Host and pathogen factors that influence variability of Mycobacterium tuberculosis lipid body content in sputum from patients with tuberculosis: an observational study.

BACKGROUND: High proportions of Mycobacterium tuberculosis cells in sputum containing triacylglycerol-rich lipid bodies have been shown to be associated with treatment failure or relapse following antituberculous chemotherapy. Although lipid body determination is a potential biomarker for supporting clinical trial and treatment decisions, factors influencing variability in sputum frequencies of lipid body-positive (%LB+) M tuberculosis in patients are unknown. We aimed to test our hypothesis that exposure to host-generated NO and M tuberculosis strains are factors associated with differences in sputum %LB+. METHODS: In this observational study, we determined %LB+ frequencies before treatment by microscopy in patients with smear-positive tuberculosis from two separate prospective observational study settings (Gondar, Ethiopia, recruited between May 1, 2010, and April 30, 2011, and Fajara, The Gambia, who provided sputum samples before treatment between May 5, 2010, and Dec 22, 2011). In Ethiopia, fractional exhaled nitric oxide (FeNO) was measured as a biomarker of host NO, and M tuberculosis strain differences were determined by spoligotyping. Treatment response was assessed by percentage weight change after 7 months. In The Gambia, treatment responses were assessed as change in BMI and radiographic burden of disease after 6 months. Sputum M tuberculosis isolates were studied in vitro for their %LB+ and triacylglycerol synthase 1 (tgs1) mRNA responses to NO exposure. Propidium iodide staining was used as a measure of NO strain toxicity. Correlation between in vitro %LB+ frequencies following NO exposure and those of the same strain in sputum was examined with linear regression and Dunnett's multiple comparison test. FINDINGS: In Ethiopia, 73 patients who were smear positive for pulmonary tuberculosis were recruited (43 [59%] were male and 30 [41%] were female). Of these, the %LB+ in the sputum of 59 patients showed linear correlation with log10 FeNO (r2=0·28; p<0·0001) and an association with strain spoligotype was suggested. Seven M tuberculosis strains from The Gambia showed different dose-responses to NO in vitro, demonstrated by changing lipid body content, tgs1 transcription, and bacterial toxicity. In sputum %LB+ frequencies correlated with in vitro %LB+ responses to NO of the corresponding isolate. In a subset of 34 patients across both cohorts, higher sputum %LB+ frequencies before treatment were associated with weaker responses to treatment than lower sputum %LB+ frequencies. INTERPRETATION: M tuberculosis strain and exposure to host-generated NO are associated with sputum %LB+. Our results support the use of M tuberculosis strain-dependent sputum %LB+ as a predictive biomarker of treatment response. FUNDING: The Medical Research Council, the University of Leicester, and the University of Gondar.

A structural and metabolic framework for classifying pre-clinical tuberculosis infection phenotypes using 18F-FDG PET-CT: a prospective cohort analysis following M. tuberculosis exposure.

Tuberculosis (TB) control efforts are limited by ineffective characterisation of tuberculosis infection (TBI) -a heterogeneous spectrum of pre-clinical infection states, invisible to tools of routine clinical screening, that are associated with variable risk of progression to TB disease. In this prospective study, we use positron emission tomography-CT (PET-CT) as a high-resolution imaging modality to characterise and classify structural and metabolic features observed in 16 asymptomatic household TB contacts with normal chest radiographs. We identify four feature patterns that associate with distinct clinical and microbiological outcomes, supporting potential utility of PET-CT for objective classification of TBI phenotypes.

State-of-the-art detection of Mycobacterium tuberculosis in blood during tuberculosis infection using phage technology.

Tuberculosis (TB), an aerosol-transmitted infection caused by Mycobacterium tuberculosis (Mtb), remains the commonest cause of death globally, from an infectious bacterial disease. Nine years on from the launch of the World Health Organization (WHO)'s END-TB strategy, disease incidence rates are stubbornly unchanged [1]. While this represents, in part, a reversal of improving trends caused by the COVID-19 pandemic, it also reflects the fragility and inadequacy of healthcare systems to sustain TB control [2]. Although multifactorial, a key reason for this is the ineffectiveness of existing clinical tools to meet the two key objectives of the END-TB strategy-(i) early diagnosis and treatment of TB disease (to limit onward transmission); and (ii) disease prevention through screening for asymptomatic TB infection (TBI). Meeting both objectives will rely on the development of new biomarkers with high accuracy, but the global nature of the TB problem also requires that new tests are rapid, low cost and can be measured in patients by sampling from universally accessible sites. In this review, we will present the accumulating evidence for circulating Mtb in both TB disease and asymptomatic TBI and discuss the potential utility of novel bacteriophage-based technology for blood-based detection of Mtb.

Interferon-gamma release assay conversion after Mycobacterium tuberculosis exposure specifically associates with greater risk of progression to tuberculosis: A prospective cohort study in Leicester, UK.

OBJECTIVES: We investigated whether quantifying the serial QuantiFERON-TB Gold (QFT) response improves tuberculosis (TB) risk stratification in pulmonary TB (PTB) contacts. METHODS: A total of 297 untreated adult household PTB contacts, QFT tested at baseline and 3 months after index notification, were prospectively observed (median 1460 days). Normal variance of serial QFT responses was established in 46 extrapulmonary TB contacts. This informed categorisation of the response in QFT-positive PTB contacts as converters, persistently QFT-positive with significant increase (PPincrease), and without significant increase (PPno-increase). RESULTS: In total, eight co-prevalent TB (disease ≤3 months after index notification) and 12 incident TB (>3 months after index notification) cases were diagnosed. Genetic linkage to the index strain was confirmed in all culture-positive progressors. The cumulative 2-year incident TB risk in QFT-positive contacts was 8.4% (95% confidence interval, 3.0-13.6%); stratifying by serial QFT response, significantly higher risk was observed in QFT converters (28%), compared with PPno-increase (4.8%) and PPincrease (3.7%). Converters were characterised by exposure to index cases with a shorter interval from symptom onset to diagnosis (median reduction 50.0 days, P = 0.013). CONCLUSIONS: QFT conversion, rather than quantitative changes of a persistently positive serial QFT response, is associated with greater TB risk and exposure to rapidly progressive TB.

Prognostication of co-morbidity clusters on hospitalisation and mortality in advanced COPD.

RATIONALE: As the prevalence of multimorbidity increases, understanding the impact of isolated comorbidities in people COPD becomes increasingly challenging. A simplified model of common comorbidity patterns may improve outcome prediction and allow targeted therapy. OBJECTIVES: To assess whether comorbidity phenotypes derived from routinely collected clinical data in people with COPD show differences in risk of hospitalisation and mortality. METHODS: Twelve clinical measures related to common comorbidities were collected during annual reviews for people with advanced COPD and k-means cluster analysis performed. Cox proportional hazards with adjustment for covariates was used to determine hospitalisation and mortality risk between clusters. MEASUREMENTS AND MAIN RESULTS: In 203 participants (age 66 ± 9 years, 60 % male, FEV1%predicted 31 ± 10 %) no comorbidity in isolation was predictive of worse admission or mortality risk. Four clusters were described: cluster A (cardiometabolic and anaemia), cluster B (malnourished and low mood), cluster C (obese, metabolic and mood disturbance) and cluster D (less comorbid). FEV1%predicted did not significantly differ between clusters. Mortality risk was higher in cluster A (HR 3.73 [95%CI 1.09-12.82] p = 0.036) and B (HR 3.91 [95%CI 1.17-13.14] p = 0.027) compared to cluster D. Time to admission was highest in cluster A (HR 2.01 [95%CI 1.11-3.63] p = 0.020). Cluster C was not associated with increased risk of mortality or hospitalisation. CONCLUSIONS: Despite presence of advanced COPD, we report striking differences in prognosis for both mortality and hospital admissions for different co-morbidity phenotypes. Objectively assessing the multi-system nature of COPD could lead to improved prognostication and targeted therapy for patients.

PET-CT-guided characterisation of progressive, preclinical tuberculosis infection and its association with low-level circulating Mycobacterium tuberculosis DNA in household contacts in Leicester, UK: a prospective cohort study.

BACKGROUND: Incipient tuberculosis, a progressive state of Mycobacterium tuberculosis infection with an increased risk of developing into tuberculosis disease, remains poorly characterised. Animal models suggest an association of progressive infection with bacteraemia. Circulating M tuberculosis DNA has previously been detected in pulmonary tuberculosis by use of Actiphage, a bacteriophage-based real-time PCR assay. We aimed to investigate whether serial [18F]fluorodeoxyglucose ([18F]FDG)-PET-CT could be used to characterise the state and progressive trajectory of incipient tuberculosis, and examine whether these PET-CT findings are associated with Actiphage-based detection of circulating M tuberculosis DNA. METHODS: We did a prospective 12-month cohort study in healthy, asymptomatic adults (aged ≥16 years) who were household contacts of patients with pulmonary tuberculosis, and who had a clinical phenotype of latent tuberculosis infection, in Leicester, UK. Actiphage testing of participants' blood samples was done at baseline, and [18F]FDG PET-CT at baseline and after 3 months. Baseline PET-CT features were classified as positive, indeterminate, or negative, on the basis of the quantitation (maximum standardised uptake value [SUVmax]) and distribution of [18F]FDG uptake. Microbiological sampling was done at amenable sites of [18F]FDG uptake. Changes in [18F]FDG uptake after 3 months were quantitatively categorised as progressive, stable, or resolving. Participants received treatment if features of incipient tuberculosis, defined as microbiological detection of M tuberculosis or progressive PET-CT change, were identified. FINDINGS: 20 contacts were recruited between Aug 5 and Nov 5, 2020; 16 of these participants had a positive result on IFNγ release assay (QuantiFERON-TB Gold Plus [QFT]) indicating tuberculosis infection. Baseline PET-CT scans were positive in ten contacts (all QFT positive), indeterminate in six contacts (three QFT positive), and negative in four contacts (three QFT positive). Four of eight PET-CT-positive contacts sampled had M tuberculosis identified (three through culture, one through Xpert MTB/RIF Ultra test) from intrathoracic lymph nodes or bronchial wash and received full antituberculosis treatment. Two further unsampled PET-CT-positive contacts were also treated: one with [18F]FDG uptake in the lung (SUVmax 9·4) received empirical antituberculosis treatment and one who showed progressive [18F]FDG uptake received preventive treatment. The ten untreated contacts with [18F]FDG uptake at baseline (seven QFT positive) had stable or resolving changes at follow-up and remained free of tuberculosis disease after 12 months. A positive baseline Actiphage test was associated with the presence of features of incipient tuberculosis requiring treatment (p=0·018). INTERPRETATION: Microbiological and inflammatory features of incipient tuberculosis can be visualised on PET-CT and are associated with M tuberculosis detection in the blood, supporting the development of pathogen-directed blood biomarkers of tuberculosis risk. FUNDING: MRC Confidence in Concept.

A data-driven framework for clinical decision support applied to pneumonia management.

Despite their long history, it can still be difficult to embed clinical decision support into existing health information systems, particularly if they utilise machine learning and artificial intelligence models. Moreover, when such tools are made available to healthcare workers, it is important that the users can understand and visualise the reasons for the decision support predictions. Plausibility can be hard to achieve for complex pathways and models and perceived "black-box" functionality often leads to a lack of trust. Here, we describe and evaluate a data-driven framework which moderates some of these issues and demonstrate its applicability to the in-hospital management of community acquired pneumonia, an acute respiratory disease which is a leading cause of in-hospital mortality world-wide. We use the framework to develop and test a clinical decision support tool based on local guideline aligned management of the disease and show how it could be used to effectively prioritise patients using retrospective analysis. Furthermore, we show how this tool can be embedded into a prototype clinical system for disease management by integrating metrics and visualisations. This will assist decision makers to examine complex patient journeys, risk scores and predictions from embedded machine learning and artificial intelligence models. Our results show the potential of this approach for developing, testing and evaluating workflow based clinical decision support tools which include complex models and embedding them into clinical systems.

PET-CT for characterising TB infection (TBI) in immunocompetent subjects: a systematic review.

Introduction. There is emerging evidence of a potential role for PET-CT scan as an imaging biomarker to characterise the spectrum of tuberculosis infection (TBI) in humans and animal models.Gap Statement. Synthesis of available evidence from current literature is needed to understand the utility of PET-CT for characterising TBI and how this may inform application of PET-CT in future TBI research.Aim. The aims of this review are to summarise the evidence of PET-CT scan use in immunocompetent hosts with TBI, and compare PET-CT features observed in humans and animal models.Methodology. MEDLINE, Embase and PubMed Central were searched to identify relevant publications. Studies were selected if they reported PET-CT features in human or animals with TBI. Studies were excluded if immune deficiency was present at the time of the initial PET-CT scan.Results. Six studies - four in humans and two in non-human primates (NHP) were included for analysis. All six studies used 2-deoxy-2-[18F]fluoro-d-glucose (2-[18F]FDG) PET-CT. Features of TBI were comparable between NHP and humans, with 2-[18F]FDG avid intrathoracic lymph nodes observed during early infection. Progressive TBI was characterised in NHP by increasing 2-[18F]FDG avidity and size of lesions. Two human studies suggested that PET-CT can discriminate between active TB and inactive TBI. However, data synthesis was generally limited by human studies including inconsistent and poorly characterised cohorts and the small number of eligible studies for review.Conclusion. Our review provides some evidence, limited primarily to non-human primate models, of PET-CT utility as a highly sensitive imaging modality to reveal and characterise meaningful metabolic and structural change in early TBI. The few human studies identified exhibit considerable heterogeneity. Larger prospective studies are needed recruiting well characterised cohorts with TBI and adopting a standardized PET-CT protocol, to better understand utility of this imaging biomarker to support future research.

Vulnerability and tuberculosis treatment outcomes in urban settings in England: A mixed-methods study.

BACKGROUND: Evidence on factors contributing to poor treatment outcome and healthcare priorities in vulnerable populations affected by tuberculosis (TB) in urban areas of England other than London is needed to inform setting-specific prevention and care policies. We addressed this knowledge gap in a cohort of TB patients and healthcare providers in Birmingham and Leicester, UK. METHODS: A mixed-methods study was performed. Logistic regression was used to identify TB patients more likely to have poor treatment outcomes according to clinical and demographic characteristics and social risk factors (SRFs) in a 2013-18 cohort. 25 semi-structured interviews were undertaken in purposely selected individuals (9 patients and 16 healthcare professionals) to glean insights on their healthcare priorities and the factors that contribute to poor treatment outcome. RESULTS: The quantitative cohort comprised 2252 patients. Those who were ≥ 55 years of age, foreign-born from Central Europe, East Asia and Sub Saharan Africa and with MDR-TB were more likely to have poor treatment outcomes. According to patients and healthcare professionals, the factors that contribute to vulnerability to develop TB and poor treatment outcomes include poor working and living conditions, inadequate or absent welfare protection, poor primary healthcare responsiveness, treatment duration and side effects. These factors could be addressed by increased networking, partnership and integration between healthcare and social services and better integration between primary and secondary healthcare. CONCLUSIONS: In both cities, being ≥ 55 years of age, having MDR-TB and being of foreign-birth are predictors of unfavourable treatment outcome. Risk of poor treatment outcome and vulnerability seem to be multidimensional. A better understanding of specific vulnerabilities and how they affect patient care pathway is needed to design adequate support programmes.

Exhaled Mycobacterium tuberculosis Predicts Incident Infection in Household Contacts.

BACKGROUND: Halting transmission of Mycobacterium tuberculosis (Mtb) by identifying infectious individuals early is key to eradicating tuberculosis (TB). Here we evaluate face mask sampling as a tool for stratifying the infection risk of individuals with pulmonary TB (PTB) to their household contacts. METHODS: Forty-six sputum-positive PTB patients in The Gambia (August 2016-November 2017) consented to mask sampling prior to commencing treatment. Incident Mtb infection was defined in 181 of their 217 household contacts as QuantiFERON conversion or an increase in interferon-γ of ≥1 IU/mL, 6 months after index diagnosis. Multilevel mixed-effects logistical regression analysis with cluster adjustment by household was used to identify predictors of incident infection. RESULTS: Mtb was detected in 91% of PTB mask samples with high variation in IS6110 copies (5.3 × 102 to 1.2 × 107). A high mask Mtb level (≥20 000 IS6110 copies) was observed in 45% of cases and was independently associated with increased likelihood of incident Mtb infection in contacts (adjusted odds ratio, 3.20 [95% confidence interval, 1.26-8.12]; P = .01), compared with cases having low-positive/negative mask Mtb levels. Mask Mtb level was a better predictor of incident Mtb infection than sputum bacillary load, chest radiographic characteristics, or sleeping proximity. CONCLUSIONS: Mask sampling offers a sensitive and noninvasive tool to support the stratification of individuals who are most infectious in high-TB-burden settings. Our approach can provide better insight into community transmission in complex environments.

Demographic and Clinical Determinants of Tuberculosis and TB Recurrence: A Double-Edged Retrospective Study from Pakistan.

Objective: TB recurrence is the second episode of TB after initial treatment bringing about an additional 7% load in TB burden intensified by 17.7% of multidrug-resistant recurrent cases. It is necessary to curb recurrence so that attempts to deal with active disease can be made more effective. This study aimed to characterize sociodemographic and clinical factors associated with recurrent TB in a high-burden setting. Methodology. A retrospective case-control study was carried out at two hospitals in Rawalpindi, Pakistan. TB patients and controls were included in the study. Sociodemographic and clinical data were collected by questionnaire from all subjects. Multivariate regression analysis was performed to determine factors associated with TB and TB recurrence respectively. Results: In our study cohort, factors significantly associated with TB were low BMI (OR: 0.961 (CI 0.954-0.968), p < 0.001), female gender (OR: 2.065 (CI 1.922-2.219), p < 0.001), being single/unmarried (OR: 1.214 (CI 1.109-1.328), p=0.003), middle-income status (OR: 1.935 (CI 1.616-2.323), p < 0.001), smoking (OR: 1.567 (CI 1.435-1.710), p < 0.001), and diabetes mellitus (OR: 1.142 (CI 1.017-1.278), p=0.023). TB recurrence constituted 11.2% of patients presenting to the hospital. Compared with the first episode of TB, cases with recurrence were more likely to be older (OR: 1.011 (CI 1.004-1.017), p < 0.001), have disease awareness (OR: 1.906 (CI 1.486-2.437), p < 0.001), smear positive (OR: 2.384 (CI 1.650-3.536), p < 0.001), and be drug-resistant (OR: 5.615 (CI 4.265-7.386), p < 0.001). Conclusion: In the present study cohort, low BMI, female gender, being single, middle-income status, being unemployed, smoking, and being diabetic came out to be the sociodemographic and clinical risk factors for TB. Further exploring the TB cases increasing age, drug resistance and smear positivity stood out to be the major sociodemographic and clinical factors of TB recurrence despite high disease awareness.

Discriminatory Ability of Gas Chromatography-Ion Mobility Spectrometry to Identify Patients Hospitalized With COVID-19 and Predict Prognosis.

Background: Rapid diagnostic and prognostic tests for coronavirus disease (COVID-19) are urgently required. We aimed to evaluate the diagnostic and prognostic ability of breath analysis using gas chromatography-ion mobility spectrometry (GC-IMS) in hospitalized patients with COVID-19. Methods: Between February and May 2021, we took 1 breath sample for analysis using GC-IMS from participants who were admitted to the hospital for COVID-19, participants who were admitted to the hospital for other respiratory infections, and symptom-free controls, at the University Hospitals of Leicester NHS Trust, United Kingdom. Demographic, clinical, and radiological data, including requirement for continuous positive airway pressure (CPAP) ventilation as a marker for severe disease in the COVID-19 group, were collected. Results: A total of 113 participants were recruited into the study. Seventy-two (64%) were diagnosed with COVID-19, 20 (18%) were diagnosed with another respiratory infection, and 21 (19%) were healthy controls. Differentiation between participants with COVID-19 and those with other respiratory tract infections with GC-IMS was highly accurate (sensitivity/specificity, 0.80/0.88; area under the receiver operating characteristics curve [AUROC], 0.85; 95% CI, 0.74-0.96). GC-IMS was also moderately accurate at identifying those who subsequently required CPAP (sensitivity/specificity, 0.62/0.80; AUROC, 0.70; 95% CI, 0.53-0.87). Conclusions: GC-IMS shows promise as both a diagnostic tool and a predictor of prognosis in hospitalized patients with COVID-19 and should be assessed further in larger studies.

A Persistent Tuberculosis Outbreak in the UK Is Characterized by Hydrophobic fadB4-Deficient Mycobacterium tuberculosis That Replicates Rapidly in Macrophages.

The genetic diversity of Mycobacterium tuberculosis can influence disease severity and transmissibility. To better understand how this diversity influences individuals and communities, we phenotyped M. tuberculosis that was causing a persistent outbreak in the East Midlands, United Kingdom. Compared to nonoutbreak isolates, bacilli had higher lipid contents and more hydrophobic cell surfaces. In macrophage infection models, the bacteria increased more rapidly, provoked the enhanced accumulation of macrophage lipid droplets and enhanced the secretion of IL-1ß. Natural deletions in fadB4, nrdB, and plcC distinguished the outbreak isolates from other lineage 3 isolates in the region. fadB4 is annotated with a putative role in cell envelope biosynthesis, so the loss of this gene has the potential to alter the interactions of bacteria with immune cells. Reintroduction of fadB4 to the outbreak strain led to a phenotype that more closely resembled those of nonoutbreak strains. The improved understanding of the microbiological characteristics and the corresponding genetic polymorphisms that associate with outbreaks have the potential to inform tuberculosis control. IMPORTANCE Tuberculosis (TB) killed 1.5 million people in 2020 and affects every country. The extent to which the natural genetic diversity of Mycobacterium tuberculosis influences disease manifestation at both the individual and epidemiological levels remains poorly understood. Insights into how pathogen polymorphisms affect patterns of TB have the potential to translate into clinical and public health practice. Two distinct lineage 3 strains isolated from local TB outbreaks, one of which (CH) was rapidly terminated and the other of which (Lro) persistently transmitted for over a decade, provided us with an opportunity to study these issues. We compared genome sequences, microbiological characteristics, and early immune responses that were evoked upon infection. Our results indicate that the natural lack of fadB4 in the Lro strain contributes to its unique features.

Clinical prediction models for mortality in patients with covid-19: external validation and individual participant data meta-analysis.

OBJECTIVE: To externally validate various prognostic models and scoring rules for predicting short term mortality in patients admitted to hospital for covid-19. DESIGN: Two stage individual participant data meta-analysis. SETTING: Secondary and tertiary care. PARTICIPANTS: 46 914 patients across 18 countries, admitted to a hospital with polymerase chain reaction confirmed covid-19 from November 2019 to April 2021. DATA SOURCES: Multiple (clustered) cohorts in Brazil, Belgium, China, Czech Republic, Egypt, France, Iran, Israel, Italy, Mexico, Netherlands, Portugal, Russia, Saudi Arabia, Spain, Sweden, United Kingdom, and United States previously identified by a living systematic review of covid-19 prediction models published in The BMJ, and through PROSPERO, reference checking, and expert knowledge. MODEL SELECTION AND ELIGIBILITY CRITERIA: Prognostic models identified by the living systematic review and through contacting experts. A priori models were excluded that had a high risk of bias in the participant domain of PROBAST (prediction model study risk of bias assessment tool) or for which the applicability was deemed poor. METHODS: Eight prognostic models with diverse predictors were identified and validated. A two stage individual participant data meta-analysis was performed of the estimated model concordance (C) statistic, calibration slope, calibration-in-the-large, and observed to expected ratio (O:E) across the included clusters. MAIN OUTCOME MEASURES: 30 day mortality or in-hospital mortality. RESULTS: Datasets included 27 clusters from 18 different countries and contained data on 46 914patients. The pooled estimates ranged from 0.67 to 0.80 (C statistic), 0.22 to 1.22 (calibration slope), and 0.18 to 2.59 (O:E ratio) and were prone to substantial between study heterogeneity. The 4C Mortality Score by Knight et al (pooled C statistic 0.80, 95% confidence interval 0.75 to 0.84, 95% prediction interval 0.72 to 0.86) and clinical model by Wang et al (0.77, 0.73 to 0.80, 0.63 to 0.87) had the highest discriminative ability. On average, 29% fewer deaths were observed than predicted by the 4C Mortality Score (pooled O:E 0.71, 95% confidence interval 0.45 to 1.11, 95% prediction interval 0.21 to 2.39), 35% fewer than predicted by the Wang clinical model (0.65, 0.52 to 0.82, 0.23 to 1.89), and 4% fewer than predicted by Xie et al's model (0.96, 0.59 to 1.55, 0.21 to 4.28). CONCLUSION: The prognostic value of the included models varied greatly between the data sources. Although the Knight 4C Mortality Score and Wang clinical model appeared most promising, recalibration (intercept and slope updates) is needed before implementation in routine care.

Blood transcriptomics reveal the evolution and resolution of the immune response in tuberculosis.

Blood transcriptomics have revealed major characteristics of the immune response in active TB, but the signature early after infection is unknown. In a unique clinically and temporally well-defined cohort of household contacts of active TB patients that progressed to TB, we define minimal changes in gene expression in incipient TB increasing in subclinical and clinical TB. While increasing with time, changes in gene expression were highest at 30 d before diagnosis, with heterogeneity in the response in household TB contacts and in a published cohort of TB progressors as they progressed to TB, at a bulk cohort level and in individual progressors. Blood signatures from patients before and during anti-TB treatment robustly monitored the treatment response distinguishing early and late responders. Blood transcriptomics thus reveal the evolution and resolution of the immune response in TB, which may help in clinical management of the disease.