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Candidate biomarkers for discrimination between infection and disease caused by Mycobacterium tuberculosis

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Abstract

Infection with Mycobacterium tuberculosis is controlled by an efficacious immune response in about 90% of infected individuals who do not develop disease. Although essential mediators of protection, e.g., interferon-γ, have been identified, these factors are insufficient to predict the outcome of M. tuberculosis infection. As a first step to determine additional biomarkers, we compared gene expression profiles of peripheral blood mononuclear cells from tuberculosis patients and M. tuberculosis-infected healthy donors by microarray analysis. Differentially expressed candidate genes were predominantly derived from monocytes and comprised molecules involved in the antimicrobial defense, inflammation, chemotaxis, and intracellular trafficking. We verified differential expression for alpha-defensin 1, alpha-defensin 4, lactoferrin, Fcγ receptor 1A (cluster of differentiation 64 [CD64]), bactericidal permeability-increasing protein, and formyl peptide receptor 1 by quantitative polymerase chain reaction analysis. Moreover, we identified increased protein expression of CD64 on monocytes from tuberculosis patients. Candidate biomarkers were then assessed for optimal study group discrimination. Using a linear discriminant analysis, a minimal group of genes comprising lactoferrin, CD64, and the Ras-associated GTPase 33A was sufficient for classification of (1) tuberculosis patients, (2) M. tuberculosis-infected healthy donors, and (3) noninfected healthy donors.

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References

  1. Altman DG, Royston P (2000) What do we mean by validating a prognostic model? Stat Med 19:453–473

    Article  PubMed  CAS  Google Scholar 

  2. Beigier-Bompadre M, Barrionuevo P, Alves-Rosa F, Rubel CJ, Palermo MS, Isturiz MA (2001) N-formyl-methionyl-leucyl-phenylalanine inhibits both gamma interferon-and interleukin-10-induced expression of FcgammaRI on human monocytes. Clin Diagn Lab Immunol 8:402–408

    Article  PubMed  CAS  Google Scholar 

  3. Bennett L, Palucka AK, Arce E, Cantrell V, Borvak J, Banchereau J, Pascual V (2003) Interferon and granulopoiesis signatures in systemic lupus erythematosus blood. J Exp Med 197:711–723

    Article  PubMed  CAS  Google Scholar 

  4. Bomprezzi R, Ringner M, Kim S, Bittner ML, Khan J, Chen Y, Elkahloun A, Yu A, Bielekova B, Meltzer PS, Martin R, McFarland HF, Trent JM (2003) Gene expression profile in multiple sclerosis patients and healthy controls: identifying pathways relevant to disease. Hum Mol Genet 12:2191–2199

    Article  PubMed  CAS  Google Scholar 

  5. Bullinger L, Dohner K, Bair E, Frohling S, Schlenk RF, Tibshirani R, Dohner H, Pollack JR (2004) Use of gene-expression profiling to identify prognostic subclasses in adult acute myeloid leukemia. N Engl J Med 350:1605–1616

    Article  PubMed  CAS  Google Scholar 

  6. Chan YH (2005) Biostatistics 303. Discriminant analysis. Singap Med J 46:54–61, quiz 62

    CAS  Google Scholar 

  7. Chun T, Serbina NV, Nolt D, Wang B, Chiu NM, Flynn JL, Wang CR (2001) Induction of M3-restricted cytotoxic T lymphocyte responses by N-formylated peptides derived from Mycobacterium tuberculosis. J Exp Med 193:1213–1220

    Article  PubMed  CAS  Google Scholar 

  8. Flynn JL, Chan J (2001) Immunology of tuberculosis. Annu Rev Immunol 19:93–129

    Article  PubMed  CAS  Google Scholar 

  9. Jacobsen M, Repsilber D, Gutschmidt A, Neher A, Feldmann K, Mollenkopf HJ, Ziegler A, Kaufmann SH (2005) Ras-associated small GTPase 33A, a novel T cell factor, is downregulated in patients with tuberculosis. J Infect Dis 192:1211–1218

    Article  PubMed  CAS  Google Scholar 

  10. Jacobsen M, Schweer D, Ziegler A, Gaber R, Schock S, Schwinzer R, Wonigeit K, Lindert RB, Kantarci O, Schaefer-Klein J, Schipper HI, Oertel WH, Heidenreich F, Weinshenker BG, Sommer N, Hemmer B (2000) A point mutation in PTPRC is associated with the development of multiple sclerosis. Nat Genet 26:495–499

    Article  PubMed  CAS  Google Scholar 

  11. Juffermans NP, Verbon A, van Deventer SJ, Buurman WA, van Deutekom H, Speelman P, van der Poll T (1998) Serum concentrations of lipopolysaccharide activity-modulating proteins during tuberculosis. J Infect Dis 178:1839–1842

    Article  PubMed  CAS  Google Scholar 

  12. Kalita A, Verma I, Khuller GK (2004) Role of human neutrophil peptide-1 as a possible adjunct to antituberculosis chemotherapy. J Infect Dis 190:1476–1480

    Article  PubMed  CAS  Google Scholar 

  13. Kaufmann SH (2001) How can immunology contribute to the control of tuberculosis? Nat Rev Immunol 1:20–30

    Article  PubMed  CAS  Google Scholar 

  14. Kaufmann SH, McMichael AJ (2005) Annulling a dangerous liaison: vaccination strategies against AIDS and tuberculosis. Nat Med 11:S33–S44

    Article  PubMed  CAS  Google Scholar 

  15. Le Y, Murphy PM, Wang JM (2002) Formyl-peptide receptors revisited. Trends Immunol 23:541–548

    Article  PubMed  CAS  Google Scholar 

  16. Ochoa MT, Stenger S, Sieling PA, Thoma-Uszynski S, Sabet S, Cho S, Krensky AM, Rollinghoff M, Nunes Sarno E, Burdick AE, Rea TH, Modlin RL (2001) T-cell release of granulysin contributes to host defense in leprosy. Nat Med 7:174–179

    Article  PubMed  CAS  Google Scholar 

  17. Perussia B, Dayton ET, Lazarus R, Fanning V, Trinchieri G (1983) Immune interferon induces the receptor for monomeric IgG1 on human monocytic and myeloid cells. J Exp Med 158:1092–1113

    Article  PubMed  CAS  Google Scholar 

  18. Schaible UE, Collins HL, Priem F, Kaufmann SH (2002) Correction of the iron overload defect in beta-2-microglobulin knockout mice by lactoferrin abolishes their increased susceptibility to tuberculosis. J Exp Med 196:1507–1513

    Article  PubMed  CAS  Google Scholar 

  19. Sharma S, Verma I, Khuller GK (2000) Antibacterial activity of human neutrophil peptide-1 against Mycobacterium tuberculosis H37Rv: in vitro and ex vivo study. Eur Respir J 16:112–117

    Article  PubMed  CAS  Google Scholar 

  20. Shiloh MU, Nathan CF (2000) Reactive nitrogen intermediates and the pathogenesis of Salmonella and mycobacteria. Curr Opin Microbiol 3:35–42

    Article  PubMed  CAS  Google Scholar 

  21. Snyderman R, Pike MC (1984) Chemoattractant receptors on phagocytic cells. Annu Rev Immunol 2:257–281

    Article  PubMed  CAS  Google Scholar 

  22. Stenger S, Modlin RL (2002) Control of Mycobacterium tuberculosis through mammalian Toll-like receptors. Curr Opin Immunol 14:452–457

    Article  PubMed  CAS  Google Scholar 

  23. te Velde AA, de Waal Malefijt R, Huijbens RJ, de Vries JE, Figdor CG (1992) IL-10 stimulates monocyte Fc gamma R surface expression and cytotoxic activity. Distinct regulation of antibody-dependent cellular cytotoxicity by IFN-gamma, IL-4, and IL-10. J Immunol 149:4048–4052

    Google Scholar 

  24. Ting LM, Kim AC, Cattamanchi A, Ernst JD (1999) Mycobacterium tuberculosis inhibits IFN-gamma transcriptional responses without inhibiting activation of STAT1. J Immunol 163:3898–3906

    PubMed  CAS  Google Scholar 

  25. van de Winkel JG, Capel PJ (1993) Human IgG Fc receptor heterogeneity: molecular aspects and clinical implications. Immunol Today 14:215–221

    Article  PubMed  Google Scholar 

  26. Vanham G, Edmonds K, Qing L, Hom D, Toossi Z, Jones B, Daley CL, Huebner B, Kestens L, Gigase P, Ellner JJ (1996) Generalized immune activation in pulmonary tuberculosis: co-activation with HIV infection. Clin Exp Immunol 103:30–34

    Article  PubMed  CAS  Google Scholar 

  27. Via LE, Deretic D, Ulmer RJ, Hibler NS, Huber LA, Deretic V (1997) Arrest of mycobacterial phagosome maturation is caused by a block in vesicle fusion between stages controlled by rab5 and rab7. J Biol Chem 272:13326–13331

    Article  PubMed  CAS  Google Scholar 

  28. Ward PP, Uribe-Luna S, Conneely OM (2002) Lactoferrin and host defense. Biochem Cell Biol 80:95–102

    Article  PubMed  CAS  Google Scholar 

  29. Young PHWaSS (1993) Resampling-based multiple testing: examples and methods for p-value adjustment. Wiley

  30. Zerial M, McBride H (2001) Rab proteins as membrane organizers. Nat Rev Mol Cell Biol 2:107–117

    Article  PubMed  CAS  Google Scholar 

  31. Jacobsen M, Repsilber D, Gutschmidt A, Neher A, Feldmann K, Mollenkopf H-J, Kaufmann SHE, Ziegler A (2006) Deconfounding microarray analyses: independent measurements of cell type proportions used in a regression model to resolve tissue heterogeneity bias. Methods Inf Med 45:557–563

    PubMed  CAS  Google Scholar 

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Acknowledgments

This study was supported in part by the National Genome Research Network (Germany), the EU FP6 funded IP “TBVAC”, and Grand Challenge 6 of the Bill & Melinda Gates Foundation to S. H. E. Kaufmann and M. Jacobsen. H.-J. Mollenkopf and S. H. E. Kaufmann acknowledge additional funding by the European Fund for Regional Development/State of Berlin. The authors have no conflicting financial interests. We thank M. L. Grossman for carefully revising the manuscript.

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Author notes

  1. Dirk Repsilber

    Present address: Institute for Biochemistry and Biology, University Potsdam, 14476, Potsdam-Golm, Germany

Authors and Affiliations

  1. Department of Immunology, Max Planck Institute for Infection Biology, Chariteplatz 1, 10117, Berlin, Germany

    Marc Jacobsen, Andrea Gutschmidt & Stefan H. E. Kaufmann

  2. Institute for Medical Biometry and Statistics, University at Lübeck, 23538, Lübeck, Germany

    Dirk Repsilber & Andreas Ziegler

  3. Asklepios Center for Respiratory Medicine and Thoracic Surgery, 82131, Munich-Gauting, Germany

    Albert Neher & Knut Feldmann

  4. Microarray Core Facilities, Max Planck Institute for Infection Biology, 10117, Berlin, Germany

    Hans J. Mollenkopf

Authors
  1. Marc Jacobsen
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  8. Stefan H. E. Kaufmann
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Corresponding author

Correspondence to Marc Jacobsen.

Electronic supplementary material

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Supplementary Table S2

Top 95 candidate genes from microarray comparisons between TB patients and latently M. tuberculosis infected healthy contacts (XLS 84 kb)

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Jacobsen, M., Repsilber, D., Gutschmidt, A. et al. Candidate biomarkers for discrimination between infection and disease caused by Mycobacterium tuberculosis . J Mol Med 85, 613–621 (2007). https://doi.org/10.1007/s00109-007-0157-6

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  • DOI: https://doi.org/10.1007/s00109-007-0157-6

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