期刊
PEDIATRIC RESEARCH
卷 89, 期 6, 页码 1396-1404出版社
SPRINGERNATURE
DOI: 10.1038/s41390-020-01149-z
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资金
- Novo Nordisk Foundation
- Lundbeck Foundation [R102-A9118, R155-2014-1724]
This study utilized metabolomics tools to measure over 9000 metabolites in 298 neonatal blood samples, identifying approximately 16% of metabolites significantly correlated with gestational age. Eighty-three metabolites explained 48% of the variance in gestational age, revealing the age-dependent development of the neonatal blood metabolome.
BACKGROUND: Prematurity is a severe pathophysiological condition, however, little is known about the gestational age-dependent development of the neonatal metabolome. METHODS: Using an untargeted liquid chromatography-tandem mass spectrometry metabolomics protocol, we measured over 9000 metabolites in 298 neonatal residual heel prick dried blood spots retrieved from the Danish Neonatal Screening Biobank. By combining multiple state-of-the-art metabolome mining tools, we retrieved chemical structural information at a broad level for over 5000 (60%) metabolites and assessed their relation to gestational age. RESULTS: A total of 1459 (similar to 16%) metabolites were significantly correlated with gestational age (false discovery rate-adjusted P < 0.05), whereas 83 metabolites explained on average 48% of the variance in gestational age. Using a custom algorithm based on hypergeometric testing, we identified compound classes (617 metabolites) overrepresented with metabolites correlating with gestational age (P < 0.05). Metabolites significantly related to gestational age included bile acids, carnitines, polyamines, amino acid-derived compounds, nucleotides, phosphatidylcholines and dipeptides, as well as treatment-related metabolites, such as antibiotics and caffeine. CONCLUSIONS: Our findings elucidate the gestational age-dependent development of the neonatal blood metabolome and suggest that the application of metabolomics tools has great potential to reveal novel biochemical underpinnings of disease and improve our understanding of complex pathophysiological mechanisms underlying prematurity-associated disorders.
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