Modular repertoire analyses identify dynamic type I and type II interferon transcriptional signatures in adult SLE patients
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Damien Chaussabel
PROVIDER: E-GEOD-49454 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:The objective of this study is to: 1) Characterize the transcriptional signature of early acute HIV infection. 2) Eucidate the evolution of the signature in both anti-retroviral treated and untreated populations over a 24 week time course. 3) Correlate clinical and disease related parameters to heterogenaity in the transcriptional signature to identify pathways explaining clinical heterogeneity 4) Compare the acute signature of HIV infection to other acute viral signatures. 58 acute HIV patients were recruited from locations in Africa (n=43) and the United States (n=15). These patients were allocated into training (n=18), test (n=10) and validation sets (n=30). Patient samples were collected at study enrollment (confirmed acute) for all patients and at weeks 1,2,4,12,and 24 for training and test set constituents. 13 of 15 US patients initiated anti-retroviral therapy after after enollment and before the week 1 visit. The remining 2 US patients and 43 African patients were not placed on therapy through the 24 week time course. Matched uninfected controls patients were also recuited from each site (n= 55). In total 232 samples were collectd.
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Project description:The aim of the longitudinal analysis was to examine the transcriptional blood profile of active TB patients at the time of recruitment (before drug treatment) and then subsequently at specific time points after drug treatment to determine whether the signature is extinguished with treatment and when. Whole blood collected in tempus tubes from patients with different spectra of TB disease and healthy controls. 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 Interferon-Gamma Release assay(IGRA); specifically Quantiferon Gold In-Tube Assay (Cellestis, Australia). Here the aim of the experiment is to assess the longitudinal effect of antimycobacterial treatment on the active TB signature, during and after treatment. Blood was taken from the active TB patients at baseline, pre-treatment, 2 months after treatment inititation, and 12 months after treatment initiation, which would be after treatment was completed. These samples were then amplified at the same time with samples from healthy controls and hybridised to the same chips to permit an assessment of whether the post treatment samples had similar transcriptional profiles to healthy controls or were distinct. In this dataset: PTB baseline, n = 7; PTB 2 months, n = 7; PTB 12 months, n = 7. BCG+ control baseline, n =12. Experimental variables: Patient group: Active PTB; Healthy controls (all BCG vaccinated). ethnicity - a wide range of ethnic groups is represented. The active PTB group incorporates a range of smear positive and smear negative disease and a spectrum of disease extent/severity. Timepoint: 0 months = baseline pre-treatment;2 months = 2 months after initiation of treatment; 12 months = 12 months after initiation of treatment.
2010-08-11 | E-GEOD-19435 | biostudies-arrayexpress
Project description:This series regroups different datasets (training set, test set, validation set, longitudinal set, separated cell set) to identify and characterise a specific transcriptional signature for patients with active TB, distinct from patients with latent TB and healthy controls. The training set dataset was used to identify a whole blood transcriptional signature for active TB patients in London, across a range of ethnicity. This signature was then validated in an independent cohort of patients, also recruited in London (the test set), and then further confirmed in an additional independent cohort recruited in Cape Town, South Africa (validation set), in order to confirm that the defined signature was present in both high (Cape Town, South Africa) and medium incidence regions (London, UK). The longitudinal dataset was then used to explore how successful TB treatment modifies this transcriptional signature. The separated cell set compares the transcriptional profiles in purified cell subsets (neutrophils, monocytes and T cells) to assess which cell types are contributing to the whole blood signature, and in what way. These studies may ultimately help to improve the diagnosis of active tuberculosis which normally relies on culture of the bacilli, which can take up to 6 weeks, and sometimes the bacilli cannot be obtained from sputum thus requiring invasive techniques such as bronchoalveolar lavage (BAL). In some cases (30%) the bacill cannot be grown from sputum or BAL. Any diagnostic tool would need to be valid across a range of ethnicities, and be valid in both high and low incidence countries. A further aim was to determine whether latent TB patients have a distinct homogeneous or heterogeneous signature, since it is not currently possible to determine using present tests (Tuberculin skin test - TST - or MTb antigen responsiveness of blood cells to produce IFN-gamma - IGRA assay) whether the mycobacteria have been cleared, are still present but are controlled by an active immune response, or to predict which patients will develop active TB. Defining heterogeneity in the latent TB patients would be an important step in developing diagnostics which could detect those most at risk of developing active TB, and thus enable targeted preventive therapy. The latter situation may be determined if Latent patients have a blood transcriptional signature similar to that in Active patients. The transcriptional signature in whole blood and cell subsets from Active TB patients may also provide information as to the factors leading to immunopathogenesis, thus possibly identifying therapeutic targets. The transcriptional profile in latent TB may give information regarding protective factors controlling the infection, important for vaccine development. Finally, definition of a transcriptional signature which responds to therapy could facilitate the development of surrogate biomarkers for drug or vaccine studies. Since any active TB signature may reflect common inflammatory responses evoked during many diseases, we also performed analysis of significance, comparing transcriptional profiles from patients with TB to those from patients with other bacterial and inflammatory diseases to identify a TB specific signature. The resulting signature was then tested against patients normalized to their own controls from 7 independent datasets: TB (Training and Validation Sets), Staphylococcus infection, Group A Streptococcus infection, Still's disease, and adult and pediatric SLE. This SuperSeries is composed of the following subset Series: GSE19435: Transcriptional profiles in Blood of patients with Tuberculosis - Longitudinal Study GSE19439: Blood Transcriptional Profiles in Active and Latent Tuberculosis UK (Training Set) GSE19442: Blood Transcriptional Profiles of TB in South Africa GSE19443: Blood Transcriptional Profiles of Active TB (UK Test Set Separated) GSE19444: Blood Transcriptional Profiles of Active and Latent TB (UK Test Set) GSE22098: Whole blood transcriptional profiles of patients with active tuberculosis (TB) and other inflammatory and infectious diseases Active Pulmonary TB: PTB - All patients were confirmed by isolation of Mycobacterium Tuberculosis on culture of sputum or bronchoalvelolar lavage fluid. Latent TB: LTB - All patients were screened at a tuberculosis clinic, being either new entrants to the UK from endemic countries or being household contacts of infectious cases, or in the case of the validation set recruited in South Africa, were residents of a high incidence country. All UK patients were positive by tuberculin skin test (>14mm if BCG vaccinated, >5mm if not vaccinated) and were also positive by Interferon-Gamma Release assay(IGRA); specifically Quantiferon Gold In-Tube Assay (Cellestis, Australia). The South African latent TB patients were all positive by Interferon-Gamma Release assay (IGRA); specifically Quantiferon Gold In-Tube Assay. Latent patients had no clinical, radiological or microbiological evidence of active infection and were asymptomatic. Healthy controls - these were volunteers without exposure to TB who were negative by both tuberculin skin test (<15mm if BCG vaccinated, <6mm if unvaccinated); and IGRA (as described above). Experimental variables : Patient group: Active PTB; Latent TB, Healthy controls (BCG vaccinated and unvaccinated). Ethnicity - a wide range of ethnic groups is represented. The active PTB group incorporates a range of smear positive and smear negative disease and a spectrum of disease extent/severity. Experimental methods: Whole blood was collected into Tempus tubes (Applied Biosystems, Foster City, CA, USA) and stored between -20degrees Celsius and -80 degrees Celsius before RNA extraction. For the training set cohort, and the active TB patients baseline samples in the longitudinal cohort, total RNA was isolated from whole blood using the PerfectPure RNA Blood kit (5 PRIME Inc, Gaithersburg, MD, USA). For the separated cell samples, total RNA was isolated using the Qiagen RNeasy Mini Kit. For all other cohorts Total RNA was isolated from whole blood using the MagMAX 96 well RNA isolation kit (Applied Biosystems, Foster City, CA, USA). 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2010-08-11 | E-GEOD-19491 | biostudies-arrayexpress
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.
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2014-01-09 | E-GEOD-51404 | biostudies-arrayexpress
Project description:Transcriptional profiling was used to characterize the immunologic networks in subjects with CVID who have inflammatory complications to identify clues as to pathogenesis and potentially better modes of treatment. CVID subjects who fulfilled the standard diagnostic criteria, including significantly decreased levels of IgG, IgA, and/or IgM and poor or absent specific antibody production were enrolled. They were classified into, with or without characteristic inflammatory complications, as previously designated (hematologic or organ-specific autoimmunity, biopsy-proven granulomatous disease, or interstitial lung disease, lymphoid hyperplasia/ with splenomegaly or gastrointestinal inflammatory disease). 59 patients were included in the training set and 21 healthy controls and for test set 32 patients and 15 healthy controls. Disease controls included 6 X-linked agammaglobulinemia (XLA) patients and 15 healthy controls were included. Blood was taken before the interval intravenous immune globulin (Ig) infusions, or between subcutaneous administrations. The blood was collected using Tempus tubes and processed for microarray analysis.
2014-01-09 | E-GEOD-51405 | biostudies-arrayexpress
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Project description:SLE patients are always with various disease manifestation. Various cytokines are pointed interacting and playing pathological roles in SLE although the etiopathology is still obscure. In this study, we aimed to investigate the effects of cytokine interactions in the immune response of SLE patients. Overexpressed interferon-inducible(IFI) genes were confirmed in peripheral blood from SLE patients. Using network-based analysis on the immune response-related genes, several networks including cytokines such as TNF and IFN-γ, or beta-estradiol(E2), were constructed. TNF-regulated genes were dominant in these networks but in vitro TNF stimulation on PBMCs showed no different responses in the expressions of these genes between SLE and healthy individuals. Co-stimulating experiments by TNF, IFN-γ, and E2 with IFN-α, revealed that TNF has repressive while IFN-γ essentially has synergistic effect with IFN-α on IFI gene expressions in vitro. E2 showed different effects on IFI gene expressions among 3 individuals. Peripheral blood was obtained from patients with SLE (n=11) and healthy women (n=6). Gene expression profile was analyzed using DNA microarray covering 30,000 human genes. Differentially expressed immune response-related genes were selected and analyzed by using Expression Analysis Systemic Explorer (EASE) based on Gene Ontology (GO) followed by network pathway analysis with Ingenuity Pathways Analysis (IPA).
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