Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Profiling of bacterial respiratory infection, viral respiratory infection, and non-infectious illness

ABSTRACT: A pressing clinical challenge is identifying the etiologic basis of acute respiratory illness. Without reliable diagnostics, the uncertainty associated with this clinical entity leads to a significant, inappropriate use of antibacterials. Use of host peripheral blood gene expression data to classify individuals with bacterial infection, viral infection, or non-infection represents a complementary diagnostic approach. Patients with respiratory tract infection along with ill, non-infected controls were enrolled through the emergency department or undergraduate student health services. Whole blood was obtained to generate gene expression profiles. These profiles were then used to generate signatures of bacterial acute respiratory infection, viral acute respiratory infection, and non-infectious illness.

ORGANISM(S): Homo sapiens

PROVIDER: GSE63990 | GEO | 2016/01/20

SECONDARY ACCESSION(S): PRJNA269949

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Profiling of bacterial respiratory infection, viral respiratory infection, and non-infectious illness

Project description:A pressing clinical challenge is identifying the etiologic basis of acute respiratory illness. Without reliable diagnostics, the uncertainty associated with this clinical entity leads to a significant, inappropriate use of antibacterials. Use of host peripheral blood gene expression data to classify individuals with bacterial infection, viral infection, or non-infection represents a complementary diagnostic approach. Patients with respiratory tract infection along with ill, non-infected controls were enrolled through the emergency department or undergraduate student health services. Whole blood was obtained to generate gene expression profiles. These profiles were then used to generate signatures of bacterial acute respiratory infection, viral acute respiratory infection, and non-infectious illness. 273 subjects were ascertained for this analysis. This included 88 patients with non-infectious illness, 115 with viral acute respiratory infection, and 70 with bacterial acute respiratory infection. Samples were obtained at the time of enrollment, which was at initial clinical presentation. Total RNA was extracted from human blood using the PAXgene Blood RNA Kit. Microarray data were generated using the GeneChip Human Genome U133A 2.0 Array. Microarrays were generated in two microarray batches with seven overlapping samples giving rise to 280 total microarray experiments.

2016-01-20 | E-GEOD-63990 | biostudies-arrayexpress

Genomic Circuitry Underlying Immunological Response to Pediatric Acute Respiratory Infection

Project description:Acute respiratory tract viral infections (ARTI) cause significant morbidity and mortality. While CD8 T cells are fundamental to the host response, the transcriptional alterations underlying anti-viral mechanisms within these cells, and the links to clinical characteristics, remain unclear. The transcriptional circuitry in CD8 T cells from acutely ill pediatric patients with influenza-like illness was distinct for different viral pathogens. We used microarray analysis to profile sorted CD8 T cells from PBMCs of various influenza-like illness patients.

2018-01-09 | GSE106475 | GEO

Viral Respiratory Pathogens Genetics

Project description:The overall purpose of this study is to investigate the host genetic factors in response to influenza virus infection, with the focus on influenza vaccination in the first substudy "Adult Influenza Vaccine Genetics" and with the focus on influenza natural infection and other acute respiratory infections (ARIs) in the second substudy "Acute Viral Respiratory Infection Genetics". In the first substudy, healthy adults were enrolled in 2008 (male cohort) and 2010 (female cohort) and immunized with seasonal influenza vaccine. In the second substudy, healthy adults were invited to enroll to be followed for acute respiratory illness through two consecutive influenza seasons 2009-2010 and 2010-2011. Peripheral blood genomic DNA samples were collected from all the subjects, and time-series RNA and serum samples were obtained pre- and post- immunization/infection. Genotyping was carried out on peripheral blood genomic DNA samples using Illumina HumanOmniExpress-12 v1 arrays. Peripheral blood RNA samples obtained at each visit were analyzed using Illumina Human HT-12 (for all the samples) and HiSeq 2000 (for 130 samples in the "Acute Viral Respiratory Infection Genetics" study). Serum specimens were tested using hemagglutination-inhibition (HAI) antibody assay for Influenza H1N1, H3N2, and Influenza B strains. A detailed description of each substudy is provided under their own pages below and via the grouping tool in the right-hand box: <ul> <li><a href="./study.cgi?study_id=phs000635">phs000635</a> Adult Influenza Vaccine Genetics</li> <li><a href="./study.cgi?study_id=phs001031">phs001031</a> Acute Viral Respiratory Infection Genetics</li> </ul>

| phs001030 | dbGaP

Gene expression signatures of symptomatic respiratory viral infection in adults

Project description:Diagnosis of acute respiratory viral infection is currently based on clinical symptoms and pathogen detection. Use of host peripheral blood gene expression data to classify individuals with viral respiratory infection represents a novel means of infection diagnosis. We used microarrays to capture peripheral blood gene expression at baseline and time of peak symptoms in healthy volunteers infected intranasally with influenza A H3N2, respiratory syncytial virus or rhinovirus. We determined groups of coexpressed genes that accurately classified symptomatic versus asymptomatic individuals. We experimentally inoculated healthy volunteers with intranasal influenza, respiratory syncytial virus or rhinovirus. Symptoms were documented and peripheral blood samples drawn into PAXgene tubes for RNA isolation.

2009-08-06 | E-GEOD-17156 | biostudies-arrayexpress

Gene expression signatures of symptomatic respiratory viral infection in adults

Project description:Diagnosis of acute respiratory viral infection is currentlybased on clinical symptoms and pathogen detection. Use of host peripheral blood gene expression data to classify individuals with viral respiratory infection represents a novel means of infection diagnosis. We used microarrays to capture peripheral blood gene expression at baseline and time of peak symptoms in healthy volunteers infected intranasally with influenza A H3N2, respiratory syncytial virus or rhinovirus. We determined groups of coexpressed genes that accurately classified symptomatic versus asymptomatic individuals.

2009-08-06 | GSE17156 | GEO

Fungal Dysbiosis in Post-Influenza MRSA Infection

Project description:A leading cause of morbidity and mortality during influenza infection is the development of a secondary bacterial pneumonia, which is appropriately treated with antibiotics. In the absence of a bacterial superinfection, prescribing antibiotics is not indicated but has nevertheless become a common clinical practice for those presenting with a respiratory viral illness. We found that antibiotic use during an antecedent influenza infection impaired the lung innate immunologic defenses toward a secondary challenge with methicillin-resistantStaphylococcus aureus(MRSA). The antibiotics perturbed the gut microbiome causing a fungal dysbiosis that drives an increase in lung eosinophils. We also demonstrate eosinophils, through the release of major basic protein, impair macrophage ability to clear MRSA. Moreover, we provide clinical evidence that eosinophils positively correlate with antibiotic use and worsened outcomes in patients hospitalized for viral infections. Altogether, our work establishes a counterproductive effect of antibiotic treatment during influenza infection that have negative immunologic consequences in the lungs thereby increasing the risk of developing a secondary bacterial infection.

2024-08-21 | GSE243542 | GEO

Characterization of antibiotic resistance and host-microbiome interactions in the human upper respiratory tract during influenza infection [RNA-Seq]

Project description:Antibiotic resistance genes expressed in the upper respiratory tract of patients infected with influenza viruses were associated with the microbial community and microbial activities. Interactions between the host systemic responses to influenza infection and ARG expression highlight the importance of antibiotic resistance in viral-bacterial co-infection.

2020-03-19 | GSE126901 | GEO

Characterization of antibiotic resistance and host-microbiome interactions in the human upper respiratory tract during influenza infection [human host RNA-seq]

2020-03-19 | GSE114588 | GEO

Gene Array to Predict Bacterial Infection with in Respiratory Illness

Project description:Accurate tests for microbiologic diagnosis of lower respiratory tract infections (LRTI) are needed. Gene expression profiling of whole blood represents a powerful new approach for analysis of the host response during respiratory infection that can be used to supplement pathogen detection testing. Using qPCR, we prospectively validated the differential expression of 10 genes previously shown to discriminate bacterial and non-bacterial LRTI confirming the utility of this approach. In addition, a novel approach using RNAseq analysis identified 141 genes differentially expressed in LRTI subjects with bacterial infection. Using "pathway-informed" dimension reduction, we identified a novel 11 gene set (selected from lymphocyte, α-linoleic acid metabolism, and IGF regulation pathways) and demonstrated a predictive accuracy for bacterial LRTI (nested CV-AUC=0.87). RNAseq represents a new and an unbiased tool to evaluate host gene expression for the diagnosis of LRTI.

| phs001248 | dbGaP