Literature DB >> 24305685

Quality markers addressing preanalytical variations of blood and plasma processing identified by broad and targeted metabolite profiling.

Beate Kamlage1, Sandra González Maldonado, Bianca Bethan, Erik Peter, Oliver Schmitz, Volker Liebenberg, Philipp Schatz.   

Abstract

BACKGROUND: Metabolomics is a valuable tool with applications in almost all life science areas. There is an increasing awareness of the essential need for high-quality biospecimens in studies applying omics technologies and biomarker research. Tools to detect effects of both blood and plasma processing are a key for assuring reproducible and credible results. We report on the response of the human plasma metabolome to common preanalytical variations in a comprehensive metabolomics analysis to reveal such high-quality markers.
METHODS: Human EDTA blood was subjected to preanalytical variations while being processed to plasma: microclotting, prolonged processing times at different temperatures, hemolysis, and contamination with buffy layer. In a second experiment, EDTA plasma was incubated at different temperatures for up to 16 h. Samples were subjected to GC-MS and liquid chromatography-tandem mass spectrometry-based metabolite profiling (MxP™ Broad Profiling) complemented by targeted methods, i.e., sphingoids (as part of MxP™ Lipids), MxP™ Catecholamines, and MxP™ Eicosanoids.
RESULTS: Short-term storage of blood, hemolysis, and short-term storage of noncooled plasma resulted in statistically significant increases of 4% to 19% and decreases of 8% to 12% of the metabolites. Microclotting, contamination of plasma with buffy layer, and short-term storage of cooled plasma were of less impact on the metabolome (0% to 11% of metabolites increased, 0% to 8% decreased).
CONCLUSIONS: The response of the human plasma metabolome to preanalytical variation demands implementation of thorough quality assurance and QC measures to obtain reproducible and credible results from metabolomics studies. Metabolites identified as sensitive to preanalytics can be used to control for sample quality.

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Year:  2013        PMID: 24305685     DOI: 10.1373/clinchem.2013.211979

Source DB:  PubMed          Journal:  Clin Chem        ISSN: 0009-9147            Impact factor:   8.327


  55 in total

1.  Minimal variation of the plasma lipidome after delayed processing of neonatal cord blood.

Authors:  John M Wentworth; Naiara G Bediaga; Megan A S Penno; Esther Bandala-Sanchez; Komal N Kanojia; Konstantinos A Kouremenos; Jennifer J Couper; Leonard C Harrison
Journal:  Metabolomics       Date:  2018-09-25       Impact factor: 4.290

2.  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

3.  Impact of post-collection freezing delay on the reliability of serum metabolomics in samples reflecting the California mid-term pregnancy biobank.

Authors:  Michael R La Frano; Suzan L Carmichael; Chen Ma; Macy Hardley; Tong Shen; Ron Wong; Lorenzo Rosales; Kamil Borkowski; Theresa L Pedersen; Gary M Shaw; David K Stevenson; Oliver Fiehn; John W Newman
Journal:  Metabolomics       Date:  2018-11-15       Impact factor: 4.290

4.  Analytes related to erythrocyte metabolism are reliable biomarkers for preanalytical error due to delayed plasma processing in metabolomics studies.

Authors:  Mahim Jain; Adam D Kennedy; Sarah H Elsea; Marcus J Miller
Journal:  Clin Chim Acta       Date:  2017-01-06       Impact factor: 3.786

Review 5.  Understanding preanalytical variables and their effects on clinical biomarkers of oncology and immunotherapy.

Authors:  Lokesh Agrawal; Kelly B Engel; Sarah R Greytak; Helen M Moore
Journal:  Semin Cancer Biol       Date:  2017-12-16       Impact factor: 15.707

Review 6.  Targeted lipidomic strategies for oxygenated metabolites of polyunsaturated fatty acids.

Authors:  Giuseppe Astarita; Alexandra C Kendall; Edward A Dennis; Anna Nicolaou
Journal:  Biochim Biophys Acta       Date:  2014-12-05

7.  Impact of Pre-analytic Blood Sample Collection Factors on Metabolomics.

Authors:  Mary K Townsend; Ying Bao; Clary B Clish; Shelley S Tworoger; Elizabeth M Poole; Kimberly A Bertrand; Peter Kraft; Brian M Wolpin
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2016-03-03       Impact factor: 4.254

8.  Directed Non-targeted Mass Spectrometry and Chemical Networking for Discovery of Eicosanoids and Related Oxylipins.

Authors:  Jeramie D Watrous; Teemu J Niiranen; Kim A Lagerborg; Mir Henglin; Yong-Jiang Xu; Jian Rong; Sonia Sharma; Ramachandran S Vasan; Martin G Larson; Aaron Armando; Samia Mora; Oswald Quehenberger; Edward A Dennis; Susan Cheng; Mohit Jain
Journal:  Cell Chem Biol       Date:  2019-01-17       Impact factor: 8.116

Review 9.  Standardized Assessment of Hereditary Ataxia Patients in Clinical Studies.

Authors:  Brigitte K Paap; Sandra Roeske; Alexandra Durr; Ludger Schöls; Tetsuo Ashizawa; Sylvia Boesch; Lisa M Bunn; Martin B Delatycki; Paola Giunti; Stéphane Lehéricy; Caterina Mariotti; Jörg Melegh; Massimo Pandolfo; Chantal M E Tallaksen; Dagmar Timmann; Shoji Tsuji; Jörg Bela Schulz; Bart P van de Warrenburg; Thomas Klockgether
Journal:  Mov Disord Clin Pract       Date:  2016-02-11

10.  Influence of pregnancy and non-fasting conditions on the plasma metabolome in a rat prenatal toxicity study.

Authors:  S Ramirez-Hincapie; V Giri; J Keller; H Kamp; V Haake; E Richling; B van Ravenzwaay
Journal:  Arch Toxicol       Date:  2021-07-30       Impact factor: 5.153

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