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A systems genomics approach uncovers molecular associates of RSV severity
- Source :
- PLoS Computational Biology, Vol 17, Iss 12, p e1009617 (2021), PLoS Computational Biology
- Publication Year :
- 2021
- Publisher :
- Public Library of Science (PLoS), 2021.
-
Abstract
- Respiratory syncytial virus (RSV) infection results in millions of hospitalizations and thousands of deaths each year. Variations in the adaptive and innate immune response appear to be associated with RSV severity. To investigate the host response to RSV infection in infants, we performed a systems-level study of RSV pathophysiology, incorporating high-throughput measurements of the peripheral innate and adaptive immune systems and the airway epithelium and microbiota. We implemented a novel multi-omic data integration method based on multilayered principal component analysis, penalized regression, and feature weight back-propagation, which enabled us to identify cellular pathways associated with RSV severity. In both airway and immune cells, we found an association between RSV severity and activation of pathways controlling Th17 and acute phase response signaling, as well as inhibition of B cell receptor signaling. Dysregulation of both the humoral and mucosal response to RSV may play a critical role in determining illness severity.<br />Author summary This paper presents a novel approach to understanding the localized molecular responses to respiratory syncytial virus (RSV) and the system-level correlates of clinical outcomes. To do this, we developed a novel statistical method able to integrate high dimensional molecular data characterizing the host airway microbota and immune and nasal gene expression. We show that this integrative approach facilitates superior performance in estimating clinical outcome as opposed to any single data type. Using this approach, we identified both cell type-specific and shared biomarkers and regulatory pathways associated with RSV severity. Specifically, we identified an association between RSV severity, activation of pathways controlling Th17, and inhibition of B cell receptor signaling, which were present in both the site of infection airway and in peripheral immune cells. These results can guide future efforts to identify biomarkers for identifying or predicting illness severity following infant RSV infection. They may also be useful as biomarkers to inform the efficacy of future interventions (e.g., therapies) or preventative measures to suppress the rate of severe disease (e.g., vaccines).
- Subjects :
- Physiology
viruses
Gene Expression
Disease
Severity of Illness Index
Epithelium
Machine Learning
White Blood Cells
Mathematical and Statistical Techniques
Animal Cells
Medicine and Health Sciences
Medicine
Lymphocytes
RNA-Seq
Biology (General)
Principal Component Analysis
Ecology
Microbiota
Statistics
Acute-phase protein
Genomics
respiratory system
Pathophysiology
Physiological Parameters
Computational Theory and Mathematics
Medical Microbiology
Modeling and Simulation
Physical Sciences
Cellular Types
Anatomy
Nasal Cavity
Research Article
QH301-705.5
Immune Cells
Immunology
Microbial Genomics
Respiratory Syncytial Virus Infections
Research and Analysis Methods
Microbiology
Virus
Cellular and Molecular Neuroscience
Immune system
Gene Types
Genetics
Humans
Gene Regulation
Statistical Methods
Molecular Biology
Ecology, Evolution, Behavior and Systematics
Innate immune system
Blood Cells
business.industry
Body Weight
Biology and Life Sciences
Infant
Epithelial Cells
Cell Biology
Immunity, Innate
Biological Tissue
Multivariate Analysis
Respiratory epithelium
Regulator Genes
Microbiome
business
Mathematics
Subjects
Details
- ISSN :
- 15537358
- Volume :
- 17
- Database :
- OpenAIRE
- Journal :
- PLOS Computational Biology
- Accession number :
- edsair.doi.dedup.....dbbdc3019acabb65d8a303b663eacfb4