Ontogeny Related Changes in the Pediatric Liver Metabolome

Abstract

Background: A major challenge in implementing personalized medicine in pediatrics is identifying appropriate drug dosages for children. The majority of drug dosing studies have been based on adult populations, often with modification of the dosing for children based on size and weight. However, the growth and development experienced by children between birth and adulthood represents a dynamically changing biological system, with implications for effective drug dosing, efficacy as well as potential drug toxicity. The purpose of this study was to apply a metabolomics approach to gain preliminary insights into the ontogeny of liver function from newborn to adolescent. Methods: Metabolites were measured in 98 post-mortem pediatric liver samples in two experiments 3 batches of samples, allowing for both technical and biological validation. After extensive quality control, imputation and normalization, non-parametric tests were used to determine which metabolite levels differ between the four age groups (AG) ranging in age from newborn to adolescent (AG1-children <1 year; AG2-children with age between 1 and 6 years; AG3-children with age between 6 and 12 years; AG4-children with age between 12 and 18 years). To identify which metabolites had different concentration levels among the age groups, Kruskal-Wallis and Spearman correlation tests were conducted. Pathway analysis utilized the Gamma Method. Correction for multiple testing was completed using Bonferroni correction. Results: We found 41 metabolites (out of 884) that were biologically validated, and of those 25 were technically replicated, of which 24 were known metabolites. For the majority of these 24 metabolites, concentration levels were significantly lower in newborns than in the other age groups, many of which were long chain fatty acids or involved in pyrimidine or purine metabolism. Additionally, we found two KEGG pathways enriched for association with age: betaine metabolism and alpha linolenic acid and linoleic acid metabolism. Conclusions: Understanding the role that ontogeny of childhood liver plays may aid in determining better drug dosing algorithms for children.

Keywords: bioinformatics; childhood development; liver; metabolites; ontogeny.