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Use of Functional Genomics to Understand Influenza–Host Interactions

Infection with influenza typically results in mild‐to‐moderate illness in healthy individuals; however, it is responsible for 30,000–40,000 deaths each year in the United States. In extreme cases, such as the influenza pandemic of 1918, tens of millions of people have died from the infection. To pre...

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Detalles Bibliográficos
Autores principales: Fornek, Jamie L., Korth, Marcus J., Katze, Michael G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112328/
https://www.ncbi.nlm.nih.gov/pubmed/17765704
http://dx.doi.org/10.1016/S0065-3527(07)70003-9
Descripción
Sumario:Infection with influenza typically results in mild‐to‐moderate illness in healthy individuals; however, it is responsible for 30,000–40,000 deaths each year in the United States. In extreme cases, such as the influenza pandemic of 1918, tens of millions of people have died from the infection. To prepare for future influenza outbreaks, it is necessary to understand how the virus interacts with the host and to determine what makes certain strains of influenza highly pathogenic. Functional genomics provides a unique approach to this effort by allowing researchers to examine the effect of influenza infection on global host mRNA levels. Researchers are making increasing use of this approach to study virus–host interactions using a variety of model systems. For example, data obtained using microarray technology, in combination with mouse and macaque infection models, is providing exciting new insights into the pathogenicity of the 1918 virus. These studies suggest that the lethality associated with this virus is in part due to an aberrant and unchecked immune response. Progress is also being made toward using functional genomics in the diagnosis and prognosis of acute lung infections and in the development of more effective influenza vaccines and antivirals.