Evidence map›Paper›PMID 42750944›Full record

ArticleAdvances in hematology2026

Urinary Proteomic Signatures in Sickle Cell Disease: Search for Biomarkers Associated With Underlying Molecular Pathways.

Vera Hoving, Hans Wessels, Jolein Gloerich, Miranda van Berkel, Albertine E Donker, Dorine W Swinkels, Saskia E M Schols

Abstract read
In one paragraph

Article in Advances in hematology, 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

7 authors.

Vera HovingDepartment of Hematology, Radboud University Medical Center, Nijmegen 6525 GA 10, the Netherlands, radboudumc.nl.ORCID https://orcid.org/0000-0002-5036-8554
Hans WesselsDepartment of Human Genetics, Translational Metabolic Laboratory, Radboud University Medical Center, Nijmegen 6525 GA 10, the Netherlands, radboudumc.nl.ORCID https://orcid.org/0000-0001-5957-3127
Jolein GloerichDepartment of Human Genetics, Translational Metabolic Laboratory, Radboud University Medical Center, Nijmegen 6525 GA 10, the Netherlands, radboudumc.nl.ORCID https://orcid.org/0000-0001-5976-8426
Miranda van BerkelDepartment of Laboratory Medicine, Radboud Laboratory for Diagnostics, Radboud University Medical Center, Nijmegen 6525 GA 10, the Netherlands, radboudumc.nl.ORCID https://orcid.org/0000-0002-6500-3419
Albertine E DonkerRadboudumc Iron Expertise Center, Nijmegen 6525 GA 10, the Netherlands.ORCID https://orcid.org/0000-0002-9852-515X
Dorine W SwinkelsRadboudumc Iron Expertise Center, Nijmegen 6525 GA 10, the Netherlands.ORCID https://orcid.org/0000-0002-1040-9446
Saskia E M ScholsDepartment of Hematology, Radboud University Medical Center, Nijmegen 6525 GA 10, the Netherlands, radboudumc.nl.ORCID https://orcid.org/0000-0003-2423-2829

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identifying urinary biomarkers of sickle cell disease (SCD) may provide insights into disease mechanisms and support improved disease monitoring. In this pilot study, we analyzed the urinary proteome of 32 SCD patients (children and adults, steady state, and various genotypes) and 19 healthy controls using mass spectrometry-based proteomics. A total of 2263 proteins were detected, of which 978 were consistently quantified across groups. Ninety proteins showed differential abundance between SCD patients and controls, with 26 upregulated and 64 downregulated in SCD. Upregulated proteins included those associated with cellular stress response (e.g., DNA damage-inducible 1 homolog 2) and immune activation, whereas proteins involved in hemoglobin clearance and mitochondrial metabolism were downregulated, consistent with hemolysis and mitochondrial dysfunction. These findings suggest that urinary proteomics can capture systemic processes relevant to SCD pathophysiology. Despite the small and heterogeneous cohort, this study highlights candidate urinary biomarkers and molecular pathways that warrant validation in larger, stratified cohorts to assess their potential for disease monitoring.

Identifiers

PMID42750944
PMCPMC13578929

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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.