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Molecular diagnosis of polycystic ovary syndrome in obese and non-obese women by targeted plasma miRNA profiling

Authors :
Rafael Pineda
Elier Paz
Fe Isabel Garcia-Maceira
Juan Lorente
Concepcion Muñoz
Ipek Guler
Cecilia Perdices-Lopez
David Ovelleiro
Cristina Romero-Baldonado
Manuel Tena-Sempere
Beatriz Pineda
María Jesús Vázquez
Alvaro Jimenez
Jose Eduardo Arjona
Mariasara Persano
E. Torres
Álvaro Arjona-Sánchez
Antonio Romero-Ruiz
Source :
European journal of endocrinology. 185(5)
Publication Year :
2021

Abstract

Objective Polycystic ovary syndrome (PCOS) is diagnosed based on the clinical signs, but its presentation is heterogeneous and potentially confounded by concurrent conditions, such as obesity and insulin resistance. miRNA have recently emerged as putative pathophysiological and diagnostic factors in PCOS. However, no reliable miRNA-based method for molecular diagnosis of PCOS has been reported. The aim of this study was to develop a tool for accurate diagnosis of PCOS by targeted miRNA profiling of plasma samples, defined on the basis of unbiased biomarker-finding analyses and biostatistical tools. Methods A case–control PCOS cohort was cross-sectionally studied, including 170 women classified into four groups: non-PCOS/lean, non-PCOS/obese, PCOS/lean, and PCOS/obese women. High-throughput miRNA analyses were performed in plasma, using NanoString technology and a 800 human miRNA panel, followed by targeted quantitative real-timePCR validation. Statistics were applied to define optimal normalization methods, identify deregulated biomarker miRNAs, and build classification algorithms, considering PCOS and obesity as major categories. Results The geometric mean of circulating hsa-miR-103a-3p, hsa-miR-125a-5p, and hsa-miR-1976, selected among 125 unchanged miRNAs, was defined as optimal reference for internal normalization (named mR3-method). Ten miRNAs were identified and validated after mR3-normalization as differentially expressed across the groups. Multinomial least absolute shrinkage and selection operator regression and decision-tree models were built to reliably discriminate PCOS vs non-PCOS, either in obese or non-obese women, using subsets of these miRNAs as performers. Conclusions We define herein a robust method for molecular classification of PCOS based on unbiased identification of miRNA biomarkers and decision-tree protocols. This method allows not only reliable diagnosis of non-obese women with PCOS but also discrimination between PCOS and obesity. Capsule We define a novel protocol, based on plasma miRNA profiling, for molecular diagnosis of PCOS. This tool not only allows proper discrimination of the condition in non-obese women but also permits distinction between PCOS and obesity, which often display overlapping clinical presentations.

Details

ISSN :
1479683X
Volume :
185
Issue :
5
Database :
OpenAIRE
Journal :
European journal of endocrinology
Accession number :
edsair.doi.dedup.....79940a6661608d1bb38ec0bcf1a3947d