Evidence map›Paper›PMID 32942288›Full record

ArticlePediatric research2021

Gestational age-dependent development of the neonatal metabolome.

Madeleine Ernst, Simon Rogers, Ulrik Lausten-Thomsen, Anders Björkbom, Susan Svane Laursen, Julie Courraud, Anders Børglum, Merete Nordentoft, Thomas Werge, Preben Bo Mortensen and 2 more

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Article in Pediatric research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
5.6field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.

  1. Pooled it
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  6. Environmental and Maternal Imprints on Infant Gut Metabolic Programming.bioRxiv : the preprint server for biology · 2025
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  11. Effects of Long-Term Storage on the Biobanked Neonatal Dried Blood Spot Metabolome.Journal of the American Society for Mass Spectrometry · 2023
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 6 institutions in 2 countries.

Madeleine ErnstSection for Clinical Mass Spectrometry, Department of Congenital Disorders, Danish Center for Neonatal Screening, Statens Serum Institut, Copenhagen, Denmark. maet@ssi.dk.
Simon RogersSchool of Computing Science, University of Glasgow, Glasgow, G12 8QQ, UK.
Ulrik Lausten-ThomsenDepartment of Neonatology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark.
Anders BjörkbomSection for Clinical Mass Spectrometry, Department of Congenital Disorders, Danish Center for Neonatal Screening, Statens Serum Institut, Copenhagen, Denmark.
Susan Svane LaursenSection for Clinical Mass Spectrometry, Department of Congenital Disorders, Danish Center for Neonatal Screening, Statens Serum Institut, Copenhagen, Denmark.
Julie CourraudSection for Clinical Mass Spectrometry, Department of Congenital Disorders, Danish Center for Neonatal Screening, Statens Serum Institut, Copenhagen, Denmark.
Anders BørglumiPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark.
Merete NordentoftiPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark.
Thomas WergeiPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark.
Preben Bo MortenseniPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark.
David M HougaardSection for Clinical Mass Spectrometry, Department of Congenital Disorders, Danish Center for Neonatal Screening, Statens Serum Institut, Copenhagen, Denmark.
Arieh S CohenSection for Clinical Mass Spectrometry, Department of Congenital Disorders, Danish Center for Neonatal Screening, Statens Serum Institut, Copenhagen, Denmark.
Lundbeck Foundation · DKStatens Serum Institut · DKAarhus University · DKCopenhagen University Hospital · DKUniversity of Copenhagen · DKUniversity of Glasgow · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrematurity is a severe pathophysiological condition, however, little is known about the gestational age-dependent development of the neonatal metabolome.

methodsUsing 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.

resultsA total of 1459 (~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.

conclusionsOur 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. IMPACT: A large variation in the neonatal dried blood spot metabolome from residual heel pricks stored at the Danish Neonatal Screening Biobank can be explained by gestational age. While previous studies have assessed the relation of selected metabolic markers to gestational age, this study assesses metabolome-wide changes related to prematurity. Using a combination of recently developed metabolome mining tools, we assess the relation of over 9000 metabolic features to gestational age. The ability to assess metabolome-wide changes related to prematurity in neonates could pave the way to finding novel biochemical underpinnings of health complications related to preterm birth.

Indexed as

Gestational AgeMetabolomeChromatography, LiquidCohort StudiesDenmarkFemaleHumansInfant, NewbornInfant, PrematureMaleTandem Mass Spectrometry

Identifiers

PMID32942288
OpenAlexW3087038844

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.