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.

Improving Clinician Awareness of and Screening for Chagas Disease with an Educational Intervention.

Chagas disease is an underrecognized, chronic, and potentially life-threatening disease caused by the parasite Trypanosoma cruzi. We aimed to improve awareness and screening for Chagas disease among patients from endemic areas using a large safety-net academic hospital system in the United States. We developed an educational intervention consisting of a case-based didactic session presented to physicians, trainees, and other healthcare providers at conferences across different departments. Performance on a knowledge assessment administered before and after the presentation was analyzed with paired Student's t-test for within-subject difference testing. Institutional testing rates for T. cruzi were evaluated for an equal time period (29 months) before and after the start of the intervention. Testing rates were compared by a Welch's unequal variances t-test and by interrupted time series based on multivariate linear regression. Eleven educational sessions were held over the intervention period, and 103 participants completed the pre- and post-presentation surveys. The mean survey scores were 59.2% before the presentation and 96.6% after presentation (P <0.001). Trypanosoma cruzi testing during the postintervention period was significantly higher than testing during the pre-intervention period (171 patients pre-intervention versus 378 patients postintervention [P = 0.015]). Notable increases in testing from the pre-intervention to postintervention periods occurred among midwives (1-68 patients tested) and trainees (57-133 patients tested). Overall, 56/537 (10.4%) nonduplicate T. cruzi commercial screening tests were positive. Testing increased over time, both at an institutional level and within targeted departments. In addition to the educational program, other factors likely influenced expanded testing.

Chagas cardiomyopathy in Boston, Massachusetts: Identifying disease and improving management after community and hospital-based screening.

BACKGROUND: Limited data exist regarding cardiac manifestations of Chagas disease in migrants living in non-endemic regions. METHODS: A retrospective cohort analysis of 109 patients with Chagas disease seen at Boston Medical Center (BMC) between January 2016 and January 2023 was performed. Patients were identified by screening and testing migrants from endemic regions at a community health center and BMC. Demographic, laboratory, and cardiac evaluation data were collected. RESULTS: Mean age of the 109 patients was 43 years (range 19-76); 61% were female. 79% (86/109) were diagnosed with Chagas disease via screening and 21% (23/109) were tested given symptoms or electrocardiogram abnormalities. Common symptoms included palpitations (25%, 27/109) and chest pain (17%, 18/109); 52% (57/109) were asymptomatic. Right bundle branch block (19%, 19/102), T-wave changes (18%, 18/102), and left anterior fascicular block (11%, 11/102) were the most common electrocardiogram abnormalities; 51% (52/102) had normal electrocardiograms. Cardiomyopathy stage was ascertained in 94 of 109 patients: 51% (48/94) were indeterminate stage A and 49% (46/94) had cardiac structural disease (stages B1-D). Clinical findings that required clinical intervention or change in management were found in 23% (25/109), and included cardiomyopathy, apical hypokinesis/aneurysm, stroke, atrial or ventricular arrhythmias, and apical thrombus. CONCLUSIONS: These data show high rates of cardiac complications in a cohort of migrants living with Chagas disease in a non-endemic setting. We demonstrate that Chagas disease diagnosis prompts cardiac evaluation which often identifies actionable cardiac disease and provides opportunities for prevention and treatment.

Inclusion, Diversity, Access, and Equity in Infectious Diseases Fellowship Training: Tools for Program Directors.

The Infectious Diseases Society of America (IDSA) has set clear priorities in recent years to promote inclusion, diversity, access, and equity (IDA&E) in infectious disease (ID) clinical practice, medical education, and research. The IDSA IDA&E Task Force was launched in 2018 to ensure implementation of these principles. The IDSA Training Program Directors Committee met in 2021 and discussed IDA&E best practices as they pertain to the education of ID fellows. Committee members sought to develop specific goals and strategies related to recruitment, clinical training, didactics, and faculty development. This article represents a presentation of ideas brought forth at the meeting in those spheres and is meant to serve as a reference document for ID training program directors seeking guidance in this area.

Not business as usual: Engaging the corporate sector in India's TB elimination efforts.

India has the highest global burden of tuberculosis (TB), accounting for a quarter of the worldwide TB disease incidence. Given the magnitude of India's epidemic, TB has enormous economic implications. Indeed, the majority of individuals with TB disease are in their prime years of economic productivity. Absenteeism and employee turnover due to TB have economic ramifications for employers. Furthermore, TB can easily spread in the workplace and compound the economic impact. Employers who fund workplace, community, or national TB initiatives stand to gain directly and also enjoy reputational benefits, which are important in the era of socially conscious investing. Corporate social responsibility laws in India and tax incentives can be leveraged to bring the logistical networks, reach, and innovative spirit of the private sector to bear on India's formidable TB epidemic. In this perspective piece, we explore the economic impacts of TB; opportunities for and benefits from businesses contributing to TB elimination efforts; and strategies to enlist India's corporate sector in the fight against TB.

Heterogeneity in Vaccinal Immunity to SARS-CoV-2 Can Be Addressed by a Personalized Booster Strategy.

SARS-CoV-2 vaccinations were initially shown to substantially reduce risk of severe disease and death. However, pharmacokinetic (PK) waning and rapid viral evolution degrade neutralizing antibody (nAb) binding titers, causing loss of vaccinal protection. Additionally, there is inter-individual heterogeneity in the strength and durability of the vaccinal nAb response. Here, we propose a personalized booster strategy as a potential solution to this problem. Our model-based approach incorporates inter-individual heterogeneity in nAb response to primary SARS-CoV-2 vaccination into a pharmacokinetic/pharmacodynamic (PK/PD) model to project population-level heterogeneity in vaccinal protection. We further examine the impact of evolutionary immune evasion on vaccinal protection over time based on variant fold reduction in nAb potency. Our findings suggest viral evolution will decrease the effectiveness of vaccinal protection against severe disease, especially for individuals with a less durable immune response. More frequent boosting may restore vaccinal protection for individuals with a weaker immune response. Our analysis shows that the ECLIA RBD binding assay strongly predicts neutralization of sequence-matched pseudoviruses. This may be a useful tool for rapidly assessing individual immune protection. Our work suggests vaccinal protection against severe disease is not assured and identifies a potential path forward for reducing risk to immunologically vulnerable individuals.

Vaccines Alone Cannot Slow the Evolution of SARS-CoV-2.

The rapid emergence of immune-evading viral variants of SARS-CoV-2 calls into question the practicality of a vaccine-only public-health strategy for managing the ongoing COVID-19 pandemic. It has been suggested that widespread vaccination is necessary to prevent the emergence of future immune-evading mutants. Here, we examined that proposition using stochastic computational models of viral transmission and mutation. Specifically, we looked at the likelihood of emergence of immune escape variants requiring multiple mutations and the impact of vaccination on this process. Our results suggest that the transmission rate of intermediate SARS-CoV-2 mutants will impact the rate at which novel immune-evading variants appear. While vaccination can lower the rate at which new variants appear, other interventions that reduce transmission can also have the same effect. Crucially, relying solely on widespread and repeated vaccination (vaccinating the entire population multiple times a year) is not sufficient to prevent the emergence of novel immune-evading strains, if transmission rates remain high within the population. Thus, vaccines alone are incapable of slowing the pace of evolution of immune evasion, and vaccinal protection against severe and fatal outcomes for COVID-19 patients is therefore not assured.

Comparison of IGRA and TST in the diagnosis of latent tuberculosis among women of reproductive age in South India.

BACKGROUND: Latent tuberculosis infection (LTBI) is a mycobacterial infection defined on the basis of cellular immune response to mycobacterial antigens. The tuberculin skin test (TST) and the Interferon-Gamma Release Assay (IGRA) are the two tests currently used to establish the diagnosis of LTB. Literature suggests that a study regarding tuberculosis (TB) infection among women of reproductive age group is limited. METHODS: Female household contact, married, aged 18-49 years underwent written consent form and are screened for LTBI using the TST and IGRA. Participants are injected with TST [5 tuberculin unit (TU), purified protein derivative (PPD)] and IGRA [QuantiFERON®-TB Gold Plus kit (QFT-Plus)]. All the household contacts were followed-up for one year for incident TB cases. Statistical analysis was done using STATA version 14 (StataCorp., Texas, USA). Cohen's kappa test was used to determine the agreement between two tests. RESULTS: The prevalence of LTBI was found to be 69% (either TST or IGRA positive). Positivity rate of IGRA was higher when compared to that of TST. Out of 139 participants, 68 (49%) tested positive for TST, 80 (57.6%) tested positive for IGRA and 52 (37.4%) tested positive for both. Discordant results were observed in about two fifth of the study population and there was poor agreement between the two tests. CONCLUSION: Longitudinal studies are required to detect incident TB cases to evaluate the usefulness of these tests. The study was found that IGRA is more consistent to diagnosis of latent tuberculosis infection than the TST. Such studies can also be performed in varied settings among different populations which would help us to improve the diagnosis of LTBI and consequently help in TB control.

Chagas Disease.

Chagas disease, which is caused by infection with the parasite Trypanosoma cruzi, is a leading neglected tropical disease in the United States. An estimated 240 000 to 350 000 persons in the United States are infected, primarily immigrants from Mexico, Central America, and South America, where the disease is endemic. The parasite is transmitted by the triatomine bug but can also be passed through blood transfusion, via organ transplant, or congenitally. Approximately 30% of infected persons later develop cardiac and/or gastrointestinal complications. Health care providers should consider screening at-risk patients with serologic testing. Early diagnosis and treatment with benznidazole or nifurtimox can help prevent complications.

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

Rationale: Many blood-based transcriptional gene signatures for tuberculosis (TB) have been developed with potential use to diagnose disease, predict risk of progression from infection to disease, and monitor TB treatment outcomes. However, an unresolved issue is whether gene set enrichment analysis (GSEA) of the signature transcripts alone is sufficient for prediction and differentiation, or whether it is necessary to use the original statistical model created when the signature was derived. Intra-method comparison is complicated by the unavailability of original training data, missing details about the original trained model, and inadequate publicly-available software tools or source code implementing models. To facilitate these signatures' replicability and appropriate utilization in TB research, comprehensive comparisons between gene set scoring methods with cross-data validation of original model implementations are needed. Objectives: We compared the performance of 19 TB gene signatures across 24 transcriptomic datasets using both re-rebuilt original models and gene set scoring methods to evaluate whether gene set scoring is a reasonable proxy to the performance of the original trained model. We have provided an open-access software implementation of the original models for all 19 signatures for future use. Methods: We considered existing gene set scoring and machine learning methods, including ssGSEA, GSVA, PLAGE, Singscore, and Zscore, as alternative approaches to profile gene signature performance. The sample-size-weighted mean area under the curve (AUC) value was computed to measure each signature's performance across datasets. Correlation analysis and Wilcoxon paired tests were used to analyze the performance of enrichment methods with the original models. Measurement and Main Results: For many signatures, the predictions from gene set scoring methods were highly correlated and statistically equivalent to the results given by the original diagnostic models. PLAGE outperformed all other gene scoring methods. 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 blood-based biomarker gene sets can distinguish patients with active TB disease from latent TB infection and 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.

Performance of three screening tools to predict COVID-19 positivity in emergency department patients.

BACKGROUND: COVID-19 symptoms vary widely. This retrospective study assessed which of three clinical screening tools-a nursing triage screen (NTS), an ED review of systems (ROS) performed by physicians and physician assistants and a standardised ED attending (ie, consultant) physician COVID-19 probability assessment (PA)-best identified patients with COVID-19 on a subsequent reverse transcription PCR (RT-PCR) confirmation. METHODS: All patients admitted to Boston Medical Center from the ED between 27 April 2020 and 17 May 2020 were included. Sensitivity, specificity and positive predictive value (PPV) and negative predictive value (NPV) were calculated for each method. Logistic regression assessed each tool's performance. RESULTS: The attending physician PA had higher sensitivity (0.62, 95% CI 0.53 to 0.71) than the NTS (0.46, 95% CI 0.37 to 0.56) and higher specificity (0.76, 95% CI 0.72 to 0.80) than the NTS (0.71, 95% CI 0.66 to 0.75) and ED ROS (0.62, 95% CI 0.58 to 0.67). Categorisation as moderate or high probability on the ED physician PA was associated with the highest odds of having COVID-19 in regression analyses (adjusted OR=4.61, 95% CI 3.01 to 7.06). All methods had a low PPV (ranging from 0.26 for the ED ROS to 0.40 for the attending physician PA) and a similar NPV (0.84 for both the NTS and the ED ROS, and 0.89 for the attending physician PA). CONCLUSION: The ED attending PA had higher sensitivity and specificity than the other two methods, but none was accurate enough to replace a COVID-19 RT-PCR test in a clinical setting where transmission control is crucial. Therefore, we recommend universal COVID-19 testing prior to all admissions.

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.

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.

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.

Accuracy of Timika X-ray scoring system to predict the treatment outcomes among tuberculosis patients in India.

BACKGROUND: Timika scoring system is a radiographic grading tool, widely employed for grading the severity of tuberculosis (TB). We evaluated the predictive accuracy of this tool for adverse treatment outcomes among TB patients in Indian setting. METHODS: We undertook a longitudinal analysis of cohort data under the RePORT-India consortium. Cohort having participants with active pulmonary TB were included. CXRs were independently scored by chest physicians. Timika scoring system had a total score of 140. The predictive nature of the tool was assessed using the ROC analysis. RESULTS: Around 364 laboratory confirmed TB patients were enrolled. The mean (SD) of overall Timika score was 62.3 (24.9). Sputum conversion was achieved among 218/260 (83.8%) patients available at end of intensive phase. AUC for Timika score was 0.53 (95% CI: 0.43-0.63) and for percent lung affected, was 0.56 (95% CI: 0.46-0.65). Unfavorable treatment outcome was observed among 67/287 (23.3%) at the end of continuation phase. AUC for percent lung affected was 0.62 (95% CI: 0.54-0.70) and for Timika score was 0.59 (95% CI: 0.51-0.67). CONCLUSION: Both Timika scoring system and percent lung affected had poor predictive accuracy, highlighting the inability of a single CXR scoring system to predict the treatment outcome in Indian setting.

No magic bullet: Limiting in-school transmission in the face of variable SARS-CoV-2 viral loads.

In the face of a long-running pandemic, understanding the drivers of ongoing SARS-CoV-2 transmission is crucial for the rational management of COVID-19 disease burden. Keeping schools open has emerged as a vital societal imperative during the pandemic, but in-school transmission of SARS-CoV-2 can contribute to further prolonging the pandemic. In this context, the role of schools in driving SARS-CoV-2 transmission acquires critical importance. Here we model in-school transmission from first principles to investigate the effectiveness of layered mitigation strategies on limiting in-school spread. We examined the effect of masks and air quality (ventilation, filtration and ionizers) on steady-state viral load in classrooms, as well as on the number of particles inhaled by an uninfected person. The effectiveness of these measures in limiting viral transmission was assessed for variants with different levels of mean viral load (ancestral, Delta, Omicron). Our results suggest that a layered mitigation strategy can be used effectively to limit in-school transmission, with certain limitations. First, poorly designed strategies (insufficient ventilation, no masks, staying open under high levels of community transmission) will permit in-school spread even if some level of mitigation is present. Second, for viral variants that are sufficiently contagious, it may be difficult to construct any set of interventions capable of blocking transmission once an infected individual is present, underscoring the importance of other measures. Our findings provide practical recommendations; in particular, the use of a layered mitigation strategy that is designed to limit transmission, with other measures such as frequent surveillance testing and smaller class sizes (such as by offering remote schooling options to those who prefer it) as needed.

Corrigendum: Malnutrition leads to increased inflammation and expression of tuberculosis risk signatures in recently exposed household contacts of pulmonary tuberculosis.

[This corrects the article DOI: 10.3389/fimmu.2022.1011166.].

Malnutrition leads to increased inflammation and expression of tuberculosis risk signatures in recently exposed household contacts of pulmonary tuberculosis.

Background: Most individuals exposed to Mycobacterium tuberculosis (Mtb) develop latent tuberculosis infection (LTBI) and remain at risk for progressing to active tuberculosis disease (TB). Malnutrition is an important risk factor driving progression from LTBI to TB. However, the performance of blood-based TB risk signatures in malnourished individuals with LTBI remains unexplored. The aim of this study was to determine if malnourished and control individuals had differences in gene expression, immune pathways and TB risk signatures. Methods: We utilized data from 50 tuberculin skin test positive household contacts of persons with TB - 18 malnourished participants (body mass index [BMI] < 18.5 kg/m2) and 32 controls (individuals with BMI ≥ 18.5 kg/m2). Whole blood RNA-sequencing was conducted to identify differentially expressed genes (DEGs). Ingenuity Pathway Analysis was applied to the DEGs to identify top canonical pathways and gene regulators. Gene enrichment methods were then employed to score the performance of published gene signatures associated with progression from LTBI to TB. Results: Malnourished individuals had increased activation of inflammatory pathways, including pathways involved in neutrophil activation, T-cell activation and proinflammatory IL-1 and IL-6 cytokine signaling. Consistent with known association of inflammatory pathway activation with progression to TB disease, we found significantly increased expression of the RISK4 (area under the curve [AUC] = 0.734) and PREDICT29 (AUC = 0.736) progression signatures in malnourished individuals. Conclusion: Malnourished individuals display a peripheral immune response profile reflective of increased inflammation and a concomitant increased expression of risk signatures predicting progression to TB. With validation in prospective clinical cohorts, TB risk biomarkers have the potential to identify malnourished LTBI for targeted therapy.