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A systems genomics approach uncovers molecular associates of RSV severity.
McCall, Matthew N; Chu, Chin-Yi; Wang, Lu; Benoodt, Lauren; Thakar, Juilee; Corbett, Anthony; Holden-Wiltse, Jeanne; Slaunwhite, Christopher; Grier, Alex; Gill, Steven R; Falsey, Ann R; Topham, David J; Caserta, Mary T; Walsh, Edward E; Qiu, Xing; Mariani, Thomas J.
Afiliação
  • McCall MN; Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester New York, United States of America.
  • Chu CY; Department of Biomedical Genetics, University of Rochester Medical Center, Rochester New York, United States of America.
  • Wang L; Division of Neonatology and Pediatric Molecular and Personalized Medicine Program, University of Rochester Medical Center, Rochester New York, United States of America.
  • Benoodt L; Department of Pediatrics, University of Rochester Medical Center, Rochester New York, United States of America.
  • Thakar J; Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester New York, United States of America.
  • Corbett A; Department of Biochemistry and Biophysics, University of Rochester Medical Center, Rochester New York, United States of America.
  • Holden-Wiltse J; Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester New York, United States of America.
  • Slaunwhite C; Department of Microbiology and Immunology, University of Rochester Medical Center, Rochester New York, United States of America.
  • Grier A; Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester New York, United States of America.
  • Gill SR; Clinical and Translational Science Institute, University of Rochester Medical Center, Rochester New York, United States of America.
  • Falsey AR; Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester New York, United States of America.
  • Topham DJ; Clinical and Translational Science Institute, University of Rochester Medical Center, Rochester New York, United States of America.
  • Caserta MT; Division of Neonatology and Pediatric Molecular and Personalized Medicine Program, University of Rochester Medical Center, Rochester New York, United States of America.
  • Walsh EE; Department of Pediatrics, University of Rochester Medical Center, Rochester New York, United States of America.
  • Qiu X; Department of Microbiology and Immunology, University of Rochester Medical Center, Rochester New York, United States of America.
  • Mariani TJ; Department of Microbiology and Immunology, University of Rochester Medical Center, Rochester New York, United States of America.
PLoS Comput Biol ; 17(12): e1009617, 2021 12.
Article em En | MEDLINE | ID: mdl-34962914
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Infecções por Vírus Respiratório Sincicial / Genômica Tipo de estudo: Risk_factors_studies Limite: Humans / Infant Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Infecções por Vírus Respiratório Sincicial / Genômica Tipo de estudo: Risk_factors_studies Limite: Humans / Infant Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos