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Urine Metabolome during Parturition.
Gevi, Federica; Meloni, Alessandra; Mereu, Rossella; Lelli, Veronica; Chiodo, Antonella; Ragusa, Antonio; Timperio, Anna Maria.
Affiliation
  • Gevi F; Department of Biology and Ecology, University of Tuscia, 01100 Viterbo, Italy.
  • Meloni A; Neonatal Department, Obstetrics and Gynecology Unit, Azienda Ospedaliera Universitaria (AOU), 09124 Cagliari, Italy.
  • Mereu R; Neonatal Department, Obstetrics and Gynecology Unit, Azienda Ospedaliera Universitaria (AOU), 09124 Cagliari, Italy.
  • Lelli V; Department of Biology and Ecology, University of Tuscia, 01100 Viterbo, Italy.
  • Chiodo A; Neonatal Department, Obstetrics and Gynecology Unit, Azienda Ospedaliera Universitaria (AOU), 09124 Cagliari, Italy.
  • Ragusa A; Department of Obstetrics and Gynecology, Ospedale San Giovanni Calibita, Fatebenefratelli, Isola Tiberina, Via di Ponte Quattro Capi, 39, 00186 Roma, Italy.
  • Timperio AM; Department of Biology and Ecology, University of Tuscia, 01100 Viterbo, Italy.
Metabolites ; 10(7)2020 07 16.
Article in En | MEDLINE | ID: mdl-32708819
In recent years, some studies have described metabolic changes during human childbirth labor. Metabolomics today is recognized as a powerful approach in a prenatal research context, since it can provide detailed information during pregnancy and it may enable the identification of biomarkers with potential diagnostic or predictive. This is an observational, longitudinal, prospective cohort study of a total of 51 serial urine samples from 15 healthy pregnant women, aged 29-40 years, which were collected before the onset of labor (out of labor, OL). In the same women, during labor (in labor or dilating phase, IL-DP). Samples were analyzed by hydrophilic interaction ultra-performance liquid chromatography coupled with mass spectrometry (HILIC-UPLC-MS), a highly sensitive, accurate, and unbiased approach. Metabolites were then subjected to multivariate statistical analysis and grouped by metabolic pathway. This method was used to identify the potential biomarkers. The top 20 most discriminative metabolites contributing to the complete separation of OL and IL-DP were identified. Urinary metabolites displaying the largest differences between OL and IL-DP belonged to steroid hormone, particularly conjugated estrogens and amino acids much of this difference is determined by the fetal contribution. In addition, our results highlighted the efficacy of using urine samples instead of more invasive techniques to evaluate the difference in metabolic analysis between OL and IL-DP.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Observational_studies / Risk_factors_studies Language: En Journal: Metabolites Year: 2020 Document type: Article Affiliation country: Italia Country of publication: Suiza

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Observational_studies / Risk_factors_studies Language: En Journal: Metabolites Year: 2020 Document type: Article Affiliation country: Italia Country of publication: Suiza