TB
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ABSTRACT:
PROVIDER: EGAD00000000016 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:This project involves RNA-Seq analysis of samples obtained from the Phase IIA clinical trial TB-019 (NCT01669096) which evaluated kinetics of response, safety, and immunogenicity of the GSK Mycobacterium tuberculosis (MTB) vaccine M72/AS01E (“GSK M72”). GSK M72 consists of the M72 recombinant fusion of Mycobacterium tuberculosis (MTB) proteins Rv0125 and Rv1196 in combination with the liposome, TLR4 ligand (MPL), and QS21 saponin adjuvant AS01E (Leroux-Roels et al., 2013).
2023-12-30 | GSE102574 | GEO
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:WTCCC genome-wide case-control association study for Tuberculosis (TB) using the African samples as controls.
| EGAS00000000027 | EGA
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:Genome wide DNA methylation profiling of PBMC from South African patients either infected with HIV only or coinfected with HIV and tuberculosis (TB). The Illumina Infinium 27k Human DNA methylation Beadchip was used to obtain DNA methylation profiles from PBMC samples. Samples included 19 HIV patients and 20 HIV/TB co-infected patients.
2014-03-05 | GSE50835 | GEO
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:Pulmonary tuberculosis (TB) generates chronic systemic inflammation and metabolic dysregulation. The liver is the master regulator of metabolism and to determine the impact of pulmonary TB on this organ we undertook unbiased mRNA analyses of the liver in mice with TB. Pulmonary TB led to upregulation of genes in the liver related to interferon signalling and glycolysis, and downregulation of genes encoding gluconeogenesis rate-limiting enzyme
2024-09-17 | GSE273691 | GEO
Project description:Most individuals infected with Mycobacterium tuberculosis can control the infection by forming and maintaining TB granulomas at the local infection foci. However, when the chronic infection (also known as latency) becomes active, the caseous center of TB granuloma enlarges, and it liquefies and cavitates, ultimately releasing bacilli into airway. Deciphering how genes are regulated within TB granulomas will help to understand the granuloma biology. Therefore, we performed genome-wide microarray on caseous human pulmonary TB granulomas and compared with normal lung tissues.
2010-06-02 | GSE20050 | 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:Understanding the immune response to tuberculosis requires greater knowledge of humoral responses. To characterize antibody targets and the effect of disease parameters on target recognition, we developed a systems immunology approach that integrated detection of antibodies against the entire Mycobacterium tuberculosis proteome, bacterial metabolic and regulatory pathway information, and patient data. Probing ~4,000 M. tuberculosis proteins with sera from >500 suspected tuberculosis patients worldwide revealed that antibody responses recognized ~10% of the bacterial proteome. This result defines the immunoproteome of M. tuberculosis, which is rich in membrane-associated and extracellular proteins. Most serum reactivity during active tuberculosis focused onto ~0.5% of the proteome. Within this pool, which is selectively enriched for extracellular proteins (but not for membrane-associated proteins), relative target preference varied among patients. The shift in relative M. tuberculosis protein reactivity observed with active tuberculosis defines the evolution of the humoral immune response during M. tuberculosis infection and disease. Peripheral blood was collected from prospectively enrolled TB suspects among subjects seeking care for pulmonary symptoms at clinics associated with national TB control programs in 11 countries. M. tuberculosis proteome microarrays representing 4099 bacterial protein spots were probed with sera from 561 TB suspects. Based on the final diagnosis, they belonged to two classes: TB (n=254) and Non-TB Disease (n=307). In addition, healthy individuals negative to Latent TB Infection (LTBI neg, n=64) were also tested (negative control sera). Each serum was tested with a single array and no replicate experiments were performed. The reactivity of a serum to an M. tuberculosis protein (reactivity call) was defined based on the distribution of negative control sera intensity for that protein using Z-statistics. Based on the distribution of reactivity calls, 27 outlier samples reacting with more than 20 proteins were excluded from further analysis. The association of reactivity calls of each protein with TB/NTBD status of TB suspects was determined by estimating odds ratio and 95% confidence interval.
2010-07-13 | E-GEOD-19433 | biostudies-arrayexpress