Gestational age-dependent development of the neonatal metabolome

Research output: Contribution to journal › Journal article › Research › peer-review

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Gestational age-dependent development of the neonatal metabolome. / Ernst, Madeleine; Rogers, Simon; Lausten-Thomsen, Ulrik; Björkbom, Anders; Laursen, Susan Svane; Courraud, Julie; Borglum, Anders; Nordentoft, Merete; Werge, Thomas; Mortensen, Preben Bo; Hougaard, David M.; Cohen, Arieh S.

In: Pediatric Research, Vol. 89, 2021, p. 1396–1404.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Ernst, M, Rogers, S, Lausten-Thomsen, U, Björkbom, A, Laursen, SS, Courraud, J, Borglum, A, Nordentoft, M, Werge, T, Mortensen, PB, Hougaard, DM & Cohen, AS 2021, 'Gestational age-dependent development of the neonatal metabolome', Pediatric Research, vol. 89, pp. 1396–1404. https://doi.org/10.1038/s41390-020-01149-z

APA

Ernst, M., Rogers, S., Lausten-Thomsen, U., Björkbom, A., Laursen, S. S., Courraud, J., Borglum, A., Nordentoft, M., Werge, T., Mortensen, P. B., Hougaard, D. M., & Cohen, A. S. (2021). Gestational age-dependent development of the neonatal metabolome. Pediatric Research, 89, 1396–1404. https://doi.org/10.1038/s41390-020-01149-z

Vancouver

Ernst M, Rogers S, Lausten-Thomsen U, Björkbom A, Laursen SS, Courraud J et al. Gestational age-dependent development of the neonatal metabolome. Pediatric Research. 2021;89:1396–1404. https://doi.org/10.1038/s41390-020-01149-z

Author

Ernst, Madeleine ; Rogers, Simon ; Lausten-Thomsen, Ulrik ; Björkbom, Anders ; Laursen, Susan Svane ; Courraud, Julie ; Borglum, Anders ; Nordentoft, Merete ; Werge, Thomas ; Mortensen, Preben Bo ; Hougaard, David M. ; Cohen, Arieh S. / Gestational age-dependent development of the neonatal metabolome. In: Pediatric Research. 2021 ; Vol. 89. pp. 1396–1404.

Bibtex

@article{d42b921fe83a4cc38b169d6f5c580fdb,
title = "Gestational age-dependent development of the neonatal metabolome",
abstract = "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.",
keywords = "PRETERM BIRTH, MOLECULAR NETWORKING, NATURAL-PRODUCTS, MICROBIOTA, MORTALITY, DISCOVERY, AUTISM",
author = "Madeleine Ernst and Simon Rogers and Ulrik Lausten-Thomsen and Anders Bj{\"o}rkbom and Laursen, {Susan Svane} and Julie Courraud and Anders Borglum and Merete Nordentoft and Thomas Werge and Mortensen, {Preben Bo} and Hougaard, {David M.} and Cohen, {Arieh S.}",
year = "2021",
doi = "10.1038/s41390-020-01149-z",
language = "English",
volume = "89",
pages = "1396–1404",
journal = "Pediatric Research",
issn = "0031-3998",
publisher = "nature publishing group",

}

RIS

TY - JOUR

T1 - Gestational age-dependent development of the neonatal metabolome

AU - Ernst, Madeleine

AU - Rogers, Simon

AU - Lausten-Thomsen, Ulrik

AU - Björkbom, Anders

AU - Laursen, Susan Svane

AU - Courraud, Julie

AU - Borglum, Anders

AU - Nordentoft, Merete

AU - Werge, Thomas

AU - Mortensen, Preben Bo

AU - Hougaard, David M.

AU - Cohen, Arieh S.

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

KW - PRETERM BIRTH

KW - MOLECULAR NETWORKING

KW - NATURAL-PRODUCTS

KW - MICROBIOTA

KW - MORTALITY

KW - DISCOVERY

KW - AUTISM

U2 - 10.1038/s41390-020-01149-z

DO - 10.1038/s41390-020-01149-z

M3 - Journal article

C2 - 32942288

VL - 89

SP - 1396

EP - 1404

JO - Pediatric Research

JF - Pediatric Research

SN - 0031-3998

ER -

ID: 250540157