Abstract
There is an urgent need to identify immunological markers of tuberculosis (TB) risk in HIV co-infected individuals. Previously we have shown that TB recurrence in HIV co-infected individuals on ART was associated with markers of systemic inflammation (IL-6, IL1β and IL-1Rα). Here we examined the effect of additional acute inflammation and microbial translocation marker expression on risk of TB recurrence. Stored plasma samples were drawn from the TB Recurrence upon Treatment with HAART (TRuTH) study, in which individuals with previously treated pulmonary TB were screened for recurrence quarterly for up to 4 years. Recurrent TB cases (n = 37) were matched to controls (n = 102) by original trial study arm assignment and ART start date. Additional subsets of HIV infected (n = 41) and HIV uninfected (n = 37) individuals from Improving Recurrence Success (IMPRESS) study were sampled at active TB and post successful treatment completion. Plasma concentrations of soluble adhesion molecules (sMAdCAM, sICAM and sVCAM), lipopolysaccharide binding protein (LBP) and transforming growth factor-beta (TGF-β1, TGF-β2, TGF-β3) were measured by multiplex immunoassays and ELISA. Cytokine data was square root transformed in order to reduce variability. Multivariable analysis adjusted for a number of potential confounders measured at sample time-point: age, BMI, CD4 count, viral load (VL) and measured at baseline: presence or absence of lung cavities, previous history of TB, and WHO disease stage (4 vs 3). The following analytes were associated with increased risk of TB recurrence in the multivariable model: sICAM (aOR 1.06, 95% CI: 1.02-1.12, p = 0.009), LBP (aOR 8.78, 95% CI: 1.23-62.66, p = 0.030) and TGF-β3 (aOR 1.44, 95% CI 1.01-2.05, p = 0.044). Additionally, we observed a positive correlation between LBP and sICAM (r= 0.347, p<0.0001), and LBP and IL-6, identified to be one of the strongest predictors of TB risk in our previous study (r=0.623, p=0.03). These data show that increased risk of TB recurrence in HIV infected individuals on ART is likely associated with HIV mediated translocation of microbial products and the resulting chronic immune activation.
Highlights
Despite being a preventable and treatable disease, tuberculosis (TB) is currently one of the top ten causes of mortality globally and ranks above human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) as the primary cause of mortality from an infectious agent [1]
In the univariable and multivariable logistic models, the risk of TB recurrence was significantly associated with increase in plasma expression of soluble intracellular adhesion molecule (sICAM) and lipopolysaccharide binding protein (LBP), known to play a role in inflammation and translocation of microbial products, respectively [6, 19, 21]
Soluble, circulating forms of ICAM have been involved in a range of proinflammatory responses, and increase in sICAM levels have been linked with a range of human diseases including atherosclerosis and heart failure [21, 22]
Summary
Despite being a preventable and treatable disease, tuberculosis (TB) is currently one of the top ten causes of mortality globally and ranks above human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) as the primary cause of mortality from an infectious agent [1]. There is a dire need to improve our ability to predict those most at risk for TB disease progression and poor TB treatment response especially among HIV infected patients to enable early implementation of mitigating clinical and public health measures. Well defined correlates of TB risk and protection could facilitate rapid screening of new prevention methods and could improve diagnosis of active disease thereby slowing down transmission [9]. The current diagnosis of active disease and monitoring of response to TB treatment relies on sputum samples, whose volume and quality vary during the course of the disease. Blood-based biomarkers would be advantageous for several reasons, mainly due to relative ease of sample collection, reduced transmission risk, and the ability to measure multiple biomarkers at the same time improving the predictive power of the test [10]
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