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Licensed Unlicensed Requires Authentication Published by De Gruyter January 21, 2022

Introduction of BD Vacutainer® Barricor™ tubes in clinical biobanking and application of amino acid and cytokine quality indicators to Barricor plasma

Nadine Knutti, Sophie Neugebauer, Franziska Scherr, Conny Mathay, Monica Marchese, Estelle Henry, Julia Palm, Fay Betsou and Michael Kiehntopf

Abstract

Objectives

The use of BD Vacutainer® Barricor™ tubes (BAR) can reduce turnaround time (TAT) and improve separation of plasma from cellular components using a specific mechanical separator. Concentrations of amino acids (AAs) and cytokines, known to be labile during pre-analytical time delays, were compared in heparin (BAR, BD Heparin standard tube [PST]), EDTA and serum gel tubes (SER) to validate previously identified quality indicators (QIs) in BAR.

Methods

Samples of healthy individuals (n=10) were collected in heparin, EDTA and SER tubes and exposed to varying pre- and post-centrifugation delays at room temperature (RT). Cytokines (interleukin [IL]-8, IL-16 and sCD40L) were analyzed by enzyme-linked immunosorbent assay (ELISA) and AAs were characterized by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS).

Results

All QIs, AAs/AA ratio and cytokines increased during prolonged blood storage in heparin plasma (PST, BAR) and SER tubes. Comparison of 53 h/1 h pre-centrifugation delay resulted in an increase in taurine (Tau) and glutamic acid (Glu) concentrations by more than three times, soluble CD40L increased by 13.6, 9.2 and 4.3 fold in PST, BAR-CTRL and BAR-FAST, and IL-8 increased even more by 112.8 (PST), 266.1 (BAR-CTRL), 268.1 (BAR-FAST) and 70.0 (SER) fold, respectively. Overall, compared to prolonged blood storage, effects of post-centrifugation delays were less pronounced in all tested materials.

Conclusions

BAR tubes are compatible with the use of several established QIs and can therefore be used in clinical biobanking to reduce pre-analytical TAT without compromising QIs and thus pre-analytical sample quality analysis.


Corresponding author: Dr. Nadine Knutti, Institute of Clinical Chemistry and Laboratory Diagnostics, Jena University Hospital, Am Klinikum 1, 07747 Jena, Germany, Phone: +49 (3641) 9 325147, Fax: +49 (3641) 9 325012, E-mail:

Funding source: BMBF

Award Identifier / Grant number: 01EK1505B

Acknowledgments

We thank Kerstin Stein for her support in sample collection and AA analysis at the Institute of Clinical Chemistry and Laboratory Diagnostics and the Integrated Biobank in Jena (IBBJ) for excellent technical assistance in sample collection, transport and storage.

  1. Research funding: The study was funded by the BMBF (01EK1505B). The funding organization played no role in the study design, collection, analysis and interpretation of data, in the writing of the article or in the decision to submit the article for publication.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: Authors state no conflict of interest.

  4. Informed consent: Informed consent was obtained from all individuals included in this study.

  5. Ethical approval: Human sample collections of the study followed all relevant national regulations, institutional policies and have been approved by the Ethics Committee of the University Hospital Jena and the CNER, Comité National d’Ethique de Recherche Luxembourg.

References

1. Bowen, RA, Hortin, GL, Csako, G, Otanez, OH, Remaley, AT. Impact of blood collection devices on clinical chemistry assays. Clin Biochem 2010;43:4–25. https://doi.org/10.1016/j.clinbiochem.2009.10.001.Search in Google Scholar

2. Lesche, D, Geyer, R, Lienhard, D, Nakas, CT, Diserens, G, Vermathen, P, et al.. Does centrifugation matter? Centrifugal force and spinning time alter the plasma metabolome. Metabolomics 2016;12:159. https://doi.org/10.1007/s11306-016-1109-3.Search in Google Scholar

3. Lippi, G, von Meyer, A, Cadamuro, J, Simundic, AM. Blood sample quality. Diagnosis (Berl) 2019;6:25–31. https://doi.org/10.1515/dx-2018-0018.Search in Google Scholar

4. Holland, NT, Smith, MT, Eskenazi, B, Bastaki, M. Biological sample collection and processing for molecular epidemiological studies. Mutat Res 2003;543:217–34. https://doi.org/10.1016/s1383-5742(02)00090-x.Search in Google Scholar

5. Lehmann, S, Guadagni, F, Moore, H, Ashton, G, Barnes, M, Benson, E, et al.. Standard preanalytical coding for biospecimens: review and implementation of the Sample PREanalytical Code (SPREC). Biopreserv Biobanking 2012;10:366–74. https://doi.org/10.1089/bio.2012.0012.Search in Google Scholar

6. Riondino, S, Ferroni, P, Spila, A, Alessandroni, J, D’Alessandro, R, Formica, V, et al.. Ensuring sample quality for biomarker discovery studies - use of ICT tools to trace biosample life-cycle. Cancer Genomics Proteomics 2015;12:291–9.Search in Google Scholar

7. Betsou, F, Bulla, A, Cho, SY, Clements, J, Chuaqui, R, Coppola, D, et al.. Assays for qualification and quality stratification of clinical biospecimens used in research: a technical report from the ISBER Biospecimen Science Working Group. Biopreserv Biobanking 2016;14:398–409. https://doi.org/10.1089/bio.2016.0018.Search in Google Scholar

8. Betsou, F. Quality assurance and quality control in biobanking. In: Hainaut, P, Vaught, J, Zatloukal, K, Pasterk, M, editors. Biobanking of human biospecimens, 1st ed Cham: Springer; 2017:23–49 pp.10.1007/978-3-319-55120-3_2Search in Google Scholar

9. Anton, G, Wilson, R, Yu, ZH, Prehn, C, Zukunft, S, Adamski, J, et al.. Pre-analytical sample quality: metabolite ratios as an intrinsic marker for prolonged room temperature exposure of serum samples. PLoS One 2015;10:e0121495. https://doi.org/10.1371/journal.pone.0121495.Search in Google Scholar

10. Cao, Z, Kamlage, B, Wagner-Golbs, A, Maisha, M, Sun, J, Schnackenberg, LK, et al.. An integrated analysis of metabolites, peptides, and inflammation biomarkers for assessment of preanalytical variability of human plasma. J Proteome Res 2019;18:2411–21. https://doi.org/10.1021/acs.jproteome.8b00903.Search in Google Scholar

11. Kamlage, B, Neuber, S, Bethan, B, Gonzalez Maldonado, S, Wagner-Golbs, A, Peter, E, et al.. Impact of prolonged blood incubation and extended serum storage at room temperature on the human serum metabolome. Metabolites 2018;8. https://doi.org/10.3390/metabo8010006.Search in Google Scholar

12. Findeisen, P, Hemanna, S, Maharjan, RS, Mindt, S, Costina, V, Hofheinz, R, et al.. Mass spectrometry based analytical quality assessment of serum and plasma specimens with patterns of endo- and exogenous peptides. Clin Chem Lab Med 2019;57:668–78. https://doi.org/10.1515/cclm-2018-0811.Search in Google Scholar

13. Kamlage, B, Maldonado, SG, Bethan, B, Peter, E, Schmitz, O, Liebenberg, V, et al.. Quality markers addressing preanalytical variations of blood and plasma processing identified by broad and targeted metabolite profiling. Clin Chem 2014;60:399–412. https://doi.org/10.1373/clinchem.2013.211979.Search in Google Scholar

14. Kofanova, O, Henry, E, Aguilar Quesada, R, Bulla, A, Navarro Linares, H, Lescuyer, P, et al.. IL8 and IL16 levels indicate serum and plasma quality. Clin Chem Lab Med 2018;56:1054–62. https://doi.org/10.1515/cclm-2017-1047.Search in Google Scholar

15. Schwarz, N, Knutti, N, Rose, M, Neugebauer, S, Geiger, J, Jahns, R, et al.. Quality assessment of the preanalytical workflow in liquid biobanking: taurine as a serum-specific quality indicator for preanalytical process variations. Biopreserv Biobanking 2019;17:458–67. https://doi.org/10.1089/bio.2019.0004.Search in Google Scholar

16. Nuttall, KL, Chen, M, Komaromy-Hiller, G. Delayed separation and the plasma amino acids arginine and ornithine. Ann Clin Lab Sci 1998;28:354–9.Search in Google Scholar

17. Jain, M, Kennedy, AD, Elsea, SH, Miller, MJ. Analytes related to erythrocyte metabolism are reliable biomarkers for preanalytical error due to delayed plasma processing in metabolomics studies. Clin Chim Acta 2017;466:105–11. https://doi.org/10.1016/j.cca.2017.01.005.Search in Google Scholar

18. Lengelle, J, Panopoulos, E, Betsou, F. Soluble CD40 ligand as a biomarker for storage-related preanalytic variations of human serum. Cytokine 2008;44:275–82. https://doi.org/10.1016/j.cyto.2008.08.010.Search in Google Scholar

19. Drake, SK, Bowen, RA, Remaley, AT, Hortin, GL. Potential interferences from blood collection tubes in mass spectrometric analyses of serum polypeptides. Clin Chem 2004;50:2398–401. https://doi.org/10.1373/clinchem.2004.040303.Search in Google Scholar

20. Karppi, J, Akerman, KK, Parviainen, M. Suitability of collection tubes with separator gels for collecting and storing blood samples for therapeutic drug monitoring (TDM). Clin Chem Lab Med 2000;38:313–20. https://doi.org/10.1515/CCLM.2000.045.Search in Google Scholar

21. Preanalytical systems. BD life sciences product catalogue: Becton. Dickinson and Company: Heidelberg; 2018.Search in Google Scholar

22. Ramakers, C, Meyer, B, Yang, W, Plokhoy, E, Xiong, Y, Church, S, et al.. Switching from serum to plasma: implementation of BD Vacutainer® Barricor Plasma Blood Collection Tubes improves sample quality and laboratory turnaround time. Pract Lab Med 2020;18:e00149. https://doi.org/10.1016/j.plabm.2019.e00149.Search in Google Scholar

23. Raizman, JE, Goudreau, BL, Fuzery, AK, Cembrowski, GS. Barricor blood collection tubes are equivalent to PST for a variety of chemistry and immunoassay analytes except for lactate dehydrogenase. Clin Chim Acta 2019;496:18–24. https://doi.org/10.1016/j.cca.2019.06.013.Search in Google Scholar

24. Dupuy, AM, Badiou, S, Daubin, D, Bargnoux, AS, Magnan, C, Klouche, K, et al.. Comparison of Barricor (TM) vs. lithium heparin tubes for selected routine biochemical analytes and evaluation of post centrifugation stability. Biochem Med 2018;28. https://doi.org/10.11613/BM.2018.020902.Search in Google Scholar

25. Gawria, G, Tillmar, L, Landberg, E. A comparison of stability of chemical analytes in plasma from the BD Vacutainer® Barricor tube with mechanical separator versus tubes containing gel separator. J Clin Lab Anal 2020;34:e23060. https://doi.org/10.1002/jcla.23060.Search in Google Scholar

26. Balbas, LA, Amaro, MS, Rioja, RG, Martin, MJ, Soto, AB. Stability of plasma electrolytes in Barricor and PST II tubes under different storage conditions. Biochem Med 2017;27:225–30. https://doi.org/10.11613/bm.2017.024.Search in Google Scholar

27. Cadamuro, J, Mrazek, C, Leichtle, AB, Kipman, U, Felder, TK, Wiedemann, H, et al.. Influence of centrifugation conditions on the results of 77 routine clinical chemistry analytes using standard vacuum blood collection tubes and the new BD-Barricor tubes. Biochem Med 2018;28:010704. https://doi.org/10.11613/BM.2018.010704.Search in Google Scholar

28. Benjamini, Y, Hochberg, Y. Controlling the false discovery rate - a practical and powerful approach to multiple testing. J Roy Stat Soc B 1995;57:289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x.Search in Google Scholar

29. Tukey, JW. Comparing individual means in the analysis of variance. Biometrics 1949;5:99–114. https://doi.org/10.2307/3001913.Search in Google Scholar

30. Satterthwaite, FE. An approximate distribution of estimates of variance components. Biometrics Bull 1946;2:110–4. https://doi.org/10.2307/3002019.Search in Google Scholar

31. Ruiz-Godoy, L, Enriquez-Carcamo, V, Suarez-Roa, L, Lopez-Castro, ML, Santamaria, A, Orozco-Morales, M, et al.. Identification of specific pre-analytical quality control markers in plasma and serum samples. Anal Methods 2019;11:2259–71. https://doi.org/10.1039/c9ay00131j.Search in Google Scholar

32. Paglia, G, Del Greco, FM, Sigurdsson, BB, Rainer, J, Volani, C, Hicks, AA, et al.. Influence of collection tubes during quantitative targeted metabolomics studies in human blood samples. Clin Chim Acta 2018;486:320–8. https://doi.org/10.1016/j.cca.2018.08.014.Search in Google Scholar

33. Daniels, JR, Cao, Z, Maisha, M, Schnackenberg, LK, Sun, J, Pence, L, et al.. Stability of the human plasma proteome to pre-analytical variability as assessed by an aptamer-based approach. J Proteome Res 2019;18:3661–70. https://doi.org/10.1021/acs.jproteome.9b00320.Search in Google Scholar

34. Yu, Z, Kastenmuller, G, He, Y, Belcredi, P, Moller, G, Prehn, C, et al.. Differences between human plasma and serum metabolite profiles. PLoS One 2011;6:e21230. https://doi.org/10.1371/journal.pone.0021230.Search in Google Scholar

35. Holden, JT, United States, Office of Naval Research; City of Hope National Medical Center (U.S.). Amino acid pools: distribution, formation and function of free amino acids; proceedings (Soupart, P: “Free amino acids of blood and urine in the human”). Amsterdam, New York: Elsevier Pub. Co. Sole Distributor for the U.S., American Elsevier Pub. Co.; 1962, xi:815 p.Search in Google Scholar

36. Tunnicliff, G. Amino acid transport by human erythrocyte membranes. Comp Biochem Physiol A Comp Physiol 1994;108:471–8. https://doi.org/10.1016/0300-9629(94)90329-8.Search in Google Scholar

37. Canepa, A, Filho, JC, Gutierrez, A, Carrea, A, Forsberg, AM, Nilsson, E, et al.. Free amino acids in plasma, red blood cells, polymorphonuclear leukocytes, and muscle in normal and uraemic children. Nephrol Dial Transplant 2002;17:413–21. https://doi.org/10.1093/ndt/17.3.413.Search in Google Scholar

38. Fukuda, K, Hirai, Y, Yoshida, H, Nakajima, T, Usui, T. Free amino acid content of lymphocytes nd granulocytes compared. Clin Chem 1982;28:1758–61. https://doi.org/10.1093/clinchem/28.8.1758.Search in Google Scholar

39. Stein, WH, Moore, S. The free amino acids of human blood plasma. J Biol Chem 1954;211:915–26. https://doi.org/10.1016/s0021-9258(18)71179-4.Search in Google Scholar

40. Sahai, S. Glutaminase in human platelets. Clin Chim Acta 1983;127:197–203. https://doi.org/10.1016/s0009-8981(83)80004-7.Search in Google Scholar

41. Spector, EB, Rice, SC, Kern, RM, Hendrickson, R, Cederbaum, SD. Comparison of arginase activity in red blood cells of lower mammals, primates, and man: evolution to high activity in primates. Am J Hum Genet 1985;37:1138–45.Search in Google Scholar

42. Caldwell, RW, Rodriguez, PC, Toque, HA, Narayanan, SP, Caldwell, RB. Arginase: a multifaceted enzyme important in health and disease. Physiol Rev 2018;98:641–65. https://doi.org/10.1152/physrev.00037.2016.Search in Google Scholar

43. Gao, C, Boylan, B, Fang, J, Wilcox, DA, Newman, DK, Newman, PJ. Heparin promotes platelet responsiveness by potentiating alphaIIbbeta3-mediated outside-in signaling. Blood 2011;117:4946–52. https://doi.org/10.1182/blood-2010-09-307751.Search in Google Scholar

44. Ahtee, L, Boullin, DJ, Paasonen, MK. Transport of taurine by normal human blood platelets. Br J Pharmacol 1974;52:245–51. https://doi.org/10.1111/j.1476-5381.1974.tb09707.x.Search in Google Scholar

45. Rendu, F, Brohard-Bohn, B. The platelet release reaction: granules’ constituents, secretion and functions. Platelets 2001;12:261–73. https://doi.org/10.1080/09537100120068170.Search in Google Scholar

46. Lee, JE, Kim, JW, Han, BG, Shin, SY. Impact of whole-blood processing conditions on plasma and serum concentrations of cytokines. Biopreserv Biobanking 2016;14:51–5. https://doi.org/10.1089/bio.2015.0059.Search in Google Scholar

47. Wu, DM, Zhang, Y, Parada, NA, Kornfeld, H, Nicoll, J, Center, DM, et al.. Processing and release of IL-16 from CD4+ but not CD8+ T cells is activation dependent. J Immunol 1999;162:1287–93.Search in Google Scholar

48. Vanichakarn, P, Blair, P, Wu, C, Freedman, JE, Chakrabarti, S. Neutrophil CD40 enhances platelet-mediated inflammation. Thromb Res 2008;122:346–58. https://doi.org/10.1016/j.thromres.2007.12.019.Search in Google Scholar

49. Sokol, CL, Luster, AD. The chemokine system in innate immunity. Cold Spring Harbor Perspect Biol 2015;7. https://doi.org/10.1101/cshperspect.a016303.Search in Google Scholar

50. Ribeiro, LS, Migliari Branco, L, Franklin, BS. Regulation of innate immune responses by platelets. Front Immunol 2019;10:1320. https://doi.org/10.3389/fimmu.2019.01320.Search in Google Scholar

51. Mason, PJ, Chakrabarti, S, Albers, AA, Rex, S, Vitseva, O, Varghese, S, et al.. Plasma, serum, and platelet expression of CD40 ligand in adults with cardiovascular disease. Am J Cardiol 2005;96:1365–9. https://doi.org/10.1016/j.amjcard.2005.07.039.Search in Google Scholar

52. Takehana, S, Yoshida, H, Ozawa, S, Yamazaki, J, Shimbo, K, Nakayama, A, et al.. The effects of pre-analysis sample handling on human plasma amino acid concentrations. Clin Chim Acta 2016;455:68–74. https://doi.org/10.1016/j.cca.2016.01.026.Search in Google Scholar

53. Padoan, A, Zaninotto, M, Piva, E, Sciacovelli, L, Aita, A, Tasinato, A, et al.. Quality of plasma samples and BD Vacutainer Barricor tubes: effects of centrifugation. Clin Chim Acta 2018;483:271–4. https://doi.org/10.1016/j.cca.2018.05.018.Search in Google Scholar

54. Gremmel, T, Frelinger, AL3rd, Michelson, AD. Platelet physiology. Semin Thromb Hemost 2016;42:191–204. https://doi.org/10.1055/s-0035-1564835.Search in Google Scholar

55. Kristensen, SD, Wurtz, M, Grove, EL, De Caterina, R, Huber, K, Moliterno, DJ, et al.. Contemporary use of glycoprotein IIb/IIIa inhibitors. Thromb Haemostasis 2012;107:215–24. https://doi.org/10.1160/TH11-07-0468.Search in Google Scholar

56. Ammerlaan, W, Trezzi, JP, Lescuyer, P, Mathay, C, Hiller, K, Betsou, F. Method validation for preparing serum and plasma samples from human blood for downstream proteomic, metabolomic, and circulating nucleic acid-based applications. Biopreserv Biobanking 2014;12:269–80. https://doi.org/10.1089/bio.2014.0003.Search in Google Scholar


Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2021-0899).


Received: 2021-08-12
Accepted: 2022-01-10
Published Online: 2022-01-21
Published in Print: 2022-04-26

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