The Metabolomic Profile of Umbilical Cord Blood in Neonatal Hypoxic Ischaemic Encephalopathy

<div><h3>Background</h3><p>Hypoxic ischaemic encephalopathy (HIE) in newborns can cause significant long-term neurological disability. The insult is a complex injury characterised by energy failure and disruption of cellular homeostasis, leading to mitochondrial damage. The importance of individual metabolic pathways, and their interaction in the disease process is not fully understood. The aim of this study was to describe and quantify the metabolomic profile of umbilical cord blood samples in a carefully defined population of full-term infants with HIE.</p> <h3>Methods and Findings</h3><p>The injury severity was defined using both the modified Sarnat score and continuous multichannel electroencephalogram. Using these classification systems, our population was divided into those with confirmed HIE (n = 31), asphyxiated infants without encephalopathy (n = 40) and matched controls (n = 71). All had umbilical cord blood drawn and biobanked at −80°C within 3 hours of delivery. A combined direct injection and LC-MS/MS assay (AbsolutIDQ p180 kit, Biocrates Life Sciences AG, Innsbruck, Austria) was used for the metabolomic analyses of the samples. Targeted metabolomic analysis showed a significant alteration between study groups in 29 metabolites from 3 distinct classes (Amino Acids, Acylcarnitines, and Glycerophospholipids). 9 of these metabolites were only significantly altered between neonates with Hypoxic ischaemic encephalopathy and matched controls, while 14 were significantly altered in both study groups. Multivariate Discriminant Analysis models developed showed clear multifactorial metabolite associations with both asphyxia and HIE. A logistic regression model using 5 metabolites clearly delineates severity of asphyxia and classifies HIE infants with AUC = 0.92. These data describe wide-spread disruption to not only energy pathways, but also nitrogen and lipid metabolism in both asphyxia and HIE.</p> <h3>Conclusion</h3><p>This study shows that a multi-platform targeted approach to metabolomic analyses using accurately phenotyped and meticulously biobanked samples provides insight into the pathogenesis of perinatal asphyxia. It highlights the potential for metabolomic technology to develop a diagnostic test for HIE.</p> </div

Canonical Variate Analysis for the combined data sets.

<p>Squares = asphyxia cases; Circles = matched asphyxia controls; Triangles = HIE cases; Diamonds = matched HIE controls. Solid circles = 95% confidence intervals for each group population; Dashed circles = 95% confidence intervals for the mean of each group.</p

Demographic Details of Study Population.

<p>Values are mean (SD), median (interquartile range), or n (%).</p

A ROC comparison of all models produced in this study.

<p>Triangle = PLS-DA: HIE versus matched controls, AUC = 0.96 (95% CI = 0.83–1.00); Square = PLS-DA: Asphyxia versus matched controls, AUC = 0.91 (0.83–0.96); Diamond = PLS-DA: HIE versus ‘all other outcomes’ (all metabolites), AUC = 0.91 (0.83–0.96); Circle = Logistic Regression: HIE versus ‘all other outcomes’ (5 metabolites), AUC = 0.92 (0.84–0.97). For clarity the convex-hull ROC curve approximations are shown. All AUC calculations were made on the actual predicted values.</p

Variable importance plot for the HIE versus ‘all other outcomes’ PLD-DA model.

<p>A VIP score >1 indicates an important contribution to the model.</p

The predictive scores for a PLS-DA model built to discriminate between HIE versus all other outcomes (asphyxia and both the control groups) using the complete data set.

<p>The PLS score box plot is grouped by Sarnat score. Here a Sarnat score of zero is equivalent to the “asphyxia” classification, and Sarnat grade of 1, 2 and 3 represent the 3 levels of increasing HIE severity. The model was optimally built using 2 latent factors. The model had an R² = 0.32, Q² = 0.22, and an AUC of 0.92 (95% CI: 0.84–0.97). For a fixed specificity of 0.95 the corresponding sensitivity for predicting HIE (at any level) is 0.75 (95% CI: 0.55–0.88), the corresponding decision boundary is indicated by a dashed line in the boxplot. Note: the Quality Control samples (repeated injection of serum from two control patients: QC1 & QC2) are projected through the PLS-DA model and the subsequent predictions give an estimation of model precision.</p

Metabolites Identified as significantly altered in Umbilical Cord Blood Samples of Cases compared to Matched Controls.

<p>Metabolites Identified as significantly altered in Umbilical Cord Blood Samples of Cases compared to Matched Controls.</p

¹H NMR Derived Metabolomic Profile of Neonatal Asphyxia in Umbilical Cord Serum: Implications for Hypoxic Ischemic Encephalopathy

Neonatal hypoxic ischemic encephalopathy (HIE) is a severe consequence of perinatal asphyxia (PA) that can result in life-long neurological disability. Disease mechanisms, including the role and interaction of individual metabolic pathways, remain unclear. As hypoxia is an acute condition, aerobic energy metabolism is central to global metabolic pathways, and these metabolites are detectable using ¹H NMR spectroscopy, we hypothesized that characterizing the NMR-derived umbilical cord serum metabolome would offer insight into the consequences of PA that lead to HIE. Fifty-nine at-risk infants were enrolled, together with 1:1 matched healthy controls, and stratified by disease severity (<i>n</i> = 25, HIE; <i>n</i> = 34, non-HIE PA). Eighteen of 37 reproducibly detectable metabolites were significantly altered between study groups. Acetone, 3-hydroxybutyrate, succinate, and glycerol were significantly differentially altered in severe HIE. Multivariate data analysis revealed a metabolite profile associated with both asphyxia and HIE. Multiple-linear regression modeling using 4 metabolites (3-hydroxybutyrate, glycerol, <i>O</i>-phosphocholine, and succinate) predicted HIE severity with an adjusted <i>R</i>² of 0.4. Altered ketones suggest that systemic metabolism may play a critical role in preventing neurological injury, while altered succinate provides a possible explanation for hypoxia-inducible factor 1-α (HIF-1α) stabilization in HI injury

The sample selection process.

<p>The sample selection process.</p

Long chain fatty acids that differed significantly between control and UQ groups at 2-y follow-up (<i>p</i>&lt;0.05).

<p>PC, phosphatidylcholine; PE, phosphatidylethanolamine; PG, glycerophosphoglycerol; PS, phosphatidylserine.</p