Influence of preanalytical sampling conditions on the 1H NMR metabolic profile of human blood plasma and introduction of the Standard PREanalytical Code used in biobanking

Metabolomics

Volumn 11, Issue 5, 2015, Pages 1197-1207

  Bervoets, Liene ^a   Louis, Evelyne ^a   Reekmans, Gunter ^b   Mesotten, Liesbet ^a,c   Thomeer, Michiel ^a,c   Adriaensens, Peter ^b   Linsen, Loes ^a,d  

^a HASSELT UNIVERSITY   (Belgium)

^b HASSELT UNIVERSITY   (Belgium)

^c DEPARTMENT OF CARDIOLOGY   (Belgium)

^d University Biobank Limburg   (Belgium)

Author keywords

1H NMR spectroscopy; Biobanking; Biomedical research; Plasma; Preanalytical conditions; Standard PREanalytical Code

Indexed keywords

EDETIC ACID; GLUCOSE; LACTIC ACID; LIQUID NITROGEN; PYRUVIC ACID;

ADULT; ARTICLE; BLOOD BANK; BLOOD SAMPLING; CELL METABOLISM; FEMALE; FOURIER TRANSFORMATION; HEMOLYSIS; HUMAN; HUMAN CELL; LIQUID CHROMATOGRAPHY; MALE; METABOLOMICS; NORMAL HUMAN; PRINCIPAL COMPONENT ANALYSIS; PROTON NUCLEAR MAGNETIC RESONANCE; ROOM TEMPERATURE; SAMPLING; SENSITIVITY ANALYSIS; SIGNAL PROCESSING; VALIDATION STUDY;

EID: 84941025536     PISSN: 15733882     EISSN: 15733890     Source Type: Journal    
DOI: 10.1007/s11306-015-0774-y     Document Type: Article

References (36)

1. Baynes, J. W., & Dominiczak, M. H. (2010). Medical biochemistry (3rd ed.). Amsterdam: Elsevier.
2. Bernini, P., Bertini, I., Luchinat, C., Nincheri, P., Staderini, S., & Turano, P. (2011). Standard operating procedures for pre-analytical handling of blood and urine for metabolomic studies and biobanks. Journal of Biomolecular NMR,49(3–4), 231–243.
3. Betsou, F., Lehmann, S., Ashton, G., Barnes, M., Benson, E. E., Coppola, D., et al. (2010). Standard preanalytical coding for biospecimens: defining the sample PREanalytical code. Cancer Epidemiology Biomarkers,19(4), 1004–1011.
4. 1H-NMR-based metabonomics. Nature Medicine,8(12), 1439–1445.
5. Burns, E. R., & Yoshikawa, N. (2002). Hemolysis in serum samples drawn by emergency department personnel versus laboratory phlebotomists. Laboratory Medicine,33(5), 378–380.
6. Collino, S., Martin, F. P., & Rezzi, S. (2013). Clinical metabolomics paves the way towards future healthcare strategies. British Journal of Clinical Pharmacology,75(3), 619–629.
7. Deprez, S., Sweatman, B. C., Connor, S. C., Haselden, J. N., & Waterfield, C. J. (2002). Optimisation of collection, storage and preparation of rat plasma for 1H NMR spectroscopic analysis in toxicology studies to determine inherent variation in biochemical profiles. Journal of Pharmaceutical and Biomedical Analysis,30(4), 1297–1310.
8. Dunn, W. B., Broadhurst, D., Ellis, D. I., Brown, M., Halsall, A., O’Hagan, S., et al. (2008). A GC-TOF-MS study of the stability of serum and urine metabolomes during the UK Biobank sample collection and preparation protocols. International Journal of Epidemiology,37(suppl 1), i23–i30.
9. Felli, I. C., & Brutscher, B. (2009). Recent advances in solution NMR: fast methods and heteronuclear direct detection. ChemPhysChem,10(9–10), 1356–1368.
10. Fiehn, O. (2002). Metabolomics–the link between genotypes and phenotypes. Plant Molecular Biology,48(1–2), 155–171.
11. Fliniaux, O., Gaillard, G., Lion, A., Cailleu, D., Mesnard, F., & Betsou, F. (2011). Influence of common preanalytical variations on the metabolic profile of serum samples in biobanks. Journal of Biomolecular NMR,51(4), 457–465.
12. Issaq, H. J., Van, Q. N., Waybright, T. J., Muschik, G. M., & Veenstra, T. D. (2009). Analytical and statistical approaches to metabolomics research. Journal of Separation Science,32(13), 2183–2199.
13. Kamlage, B., Maldonado, S. G., Bethan, B., Peter, E., Schmitz, O., Liebenberg, V., et al. (2014). Quality markers addressing preanalytical variations of blood and plasma processing identified by broad and targeted metabolite profiling. Clinical Chemistry,60(2), 399–412.
14. Kennedy, C., Angermuller, S., King, R., Noviello, S., Walker, J., Warden, J., et al. (1996). A comparison of hemolysis rates using intravenous catheters versus venipuncture tubes for obtaining blood samples. Journal of Emergency Nursing,22(6), 566–569.
15. Kentgens, A., Bart, J., Van Bentum, P., Brinkmann, A., Van Eck, E., Gardeniers, J., et al. (2008). High-resolution liquid-and solid-state nuclear magnetic resonance of nanoliter sample volumes using microcoil detectors. Journal of Chemical Physics,128(5), 052202.
16. Koseoglu, M., Hur, A., Atay, A., & Cuhadar, S. (2011). Effects of hemolysis interferences on routine biochemistry parameters. Biochemia Medica: Casopis Hrvatskoga Drustva Medicinskih Biokemicara,21(1), 79–85.
17. Kroll, M. H., & Elin, R. J. (1994). Interference with clinical laboratory analyses. Clinical Chemistry,40(11), 1996–2005.
18. Lehmann, S., Guadagni, F., Moore, H., Ashton, G., Barnes, M., Benson, E., et al. (2012). Standard preanalytical coding for biospecimens: review and implementation of the Sample PREanalytical Code (SPREC). Biopreserv Biobank,10(4), 366–374.
19. Lindon, J. C., & Nicholson, J. K. (2008). Spectroscopic and statistical techniques for information recovery in metabonomics and metabolomics. Annual Review of Analytical Chemistry,1, 45–69.
20. Lippi, G., Salvagno, G. L., Montagnana, M., Brocco, G., & Guidi, G. C. (2006). Influence of hemolysis on routine clinical chemistry testing. Clinical Chemistry and Laboratory Medicine,44(3), 311–316.
21. 1H-NMR: A robust protocol based on metabolite spiking and its evaluation in breast cancer. Metabolomics,11(1), 225–236.
22. Madsen, R. K., Lundstedt, T., Gabrielsson, J., Sennbro, C.-J., Alenius, G.-M., Moritz, T., et al. (2011). Diagnostic properties of metabolic perturbations in rheumatoid arthritis. Arthritis Research & Therapy,13(1), R19.
23. 1H-NMR studies of vertebrate blood and plasma. Biochemical Journal,211, 605–615.
24. 13C NMR spectroscopy of human blood plasma. Analytical Chemistry,67(5), 793–811.
25. Nicholson, J. K., Lindon, J. C., & Holmes, E. (1999). ‘Metabonomics’: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica,29(11), 1181–1189.
26. Shen, J., Yan, L., Liu, S., Ambrosone, C. B., & Zhao, H. (2013). Plasma metabolomic profiles in breast cancer patients and healthy controls: by race and tumor receptor subtypes. Translational Oncology,6(6), 757.
27. Teahan, O., Gamble, S., Holmes, E., Waxman, J., Nicholson, J. K., Bevan, C., et al. (2006). Impact of analytical bias in metabonomic studies of human blood serum and plasma. Analytical Chemistry,78(13), 4307–4318.
28. Van der Greef, J., Tas, A., Bouwman, J., Ten Noever de Brauw, M., & Schreurs, W. (1983). Evaluation of field-desorption and fast atom-bombardment mass spectrometric profiles by pattern recognition techniques. Analytica Chimica Acta,150, 45–52.
29. Wood, J. T., Williams, J. S., Pandarinathan, L., Courville, A., Keplinger, M. R., Janero, D. R., et al. (2008). Comprehensive profiling of the human circulating endocannabinoid metabolome: clinical sampling and sample storage parameters. Clinical Chemistry and Laboratory Medicine,46(9), 1289–1295.
30. World Health Organization. (2002). Use of anticoagulants in diagnostic laboratory investigations. WHO/DIL/LAB/99.1 Rev.2. Geneva: WHO.
31. World Health Organization. (2010). WHO guidelines on drawing blood: best practices in phlebotomy (pp. 1–109). Geneva: WHO.
32. Pinto, J., Domingues, M. R. M., Galhano, E., Pita, C., do Céu Almeida, M., Carreira, I. M., et al. (2014). Human plasma stability during handling and storage: impact on NMR metabolomics. Analyst,139(5), 1168–1177.
33. Yang, W., Chen, Y., Xi, C., Zhang, R., Song, Y., Zhan, Q., et al. (2013). Liquid chromatography-tandem mass spectrometry-based plasma metabonomics delineate the effect of metabolites’ stability on reliability of potential biomarkers. Analytical Chemistry,85(5), 2606–2610.
34. Yin, P., Peter, A., Franken, H., Zhao, X., Neukamm, S. S., Rosenbaum, L., et al. (2013). Preanalytical aspects and sample quality assessment in metabolomics studies of human blood. Clinical Chemistry,59(5), 833–845.
35. Yucel, D., & Dalva, K. (1992). Effect of in vitro hemolysis on 25 common biochemical tests. Clinical Chemistry,38(4), 575–577.
36. Zhang, A., Sun, H., & Wang, X. (2013). Power of metabolomics in biomarker discovery and mining mechanisms of obesity. Obesity Reviews,14(4), 344–349.