Influence of collection tubes during quantitative targeted metabolomics studies in human blood samples

被引:48
作者
Paglia, Giuseppe [1 ]
Del Greco, Fabiola M. [1 ]
Sigurdsson, Baldur B. [1 ,2 ]
Rainer, Johannes [1 ]
Volani, Chiara [1 ,3 ]
Hicks, Andrew A. [1 ]
Pramstaller, Peter P. [1 ]
Smarason, Sigurdur V. [1 ]
机构
[1] Eurac Res, Inst Biomed, Bolzano, Italy
[2] Landspitoli Univ Hosp, Dept Clin Biochem, Reykjavik, Iceland
[3] Med Univ Innsbruck, Dept Internal Med 2, Innsbruck, Austria
关键词
Targeted metabolomics; Plasma EDTA; Plasma citrate; Serum; Sarcosine; AbsoluteIDQ p180 kit biocrates; HUMAN SERUM; PLASMA; PLATELETS; AGE;
D O I
10.1016/j.cca.2018.08.014
中图分类号
R446 [实验室诊断]; R-33 [实验医学、医学实验];
学科分类号
1001 ;
摘要
Background: Plasma and serum are the most widely used matrices in clinical studies. However, some variability in absolute concentrations of metabolites are likely to be observed in these collection tubes matrices. Methods: We analyzed 189 metabolites using the same protocol for quantitative targeted metabolomics (LC-MS/MS AbsoluteIDQ p180 Kit Biocrates) in three types of samples, serum, plasma EDTA and citrate, of 80 subjects from the Cooperative Health Research In South Tyrol cohort (40 healthy elderly and 40 healthy young). Results: The concentration levels were higher in serum than citrate and EDTA, in particular for amino acids and biogenic amines. The average Pearson's correlation coefficients were however always higher than 0.7 for these two classes of metabolites. We could also demonstrate that blank EDTA vacutainer tubes contain a significant amount of sarcosine. Finally, we compared the metabolome of young people against elderly subjects and found that the highest number of metabolites significantly changing with age was detected in serum. Conclusion: Serum samples provide higher sensitivity for biomarker discovery studies. Due to the presence of spurious amount of sarcosine in vacutainer EDTA tubes, plasma EDTA is not suitable for studies requiring accurate quantification of sarcosine.
引用
收藏
页码:320 / 328
页数:9
相关论文
共 34 条
[1]  
[Anonymous], BIOANALYSIS
[2]   Prediction of intracellular metabolic states from extracellular metabolomic data [J].
Aurich, Maike K. ;
Paglia, Giuseppe ;
Rolfsson, Ottar ;
Hrafnsdottir, Sigrun ;
Magnusdottir, Manuela ;
Stefaniak, Magdalena M. ;
Palsson, Bernhard O. ;
Fleming, Ronan M. T. ;
Thiele, Ines .
METABOLOMICS, 2015, 11 (03) :603-619
[3]   UPLC-ESI-QTOF/MS and multivariate data analysis for blood plasma and serum metabolomics: Effect of experimental artefacts and anticoagulant [J].
Barri, Thaer ;
Dragsted, Lars Ove .
ANALYTICA CHIMICA ACTA, 2013, 768 :118-128
[4]   Harmonizing lipidomics: NIST interlaboratory comparison exercise for lipidomics using SRM 1950-Metabolites in Frozen Human Plasma [J].
Bowden, John A. ;
Heckert, Alan ;
Ulmer, Candice Z. ;
Jones, Christina M. ;
Koelmel, Jeremy P. ;
Abdullah, Laila ;
Ahonen, Linda ;
Alnouti, Yazen ;
Armando, Aaron M. ;
Asara, John M. ;
Bamba, Takeshi ;
Barr, John R. ;
Bergquist, Jonas ;
Borchers, Christoph H. ;
Brandsma, Joost ;
Breitkopf, Susanne B. ;
Cajka, Tomas ;
Cazenave-Gassiot, Amaury ;
Checa, Antonio ;
Cinel, Michelle A. ;
Colas, Romain A. ;
Cremers, Serge ;
Dennis, Edward A. ;
Evans, James E. ;
Fauland, Alexander ;
Fiehn, Oliver ;
Gardner, Michael S. ;
Garrett, Timothy J. ;
Gotlinger, Katherine H. ;
Han, Jun ;
Huang, Yingying ;
Neo, Aveline Huipeng ;
Hyotylainen, Tuulia ;
Izumi, Yoshihiro ;
Jiang, Hongfeng ;
Jiang, Houli ;
Jiang, Jiang ;
Kachman, Maureen ;
Kiyonami, Reiko ;
Klavins, Kristaps ;
Klose, Christian ;
Kofeler, Harald C. ;
Kolmert, Johan ;
Koal, Therese ;
Koster, Grielof ;
Kuklenyik, Zsuzsanna ;
Kurland, Irwin J. ;
Leadley, Michael ;
Lin, Karen ;
Maddipati, Krishna Rao .
JOURNAL OF LIPID RESEARCH, 2017, 58 (12) :2275-2288
[5]   Blood collection tubes as medical devices: The potential to affect assays and proposed verification and validation processes for the clinical laboratory [J].
Bowen, Raffick A. R. ;
Adcock, Dorothy M. .
CLINICAL BIOCHEMISTRY, 2016, 49 (18) :1321-1330
[6]   Reliability of Serum Metabolites over a Two-Year Period: A Targeted Metabolomic Approach in Fasting and Non-Fasting Samples from EPIC [J].
Carayol, Marion ;
Licaj, Idlir ;
Achaintre, David ;
Sacerdote, Carlotta ;
Vineis, Paolo ;
Key, Timothy J. ;
Moret, N. Charlotte Onland ;
Scalbert, Augustin ;
Rinaldi, Sabina ;
Ferrari, Pietro .
PLOS ONE, 2015, 10 (08)
[7]   Individual variability in human blood metabolites identifies age-related differences [J].
Chaleckis, Romanas ;
Murakami, Itsuo ;
Takada, Junko ;
Kondoh, Hiroshi ;
Yanagida, Mitsuhiro .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2016, 113 (16) :4252-4259
[8]  
Corso G, 2010, BIOANALYSIS, V2, P1883, DOI [10.4155/bio.10.149, 10.4155/BIO.10.149]
[9]   Molecular phenotyping of a UK population: defining the human serum metabolome [J].
Dunn, Warwick B. ;
Lin, Wanchang ;
Broadhurst, David ;
Begley, Paul ;
Brown, Marie ;
Zelena, Eva ;
Vaughan, Andrew A. ;
Halsall, Antony ;
Harding, Nadine ;
Knowles, Joshua D. ;
Francis-McIntyre, Sue ;
Tseng, Andy ;
Ellis, David I. ;
O'Hagan, Steve ;
Aarons, Gill ;
Benjamin, Boben ;
Chew-Graham, Stephen ;
Moseley, Carly ;
Potter, Paula ;
Winder, Catherine L. ;
Potts, Catherine ;
Thornton, Paula ;
McWhirter, Catriona ;
Zubair, Mohammed ;
Pan, Martin ;
Burns, Alistair ;
Cruickshank, J. Kennedy ;
Jayson, Gordon C. ;
Purandare, Nitin ;
Wu, Frederick C. W. ;
Finn, Joe D. ;
Haselden, John N. ;
Nicholls, Andrew W. ;
Wilson, Ian D. ;
Goodacre, Royston ;
Kell, Douglas B. .
METABOLOMICS, 2015, 11 (01) :9-26
[10]  
Floegel A., EUR J EPIDEMIOL