Detection of tuberculosis in HIV-infected and -uninfected African adults using whole blood RNA expression signatures: a case-control study.

• Main Authors: Myrsini Kaforou, Victoria J Wright, Tolu Oni, Neil French, Suzanne T Anderson, Nonzwakazi Bangani, Claire M Banwell, Andrew J Brent, Amelia C Crampin, Hazel M Dockrell, Brian Eley, Robert S Heyderman, Martin L Hibberd, Florian Kern, Paul R Langford, Ling Ling, Marc Mendelson, Tom H Ottenhoff, Femia Zgambo, Robert J Wilkinson, Lachlan J Coin, Michael Levin
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2013-10-01
• Series: PLoS Medicine
• Online Access: https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24167453/pdf/?tool=EBI

<h4>Background</h4>A major impediment to tuberculosis control in Africa is the difficulty in diagnosing active tuberculosis (TB), particularly in the context of HIV infection. We hypothesized that a unique host blood RNA transcriptional signature would distinguish TB from other diseases (OD) in HIV-infected and -uninfected patients, and that this could be the basis of a simple diagnostic test.<h4>Methods and findings</h4>Adult case-control cohorts were established in South Africa and Malawi of HIV-infected or -uninfected individuals consisting of 584 patients with either TB (confirmed by culture of Mycobacterium tuberculosis [M.TB] from sputum or tissue sample in a patient under investigation for TB), OD (i.e., TB was considered in the differential diagnosis but then excluded), or healthy individuals with latent TB infection (LTBI). Individuals were randomized into training (80%) and test (20%) cohorts. Blood transcriptional profiles were assessed and minimal sets of significantly differentially expressed transcripts distinguishing TB from LTBI and OD were identified in the training cohort. A 27 transcript signature distinguished TB from LTBI and a 44 transcript signature distinguished TB from OD. To evaluate our signatures, we used a novel computational method to calculate a disease risk score (DRS) for each patient. The classification based on this score was first evaluated in the test cohort, and then validated in an independent publically available dataset (GSE19491). In our test cohort, the DRS classified TB from LTBI (sensitivity 95%, 95% CI [87-100]; specificity 90%, 95% CI [80-97]) and TB from OD (sensitivity 93%, 95% CI [83-100]; specificity 88%, 95% CI [74-97]). In the independent validation cohort, TB patients were distinguished both from LTBI individuals (sensitivity 95%, 95% CI [85-100]; specificity 94%, 95% CI [84-100]) and OD patients (sensitivity 100%, 95% CI [100-100]; specificity 96%, 95% CI [93-100]). Limitations of our study include the use of only culture confirmed TB patients, and the potential that TB may have been misdiagnosed in a small proportion of OD patients despite the extensive clinical investigation used to assign each patient to their diagnostic group.<h4>Conclusions</h4>In our study, blood transcriptional signatures distinguished TB from other conditions prevalent in HIV-infected and -uninfected African adults. Our DRS, based on these signatures, could be developed as a test for TB suitable for use in HIV endemic countries. Further evaluation of the performance of the signatures and DRS in prospective populations of patients with symptoms consistent with TB will be needed to define their clinical value under operational conditions. Please see later in the article for the Editors' Summary.