Evidence map›Paper›PMID 27199628›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society

LacaScore: a novel plasma sample quality control tool based on ascorbic acid and lactic acid levels.

Jean-Pierre Trezzi, Alexandre Bulla, Camille Bellora, Michael Rose, Pierre Lescuyer, Michael Kiehntopf, Karsten Hiller, Fay Betsou

Abstract read
In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
–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

24 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  17. Reproducibility of non-fasting plasma metabolomics measurements across processing delays.Metabolomics : Official journal of the Metabolomic Society · 2018
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  18. Biobanks in the Era of Digital Medicine.Clinical pharmacology and therapeutics · 2018
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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.

Jean-Pierre TrezziIntegrated Biobank of Luxembourg, 6 rue Ernest Barble, 1210 Luxembourg, Luxembourg ; Luxembourg Centre for Systems Biomedicine, 7, Avenue des Hauts-Fourneaux, 4362 Esch-Belval, Luxembourg.
Alexandre BullaSérothèque Centrale, Département de Médecine Génétique et de Laboratoire, Hôpitaux Universitaires de Geneve, 1211 Geneve 14, Switzerland ; International Society for Biological and Environmental Repositories (ISBER) Biospecimen Science Working Group, Vancouver, Canada.
Camille BelloraIntegrated Biobank of Luxembourg, 6 rue Ernest Barble, 1210 Luxembourg, Luxembourg.
Michael RoseInstitute of Clinical Chemistry and Laboratory Diagnostics and Integrierte BioBank Jena (IBBJ), Jena University Hospital, Erlanger Allee 101, 07740 Jena, Germany.
Pierre LescuyerSérothèque Centrale, Département de Médecine Génétique et de Laboratoire, Hôpitaux Universitaires de Geneve, 1211 Geneve 14, Switzerland.
Michael KiehntopfInstitute of Clinical Chemistry and Laboratory Diagnostics and Integrierte BioBank Jena (IBBJ), Jena University Hospital, Erlanger Allee 101, 07740 Jena, Germany ; International Society for Biological and Environmental Repositories (ISBER) Biospecimen Science Working Group, Vancouver, Canada.
Karsten HillerLuxembourg Centre for Systems Biomedicine, 7, Avenue des Hauts-Fourneaux, 4362 Esch-Belval, Luxembourg.
Fay BetsouIntegrated Biobank of Luxembourg, 6 rue Ernest Barble, 1210 Luxembourg, Luxembourg ; International Society for Biological and Environmental Repositories (ISBER) Biospecimen Science Working Group, Vancouver, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionMetabolome analysis is complicated by the continuous dynamic changes of metabolites in vivo and ex vivo. One of the main challenges in metabolomics is the robustness and reproducibility of results, partially driven by pre-analytical variations.

objectivesThe objective of this study was to analyse the impact of pre-centrifugation time and temperature, and to determine a quality control marker in plasma samples.

methodsPlasma metabolites were measured by gas chromatography-mass spectrometry (GC-MS) and analysed with the MetaboliteDetector software. The metabolites, which were the most labile to pre-analytical variations, were further measured by enzymatic assays. A score was calculated for their use as quality control markers.

resultsThe pre-centrifugation temperature was shown to be critical in the stability of plasma samples and had a significant impact on metabolite concentration profiles. In contrast, pre-centrifugation delay had only a minor impact. Based on the results of this study, whole blood should be kept on wet ice and centrifuged within maximum 3 h as a prerequisite for preparing EDTA plasma samples fit for the purpose of metabolome analysis.

conclusionsWe have established a novel blood sample quality control marker, the LacaScore, based on the ascorbic acid to lactic acid ratio in plasma, which can be used as an indicator of the blood pre-centrifugation conditions, and hence the suitability of the sample for metabolome analyses. This method can be applied in research institutes and biobanks, enabling assessment of the quality of their plasma sample collections.

Indexed as

BiobankGC/MSMetabolomicsPlasma processingPre-analyticsQuality control

Identifiers

PMID27199628
PMCPMC4848344

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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.