Existing blood transcriptional classifiers accurately discriminate active tuberculosis from latent infection in individuals from south India

Samantha Leong, Yue Zhao, Noyal M. Joseph, Natasha S. Hochberg, Sonali Sarkar, Jane Pleskunas, David Hom, Subitha Lakshminarayanan, C. Robert Horsburgh, Gautam Roy, Jerrold J. Ellner, W. Evan Johnson, Padmini Salgame

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

Several studies have identified blood transcriptomic signatures that can distinguish active from latent Tuberculosis (TB). The purpose of this study was to assess how well these existing gene profiles classify TB disease in a South Indian population. RNA sequencing was performed on whole blood PAXgene samples collected from 28 TB patients and 16 latently TB infected (LTBI) subjects enrolled as part of an ongoing household contact study. Differential gene expression and clustering analyses were performed and compared with explicit predictive testing of TB and LTBI individuals based on established gene signatures. We observed strong predictive performance of TB disease states based on expression of known gene sets (ROC AUC 0.9007–0.9879). Together, our findings indicate that previously reported classifiers generated from different ethnic populations can accurately discriminate active TB from LTBI in South Indian patients. Future work should focus on converting existing gene signatures into a universal TB gene signature for diagnosis, monitoring TB treatment, and evaluating new drug regimens.

Original languageEnglish (US)
Pages (from-to)41-51
Number of pages11
JournalTuberculosis
Volume109
DOIs
StatePublished - Mar 2018

All Science Journal Classification (ASJC) codes

  • Microbiology
  • Immunology
  • Microbiology (medical)
  • Infectious Diseases

Keywords

  • Biomarker
  • Diagnostic
  • Gene signature
  • Tuberculosis

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