Blood mRNA profiling to support prognosis of disease severity in respiratory syncytial virus infected infants
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ABSTRACT: 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.
ORGANISM(S): Homo sapiens
SUBMITTER: Arno Andeweg
PROVIDER: E-MTAB-5195 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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