Aarhus University Seal / Aarhus Universitets segl

Gestational age-dependent development of the neonatal metabolome

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

  • Madeleine Ernst, iPSYCH, Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Lundbeck Fdn Initiat Integrat Psychiat Res
  • ,
  • Simon Rogers, Univ Glasgow, University of Glasgow, Sch Comp Sci
  • ,
  • Ulrik Lausten-Thomsen, Copenhagen Univ Hosp, Rigshospitalet, University of Copenhagen, Rigshosp, Dept Neonatol
  • ,
  • Anders Bjorkbom, iPSYCH, Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Lundbeck Fdn Initiat Integrat Psychiat Res
  • ,
  • Susan Svane Laursen, iPSYCH, Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Lundbeck Fdn Initiat Integrat Psychiat Res
  • ,
  • Julie Courraud, iPSYCH, Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Lundbeck Fdn Initiat Integrat Psychiat Res
  • ,
  • Anders Borglum
  • Merete Nordentoft, University of Copenhagen
  • ,
  • Thomas Werge, Mental Hlth Serv Capital Reg Denmark, Mental Hlth Ctr Sct Hans, Inst Biol Psychiat
  • ,
  • Preben Bo Mortensen
  • David M. Hougaard, iPSYCH, Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Lundbeck Fdn Initiat Integrat Psychiat Res
  • ,
  • Arieh S. Cohen, iPSYCH, Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Lundbeck Fdn Initiat Integrat Psychiat Res

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.

Original languageEnglish
JournalPediatric Research
Volume89
Issue6
Pages (from-to)1396-1404
Number of pages9
ISSN0031-3998
DOIs
Publication statusPublished - May 2021

    Research areas

  • PRETERM BIRTH, MOLECULAR NETWORKING, NATURAL-PRODUCTS, MICROBIOTA, MORTALITY, DISCOVERY, AUTISM

See relations at Aarhus University Citationformats

ID: 217670973