dc.contributor.author
Frick, Marie Antoinette
dc.contributor.author
Barba, Ignasi
dc.contributor.author
Fenoy-Alejandre, Marina
dc.contributor.author
López-López, Paula
dc.contributor.author
Baquero Artigao, Fernando
dc.contributor.author
Rodríguez-Molino, Paula
dc.contributor.author
Noguera Julian, Antoni
dc.contributor.author
Nicolás-López, Marta
dc.contributor.author
de la Fuente-Juárez, Asunción
dc.contributor.author
Codina Grau, Maria Gemma
dc.contributor.author
Esperalba Esquerra, Juliana
dc.contributor.author
Linde-Sillo, Ángeles
dc.contributor.author
Soler Palacín, Pere
dc.date.issued
2020-06-11T21:32:33Z
dc.date.issued
2020-06-11T21:32:33Z
dc.date.issued
2019-11-15
dc.date.issued
2020-06-11T21:32:33Z
dc.identifier
https://hdl.handle.net/2445/165232
dc.description.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.
dc.format
application/pdf
dc.relation
Reproducció del document publicat a: https://doi.org/10.3390/metabo9120288
dc.relation
Metabolites, 2019, vol. 9, p. 288
dc.relation
https://doi.org/10.3390/metabo9120288
dc.rights
cc-by (c) Frick, Marie Antoinette et al., 2019
dc.rights
http://creativecommons.org/licenses/by/3.0/es
dc.rights
info:eu-repo/semantics/openAccess
dc.source
Articles publicats en revistes (Cirurgia i Especialitats Medicoquirúrgiques)
dc.subject
Infeccions per citomegalovirus
dc.subject
Cytomegalovirus infections
dc.title
1H-NMR Urinary Metabolic Profile, A Promising Tool for the Management of Infants with Human Cytomegalovirus-Infection
dc.type
info:eu-repo/semantics/article
dc.type
info:eu-repo/semantics/publishedVersion