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Disease Markers
Volume 2018, Article ID 1042479, 9 pages
https://doi.org/10.1155/2018/1042479
Research Article

PROM and Labour Effects on Urinary Metabolome: A Pilot Study

1Department of Surgical Sciences, Division of Gynaecology and Obstetrics, University of Cagliari, Cagliari, Italy
2Department of Chemical and Geological Sciences, University of Cagliari, Cagliari, Italy
3Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
4Department of Surgical Sciences, Neonatal Intensive Care Unit, Puericulture Institute and Neonatal Section, Azienda Ospedaliera Universitaria, Cagliari, Italy
5Laboratory Medicine Service, IRCCS AOU San Martino-IST, University-Hospital, Genoa, Italy
6Maternal Neonatal Department, Division of Gynaecology and Obstetrics, Massa Carrara Hospital, Carrara, Italy

Correspondence should be addressed to Claudia Fattuoni; ti.acinu@nouttafc

Received 17 October 2017; Accepted 24 December 2017; Published 4 February 2018

Academic Editor: Vincent Sapin

Copyright © 2018 Alessandra Meloni et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Since pathologies and complications occurring during pregnancy and/or during labour may cause adverse outcomes for both newborns and mothers, there is a growing interest in metabolomic applications on pregnancy investigation. In fact, metabolomics has proved to be an efficient strategy for the description of several perinatal conditions. In particular, this study focuses on premature rupture of membranes (PROM) in pregnancy at term. For this project, urine samples were collected at three different clinical conditions: out of labour before PROM occurrence (Ph1), out of labour with PROM (Ph2), and during labour with PROM (Ph3). GC-MS analysis, followed by univariate and multivariate statistical analysis, was able to discriminate among the different classes, highlighting the metabolites most involved in the discrimination.