IL-10 suppresses T cell expansion while promoting tissue-resident memory cell formation during SARS-CoV-2 infection in rhesus macaques.

The regulation of inflammatory responses and pulmonary disease during SARS-CoV-2 infection is incompletely understood. Here we examine the roles of the prototypic pro- and anti-inflammatory cytokines IFNγ and IL-10 using the rhesus macaque model of mild COVID-19. We find that IFNγ drives the development of 18fluorodeoxyglucose (FDG)-avid lesions in the lungs as measured by PET/CT imaging but is not required for suppression of viral replication. In contrast, IL-10 limits the duration of acute pulmonary lesions, serum markers of inflammation and the magnitude of virus-specific T cell expansion but does not impair viral clearance. We also show that IL-10 induces the subsequent differentiation of virus-specific effector T cells into CD69+CD103+ tissue resident memory cells (Trm) in the airways and maintains Trm cells in nasal mucosal surfaces, highlighting an unexpected role for IL-10 in promoting airway memory T cells during SARS-CoV-2 infection of macaques.

Effect of Smoking on Longitudinal Interferon-ϒ Release Assay Results among Close Contacts of People with Pulmonary Tuberculosis.

Diagnosis of M. tuberculosis (Mtb) infection in close contacts is critical for TB control. Smoking is a risk factor for Mtb infection and TB disease but its effect on longitudinal interferon-gamma release assay (IGRA) results remains unknown. We conducted a multi-site prospective study in Brazil between 2015-2019, among close contacts of adults with culture-confirmed pulmonary TB. IGRA was performed at baseline, month 6 if negative at baseline, and month 24-30 after enrollment. IGRA results were categorized as IGRA-positive (maintained from baseline to last visit), IGRA-conversion (from negative to positive at any time), IGRA-reversion (from positive to negative at any time), and IGRA-negative (maintained from baseline to last visit). Associations between IGRA results and smoking status at baseline (current/former vs never) in contacts were evaluated using propensity score-adjusted logistic regression models. Estimated propensity score was used as a covariate in models, which regressed the outcome (IGRA-positive, IGRA-conversion, IGRA-reversion) on smoking status. Of 430 close contacts, 89 (21%) were IGRA-positive, 30 (7%) were converters, 30 (7%) were reverters and 22 were indeterminate. Smoking frequency was 26 (29%) among IGRA-positive contacts, 7 (23%) in converters, and 3 (10%) in reverters. Smoking in contacts was associated with lower odds of IGRA-reversion (adjusted odds ratio = 0.16; 95% confidence interval = [0.03-0.70]). We did not detect associations between smoking and IGRA-positive or IGRA-conversion. Our findings highlight the importance of smoking on longitudinal IGRA results. This has implications for clinical care and clinical trials in which IGRA status is monitored or used as an outcome.

Prediction Models for Adverse Drug Reactions During Tuberculosis Treatment in Brazil.

BACKGROUND: Tuberculosis (TB) treatment-related adverse drug reactions (TB-ADRs) can negatively affect adherence and treatment success rates. METHODS: We developed prediction models for TB-ADRs, considering participants with drug-susceptible pulmonary TB who initiated standard TB therapy. TB-ADRs were determined by the physician attending the participant, assessing causality to TB drugs, the affected organ system, and grade. Potential baseline predictors of TB-ADR included concomitant medication (CM) use, human immunodeficiency virus (HIV) status, glycated hemoglobin (HbA1c), age, body mass index (BMI), sex, substance use, and TB drug metabolism variables (NAT2 acetylator profiles). The models were developed through bootstrapped backward selection. Cox regression was used to evaluate TB-ADR risk. RESULTS: There were 156 TB-ADRs among 102 of the 945 (11%) participants included. Most TB-ADRs were hepatic (n = 82 [53%]), of moderate severity (grade 2; n = 121 [78%]), and occurred in NAT2 slow acetylators (n = 62 [61%]). The main prediction model included CM use, HbA1c, alcohol use, HIV seropositivity, BMI, and age, with robust performance (c-statistic = 0.79 [95% confidence interval {CI}, .74-.83) and fit (optimism-corrected slope and intercept of -0.09 and 0.94, respectively). An alternative model replacing BMI with NAT2 had similar performance. HIV seropositivity (hazard ratio [HR], 2.68 [95% CI, 1.75-4.09]) and CM use (HR, 5.26 [95% CI, 2.63-10.52]) increased TB-ADR risk. CONCLUSIONS: The models, with clinical variables and with NAT2, were highly predictive of TB-ADRs.

Transcriptomic signatures of progression to TB disease among close contacts in Brazil.

BACKGROUND: Approximately 5% of people infected with Mycobacterium tuberculosis progress to tuberculosis (TB) disease without preventive therapy. There is a need for a prognostic test to identify those at highest risk of incident TB, so that therapy can be targeted. We evaluated host blood transcriptomic signatures for progression to TB disease. METHODS: Close contacts (≥4 hours exposure per week) of adult patients with culture-confirmed pulmonary TB were enrolled in Brazil. Investigation for incident, microbiologically-confirmed or clinically-diagnosed pulmonary or extra-pulmonary TB disease through 24 months of follow-up was symptom-triggered. Twenty previously validated blood TB transcriptomic signatures were measured at baseline by real-time quantitative PCR. Prognostic performance for incident TB was tested using receiver operating characteristic curve (ROC) analysis at 6, 9, 12, and 24 months of follow-up. RESULTS: Between June 2015 and June 2019, 1,854 close contacts were enrolled; Twenty-five progressed to incident TB, of whom 13 had microbiologically-confirmed disease. Baseline transcriptomic signature scores were measured in 1,789 close contacts. Prognostic performance for all signatures was best within 6 months of diagnosis. Seven signatures (Gliddon4, Suliman4, Roe3, Roe1, Penn-Nicholson6, Francisco2, and Rajan5) met the minimum World Health Organization target product profile (TPP) for a prognostic test through 6 months; three (Gliddon4, Rajan5, and Duffy9) through 9 months. None met the TPP threshold through 12 or more months of follow-up. CONCLUSIONS: Blood transcriptomic signatures may be useful for predicting TB risk within 9 months of measurement among TB-exposed contacts, to target preventive therapy administration.

The Xpert® MTB/RIF cycle threshold value predicts M. tuberculosis transmission to close contacts in a Brazilian prospective multicenter cohort.

BACKGROUND: The Xpert® MTB/RIF rapid molecular test provides a quantitative measure of Mycobacterium tuberculosis (Mtb) DNA in the form of cycle threshold (Ct) values. This information can be translated into mycobacterial load and used as a potential risk measure of bacterial spread for tuberculosis cases, which can impact infection control. However, the role of Ct values in assessing Mtb transmission to close contacts has not yet been demonstrated. METHODS: A prospective study was performed to investigate the association between Xpert® MTB/RIF Ct values and Mtb transmission to close contacts of patients with culture-confirmed pulmonary TB in a multi-center Brazilian cohort. We evaluated clinical and laboratory data, such as age, sex, race, smoking habits, drug use, alcohol use, chest radiograph, Xpert® MTB/RIF results among pulmonary tuberculosis cases, and QuantiFERON(QFT)-Plus results at baseline and after six months for close contacts who had a negative result at baseline. RESULTS: A total of 1,055 close contacts of 382 pulmonary tuberculosis cases were included in the study. The median Ct values from pulmonary tuberculosis cases of QFT-Plus positive (at baseline or six months) close contacts were lower compared with those who were QFT-Plus negative. An adjusted logistic regression demonstrated that reduced Ct values from the index cases were independently associated with QFT-Plus conversion from negative to positive (OR: 1.61, 95% CI: 1.12-2.32) after adjusting for clinical characteristics. CONCLUSION: Close contacts of pulmonary TB index cases exhibiting low Xpert MTB/RIF Ct values displayed higher rates of TB infection, reflecting Mtb transmission.

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.

The Effect of Diabetes and Prediabetes on Antituberculosis Treatment Outcomes: A Multicenter Prospective Cohort Study.

BACKGROUND: It is unclear whether diabetes or prediabetes affects unfavorable treatment outcomes and death in people with tuberculosis (PWTB). METHODS: Culture-confirmed, drug-susceptible PWTB, enrolled in the Regional Prospective Observational Research in Tuberculosis (RePORT)-Brazil cohort between 2015 and 2019 (N = 643) were stratified based on glycemic status according to baseline glycated hemoglobin. Unfavorable tuberculosis (TB) outcome was defined as treatment failure or modification, recurrence, or death; favorable outcome was cure or treatment completion. We corroborated the findings using data from PWTB reported to the Brazilian National System of Diseases Notification (SINAN) during 2015-2019 (N = 20 989). Logistic regression models evaluated associations between glycemic status and outcomes. RESULTS: In both cohorts, in univariate analysis, unfavorable outcomes were more frequently associated with smoking, illicit drug use, and human immunodeficiency virus infection. Diabetes, but not prediabetes, was associated with unfavorable outcomes in the RePORT-Brazil (adjusted relative risk [aRR], 2.45; P < .001) and SINAN (aRR, 1.76; P < .001) cohorts. Furthermore, diabetes was associated with high risk of death (during TB treatment) in both RePORT-Brazil (aRR, 2.16; P = .040) and SINAN (aRR, 1.93; P = .001). CONCLUSIONS: Diabetes was associated with an increased risk of unfavorable outcomes and mortality in Brazilian PWTB. Interventions to improve TB treatment outcomes in persons with diabetes are needed.

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).

Immune Response to LinB13, a Lutzomyia Intermedia Salivary Protein Correlates With Disease Severity in Tegumentary Leishmaniasis.

BACKGROUND: We have previously shown that seropositivity to rLinB-13, a salivary protein from Lutzomyia intermedia, predicted sand fly exposure and was associated with increased risk of developing cutaneous leishmaniasis (CL). METHODS: Here, we investigated the cellular immune response to saliva from Lu. intermedia, using rLinB-13 as a surrogate antigen in naturally exposed individuals presenting positive serology to LinB-13. We also investigated the response to rLinB-13 in leishmaniasis patients, displaying active ulcers and positive PCR for Leishmania braziliensis. RESULTS: Peripheral blood mononuclear cells (PBMCs) stimulated in vitro with rLinB-13 secreted elevated levels of interleukin-10 (IL-10), IL-4, IL-1ß, IL-1α, IL-6, and chemokines (CCL3, CCL4, CCL5, and CXCL5). CL and disseminated leishmaniasis (DL) patients displayed a significantly higher immunoglobulin G (IgG) response to rLinB-13 compared with healthy subjects, and anti-rLinB-13 IgG was positively correlated with the number of lesions in DL patients. Positive serology to rLinB-13 was also associated with chemotherapy failure. PBMCs from DL patients stimulated with rLINB-13 secreted significantly higher levels of IL-10 and IL-1ß compared with CL individuals. CONCLUSIONS: In this study, we observed an association between humoral and cellular immune response to the sand fly salivary protein rLinB-13 and disease severity in tegumentary leishmaniasis. This study brings evidence that immunity to rLinB-13 influences disease outcome in L. braziliensis infection and results indicate that positive serology to rLinB-13 IgG can be used as a marker of DL, an emerging and severe form of disease caused by L. braziliensis.

A Clinical Prediction Model for Unsuccessful Pulmonary Tuberculosis Treatment Outcomes.

BACKGROUND: Despite widespread availability of curative therapy, tuberculosis (TB) treatment outcomes remain suboptimal. Clinical prediction models can inform treatment strategies to improve outcomes. Using baseline clinical data, we developed a prediction model for unsuccessful TB treatment outcome and evaluated the incremental value of human immunodeficiency virus (HIV)-related severity and isoniazid acetylator status. METHODS: Data originated from the Regional Prospective Observational Research for Tuberculosis Brazil cohort, which enrolled newly diagnosed TB patients in Brazil from 2015 through 2019. This analysis included participants with culture-confirmed, drug-susceptible pulmonary TB who started first-line anti-TB therapy and had ≥12 months of follow-up. The end point was unsuccessful TB treatment: composite of death, treatment failure, regimen switch, incomplete treatment, or not evaluated. Missing predictors were imputed. Predictors were chosen via bootstrapped backward selection. Discrimination and calibration were evaluated with c-statistics and calibration plots, respectively. Bootstrap internal validation estimated overfitting, and a shrinkage factor was applied to improve out-of-sample prediction. Incremental value was evaluated with likelihood ratio-based measures. RESULTS: Of 944 participants, 191 (20%) had unsuccessful treatment outcomes. The final model included 7 baseline predictors: hemoglobin, HIV infection, drug use, diabetes, age, education, and tobacco use. The model demonstrated good discrimination (c-statistic = 0.77; 95% confidence interval, .73-.80) and was well calibrated (optimism-corrected intercept and slope, -0.12 and 0.89, respectively). HIV-related factors and isoniazid acetylation status did not improve prediction of the final model. CONCLUSIONS: Using information readily available at treatment initiation, the prediction model performed well in this population. The findings may guide future work to allocate resources or inform targeted interventions for high-risk patients.

Host lipidome and tuberculosis treatment failure.

INTRODUCTION: Host lipids play important roles in tuberculosis (TB) pathogenesis. Whether host lipids at TB treatment initiation (baseline) affect subsequent treatment outcomes has not been well characterised. We used unbiased lipidomics to study the prospective association of host lipids with TB treatment failure. METHODS: A case-control study (n=192), nested within a prospective cohort study, was used to investigate the association of baseline plasma lipids with TB treatment failure among adults with pulmonary TB. Cases (n=46) were defined as TB treatment failure, while controls (n=146) were those without failure. Complex lipids and inflammatory lipid mediators were measured using liquid chromatography mass spectrometry techniques. Adjusted least-square regression was used to assess differences in groups. In addition, machine learning identified lipids with highest area under the curve (AUC) to classify cases and controls. RESULTS: Baseline levels of 32 lipids differed between controls and those with treatment failure after false discovery rate adjustment. Treatment failure was associated with lower baseline levels of cholesteryl esters and oxylipin, and higher baseline levels of ceramides and triglycerides compared to controls. Two cholesteryl ester lipids combined in a unique classifier model provided an AUC of 0.79 (95% CI 0.65-0.93) in the test dataset for prediction of TB treatment failure. CONCLUSIONS: We identified lipids, some with known roles in TB pathogenesis, associated with TB treatment failure. In addition, a lipid signature with prognostic accuracy for TB treatment failure was identified. These lipids could be potential targets for risk-stratification, adjunct therapy and treatment monitoring.

Baseline IL-6 is a biomarker for unfavourable tuberculosis treatment outcomes: a multisite discovery and validation study.

BACKGROUND: Biomarkers of unfavourable tuberculosis (TB) treatment outcomes are needed to accelerate new drug and regimen development. Whether plasma cytokine levels can predict unfavourable TB treatment outcomes is unclear. METHODS: We identified and internally validated the association between 20 a priori selected plasma inflammatory markers and unfavourable treatment outcomes of failure, recurrence and all-cause mortality among adults with drug-sensitive pulmonary TB in India. We externally validated these findings in two independent cohorts of predominantly diabetic and HIV co-infected TB patients in India and South Africa, respectively. RESULTS: Pre-treatment interferon-γ, interleukin (IL)-13 and IL-6 were associated with treatment failure in the discovery analysis. Internal validation confirmed higher pre-treatment IL-6 concentrations among failure cases compared with controls. External validation among predominantly diabetic TB patients found an association between pre-treatment IL-6 concentrations and subsequent recurrence and death. Similarly, external validation among predominantly HIV co-infected TB patients found an association between pre-treatment IL-6 concentrations and subsequent treatment failure and death. In a pooled analysis of 363 TB cases from the Indian and South African validation cohorts, high pre-treatment IL-6 concentrations were associated with higher risk of failure (adjusted OR (aOR) 2.16, 95% CI 1.08-4.33; p=0.02), recurrence (aOR 5.36, 95% CI 2.48-11.57; p<0.001) and death (aOR 4.62, 95% CI 1.95-10.95; p<0.001). Adding baseline IL-6 to a risk prediction model comprised of low body mass index, high smear grade and cavitation improved model performance by 15% (C-statistic 0.66 versus 0.76; p=0.02). CONCLUSIONS: Pre-treatment IL-6 is a biomarker for unfavourable TB treatment outcomes. Future studies should identify optimal IL-6 concentrations for point-of-care risk prediction.

Clinical and Immunologic Predictors of Mycobacterium avium Complex Immune Reconstitution Inflammatory Syndrome in a Contemporary Cohort of Patients With Human Immunodeficiency Virus.

BACKGROUND: People with human immunodeficiency virus (HIV) can present with new or worsening symptoms associated with Mycobacterium avium complex (MAC) infection shortly after antiretroviral therapy (ART) initiation as MAC immune reconstitution inflammatory syndrome (MAC-IRIS). In this study, we assessed the utility of several laboratory tests as predictors of MAC-IRIS. METHODS: People with HIV with clinical and histologic and/or microbiologic evidence of MAC-IRIS were identified and followed up to 96 weeks post-ART initiation within a prospective study of 206 ART-naive patients with CD4 <100 cells/µL. RESULTS: Fifteen (7.3%) patients presented with MAC-IRIS within a median interval of 26 days after ART initiation. Patients who developed MAC-IRIS had lower body mass index, lower hemoglobin levels, higher alkaline phosphatase (ALP), and increased CD38 frequency and mean fluorescence intensity on CD8+ T cells at the time of ART initiation compared with non-MAC IRIS patients. A decision tree inference model revealed that stratifying patients based on levels of ALP and D-dimer could predict the likelihood of MAC-IRIS. A binary logistic regression demonstrated that higher levels of ALP at baseline were associated with increased risk of MAC-IRIS development. CONCLUSIONS: High ALP levels and increased CD8+ T-cell activation with low CD4 counts at ART initiation should warrant suspicion for subsequent development of MAC-IRIS.

An Inflammatory Composite Score Predicts Mycobacterial Immune Reconstitution Inflammatory Syndrome in People with Advanced HIV: A Prospective International Cohort Study.

BACKGROUND: Immune reconstitution inflammatory syndrome (IRIS) is a common cause of morbidity among people with human immunodeficiency virus (PWH) who initiate antiretroviral therapy (ART) with severe lymphopenia. Easily accessible tools that reliably predict emergence and elucidate pathogenesis of IRIS are needed to facilitate improved clinical management. METHODS: Plasma levels of biomarkers were measured before ART initiation in a large multinational cohort of ART-naive PWH with severe immunosuppression (CD4+ count <100 cells/mm3) in United States, Kenya, and Thailand. We performed a series of multiparametric analyses of inflammatory and clinical biomarkers and developed a composite score merging relevant biomarkers for use in a prediction model. RESULTS: We identified a distinct baseline inflammatory profile and changes in inflammatory networks among biomarkers in participants who subsequently developed mycobacterial or viral IRIS. We also developed a composite score incorporating biomarkers associated with IRIS (interleukin-6 [IL-6], IL-10, IL-27, sCD14, interferon-γ, tumor necrosis factor-α, hyaluronic acid, D-dimer, body mass index, and hemoglobin) that accurately predicted mycobacterial IRIS and death in this cohort. CONCLUSIONS: Systemic inflammatory profiles in PWH with severe immunosuppression are predictive of IRIS. Composite scores for the prediction of mycobacterial IRIS and death could be useful for risk stratification in PWH and lymphopenia initiating ART. CLINICAL TRIALS REGISTRATION: NCT00286767.

The Effect of Diabetes and Prediabetes on Mycobacterium tuberculosis Transmission to Close Contacts.

BACKGROUND: It is unknown whether dysglycemia is associated with Mycobacterium tuberculosis transmission. METHODS: We assessed epidemiological and clinical characteristics of patients with culture-confirmed pulmonary tuberculosis and their close contacts, enrolled in a multicenter prospective cohort in Brazil. Contacts were investigated at baseline and 6 months after enrollment. QuantiFERON positivity at baseline and conversion (from negative to positive at month 6) were compared between subgroups of contacts according to glycemic status of persons with tuberculosis (PWTB) as diabetes mellitus (DM) or prediabetes. Multivariable mixed-effects logistic regression models were performed to test independent associations with baseline QuantiFERON positive and QuantiFERON conversion. RESULTS: There were 592 PWTB (153 DM, 141 prediabetes, 211 normoglycemic) and 1784 contacts, of whom 658 were QuantiFERON-positive at baseline and 106 converters. Multivariable analyses demonstrated that tuberculosis-prediabetes cases, acid-fast bacilli-positive, pulmonary cavities, and living with someone who smoked were independently associated with QuantiFERON positive in contacts at baseline. DM, persistent cough, acid-fast bacilli-positive, and pulmonary cavities in tuberculosis source cases were associated with QuantiFERON conversion. CONCLUSIONS: Contacts of persons with pulmonary tuberculosis and dysglycemia were at increased risk of being QuantiFERON positive at baseline or month 6. Increased focus on such close contacts could improve tuberculosis control.

Derivation and Validation of a Novel Severity Scoring System for Pneumonia at Intensive Care Unit Admission.

BACKGROUND: Severity stratification scores developed in intensive care units (ICUs) are used in interventional studies to identify the most critically ill. Studies that evaluate accuracy of these scores in ICU patients admitted with pneumonia are lacking. This study aims to determine performance of severity scores as predictors of mortality in critically ill patients admitted with pneumonia. METHODS: Prospective cohort study in a general ICU in Brazil. ICU severity scores (Simplified Acute Physiology Score 3 [SAPS 3] and Sepsis-Related Organ Failure Assessment [qSOFA]), prognostic scores of pneumonia (CURB-65 [confusion, urea, respiratory rate, blood pressure, age] and CRB-65 [confusion, respiratory rate, blood pressure, age]), and clinical and epidemiological variables in the first 6 hours of hospitalization were analyzed. RESULTS: Two hundred patients were included between 2015 and 2018, with a median age of 81 years (interquartile range, 67-90 years) and female predominance (52%), primarily admitted from the emergency department (65%) with community-acquired pneumonia (CAP, 80.5%). SAPS 3, CURB-65, CRB-65,and qSOFA all exhibited poor performance in predicting mortality. Multivariate regression identified variables independently associated with mortality that were used to develop a novel pneumonia-specific ICU severity score (Pneumonia Shock score) that outperformed SAPS 3, CURB-65, and CRB-65. The Shock score was validated in an external multicenter cohort of critically ill patients admitted with CAP. CONCLUSIONS: We created a parsimonious score that accurately identifies patients with pneumonia at highest risk of ICU death. These findings are critical to accurately stratify patients with severe pneumonia in therapeutic trials that aim to reduce mortality.

Newborns With Zika Virus-Associated Microcephaly Exhibit Marked Systemic Inflammatory Imbalance.

BACKGROUND: Zika virus (ZIKV) is an emergent flavivirus initially considered a benign and self-limited exanthematic illness. In 2015, a new epidemic emerged in northeastern of Brazil with increased incidence of a previously rare clinical outcome, microcephaly, in newborns from mothers who were infected during pregnancy. Little is known about the immunopathogenesis of ZIKV-associated microcephaly. Understanding the inflammatory profile and degree of inflammation of persons affected with such condition is an important step towards development of innovative therapeutic strategies. METHODS: A case-control study compared plasma levels of several inflammatory biomarkers from newborns with ZIKV microcephaly, asymptomatic ZKV infection, or uninfected controls. Plasma biomarkers were assessed using Luminex. A series of multidimensional analysis was performed to characterize the systemic immune activation profile of the clinical groups. RESULTS: We identified an inflammatory signature associated with ZIKV microcephaly that suggested an increased inflammation. Network analysis suggested that ZIKV microcephaly is associated with imbalanced immune activation and inflammation. The cephalic perimeter was inversely proportional with the degree of inflammatory perturbation. Furthermore, a combination of plasma inflammatory biomarkers could discriminate ZIKV with microcephaly from those with ZIKV without microcephaly or uninfected neonates. CONCLUSIONS: An intense inflammatory imbalance that is proportional to the disease severity hallmarks ZIKV microcephaly.

Lack of Weight Gain During the First 2 Months of Treatment and Human Immunodeficiency Virus Independently Predict Unsuccessful Treatment Outcomes in Tuberculosis.

BACKGROUND: Weight change may inform tuberculosis treatment response, but its predictive power may be confounded by human immunodeficiency virus (HIV). METHODS: We prospectively followed up adults with culture-confirmed, drug-susceptible, pulmonary tuberculosis receiving standard 4-drug therapy (isoniazid, rifampin, pyrazinamide, and ethambutol) in Brazil. We examined median weight change 2 months after treatment initiation by HIV status, using quantile regression, and unsuccessful tuberculosis treatment outcome (treatment failure, tuberculosis recurrence, or death) by HIV and weight change status, using Cox regression. RESULTS: Among 547 participants, 102 (19%) were HIV positive, and 35 (6%) had an unsuccessful outcome. After adjustment for confounders, persons living with HIV (PLWH) gained a median of 1.3 kg (95% confidence interval [CI], -2.8 to .1) less than HIV-negative individuals during the first 2 months of tuberculosis treatment. PLWH were at increased risk of an unsuccessful outcome (adjusted hazard ratio, 4.8; 95% CI, 2.1-10.9). Weight change was independently associated with outcome, with risk of unsuccessful outcome decreasing by 12% (95% CI, .81%-.95%) per 1-kg increase. CONCLUSIONS: PLWH gained less weight during the first 2 months of tuberculosis treatment, and lack of weight gain and HIV independently predicted unsuccessful tuberculosis treatment outcomes. Weight, an easily collected biomarker, may identify patients who would benefit from alternative treatment strategies.

Transcriptomic Profiles of Confirmed Pediatric Tuberculosis Patients and Household Contacts Identifies Active Tuberculosis, Infection, and Treatment Response Among Indian Children.

BACKGROUND: Gene expression profiling is emerging as a tool for tuberculosis diagnosis and treatment response monitoring, but limited data specific to Indian children and incident tuberculosis infection (TBI) exist. METHODS: Sixteen pediatric Indian tuberculosis cases were age- and sex-matched to 32 tuberculosis-exposed controls (13 developed incident TBI without subsequent active tuberculosis). Longitudinal samples were collected for ribonucleic acid sequencing. Differential expression analysis generated gene lists that identify tuberculosis diagnosis and tuberculosis treatment response. Data were compared with published gene lists. Population-specific risk score thresholds were calculated. RESULTS: Seventy-one genes identified tuberculosis diagnosis and 25 treatment response. Within-group expression was partially explained by age, sex, and incident TBI. Transient changes in gene expression were identified after both infection and treatment. Application of 27 published gene lists to our data found variable performance for tuberculosis diagnosis (sensitivity 0.38-1.00, specificity 0.48-0.93) and treatment response (sensitivity 0.70-0.80, specificity 0.40-0.80). Our gene lists found similarly variable performance when applied to published datasets for diagnosis (sensitivity 0.56-0.85, specificity 0.50-0.85) and treatment response (sensitivity 0.49- 0.86, specificity 0.50-0.84). CONCLUSIONS: Gene expression profiles among Indian children with confirmed tuberculosis were distinct from adult-derived gene lists, highlighting the importance of including distinct populations in differential gene expression models.

Differential Expression of Activation Markers by Mycobacterium tuberculosis-specific CD4+ T Cell Distinguishes Extrapulmonary From Pulmonary Tuberculosis and Latent Infection.

BACKGROUND: Diagnosis of active tuberculosis (ATB) currently relies on detection of Mycobacterium tuberculosis (Mtb). Identifying patients with extrapulmonary TB (EPTB) remains challenging because microbiological confirmation is often not possible. Highly accurate blood-based tests could improve diagnosis of both EPTB and pulmonary TB (PTB) and timely initiation of anti-TB therapy. METHODS: A case-control study was performed using discriminant analyses to validate an approach using Mtb-specific CD4+T-cell activation markers in blood to discriminate PTB and EPTB from latent TB infection (LTBI) as well as EPTB from PTB in 270 Brazilian individuals. We further tested the effect of human immunodeficiency virus (HIV) coinfection on diagnostic performance. Frequencies of interferon-γ +CD4+T cells expressing CD38, HLADR, and/or Ki67 were assessed by flow cytometry. RESULTS: EPTB and PTB were associated with higher frequencies of CD4+T cells expressing CD38, HLADR, or Ki67 compared with LTBI (all P values < .001). Moreover, frequencies of HLADR+ (P = .03) or Ki67+ (P < .001) cells accurately distinguished EPTB from PTB. HIV infection did not affect the capacity of these markers to distinguish ATB from LTBI or EPTB from PTB. CONCLUSIONS: Cell activation markers in Mtb-specific CD4+T cells distinguished ATB from LTBI and EPTB from PTB, regardless of HIV infection status. These parameters provide an attractive approach for developing blood-based diagnostic tests for both active and latent TB.