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

J Mol Med (Berl). 2007 Jun;85(6):613-21. doi: 10.1007/s00109-007-0157-6. Epub 2007 Feb 23.


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-gamma, 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, Fcgamma 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Biomarkers / metabolism
  • Case-Control Studies
  • Discriminant Analysis
  • Female
  • Gene Expression Profiling
  • Health
  • Humans
  • Immunity, Innate / genetics
  • Male
  • Monocytes / metabolism
  • Monocytes / microbiology
  • Mycobacterium tuberculosis / physiology*
  • Receptors, IgG / metabolism
  • Tissue Donors
  • Transcription, Genetic
  • Tuberculosis / genetics*
  • Up-Regulation / genetics


  • Biomarkers
  • Receptors, IgG