Genome wide transcriptional profiling of HIV positive and negative children with active tuberculosis, latent TB infection and other diseases from Kenya
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE39939 | GEO | 2014/05/01
SECONDARY ACCESSION(S): PRJNA172139
REPOSITORIES: GEO
Similar Datasets
Project description:The study aimed to define transcriptional signatures for detection of active TB (TB) compared to latent TB infection (LTBI) as well as to other diseases (OD) with similar clinical phenotypes in patients with and without HIV in a paediatric cohort from Kenya Transcriptional signatures were identified that distinguished active TB from LTBI, active TB from other diseases, and active TB from both LTBI and other diseases in HIV+/- patients. Children were recruited from 2 hospitals in Coast Province, Kenya (n=157) who were either HIV+ or HIV - with either active TB (culture confirmed), active TB (culture negative), LTBI or OD. Blood was collected into PAX gene tubes (PreAnalytiX). Total RNA integrity was assessed using an Agilent 2100 Bioanalyzer (Agilent, Palo Alto, CA). Labeled cRNA was hybridized to Illumina Human HT-12 Beadchips. Data were analysed in R.
2014-05-01 | E-GEOD-39939 | biostudies-arrayexpress
Project description:The study aimed to define transcriptional signatures for detection of active TB (TB) compared to latent TB infection (LTBI) as well as to other diseases (OD) with similar clinical phenotypes in patients with and without HIV in two African paediatric populations. Transcriptional signatures were identified that distinguished active TB from LTBI, and active TB from other diseases.
2014-05-01 | GSE39940 | GEO
Project description:The study aimed to define transcriptional signatures for detection of active TB (TB) compared to latent TB infection (LTBI) as well as to other diseases (OD) with similar clinical phenotypes in patients with and without HIV in two African paediatric populations. Transcriptional signatures were identified that distinguished active TB from LTBI, and active TB from other diseases. Children were recruited from Cape Town, South Africa (n=157) and Blantyre, Malawi (n=177) who were either HIV+ or HIV - with either active TB, LTBI or OD. Blood was collected into PAX gene tubes (PreAnalytiX). Total RNA integrity was assessed using an Agilent 2100 Bioanalyzer (Agilent, Palo Alto, CA). Labeled cRNA was hybridized to Illumina Human HT-12 Beadchips. Data were analysed in R.
2014-05-01 | E-GEOD-39940 | biostudies-arrayexpress
Project description:The study aimed to define transcriptional signatures for detection of active TB (TB) compared to latent TB infection (LTBI) as well as to other diseases (OD) with similar clinical phenotypes in patients with and without HIV in two African adult populations. Transcriptional signatures were identified that distinguished active TB from LTBI, active TB from other diseases, and active TB from both LTBI and other diseases in HIV+/- patients.
2013-10-23 | GSE37250 | GEO
Project description:The study aimed to define transcriptional signatures for detection of active TB (TB) compared to latent TB infection (LTBI) as well as to other diseases (OD) with similar clinical phenotypes in patients with and without HIV in two African adult populations. Transcriptional signatures were identified that distinguished active TB from LTBI, active TB from other diseases, and active TB from both LTBI and other diseases in HIV+/- patients. Adults were recruited from Cape Town, South Africa (n=300) and Karonga, Malawi (n=237) who were either HIV+ or HIV - with either active TB, LTBI or OD. Blood was collected into PAX gene tubes (PreAnalytiX). Total RNA integrity was assessed using an Agilent 2100 Bioanalyzer (Agilent, Palo Alto, CA). Labeled cRNA was hybridized to Illumina Human HT-12 Beadchips. Data were analysed in R.
2013-10-23 | E-GEOD-37250 | biostudies-arrayexpress
Project description:Mycobacterium tuberculosis (Mtb) has developed specialized mechanisms to parasitize its host cell, the macrophage. These mechanisms allow it to overcome killing by oxidative burst and persist in the wake of an inflammatory response. Mtb infection in the majority of those exposed is controlled in an asymptomatic form referred to as latent tuberculosis infection (LTBI). HIV is a well-known catalyst of reactivation of LTBI to active TB infection (ATB). Through the use of nonhuman primates (NHPs) co-infected with Mtb and Simian Immunodeficiency Virus (Mtb/SIV), we are able to simulate human progression of TB/AIDS comorbidity. The advantage of NHP models is that they recapitulate the breadth of human TB outcomes, including immune control of infection, and loss of this control due to SIV co-infection. Using macaques infected with Mtb or Mtb/SIV and with different clinical outcomes we attempted to identify signatures between those that progress to active infection after SIV challenge (reactivators) and those that control the infection (non-reactivators).
2022-09-23 | GSE213850 | GEO
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:To study the role of miRNAs in the transition from latent to active TB and to discover candidate biomarkers that may help predict TB progression, we have employed miRNA microarray expression profiling as a discovery platform to probe the transcriptome of peripheral blood mononuclear cells (PBMCs) with active TB, latent TB infection (LTBI), and healthy donors.Patients were recruited at the Shanghai Public Health Clinical Centre (Shanghai, China) from December, 2008 to May, 2009. The diagnosis of active TB was based on clinical presentation, chest radiography, and acid-fast stain of sputum smear.All the patients were HIV negative, as diagnosed by the Livzon Anti-HIV1/2 EIA Kit (Livzon Pharmaceutical Group Inc., Guangdong, China). Additional tests were also performed to detect hepatitis B virus (HBV) and hepatitis C virus (HCV) by using the Abbott AxSYM anti-HBsAg and HCV 3.0 antibody assay kit (Abbott Laboratories, Illinois) to exclude HBV- and HCV-positive patients (these 2 diseases are highly prevalent in China). Patients with a diabetes history were also excluded because diabetes could increase the risk of TB. Peripheral venous blood was drawn before treatment. Subjects with LTBI and healthy donors both without a history of clinical TB or other infectious diseases were recruited from the staff at the Shanghai Public Health Clinical Centre. TST and IGRA (T-SPOTM-BM-..TB, Oxford Immunuotec, Oxfordshire, U.K) results were used to distinguish the two groups. The LTBI group was TST-positive (TST>10 mm) and IGRA-positive while the healthy donors were TST-negative (TST<5 mm) and IGRA-negative. RNA of PBMC from 6 patients with active TB, 6 donors with Latent TB, and 3 healthy controls (total of 15 biologically independent samples) were used to perform Agilent Human miRNA (version 3) microarray , No replicates were included
2011-05-10 | E-GEOD-29190 | 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:To further understand the host immune factors involved in the progression from latent tuberculosis infection (LTBI) to active tuberculosis (TB) and identify the potential signatures for discriminating TB from LTBI, the genome-wide transcriptional profile of the Mycobacterium.Tuberculosis (M.TB)–specific antigens stimulated peripheral blood mononuclear cells (PBMCs) from active TB, LTBI and health controls (HCs) were performed. A total of 209- and 234- differentially expressed genes (Fold change > 4, P < 0.05) were detected in comparisons of TB vs. LTBI and TB vs. HCs, respectively. Nineteen differentially expressed genes with top fold change between TB and the other two groups were validated in the same RNA samples by real-time PCR, and showed 94.7% consistent expression pattern with microarray test.
2018-02-14 | GSE98461 | GEO