Identification of a 251 gene expression signature that can accurately detect M. tuberculosis in patients with and without HIV co-infection

PLoS One. 2014 Feb 25;9(2):e89925. doi: 10.1371/journal.pone.0089925. eCollection 2014.

Abstract

Background: Co-infection with tuberculosis (TB) is the leading cause of death in HIV-infected individuals. However, diagnosis of TB, especially in the presence of an HIV co-infection, can be limiting due to the high inaccuracy associated with the use of conventional diagnostic methods. Here we report a gene signature that can identify a tuberculosis infection in patients co-infected with HIV as well as in the absence of HIV.

Methods: We analyzed global gene expression data from peripheral blood mononuclear cell (PBMC) samples of patients that were either mono-infected with HIV or co-infected with HIV/TB and used support vector machines to identify a gene signature that can distinguish between the two classes. We then validated our results using publically available gene expression data from patients mono-infected with TB.

Results: Our analysis successfully identified a 251-gene signature that accurately distinguishes patients co-infected with HIV/TB from those infected with HIV only, with an overall accuracy of 81.4% (sensitivity = 76.2%, specificity = 86.4%). Furthermore, we show that our 251-gene signature can also accurately distinguish patients with active TB in the absence of an HIV infection from both patients with a latent TB infection and healthy controls (88.9-94.7% accuracy; 69.2-90% sensitivity and 90.3-100% specificity). We also demonstrate that the expression levels of the 251-gene signature diminish as a correlate of the length of TB treatment.

Conclusions: A 251-gene signature is described to (a) detect TB in the presence or absence of an HIV co-infection, and (b) assess response to treatment following anti-TB therapy.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Coinfection / microbiology*
  • Coinfection / virology*
  • Female
  • Gene Expression Profiling
  • HIV Infections / microbiology*
  • Humans
  • Leukocytes, Mononuclear / metabolism
  • Male
  • Mycobacterium tuberculosis / genetics*
  • Sensitivity and Specificity
  • South Africa
  • Support Vector Machine
  • Transcriptome / genetics*
  • Tuberculosis / diagnosis*