Plasma miRNAs as biomarkers for endometriosis

A Vanhie, Arne Vanhie, Dolores Saavedra O., D O, Daniëlle Peterse, D Peterse, A Beckers, Anneleen Beckers, A Cuéllar, Amelie Fassbender, A Fassbender, C Meuleman, Christel Meuleman, Pieter Mestdagh, P Mestdagh, T D'Hooghe, Thomas D'Hooghe, Thomas D’Hooghe
Human Reproduction · 2019 · vol. 34(9) , pp. 1650–1660 · doi:10.1093/humrep/dez116 · PMID:31411334 · W2968520120
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Plasma miRNA diagnostic models for endometriosis failed independent validation, although one model showed weak discriminatory power for minimal-mild disease.

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Abstract

STUDY QUESTION: Can plasma miRNAs be used for the non-invasive diagnosis of endometriosis in infertile women? SUMMARY ANSWER: miRNA-based diagnostic models for endometriosis failed the test of independent validation. WHAT IS KNOWN ALREADY: Circulating miRNAs have been described to be differentially expressed in patients with endometriosis compared with women without endometriosis, suggesting that they could be used for the non-invasive diagnosis of endometriosis. However, these studies have shown limited consistency or conflicting results, and no miRNA-based diagnostic test has been validated in an independent patient cohort. STUDY DESIGN, SIZE, DURATION: We performed genome-wide miRNA expression profiling by small RNA sequencing to identify a set of plasma miRNAs with discriminative potential between patients with and without endometriosis. Expression of this set of miRNAs was confirmed by RT-qPCR. Diagnostic models were built using multivariate logistic regression with stepwise feature selection. In a final step, the models were tested for validation in an independent patient cohort. PARTICIPANTS/MATERIALS, SETTINGS, METHODS: Plasma of all patients was available in the biobank of the Leuven Endometriosis Centre of Excellence. Biomarker discovery and model development were performed in a discovery cohort of 120 patients (controls = 38, endometriosis = 82), and models were tested for validation in an independent cohort of 90 patients (controls = 30, endometriosis = 60). RNA was extracted with the miRNeasy Plasma Kit. Genome-wide miRNA expression analysis was done by small RNA sequencing using the NEBNext small RNA library prep kit and the NextSeq 500 System. cDNA synthesis and qPCR were performed using the Qiagen miScript technology. MAIN RESULTS AND THE ROLE OF CHANCE: We identified a set of 42 miRNAs with discriminative power between patients with and without endometriosis based on genome-wide miRNA expression profiling. Expression of 41 miRNAs was confirmed by RT-qPCR, and 3 diagnostic models were built. Only the model for minimal-mild endometriosis (Model 2: hsa-miR-125b-5p, hsa-miR-28-5p and hsa-miR-29a-3p) had diagnostic power above chance performance in the independent validation (AUC = 60%) with an acceptable sensitivity (78%) but poor specificity (37%). LIMITATIONS, REASONS FOR CAUTION: The diagnostic models were built and tested for validation in two patient cohorts from a single tertiary endometriosis centre. Further validation tests in large cohorts with patients from multiple endometriosis centres are needed. WIDER IMPLICATION OF THE FINDINGS: Our study supports a possible biological link between certain miRNAs and endometriosis, but the potential of these miRNAs as clinically useful biomarkers is questionable in women with infertility. Large studies in well-described patient cohorts, with rigorous methodology for miRNA expression analysis, sufficient statistical power and an independent validation step, are necessary to answer the question of whether miRNAs can be used as diagnostics markers for endometriosis. STUDY FUNDING/COMPETING INTEREST(S): The project was funded by a grant from the Research Foundation - Flanders (FWO). A.V., D.F.O. and D.P. are PhD fellows from the FWO. T.D. is vice president and Head of Global Medical Affairs Fertility, Research and Development, Merck KGaA, Darmstadt, Germany. He is also a professor in Reproductive Medicine and Biology at the Department of Development and Regeneration, Group Biomedical Sciences, KU Leuven (University of Leuven), Belgium and an adjunct professor at the Department of Obstetrics and Gynecology in the University of Yale, New Haven, USA. Neither his corporate role nor his academic roles represent a conflict of interest with respect to the work done by him for this study. The other co-authors have no conflict of interest. TRIAL REGISTRATION NUMBER: Not applicable.

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Condition tags

mesh:D004715endometriosisinfertility

MeSH descriptors

Endometriosis Endometriosis MicroRNAs Adult Biomarkers Biomarkers Case-Control Studies Cohort Studies Endometriosis Endometriosis Female Humans Infertility, Female Infertility, Female Infertility, Female MicroRNAs MicroRNAs Prevalence Reverse Transcriptase Polymerase Chain Reaction

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