Gene expression profiles classifying clinical stages of tuberculosis and monitoring treatment responses in Ethiopian HIV-negative and HIV-positive cohorts.

BACKGROUND: Validation of previously identified candidate biomarkers and identification of additional candidate gene expression profiles to facilitate diagnosis of tuberculosis (TB) disease and monitoring treatment responses in the Ethiopian context is vital for improving TB control in the future. METHODS: Expression levels of 105 immune-related genes were determined in the blood of 80 HIV-negative study participants composed of 40 active TB cases, 20 latent TB infected individuals with positive tuberculin skin test (TST+), and 20 healthy controls with no Mycobacterium tuberculosis (Mtb) infection (TST-), using focused gene expression profiling by dual-color Reverse-Transcription Multiplex Ligation-dependent Probe Amplification assay. Gene expression levels were also measured six months after anti-TB treatment (ATT) and follow-up in 38 TB patients. RESULTS: The expression of 15 host genes in TB patients could accurately discriminate between TB cases versus both TST+ and TST- controls at baseline and thus holds promise as biomarker signature to classify active TB disease versus latent TB infection in an Ethiopian setting. Interestingly, the expression levels of most genes that markedly discriminated between TB cases versus TST+ or TST- controls did not normalize following completion of ATT therapy at 6 months (except for PTPRCv1, FCGR1A, GZMB, CASP8 and GNLY) but had only fully normalized at the 18 months follow-up time point. Of note, network analysis comparing TB-associated host genes identified in the current HIV-negative TB cohort to TB-associated genes identified in our previously published Ethiopian HIV-positive TB cohort, revealed an over-representation of pattern recognition receptors including TLR2 and TLR4 in the HIV-positive cohort which was not seen in the HIV-negative cohort. Moreover, using ROC cutoff ≥ 0.80, FCGR1A was the only marker with classifying potential between TB infection and TB disease regardless of HIV status. CONCLUSIONS: Our data indicate that complex gene expression signatures are required to measure blood transcriptomic responses during and after successful ATT to fully diagnose TB disease and characterise drug-induced relapse-free cure, combining genes which resolve completely during the 6-months treatment phase of therapy with genes that only fully return to normal levels during the post-treatment resolution phase

Host Gene Expression Kinetics During Treatment of Tuberculosis in HIV-Coinfected Individuals Is Independent of Highly Active Antiretroviral Therapy.

Background: Limitations in diagnostic tools to discriminate between active tuberculosis and latent Mycobacterium tuberculosis infection and for monitoring antituberculosis treatment responses are major challenges in tuberculosis control, especially in human immunodeficiency virus (HIV)-coinfected individuals. Methods: Expression levels of 105 immune-related genes were determined in 131 HIV-infected patients with active tuberculosis (n = 48), patients with latent M. tuberculosis infection (LTBI; n = 37), and controls with no M. tuberculosis infection (n = 46) in Addis Ababa, Ethiopia, using focused gene expression profiling with a dual-color reverse-transcription multiplex ligation-dependent probe amplification assay. Results: Within the cohort of HIV-positive subjects, the expression profiles of 7 genes at baseline (FCGR1A, RAB24, TLR1, TLR4, MMP9, NLRC4, and IL1B) could accurately discriminate between active tuberculosis and both latent and no M. tuberculosis infection, largely independently of (in)eligibility for highly active antiretroviral therapy (HAART). Six months after antituberculosis treatment, biomarker profiles of patients with tuberculosis became indistinguishable from those of patients with LTBI and controls. Importantly, host gene expression kinetics during antituberculosis treatment in HIV-coinfected individuals was found to be independent of HAART use. Conclusions: Blood transcriptomic profiles can potentially be used as biomarkers to discriminate the different clinical stages of tuberculosis in HIV-coinfected individuals and to monitor tuberculosis treatment responses in both HAART recipients and untreated individuals

Host gene expression kinetics during treatment of tuberculosis in HIV-coinfected individuals is independent of HAART therapy.

Limitations in diagnostic tools to discriminate between active and latent tuberculosis (TB) and for monitoring TB treatment responses are major challenges in TB control, especially in HIV-coinfected individuals