Original Article

Journal of Molecular Medicine

, Volume 85, Issue 6, pp 613-621

First online:

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

  • Marc JacobsenAffiliated withDepartment of Immunology, Max Planck Institute for Infection Biology Email author 
  • , Dirk RepsilberAffiliated withInstitute for Medical Biometry and Statistics, University at LübeckInstitute for Biochemistry and Biology, University Potsdam
  • , Andrea GutschmidtAffiliated withDepartment of Immunology, Max Planck Institute for Infection Biology
  • , Albert NeherAffiliated withAsklepios Center for Respiratory Medicine and Thoracic Surgery
  • , Knut FeldmannAffiliated withAsklepios Center for Respiratory Medicine and Thoracic Surgery
  • , Hans J. MollenkopfAffiliated withMicroarray Core Facilities, Max Planck Institute for Infection Biology
  • , Andreas ZieglerAffiliated withInstitute for Medical Biometry and Statistics, University at Lübeck
  • , Stefan H. E. KaufmannAffiliated withDepartment of Immunology, Max Planck Institute for Infection Biology

Rent the article at a discount

Rent now

* Final gross prices may vary according to local VAT.

Get Access

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.

Keywords

Mycobacterium tuberculosis Tuberculosis Biomarkers