Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA315611 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR3235790_1.fastq.gz | Fastqsanger.gz | |||
| SRR3235790_2.fastq.gz | Fastqsanger.gz | |||
| SRR3235800_1.fastq.gz | Fastqsanger.gz | |||
| SRR3235800_2.fastq.gz | Fastqsanger.gz | |||
| SRR3235810_1.fastq.gz | Fastqsanger.gz |
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Project description:Identification of blood biomarkers that prospectively predict progression of Mycobacterium tuberculosis infection to tuberculosis disease might lead to interventions that combat the tuberculosis epidemic. We aimed to assess whether global gene expression measured in whole blood of healthy people allowed identification of prospective signatures of risk of active tuberculosis disease. RESULTS:Between July 6, 2005, and April 23, 2007, we enrolled 6363 from the ACS study and 4466 from independent South African and Gambian cohorts. 46 progressors and 107 matched controls were identified in the ACS cohort. A 16 gene signature of risk was identified. The signature predicted tuberculosis progression with a sensitivity of 66·1% (95% CI 63·2â68·9) and a specificity of 80·6% (79·2â82·0) in the 12 months preceding tuberculosis diagnosis. The risk signature was validated in an untouched group of adolescents (p=0·018 for RNA sequencing and p=0·0095 for qRT-PCR) and in the independent South African and Gambian cohorts (p values <0·0001 by qRT-PCR) with a sensitivity of 53·7% (42·6â64·3) and a specificity of 82·8% (76·7â86) in 12 months preceding tuberculosis. Interpretation: The whole blood tuberculosis risk signature prospectively identified people at risk of developing active tuberculosis, opening the possibility for targeted intervention to prevent the disease. In this prospective cohort study, we followed up healthy, South African adolescents aged 12â18 years from the adolescent cohort study (ACS) who were infected with M tuberculosis for 2 years. We collected blood samples from study participants every 6 months and monitored the adolescents for progression to tuberculosis disease. A prospective signature of risk was derived from whole blood RNA sequencing data by comparing participants who developed active tuberculosis disease (progressors) with those who remained healthy (matched controls). After adaptation to multiplex qRT-PCR, the signature was used to predict tuberculosis disease in untouched adolescent samples and in samples from independent cohorts of South African and Gambian adult progressors and controls. Participants of the independent cohorts were household contacts of adults with active pulmonary tuberculosis disease.
2016-03-22 | E-GEOD-79362 | biostudies-arrayexpress
Project description:A blood RNA signature for tuberculosis disease risk in household contact study - GC6 cohort.
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Project description:Identification of blood biomarkers that prospectively predict progression of Mycobacterium tuberculosis infection to tuberculosis disease might lead to interventions that combat the tuberculosis epidemic. We aimed to assess whether global gene expression measured in whole blood of healthy people allowed identification of prospective signatures of risk of active tuberculosis disease. RESULTS:Between July 6, 2005, and April 23, 2007, we enrolled 6363 from the ACS study and 4466 from independent South African and Gambian cohorts. 46 progressors and 107 matched controls were identified in the ACS cohort. A 16 gene signature of risk was identified. The signature predicted tuberculosis progression with a sensitivity of 66·1% (95% CI 63·2–68·9) and a specificity of 80·6% (79·2–82·0) in the 12 months preceding tuberculosis diagnosis. The risk signature was validated in an untouched group of adolescents (p=0·018 for RNA sequencing and p=0·0095 for qRT-PCR) and in the independent South African and Gambian cohorts (p values <0·0001 by qRT-PCR) with a sensitivity of 53·7% (42·6–64·3) and a specificity of 82·8% (76·7–86) in 12 months preceding tuberculosis. Interpretation: The whole blood tuberculosis risk signature prospectively identified people at risk of developing active tuberculosis, opening the possibility for targeted intervention to prevent the disease.
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Project description:An RNA signature for tuberculosis risk in pregnant women: a prospective cohort study from Pune, India
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Project description:Background: Pregnant and postpartum women are at high risk of developing active tuberculosis (TB), but transcriptional TB studies have excluded pregnant women. We identified differentially expressed genes (DEGs) in pregnant women who did and did not progress to active TB. Methods: We followed a cohort of pregnant Indian women with TB infection for one year postpartum, collecting blood at study entry, 6 weeks postpartum and active TB diagnosis. A prospective signature of risk was identified by comparing whole blood RNA sequencing data from women who developed active TB postpartum (cases) with those who remained healthy (controls). Results: We identified 9 cases and matched them to 18 controls by HIV status and gestational age. A gene set of risk was identified: Expression of KCNIP4 > 2.2 log CPM and S1PR4 < 7.3 log CPM indicated a high probability of developing active TB postpartum. SF3B4 (>4.3 log CPM) and PGAM1 (>6.6 log CPM) correctly classified postpartum cases and controls. Both pairs displayed high accuracy (AUC >0.9) and were unique from 36 published TB signatures.Conclusions: We identified two genes that prospectively differentiated pregnant women who developed active TB postpartum from those who did not. If validated, this signature could be useful in targeted TB prevention programs.
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Project description:Background: Blood transcriptomic signatures for diagnosis of tuberculosis (TB) have shown promise in case-control studies but their diagnostic accuracy has not been prospectively validated in adults presenting with the full clinical spectrum of suspected TB, including extra-pulmonary TB, and its associated differential diagnoses with concomitant latent TB infection. Methods: Our study was nested within a prospective multi-center cohort study in secondary care in England. Patients had whole-blood taken for microarray to measure abundance of 47,275 transcripts and interferon-gamma release assays (IGRAs) at clinical presentation with suspected TB and were followed up for 6-12 months’ to determine final diagnoses based on pre-defined diagnostic criteria. The diagnostic accuracy of published transcriptomic signatures and a novel cohort-derived signature were assessed to generate area under the receiver-operating characteristic curves (AUC), sensitivities and specificities.
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Project description:A blood RNA signature for predicting the treatment outcome in the Tuberculosis Treatment Response Cohort
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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.
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Project description:Prospective cohort carriage study
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