Identifying hypoxia in a newborn piglet model using urinary NMR metabolomic profiling

Abstract

Establishing the severity of hypoxic insult during the delivery of a neonate is key step in the determining the type of therapy administered. While successful therapy is present, current methods for assessing hypoxic injuries in the neonate are limited. Urine Nuclear Magnetic Resonance (NMR) metabolomics allows for the rapid non-invasive assessment of a multitude breakdown products of physiological processes. In a newborn piglet model of hypoxia, we used NMR spectroscopy to determine the levels of metabolites in urine samples, which were correlated with physiological measurements. Using PLS-DA analysis, we identified 13 urinary metabolites that differentiated hypoxic versus nonhypoxic animals (1-methylnicotinamide, 2-oxoglutarate, alanine, asparagine, betaine, citrate, creatine, fumarate, hippurate, lactate, N-acetylglycine, N-carbamoyl-β-alanine, and valine). Using this metabolomic profile, we then were able to blindly identify hypoxic animals correctly 84% of the time compared to nonhypoxic controls. This was better than using physiologic measures alone. Metabolomic profiling of urine has potential for identifying neonates that have undergone episodes of hypoxia.

Figure 1. Physiological effects of hypoxia in newborn piglets.

Temporal changes in (A) oxygen saturation (% O₂), (B) blood pH, (C) mean arterial pressure (mmHg), and (D) cardiac output between hypoxia (n = 7) and sham (n = 6) treated animals. *P<0.05 Sham vs. Hypoxia for corresponding time point.

Figure 2. Differentiating hypoxic animals vs. sham treated animals.

The PLS-DA algorithm separates groups of data based on a score of 0–1; in this case a value closer to zero indicates no hypoxemia (sham, n = 6) and above 0.5 indicates hypoxemia (n = 7). Illustrated are the PLS-DA prediction scores for each animal including blinded test groups. Error bars represent medians and interquartile ranges.

Figure 3. The metabolomic model of hypoxic vs. sham treated animals.

PLS-DA analysis of urine from hypoxic versus sham treated animals was based on differences in metabolites between groups shown as the Coefficient of Variation (CoV) plot (A). The importance of each metabolite within the model is shown as the Variability of Importance (VIP) plot (B).