SARAH athlete respiratory microbiome
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB45648 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Background: Farm exposures in early life reduce the risks for childhood allergic diseases and asthma. There is less information about how farm exposures relate to respiratory illnesses and mucosal immune development. Objective: We hypothesized that children raised in farm environments have a lower incidence of viral illnesses over the first two years of life than non-farm children. We also analyzed between farm exposures or respiratory illnesses were related to patterns of nasal cell gene expression. Methods: The Wisconsin Infant Study Cohort (WISC) birth cohort enrolled farm and non-farm pregnant women from central Wisconsin. Parents reported prenatal farm and other environmental exposures. Illness frequency and severity were assessed using illness diaries and periodic surveys. Nasopharyngeal cell gene expression at age two years was compared to farm exposure and respiratory illness history. Results: There was a higher rate of respiratory illnesses in the non-farm vs. farm group (rate ratio 0.82 [0.69,0.97], p=0.020), but no significant differences in wheezing illnesses. There was a stepwise reduction in rates of respiratory illnesses in children exposed at least weekly to 0, 1, or ≥2 animals (p=0.006). In analyzing nasal cell gene expression, farm exposures and preceding respiratory illnesses were positively related to gene signatures for mononuclear cells and innate and antimicrobial responses. Conclusions: Children exposed to farms and farm animals had lower rates of respiratory illnesses over the first two years of life. Both farm exposures and preceding respiratory illnesses were associated with increased innate immune responses, suggesting that these exposures stimulate mucosal immune responses to reduce subsequent illness frequency.
2024-01-29 | GSE233761 | GEO
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
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.
2016-01-20 | GSE63990 | GEO
Project description:This series includes 1 microarray used to detect a human metapneumovirus strain associated with critical respiratory illness in an elderly male with leukemia (Chiu, et al 2006) Keywords: viral detection
2008-03-01 | GSE6214 | GEO
Project description:Respiratory failure and mortality from COVID-19 result from virus- and inflammation-induced lung tissue damage. The intestinal microbiome and associated metabolites are implicated in immune responses to respiratory viral infections, however their impact on progression of severe COVID-19 remains unclear. We prospectively enrolled 71 patients with COVID-19 associated critical illness, collected fecal specimens within 3 days of medical intensive care unit admission, defined microbiome compositions by shotgun metagenomic sequencing, and quantified microbiota-derived metabolites (NCT 04552834). Of the 71 patients, 39 survived and 32 died. Mortality was associated with increased representation of Proteobacteria in the fecal microbiota and decreased concentrations of fecal secondary bile acids and desaminotyrosine (DAT). A microbiome metabolic profile (MMP) that accounts for fecal secondary bile acids and desaminotyrosine concentrations was independently associated with progression of respiratory failure leading to mechanical ventilation. Our findings demonstrate that fecal microbiota composition and microbiota-derived metabolite concentrations can predict the trajectory of respiratory function and death in patients with severe SARS-Cov-2 infection and suggest that the gut-lung axis plays an important role in the recovery from COVID-19.
2023-05-02 | MTBLS5288 | MetaboLights
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:Acute respiratory illness (ARI) is the leading cause of asthma exacerbations yet the mechanisms underlying this association remain unclear. To address the deficiencies in our understanding of the molecular mechanisms driving ARI-induced asthma exacerbations, we undertook a transcriptional profiling study of the nasal mucosa over the course of ARI amongst individuals with a history of asthma, allergic rhinitis and no underlying respiratory disease. We found that ARI is characterized by dynamic, time-specific transcriptional profiles whose magnitudes of expression are influenced by underlying respiratory disease and the mucosal repair signature evoked during ARI. Most strikingly, we report that asthmatics that experience ARI-induced exacerbations are characterized by a reduced but prolonged inflammatory immune response, inadequate activation of mucosal repair and the expression of a newly described exacerbation-specific signature. Findings from our study represent a significant contribution towards clarifying the complex molecular interactions which typify ARI-induced asthma exacerbations. Upon the onset of ‘common cold’, volunteers were instructed to attend the first of three required visits to the study clinic. The first and second visits were designed to obtain samples and clinical data during the early and late stages of symptomatic illness respectively, whereas the third visit would occur when volunteers were asymptomatic and serve as a prospective baseline (BL) for the study.
2013-08-02 | E-GEOD-46171 | biostudies-arrayexpress
Project description:Understanding the pathology of COVID-19 is a global research priority. Early evidence suggests that the microbiome may be playing a role in disease progression, yet current studies report contradictory results. Here, we examine potential confounders in COVID-19 microbiome studies by analyzing the upper respiratory tract microbiome in well-phenotyped COVID-19 patients and controls combining microbiome sequencing, viral load determination, and immunoprofiling. We found that time in the intensive care unit and the type of oxygen support explained the most variation within the upper respiratory tract microbiome, dwarfing (non-significant) effects from viral load, disease severity, and immune status. Specifically, mechanical ventilation was linked to altered community structure, lower species- and higher strain-level diversity, and significant shifts in oral taxa previously associated with COVID-19.
| EGAS00001004951 | EGA
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