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© 2021 European Society of Endocrinology
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https://doi.org/10.1530/EJE-21-0552
European Journal of Endocrinology
185:5 637–652 A Romero-Ruiz, B Pineda,
D Ovelleiro and others
microRNA profling and PCOS
diagnosis
Molecular diagnosis of polycystic ovary
syndrome in obese and non-obese women by
targeted plasma miRNA profiling
Antonio Romero-Ruiz
1,2,3,
*, Beatriz Pineda
1,3,
*, David Ovelleiro
4,
*, Cecilia Perdices-Lopez
1,2,5
,
Encarnación Torres
1,2,3
, María J Vazquez
1,2,3
, Ipek Guler
1
, Álvaro Jiménez
1
, Rafael Pineda
1,2
, Mariasara Persano
1,3
,
Cristina Romero-Baldonado
3
, José E Arjona
3
, Juan Lorente
3
, Concepción Muñoz
1,3
, Elier Paz
6
,
Fe-Isabel Garcia-Maceira
6
, Álvaro Arjona-Sánchez
1,3
and Manuel Tena-Sempere
1,2,3,5,7
1
Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC),
2
Department of Cell Biology, Physiology and
Immunology, University of Córdoba, Córdoba, Spain,
3
Hospital Universitario Reina Sofa, Córdoba, Spain,
4
Area of
Cellular Biology, Department of Experimental Biology, University of Jaen, Jaen, Spain,
5
CIBER Fisiopatología de la
Obesidad y Nutrición, Instituto de Salud Carlos III, Córdoba, Spain,
6
Canvax Biotech, Córdoba, Spain, and
7
Institute of
Biomedicine, University of Turku, Turku, Finland
*(A Romero-Ruiz, B Pineda and D Ovelleiro contributed equally to this work)
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 profling of plasma samples, defned on the basis of unbiased
biomarker-fnding analyses and biostatistical tools.
Methods: A case–control PCOS cohort was cross-sectionally studied, including 170 women classifed 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 defne optimal normalization methods, identify deregulated
biomarker miRNAs, and build classifcation 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 defned as optimal reference for internal normalization (named mR3-method). Ten
miRNAs were identifed and validated after mR3-normalization as diferentially 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 defne herein a robust method for molecular classifcation of PCOS based on unbiased identifcation
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 defne a novel protocol, based on plasma miRNA profling, 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.
Correspondence
should be addressed
to A Romero-Ruiz or
M Tena-Sempere
Email
antonioromeroruiz@gmail.
com or fi1tesem@uco.es
Clinical Study
European Journal of
Endocrinology
(2021) 185, 637–652
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