Undernourished Household Contacts Are at Increased Risk of Tuberculosis (TB) Disease, but not TB Infection- a Multicenter Prospective Cohort Analysis.

Undernutrition is the leading risk factor for tuberculosis (TB) globally and in India. This multicenter prospective cohort analysis from India suggests that undernutrition is associated with increased risk of TB disease but not TB infection among household contacts of persons with TB.

Comparison of gene set scoring methods for reproducible evaluation of tuberculosis gene signatures.

BACKGROUND: Blood-based transcriptional gene signatures for tuberculosis (TB) have been developed with potential use to diagnose disease. However, an unresolved issue is whether gene set enrichment analysis of the signature transcripts alone is sufficient for prediction and differentiation or whether it is necessary to use the original model created when the signature was derived. Intra-method comparison is complicated by the unavailability of original training data and missing details about the original trained model. To facilitate the utilization of these signatures in TB research, comparisons between gene set scoring methods cross-data validation of original model implementations are needed. METHODS: We compared the performance of 19 TB gene signatures across 24 transcriptomic datasets using both rrebuilt original models and gene set scoring methods. Existing gene set scoring methods, including ssGSEA, GSVA, PLAGE, Singscore, and Zscore, were used as alternative approaches to obtain the profile scores. The area under the ROC curve (AUC) value was computed to measure performance. Correlation analysis and Wilcoxon paired tests were used to compare the performance of enrichment methods with the original models. RESULTS: For many signatures, the predictions from gene set scoring methods were highly correlated and statistically equivalent to the results given by the original models. In some cases, PLAGE outperformed the original models when considering signatures' weighted mean AUC values and the AUC results within individual studies. CONCLUSION: Gene set enrichment scoring of existing gene sets can distinguish patients with active TB disease from other clinical conditions with equivalent or improved accuracy compared to the original methods and models. These data justify using gene set scoring methods of published TB gene signatures for predicting TB risk and treatment outcomes, especially when original models are difficult to apply or implement.

Impact of Undernutrition on Tuberculosis Treatment Outcomes in India: A Multicenter, Prospective, Cohort Analysis.

BACKGROUND: Undernutrition is the leading risk factor for tuberculosis (TB) globally. Its impact on treatment outcomes is poorly defined. METHODS: We conducted a prospective cohort analysis of adults with drug-sensitive pulmonary TB at 5 sites from 2015-2019. Using multivariable Poisson regression, we assessed associations between unfavorable outcomes and nutritional status based on body mass index (BMI) nutritional status at treatment initiation, BMI prior to TB disease, stunting, and stagnant or declining BMI after 2 months of TB treatment. Unfavorable outcome was defined as a composite of treatment failure, death, or relapse within 6 months of treatment completion. RESULTS: Severe undernutrition (BMI <16 kg/m2) at treatment initiation and severe undernutrition before the onset of TB disease were both associated with unfavorable outcomes (adjusted incidence rate ratio [aIRR], 2.05; 95% confidence interval [CI], 1.42-2.91 and aIRR, 2.20; 95% CI, 1.16-3.94, respectively). Additionally, lack of BMI increase after treatment initiation was associated with increased unfavorable outcomes (aIRR, 1.81; 95% CI, 1.27-2.61). Severe stunting (height-for-age z score <-3) was associated with unfavorable outcomes (aIRR, 1.52; 95% CI, 1.00-2.24). Severe undernutrition at treatment initiation and lack of BMI increase during treatment were associated with a 4- and 5-fold higher rate of death, respectively. CONCLUSIONS: Premorbid undernutrition, undernutrition at treatment initiation, lack of BMI increase after intensive therapy, and severe stunting are associated with unfavorable TB treatment outcomes. These data highlight the need to address this widely prevalent TB comorbidity. Nutritional assessment should be integrated into standard TB care.

Effect of treatment adherence on the association between sex and unfavourable treatment outcomes among tuberculosis patients in Puducherry, India: a mediation analysis.

BACKGROUND: A better understanding of the complex interplay between risk factors of tuberculosis (TB) is essential. This study was part of the Regional Prospective Observational Research for Tuberculosis (RePORT) India consortium and includes newly diagnosed TB patients in Puducherry between 2014 and 2018. We employed mediation analysis to identify the effect of treatment adherence on association between sex and unfavourable TB treatment outcomes. METHODS: Required demographic and treatment-related variables were extracted from the RePORT India consortium database and causal mediation analysis using parametric regression models was done. RESULTS: Of the 712 TB patients, ~87 (12.2%) had unfavourable TB treatment outcomes. Total effect of male sex was significantly associated with the unfavourable TB treatment outcomes [adjusted odds ratio (aOR) = 2.48; 95% confidence interval (CI): 1.11-5.55]. However, the overall association between male sex and TB treatment outcomes was dominated by the indirect pathway, as the direct pathway does not show significant association (aOR = 1.67; 95% CI: 0.75-3.75), while the indirect pathway shows significantly higher odds of TB treatment outcomes (aOR = 1.48; 95% CI:1.27-1.73), indicating complete mediation by the treatment adherence. CONCLUSIONS: The study has shown a complete mediation of sexes through TB treatment adherence for unfavourable treatment outcomes. Developing of treatment strategies require better understanding between the biological and social factors related to TB.

Predictors of weight loss during the intensive phase of tuberculosis treatment in patients with drug-susceptible pulmonary tuberculosis in South India.

BACKGROUND: Tuberculosis (TB) is well-known for causing wasting. Patients on treatment gain weight and weight loss is associated with unfavorable treatment outcomes. There is limited description of weight loss and its predictors during intensive treatment phase. The objective of this study was to assess the predictors of weight loss during intensive phase and to see if there is any association exists with sputum conversion at the end of intensive phase of treatment. METHODS: Data collected as a part of the prospective TB cohort (Regional Prospective Observational Research for TB India Phase 1) conducted in Pondicherry, Cuddalore and Viluppuram districts of Tamil Nadu were used for this study. Sputum smear and body weight comparison were made in the baseline and at the end of second month of treatment. RESULTS: In all, 726 participants had weight measurements at the two time points and 18.7% had weight loss; mean weight lost being 2.3 kg (SD 3.05). Mean weight loss was more among males (2.4 kg, SD 3.2), diabetics (2.8 kg, SD 3.9) and alcoholics (2.1 kg, SD 2.4). Alcohol consumption was the only predictor of weight loss after adjusting for age, diabetes, marital status and BMI (aRR 1.52, P 0.02). Weight loss was not associated with sputum conversion at the end of second month. CONCLUSIONS: Alcohol use emerged as the major predictor for weight loss during intensive phase.

Development of prognostic scoring system for predicting 1-year mortality among pulmonary tuberculosis patients in South India.

BACKGROUND: Development of a prediction model using baseline characteristics of tuberculosis (TB) patients at the time of diagnosis will aid us in early identification of the high-risk groups and devise pertinent strategies accordingly. Hence, we did this study to develop a prognostic-scoring model for predicting the death among newly diagnosed drug sensitive pulmonary TB patients in South India. METHODS: We undertook a longitudinal analysis of cohort data under the Regional Prospective Observational Research for Tuberculosis India consortium. Multivariable cox regression using the stepwise backward elimination procedure was used to select variables for the model building and the nomogram-scoring system was developed with the final selected model. RESULTS: In total, 54 (4.6%) out of the 1181 patients had died during the 1-year follow-up period. The TB mortality rate was 0.20 per 1000 person-days. Eight variables (age, gender, functional limitation, anemia, leukopenia, thrombocytopenia, diabetes, neutrophil-lymphocyte ratio) were selected and a nomogram was built using these variables. The discriminatory power was 0.81 (95% confidence interval: 0.75-0.86) and this model was well-calibrated. Decision curve analysis showed that the model is beneficial at a threshold probability ~15-65%. CONCLUSIONS: This scoring system could help the clinicians and policy makers to devise targeted interventions and in turn reduce the TB mortality in India.

Development and Validation of a Parsimonious Tuberculosis Gene Signature Using the digital NanoString nCounter Platform.

BACKGROUND: Blood-based biomarkers for diagnosing active tuberculosis (TB), monitoring treatment response, and predicting risk of progression to TB disease have been reported. However, validation of the biomarkers across multiple independent cohorts is scarce. A robust platform to validate TB biomarkers in different populations with clinical end points is essential to the development of a point-of-care clinical test. NanoString nCounter technology is an amplification-free digital detection platform that directly measures mRNA transcripts with high specificity. Here, we determined whether NanoString could serve as a platform for extensive validation of candidate TB biomarkers. METHODS: The NanoString platform was used for performance evaluation of existing TB gene signatures in a cohort in which signatures were previously evaluated on an RNA-seq dataset. A NanoString codeset that probes 107 genes comprising 12 TB signatures and 6 housekeeping genes (NS-TB107) was developed and applied to total RNA derived from whole blood samples of TB patients and individuals with latent TB infection (LTBI) from South India. The TBSignatureProfiler tool was used to score samples for each signature. An ensemble of machine learning algorithms was used to derive a parsimonious biomarker. RESULTS: Gene signatures present in NS-TB107 had statistically significant discriminative power for segregating TB from LTBI. Further analysis of the data yielded a NanoString 6-gene set (NANO6) that when tested on 10 published datasets was highly diagnostic for active TB. CONCLUSIONS: The NanoString nCounter system provides a robust platform for validating existing TB biomarkers and deriving a parsimonious gene signature with enhanced diagnostic performance.

Transmission phenotype of Mycobacterium tuberculosis strains is mechanistically linked to induction of distinct pulmonary pathology.

In a study of household contacts (HHC), households were categorized into High (HT) and Low (LT) transmission groups based on the proportion of HHC with a positive tuberculin skin test. The Mycobacterium tuberculosis (Mtb) strains from HT and LT index cases of the households were designated Mtb-HT and Mtb-LT, respectively. We found that C3HeB/FeJ mice infected with Mtb-LT strains exhibited significantly higher bacterial burden compared to Mtb-HT strains and also developed diffused inflammatory lung pathology. In stark contrast, a significant number of mice infected with Mtb-HT strains developed caseating granulomas, a lesion type with high potential to cavitate. None of the Mtb-HT infected animals developed diffused inflammatory lung pathology. A link was observed between increased in vitro replication of Mtb-LT strains and their ability to induce significantly high lipid droplet formation in macrophages. These results support that distinct early interactions of Mtb-HT and Mtb-LT strains with macrophages and subsequent differential trajectories in pathological disease may be the mechanism underlying their transmission potential.

Prevalence and risk factors associated with latent tuberculosis infection among household contacts of smear positive pulmonary tuberculosis patients in South India.

OBJECTIVE: We aimed to determine the prevalence and find the risk factors associated with latent tuberculosis infection (LTBI) among the household contacts (HHC) of pulmonary TB patients. METHODS: This cohort study was conducted from 2014 to 2019. Pretested standardised questionnaires and tools were used for data collection. The prevalence of LTBI among HHCs of TB patients was summarised as proportion with 95% confidence interval (CI). Mixed-effects generalised linear modelling function (meglm) in STATA with family Poisson and log link was performed to find the factors associated with LTBI. RESULTS: In total, 1523 HHC of pulmonary TB patients were included in the study. Almost all HHC shared their residence with the index case (IC) for more than a year; 25% shared the same bed with the IC. The prevalence of LTBI among the HHC of TB patients was 52.6% (95% CI: 50.1-55.1%). In an adjusted model, we found that among HHC belonging to the age group of 19-64 years (aIRR = 1.2; 95% CI: 1.1-1.3; p-value: 0.02), to the age group >65 years (aIRR = 1.4, 95% CI: 1.1-1.9, p-value: 0.02) and sharing the same bed with the IC (aIRR = 1.2, 95% CI: 1.1-1.3, p value: 0.04) were independent determinants of LTBI among the HHC. CONCLUSION: One in two household contacts of TB patients have latent tuberculosis infection. This underscores the need of targeted contact screening strategies, effective contact tracing and testing using standardised methods in high TB burden settings.

Tuberculosis-Learning the Impact of Nutrition (TB LION): protocol for an interventional study to decrease TB risk in household contacts.

BACKGROUND: Comorbidities such as undernutrition and parasitic infections are widespread in India and other tuberculosis (TB)-endemic countries. This study examines how these conditions as well as food supplementation and parasite treatment might alter immune responses to Mycobacterium tuberculosis (Mtb) infection and risk of progression to TB disease. METHODS: This is a 5-year prospective clinical trial at Jawaharlal Institute of Post Graduate Medical Education and Research in Puducherry, Tamil Nadu, India. We aim to enroll 760 household contacts (HHC) of adults with active TB in order to identify 120 who are followed prospectively for 2 years: Thirty QuantiFERON-TB Gold Plus (QFT-Plus) positive HHCs ≥ 18 years of age in four proposed groups: (1) undernourished (body mass index [BMI] < 18.5 kg/m2); (2) participants with a BMI ≥ 18.5 kg/m2 who have a parasitic infection (3) undernourished participants with a parasitic infection and (4) controls-participants with BMI ≥ 18.5 kg/m2 and without parasitic infection. We assess immune response at baseline and after food supplementation (for participants with BMI < 18.5 kg/m2) and parasite treatment (for participants with parasites). Detailed nutritional assessments, anthropometry, and parasite testing through polymerase chain reaction (PCR) and microscopy are performed. In addition, at serial time points, these samples will be further analyzed using flow cytometry and whole blood transcriptomics to elucidate the immune mechanisms involved in disease progression. CONCLUSIONS: This study will help determine whether undernutrition and parasite infection are associated with gene signatures that predict risk of TB and whether providing nutritional supplementation and/or treating parasitic infections improves immune response towards this infection. This study transcends individual level care and presents the opportunity to benefit the population at large by analyzing factors that affect disease progression potentially reducing the overall burden of people who progress to TB disease. Trial registration ClinicalTrials.gov; NCT03598842; Registered on July 26, 2018; https://clinicaltrials.gov/ct2/show/NCT03598842.

Comparing tuberculosis gene signatures in malnourished individuals using the TBSignatureProfiler.

BACKGROUND: Gene expression signatures have been used as biomarkers of tuberculosis (TB) risk and outcomes. Platforms are needed to simplify access to these signatures and determine their validity in the setting of comorbidities. We developed a computational profiling platform of TB signature gene sets and characterized the diagnostic ability of existing signature gene sets to differentiate active TB from LTBI in the setting of malnutrition. METHODS: We curated 45 existing TB-related signature gene sets and developed our TBSignatureProfiler software toolkit that estimates gene set activity using multiple enrichment methods and allows visualization of single- and multi-pathway results. The TBSignatureProfiler software is available through Bioconductor and on GitHub. For evaluation in malnutrition, we used whole blood gene expression profiling from 23 severely malnourished Indian individuals with TB and 15 severely malnourished household contacts with latent TB infection (LTBI). Severe malnutrition was defined as body mass index (BMI) < 16 kg/m2 in adults and based on weight-for-height Z scores in children < 18 years. Gene expression was measured using RNA-sequencing. RESULTS: The comparison and visualization functions from the TBSignatureProfiler showed that TB gene sets performed well in malnourished individuals; 40 gene sets had statistically significant discriminative power for differentiating TB from LTBI, with area under the curve ranging from 0.662-0.989. Three gene sets were not significantly predictive. CONCLUSION: Our TBSignatureProfiler is a highly effective and user-friendly platform for applying and comparing published TB signature gene sets. Using this platform, we found that existing gene sets for TB function effectively in the setting of malnutrition, although differences in gene set applicability exist. RNA-sequencing gene sets should consider comorbidities and potential effects on diagnostic performance.

A Parsimonious Host Inflammatory Biomarker Signature Predicts Incident Tuberculosis and Mortality in Advanced Human Immunodeficiency Virus.

BACKGROUND: People with advanced human immunodeficiency virus (HIV) (CD4 < 50) remain at high risk of tuberculosis (TB) or death despite the initiation of antiretroviral therapy (ART). We aimed to identify immunological profiles that were most predictive of incident TB disease and death. METHODS: The REMEMBER randomized clinical trial enrolled 850 participants with HIV (CD4 < 50 cells/µL) at ART initiation to receive either empiric TB treatment or isoniazid preventive therapy (IPT). A case-cohort study (n = 257) stratified by country and treatment arm was performed. Cases were defined as incident TB or all-cause death within 48 weeks after ART initiation. Using multiplexed immunoassay panels and ELISA, 26 biomarkers were assessed in plasma. RESULTS: In total, 52 (6.1%) of 850 participants developed TB; 47 (5.5%) died (13 of whom had antecedent TB). Biomarkers associated with incident TB overlapped with those associated with death (interleukin [IL]-1ß, IL-6). Biomarker levels declined over time in individuals with incident TB while remaining persistently elevated in those who died. Dividing the cohort into development and validation sets, the final model of 6 biomarkers (CXCL10, IL-1ß, IL-10, sCD14, tumor necrosis factor [TNF]-α, and TNF-ß) achieved a sensitivity of 0.90 (95% confidence interval [CI]: .87-.94) and a specificity of 0.71(95% CI: .68-.75) with an area under the curve (AUC) of 0.81 (95% CI: .78-.83) for incident TB. CONCLUSION: Among people with advanced HIV, a parsimonious inflammatory biomarker signature predicted those at highest risk for developing TB despite initiation of ART and TB preventive therapies. The signature may be a promising stratification tool to select patients who may benefit from increased monitoring and novel interventions. CLINICAL TRIALS REGISTRATION: NCT01380080.

Using Cure Models to Estimate the Serial Interval of Tuberculosis With Limited Follow-up.

Serial interval (SI), defined as the time between symptom onset in an infector and infectee pair, is commonly used to understand infectious diseases transmission. Slow progression to active disease, as well as the small percentage of individuals who will eventually develop active disease, complicate the estimation of the SI for tuberculosis (TB). In this paper, we showed via simulation studies that when there is credible information on the percentage of those who will develop TB disease following infection, a cure model, first introduced by Boag in 1949, should be used to estimate the SI for TB. This model includes a parameter in the likelihood function to account for the study population being composed of those who will have the event of interest and those who will never have the event. We estimated the SI for TB to be approximately 0.5 years for the United States and Canada (January 2002 to December 2006) and approximately 2.0 years for Brazil (March 2008 to June 2012), which might imply a higher occurrence of reinfection TB in a developing country like Brazil.

Evaluation of a Rapid Molecular Drug-Susceptibility Test for Tuberculosis.

BACKGROUND: Fluoroquinolones and second-line injectable drugs are the backbone of treatment regimens for multidrug-resistant tuberculosis, and resistance to these drugs defines extensively drug-resistant tuberculosis. We assessed the accuracy of an automated, cartridge-based molecular assay for the detection, directly from sputum specimens, of Mycobacterium tuberculosis with resistance to fluoroquinolones, aminoglycosides, and isoniazid. METHODS: We conducted a prospective diagnostic accuracy study to compare the investigational assay against phenotypic drug-susceptibility testing and DNA sequencing among adults in China and South Korea who had symptoms of tuberculosis. The Xpert MTB/RIF assay and sputum culture were performed. M. tuberculosis isolates underwent phenotypic drug-susceptibility testing and DNA sequencing of the genes katG, gyrA, gyrB, and rrs and of the eis and inhA promoter regions. RESULTS: Among the 308 participants who were culture-positive for M. tuberculosis, when phenotypic drug-susceptibility testing was used as the reference standard, the sensitivities of the investigational assay for detecting resistance were 83.3% for isoniazid (95% confidence interval [CI], 77.1 to 88.5), 88.4% for ofloxacin (95% CI, 80.2 to 94.1), 87.6% for moxifloxacin at a critical concentration of 0.5 µg per milliliter (95% CI, 79.0 to 93.7), 96.2% for moxifloxacin at a critical concentration of 2.0 µg per milliliter (95% CI, 87.0 to 99.5), 71.4% for kanamycin (95% CI, 56.7 to 83.4), and 70.7% for amikacin (95% CI, 54.5 to 83.9). The specificity of the assay for the detection of phenotypic resistance was 94.3% or greater for all drugs except moxifloxacin at a critical concentration of 2.0 µg per milliliter (specificity, 84.0% [95% CI, 78.9 to 88.3]). When DNA sequencing was used as the reference standard, the sensitivities of the investigational assay for detecting mutations associated with resistance were 98.1% for isoniazid (95% CI, 94.4 to 99.6), 95.8% for fluoroquinolones (95% CI, 89.6 to 98.8), 92.7% for kanamycin (95% CI, 80.1 to 98.5), and 96.8% for amikacin (95% CI, 83.3 to 99.9), and the specificity for all drugs was 99.6% (95% CI, 97.9 to 100) or greater. CONCLUSIONS: This investigational assay accurately detected M. tuberculosis mutations associated with resistance to isoniazid, fluoroquinolones, and aminoglycosides and holds promise as a rapid point-of-care test to guide therapeutic decisions for patients with tuberculosis. (Funded by the National Institute of Allergy and Infectious Diseases, National Institutes of Health, and the Ministry of Science and Technology of China; ClinicalTrials.gov number, NCT02251327 .).

Interaction of nutritional status and diabetes on active and latent tuberculosis: a cross-sectional analysis.

BACKGROUND: Malnutrition and diabetes are risk factors for active tuberculosis (TB), possible risk factors for latent TB infection (LTBI), and may interact to alter their effect on these outcomes. Studies to date have not investigated this interaction. METHODS: We enrolled 919 newly diagnosed active TB patients and 1113 household contacts at Primary Health Centres in Puducherry and Tamil Nadu, India from 2014 to 2018. In cross-sectional analyses, we used generalized estimating equations to measure additive and multiplicative interaction of body mass index (BMI) and diabetes on two outcomes, active TB and LTBI. RESULTS: Among overweight or obese adults, active TB prevalence was 12-times higher in diabetic compared to non-diabetic participants, 2.5-times higher among normal weight adults, and no different among underweight adults (P for interaction < 0.0001). Diabetes was associated with 50 additional active TB cases per 100 overweight or obese participants, 56 per 100 normal weight participants, and 17 per 100 underweight participants (P for interaction < 0.0001). Across BMI categories, screening 2.3-3.8 active TB patients yielded one hyperglycemic patient. LTBI prevalence did not differ by diabetes and BMI*diabetes interaction was not significant. CONCLUSIONS: BMI and diabetes are associated with newly diagnosed active TB, but not LTBI. Diabetes conferred the greatest risk of active TB in overweight and obese adults whereas the burden of active TB associated with diabetes was similar for normal and overweight or obese adults. Hyperglycemia was common among all active TB patients. These findings highlight the importance of bi-directional diabetes-active TB screening in India.

Ambroxol Induces Autophagy and Potentiates Rifampin Antimycobacterial Activity.

Host-directed therapy in tuberculosis is a potential adjunct to antibiotic chemotherapy directed at Mycobacterium tuberculosis Ambroxol, a lead compound, emerged from a screen for autophagy-inducing drugs. At clinically relevant doses, ambroxol induced autophagy in vitro and in vivo and promoted mycobacterial killing in macrophages. Ambroxol also potentiated rifampin activity in a murine tuberculosis model.

Intensity of exposure to pulmonary tuberculosis determines risk of tuberculosis infection and disease.

Household contacts of pulmonary tuberculosis (TB) patients are at increased risk of TB infection and disease. However, their risk in relation to the intensity of exposure remains unknown.We studied smear-positive TB cases and their household contacts in Vitória, Brazil. We collected clinical, demographic and radiographic information from TB cases, and obtained tuberculin skin test (TST) and QuantiFERON-TB Gold (QFT) results from household contacts. We measured intensity of exposure using a proximity score and sleep location in relation to the TB index case and defined infection by TST ≥10 mm or QFT ≥0.35 UI·mL-1 We ascertained secondary TB cases by reviewing local and nationwide case registries.We included 160 TB index cases and 894 household contacts. 464 (65%) had TB infection and 23 (2.6%) developed TB disease. Risk of TB infection and disease increased with more intense exposures. In an adjusted analysis, the proximity score was associated with TB disease (OR 1.61, 95% CI 1.25-2.08; p<0.000); however, its diagnostic performance was only moderate.Intensity of exposure increased risk of TB infection and disease among household contacts; however, its diagnostic performance was still suboptimal. A biomarker to target preventive therapy is urgently needed in this at-risk population.

"Tuberculosis in advanced HIV infection is associated with increased expression of IFNγ and its downstream targets".

BACKGROUND: Tuberculosis (TB) is the major cause of death in Human Immunodeficiency Virus (HIV)-infected individuals. However, diagnosis of TB in HIV remains challenging particularly when HIV infection is advanced. Several gene signatures and serum protein biomarkers have been identified that distinguish active TB from latent infection. Our study was designed to assess if gene expression signatures and cytokine levels would distinguish active TB in advanced HIV. METHODS: We conducted a case-control study of whole blood RNA-Seq and plasma cytokine/chemokine analysis in HIV-infected with CD4+ T cell count of ≤ 100 cells/µl, with and without active TB. Next, the overlap of the differentially expressed genes (DEG) with the published signatures was performed and then receiver operator characteristic (ROC) analysis was done on small gene discriminators to determine their performance in distinguishing TB in advanced HIV. ELISA was performed on plasma to evaluate cytokine and chemokine levels. RESULTS: Hierarchical clustering of the transcriptional profiles showed that, in general, HIV-infected individuals with TB (TB-HIV) clustered separately from those without TB. IPA indicated that the TB-HIV signature was characterized by an increase in inflammatory signaling pathways. Analysis of overlaps between DEG in our data set with published TB signatures revealed that significant overlap was seen with one TB signature and one TB-IRIS signature. ROC analysis revealed that transcript levels of FcGR1A (AUC = 0.85) and BATF2 (AUC = 0.82), previously reported as consistent single gene classifiers of active TB irrespective of HIV status, performed successfully even in advanced HIV. Plasma protein levels of IFNγ, a stimulator of FcGR1A and BATF2, and CXCL10, also up-regulated by IFNγ, accurately classified active TB (AUC = 0.98 and 0.91, respectively) in advanced HIV. Neither of these genes nor proteins distinguished between TB and TB-IRIS. CONCLUSIONS: Gene expression of FcGR1A and BATF2, and plasma protein levels of IFNγ and CXCL10 have the potential to independently detect TB in advanced HIV. However, since other lung diseases were not included in this study, these final candidates need to be validated as specific to TB in the advanced HIV population with TB.

A Comparative Analysis of Pulmonary and Critical Care Medicine Guideline Development Methodologies.

RATIONALE: The Institute of Medicine (IOM) standards for guideline development have had unintended negative consequences. A more efficient approach is desirable. OBJECTIVES: To determine whether a modified Delphi process early during guideline development discriminates recommendations that should be informed by a systematic review from those that can be based upon expert consensus. METHODS: The same questions addressed by IOM-compliant pulmonary or critical care guidelines were addressed by expert panels using a modified Delphi process, termed the Convergence of Opinion on Recommendations and Evidence (CORE) process. The resulting recommendations were compared. Concordance of the course of action, strength of recommendation, and quality of evidence, as well as the duration of recommendation development, were measured. MEASUREMENTS AND MAIN RESULTS: When 50% agreement was required to make a recommendation, all questions yielded recommendations, and the recommended courses of action were 89.6% concordant. When 70% agreement was required, 17.9% of questions did not yield recommendations, but for those that did, the recommended courses of action were 98.2% concordant. The time to completion was shorter for the CORE process (median, 19.3 vs. 1,309.0 d; P = 0.0002). CONCLUSIONS: We propose the CORE process as an early step in guideline creation. Questions for which 70% agreement on a recommendation cannot be achieved should go through an IOM-compliant process; however, questions for which 70% agreement on a recommendation can be achieved can be accepted, avoiding a lengthy systematic review.

Extensions to Bayesian generalized linear mixed effects models for household tuberculosis transmission.

Household contact studies, a mainstay of tuberculosis transmission research, often assume that tuberculosis-infected household contacts of an index case were infected within the household. However, strain genotyping has provided evidence against this assumption. Understanding the household versus community infection dynamic is essential for designing interventions. The misattribution of infection sources can also bias household transmission predictor estimates. We present a household-community transmission model that estimates the probability of community infection, that is, the probability that a household contact of an index case was actually infected from a source outside the home and simultaneously estimates transmission predictors. We show through simulation that our method accurately predicts the probability of community infection in several scenarios and that not accounting for community-acquired infection in household contact studies can bias risk factor estimates. Applying the model to data from Vitória, Brazil, produced household risk factor estimates similar to two other standard methods for age and sex. However, our model gave different estimates for sleeping proximity to index case and disease severity score. These results show that estimating both the probability of community infection and household transmission predictors is feasible and that standard tuberculosis transmission models likely underestimate the risk for two important transmission predictors. Copyright © 2017 John Wiley & Sons, Ltd.