Host transcriptome profile of children with respiratory virus infection
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ABSTRACT:
PROVIDER: PRJNA656180 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12416400.fastq.gz | Fastqsanger.gz | |||
| SRR12416401.fastq.gz | Fastqsanger.gz | |||
| SRR12416402.fastq.gz | Fastqsanger.gz | |||
| SRR12416403.fastq.gz | Fastqsanger.gz | |||
| SRR12416404.fastq.gz | Fastqsanger.gz |
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Project description:Purpose: The aim of this study is to determine the expression profile in whole blood samples of children infected with respiratory syncytial virus and other respiratory viruses. Method: Host mRNA profiles in whole blood samples of children were generated by next-generation sequencing using Illumina Hiseq. Sequence reads were trimmed for adapter using skewer, mapped to reference human genome using STAR, and quantified using RSEM. Differential expression analysis was performed using DESeq2. Results: Transcriptional module analysis revealed dysregulation of genes related to inflammatory response, neutrophils, monocytes, B-cell and T-cell response. Conclusion: This study showed an imbalance in innate and adaptive immune responses in children with respiratory virus infections. This study also showed that NGS provides a comprehensive assessment of transcripts in whole blood samples.
2021-01-29 | GSE155925 | GEO
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.
2016-05-09 | GSE77087 | GEO
Project description:Analysis of transcriptional profiles in whole blood and nasopharyngeal swaps from children hospitalized with lower respiratory tract infections at their admission and their discharge, and diagnosed with either RSV or rhinovirus infections. The hypothesis is that this information will contribute to better understand the viral specific immunity and host responses to RSV infection and may suggest leads for the develoment of vaccines and specific treatment.
2017-04-14 | GSE97742 | GEO
Project description:Analysis of transcriptional profiles in whole blood and nasopharyngeal swaps from children hospitalized with lower respiratory tract infections at their admission and their discharge, and diagnosed with either RSV or rhinovirus infections. The hypothesis is that this information will contribute to better understand the viral specific immunity and host responses to RSV infection and may suggest leads for the develoment of vaccines and specific treatment.
2017-04-14 | GSE97741 | GEO
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:BACKGROUND. Lower respiratory tract infection (LRTI) is a leading cause of death in children worldwide. LRTI diagnosis is challenging since non-infectious respiratory illnesses appear clinically similar and existing microbiologic tests are often falsely negative or detect incidentally-carried microbes common in children. These challenges result in antimicrobial overuse and adverse patient outcomes. Lower airway metagenomics has the potential to detect host and microbial signatures of LRTI. Whether it can be applied at scale and in a pediatric population to enable improved diagnosis and precision treatment remains unclear. METHODS. We used tracheal aspirate RNA-sequencing to profile host gene expression and respiratory microbiota in 261 children with acute respiratory failure. We developed a random forest gene expression classifier for LRTI by training on patients with an established diagnosis of LRTI (n=117) or of non-infectious respiratory failure (n=50). We then developed a classifier that integrates the: i) host LRTI probability, ii) abundance of respiratory viruses, and iii) dominance in the lung microbiome of bacteria/fungi considered pathogenic by a rules-based algorithm. RESULTS. The host classifier achieved a median AUC of 0.967 by 5-fold cross-validation, driven by activation markers of T cells, alveolar macrophages and the interferon response. The integrated classifier achieved a median AUC of 0.986 and significantly increased the confidence of patient classifications. When applied to patients with an uncertain diagnosis (n=94), the integrated classifier indicated LRTI in 52% of cases and nominated likely causal pathogens in 98% of those. CONCLUSIONS. Lower airway metagenomics enables accurate LRTI diagnosis and pathogen identification in a heterogeneous cohort of critically ill children through integration of host, pathogen, and microbiome features.
2022-12-06 | GSE212532 | GEO
Project description:Analysis of transcriptional profiles in whole blood from children < 2 years of age (and healthy matched controls) with RSV, rhinovirus and influenza infection. The hypothesis tested is that transcriptional profile heterogeneity will reflect patient clinical heterogeneity and that RSV infection induces a distinct host response compared with influenza and rhinovirus infection Total RNA extracted from whole blood (lysed in Tempus tubes) drawn from individual pediatric patients with acute RSV, influenza and Rhinovirus lower respiratory tract infection. A total of 241 samples are analyzed: 135 with acute RSV LRTI, 30 with Rhinovirus LRTI, 16 with influenza LRTI, 39 age-sex matched healthy controls and 21 samples obtained one month after the acute hospitalization in children with RSV. Samples GSM1226237-GSM1226272, which were hybridized to Platform GPL10558, were normalized separately from the other Samples in this Series, which were hybridized to Platform GPL6884. 'GSE38900_non-normalized_GSM1226237-GSM1226272.txt.gz' includes the non-normalized data for Samples GSM1226237-GSM1226272; 'GSE38900_non-normalized.txt.gz' includes the non-normalized data for the other Samples.
2013-11-12 | E-GEOD-38900 | biostudies-arrayexpress
Project description:Host transcription profile in nasal epithelium and blood of hospitalized children under two years old with Respiratory Syncitial Virus infection
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Project description:Host transcriptional response to porcine reproductive and respiratory syndrome virus persistent infection
| PRJNA641670 | ENA
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