Evidence map›Paper›PMID 42776325›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2026

Comparative metabolomics of paired maternal-cord samples identifies pathway-level divergence.

Ashley Van Winckel, Mrinalini Gupta, Rachel Klein, Jagadeesh Puvvula, Joseph M Braun, Kurt D Pennell, Emily A DeFranco, Shuk-Mei Ho, Yuet-Kin Leung, Ann M Vuong and 9 more

Abstract readComparative Study
In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

19 authors.

Ashley Van Winckel *Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
Mrinalini Gupta *Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
Rachel KleinDepartment of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
Jagadeesh PuvvulaDepartment of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Joseph M BraunDepartment of Epidemiology, Brown University, Providence, RI, USA.
Kurt D PennellSchool of Engineering, Brown University, Providence, RI, USA.
Emily A DeFrancoDepartment of Obstetrics and Gynecology, College of Medicine, University of Kentucky, Lexington, KY, USA.
Shuk-Mei HoDepartment of Pharmacology and Toxicology, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
Yuet-Kin LeungDepartment of Pharmacology and Toxicology, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
Ann M VuongDepartment of Epidemiology and Biostatistics, School of Public Health, University of Nevada Las Vegas, Las Vegas, NV, USA.
Zana PercyDepartment of Psychiatry and Human Behavior, Warren Alpert School of Medicine, Brown University, Providence, RI, USA.
Priyanka BhashyamCollege of Arts & Sciences, University of Pennsylvania, Philadelphia, PA, USA.
Raymund LeeCollege of Arts & Sciences, University of Pennsylvania, Philadelphia, PA, USA.
Dean P JonesDivision of Pulmonary, Allergy, Critical Care and Sleep Medicine, Emory University, Atlanta, GA, USA.
Vilinh TranDivision of Pulmonary, Allergy, Critical Care and Sleep Medicine, Emory University, Atlanta, GA, USA.
Dasom V KimImmunology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Shouxiong HuangPathogen-Host Interaction Program, Texas Biomedical Research Institute, San Antonio, TX, USA.
Aimin ChenDepartment of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Katherine E ManzDepartment of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA. katmanz@umich.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionDuring pregnancy, the maternal and fetal metabolomes are linked and can influence one another through factors such as maternal diet. However, there is a lack of understanding of baseline maternal and neonate metabolomic similarities and differences.

objectivesTo investigate whether, for typical dyads, maternal metabolomic profiles can serve as a proxy for fetal metabolomic profiles, we conducted a cross-sectional study among a cohort of 65 pregnant persons and their neonates.

methodsWe collected maternal and cord blood at the time of the delivery and utilized high-resolution mass spectrometry to perform untargeted metabolomics on maternal (n = 65) and neonate (n = 65) samples. We performed principal component analysis of the detected features to assess differences between mothers and neonates. We then performed a metabolome-wide association study to identify significant features and subsequently performed pathway enrichment analysis to identify associated metabolic pathways.

resultsWe observed distinct separation between features detected in mothers and neonates from both negative and positive ionization data. Our pathway analysis indicated that maternal and neonate metabolomes differ with respect to five major classes of metabolism, with 16 pathways implicated in metabolic differences between mothers and neonates. We observed pathway-specific metabolomic differences in mothers only, for fatty acid and lipid metabolism, with neonate metabolomic differences driven by non-pathway specific alterations in the global fetal metabolic profile.

conclusionOur study provides evidence to support that maternal metabolomes are not proxies for fetal metabolomes and provides important insight on neonate metabolic changes in the window immediately before and after birth.

Indexed as

Fetal BloodMetabolomeMetabolomicsAdultCross-Sectional StudiesFemaleHumansInfant, NewbornMass SpectrometryMetabolic Networks and PathwaysPregnancyPrincipal Component AnalysisBirthMaternalMetabolomicsNeonatePregnancy

Identifiers

PMID42776325
PMCPMC13601144

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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.