Search

Type 2 diabetes (T2D) is a prevalent risk factor for tuberculosis (TB), but most studies on TB-T2D have focused on TB patients, been limited to one community, and shown a variable impact of T2D on TB risk or treatment outcomes. We conducted a cross-sectional assessment of sociodemographic and metabolic factors in adult TB contacts with T2D (versus no T2D), from the Texas-Mexico border to study Hispanics, and in Cape Town to study South African Coloured ethnicities. The prevalence of T2D was 30.2% in Texas-Mexico and 17.4% in South Africa, with new diagnosis in 34.4% and 43.9%, respectively. Contacts with T2D differed between ethnicities, with higher smoking, hormonal contraceptive use and cholesterol levels in South Africa, and higher obesity in Texas-Mexico (p < 0.05). PCA analysis revealed striking differences between ethnicities in the relationships between factors defining T2D and dyslipidemias. Our findings suggest that screening for new T2D in adult TB contacts is effective to identify new T2D patients at risk for TB. Furthermore, studies aimed at predicting individual TB risk in T2D patients, should take into account the heterogeneity in dyslipidemias that are likely to modify the estimates of TB risk or adverse treatment outcomes that are generally attributed to T2D alone.

Host markers to monitor the response to tuberculosis (TB) therapy hold some promise. We evaluated the changes in concentration of Mycobacterium tuberculosis (M.tb)-induced soluble biomarkers during early treatment for predicting short- and long-term treatment outcomes. Whole blood samples from 30 cured and 12 relapsed TB patients from diagnosis, week 1, 2, and 4 of treatment were cultured in the presence of live M.tb for seven days and patients followed up for 24 weeks after the end of treatment. 57 markers were measured in unstimulated and antigen-stimulated culture supernatants using Luminex assays. Top performing multi-variable models at diagnosis using unstimulated values predicted outcome at 24 months after treatment completion with a sensitivity of 75.0% (95% CI, 42.8 – 94.5%) and specificity of 72.4% (95% CI, 52.8 – 87.3%) in leave-one-out cross validation. Month two treatment responder classification was correctly predicted with a sensitivity of 79.2% (95% CI, 57.8 – 92.9) and specificity of 93.3% (95% CI, 64– 99.8%). This study provides evidence of the early M.tb-specific treatment response in TB patients but shows that the observed unstimulated marker models are not outperformed by stimulated marker models. Performance of unstimulated predictive host marker signatures is promising and requires validation in larger studies.