# Untargeted 1H-NMR Urine Metabolomic Analysis of Preterm Infants with Neonatal Sepsis
## 3 Results
### Metabolic Profile Alterations of Pretems with EOS  
#### 3.1.1 EOS Preterms Versus Non NICU Healthy Preterms  
Twenty-three preterm infants (n = 23), hospitalized in NICU, were diagnosed with EOS and their urine NMR metabolic profiles were compared to the first day of life spectroscopic data of the control group, consisting of twenty (n = 20) healthy preterm neonates, treated by their mothers immediately after birth and non-hospitalized in NICU (non NICU preterms). The generated data, consisting of 359 spectral bins, were processed using Pareto normalization. The numerical data matrix was applied as input for the unsupervised PCA and the supervised PLS-DA. Both showed a clear discrimination between the two groups. According to PC1 and PC2, explaining the 73.4% of the total variance, loadings belonging to an unknown pattern of multiple peaks between 7.40-7.50 ppm and at 1.40 ppm, observed to the majority of the NMR spectra of the NICU urine samples (20 out of 23 spectra of EOS samples), were responsible for the separation (Supplementary materials Figure S1). Additionally, gluconate and lactose differed between the two groups, with EOS neonates having the higher concentration level of gluconate and lower of lactose. The PLS-DA model (Figure 1a) shows a discrimination between the two groups, with an R\({}^{2}\) of 0.664 and Q\({}^{2}\) of 0.409 for the third component after a 10-fold cross-validation test, supporting the unsupervised PCA's clustering. VIP scores, with colored boxes on the right representing the differentiated relative concentrations of the corresponding buckets in each group (blue--low--and red--high--relative concentration) were in accordance with loadings (Figure 1b) and those with higher scores reveal lower intensity of buckets related to ppm of taurine, myo-inositol and betaine, creatinine for EOS and higher intensity of the unknown area 7.40-7.50 ppm. The box plots of the metabolites responsible for the group clustering confirm the concentration's alteration among the compared groups (Figure 1c). The Y axis represents the normalized concentration of the corresponding spectral region. The obtained negative values come as a result of the total spectral area normalization. The unassigned spectral region of two different types of peaks that resonate at 1.40 ppm statistically correlate with the multiple peaks at the aromatic region of 7.40-7.50 ppm. The statistical correlation was confirmed with the 1D-STOCSY (Supplementary materials Figure S2) that indicates all the correlations of all spectral variables (buckets). To further examine and highlight the structural correlations with the spectral variables that resonate at 7.40-7.50 ppm, we set as \"driver peak\" the variable x.1.41, which includes the signals at 1.40 ppm and the observed maximum correlation displayed between the variable x.1.41 and x.7.51. Thus, they may belong to the same metabolite or group of metabolites derived from medication or parenteral nutrition. We attribute the unknown spectral pattern at 7.40-7.50 ppm and at 1.40 ppm as a NICU metabolic-induced characteristic, since it is present predominantly in the \({}^{1}\)H NMR spectra from NICU urine samples (Figure 2). Most of the preterm neonates hospitalized in NICU are under antibiotic treatment because of sepsis or of other infectious condition suspicion; also, prophylactic administration of broad-spectrum antibiotics is unfortunately very common. Antibiotics can lead to adverse effects, including necrotizing enterocolitis (NEC) and LOS [37]. [PERSON] et al. studied their impact on fecal metabolome of preterm infants, but urine metabolome has not been investigated yet [38]. Our study suggests the further analysis of these unidentified spectral regions as antibiotic outcome on \({}^{1}\)H NMR spectra of urine samples. However, in depth investigation of the antibiotic and/or additional medication effect on the urine NMR metabolic profile is beyond the scope of this research.