Host transcriptome profile of children with respiratory virus infection
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE155925 | GEO | 2021/01/29
REPOSITORIES: GEO
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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
Project description:Assessment of host gene expression is an emerging tool for the diagnosis of human infections. We compared nasal and blood samples for evaluation of the host transcriptomic response in children with acute respiratory syncytial virus (RSV), symptomatic and asymptomatic picornavirus (PV) infection, and virus-negative asymptomatic controls (Ctrls). RNA was extracted from nasal and blood samples and analyzed by microarray. Despite generally lower quality of nasal RNA, the number of genes detected in each sample type was equivalent. Nasal gene expression signal derived mainly from epithelial cells but also included a leukocyte contribution that was higher in samples from symptomatic children. The number of genes with increased expression in virus-infected children was comparable in nasal and blood samples, while nasal samples also had large numbers of genes with decreased expression, including many genes associated with ciliary function and assembly. Compared to symptomatic children, those with asymptomatic PV had fewer genes with increased or decreased expression in both sample types. Genes with increased expression in comparisons of symptomatic children versus Ctrls included genes associated with components of innate immunity and apoptosis. Children with RSV but not PV also had increased expression of genes related to the cell cycle. Using nested leave-one-pair-out cross-validation and supervised principal components analysis, we defined sets of genes whose expression patterns accurately classified subjects, with high area-under-the-curve values in receiver operating characteristic analysis. Our results support use of nasal samples to augment pathogen-based tests to diagnose viral respiratory infection.
2019-01-01 | GSE117827 | GEO
Project description:Respiratory viral infections follow an unpredictable clinical course in young children ranging from a common cold to respiratory failure. The transition from mild to severe disease occurs rapidly and is difficult to predict. The pathophysiology underlying disease severity has remained elusive. There is an urgent need to better understand the immune response in this disease to come up with biomarkers that may aid clinical decision making. In a prospective study, flow cytometric and genome-wide gene expression analyses were performed on blood samples of 26 children with a diagnosis of severe, moderate or mild Respiratory Syncytial Virus (RSV) infection. Differentially expressed genes were validated using Q-PCR in a second cohort of 80 children during three consecutive winter seasons. FACS analyses were also performed in the second cohort and on recovery samples of severe cases in the first cohort. Severe RSV infection was associated with a transient but marked decrease in CD4+ T, CD8+ T, and NK cells in peripheral blood. Gene expression analyses in both cohorts identified Olfactomedin4 (OLFM4) as a fully discriminative marker between children with mild and severe RSV infection, giving a PAM cross-validation error of 0%. Patients with an OLFM4 gene expression level above -7.5 were 6 times more likely to develop severe disease, after correction for age at hospitalization and gestational age. In conclusion, by combining genome-wide expression profiling of blood cell subsets with clinically well-annotated samples, OLFM4 was identified as a biomarker for severity of pediatric RSV infection.
2015-06-06 | GSE69606 | GEO
Project description:The objective of this study was to identify gene expression markers of disease severity in a cohort of RSV infected children Respiratory syncytial virus (RSV) is the number one pathogen causing lower respiratory tract infection that leads to hospitalization in young children. Despite growing insights in the disease pathogenesis, the clinical presentation in these children is highly variable and heterogeneous, and reliable markers predictive of disease progression are lacking. We characterized the host response to acute RSV infection to identify biomarkers associated with RSV disease and disease severity. Whole genome transcriptome was analysed early on the disease course in blood samples from otherwise healthy children <2 years of age, who were either hospitalized (n = 110) or evaluated as outpatients (n = 37) due to RSV infection. Age-matched non-RSV-infected healthy children (n = 51) were analysed in parallel. A clustering approach on the transcriptome data revealed biologically meaningful biomarkers associated with progression to severe RSV disease. Overall, the whole blood transcriptome pointed to alterations in frequency of specific immune cell types (neutrophils, T- and B-lymphocytes, NK cells, monocytes) in RSV-infected children. In addition, a cluster enriched for neutrophil degranulation genes, was highly correlated with clinical disease severity. The driver genes of this cluster (OLFM4, ELANE, MMP8, BPI, CEACAM8, LCN2, LTF and MPO) were selected and validated in independent existing transcriptomics datasets. We identified a set of genes involved in neutrophil degranulation as markers for RSV disease severity. Additional prospective studies using these markers are required to further confirm their value as predictive tool in routine clinical care.
2022-01-21 | GSE188427 | GEO
Project description:Human bocavirus (HBoV) is a newly discovered parvovirus identified from pooled nasopharyngeal aspirate specimens. Human bocavirus 1 (HBoV1) is a respiratory virus observed in respiratory samples from small children presenting bronchiolitis, wheezing, cough, fever, and rhinorrhea. It is the fourth most common virus detected in respiratory infections. DNA of HBoV1 was detected in up to 18% of nasal or nasopharyngeal samples and another study has been shown that over than 85% of children in the United States have antibodies to this virus. HBoV1 is a small DNA virus with a nonenveloped icosahedral capsid. This virus previously has been associated with wheezing, acute otitis media, severe pneumonia and respiratory failure. HBoV 1 has been also detected in the blood of acute respiratory patients and the selected group of immunocompromised children and also determined in healthy blood donors. The role of HBoV1 in the inflammatory process is poorly known. The aim of this project is to clarify the role of HBOV1 in the immunoregulatory mechanisms.
2023-01-06 | GSE143163 | GEO
Project description:Respiratory viral infections follow an unpredictable clinical course in young children ranging from a common cold to respiratory failure. The transition from mild to severe disease occurs rapidly and is difficult to predict. The pathophysiology underlying disease severity has remained elusive. There is an urgent need to better understand the immune response in this disease to come up with biomarkers that may aid clinical decision making. In a prospective study, flow cytometric and genome-wide gene expression analyses were performed on blood samples of 26 children with a diagnosis of severe, moderate or mild Respiratory Syncytial Virus (RSV) infection. Differentially expressed genes were validated using Q-PCR in a second cohort of 80 children during three consecutive winter seasons. FACS analyses were also performed in the second cohort and on recovery samples of severe cases in the first cohort. Severe RSV infection was associated with a transient but marked decrease in CD4+ T, CD8+ T, and NK cells in peripheral blood. Gene expression analyses in both cohorts identified Olfactomedin4 (OLFM4) as a fully discriminative marker between children with mild and severe RSV infection, giving a PAM cross-validation error of 0%. Patients with an OLFM4 gene expression level above -7.5 were 6 times more likely to develop severe disease, after correction for age at hospitalization and gestational age. In conclusion, by combining genome-wide expression profiling of blood cell subsets with clinically well-annotated samples, OLFM4 was identified as a biomarker for severity of pediatric RSV infection. Samples were taken of 26 patients with acute RSV infections, divided into mild (n=9), moderate (n=9) and severe (n=8) disease. From moderate and severe diseased patients recovery samples were obtained as well.
2015-06-06 | E-GEOD-69606 | biostudies-arrayexpress
Project description:Respiratory syncytial virus whole genome sequencing
| PRJNA1048457 | ENA
Project description:This series includes a 32-array training dataset used to evaluate E-Predict normalization and similarity metric parameters as well as 13 microarrays used as examples in (Urisman, et. al 2005). Training data set includes 15 independent HeLa RNAhybridizations (microarrays 1-15), 10 independent nasal lavage samples positive for Respiratory Syncytial virus (microarrays 16-25), and 7 independent nasal lavage samples positive for Influenza A virus (microarrays 26-32). Examples iclude a serum sample positive for Hepatitis B virus (microarray 33), a nasal lavage sample positive for both Influenza A virus and Respiratory Syncytial virus (microarray 34), and culture samples of 11 distinct Human Rhinovirus serotypes (microarrays 35-45). Keywords = virus detection, E-Predict, species identification, metagenomics Keywords: other
2005-03-01 | GSE2228 | GEO
Project description:Viral respiratory infections significantly affect young children, particularly extremely premature infants, resulting in high hospitalization rates and increased health-care burdens. Despite posing substantial health risks, airway immune responses in early life remain largely unexplored. Nasal epithelial cells, the primary defense against respiratory infections, are vital for understanding nasal immune responses and serve as a promising target for uncovering underlying molecular and cellular mechanisms. Using a trans-well pseudostratified nasal epithelial cell system, we examined age-dependent developmental differences and antiviral responses to influenza A and respiratory syncytial virus through systems biology approaches. Our studies revealed differences in innate-receptor repertoires, distinct developmental pathways, and differentially connected antiviral network circuits between neonatal and adult nasal epithelial cells. Consensus network analysis identified unique and shared cellular networks for influenza A and respiratory syncytial virus, emphasizing highly relevant virus-specific pathways. This research highlights the importance of nasal epithelial cells in innate antiviral immune responses and offers novel insights that should enable a deeper understanding of age-related differences in nasal epithelial cell immunity following respiratory virus infections.
2024-11-06 | PXD042209 | Pride
Project description:This series includes a 32-array training dataset used to evaluate E-Predict normalization and similarity metric parameters as well as 13 microarrays used as examples in (Urisman, et. al 2005). Training data set includes 15 independent HeLa RNAhybridizations (microarrays 1-15), 10 independent nasal lavage samples positive for Respiratory Syncytial virus (microarrays 16-25), and 7 independent nasal lavage samples positive for Influenza A virus (microarrays 26-32). Examples iclude a serum sample positive for Hepatitis B virus (microarray 33), a nasal lavage sample positive for both Influenza A virus and Respiratory Syncytial virus (microarray 34), and culture samples of 11 distinct Human Rhinovirus serotypes (microarrays 35-45). Keywords = virus detection, E-Predict, species identification, metagenomics
2010-06-10 | E-GEOD-2228 | biostudies-arrayexpress