Ontology highlight
ABSTRACT:
PROVIDER: PRJNA473457 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Despite increases in vaccination coverage, reductions in influenza-related mortality have not been observed. Better vaccines are therefore required and influenza challenge studies can be used to test the efficacy of new vaccines. However, this requires the accurate post-challenge classification of subjects by outcome, which is limited in current methods that use artificial thresholds to assign “symptomatic” and “asymptomatic” phenotypes. We present data from an influenza challenge study in which 22 healthy adults (11 vaccinated) were inoculated with H3N2 influenza (A/Wisconsin/67/2005). We generated genome-wide gene expression data from peripheral blood taken immediately before the challenge and at 12, 24, and 48 hours post-challenge. Variation in symptomatic scoring was found among those with laboratory confirmed influenza. By combining the dynamic transcriptomic data with the clinical parameters this variability can be reduced. We identified four subjects with severe laboratory confirmed flu that show differential gene expression in 1,103 probes 48 hours post-challenge compared to the remaining subjects. We have further reduced this profile to 6 genes that can be used to define these subjects. We have used this gene set to predict symptomatic infection from an independent study. This analysis gives further insight into host-pathogen interactions during influenza infection. However, the major potential value is in the clinical trial setting by providing a more quantitative method to better classify symptomatic individuals post influenza challenge. Twenty two healthy volunteers were enrolled for an influenza challenge study. Eleven were vaccinated thirty days before challenge with H3N2 influenza. Whole blood was collected in PAXgene tubes prior to influenza challenge and then at three further timepoints (12, 24 and 48 hours post-challenge).
2014-11-06 | E-GEOD-61754 | biostudies-arrayexpress
Project description:Influenza challenge trials are important for vaccine efficacy testing. Currently, disease severity is determined by self-reported scores to a list of symptoms which can be highly subjective. A more objective measure would allow for improved data analysis. Twenty one volunteers participated in an influenza challenge trial. We calculated the Daily Sum of Scores (DSS) for a list of 16 influenza symptoms. Whole blood collected at baseline and 24, 48, 72 and 96 hours post challenge was profiled on Illumina HT12v4 microarrays. We selected 19 genes with the largest fold change to train a random forest model with out of bag sampling cross validation. We observed good concordance between predicted and actual scores in an independent test set (overall Pearson correlation, r = 0.57; RMSE = -16.1%).
2017-06-10 | GSE90732 | GEO
Project description:Diagnosis of influenza A infection is currently based on clinical symptoms and pathogen detection. Use of host peripheral blood gene expression data to classify individuals with influenza A virus infection represents a novel approach to infection diagnosis We used microarrays to assay peripheral blood gene expression at baseline and every 8 hours for 7 days following intranasal influenza A H1N1 or H3N2 inoculation in healthy volunteers. We determined groups of coexpressed genes that classified symptomatic influenza infection. We then tested this gene expression classifier in patients with naturally acquired respiratory illness.
2013-11-16 | GSE52428 | GEO
Project description:Diagnosis of influenza A infection is currently based on clinical symptoms and pathogen detection. Use of host peripheral blood gene expression data to classify individuals with influenza A virus infection represents a novel approach to infection diagnosis We used microarrays to assay peripheral blood gene expression at baseline and every 8 hours for 7 days following intranasal influenza A H1N1 or H3N2 inoculation in healthy volunteers. We determined groups of coexpressed genes that classified symptomatic influenza infection. We then tested this gene expression classifier in patients with naturally acquired respiratory illness. We experimentally inoculated healthy volunteers with intranasal influenza A H1N1 and H3N2. Symptoms were documented and peripheral blood samples drawn into PAXgene RNA tubes for RNA isolation. We further enrolled patients presenting to the Emergency Department with naturally acquired respiratory illness, and documented symptoms and collected PAXgene RNA samples for RNA isolation.
2013-11-16 | E-GEOD-52428 | biostudies-arrayexpress
Project description:Seasonal influenza outbreaks represent a large burden for the healthcare system as well as the economy. While the role of the microbiome in the context of various diseases has been elucidated, the effects on the respiratory and gastrointestinal microbiome during influenza illness is largely unknown. Therefore, this study aimed to characterize the temporal development of the respiratory and gastrointestinal microbiome of swine using a multi-omics approach prior and during influenza infection. Swine is a suitable animal model for influenza research, as it is closely related to humans and a natural host for influenza viruses. Our results showed that IAV infection resulted in significant changes in the abundance of Moraxellaceae and Pasteurellaceae families in the upper respiratory tract. To our surprise, temporal development of the respiratory microbiome was not affected. Furthermore, we observed significantly altered microbial richness and diversity in the gastrointestinal microbiome after IAV infection. In particular, we found increased abundances of Prevotellaceae, while Clostridiaceae and Lachnospiraceae decreased. Furthermore, metaproteomics showed that the functional composition of the microbiome, known to be robust and stable under healthy conditions, was heavily affected by the influenza infection. Metabolome analysis proved increased amounts of short-chain fatty acids in the gastrointestinal tract, which might be involved in faster recovery. Furthermore, metaproteome data suggest a possible immune response towards flagellated Clostridia induced during the infection. Therefore, it can be assumed that the respiratory infection with IAV caused a systemic effect in the porcine host and microbiome.
2022-02-16 | PXD024077 | Pride
Project description:Transciptional responses in T cells in blood and BAL from healthy adult volunteers infected with influenza
2021-07-01 | GSE175551 | GEO
Project description:Abstract: Many mouse models of neurological disease use the tetracycline transactivator (tTA) system to control transgene expression by oral treatment with the broad-spectrum antibiotic doxycycline. Antibiotic treatment used for transgene control might have undesirable systemic effects, including the potential to affect immune responses in the brain via changes in the gut microbiome. Recent work has shown that an antibiotic cocktail to perturb the gut microbiome can suppress microglial reactivity to brain amyloidosis in transgenic mouse models of Alzheimer's disease based on controlled overexpression of the amyloid precursor protein (APP). Here we assessed the impact of chronic low dose doxycycline on gut microbiome diversity and neuroimmune response to systemic LPS challenge in a tTA-regulated model of Alzheimer's amyloidosis. We show that doxycycline decreased microbiome diversity in both APP transgenic and wild-type mice and that these changes persisted long after drug withdrawal. Despite this change in microbiome composition, dox treatment had minimal effect on transcriptional signatures in the brain, both at baseline and following acute LPS challenge. Our findings suggest that central neuroinflammatory responses may be less affected by dox at doses needed for transgene control than by antibiotic cocktail at doses used for microbiome manipulation.
2024-01-10 | GSE236242 | GEO
Project description:Total plasma IgA glycosylation was compared between healthy volunteers and volunteers suffering fromo infections with either the influenza A virus or the severe acute respiratory syndrome corona virus 2. Data from functional assays of the same plasma samples, such as neutrophil extracellular trap formation is also available.
2024-10-22 | PXD057019 | Pride