Evidence map›Paper›PMID 39152333›Full record

ArticlePediatric research2025

Distinct protein patterns related to postnatal development in small for gestational age preterm infants.

Eva R Smit, Michelle Romijn, Pieter Langerhorst, Carmen van der Zwaan, Hilde van der Staaij, Joost Rotteveel, Anton H van Kaam, Suzanne F Fustolo-Gunnink, Arie J Hoogendijk, Wes Onland and 2 more

Abstract read
In one paragraph

Article in Pediatric research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
  4. [Correlation Between Inflammatory Cytokine Levels and Growth Restriction in Full-term Small-for-Date Infants].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2025
    Article
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.

Eva R Smit *Department of Molecular Hematology, Sanquin Research, Amsterdam, the Netherlands.
Michelle Romijn *Department of Neonatology, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands.
Pieter LangerhorstDepartment of Molecular Hematology, Sanquin Research, Amsterdam, the Netherlands.
Carmen van der ZwaanDepartment of Molecular Hematology, Sanquin Research, Amsterdam, the Netherlands.
Hilde van der StaaijSanquin Research & Lab Services, Sanquin Blood Supply Foundation, Amsterdam, the Netherlands.
Joost RotteveelAmsterdam Reproduction and Development Research Institute, Amsterdam, the Netherlands.
Anton H van KaamDepartment of Neonatology, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands.
Suzanne F Fustolo-GunninkSanquin Research & Lab Services, Sanquin Blood Supply Foundation, Amsterdam, the Netherlands.
Arie J HoogendijkDepartment of Molecular Hematology, Sanquin Research, Amsterdam, the Netherlands.
Wes OnlandDepartment of Neonatology, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands.
Martijn J J FinkenAmsterdam Reproduction and Development Research Institute, Amsterdam, the Netherlands.
Maartje van den BiggelaarDepartment of Molecular Hematology, Sanquin Research, Amsterdam, the Netherlands. m.vandenbiggelaar@sanquin.nl.ORCID 0000-0001-6970-5496

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPreterm infants, especially those born small for gestational age (SGA), are at risk of short-term and long-term health complications. Characterization of changes in circulating proteins postnatally in preterm infants may provide valuable fundamental insights into this population. Here, we investigated postnatal developmental patterns in preterm infants and explored protein signatures that deviate between SGA infants and appropriate for gestational age (AGA) infants using a mass spectrometry (MS)-based proteomics workflow.

methodsLongitudinal serum samples obtained at postnatal days 0, 3, 7, 14, and 28 from 67 preterm infants were analyzed using unbiased MS-based proteomics.

results314 out of 833 quantified serum proteins change postnatally, including previously described age-related changes in immunoglobulins, hemoglobin subunits, and new developmental patterns, e.g. apolipoproteins (APOA4) and terminal complement cascade (C9) proteins. Limited differences between SGA and AGA infants were found at birth while longitudinal monitoring revealed 69 deviating proteins, including insulin-sensitizing hormone adiponectin, platelet proteins, and 24 proteins with an annotated function in the immune response.

conclusionsThis study shows the potential of MS-based serum profiling in defining circulating protein trajectories in the preterm infant population and its ability to identify longitudinal alterations in protein levels associated with SGA. IMPACT: Postnatal changes of circulating proteins in preterm infants have not fully been elucidated but may contribute to development of health complications. Mass spectrometry-based analysis is an attractive approach to study circulating proteins in preterm infants with limited material. Longitudinal plasma profiling reveals postnatal developmental-related patterns in preterm infants (314/833 proteins) including previously described changes, but also previously unreported proteins. Longitudinal monitoring revealed an immune response signature between SGA and AGA infants. This study highlights the importance of taking postnatal changes into account for translational studies in preterm infants.

Indexed as

Blood ProteinsInfant, PrematureInfant, Small for Gestational AgeBiomarkersFemaleGestational AgeHumansInfant, NewbornLongitudinal StudiesMaleMass SpectrometryProteomicsBiomarkersBlood Proteins

Identifiers

PMID39152333
PMCPMC12119372

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.