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.

Introduction Hepatotoxicity is one of the risk factors associated with treatment non-adherence, which is the main risk factor for drug resistance. Therefore, this study aimed to determine the incidence and risk factors of hepatotoxicity during highly active antiretroviral therapy (HAART) among people living with HIV in Ethiopia. Methods A prospective cohort study was conducted between April 2007 and January 2011 at Saint Peter Specialized Hospital, Akaki and Kality Health Centers, Addis Ababa, Ethiopia. A total of 316 HIV-infected adult individuals (70 participants were HIV and TB co-infected and 246 were infected with HIV alone) were included in this study. The study participants were followed for a total of 18 months with or without HAART. Socio-demographic data were collected using a structured questionnaire, and venous blood samples were collected for laboratory tests. Logistic regression and Poisson regression were used to determine the independent effect of each variable on hepatotoxicity at baseline and end of follow-up. Results Of 316 HIV-infected people, 72 (22.8%) participants had an elevated ALT/AST which was 100% mild-to moderate hepatotoxicity at baseline. Baseline CD4 T-cell count ( p = 0.027) and HIV co-infection with TB ( p < 0.001) were independently associated with hepatotoxicity at baseline. The overall incidence rate of hepatotoxicity in participants on HAART (21.8 per 100 person-years) was lower than participants who were HAART naïve (33.3 per 100 person-years) ( p = 0.009). Conclusion High incidence of mild-to-moderate hepatotoxicity and low severe hepatotoxicity were observed in HIV-infected individuals who were on HAART or were HAART naïve. HAART may minimize the occurrence of hepatotoxicity. Although HAART could minimize hepatotoxicity among HIV-infected people, to manage mild and moderate hepatotoxicity liver function test monitoring is required.

BackgroundValidation 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.MethodsExpression 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.ResultsThe 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.ConclusionsOur 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.

Background: Assessing immunological profiles from HIV-TB co-infection is essential to predict mortality, to facilitate the development of effective assays, the discovery of novel therapeutic targets and to conduct new interventions appropriately.Methods: Expression levels of 105 immune-related genes were measured at baseline of enrolment from 9 death HIV and TB coinfected study participants during follow-up and 18 survived groups for 2 years and matched controls, using focused gene expression profiling by dual-color Reverse-Transcription Multiplex Ligation-dependent Probe Amplification assay. Gene expression levels were also measured at six months and 18th month follow-up.Results: Eleven of the 105 selected genes were differentially expressed between death individuals and survivor matched controls. IL4δ2 was significantly higher expressed in death groups than survivor matched controls, whereas CD3E, IL7R, PTPRCv1, CCL4, GNLY, BCL2, CCL5, NOD1, TLR3 and NLRP13 had significantly lower expression levels in death groups compared to survivor matched controls. The expression of PTPRCv1, CD3E, CCL5, IL7R, NOD1, IL4δ2 and GNLY at baseline could accurately predict the mortality from TB-HIV co-infection.Conclusions: The expression of PTPRCv1, CD3E, CCL5 and IL7R host genes in peripheral blood of patients with TB-HIV coinfected can potentially be used as predictor of mortality in Ethiopian setting. Anti-TB treatment might be less likely to restore gene expression in the level expression of death groups. Therefore, other new therapeutic that can restore these gene (PTPRCv1, CD3E, IL7R and CCL5) in the death groups at baseline might be needed to save lives.