Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1)

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




Julkaisun tekijät: Romero-Ruiz Antonio, Pineda Beatriz, Ovelleiro David, Perdices-Lopez Cecilia, Torres Encarnación, Vazquez Maria J, Guler Ipek, Jiménez Álvaro, Pineda Rafael, Persano Mariasara, Romero-Baldonado Christina, Arjona José E, Lorente Juan, Muñoz Concepción, Paz Elier, Garcia-Maceira Fe-Isabel, Arjona-Sánchez Álvaro, Tena-Sempere Manuel

Kustantaja: European society of endocrinology

Julkaisuvuosi: 2021

Journal: European Journal of Endocrinology

Tietokannassa oleva lehden nimi: European journal of endocrinology

Lehden akronyymi: Eur J Endocrinol

Volyymi: 185

Julkaisunumero: 5

ISSN: 0804-4643

eISSN: 1479-683X

DOI: http://dx.doi.org/10.1530/EJE-21-0552


Tiivistelmä

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.


Last updated on 2022-04-03 at 09:39