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Approved research

Genomic analysis of severe outcomes to acute respiratory infection

Principal Investigator: Professor Jeffrey Shaman
Approved Research ID: 41369
Approval date: October 10th 2018

Lay summary

Each year respiratory viruses, such as influenza, respiratory syncytial virus, coronavirus and adenovirus, produce billions of infections worldwide. Within the broader population in a given year some individuals may not be infected at all whereas others may suffer multiple infections, and among the infected, some may experience little to no symptoms whereas others may be hospitalized or even die. Individual risk of infection by a particular circulating respiratory pathogen is likely controlled by a complex combination of factors associated with exposure dose, behavior, prior exposure to related pathogens, and genetic predisposition. Many studies have examined the effects of exposure dose, behavior and prior exposure on infection risk and even infection severity; however, to date, few studies have examined how genetic variability affects susceptibility to respiratory virus infection or the severity of infection. Here, we propose to use the vast data archives of the UK Biobank to determine which heritable factors influence the likelihood of hospitalization with an acute respiratory infection. Among Biobank participants, nearly 30,000 hospitalizations with a diagnosis of acute upper respiratory infection, acute lower respiratory infection, or influenza and pneumonia have been recorded. We will use the entire Biobank population of nearly 500,000 participants to determine whether these hospitalizations are associated with specific genetic variants. That is, we will determine which genetic traits are associated with severe outcomes due to respiratory infection. In the process of conducting this analysis we will account for other conditions that might affect symptom severity and hospitalization, such as chronic respiratory disease (e.g. asthma, chronic obstructive pulmonary disease) and autoimmune disease, as well as age and infectious agent. Our specific aims are: 1. To identify genes associated with inpatient diagnosis for acute respiratory infection. 2. To determine the strength of the association between these genes and risk of inpatient diagnosis with acute respiratory infection. Findings from this 24-month project will provide an initial characterization of genetic factors affecting immune response to respiratory infection. Based on these findings we can begin to identify genetic profiles of individuals at greater risk for severe outcomes and develop strategies for preemptive treatment. In this fashion, precision medicine, the targeting of treatments based on genetic risk, may ultimately be used to combat infectious disease, and in so doing keep people out of hospital and reduce mortality.