Active Tuberculosis Is Associated with Depletion of HIV-Specific CD4 and CD8 T Cells in People with HIV.

Infection with Mycobacterium tuberculosis (Mtb) in people with HIV (PWH) is associated with depletion of Mtb-specific CD4 T cell responses, increased risk of progression to active tuberculosis (TB) disease, and increased immune activation. Although higher HIV viral loads have been reported in Mtb/HIV co-infection, the extent to which Mtb infection and TB disease impact the frequency and phenotype of HIV-specific T cell responses has not been well described. We enrolled a cohort of PWH in Kenya across a spectrum of Mtb infection states, including those with no evidence of Mtb infection, latent Mtb infection (LTBI), and active pulmonary TB disease, and evaluated the frequency, immune activation, and cytotoxicity phenotype of HIV-specific CD4 and CD8 T cell responses in peripheral blood by flow cytometry. We found evidence of depletion of HIV-specific CD4 and CD8 T cells in people with TB, but not with LTBI. Expression of the immune activation markers human leukocyte antigen-DR isotype (HLA-DR) and Ki67 and of the cytotoxic molecules granzyme B and perforin were increased in total CD4 and CD8 T cell populations in individuals with TB, although expression of these markers by HIV-specific CD4 and CD8 T cells did not differ by Mtb infection status. These data suggest that TB is associated with overall increased T cell activation and cytotoxicity and with depletion of HIV-specific CD4 and CD8 T cells, which may contribute to further impairment of T cell-mediated immune control of HIV replication in the setting of TB.

Estimating severe acute respiratory coronavirus virus 2 (SARS-CoV-2) seroprevalence from residual clinical blood samples, January-March 2021.

We describe severe acute respiratory coronavirus virus 2 (SARS-CoV-2) IgG seroprevalence and antigenemia among patients at a medical center in January-March 2021 using residual clinical blood samples. The overall seroprevalences were 17% by infection and 16% by vaccination. Spent or residual samples are a feasible alternative for rapidly estimating seroprevalence or monitoring trends in infection and vaccination.

Model-Predicted Impact of ECG Monitoring Strategies During Bedaquiline Treatment.

Background: The M2 metabolite of bedaquiline causes QT-interval prolongation, making electrocardiogram (ECG) monitoring of patients receiving bedaquiline for drug-resistant tuberculosis necessary. The objective of this study was to determine the relationship between M2 exposure and Fridericia-corrected QT (QTcF)-interval prolongation and to explore suitable ECG monitoring strategies for 6-month bedaquiline treatment. Methods: Data from the PROBeX study, a prospective observational cohort study, were used to characterize the relationship between M2 exposure and QTcF. Established nonlinear mixed-effects models were fitted to pharmacokinetic and ECG data. In a virtual patient population, QTcF values were simulated for scenarios with and without concomitant clofazimine. ECG monitoring strategies to identify patients who need to interrupt treatment (QTcF > 500 ms) were explored. Results: One hundred seventy patients were included, providing 1131 bedaquiline/M2 plasma concentrations and 1702 QTcF measurements; 2.1% of virtual patients receiving concomitant clofazimine had QTcF > 500 ms at any point during treatment (0.7% without concomitant clofazimine). With monthly monitoring, almost all patients with QTcF > 500 ms were identified by week 12; after week 12, patients were predominantly falsely identified as QTcF > 500 ms due to stochastic measurement error. Following a strategy with monitoring before treatment and at weeks 2, 4, 8, and 12 in simulations with concomitant clofazimine, 93.8% of all patients who should interrupt treatment were identified, and 26.4% of all interruptions were unnecessary (92.1% and 32.2%, respectively, without concomitant clofazimine). Conclusions: Our simulations enable an informed decision for a suitable ECG monitoring strategy by weighing the risk of missing patients with QTcF > 500 ms and that of interrupting bedaquiline treatment unnecessarily. We propose ECG monitoring before treatment and at weeks 2, 4, 8, and 12 after starting bedaquiline treatment.

Modeling Missing Cases and Transmission Links in Networks of Extensively Drug-Resistant Tuberculosis in KwaZulu-Natal, South Africa.

Patterns of transmission of drug-resistant tuberculosis (TB) remain poorly understood, despite over half a million incident cases worldwide in 2017. Modeling TB transmission networks can provide insight into drivers of transmission, but incomplete sampling of TB cases can pose challenges for inference from individual epidemiologic and molecular data. We assessed the effect of missing cases on a transmission network inferred from Mycobacterium tuberculosis sequencing data on extensively drug-resistant TB cases in KwaZulu-Natal, South Africa, diagnosed in 2011-2014. We tested scenarios in which cases were missing at random, missing differentially by clinical characteristics, or missing differentially by transmission (i.e., cases with many links were under- or oversampled). Under the assumption that cases were missing randomly, the mean number of transmissions per case in the complete network needed to be larger than 20, far higher than expected, to reproduce the observed network. Instead, the most likely scenario involved undersampling of high-transmitting cases, and models provided evidence for super-spreading. To our knowledge, this is the first analysis to have assessed support for different mechanisms of missingness in a TB transmission study, but our results are subject to the distributional assumptions of the network models we used. Transmission studies should consider the potential biases introduced by incomplete sampling and identify host, pathogen, or environmental factors driving super-spreading.

Social Mixing and Clinical Features Linked With Transmission in a Network of Extensively Drug-resistant Tuberculosis Cases in KwaZulu-Natal, South Africa.

BACKGROUND: Tuberculosis (TB) is the leading infectious cause of death globally, and drug-resistant TB strains pose a serious threat to controlling the global TB epidemic. The clinical features, locations, and social factors driving transmission in settings with high incidences of drug-resistant TB are poorly understood. METHODS: We measured a network of genomic links using Mycobacterium tuberculosis whole-genome sequences. RESULTS: Patients with 2-3 months of cough or who spent time in urban locations were more likely to be linked in the network, while patients with sputum smear-positive disease were less likely to be linked than those with smear-negative disease. Associations persisted using different thresholds to define genomic links and irrespective of assumptions about the direction of transmission. CONCLUSIONS: Identifying factors that lead to many transmissions, including contact with urban areas, can suggest settings instrumental in transmission and indicate optimal locations and groups to target with interventions.

Treatment Adherence Among Persons Receiving Concurrent Multidrug-Resistant Tuberculosis and HIV Treatment in KwaZulu-Natal, South Africa.

BACKGROUND: Success in multidrug-resistant tuberculosis (MDR-TB) and HIV treatment requires high medication adherence despite high pill burdens, frequent adverse events, and long treatment duration, which may jeopardize adherence. We prospectively compared MDR-TB/HIV-coinfected persons to those with MDR-TB alone to determine the impact of concurrent treatment on adherence and outcomes. METHODS: We assessed medication adherence monthly using 3-day recall, 30-day recall, and visual analog scale and examined adherence to monthly study visits (months 0-12). We determined the proportion of participants fully adherent (no reported missed doses) to MDR-TB vs. HIV treatment by each measure. We assessed the association of medication and clinic visit adherence with MDR-TB treatment success (cure or completion, 18-24 months) and HIV virologic suppression. RESULTS: Among 200 patients with MDR-TB, 63% were women, median age was 33 years, 144 (72%) were HIV-infected, and 81% were receiving antiretroviral therapy (ART) at baseline. Adherence to medications (81%-98% fully adherent across all measures) and clinic visits (80% missed ≤1 visit) was high, irrespective of HIV status. Adherence to ART was significantly higher than to MDR-TB treatment by all self-reported measures (3-day recall: 92% vs. 84%, respectively; P = 0.003). In multivariable analysis, the adjusted risk ratio of unsuccessful MDR-TB treatment increased with every missed visit: 1.50, 2.25, and 3.37 for unsuccessful treatment, for 1, 2, and ≥3 missed visits. CONCLUSIONS: Adherence to ART was higher than to MDR-TB treatment among persons with MDR-TB/HIV coinfection. Missed clinic visits may be a simple measure for identifying patients at risk of unsuccessful MDR-TB treatment outcome.

Spatial Patterns of Extensively Drug-Resistant Tuberculosis Transmission in KwaZulu-Natal, South Africa.

Background: Transmission is driving the global drug-resistant tuberculosis (TB) epidemic; nearly three-quarters of drug-resistant TB cases are attributable to transmission. Geographic patterns of disease incidence, combined with information on probable transmission links, can define the spatial scale of transmission and generate hypotheses about factors driving transmission patterns. Methods: We combined whole-genome sequencing data with home Global Positioning System coordinates from 344 participants with extensively drug-resistant (XDR) TB in KwaZulu-Natal, South Africa, diagnosed from 2011 to 2014. We aimed to determine if genomically linked (difference of ≤5 single-nucleotide polymorphisms) cases lived close to one another, which would suggest a role for local community settings in transmission. Results: One hundred eighty-two study participants were genomically linked, comprising 1084 case-pairs. The median distance between case-pairs' homes was 108 km (interquartile range, 64-162 km). Between-district, as compared to within-district, links accounted for the majority (912/1084 [84%]) of genomic links. Half (526 [49%]) of genomic links involved a case from Durban, the urban center of KwaZulu-Natal. Conclusions: The high proportions of between-district links with Durban provide insight into possible drivers of province-wide XDR-TB transmission, including urban-rural migration. Further research should focus on characterizing the contribution of these drivers to overall XDR-TB transmission in KwaZulu-Natal to inform design of targeted strategies to curb the drug-resistant TB epidemic.