Jinsheng Yu1, Derick R Peterson2, Andrea M Baran2, Soumyaroop Bhattacharya3, Todd N Wylie4,5, Ann R Falsey6, Thomas J Mariani3, Gregory A Storch4. 1. Department of Genetics, Washington University School of Medicine, St. Louis, Missouri. 2. Department of Biostatistics and Computational Biology, University of Rochester School of Medicine, New York. 3. Division of Neonatology and Pediatric Molecular and Personalized Medicine Program, Department of Pediatrics, University of Rochester School of Medicine, New York. 4. Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri. 5. McDonnell Genome Institute, Washington University School of Medicine, St. Louis, Missouri. 6. Department of Medicine, University of Rochester School of Medicine, New York.
Abstract
BACKGROUND: Recently there has been a growing interest in the potential for host transcriptomic analysis to augment the diagnosis of infectious diseases. METHODS: We compared nasal and blood samples for evaluation of the host transcriptomic response in children with acute respiratory syncytial virus (RSV) infection, symptomatic non-RSV respiratory virus infection, asymptomatic rhinovirus infection, and virus-negative asymptomatic controls. We used nested leave-one-pair-out cross-validation and supervised principal components analysis to define small sets of genes whose expression patterns accurately classified subjects. We validated gene classification scores using an external data set. RESULTS: Despite lower quality of nasal RNA, the number of genes detected by microarray in each sample type was equivalent. Nasal gene expression signal derived mainly from epithelial cells but also included a variable leukocyte contribution. The number of genes with increased expression in virus-infected children was comparable in nasal and blood samples, while nasal samples also had decreased expression of many genes associated with ciliary function and assembly. Nasal gene expression signatures were as good or better for discriminating between symptomatic, asymptomatic, and uninfected children. CONCLSUSIONS: Our results support the use of nasal samples to augment pathogen-based tests to diagnose viral respiratory infection.
BACKGROUND: Recently there has been a growing interest in the potential for host transcriptomic analysis to augment the diagnosis of infectious diseases. METHODS: We compared nasal and blood samples for evaluation of the host transcriptomic response in children with acute respiratory syncytial virus (RSV) infection, symptomatic non-RSV respiratory virus infection, asymptomatic rhinovirus infection, and virus-negative asymptomatic controls. We used nested leave-one-pair-out cross-validation and supervised principal components analysis to define small sets of genes whose expression patterns accurately classified subjects. We validated gene classification scores using an external data set. RESULTS: Despite lower quality of nasal RNA, the number of genes detected by microarray in each sample type was equivalent. Nasal gene expression signal derived mainly from epithelial cells but also included a variable leukocyte contribution. The number of genes with increased expression in virus-infected children was comparable in nasal and blood samples, while nasal samples also had decreased expression of many genes associated with ciliary function and assembly. Nasal gene expression signatures were as good or better for discriminating between symptomatic, asymptomatic, and uninfected children. CONCLSUSIONS: Our results support the use of nasal samples to augment pathogen-based tests to diagnose viral respiratory infection.
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