Whole blood transcriptional profiles of patients with active tuberculosis (TB) and other inflammatory and infectious diseases
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE22098 | GEO | 2010/08/11
SECONDARY ACCESSION(S): PRJNA128917
REPOSITORIES: GEO
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Project description:Tuberculosis (TB), caused by infection with Mycobacterium tuberculosis (M. tuberculosis), is a major cause of morbidity and mortality worldwide and efforts to control TB are hampered by difficulties with diagnosis, prevention and treatment. Most people infected with M. tuberculosis remain asymptomatic, termed latent TB, with a 10% lifetime risk of developing active TB disease, but current tests cannot identify which individuals will develop disease. The immune response to M. tuberculosis is complex and incompletely characterized, hindering development of new diagnostics, therapies and vaccines. The goals of this study include: 1. Identify a transcript signature for active TB in intermediate and high burden settings, correlating with radiological extent of disease and reverting to that of healthy controls following treatment; 2. Identify a specific transcript signature that discriminated active TB from other inflammatory and infectious diseases; 3. Classify TB signature using modular and pathway analysis tools. Three milliliters of whole blood was collected in Tempus tubes from 12 pediatric streptococcus, 40 pediatric staphylococcus, 31 still’s disease, 82 pediatric systemic lupus erythematosus (SLE) and 28 adult SLE patients. RNA was extracted and globin reduced. Labeled cRNA was hybridized to Illumina Human HT-12 Beadchips. Healthy controls were included to match patients’ demographic data. Genespring software was used to analyze active TB transcript signatures, comparing with healthy controls and other inflammatory and infectious diseases.
2010-08-11 | E-GEOD-22098 | biostudies-arrayexpress
Project description:Changes in the blood transcriptome upon treatment were studied in a cohort of 42 latent tuberculosis (TB) subjects and 8 active TB subiects. Samples were collected at diagnosis (prior the start of treatment) and post treatment and gene expression studied with Illumina microarrays. We hypothesize that individuals with latent TB at risk of developing active disease are immunologically closer to those with active TB and will thus display a blood transcriptomic signature similar to active TB subjects upon treatment. This signature should significantly differ from the one mounted by latent TB individuals at low risk of progression. Thus, monitoring blood transcriptomic changes following anti-TB therapy might inform on which latent TB subjects should be prioritized for receiving therapeutic intervention in order to prevent further transmission.
2021-12-08 | GSE152532 | GEO
Project description:This dataset aims to dissect the whole blood transcriptional signature by determining if elements of the whole blood signature are still present in purified cell subpopulations. We aimed to characterise the transcriptional response during TB and identify if cell subsets drove changes in whole blood cellular composition. The aim of the experiment was to define transcriptional signatures in neutrophils, monocytes, CD4+ and CD8+ cells from blood of active TB patients and healthy controls to distinguish the signature of active TB patients from each other and from healthy controls. This will help in the diagnosis of active tuberculosis, which normally relies on culture of the bacilli, which can take up to 6 weeks, sometimes the bacilli cannot be obtained from sputum thus requiring invasive techniques obtaining bronchoalveolar lavage (BAL). In some cases the bacill cannot be grown from sputum or BAL. Experimental design : Whole blood collected in EDTA tubes from patients with active TB disease and healthy controls. Blood was then processed or separated sequentially into neutrophil, monocyte, CD4+ or CD8+ populations and then processed. All patients were sampled prior to the initiation of any antimycobacterial therapy. Active pulmonary TB: PTB - all patients confirmed by isolation of Mycobacterium tuberculosis on culture of sputum or bronchoalvelolar lavage fluid. Healthy controls - these were volunteers without exposure to TB who were negative by both tuberculin skin test (<15mm if BCG vaccinated, <6mm if unvaccinated); who were also negative by IGRA (as described above). This dataset: PTB, n = 7 patients (whole blood, neutrophils, monocytes, CD4+ or CD8+). BCG+, n = 4 patients (whole blood, neutrophils, monocytes, CD4+ or CD8+). Experimental variables : Patient group: Active PTB; Healthy controls (BCG vaccinated only) and Cell populations: Neutrophils, Monocytes, CD4+, CD8+. Ethnicity - a range of ethnic groups is represented.
2010-08-11 | E-GEOD-19443 | biostudies-arrayexpress
Project description:While blood transcriptional profiling has improved diagnosis and understanding of disease pathogenesis of adult tuberculosis (TB), no studies applying gene expression profiling of children with TB have been described so far. In this study, we have compared whole blood gene expression in childhood TB patients, as well as in healthy latently infected (LTBI) and uninfected (HC) children in a cohort of Warao Amerindians in the Delta Amacuro in Venezuela. We identified a 116-gene signature set by means of random forest analysis that showed an average prediction error of 11% for TB vs. LTBI and for TB vs. LTBI vs. HC in our dataset. Furthermore, a minimal set of only 9 genes showed a significant predictive value for all previously published adult studies using whole blood gene expression, with average prediction errors between 17% and 23%. Additionally, a minimal gene set of 42 genes with a comparable predictive value to the 116-gene set in both our dataset and the previously published literature cohorts for the comparsion of TB vs. LTBI vs. HC was identified. In order to identify a robust representative gene set that would hold stand among different ethnic populations, we selected ten genes that were highly discriminative between TB, LTBI and HC in all literature datasets as well as in our dataset. Functional annotation of these ten genes highlights a possible role for genes involved in calcium signaling and calcium metabolism as biomarkers for active TB. These ten genes were validated by quantitative real-time polymerase chain reaction in an additional cohort of 54 Warao Amerindian children with LTBI, HC and non-TB pneumonia. Decision tree analysis indicated that five of the ten genes were sufficient to diagnose 78% of the TB cases correctly with 100% specificity. We conclude that our data justify the further exploration of our signature set as biomarkers to diagnose childhood TB. Furthermore, as the identification of different biomarkers in ethnically distinct cohorts is apparent, it is important to cross-validate newly identified markers in all available cohorts. In this study, 27 children 1 to 15 years of age with TB (n=9), LTBI (n=9) and HC (n=9) were recruited between May 2010 and December 2010. Tuberculin skin test (TST) and QuantiFERON-TB Gold In-Tube assay (QFT-GIT) were performed on all children. A sputum sample was collected from all children with expectoration and a gastric aspirate was taken from all children under 6 years of age. Children with active TB were diagnosed based on culture of M. tuberculosis (n=2) or on the basis of clinical, epidemiological and radiological features (n=7). The latter group were children with a TST = 10 mm or a positive QFT-GIT result who presented all of: persistent fever >38M-BM-0C objectively recorded daily for at least two weeks, persistent cough for more than three weeks, weight loss (>5% reduction in weight compared with the highest weight recorded in last three months) or failure to thrive (documented crossing of percentile lines in the preceding three months), persistent lethargy or decrease in playfulness/activity reported by the parent and absence of clinical response on broad-spectrum antibiotics. Standard antero-posterior and lateral chest radiographs (CXRs) were taken from all children. Two independent experts, blinded to all clinical information, evaluated the CXRs and documented their findings on a standard report form. Where the two objective experts disagreed, a third expert was consulted and final consensus was achieved. A diagnosis of TB was only made when the CXR was consistent with TB9 and the child showed a positive clinical response to anti-TB treatment. Children were followed up clinically, radiologically and, in case of a negative TST at inclusion, by means of TST at six and 12 months after inclusion. LTBI was defined as a TST = 10mm and a positive QFT-GIT with a negative culture result on inclusion in the absence of radiological and clinical evidence of TB disease on inclusion as well as on t=6 and t=12 months. HC were children with a TST = 0 mm at inclusion and at t=6 and t=12 months. The HC had a negative QFT-GIT and a negative culture result at inclusion without radiological or clinical evidence of TB disease on inclusion nor on t=6 and t=12 months. TB patients were sampled before initiation of anti-TB treatment. Of three of the nine TB patients, a follow-up sample was taken when the patient was in anti-TB treatment for five months. All children were HIV-negative. 27 samples in total where analyzed, active TB infection (TB, n=9), Latent TB infection (LTBI, n=9) and healthy controls (HC, n=9) . Gene expression values were log2-transformed and differentially expressed genes were identified based on log2 fold changes (M-values). P values were calculated with a Bayes-regularized one-way ANOVA. Random Forest recursive feature elimination was used to find a signature geneset capable of discrimination active TB from latent TB and from non-infected individuals.
2013-02-05 | E-GEOD-41055 | biostudies-arrayexpress
Project description:Human infection with Mycobacterium tuberculosis results in a continuum of ill-defined, clinical manifestations with stable latent M. tuberculosis infection (LTBI) and severe active disease at the ends. Identifying different states of infection is of importance to tuberculosis (TB) control since risk of developing active disease varies among different asymptomatic states while infectiousness varies among patients with different bacterial burden. We investigated changes in proteome-scale antibody responses during disease progression in a non-human primate model of tuberculosis. We probed M. tuberculosis proteome microarrays with serial sera collected from three infection-outcome groups (active, reactivation, and latent). We found that each infection outcome is associated with characteristic changes in the antibody levels and number of antigenic targets, which suggested an association between antibody responses and bacillary burden. Additional proteome-scale serological profiling of > 400 human TB suspects established that antibody responses are positively associated with bacterial load. Thus tuberculosis-specific antibody levels and number of antigenic targets increases with disease progression. Serum samples collected from adult patients with suspected tuberculosis during a multi-site study was used to probe whole proteome microarrays. Subject recruitment was conducted under uniform protocols approved by the institutional ethics committee at each site. Final diagnosis of active TB was based on positive M. tuberculosis culture results. The active TB patients were further subdivided into smear-positive and negative disease based on results of Ziehl-Neelsen staining of sputum smears for acid fast bacilli. Active TB was excluded as a diagnosis (Non-TB Disease [NTBD] patients) based on having negative M. tuberculosis culture and smear results and on having an alternate diagnosis. All subjects were presumably negative for HIV infection given the very low incidence of HIV infection in the study sites. Sera from 169 TB and 242 NTBD patients were selected for microarray probing. The control sera (n = 14) which was used to generate negative control distribution for each protein were negative to latent M. tuberculosis infection, as indicated by negative results to tuberculin skin test.
2012-07-05 | E-GEOD-30722 | biostudies-arrayexpress
Project description:This dataset aims to dissect the whole blood transcriptional signature by determining if elements of the whole blood signature are still present in purified cell subpopulations. We aimed to characterise the transcriptional response during TB and identify if cell subsets drove changes in whole blood cellular composition. The aim of the experiment was to define transcriptional signatures in neutrophils, monocytes, CD4+ and CD8+ cells from blood of active TB patients and healthy controls to distinguish the signature of active TB patients from each other and from healthy controls. This will help in the diagnosis of active tuberculosis, which normally relies on culture of the bacilli, which can take up to 6 weeks, sometimes the bacilli cannot be obtained from sputum thus requiring invasive techniques obtaining bronchoalveolar lavage (BAL). In some cases the bacill cannot be grown from sputum or BAL.
2010-08-11 | GSE19443 | GEO
Project description:Tuberculosis (TB) is a chronic granulomatous disease caused by the pathogen Mycobacterium tuberculosis. The success of M. tuberculosis can be attributed to its ability to evade protective host immune responses and its recalcitrance to antimicrobial chemotherapy. Detailed understanding of protective host immune response to TB is still lacking and there are limited reports that characterize host responses to TB at the site of disease. Furthermore, although cure of the majority of patients treated with the standard 6-month multidrug regimen indicates that treatment is highly effective, approximately 4-10% of clinically cured patients will develop recurrent disease within the first 12 months after completing therapy. We therefore analyzed BALF supernatant proteomes from pulmonary TB patients and patients at the end of standard anti-TB treatment to gain a better understanding of the host response at the site of disease. This would not only aid our understanding of localised host responses during TB disease, but could allow us to identify protein signatures associated with active TB disease or clinical cure.
2021-11-03 | PXD018907 | Pride
Project description:The aim of this study was to compare the transcriptional response to TB in regions of different incidence / prevalence. Experimental Design: Whole blood collected in tempus tubes from patients with different spectra of TB disease. All patients were sampled prior to the initiation of any antimycobacterial therapy. Active Pulmonary TB: PTB - All patients confirmed by isolation of Mycobacterium Tuberculosis on culture of sputum. Latent TB: LTB - All patients were screened at a tuberculosis clinic. All were positive by Interferon-Gamma Release assay(IGRA); specifically Quantiferon Gold In-Tube Assay (Cellestis, Australia). Latent patients had no clinical, or microbiological evidence of active infection and were asymptomatic. Experimental Variables: Patient group: Active PTB; Latent TB. There are no healthy controls in this dataset as it was being used for validation only. Controls: Latent TB individuals are used as a control for PTB in this dataset since there are few to no unexposed adult controls in Cape Town.
2010-08-11 | E-GEOD-19442 | biostudies-arrayexpress
Project description:Identification of blood transcriptional biomarkers linked to different phases of tuberculosis. The discovery of a transcriptional signature that distinguishes subclinical TB from incipient TB at baseline could lead to tuberculosis interventions that combat the tuberculosis epidemic in the context of household contacts.
2023-01-10 | GSE193777 | GEO
Project description:Human infection with Mycobacterium tuberculosis results in a continuum of ill-defined, clinical manifestations with stable latent M. tuberculosis infection (LTBI) and severe active disease at the ends. Identifying different states of infection is of importance to tuberculosis (TB) control since risk of developing active disease varies among different asymptomatic states while infectiousness varies among patients with different bacterial burden. We investigated changes in proteome-scale antibody responses during disease progression in a non-human primate model of tuberculosis. We probed M. tuberculosis proteome microarrays with serial sera collected from three infection-outcome groups (active, reactivation, and latent). We found that each infection outcome is associated with characteristic changes in the antibody levels and number of antigenic targets, which suggested an association between antibody responses and bacillary burden. Additional proteome-scale serological profiling of > 400 human TB suspects established that antibody responses are positively associated with bacterial load. Thus tuberculosis-specific antibody levels and number of antigenic targets increases with disease progression.
2012-07-06 | GSE30722 | GEO