Evidence map›Paper›PMID 38716308›Full record

ArticleAnalytical science advances2023

A global metabolomics minefield: Confounding effects of preanalytical factors when studying rare disorders.

Hanne Bendiksen Skogvold, Steven Ray Haakon Wilson, Per Ola Rønning, Linda Ferrante, Siri Hauge Opdal, Torleiv Ole Rognum, Helge Rootwelt, Katja Benedikte Prestø Elgstøen

Abstract read
In one paragraph

Article in Analytical science advances, 2023. 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. Global Metabolomics Using LC-MS for Clinical Applications.Methods in molecular biology (Clifton, N.J.) · 2025
    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

8 authors.

Hanne Bendiksen SkogvoldDepartment of Mechanical, Electronic and Chemical Engineering, Faculty of Technology, Art and Design Oslo Metropolitan University Oslo Norway.ORCID https://orcid.org/0000-0002-3965-9406
Steven Ray Haakon WilsonDepartment of Chemistry University of Oslo Oslo Norway.
Per Ola RønningDepartment of Mechanical, Electronic and Chemical Engineering, Faculty of Technology, Art and Design Oslo Metropolitan University Oslo Norway.
Linda FerranteDepartment of Forensic Sciences, Section of Forensic Pathology and Clinical Forensic Medicine Oslo University Hospital Oslo Norway.
Siri Hauge OpdalDepartment of Forensic Sciences, Section of Forensic Pathology and Clinical Forensic Medicine Oslo University Hospital Oslo Norway.
Torleiv Ole RognumDepartment of Forensic Sciences, Section of Forensic Pathology and Clinical Forensic Medicine Oslo University Hospital Oslo Norway.
Helge RootweltDepartment of Medical Biochemistry Oslo University Hospital Oslo Norway.
Katja Benedikte Prestø ElgstøenDepartment of Medical Biochemistry Oslo University Hospital Oslo Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A common challenge when studying rare diseases or medical conditions is the limited number of patients, usually resulting in long inclusion periods as well as unequal sampling and storage conditions. The main purpose of this study was to demonstrate the challenges when comparing samples subject to different preanalytical conditions. We performed a global (commonly referred to as "untargeted") liquid chromatography-high resolution mass spectrometry metabolomics analysis of blood samples from cases of sudden infant death syndrome and controls stored as dried blood spots on a chemical-free filter card for 15 years at room temperature compared with the same blood samples stored as whole blood at -80°C before preparing new dried blood spots using a chemically treated filter card. Principal component analysis plots distinctly separated the samples based on the type of filter card and storage, but not sudden infant death syndrome versus controls. Note that, 1263 out of 5161 and 642 out of 1587 metabolite features detected in positive and negative ionization mode, respectively, were found to have significant 2-fold changes in amounts corresponding to different preanalytical conditions. The study demonstrates that the dried blood spot metabolome is largely affected by preanalytical factors. This emphasizes the importance of thoroughly addressing preanalytical factors during study design and interpretation, enabling identification of real, biological differences between sample groups whilst preventing other factors or random variation to be falsely interpreted as positive results.

Indexed as

dried blood spotsmetabolomicspreanalytical effectspreanalytical variationrare disordersstoragesudden infant death syndrome

Identifiers

PMID38716308
PMCPMC10989595

What Socratic holds

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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 Socratic graph.