Skip to main content
SpringerLink
Log in

Standard operating procedures for pre-analytical handling of blood and urine for metabolomic studies and biobanks

  • Article
  • Published:
Journal of Biomolecular NMR Aims and scope Submit manuscript

Abstract

1H NMR metabolic profiling of urine, serum and plasma has been used to monitor the impact of the pre-analytical steps on the sample quality and stability in order to propose standard operating procedures (SOPs) for deposition in biobanks. We analyzed the quality of serum and plasma samples as a function of the elapsed time (t = 0−4 h) between blood collection and processing and of the time from processing to freezing (up to 24 h). The stability of the urine metabolic profile over time (up to 24 h) at various storage temperatures was monitored as a function of the different pre-analytical treatments like pre-storage centrifugation, filtration, and addition of the bacteriostatic preservative sodium azide. Appreciable changes in the profiles, reflecting changes in the concentration of a number of metabolites, were detected and discussed in terms of chemical and enzymatic reactions for both blood and urine samples. Appropriate procedures for blood derivatives collection and urine preservation/storage that allow maintaining as much as possible the original metabolic profile of the fresh samples emerge, and are proposed as SOPs for biobanking.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Scheme 1
Fig. 1
Fig. 2
Scheme 2
Fig. 3
Fig. 4
Scheme 3

Similar content being viewed by others

References

  • Akira K, Masu S, Imachi M, Mitome H, Hashimoto M, Hashimoto T (2008) 1H NMR-based metabonomic analysis of urine from young spontaneously hypertensive rats. J Pharm Biomed Anal 46:550–556

    Article  Google Scholar 

  • Assfalg M, Bertini I, Colangiuli D, Luchinat C, Schäfer H, Schütz B, Spraul M (2008) Evidence of different metabolic phenotypes in humans. Proc Natl Acad Sci USA 105:1420–1424

    Article  ADS  Google Scholar 

  • Barton RH, Nicholson JK, Elliott P, Holmes E (2008) High-throughput 1H NMR-based metabolomic analysis of human serum and urine for large-scale epidemiological studies: validation study. Int J Epidemiol 37:i31–i40

    Article  Google Scholar 

  • Bartsch T, Alfke K, Wolff S, Rohr A, Jansen O, Deuschl G (2008) Focal MR spectroscopy of hippocampal CA-1 lesions in transient global amnesia. Neurology 70:1030–1035

    Article  Google Scholar 

  • Baynes JW, Dominiczak MH (2010) Medical biochemistry. Elsevier, Amsterdam

    Google Scholar 

  • Beckonert O, Keun HC, Ebbels TMD, Bundy J, Holmes E, Lindon JC, Nicholson JK (2007) Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts. Nature 11:2692–2703

    Google Scholar 

  • Bernini P, Bertini I, Luchinat C, Nepi S, Saccenti E, Schäfer H, Schütz B, Spraul M, Tenori L (2009) Individual human phenotypes in metabolic space and time. J Proteome Res 8:4264–4271

    Article  Google Scholar 

  • Bertini I, Calabrò A, De Carli V, Luchinat C, Nepi S, Porfirio B, Renzi D, Saccenti E, Tenori L (2009) Metabonomic signature of celiac disease. J Proteome Res 8:170–177

    Article  Google Scholar 

  • Brindle JT, Antti H, Holmes E, Tranter G, Nicholson JK, Bethell HW, Clarke S, Schofield PM, McKilligin E, Mosedale DE, Grainger DJ (2002) Rapid and noninvasive diagnosis of the presence and severity of coronary heart disease using 1H-NMR-based metabonomics. Nat Med 8:1439–1444

    Article  Google Scholar 

  • Claudino WM, Quattrone A, Biganzoli L, Pestrin M, Bertini I, Di Leo A (2007) Metabolomics: available results, current research projects in breast cancer, and future applications. J Clin Onc 25:2840–2846

    Article  Google Scholar 

  • Coen M, O’Sullivan M, Bubb WA, Kuchel PW, Sorrell T (2005) Proton nuclear magnetic resonance-based metabonomics for rapid diagnosis of meningitis and ventriculitis. Clin Infect Dis 41:1582–1590

    Article  Google Scholar 

  • Constantinou MA, Theocharis SE, Mikros E (2007) Application of metabonomics on an experimental model of fibrosis and cirrhosis induced by thioacetamide in rats. Toxicol Appl Pharmacol 218:11–19

    Article  Google Scholar 

  • Coolen SA, Daykin CA, van Duynhoven JP, van Dorsten FA, Wulfert F, Mathot J, Scheltinga MR, Stroosma O, Vader H, Wijnen MH (2008) Measurement of ischaemia-reperfusion in patients with intermittent claudication using NMR-based metabonomics. NMR Biomed 21:686–695

    Article  Google Scholar 

  • Dunn WB, Broadhurst D, Ellis DI, Brown M, Halsall A, O’Hagan S, Spasic I, Tseng A, Douglas BK (2008) A GC-TOF-MS study of the stability of serum and urine metabolomes during the UK Biobank sample collection and preparation protocols. Int J Epidemiol 37:i23–i30

    Article  Google Scholar 

  • Fearnside JF, Dumas ME, Rothwell AR, Wilder SP, Cloarec O, Toye A, Blancher C, Holmes E, Tatoud R, Barton RH, Scott J, Nicholson JK, Gauguier D (2008) Phylometabonomic patterns of adaptation to high fat diet feeding in inbred mice. PLoS ONE 3:e1668

    Article  ADS  Google Scholar 

  • Fiehn O (2002) Metabolomics–the link between genotypes and phenotypes. Plant Mol Biol 48:155–171

    Article  Google Scholar 

  • Gao XX, Ge HM, Zheng WF, Tan RX (2008) NMR-based metabonomics for detection of Helicobacter pylori infection in gerbils: which is more descriptive. Helicobacter 13:103–111

    Article  Google Scholar 

  • Garber K (2004) Energy boost: the Warburg effect returns in a new theory of cancer. J Natl Cancer Inst 96:1805–1806

    Article  Google Scholar 

  • German JB, Hammock BD, Watkins SM (2005) Metabolomics: building on a century of biochemistry to guide human health. Metabolomics 1:3–9

    Article  Google Scholar 

  • Griffin JL, Scott J, Nicholson JK (2007) The influence of pharmacogenetics on fatty liver disease in the wistar and kyoto rats: a combined transcriptomic and metabonomic study. J Proteome Res 6:54–61

    Article  Google Scholar 

  • Holmes E, Loo RL, Stamler J, Bictash M, Yap IKS, Chan Q, Ebbels T, Delorio M, Brown IJ, Veselkov KA, Daviglus ML, Kesteloot H, Ueshima H, Zhao L, Nicholson JK, Elliott P (2008) Human metabolic phenotype diversity and its association with diet and blood pressure. Nature 453:396–401

    Article  ADS  Google Scholar 

  • Jackson C, Best N, Elliott P (2008) The UK Biobank sample handling and storage validation studies. Int J Epidemiol 37:i2–i6

    Article  Google Scholar 

  • Jung M, Pergande M (1983) Particulate and free enzyme activity in urine as a result of the shedding of brush-border membranes from kidney. Clin Chem 29(2):392–393

    Google Scholar 

  • Koukoulaki M, Donovan MO, Pursglove S, Alexopoulou D, Hadjiconstantinou V, Drakopoulos S (2008) Prospective study of urine cytology screening for BK polyomavirus replication in renal transplant recipients. Cytopathology 19:385–388

    Article  Google Scholar 

  • Lindon JC, Holmes E, Nicholson JK (2004) Toxicological applications of magnetic resonance. Prog NMR Spectrosc 45:109–143

    Article  Google Scholar 

  • Madsen R, Lundstedt T, Trygg J (2010) Chemometrics in metabolomics—a review in human disease diagnosis. Anal Chim Acta 659(1–2):23–33

    Article  Google Scholar 

  • Makinen VP, Soininen P, Forsblom C, Parkkonen M, Ingman P, Kaski K, Groop PH, Ala-Korpela M (2008) 1H NMR metabonomics approach to the disease continuum of diabetic complications and premature death. Mol Syst Biol 4:167

    Article  Google Scholar 

  • Marchesi JR, Holmes E, Khan F, Kochhar S, Scanlan P, Shanahan F, Wilson ID, Wang Y (2007) Rapid and noninvasive metabonomic characterization of inflammatory bowel disease. J Proteome Res 6:546–551

    Article  Google Scholar 

  • Nicholson JK, Lindon JC (2008) Metabonomics. Nature 455:1054–1056

    Article  ADS  Google Scholar 

  • Nicholson JK, Lindon JC, Holmes E (1999) ‘Metabonomics’: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 29:1181–1189

    Article  Google Scholar 

  • Oakman C, Tenori L, Biganzoli L, Santarpia L, Cappadodona S, Luchinat C, Di Leo A (2010) Uncovering the metabolomic fingerprint of breast cancer. Int J Biochem Cell Biol (in press)

  • Peakman TC, Elliott P (2008) UK Biobank Pilot Study: stability of haematological and clinical chemistry analytes. Int J Epidemiol 37:i16–i22

    Article  Google Scholar 

  • Qiu YP, Cai GX, Su MM, Chen T, Zheng X, Xu Y, Ni Y, Zhao A, Xu LX, Cai S, Jia W (2009) Serum metabolite profiling of human colorectal cancer using GC-TOFMS and UPLC-QTOFMS. J Proteome Res 8:4844–4850

    Article  Google Scholar 

  • Saude EJ, Sykes BD (2007) Urine stability for metabolomic studies: effects of preparation and storage. Metabolomics 3:19–27

    Article  Google Scholar 

  • Schnackenberg LK, Sun J, Espandiari P, Holland RD, Hanig J, Beger RD (2007) Metabonomics evaluations of age-related changes in the urinary compositions of male Sprague Dawley rats and effects of data normalization methods on statistical and quantitative analysis. BMC Bioinf 8(Suppl 7):S3

    Article  Google Scholar 

  • Shaw RJ (2006) Glucose metabolism and cancer. Curr Opin Cell Biol 18:598–608

    Article  Google Scholar 

  • Silwood CJL, Grootveld M, Lynch E (2002) 1H NMR investigations of the molecular nature of low-molecular-mass calcium ions in biofluids. J Biol Inorg Chem 7:46–57

    Article  Google Scholar 

  • Sreekumar A, Poisson LM, Rajendiran TM, Khan AP, Cao Q, Yu J, Laxman B, Mehra R, Lonigro RJ, Li Y, Nyati MK, Ahsan A, Kalyana-Sundaram S, Han B, Cao X, Byun J, Omenn GS, Ghosh D, Pennathur S, Alexander DC, Berger A, Shuster JR, Wei JT, Varambally S, Beecher C, Chinnaiyan AM (2009) Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature 457:910–914

    Article  ADS  Google Scholar 

  • Suna T, Salminen A, Soininen P, Laatikainen R, Ingman P, Makela S, Savolainen MJ, Hannuksela ML, Jauhiainen M, Taskinen M, Kaski K, Ala-Korpela M (2006) 1H NMR metabonomics of plasma lipoprotein subclasses: elucidation of metabolic clustering by self-organising-map. NMR Biomed 20:658–672

    Article  Google Scholar 

  • Teichert F, Verschoyle RD, Greaves P, Edwards RE, Teahan O, Jones DJ, Wilson ID, Farmer PB, Steward WP, Gant TW, Gescher AJ, Keun HC (2008) Metabolic profiling of transgenic adenocarcinoma of mouse prostate (TRAMP) Tissue by (1)H-NMR analysis: evidence for unusual phospholipid metabolism. Prostate 68:1035–1047

    Article  Google Scholar 

  • Warburg O (1956) On the origin of cancer cells. Science 123:309–314

    Article  ADS  Google Scholar 

  • Weckwerth W (2007) Metabolomics methods and protocols. Humana Press Inc., New York

    Google Scholar 

  • Yuille M, Illig T, Hveem K, Schmitz G, Hansen J, Neumaier M, Tybring G, Wichmann E, Ollier B (2010) Laboratory management of samples in biobanks: European consensus expert group report. Biopreserv Biobank 8(1):65–69

    Article  Google Scholar 

Download references

Acknowledgments

Research funded by the European Union Seventh Framework Programme [FP7/2007-2013] under grant agreement no 222916. Manfred Spraul and Hartmut Schäfer (Bruker BioSpin) are acknowledged for many discussions over the years. We thank Monica Biondi for her assistance in blood collection.

Author information

Authors and Affiliations

  1. Magnetic Resonance Center (CERM), University of Florence, Via L. Sacconi 6, 50019, Sesto Fiorentino, Italy

    Patrizia Bernini, Ivano Bertini, Claudio Luchinat & Paola Turano

  2. Department of Chemistry, University of Florence, Via della Lastruccia 3, 50019, Sesto Fiorentino, Italy

    Ivano Bertini, Claudio Luchinat & Paola Turano

  3. FiorGen Foundation, Via L. Sacconi 6, 50019, Sesto Fiorentino, Italy

    Patrizia Bernini, Paola Nincheri & Samuele Staderini

Authors
  1. Patrizia Bernini
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ivano Bertini
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Claudio Luchinat
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Paola Nincheri
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Samuele Staderini
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Paola Turano
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ivano Bertini.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 1016 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bernini, P., Bertini, I., Luchinat, C. et al. Standard operating procedures for pre-analytical handling of blood and urine for metabolomic studies and biobanks. J Biomol NMR 49, 231–243 (2011). https://doi.org/10.1007/s10858-011-9489-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10858-011-9489-1

Keywords

Search

Navigation