Biological variation of immunological blood biomarkers in healthy individuals and quality goals for biomarker tests

Najib Aziz, Roger Detels, Joshua J Quint, David Gjertson, Timothy Ryner, Anthony W Butch, Najib Aziz, Roger Detels, Joshua J Quint, David Gjertson, Timothy Ryner, Anthony W Butch

Abstract

Background: Cytokines, chemokines, adipocytokines, soluble cell receptors, and immune activation markers play an important role in immune responsiveness and can provide prognostic value since they reflect underlying conditions and disease states. This study was undertaken to investigate the components of biological variation for various laboratory tests of blood immunological biomarkers.

Results: Estimates of intra-individual coefficient of variation (CVI) and inter-individual coefficient of variation (CVG) were examined for blood immunological biomarkers. Biomarkers with CVI < 10% for both genders were CD3, CD4, and CD8 T-cells, serum levels of soluble cluster of differentiation 14 (sCD14), sCD163, and soluble glycoprotein 130 (sgp130). The CVI for serum levels of adiponectin, interleukin-1 receptor antagonist (IL-1Ra), macrophage inflammatory protein 1 beta (MIP-1β), soluble CD40 Ligand (sCD40L), soluble interleukin-2 receptor alpha (sIL-2Rα), soluble interleukin-6 receptor (sIL-6R), soluble tumor necrosis factor receptor II (sTNF-RII), and tumor necrosis factor alpha (TNF-α) were between 11 and 20%. Biomarkers with CVG < 20% were CD3 T-cell, and serum concentrations of sCD14, sCD40L, and sgp130. The biomarkers with CVG > 40% were adiponectin, IL-1ra, leptin, MIP-1β, sCD163, and sIL-2Rα.

Conclusion: The biological variations of biomarkers have important monitoring value for longitudinal investigation and are essential for quality specification of tests that are performed in the laboratory. The CVI was relatively small while CVG was comparatively large and mean values of each biomarker vary between subjects. The individuality of biomarkers significantly influences reference interval values. A majority of the biomarkers in this study had strong individuality and the result of each biomarker should be cautiously interpreted if using established reference interval values. Comparison of a patient's test result with previous ones may be more useful than the usage of conventional reference values.

Keywords: Chemokine; Cytokines; Immune activation; Interleukin; Soluble markers.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Mean (filled circle) and absolute range (error bar) for each subject (n=12) over six weeks, for serum level of IL-1β (a), IL-6 (b), IFN-γ (c), IL-1Ra (d), TNF-α (e), IL-8 (f), MIP-1β (g), RANTES (h), and sCD14 (i)
Fig. 2
Fig. 2
Mean (fialled circle) and absolute range (error bar) for each subject (n=12) over six weeks, for serum level of sCD40L (a), sCD163 (b), sIL-6R (c), sIL-2Rα (d), sTNF-RII (e), sgp130 (f), Adiponectin (g), Leptin (h), and Neopterin (i)
Fig. 3
Fig. 3
Mean (filled circle) and percentage range (error bar) for each subject (n=12) over six weeks, for helper T-cell (a), Cytotoxic T-cell (b), B-cell (c), and NK cell (d)

References

    1. Edlefsen KL, Martinez-Maza O, Madeleine MM, Magpantay L, Mirick DK, Kopecky KJ, La Croix AZ, De Roos AJ. Cytokines in serum in relation to future non-Hodgkin lymphoma risk: evidence for associations by histologic subtype. Int J Cancer. 2014;135(4):913–922. doi: 10.1002/ijc.28724.
    1. Fahey J. Cytokines, plasma immune activation markers, and clinically relevant surrogate markers in human immunodeficiency virus infection. Clin Diagn Lab Immunol. 1998;5(5):597–603.
    1. French MA, Cozzi-Lepri A, Arduino RC, Johnson M, Achhra AC, Landay A. Plasma levels of cytokines and chemokines and the risk of mortality in HIV-infected individuals: a case-control analysis nested in a large clinical trial. AIDS. 2015;29(7):847–851. doi: 10.1097/QAD.0000000000000618.
    1. Han J, Wang Y, Gan X, Song J, Sun P, Dong XP. Serum cytokine profiles of children with human enterovirus 71-associated hand, foot, and mouth disease. J Med Virol. 2014;86(8):1377–1385. doi: 10.1002/jmv.23929.
    1. Ndumbi P, Gilbert L, Tsoukas CM. Comprehensive Evaluation of the Immune Risk Phenotype in Successfully Treated HIV-Infected Individuals. PLoS One. 2015;10(2):e0117039. doi: 10.1371/journal.pone.0117039.
    1. Biancotto A, Wank A, Perl S, Cook W, Olnes MJ, Dagur PK, Fuchs JC, Langweiler M, Wang E, McCoy JP. Baseline levels and temporal stability of 27 multiplexed serum cytokine concentrations in healthy subjects. PLoS One. 2013;8(12):e76091. doi: 10.1371/journal.pone.0076091.
    1. Epstein MM, Breen EC, Magpantay L, Detels R, Lepone L, Penugonda S, Bream JH, Jacobson LP, Martinez-Maza O, Brimann BM. Temporal stability of serum concentrations of cytokines and soluble receptors measure across two years in low-risk HIV seronegative men. Cancer Epidemiol Biomark Prev. 2013;22(11):2009–2015. doi: 10.1158/1055-9965.EPI-13-0379.
    1. Manolio T. Novel risk markers and clinical practice. N Engl J Med. 2003;349(17):1587–1589. doi: 10.1056/NEJMp038136.
    1. Fraser CG, editor. Biological variation: from principles to practice. Washington, DC: AACC Press; 2001.
    1. Ricos V, Alvarez V, Cava F, Garcia-Lario JV, Hernández A, Jiménez CV, Minchinela J, Perich C, Simón M. Current databases on biological variation: pros, cons and progress. Scand J Clin Lab Invest. 1999;59:491–500. doi: 10.1080/00365519950185229.
    1. Harris EK. Statistical principles underlying analytic goal-setting in clinical chemistry. Am J Clin Pathol. 1979;72:374–382.
    1. Harris EK. Distinguishing physiologic variation from analytic variation. J Chronic Disease. 1970;23:469–480. doi: 10.1016/0021-9681(70)90055-X.
    1. Ford RP, Mitchell PE, Fraser CG. Desirable performance characteristics utilkity of immunoglobulin and light-chain assays derived from data on biological variation. Clin Chem. 1988;34(9):1733–1736.
    1. Shand B, Elder P, Scott R, Frampton C, Willis J. Biovariablity of plasma adiponectin. Clin Chem Lab Med. 2006;44:1264–1268. doi: 10.1515/CCLM.2006.227.
    1. González C, Cava F, Ayllón A, Guevara P, Navajo JA, González-Buitrago JM. Biological variation of interleukin-1beta, interleukin-8 and tumor necrosis factor-alpha in serum of healthy individuals. Clin Chem Lab Med. 2001;39(9):836–841. doi: 10.1515/CCLM.2001.139.
    1. Cava F, González C, Pascual MJ, Navajo JA, González-Buitrago JM. Biological variation of interleukin 6 (IL-6) and soluble interleukin 2 receptor (sIL2R) in serum of healthy individuals. Cytokine. 2000;12(9):1423–1425. doi: 10.1006/cyto.2000.0714.
    1. Møller HJ, Petersen PH, Rejnmark L, Moestrup SK. Biological variation of soluble CD163. Scand J Clin Lab Invest. 2003;63(1):15–21. doi: 10.1080/00365510310000439.
    1. Jilma B, Dirnberger E, Löscher I, Rumplmayr A, Hildebrandt J, Eichler HG, Kapiotis S, Wagner OF. Menstrual cycle-associated changes in blood levels of interleukin-6, alpha1 acid glycoprotein, and C-reactive protein. J Lab Clin Med. 1997;130(1):69–75. doi: 10.1016/S0022-2143(97)90060-3.
    1. Brännström M, Fridén BE, Jasper M, Norman RJ. Variations in peripheral blood levels of immunoreactive tumor necrosis factor alpha (TNFalpha) throughout the menstrual cycle and secretion of TNFalpha from the human corpus luteum. Eur J Obstet Gynecol Reprod Biol. 1999;83(2):213–217. doi: 10.1016/S0301-2115(99)00003-2.
    1. van den Heuvel MJ, Horrocks J, Bashar S, Taylor S, Burke S, Hatta K, Lewis JE, Croy BA. Menstrual cycle hormones induce changes in functional interactions between lymphocytes and decidual vascular endothelial cells. J Clin Endocrinol Metab. 2005;90(5):2835–2842. doi: 10.1210/jc.2004-1742.
    1. Aziz N, Nishanian P, Taylor JM, Mitsuyasu RT, Jacobson JM, Dezube BJ, Lederman MM, Detels R, Fahey JL. Stability of plasma levels of cytokines and soluble activation markers in patients with human immunodeficiency virus infection. J Infect Dis. 1999;179(4):843–848. doi: 10.1086/314673.
    1. Han Y, Lassen K, Monie D, Sedaghat AR, Shimoji S, Liu X, Pierson TC, Margolick JB, Siliciano RF, Siliciano JD. Resting CD4+ T cells from human immunodeficiency virus type 1 (HIV-1)-infected individuals carry integrated HIV-1 genomes within. Actively transcribed host genes. J Virol. 2004;78(12):6122–6133. doi: 10.1128/JVI.78.12.6122-6133.2004.
    1. Kornbluth RS. The emerging role of CD40 ligand in HIV infection. J Leukoc Biol. 2000;68(3):373–382.
    1. Ricós C, Álvarez V, Perich C, Fernández-Calle P, Minchinela J, Cava F, Biosca C, Boned B, Domenech M, Garcia-Lario JV, Simon M, Frenadez PF, Diaz-Garzon J, Gonzalez-Lao E. Rationale for using data on biological variation. Clin Chem Lab Med. 2015;53(6):863–870. doi: 10.1515/cclm-2014-1142.
    1. Ross SM, Fraser CG. Biological variation of cardiac markers: analytical and clinical considerations. Ann Clin Biochem. 1998;30:80–84. doi: 10.1177/000456329803500110.
    1. Fraser CG, Harris EK. Generation and application of data on biological variation in clinical chemistry. Crit Rev Clin Lab Sci. 1989;27(5):409–437. doi: 10.3109/10408368909106595.
    1. Ricós C, Jiménez CV, Hernández A, Simón M, Perich C, Alvarez V, Minchinela J, Macia M. Biological variation in urine samples used for analyte measurements. Clin Chem. 1994;40(3):472–477.
    1. Schnizlein-Bick C, Mandy F, O’Gorman M, Paxton H, Nicholson J, Hultin L, Gelman R, Wilkening C, Livnat D. Use of CD45 gating in the three and four-color flow cytometric immunophenotyping: Guideline from the National Institute of Allergy and infectious Disease, Division of AIDS. Cytometry. 2002;50:46–52. doi: 10.1002/cyto.10073.
    1. Harris EK, Boyd JC. Comparison of within-subject and among-subjects variance; Statistical Bases of Reference Values in Laboratory Medicine. New York, N.Y: Marcel Dekker, Inc; 1995. pp. 187–221.
    1. Young DS, Bermes EW., Jr . TIETZ Textbook of Clinical Chemistry and Molecular Diagnostics 4th Edition. Philadelphia: WB Saunders Co; 2006. Preanalytical Variables and Biological Variation Chapter 17; p. 470.
    1. Fraser CG, Hyltoft Petersen P. Desirable standards for laboratory tests if they are to fulfill medical needs. Clin. Chem. 1993;39(7):1447–1455.

Source: PubMed

Sponsor e collaboratori

Condizioni mediche

Interventi farmacologici

3
Sottoscrivi