A Longitudinal 1 H NMR-Based Metabolic Profile Analysis of Urine from Hospitalized Premature Newborns Receiving Enteral and Parenteral Nutrition.
Nuria Esturau-EscofetEduardo Rodríguez de San MiguelMarcela Vela-AmievaMartha E García-AguileraCirce C Hernández-EspinoLuis R Macias-KaufferCarlos López-CandianiJosé J NavejaIsabel Ibarra-GonzálezPublished in: Metabolites (2022)
Preterm newborns are extremely vulnerable to morbidities, complications, and death. Preterm birth is a global public health problem due to its socioeconomic burden. Nurturing preterm newborns is a critical medical issue because they have limited nutrient stores and it is difficult to establish enteral feeding, which leads to inadequate growth frequently associated with poor neurodevelopmental outcomes. Parenteral nutrition (PN) provides nutrients to preterm newborns, but its biochemical effects are not completely known. To study the effect of PN treatment on preterm newborns, an untargeted metabolomic 1 H nuclear magnetic resonance (NMR) assay was performed on 107 urine samples from 34 hospitalized patients. Multivariate data (Principal Component Analysis, PCA, Orthogonal partial least squares discriminant analysis OPLS-DA, parallel factor analysis PARAFAC-2) and univariate analyses were used to identify the association of specific spectral data with different nutritional types (NTs) and gestational ages. Our results revealed changes in the metabolic profile related to the NT, with the tricarboxylic acid cycle and galactose metabolic pathways being the most impacted pathways. Low citrate and succinate levels, despite higher glucose relative urinary concentrations, seem to constitute the metabolic profile found in the studied critically ill preterm newborns who received PN, indicating an energetic dysfunction that must be taken into account for better nutritional management.
Keyphrases
- gestational age
- low birth weight
- preterm birth
- birth weight
- magnetic resonance
- preterm infants
- public health
- pregnant women
- high resolution
- healthcare
- electronic health record
- big data
- high throughput
- solid state
- mass spectrometry
- optical coherence tomography
- artificial intelligence
- cord blood
- oxidative stress
- type diabetes
- heavy metals
- risk assessment
- data analysis
- magnetic resonance imaging
- contrast enhanced
- adipose tissue
- machine learning
- weight loss
- gas chromatography mass spectrometry
- gas chromatography