Blood transcriptomic diagnosis of pulmonary and extrapulmonary tuberculosis.

ABSTRACT: BACKGROUND. Novel rapid diagnostics for active tuberculosis (TB) are required to overcome the time delays and inadequate sensitivity of current microbiological tests that are critically dependent on sampling the site of disease. Multiparametric blood transcriptomic signatures of TB have been described as potential diagnostic tests. We sought to identify the best transcript candidates as host biomarkers for active TB, extend the evaluation of their specificity by comparison with other infectious diseases, and to test their performance in both pulmonary and extrapulmonary TB. METHODS. Support vector machine learning, combined with feature selection, was applied to new and previously published blood transcriptional profiles in order to identify the minimal TB‑specific transcript

SUBMITTER: Roe JK 

PROVIDER: S-EPMC5053151 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature