Transcriptome assists prognosis of disease severity in respiratory syncytial virus infected infants.

ABSTRACT: Respiratory syncytial virus (RSV) causes infections that range from common cold to severe lower respiratory tract infection requiring high-level medical care. Prediction of the course of disease in individual patients remains challenging at the first visit to the pediatric wards and RSV infections may rapidly progress to severe disease. In this study we investigate whether there exists a genomic signature that can accurately predict the course of RSV. We used early blood microarray transcriptome profiles from 39 hospitalized 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 hospital

SUBMITTER: Jong VL 

PROVIDER: S-EPMC5105123 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature