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Dataset Information

Airway gene-expression classifiers for respiratory syncytial virus (RSV) disease severity in infants.


ABSTRACT:

Background

A substantial number of infants infected with RSV develop severe symptoms requiring hospitalization. We currently lack accurate biomarkers that are associated with severe illness.

Method

We defined airway gene expression profiles based on RNA sequencing from nasal brush samples from 106 full-tem previously healthy RSV infected subjects during acute infection (day 1-10 of illness) and convalescence stage (day 28 of illness). All subjects were assigned a clinical illness severity score (GRSS). Using AIC-based model selection, we built a sparse linear correlate of GRSS based on 41 genes (NGSS1). We also built an alternate model based upon 13 genes associated with severe infection acutely but displaying stable expression over time (NGSS2).

Results

NGSS1 is stro

SUBMITTER: Wang L 

PROVIDER: S-EPMC7908785 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature