Evidence map›Paper›PMID 39873382›Full record

ArticleAnalytical chemistry2025

Validating Centralized Biobanking Workflows for NMR Metabolomics Using the PRIMA Panel.

Heidi Altmann, Marko Barovic, Katrin Straßburger, Maximilian Tschäpel, Sophie Jonas, David M Poitz, Alexia Belavgeni, Triantafyllos Chavakis, Peter Mirtschink, Alexander M Funk

Abstract readValidation Study
In one paragraph

Article in Analytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

10 authors.

Heidi AltmannMedical Clinic & Polyclinic 1, University Hospital and Faculty of Medicine Carl Gustav Carus of TU Dresden, Dresden 01307, Germany.
Marko BarovicInstitute for Clinical Chemistry and Laboratory Medicine, University Hospital and Faculty of Medicine Carl Gustav Carus of TU Dresden, Dresden 01307, Germany.
Katrin StraßburgerInstitute for Clinical Chemistry and Laboratory Medicine, University Hospital and Faculty of Medicine Carl Gustav Carus of TU Dresden, Dresden 01307, Germany.
Maximilian TschäpelMedical Clinic & Polyclinic 1, University Hospital and Faculty of Medicine Carl Gustav Carus of TU Dresden, Dresden 01307, Germany.
Sophie JonasInstitute for Clinical Chemistry and Laboratory Medicine, University Hospital and Faculty of Medicine Carl Gustav Carus of TU Dresden, Dresden 01307, Germany.
David M PoitzInstitute for Clinical Chemistry and Laboratory Medicine, University Hospital and Faculty of Medicine Carl Gustav Carus of TU Dresden, Dresden 01307, Germany.
Alexia BelavgeniInstitute for Clinical Chemistry and Laboratory Medicine, University Hospital and Faculty of Medicine Carl Gustav Carus of TU Dresden, Dresden 01307, Germany.ORCID 0000-0001-6311-5858
Triantafyllos ChavakisNational Center for Tumor Diseases (NCT/UCC) Partner Site Dresden, Dresden 01307, Germany.
Peter MirtschinkNational Center for Tumor Diseases (NCT/UCC) Partner Site Dresden, Dresden 01307, Germany.ORCID 0000-0001-5832-1673
Alexander M FunkNational Center for Tumor Diseases (NCT/UCC) Partner Site Dresden, Dresden 01307, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The quality of biological samples used in metabolomics research is significantly influenced by preanalytical factors, such as the timing of centrifugation and freezing. This study aimed to evaluate how preanalytical factors, like delays in centrifugation and freezing, affect metabolomics research. Blood samples, collected in various tube types, were subjected to controlled pre- and postcentrifugation delays. Metabolite levels were quantified using NMR spectroscopy and fitted in linear mixed models used to predict changes in metabolite concentrations over time. The results showed that some metabolites, such as lactic acid, were significantly affected by even short delays, while others remained stable for longer. The study introduced the concept of a "stability time point", marking when a metabolite's concentration changes by 20%. These predictive models were validated in a separate cohort. To apply these findings, the authors developed the PRIMA Panel, an open-source R Shiny tool. This tool allows researchers to assess the impact of preanalytical variations on their samples, predict metabolite stability, and generate performance reports. The PRIMA Panel was tested using samples from the Dresden Integrated Liquid Biobank, proving its utility in a real-world biobank setting. The study emphasizes the importance of tracking preanalytical factors to improve the reliability of metabolomics analyses. The PRIMA Panel is available online and for local deployment, providing a practical solution for quality control in metabolomics research. The results of the study underscore the importance of tracking preanalytical factors in biobanking. A versatile tool for assessing their impact on metabolic data is introduced, improving the reliability of future analyses.

Indexed as

Biological Specimen BanksMetabolomicsWorkflowHumansMagnetic Resonance Spectroscopy

Identifiers

PMID39873382
PMCPMC11822734

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.