
    Affiliations
    Ziwig, 19 rue Reboud, Lyon 69003, France
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  • Anne Puchar
    Affiliations
    Sorbonne University, Department of Obstetrics and Reproductive Medicine, Hôpital Tenon, 4 rue de la Chine, Paris 75020
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  • Léa Delbos
    Affiliations
    Department of Obstetrics and Reproductive Medicine, CHU d'Angers, Endometriosis Expert Center, Pays de la Loire, France
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  • Mathieu Poilblanc
    Affiliations
    Department of Obstetrics and Reproductive Medicine, Lyon South University Hospital, Lyon Civil Hospices, Lyon, France

    Endometriosis Expert Center, Steering Committee of the EndAURA Network
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  • Philippe Descamps
    Affiliations
    Department of Obstetrics and Reproductive Medicine, CHU d'Angers, Endometriosis Expert Center, Pays de la Loire, France
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  • Julie Haury
    Affiliations
    Sorbonne University, Department of Obstetrics and Reproductive Medicine, Hôpital Tenon, 4 rue de la Chine, Paris 75020
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  • Francois Golfier
    Affiliations
    Department of Obstetrics and Reproductive Medicine, Lyon South University Hospital, Lyon Civil Hospices, Lyon, France

    Endometriosis Expert Center, Steering Committee of the EndAURA Network
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  • Ludmila Jornea
    Affiliations
    Sorbonne Université, Paris Brain Institute, Institut du Cerveau, ICM, Inserm U1127, CNRS UMR 7225, AP-HP, Hôpital Pitié-Salpêtrière, Paris, France
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  • Delphine Bouteiller
    Affiliations
    Genotyping and Sequencing Core Facility, iGenSeq, Institut du Cerveau et de la Moelle Epinière, ICM, Hôpital Pitié-Salpêtrière, 47-83 Boulevard de l'Hôpital, Paris 75013, France
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  • Cyril Touboul
    Affiliations
    Sorbonne University, Department of Obstetrics and Reproductive Medicine, Hôpital Tenon, 4 rue de la Chine, Paris 75020

    Clinical Research Group (GRC) Paris 6, Centre Expert Endométriose (C3E), Sorbonne University (GRC6 C3E SU)

    Cancer Biology and Therapeutics, Centre de Recherche Saint-Antoine (CRSA), Sorbonne University, INSERM UMR_S_938, Paris 75020, France
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  • Emile Daraï
    Affiliations
    Sorbonne University, Department of Obstetrics and Reproductive Medicine, Hôpital Tenon, 4 rue de la Chine, Paris 75020

    Clinical Research Group (GRC) Paris 6, Centre Expert Endométriose (C3E), Sorbonne University (GRC6 C3E SU)
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  • Sofiane Bendifallah
    Correspondence
    Corresponding author.
    Affiliations
    Sorbonne University, Department of Obstetrics and Reproductive Medicine, Hôpital Tenon, 4 rue de la Chine, Paris 75020

    Clinical Research Group (GRC) Paris 6, Centre Expert Endométriose (C3E), Sorbonne University (GRC6 C3E SU)

    Cancer Biology and Therapeutics, Centre de Recherche Saint-Antoine (CRSA), Sorbonne University, INSERM UMR_S_938, Paris 75020, France
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Published:September 26, 2022DOI:https://doi.org/10.1016/j.rbmo.2022.09.019

      Abstract

      Research question

      Can a saliva-based miRNA signature for endometriosis-associated infertility be designed and validated by analysing the human miRNome?

      Design

      The prospective ENDOmiARN study (NCT04728152) included 200 saliva samples obtained between January 2021 and June 2021 from women with pelvic pain suggestive of endometriosis. All patients underwent either laparoscopy, magnetic resonance imaging, or both. Patients diagnosed with endometriosis were allocated to one of two groups according to their fertility status. Data analysis consisted of identifying a set of miRNA biomarkers using next-generation sequencing, and development of a saliva-based miRNA signature of infertility among patients with endometriosis based on a random forest model.

      Results

      Among the 153 patients diagnosed with endometriosis, 24% (n = 36) were infertile and 76% (n = 117) were fertile. Small RNA-sequencing of the 153 saliva samples yielded approximately 3712 M raw sequencing reads (from ∼13.7 M to ∼39.3 M reads/sample). Of the 2561 known miRNAs, the feature selection method generated a signature of 34 miRNAs linked to endometriosis-associated infertility. After validation, the most accurate signature model had a sensitivity, specificity and area under the curve of 100%.

      Conclusion

      A saliva-based miRNA signature for endometriosis-associated infertility is reported. Although the results still require external validation before using the signature in routine practice, this non-invasive tool is likely to have a major effect on care provided to women with endometriosis.

      KEYWORDS

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      Biography

      Yohann Dabi, MD, is a gynaecologist specialized in endometriosis, He has published extensively on endometriosis, with specific focus on diagnosis and surgery of complex forms.
      Key message
      A robust saliva miRNA diagnostic signature for endometriosis-associated infertility is reported. It could be the long-awaited game changer for managing patients in this setting.