The influence of sample collection methodology and sample preprocessing on the blood metabolic profile.

AIM Blood serum and plasma have intrinsic differences in their composition and the preprocessing, such as clotting temperature in serum, and storage at room temperature may have further effect on metabolite concentrations. METHODS The influence of sampling preprocessing on the metabolic profiles in serum and different types of plasma was investigated using liquid chromatography and comprehensive 2D gas chromatography coupled to a mass spectrometer. RESULTS The profiles of polar metabolites were significantly dependent on the type of the sample, while lipid profiles were similar in serum and different types of plasma. Extended storage of plasma at room temperature resulted in degradation of lipids already after 1 day. Serum clotting at room temperature generally resulted in higher metabolite concentration compared with serum clotting on ice.

[1]  C. Unger,et al.  Lipids in Health and Disease Effects of 2 or 5 Consecutive Exercise Days on Adipocyte Area and Lipid Parameters in Wistar Rats , 2022 .

[2]  Joachim Selbig,et al.  Decision tree supported substructure prediction of metabolites from GC-MS profiles , 2010, Metabolomics.

[3]  Elaine Holmes,et al.  Impact of analytical bias in metabonomic studies of human blood serum and plasma. , 2006, Analytical chemistry.

[4]  D. Rabier,et al.  A new pitfall in plasma amino acid analysis. , 1989, Clinical chemistry.

[5]  J. Bruce German,et al.  Effects of sample handling and storage on quantitative lipid analysis in human serum , 2009, Metabolomics.

[6]  Joachim Selbig,et al.  The Golm Metabolome Database: a database for GC-MS based metabolite profiling , 2007 .

[7]  S. Eussen,et al.  Kinetic modeling of storage effects on biomarkers related to B vitamin status and one-carbon metabolism. , 2012, Clinical chemistry.

[8]  R. F. Roberts,et al.  Comparison of serum and heparinized plasma samples for measurement of chemistry analytes. , 2004, Clinical chemistry.

[9]  N. Anstey,et al.  Ex-vivo changes in amino acid concentrations from blood stored at room temperature or on ice: implications for arginine and taurine measurements , 2009, BMC clinical pathology.

[10]  Thaer Barri,et al.  UPLC-ESI-QTOF/MS and multivariate data analysis for blood plasma and serum metabolomics: effect of experimental artefacts and anticoagulant. , 2013, Analytica chimica acta.

[11]  Thomas Hankemeier,et al.  The influence of citrate, EDTA, and heparin anticoagulants to human plasma LC–MS lipidomic profiling , 2012, Metabolomics.

[12]  Simone Wahl,et al.  Targeted Metabolomics Identifies Reliable and Stable Metabolites in Human Serum and Plasma Samples , 2014, PloS one.

[13]  S. Hankinson,et al.  Collection, Processing, and Storage of Biological Samples in Epidemiologic Studies: Sex Hormones, Carotenoids, Inflammatory Markers, and Proteomics as Examples , 2006, Cancer Epidemiology Biomarkers & Prevention.

[14]  Inka J. Appel,et al.  Comparison of serum versus plasma collection in gas chromatography – Mass spectrometry‐based metabolomics , 2010, Electrophoresis.

[15]  Joana Pinto,et al.  Human plasma stability during handling and storage: impact on NMR metabolomics. , 2014, The Analyst.

[16]  Andreas Zell,et al.  Preanalytical aspects and sample quality assessment in metabolomics studies of human blood. , 2013, Clinical chemistry.

[17]  Yizeng Liang,et al.  Joint MS-based platforms for comprehensive comparison of rat plasma and serum metabolic profiling. , 2014, Biomedical chromatography : BMC.

[18]  S. Servi,et al.  Synthesis of Lysophospholipids , 2010, Molecules.

[19]  Erik Peter,et al.  Quality markers addressing preanalytical variations of blood and plasma processing identified by broad and targeted metabolite profiling. , 2014, Clinical chemistry.

[20]  Matej Oresic,et al.  MZmine: toolbox for processing and visualization of mass spectrometry based molecular profile data , 2006, Bioinform..

[21]  Matej Oresic,et al.  Processing methods for differential analysis of LC/MS profile data , 2005, BMC Bioinformatics.

[22]  Tobin J Dickerson,et al.  Characterization of differences between blood sample matrices in untargeted metabolomics. , 2011, Analytical chemistry.

[23]  Effect of Storage Time and Temperature on Serum Analytes , 2008 .

[24]  Ying Zhang,et al.  Differences in metabolite profile between blood plasma and serum. , 2010, Analytical biochemistry.

[25]  Ivano Bertini,et al.  Standard operating procedures for pre-analytical handling of blood and urine for metabolomic studies and biobanks , 2011, Journal of biomolecular NMR.

[26]  Wolfram Gronwald,et al.  Urinary metabolite quantification employing 2D NMR spectroscopy. , 2008, Analytical chemistry.

[27]  Sandra Castillo,et al.  Data analysis tool for comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry. , 2011, Analytical chemistry.

[28]  Makoto Murakami,et al.  Phospholipase A2 enzymes. , 2002, Prostaglandins & other lipid mediators.

[29]  A. Marjani.  Effect of Storage Time and Temperature on Serum Analytes , 2006 .

[30]  E. Fukusaki,et al.  Influences of biofluid sample collection and handling procedures on GC-MS based metabolomic studies. , 2010, Journal of bioscience and bioengineering.

[31]  Paolo Vineis,et al.  Performance in Omics Analyses of Blood Samples in Long-Term Storage: Opportunities for the Exploitation of Existing Biobanks in Environmental Health Research , 2013, Environmental health perspectives.

[32]  Sandra Castillo,et al.  Liquid chromatography-mass spectrometry (LC-MS)-based lipidomics for studies of body fluids and tissues. , 2011, Methods in molecular biology.