Diagnostic and Prognostic Biomarkers for Viral Severe Lung Disease

Columbia University Health Sciences, New York NY

Investigators

Linked publications, trials & patents

Abstract

Viral respiratory tract infections commonly cause hospitalizations, economic losses, morbidity and mortality in the US and worldwide. Influenza A virus (lAV), paramyxoviruses, rhinoviruses, human coronaviruses (HCoV), and other emerging, highly pathogenic respiratory viruses are a major global public health threat. Importantly, viral lung disease severity can range from mild self-limited infections to pneumonia followed by acute respiratory distress syndrome (ARDS) and death. This spectrum complicates treatment algorithms and underlies a critical need for rapid-response etiologic and prognostic indicators that readily inform treatment options in an outbreak setting. The overall goal of this program is to develop new platform technologies to rapidly recover and characterize new and emerging viruses in vitro and in vivo. Secondary objectives are to use functional genomics as diagnostic and prognostic indicators of virulence and disease severity following virus infection of the lung. Using a highly interactive team, we will test the hypothesis that -omics and other physiologic signatures will: i) predict etiology; ii) provide early prognostic indicators of virulence, and iii) inform public health measures and therapeutic responses. The program uses highly pathogenic HCoV strains (severe acute respiratory syndrome coronavirus and HCoV EMC/2012) and lAV strains (H1N1 Ca/04/2009 and H1N1 1918) and various clinical isolates as models. In Aim 1, we will develop platforms to recover novel respiratory viruses and identify diagnostic and prognostic indicators of severe lung disease by infecting primary human lung cells. In aim 2, we use the Collaborative Cross Mice to develop new animal models of human disease and to define conserved genomic signatures that correlate with etiology and disease severity and then validate the role of these biomarkers in models of outbred human populations infected with different high and low path respiratory viruses. In Aim 3, the goal is to use functional genomics and computational biology to not only diagnose virus etiology and forecast disease severity in the lung, but in parallel, develop a highly portable screening platform that rapidly identifies and then validates the lead compounds that attenuate disease severity in robust models of outbred human populations.