FluDyNeMo Parent Project

Influenza is a major public health issue around the world. Seasonal influenza accounts for approximately 20,000 deaths in the United States per year and pandemic influenza is a major public health concern. In 2009, infections with a novel H1N1 strain resulted in 274,000 hospitalizations and 12,470 deaths. Risk factors for morbidity and mortality include age, co-morbid illness–such as diabetes mellitus–and lower respiratory tract disease. In both human studies and pre-clinical animal models, several biomarkers have been associated with more severe disease. Preliminary studies show that the nasal and lower respiratory tract epithelial cells express receptors for cytokines associated with cell death that turn on specific signaling pathways and induce a unique transcriptome pattern within these cells. Thus, the epithelial transcriptome can be used to mine and understand which signals the epithelium is receiving from mucosal-associated lymphoid cells that are critical in driving influenza pathology. Based on these studies, we predict that epithelial transcriptomics can be used to model influenza severity in a predictive fashion. The overall goal of this project is to identify risk-stratifying prognostic biomarkers that could be used in the development of point-of-care testing that can easily be applied to clinically relevant respiratory samples, such as nasal washes, to identify patients at risk for severe influenza disease.