Retreatment and Anti-tuberculosis Therapy Outcomes in Brazil Between 2015 and 2022: A Nationwide Study.

Background: Adherence to anti-tuberculosis treatment (ATT) in Brazil remains a challenge in achieving the goals set by the World Health Organization (WHO). Patients who are lost to follow-up during treatment pose a significant public health problem. This study aimed to investigate the factors associated with unfavorable ATT outcomes among those undergoing retreatment in Brazil. Methods: We conducted an observational study of patients aged ≥18 years with tuberculosis (TB) reported to the Brazilian National Notifiable Disease Information System between 2015 and 2022. Clinical and epidemiologic variables were compared between the study groups (new cases and retreatment). Regression models identified variables associated with unfavorable outcomes. Results: Among 743 823 reported TB cases in the study period, 555 632 cases were eligible, consisting of 462 061 new cases and 93 571 undergoing retreatments (44 642 recurrent and 48 929 retreatments after loss to follow-up [RLTFU]). RLTFU (odds ratio [OR], 3.96 [95% confidence interval {CI}, 3.83-4.1]) was a significant risk factor for any type of unfavorable ATT. Furthermore, RLTFU (OR, 4.93 [95% CI, 4.76-5.11]) was the main risk factor for subsequent LTFU. For death, aside from advanced age, living with HIV (OR, 6.28 [95% CI, 6.03-6.54]) was the top risk factor. Conclusions: Retreatment is a substantial risk factor for unfavorable ATT outcomes, especially after LTFU. The rates of treatment success in RLTFU are distant from the WHO End TB Strategy targets throughout Brazil. These findings underscore the need for targeted interventions to improve treatment adherence and outcomes in persons who experience RLTFU.

Impact of Xpert MTB/RIF implementation in tuberculosis case detection and control in Brazil: a nationwide intervention time-series analysis (2011-2022).

Background: Since 2014, Brazil has gradually implemented the Xpert MTB/RIF (Xpert) test to enhance early tuberculosis (TB) and drug-resistant (DR-TB) detection and control, yet its nationwide impact remains underexplored. Our study conducts an intervention time-series analysis (ITSA) to evaluate how the Xpert's implementation has improved TB and DR-TB detection nationwide. Methods: 1,061,776 cases from Brazil's National TB Registry (2011-2022) were reviewed and ITSA (2011-2019) was used to gauge the impact of the Xpert's adoption on TB and DR-TB notification. Granger Causality and dynamic regression modelling determined if incorporating Xpert testing as an external regressor enhanced forecasting accuracy for Brazil's future TB trends. Findings: Xpert implementation resulted in a 9.7% increase in TB notification and substantial improvements in DR-TB (63.6%) and drug-susceptible TB (92.1%) detection compared to expected notifications if it had not been implemented. Xpert testing counts also presented a time-dependent relationship with DR-TB detection post-implementation, and improved predictions in forecasting models, which depicted a potential increase in TB and DR-TB detection in the next six years. Interpretation: This study underscores the critical role of Xpert's adoption in boosting TB and DR-TB detection in Brazil, reinforcing the case for its widespread use in disease control. Improvements in prediction accuracy resulting from integrating Xpert data are crucial for allocating resources and reducing the incidence of TB. By acknowledging Xpert's role in both disease control and improving predictions, we advocate for its expanded use and further research into advanced molecular diagnostics for effective TB and DR-TB control. Funding: FIOCRUZ.

Inflammatory profiles in sputum and blood of people with TB with and without HIV coinfection.

Although tuberculosis (TB) remains a major killer among infectious diseases and the leading cause of death for people with HIV, drivers of immunopathology, particularly at the site of infection in the lungs remain incompletely understood. To fill this gap, we compared cytokine profiles in paired plasma and sputum samples collected from adults with pulmonary TB with and without HIV. We found that people with pulmonary TB with HIV had significantly higher markers of inflammation in both plasma and sputum than those without HIV; these differences were present despite a similar extent of radiographic involvement. We also found that the strength and direction of correlations between biomarkers in the blood and lung compartments differed by HIV status and people with HIV had more positive correlations than those without HIV. Future studies can further explore these differences in inflammation by HIV status across the blood and lung compartments and seek to establish how these profiles may be associated with long-term outcomes and lung health after completion of TB treatment.

Machine learning algorithms using national registry data to predict loss to follow-up during tuberculosis treatment.

BACKGROUND: Identifying patients at increased risk of loss to follow-up (LTFU) is key to developing strategies to optimize the clinical management of tuberculosis (TB). The use of national registry data in prediction models may be a useful tool to inform healthcare workers about risk of LTFU. Here we developed a score to predict the risk of LTFU during anti-TB treatment (ATT) in a nationwide cohort of cases using clinical data reported to the Brazilian Notifiable Disease Information System (SINAN). METHODS: We performed a retrospective study of all TB cases reported to SINAN between 2015 and 2022; excluding children (< 18 years-old), vulnerable groups or drug-resistant TB. For the score, data before treatment initiation were used. We trained and internally validated three different prediction scoring systems, based on Logistic Regression, Random Forest, and Light Gradient Boosting. Before applying our models we splitted our data into training (~ 80% data) and test (~ 20%) sets, and then compared the model metrics using the test data set. RESULTS: Of the 243,726 cases included, 41,373 experienced LTFU whereas 202,353 were successfully treated. The groups were different with regards to several clinical and sociodemographic characteristics. The directly observed treatment (DOT) was unbalanced between the groups with lower prevalence in those who were LTFU. Three models were developed to predict LTFU using 8 features (prior TB, drug use, age, sex, HIV infection and schooling level) with different score composition approaches. Those prediction scoring systems exhibited an area under the curve (AUC) ranging between 0.71 and 0.72. The Light Gradient Boosting technique resulted in the best prediction performance, weighting specificity and sensitivity. A user-friendly web calculator app was developed ( https://tbprediction.herokuapp.com/ ) to facilitate implementation. CONCLUSIONS: Our nationwide risk score predicts the risk of LTFU during ATT in Brazilian adults prior to treatment commencement utilizing schooling level, sex, age, prior TB status, and substance use (drug, alcohol, and/or tobacco). This is a potential tool to assist in decision-making strategies to guide resource allocation, DOT indications, and improve TB treatment adherence.

Improved Treatment Outcome Following the Use of a Wound Dressings in Cutaneous Leishmaniasis Lesions.

Leishmaniasis, caused by Leishmania parasites, is a neglected tropical disease and Cutaneous Leishmaniasis (CL) is the most common form. Despite the associated toxicity and adverse effects, Meglumine antimoniate (MA) remains the first-choice treatment for CL in Brazil, pressing the need for the development of better alternatives. Bacterial NanoCellulose (BNC), a biocompatible nanomaterial, has unique properties regarding wound healing. In a previous study, we showed that use of topical BNC + systemic MA significantly increased the cure rate of CL patients, compared to treatment with MA alone. Herein, we performed a study comparing the combination of a wound dressing (BNC or placebo) plus systemic MA versus systemic MA alone, in CL caused by Leishmania braziliensis. We show that patients treated with the combination treatment (BNC or placebo) + MA showed improved cure rates and decreased need for rescue treatment, although differences compared to controls (systemic MA alone) were not significant. However, the overall time-to-cure was significantly lower in groups treated with the combination treatment (BNC+ systemic MA or placebo + systemic MA) in comparison to controls (MA alone), indicating that the use of a wound dressing improves CL treatment outcome. Assessment of the immune response in peripheral blood showed an overall downmodulation in the inflammatory landscape and a significant decrease in the production of IL-1a (p < 0.05) in patients treated with topical BNC + systemic MA. Our results show that the application of wound dressings to CL lesions can improve chemotherapy outcome in CL caused by L. braziliensis.

The inflammatory microenvironment of the lung at the time of infection governs innate control of SARS-CoV-2 replication.

SARS-CoV-2 infection leads to vastly divergent clinical outcomes ranging from asymptomatic infection to fatal disease. Co-morbidities, sex, age, host genetics and vaccine status are known to affect disease severity. Yet, how the inflammatory milieu of the lung at the time of SARS-CoV-2 exposure impacts the control of viral replication remains poorly understood. We demonstrate here that immune events in the mouse lung closely preceding SARS-CoV-2 infection significantly impact viral control and we identify key innate immune pathways required to limit viral replication. A diverse set of pulmonary inflammatory stimuli, including resolved antecedent respiratory infections with S. aureus or influenza, ongoing pulmonary M. tuberculosis infection, ovalbumin/alum-induced asthma or airway administration of defined TLR ligands and recombinant cytokines, all establish an antiviral state in the lung that restricts SARS-CoV-2 replication upon infection. In addition to antiviral type I interferons, the broadly inducible inflammatory cytokines TNFα and IL-1 precondition the lung for enhanced viral control. Collectively, our work shows that SARS-CoV-2 may benefit from an immunologically quiescent lung microenvironment and suggests that heterogeneity in pulmonary inflammation that precedes or accompanies SARS-CoV-2 exposure may be a significant factor contributing to the population-wide variability in COVID-19 disease outcomes.

High-throughput prioritization of target proteins for development of new antileishmanial compounds.

Leishmaniasis, a vector-borne disease, is caused by the infection of Leishmania spp., obligate intracellular protozoan parasites. Presently, human vaccines are unavailable, and the primary treatment relies heavily on systemic drugs, often presenting with suboptimal formulations and substantial toxicity, making new drugs a high priority for LMIC countries burdened by the disease, but a low priority in the agenda of most pharmaceutical companies due to unattractive profit margins. New ways to accelerate the discovery of new, or the repositioning of existing drugs, are needed. To address this challenge, our study aimed to identify potential protein targets shared among clinically-relevant Leishmania species. We employed a subtractive proteomics and comparative genomics approach, integrating high-throughput multi-omics data to classify these targets based on different druggability metrics. This effort resulted in the ranking of 6502 ortholog groups of protein targets across 14 pathogenic Leishmania species. Among the top 20 highly ranked groups, metabolic processes known to be attractive drug targets, including the ubiquitination pathway, aminoacyl-tRNA synthetases, and purine synthesis, were rediscovered. Additionally, we unveiled novel promising targets such as the nicotinate phosphoribosyltransferase enzyme and dihydrolipoamide succinyltransferases. These groups exhibited appealing druggability features, including less than 40% sequence identity to the human host proteome, predicted essentiality, structural classification as highly druggable or druggable, and expression levels above the 50th percentile in the amastigote form. The resources presented in this work also represent a comprehensive collection of integrated data regarding trypanosomatid biology.

An integrative multi-omics approach to characterize interactions between tuberculosis and diabetes mellitus.

Tuberculosis-diabetes mellitus (TB-DM) is linked to a distinct inflammatory profile, which can be assessed using multi-omics analyses. Here, a machine learning algorithm was applied to multi-platform data, including cytokines and gene expression in peripheral blood and eicosanoids in urine, in a Brazilian multi-center TB cohort. There were four clinical groups: TB-DM(n = 24), TB only(n = 28), DM(HbA1c ≥ 6.5%) only(n = 11), and a control group of close TB contacts who did not have TB or DM(n = 13). After cross-validation, baseline expression or abundance of MMP-28, LTE-4, 11-dTxB2, PGDM, FBXO6, SECTM1, and LINCO2009 differentiated the four patient groups. A distinct multi-omic-derived, dimensionally reduced, signature was associated with TB, regardless of glycemic status. SECTM1 and FBXO6 mRNA levels were positively correlated with sputum acid-fast bacilli grade in TB-DM. Values of the biomarkers decreased during the course of anti-TB therapy. Our study identified several markers associated with the pathophysiology of TB-DM that could be evaluated in future mechanistic investigations.

BACH1 promotes tissue necrosis and Mycobacterium tuberculosis susceptibility.

Oxidative stress triggers ferroptosis, a form of cellular necrosis characterized by iron-dependent lipid peroxidation, and has been implicated in Mycobacterium tuberculosis (Mtb) pathogenesis. We investigated whether Bach1, a transcription factor that represses multiple antioxidant genes, regulates host resistance to Mtb. We found that BACH1 expression is associated clinically with active pulmonary tuberculosis. Bach1 deletion in Mtb-infected mice increased glutathione levels and Gpx4 expression that inhibit lipid peroxidation. Bach1-/- macrophages exhibited increased resistance to Mtb-induced cell death, while Mtb-infected Bach1-deficient mice displayed reduced bacterial loads, pulmonary necrosis and lipid peroxidation concurrent with increased survival. Single-cell RNA-seq analysis of lungs from Mtb-infected Bach1-/- mice revealed an enrichment of genes associated with ferroptosis suppression. Bach1 depletion in Mtb-infected B6.Sst1S mice that display human-like necrotic lung pathology also markedly reduced necrosis and increased host resistance. These findings identify Bach1 as a key regulator of cellular and tissue necrosis and host resistance in Mtb infection.

Another tick bites the dust: exploring the association of microbial composition with a broad transmission competence of tick vector species.

IMPORTANCE: Some tick species are competent to transmit more than one pathogen while other species are, until now, known to be competent to transmit only one single or any pathogen. Such a difference in vector competence for one or more pathogens might be related to the microbiome, and understanding what differentiates these two groups of ticks could help us control several diseases aiming at the bacteria groups that contribute to such a broad vector competence. Using 16S rRNA from tick species that could be classified into these groups, genera such as Rickettsia and Staphylococcus seemed to be associated with such a broad vector competence. Our results highlight differences in tick species when they are divided based on the number of pathogens they are competent to transmit. These findings are the first step into understanding the relationship between one single tick species and the pathogens it transmits.

A multi-center, prospective cohort study of whole blood gene expression in the tuberculosis-diabetes interaction.

Diabetes mellitus (DM) increases tuberculosis (TB) severity. We compared blood gene expression in adults with pulmonary TB, with or without diabetes mellitus (DM) from sites in Brazil and India. RNA sequencing (RNAseq) performed at baseline and during TB treatment. Publicly available baseline RNAseq data from South Africa and Romania reported by the TANDEM Consortium were also analyzed. Across the sites, differentially expressed genes varied for each condition (DM, TB, and TBDM) and no pattern classified any one group across all sites. A concise signature of TB disease was identified but this was expressed equally in TB and TBDM. Pathway enrichment analysis failed to distinguish TB from TBDM, although there was a trend for greater neutrophil and innate immune pathway activation in TBDM participants. Pathways associated with insulin resistance, metabolic dysfunction, diabetic complications, and chromosomal instability were positively correlated with glycohemoglobin. The immune response to pulmonary TB as reflected by whole blood gene expression is substantially similar with or without comorbid DM. Gene expression pathways associated with the microvascular and macrovascular complications of DM are upregulated during TB, supporting a syndemic interaction between these coprevalent diseases.

Machine learning algorithms using national registry data to predict loss to follow- up during tuberculosis treatment.

Background: Identifying patients at increased risk of loss to follow-up (LTFU) is key to developing strategies to optimize the clinical management of tuberculosis (TB). The use of national registry data in prediction models may be a useful tool to inform healthcare workers about risk of LTFU. Here we developed a score to predict the risk of LTFU during anti-TB treatment (ATT) in a nationwide cohort of cases using clinical data reported to the Brazilian Notifiable Disease Information System (SINAN). Methods: We performed a retrospective study of all TB cases reported to SINAN between 2015-2022; excluding children (<18 years-old), vulnerable groups or drug-resistant TB. For the score, data before treatment initiation were used. We trained and internally validated three different prediction scoring systems, based on Logistic Regression, Random Forest, and Light Gradient Boosting. Before applying our models we split our data into train (~80% data) and test (~20%), and then we compare model metrics using a test data set. Results: Of the 243,726 cases included, 41,373 experienced LTFU whereas 202,353 were successfully treated and cured. The groups were different with regards to several clinical and sociodemographic characteristics. The directly observed treatment (DOT) was unbalanced between the groups with lower prevalence in those who were LTFU. Three models were developed to predict LTFU using 8 features (prior TB, drug use, age, sex, HIV infection and schooling level) with different score composition approaches. Those prediction scoring system exhibited an area under the curve (AUC) ranging between 0.71 and 0.72. The Light Gradient Boosting technique resulted in the best prediction performance, weighting specificity, and sensibility. A user-friendly web calculator app was created (https://tbprediction.herokuapp.com/) to facilitate implementation. Conclusions: Our nationwide risk score predicts the risk of LTFU during ATT in Brazilian adults prior to treatment commencement. This is a potential tool to assist in decision-making strategies to guide resource allocation, DOT indications, and improve TB treatment adherence.

Influence of dietary pattern on anti-tuberculosis treatment outcomes in persons with dysglycemia: a Peruvian prospective cohort study.

Introduction: Dietary patterns (DPs) are associated with overall nutritional status and may alter the clinical prognosis of tuberculosis. This interaction can be further intricated by dysglycemia (i.e., diabetes or prediabetes). Here, we identified DPs that are more common with tuberculosis-dysglycemia and depicted their association with tuberculosis treatment outcomes. Methods: A prospective cohort study of persons with tuberculosis and their contacts was conducted in Peru. A food frequency questionnaire and a multidimensional systems biology-based analytical approach were employed to identify DPs associated with these clinical groups. Potential independent associations between clinical features and DPs were analyzed. Results: Three major DPs were identified. TB-dysglycemia cases more often had a high intake of carbohydrates (DP1). Furthermore, DP1 was found to be associated with an increased risk of unfavorable TB outcomes independent of other factors, including dysglycemia. Conclusion: Our findings suggest that the evaluation of nutritional status through DPs in comorbidities such as dysglycemia is a fundamental action to predict TB treatment outcomes. The mechanisms underlying the association between high intake of carbohydrates, dysglycemia, and unfavorable tuberculosis treatment outcomes warrant further investigation.

Tuberculosis treatment outcomes of diabetic and non-diabetic TB/HIV co-infected patients: A nationwide observational study in Brazil.

Background: Tuberculosis (TB) is a worldwide public health problem, especially in countries that also report high numbers of people living with HIV (PLWH) and/or diabetes mellitus (DM). However, the unique features of persons with TB-HIV-DM are incompletely understood. This study compared anti-TB treatment (ATT) outcomes of diabetic and non-diabetic TB/HIV co-infected patients. Methods: A nationwide retrospective observational investigation was performed with data from the Brazilian Tuberculosis Database System among patients reported to have TB-HIV co-infection between 2014 and 2019. This database includes all reported TB cases in Brazil. Exploratory and association analyses compared TB treatment outcomes in DM and non-DM patients. Unfavorable outcomes were defined as death, treatment failure, loss to follow-up or recurrence. Multivariable stepwise logistic regressions were used to identify the variables associated with unfavorable ATT outcomes in the TB-HIV population. Results: Of the 31,070 TB-HIV patients analyzed, 999 (3.2%) reported having DM. However, in these TB-HIV patients, DM was not associated with any unfavorable treatment outcome [adjusted Odds Ratio (aOR): 0.97, 95% CI: 0.83-1.12, p = 0.781]. Furthermore, DM was also not associated with any specific type of unfavorable outcome in this study. In both the TB-HIV group and the TB-HIV-DM subpopulation, use of alcohol, illicit drugs and tobacco, as well as non-white ethnicity and prior TB were all characteristics more frequently observed in persons who experienced an unfavorable ATT outcome. Conclusion: DM is not associated with unfavorable TB treatment outcomes in persons with TB-HIV, including death, treatment failure, recurrence and loss to follow up. However, consumption habits, non-white ethnicity and prior TB are all more frequently detected in those with unfavorable outcomes in both TB-HIV and TB-HIV-DM patients.

Diagnostic biomarkers for active tuberculosis: progress and challenges.

Tuberculosis (TB) is a leading cause of morbidity and mortality from a single infectious agent, despite being preventable and curable. Early and accurate diagnosis of active TB is critical to both enhance patient care, improve patient outcomes, and break Mycobacterium tuberculosis (Mtb) transmission cycles. In 2020 an estimated 9.9 million people fell ill from Mtb, but only a little over half (5.8 million) received an active TB diagnosis and treatment. The World Health Organization has proposed target product profiles for biomarker- or biosignature-based diagnostics using point-of-care tests from easily accessible specimens such as urine or blood. Here we review and summarize progress made in the development of pathogen- and host-based biomarkers for active TB diagnosis. We describe several unique patient populations that have posed challenges to development of a universal diagnostic TB biomarker, such as people living with HIV, extrapulmonary TB, and children. We also review additional limitations to widespread validation and utilization of published biomarkers. We conclude with proposed solutions to enhance TB diagnostic biomarker validation and uptake.

Effect of Dysglycemia on Urinary Lipid Mediator Profiles in Persons With Pulmonary Tuberculosis.

Background: Oxidized lipid mediators such as eicosanoids play a central role in the inflammatory response associated with tuberculosis (TB) pathogenesis. Diabetes mellitus (DM) leads to marked changes in lipid mediators in persons with TB. However, the associations between diabetes-related changes in lipid mediators and clearance of M. tuberculosis (Mtb) among persons on anti-TB treatment (ATT) are unknown. Quantification of urinary eicosanoid metabolites can provide insights into the circulating lipid mediators involved in Mtb immune responses. Methods: We conducted a multi-site prospective observational study among adults with drug-sensitive pulmonary TB and controls without active TB; both groups had sub-groups with or without dysglycemia at baseline. Participants were enrolled from RePORT-Brazil (Salvador site) and RePORT-South Africa (Durban site) and stratified according to TB status and baseline glycated hemoglobin levels: a) TB-dysglycemia (n=69); b) TB-normoglycemia (n=64); c) non-TB/dysglycemia (n=31); d) non-TB/non-dysglycemia (n=29). We evaluated the following urinary eicosanoid metabolites: 11α-hydroxy-9,15-dioxo-2,3,4,5-tetranor-prostane-1,20-dioic acid (major urinary metabolite of prostaglandin E2, PGE-M), tetranor-PGE1 (metabolite of PGE2, TN-E), 9α-hydroxy-11,15-dioxo-2,3,4,5-tetranor-prostane-1,20-dioic acid (metabolite of PGD2, PGD-M), 11-dehydro-thromboxane B2 (11dTxB2), 2,3-dinor-6-keto-PGF1α (prostaglandin I metabolite, PGI-M), and leukotriene E4 (LTE4). Comparisons between the study groups were performed at three time points: before ATT and 2 and 6 months after initiating therapy. Results: PGE-M and LTE4 values were consistently higher at all three time-points in the TB-dysglycemia group compared to the other groups (p<0.001). In addition, there was a significant decrease in PGI-M and LTE4 levels from baseline to month 6 in the TB-dysglycemia and TB-normoglycemia groups. Finally, TB-dysglycemia was independently associated with increased concentrations of PGD-M, PGI-M, and LTE4 at baseline in a multivariable model adjusting for age, sex, BMI, and study site. These associations were not affected by HIV status. Conclusion: The urinary eicosanoid metabolite profile was associated with TB-dysglycemia before and during ATT. These observations can help identify the mechanisms involved in the pathogenesis of TB-dysglycemia, and potential biomarkers of TB treatment outcomes, including among persons with dysglycemia.

Transcriptional Analysis for Tuberculosis in Pregnant Women From the PRegnancy Associated Changes In Tuberculosis Immunology (PRACHITi) Study.

A new tuberculosis (TB) diagnostic cartridge assay, which detects a 3-gene TB signature in whole blood, was not diagnostic in women with maternal TB disease in India (area under the curve [AUC] = 0.72). In a cohort of pregnant women, we identified a novel gene set for TB diagnosis (AUC = 0.97) and one for TB progression (AUC = 0.96).

Immunologic Biomarkers in Peripheral Blood of Persons With Tuberculosis and Advanced HIV.

Introduction: Tuberculosis (TB) is a common opportunistic infection among people living with HIV. Diagnostic tests such as culture, Xpert-MTB-RIF, and ULTRA have low sensitivity in paucibacillary TB disease; a blood biomarker could improve TB diagnostic capabilities. We assessed soluble factors to identify biomarkers associated with TB among persons with advanced HIV. Methods: A case-control (1:1) study was conducted, with participants from Rio de Janeiro and Manaus, Brazil. People living with HIV presenting with CD4 count ≤100 cells/mm3 were eligible to participate. Cases had culture-confirmed TB (N=15) (positive for Mycobacterium tuberculosis [Mtb]); controls had HIV-infection only (N=15). Study visits included baseline, month 2 and end of TB therapy, during which samples of peripheral blood were obtained. A panel containing 29 biomarkers including cytokines, chemokines and growth factors was utilized to assess candidate biomarkers using Luminex technology in cryopreserved EDTA plasma samples. We used neural network analysis, based on machine learning, to identify biomarkers (single or in combination) that best distinguished cases from controls. Additional multi-dimensional analyses provided detailed profiling of the systemic inflammatory environment in cases and controls. Results: Median CD4 count and HIV-1 RNA load values were similar between groups at all timepoints. Persons with TB had lower body mass index (BMI) (median=19.6, Interquartile Range [IQR]=18.6-22.3) than controls (23.7; IQR: 21.8 = 25.5, p=0.004). TB coinfection was also associated with increased frequency of other comorbidities. The overall profile of plasma cytokines, chemokines and growth factors were distinct between the study groups at all timepoints. Plasma concentrations of IL-15 and IL-10 were on average lower in TB cases than in controls. When used in combination, such markers were able to discriminate between TB cases and controls with the highest degree of accuracy at each study timepoint. Conclusion: Among persons with advanced HIV, plasma concentrations of IL-15 and IL-10 can be used in combination to identify TB disease regardless of time on anti-TB treatment.

CD4 T cells are rapidly depleted from tuberculosis granulomas following acute SIV co-infection.

HIV/Mycobacterium tuberculosis (Mtb) co-infected individuals have an increased risk of tuberculosis prior to loss of peripheral CD4 T cells, raising the possibility that HIV co-infection leads to CD4 T cell depletion in lung tissue before it is evident in blood. Here, we use rhesus macaques to study the early effects of simian immunodeficiency virus (SIV) co-infection on pulmonary granulomas. Two weeks after SIV inoculation of Mtb-infected macaques, Mtb-specific CD4 T cells are dramatically depleted from granulomas, before CD4 T cell loss in blood, airways, and lymph nodes, or increases in bacterial loads or radiographic evidence of disease. Spatially, CD4 T cells are preferentially depleted from the granuloma core and cuff relative to B cell-rich regions. Moreover, live imaging of granuloma explants show that intralesional CD4 T cell motility is reduced after SIV co-infection. Thus, granuloma CD4 T cells may be decimated before many co-infected individuals experience the first symptoms of acute HIV infection.

Frequency of CXCR3+ CD8+ T-Lymphocyte Subsets in Peripheral Blood Is Associated With the Risk of Paradoxical Tuberculosis-Associated Immune Reconstitution Inflammatory Syndrome Development in Advanced HIV Disease.

Background: Tuberculosis-associated immune reconstitution inflammatory syndrome (TB-IRIS) is a clinical aggravation of TB symptoms observed among a fraction of HIV coinfected patients shortly after the start of antiretroviral therapy (ART). Of note, TB-IRIS is characterized by exacerbated inflammation and tissue damage that occurs in response to the elevated production of CD4+ T cell-derived IFN-γ. Nevertheless, the possible participation of CD8+ T cells in TB-IRIS development remains unclear. Methods: We performed a comprehensive assessment of the composition of CD8+ T cell memory subsets and their association with circulating inflammation-related molecules in TB-HIV coinfected patients initiating ART. Results: We found that TB-IRIS individuals display higher frequencies of Antigen-experienced CD8+ T cells during the onset of IRIS and that the levels of these cells positively correlate with baseline mycobacterial smear grade. TB-IRIS individuals exhibited higher frequencies of effector memory and lower percentages of naïve CD8+ T cells than their Non-IRIS counterparts. In both TB-IRIS and Non-IRIS patients, ART commencement was associated with fewer significant correlations among memory CD8+ T cells and cells from other immune compartments. Networks analysis revealed distinct patterns of correlation between each memory subset with inflammatory cytokines suggesting different dynamics of CD8+ T cell memory subsets reconstitution. TB-IRIS patients displayed lower levels of memory cells positive for CXCR3 (a chemokine receptor that plays a role in trafficking activated CD8+ T cells to the tissues) than Non-IRIS individuals before and after ART. Furthermore, we found that CXCR3+ naïve CD8+ T cells were inversely associated with the risk of TB-IRIS development. On the other hand, we noticed that the frequencies of CXCR3+ effector CD8+ T cells were positively associated with the probability of TB-IRIS development. Conclusion: Our data suggest that TB-IRIS individuals display a distinct profile of memory CD8+ T cell subsets reconstitution after ART initiation. Moreover, our data point to a differential association between the frequencies of CXCR3+ CD8+ T cells and the risk of TB-IRIS development. Collectively, our findings lend insights into the potential role of memory CD8+ T cells in TB-IRIS pathophysiology.