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Blood transcriptomics analysis of tuberculosis has revealed an interferon-inducible gene signature that diminishes in expression after successful treatment; this promises improved diagnostics and treatment monitoring, which are essential for the eradication of tuberculosis. Sensitive radiography revealing lung abnormalities and blood transcriptomics have demonstrated heterogeneity in patients with active tuberculosis and exposed asymptomatic people with latent tuberculosis, suggestive of a continuum of infection and immune states. Here we describe the immune response to infection with Mycobacterium tuberculosis revealed through the use of transcriptomics, as well as differences among clinical phenotypes of infection that might provide information on temporal changes in host immunity associated with evolving infection. We also review the diverse blood transcriptional signatures, composed of small sets of genes, that have been proposed for the diagnosis of tuberculosis and the identification of at-risk asymptomatic people and suggest novel approaches for the development of such biomarkers for clinical use. O’Garra and colleagues describe the immune response to infection with Mycobacterium tuberculosis revealed through the use of transcriptomics and the value of blood transcriptional gene signatures for the diagnosis of tuberculosis.

T cells are involved in control of coronavirus disease 2019 (COVID-19), but limited knowledge is available on the relationship between antigen-specific T cell response and disease severity. Here, we used flow cytometry to assess the magnitude, function, and phenotype of SARS coronavirus 2-specific (SARS-CoV-2-specific) CD4+ T cells in 95 hospitalized COVID-19 patients, 38 of them being HIV-1 and/or tuberculosis (TB) coinfected, and 38 non-COVID-19 patients. We showed that SARS-CoV-2-specific CD4+ T cell attributes, rather than magnitude, were associated with disease severity, with severe disease being characterized by poor polyfunctional potential, reduced proliferation capacity, and enhanced HLA-DR expression. Moreover, HIV-1 and TB coinfection skewed the SARS-CoV-2 T cell response. HIV-1-mediated CD4+ T cell depletion associated with suboptimal T cell and humoral immune responses to SARS-CoV-2, and a decrease in the polyfunctional capacity of SARS-CoV-2-specific CD4+ T cells was observed in COVID-19 patients with active TB. Our results also revealed that COVID-19 patients displayed reduced frequency of Mycobacterium tuberculosis-specific CD4+ T cells, with possible implications for TB disease progression. These results corroborate the important role of SARS-CoV-2-specific T cells in COVID-19 pathogenesis and support the concept of altered T cell functions in patients with severe disease.

Background Although mainly causing a respiratory syndrome, numerous neurological symptoms have been identified following of SARS-CoV-2 infection. However, how the virus affects the brain and how the mutations carried by the different variants modulate those neurological symptoms remain unclear. Methods We used primary human pericytes, foetal astrocytes, endothelial cells and a microglial cell line to investigate the effect of several SARS-CoV-2 variants of concern or interest on their functional activities. Cells and a 3D blood–brain barrier model were infected with the wild-type form of SARS-CoV-2, Alpha, Beta, Delta, Eta, or Omicron (BA.1) variants at various MOI. Cells and supernatant were used to evaluate cell susceptibility to the virus using a microscopic assay as well as effects of infection on (i) cell metabolic activity using a colorimetric MTS assay; (ii) viral cytopathogenicity using the xCELLigence system; (iii) extracellular glutamate concentration by fluorometric assay; and (iv) modulation of blood–brain barrier permeability. Results We demonstrate that productive infection of brain cells is SARS-CoV-2 variant dependent and that all the variants induce stress to CNS cells. The wild-type virus was cytopathic to all cell types except astrocytes, whilst Alpha and Beta variants were only cytopathic for pericytes, and the Omicron variant cytopathic for endothelial cells and pericytes. Lastly wild-type virus increases blood–brain barrier permeability and all variants, except Beta, modulate extracellular glutamate concentration, which can lead to excitotoxicity or altered neurotransmission. Conclusions These results suggest that SARS-CoV-2 is neurotropic, with deleterious consequences for the blood–brain barrier integrity and central nervous system cells, which could underlie neurological disorders following SARS-CoV-2 infection.

New approaches to define factors underlying the immunopathogenesis of pulmonary diseases including sarcoidosis and tuberculosis are needed to develop new treatments and biomarkers. Comparing the blood transcriptional response of tuberculosis to other similar pulmonary diseases will advance knowledge of disease pathways and help distinguish diseases with similar clinical presentations. To determine the factors underlying the immunopathogenesis of the granulomatous diseases, sarcoidosis and tuberculosis, by comparing the blood transcriptional responses in these and other pulmonary diseases. We compared whole blood genome-wide transcriptional profiles in pulmonary sarcoidosis, pulmonary tuberculosis, to community acquired pneumonia and primary lung cancer and healthy controls, before and after treatment, and in purified leucocyte populations. An Interferon-inducible neutrophil-driven blood transcriptional signature was present in both sarcoidosis and tuberculosis, with a higher abundance and expression in tuberculosis. Heterogeneity of the sarcoidosis signature correlated significantly with disease activity. Transcriptional profiles in pneumonia and lung cancer revealed an over-abundance of inflammatory transcripts. After successful treatment the transcriptional activity in tuberculosis and pneumonia patients was significantly reduced. However the glucocorticoid-responsive sarcoidosis patients showed a significant increase in transcriptional activity. 144-blood transcripts were able to distinguish tuberculosis from other lung diseases and controls. Tuberculosis and sarcoidosis revealed similar blood transcriptional profiles, dominated by interferon-inducible transcripts, while pneumonia and lung cancer showed distinct signatures, dominated by inflammatory genes. There were also significant differences between tuberculosis and sarcoidosis in the degree of their transcriptional activity, the heterogeneity of their profiles and their transcriptional response to treatment.

A major impediment to tuberculosis control in Africa is the difficulty in diagnosing active tuberculosis (TB), particularly in the context of HIV infection. We hypothesized that a unique host blood RNA transcriptional signature would distinguish TB from other diseases (OD) in HIV-infected and -uninfected patients, and that this could be the basis of a simple diagnostic test. Adult case-control cohorts were established in South Africa and Malawi of HIV-infected or -uninfected individuals consisting of 584 patients with either TB (confirmed by culture of Mycobacterium tuberculosis [M.TB] from sputum or tissue sample in a patient under investigation for TB), OD (i.e., TB was considered in the differential diagnosis but then excluded), or healthy individuals with latent TB infection (LTBI). Individuals were randomized into training (80%) and test (20%) cohorts. Blood transcriptional profiles were assessed and minimal sets of significantly differentially expressed transcripts distinguishing TB from LTBI and OD were identified in the training cohort. A 27 transcript signature distinguished TB from LTBI and a 44 transcript signature distinguished TB from OD. To evaluate our signatures, we used a novel computational method to calculate a disease risk score (DRS) for each patient. The classification based on this score was first evaluated in the test cohort, and then validated in an independent publically available dataset (GSE19491). In our test cohort, the DRS classified TB from LTBI (sensitivity 95%, 95% CI [87-100]; specificity 90%, 95% CI [80-97]) and TB from OD (sensitivity 93%, 95% CI [83-100]; specificity 88%, 95% CI [74-97]). In the independent validation cohort, TB patients were distinguished both from LTBI individuals (sensitivity 95%, 95% CI [85-100]; specificity 94%, 95% CI [84-100]) and OD patients (sensitivity 100%, 95% CI [100-100]; specificity 96%, 95% CI [93-100]). Limitations of our study include the use of only culture confirmed TB patients, and the potential that TB may have been misdiagnosed in a small proportion of OD patients despite the extensive clinical investigation used to assign each patient to their diagnostic group. In our study, blood transcriptional signatures distinguished TB from other conditions prevalent in HIV-infected and -uninfected African adults. Our DRS, based on these signatures, could be developed as a test for TB suitable for use in HIV endemic countries. Further evaluation of the performance of the signatures and DRS in prospective populations of patients with symptoms consistent with TB will be needed to define their clinical value under operational conditions. Please see later in the article for the Editors' Summary.

Antiretroviral therapy reduces the risk of tuberculosis, but tuberculosis is more common in people with HIV than in people without HIV. We aimed to assess the effect of isoniazid preventive therapy on the risk of tuberculosis in people infected with HIV-1 concurrently receiving antiretroviral therapy. For this pragmatic randomised double-blind, placebo-controlled trial in Khayelitsha, South Africa, we randomly assigned (1:1) patients to receive either isoniazid preventive therapy or a placebo for 12 months (could be completed during 15 months). Randomisation was done with random number generator software. Participants, physicians, and pharmacy staff were masked to group assignment. The primary endpoint was time to development of incident tuberculosis (definite, probable, or possible). We excluded tuberculosis at screening by sputum culture. We did a modified intention-to-treat analysis and excluded all patients randomly assigned to groups who withdrew before receiving study drug or whose baseline sputum culture results suggested prevalent tuberculosis. This study is registered with ClinicalTrials.gov, number NCT00463086. 1329 participants were randomly assigned to receive isoniazid preventive therapy (n=662) or placebo (n=667) between Jan 31, 2008, and Sept 31, 2011, and contributed 3227 person-years of follow-up to the analysis. We recorded 95 incident cases of tuberculosis; 37 were in the isoniazid preventive therapy group (2·3 per 100 person-years, 95% CI 1·6–3·1), and 58 in the placebo group (3·6 per 100 person-years, 2·8–4·7; hazard ratio [HR] 0·63, 95% CI 0·41–0·94). Study drug was discontinued because of grade 3 or 4 raised alanine transaminase concentrations in 19 of 662 individuals in the isoniazid preventive therapy group and ten of the 667 individuals in the placebo group (risk ratio 1·9, 95% CI 0·90–4·09). We noted no evidence that the effect of isoniazid preventive therapy was restricted to patients who were positive on tuberculin skin test or interferon gamma release assay (adjusted HR for patients with negative tests 0·43 [0·21–0·86] and 0·43 [0·20–0·96]; for positive tests 0·86 [0·37–2·00] and 0·55 [0·26–1·24], respectively). Without a more predictive test or a multivariate algorithm that predicts benefit, isoniazid preventive therapy should be recommended to all patients receiving antiretroviral therapy in moderate or high incidence areas irrespective of tuberculin skin test or interferon gamma release assay status. Department of Health of South Africa, the Wellcome Trust, Médecins Sans Frontières, European and Developing Countries Clinical Trials Partnership, Foundation for Innovation and New Diagnostics, the European Union, and Hasso Plattner (Institute of Infectious Diseases and Molecular Medicine, University of Cape Town).

We aimed to assess whether interferon-γ release assays (IGRAs) can predict the development of active tuberculosis and whether the predictive ability of these tests is better than that of the tuberculin skin test (TST). Longitudinal studies of the predictive value for active tuberculosis of in-house or commercial IGRAs were identified through searches of PubMed, Embase, Biosis, and Web of Science and complementary manual searches up to June 30, 2011. Eligible studies included adults or children, with or without HIV, who were free of active tuberculosis at study baseline. We summarised incidence rates in forest plots and pooled data with random-effects models when appropriate. We calculated incidence rate ratios (IRR) for rates of disease progression in IGRA-positive versus IGRA-negative individuals. 15 studies had a combined sample size of 26 680 participants. Incidence of tuberculosis during a median follow-up of 4 years (IQR 2–6), even in IGRA-positive individuals, was 4–48 cases per 1000 person-years. Seven studies with no possibility of incorporation bias and reporting baseline stratification on the basis of IGRA results showed a moderate association between positive results and subsequent tuberculosis (pooled unadjusted IRR 2·10, 95% CI 1·42–3·08). Compared with test-negative results, IGRA-positive and TST-positive results were much the same with regard to the risk of tuberculosis (pooled IRR in the five studies that used both was 2·11 [95% CI 1·29–3·46] for IGRA vs 1·60 [0·94–2·72] for TST at the 10 mm cutoff). However, the proportion of IGRA-positive individuals in seven of 11 studies that assessed both IGRAs and TST was generally lower than TST-positive individuals. Neither IGRAs nor the TST have high accuracy for the prediction of active tuberculosis, although use of IGRAs in some populations might reduce the number of people considered for preventive treatment. Until more predictive biomarkers are identified, existing tests for latent tuberculosis infection should be chosen on the basis of relative specificity in different populations, logistics, cost, and patients' preferences rather than on predictive ability alone. Special Programme for Research and Training in Tropical Diseases (WHO), Wellcome Trust, Canadian Institutes of Health Research, UK Medical Research Council, and the European and Developing Countries Clinical Trials Partnership.

Whole blood transcriptional signatures distinguishing active tuberculosis patients from asymptomatic latently infected individuals exist. Consensus has not been achieved regarding the optimal reduced gene sets as diagnostic biomarkers that also achieve discrimination from other diseases. Here we show a blood transcriptional signature of active tuberculosis using RNA-Seq, confirming microarray results, that discriminates active tuberculosis from latently infected and healthy individuals, validating this signature in an independent cohort. Using an advanced modular approach, we utilise the information from the entire transcriptome, which includes overabundance of type I interferon-inducible genes and underabundance of IFNG and TBX21 , to develop a signature that discriminates active tuberculosis patients from latently infected individuals or those with acute viral and bacterial infections. We suggest that methods targeting gene selection across multiple discriminant modules can improve the development of diagnostic biomarkers with improved performance. Finally, utilising the modular approach, we demonstrate dynamic heterogeneity in a longitudinal study of recent tuberculosis contacts. Mass screening diagnostics for Mycobacterium tuberculosis exist, but criticisms exist regarding the sensitivity and specificity of these tools. Here the authors use RNA-Seq and a modular bioinformatics approach using data from their own cohorts and meta-analysis of published cohorts to create a reduced signature for detection of tuberculosis that does not detect other diseases.

Globally there are approximately 9 million new active tuberculosis cases and 1.4 million deaths annually. Effective antituberculosis treatment monitoring is difficult as there are no existing biomarkers of poor adherence or inadequate treatment earlier than 2 months after treatment initiation. Inadequate treatment leads to worsening disease, disease transmission and drug resistance. To determine if blood transcriptional signatures change in response to antituberculosis treatment and could act as early biomarkers of a successful response. Blood transcriptional profiles of untreated active tuberculosis patients in South Africa were analysed before, during (2 weeks and 2 months), at the end of (6 months) and after (12 months) antituberculosis treatment, and compared to individuals with latent tuberculosis. An active-tuberculosis transcriptional signature and a specific treatment-response transcriptional signature were derived. The specific treatment response transcriptional signature was tested in two independent cohorts. Two quantitative scoring algorithms were applied to measure the changes in the transcriptional response. The most significantly represented pathways were determined using Ingenuity Pathway Analysis. An active tuberculosis 664-transcript signature and a treatment specific 320-transcript signature significantly diminished after 2 weeks of treatment in all cohorts, and continued to diminish until 6 months. The transcriptional response to treatment could be individually measured in each patient. Significant changes in the transcriptional signatures measured by blood tests were readily detectable just 2 weeks after treatment initiation. These findings suggest that blood transcriptional signatures could be used as early surrogate biomarkers of successful treatment response.

Background Tuberculous meningitis is the most severe form of tuberculosis and HIV-1 co-infection worsens the already poor prognosis. However, how Mycobacterium tuberculosis crosses the blood-brain barrier and how HIV-1 influences tuberculous meningitis pathogenesis remains unclear. Methods Using human pericytes, astrocytes, endothelial cells, and microglia alone and combined in an in vitro blood-brain barrier model, we investigated the effect of Mycobacterium tuberculosis +/- HIV-1 co-infection on central nervous system cell entry and function. Cells and the blood-brain barrier model were infected with Mycobacterium tuberculosis and/or HIV-1 and we evaluated the effects of both infection on (i) cells susceptibility to Mycobacterium tuberculosis and its growth in cells by flow cytometry; (ii) modulation of blood-brain barrier permeability and Mycobacterium tuberculosis passage through it; (iii) viral and bacterial cytopathogenicity using the xCELLigence system; (iv) cell metabolic activity and ROS release using colorimetric assays; (v) extracellular glutamate concentration by fluorometric assay; (vi) the inflammatory response by Luminex; and (vii) endoplasmic reticulum stress by quantitative PCR. Results We demonstrated that Mycobacterium tuberculosis infects and multiplies in all cell types with HIV-1 increasing entry to astrocytes and pericytes, and growth in HIV-1 positive pericytes and endothelial cells. Mycobacterium tuberculosis also induces an increase of the blood-brain barrier permeability resulting in translocation of bacilli across it. Cytopathic effects include (i) increased markers of cellular stress (mitochondrial metabolic activity, unfolded protein response); (ii) ROS release; (iii) the induction of neurotoxic astrocytes; (iv) and the secretion of the excitotoxic neurotransmitter glutamate. Lastly, we observed distinct cell-type specific production of inflammatory and effector mediators. Conclusion These results indicate that Mycobacterium tuberculosis can translocate the blood-brain barrier directly to initiate meningitis.