Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/165232
Title: 1H-NMR Urinary Metabolic Profile, A Promising Tool for the Management of Infants with Human Cytomegalovirus-Infection
Author: Frick, Marie Antoinette
Barba, Ignasi
Fenoy-Alejandre, Marina
López-López, Paula
Baquero-Artigao, Fernando
Rodríguez-Molino, Paula
Noguera Julian, Antoni
Nicolás-López, Marta
de la Fuente-Juárez, Asunción
Codina Grau, Maria Gemma
Esperalba Esquerra, Juliana
Linde-Sillo, Ángeles
Soler Palacín, Pere
Keywords: Infeccions per citomegalovirus
Pediatria
Metabolòmica
Cytomegalovirus infections
Pediatrics
Metabolomics
Issue Date: 15-Nov-2019
Publisher: MDPI
Abstract: Abstract: Congenital human cytomegalovirus (HCMV) infection is the most common mother-to-child transmitted infection in the developed world. Certain aspects of its management remain a challenge. Urinary metabolic profiling is a promising tool for use in pediatric conditions. The aim of this study was to investigate the urinary metabolic profile in HCMV-infected infants and controls during acute care hospitalization. Urine samples were collected from 53 patients at five hospitals participating in the Spanish congenital HCMV registry. Thirty-one cases of HCMV infection and 22 uninfected controls were included. Proton nuclear magnetic resonance (1H-NMR) spectra were obtained using NOESYPR1D pulse sequence. The dataset underwent orthogonal projection on latent structures discriminant analysis to identify candidate variables affecting the urinary metabolome: HCMV infection, type of infection, sex, chronological age, gestational age, type of delivery, twins, and diet. Statistically significant discriminative models were obtained only for HCMV infection (p = 0.03) and chronological age (p < 0.01). No significant differences in the metabolomic profile were found between congenital and postnatal HCMV infection. When the HCMV-infected group was analyzed according to chronological age, a statistically significant model was obtained only in the neonatal group (p = 0.01), with the differentiating metabolites being betaine, glycine, alanine, and dimethylamine. Despite the considerable variation in urinary metabolic profiles in a real-life setting, clinical application of metabolomics to the study of HCMV infection seems feasible.
Note: Reproducció del document publicat a: https://doi.org/10.3390/metabo9120288
It is part of: Metabolites, 2019, vol. 9, p. 288
URI: http://hdl.handle.net/2445/165232
Related resource: https://doi.org/10.3390/metabo9120288
ISSN: 2218-1989
Appears in Collections:Articles publicats en revistes (Cirurgia i Especialitats Medicoquirúrgiques)

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