Project description:In this study we investigated whether there exists a genomic signature that can accurately predict the course of a respiratory syncytial virus (RSV) infection in hospitalized young infants. We used early blood microarray transcriptome profiles from 39 infants that were followed until recovery and of which the level of disease severity was determined retrospectively. Applying support vector machine learning on age by sex standardized transcriptomic data, an 84 gene signature was identified that discriminated hospitalized infants with eventually less severe RSV infection from infants that suffered from most severe RSV disease.
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.
Project description:Human respiratory syncytial virus (HRSV) is the main cause of bronchiolitis during the first year of life, but other viruses such as rhinovirus also occur and are clinically indistinguishable. In hospitalized infants with bronchiolitis, the analysis of the peripheral blood mononuclear cells (PBMC) gene expression might be useful for identification the etiologies caused by HRSV and human rhinovirus (HRV) and to the development of future tests, as well as to elucidate the pathogenic mechanisms triggered by different viral agents and new therapeutic possibilities. In this study, we conducted a comparative global gene expression analysis of infants with acute viral bronchiolitis infected by HRSV (HRSV group) or HRV (HRV group).
Project description:Rationale: Respiratory syncytial virus (RSV) is the leading cause of acute lower respiratory tract infections and hospitalizations in infants worldwide. Known risk factors, however, incompletely explain the variability of RSV disease severity among children. We postulate that severity of RSV infection is influenced in part by modulation of the host immune response by the local microbial ecosystem at the time of infection. Objectives: To define whether different nasopharyngeal microbiota profiles are associated with distinct host transcriptome profiles and severity in children with RSV infection. Methods: We analyzed the nasopharyngeal microbiota profiles of young children with mild and severe RSV disease and healthy matched controls by 16S-rRNA sequencing. In parallel, we analyzed whole blood gene expression profiles to study the relationship between microbial community composition, the RSV-induced host transcriptional response and clinical disease severity. Measurements and Main results: We identified five nasopharyngeal microbiota profiles characterized by enrichment of H. influenzae, Streptococcus, Corynebacterium, Moraxella or S. aureus. RSV infection and RSV hospitalization were positively associated with H. influenzae and Streptococcus, and negatively associated with S. aureus abundance, independent of age. The host response to RSV was defined by overexpression of interferon-related genes, and this was independent of the microbiota composition. On the other hand, transcriptome profiles of RSV infected children with H. influenzae and Streptococcus-dominated microbiota were characterized by greater overexpression of genes linked to toll-like receptor-signaling and neutrophil activation and were more frequently hospitalized Conclusions: Our data suggest an immunomodulatory role for the resident nasopharyngeal microbial community early in RSV infection, potentially affecting RSV disease severity.
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.
Project description:Background: There is limited data on how different RSV genotypes and associated viral loads influence disease phenotypes. We characterized the genetic variability of RSV strains during five non-consecutive respiratory seasons, and evaluated the role of RSV subtypes, genotypes and viral loads on clinical disease severity. Methods: Healthy infants hospitalized with RSV bronchiolitis were prospectively enrolled and nasopharyngeal samples obtained within 24h of hospitalization for RSV load quantitation by PCR, typing and genotyping. Parameters of disease severity were assessed, and multivariate models constructed to identify virologic and clinical factors predictive of clinical outcomes. Results: From March 2004 to April 2011, we enrolled 253 patients (56.5 % males; median age 2.1 (1.1-4.0) months). RSV A infections predominated over RSV B (69% vs. 31%; p<0.001) and showed greater genotype variability. The most common genotypes were RSV A/GA2, A/GA5 and RSV B/BA. Infants infected with RSV GA5 had higher viral loads compared with GA2 or BA infection (p<0.01), independent of duration of symptoms. After adjusting for other covariates, RSV A/GA5 infections were associated with longer hospital stay. Conclusions: RSV A infections were more frequent than RSV B infections and displayed greater genetic variability. Infections with GA5 were independently associated with clinical disease severity.
2018-03-21 | GSE103842 | GEO
Project description:Defective viral genomes determine respiratory syncytial virus disease severity in children and adults
| PRJNA613295 | ENA
Project description:Defective viral genomes determine respiratory syncytial virus disease severity in children and adults
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.