Common and divergent dynamic changes of the human plasma metabolome across the first week of life in the Gambia & Papua New Guinea 2257987

Abstract

Abstract Introduction The plasma metabolome changes markedly over the first week of life yet little is known regarding how these trajectories might differ across geographically distinct populations. Methods To gain insight into potential differences in ontogeny between geographic sites, newborn participants were enrolled in The Gambia (n = 45) and Papua New Guinea (n = 45). All participants had samples collected at birth and were randomized to have their second sample collected either on the first, third, or seventh day following birth. Global untargeted plasma metabolomics employed ultra-performance liquid chromatography mass spectrometry (Metabolon). Principal Component Analysis (PCA), regression methods, and enrichment analysis were used to identify significant differences in metabolite profiles between time points (p < 0.01, adjusted for multiple comparisons). Results PCA showed plasma metabolites clustering by day of sample collection and by site. The majority (62%) of metabolite features showed a significant difference based on time point: 46% of these were lipids and 17% were amino acids. Temporal dynamics revealed dramatic changes during the first week of life, with the most pronounced shifts occurring between D1 and D3. The most significant temporal changes were consistent across the two geographic sites, suggesting that the underlying biological processes are robust. Additionally, 24% of the metabolite features showed a significant difference between sites, with the most common being lipids (28.2%). Xenobiotics including caffeine and food metabolites were distinct in GAM vs. PNG, suggesting differences in maternal diet and environmental factors. Conclusion The plasma metabolome undergoes marked changes during the first week of human life, with distinct features across geographic locations, and warrants further exploration with respect to potential correlations to immune status and clinical outcomes, with particular emphasis on lipid pathways. Funding Source National Institute Of Allergy And Infectious Diseases of the U.S. National Institutes of Health under Awards Human Immunology Project Consortium (HIPC; U19AI118608) Topic Categories Computational and Systems Immunology (COMP)