Literature DB >> 27348730

Metabolomic Quality Assessment of EDTA Plasma and Serum Samples.

Linus Malm1, Gunnel Tybring2, Thomas Moritz1, Britta Landin3, Joakim Galli4.   

Abstract

Handling and processing of blood can significantly alter the molecular composition and consistency of biobank samples and can have a major impact on the identification of biomarkers. It is thus crucial to identify tools to determine the quality of samples to be used in biomarker discovery studies. In this study, a non-targeted gas chromatography/time-of-flight mass spectrometry (GC-TOFMS) metabolomic strategy was used with the aim of identifying quality markers for serum and plasma biobank collections lacking proper documentation of preanalytical handling. The effect of postcentrifugation delay was examined in serum stored in tubes with gel separation plugs and ethylenediaminetetraacetic acid (EDTA) plasma in tubes with or without gel separation plugs. The change in metabolic pattern was negligible in all sample types processed within 3 hours after centrifugation regardless of whether the samples were kept at 4°C or 22°C. After 8 and 24 hours postcentrifugation delay before aliquoting, there was a pronounced increase in the number of affected metabolites, as well as in the magnitude of the observed changes. No protective effect on the metabolites was observed in gel-separated EDTA plasma samples. In a separate series of experiments, lactate and glucose levels were determined in plasma to estimate the effect of precentrifugation delay. This separate experiment indicates that the lactate to glucose ratio may serve as a marker to identify samples with delayed time to centrifugation. Although our data from the untargeted GC-TOFMS analysis did not identify any specific markers, we conclude that plasma and serum metabolic profiles remain quite stable when plasma and serum are centrifuged and separated from the blood cells within 3 hours.

Entities:  

Keywords:  delayed processing of serum; metabolomics; plasma

Mesh:

Substances:

Year:  2016        PMID: 27348730     DOI: 10.1089/bio.2015.0092

Source DB:  PubMed          Journal:  Biopreserv Biobank        ISSN: 1947-5543            Impact factor:   2.300


  6 in total

1.  Reproducibility of non-fasting plasma metabolomics measurements across processing delays.

Authors:  Ying Wang; Brian D Carter; Susan M Gapstur; Marjorie L McCullough; Mia M Gaudet; Victoria L Stevens
Journal:  Metabolomics       Date:  2018-09-25       Impact factor: 4.290

2.  Mixture model normalization for non-targeted gas chromatography/mass spectrometry metabolomics data.

Authors:  Anna C Reisetter; Michael J Muehlbauer; James R Bain; Michael Nodzenski; Robert D Stevens; Olga Ilkayeva; Boyd E Metzger; Christopher B Newgard; William L Lowe; Denise M Scholtens
Journal:  BMC Bioinformatics       Date:  2017-02-02       Impact factor: 3.169

3.  Prediction and modeling of pre-analytical sampling errors as a strategy to improve plasma NMR metabolomics data.

Authors:  Carl Brunius; Anders Pedersen; Daniel Malmodin; B Göran Karlsson; Lars I Andersson; Gunnel Tybring; Rikard Landberg
Journal:  Bioinformatics       Date:  2017-11-15       Impact factor: 6.937

4.  MS-based lipidomics of human blood plasma: a community-initiated position paper to develop accepted guidelines.

Authors:  Bo Burla; Makoto Arita; Masanori Arita; Anne K Bendt; Amaury Cazenave-Gassiot; Edward A Dennis; Kim Ekroos; Xianlin Han; Kazutaka Ikeda; Gerhard Liebisch; Michelle K Lin; Tze Ping Loh; Peter J Meikle; Matej Orešič; Oswald Quehenberger; Andrej Shevchenko; Federico Torta; Michael J O Wakelam; Craig E Wheelock; Markus R Wenk
Journal:  J Lipid Res       Date:  2018-08-16       Impact factor: 5.922

5.  Metabolite-related dietary patterns and the development of islet autoimmunity.

Authors:  Randi K Johnson; Lauren Vanderlinden; Brian C DeFelice; Katerina Kechris; Ulla Uusitalo; Oliver Fiehn; Marci Sontag; Tessa Crume; Andreas Beyerlein; Åke Lernmark; Jorma Toppari; Anette-G Ziegler; Jin-Xiong She; William Hagopian; Marian Rewers; Beena Akolkar; Jeffrey Krischer; Suvi M Virtanen; Jill M Norris
Journal:  Sci Rep       Date:  2019-10-15       Impact factor: 4.379

6.  Optimization of a GC-MS method for the profiling of microbiota-dependent metabolites in blood samples: An application to type 2 diabetes and prediabetes.

Authors:  Patrycja Mojsak; Katarzyna Maliszewska; Paulina Klimaszewska; Katarzyna Miniewska; Joanna Godzien; Julia Sieminska; Adam Kretowski; Michal Ciborowski
Journal:  Front Mol Biosci       Date:  2022-09-23
  6 in total

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