Influenza is a major public health concern around the world and determining the prognosis of an infectedpatient who was otherwise healthy is often a major challenge. In 2009, infections with the H1N1 strainresulted in 274,000 hospitalizations and 12,470 deaths. Risk factors for morbidity and mortality include age,co-morbid illness, such as diabetes meNitus, and lower respiratory tract disease. Viral infection is initiated inthe upper ainway and, in severe cases, followed by progression to lower tract disease. In both human studiesand pre-clinical animal models, several biomarkers have been associated with more severe disease,including TNF-a, IL-6, and IL-17. Host response to influenza infection is a complex trait that involves entirehost-pathogen interaction networks of RNA transcripts, proteins and metabolites impacting cellular, tissueand whole organism behaviors that ultimately define both the risk and severity of infection. The complexarray of these interacting factors affect entire network states that in turn increase or decrease the risk ofinfection or the severity of response to infection. The focus of our project is to integrate multi-scale datacollected over the course of influenza infections-including system-wide transcriptomics and meta-transcriptomics, immunological response and physiological markers, along with viral diversity-in order toperform network analyses and develop computational models that predict severe disease outcome. Our goalis to leverage the power of high-dimensional, large-scale Omics data and mathematical modeling to identifyrisk-stratifying prognostic biomarkers that could be used in the development of point-of-care testingapplicable to clinical respiratory samples to identify patients at risk for severe influenza disease. To achievethis goal, we will build predictive models from molecular interaction networks, translated to specific severityoutcomes. We propose to use an age-dependent animal model (neonatal, adult and aged ferrets) andclinical human samples to collect biological measurements at multiple scales of host-virus interaction.

Public Health Relevance

National Institute of Health (NIH)
National Institute of Allergy and Infectious Diseases (NIAID)
Research Project--Cooperative Agreements (U01)
Project #
Application #
Study Section
Special Emphasis Panel (ZAI1-EC-M (M1))
Program Officer
Di Francesco, Valentina
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
New York University
Schools of Arts and Sciences
New York
United States
Zip Code
Wonderlich, Elizabeth R; Swan, Zachary D; Bissel, Stephanie J et al. (2017) Widespread Virus Replication in Alveoli Drives Acute Respiratory Distress Syndrome in Aerosolized H5N1 Influenza Infection of Macaques. J Immunol 198:1616-1626
McKenzie, Andrew T; Moyon, Sarah; Wang, Minghui et al. (2017) Multiscale network modeling of oligodendrocytes reveals molecular components of myelin dysregulation in Alzheimer's disease. Mol Neurodegener 12:82
Sobel Leonard, Ashley; Weissman, Daniel B; Greenbaum, Benjamin et al. (2017) Transmission Bottleneck Size Estimation from Pathogen Deep-Sequencing Data, with an Application to Human Influenza A Virus. J Virol 91:
Katsyv, Igor; Wang, Minghui; Song, Won Min et al. (2016) EPRS is a critical regulator of cell proliferation and estrogen signaling in ER+ breast cancer. Oncotarget 7:69592-69605
Zhang, Bin; Tran, Linh; Emilsson, Valur et al. (2016) Characterization of Genetic Networks Associated with Alzheimer's Disease. Methods Mol Biol 1303:459-77
Neelamegham, Sriram; Mahal, Lara K (2016) Multi-level regulation of cellular glycosylation: from genes to transcript to enzyme to structure. Curr Opin Struct Biol 40:145-152
Segal, Leopoldo N; Clemente, Jose C; Tsay, Jun-Chieh J et al. (2016) Enrichment of the lung microbiome with oral taxa is associated with lung inflammation of a Th17 phenotype. Nat Microbiol 1:16031
Kidd, Brian A; Hoffman, Gabriel; Zimmerman, Noah et al. (2016) Evaluation of direct-to-consumer low-volume lab tests in healthy adults. J Clin Invest 126:1734-44
McKenzie, Andrew T; Katsyv, Igor; Song, Won-Min et al. (2016) DGCA: A comprehensive R package for Differential Gene Correlation Analysis. BMC Syst Biol 10:106
Zhao, Yongzhong; Forst, Christian V; Sayegh, Camil E et al. (2016) Molecular and genetic inflammation networks in major human diseases. Mol Biosyst 12:2318-41

Showing the most recent 10 out of 28 publications