The Ebola epidemic that ravaged West Africa from 2013 to 2016 is by far the largest outbreak ever recorded. Weak healthcare infrastructure, community resistance, and a slow uncoordinated response, allowed the epidemic to spin out of control. The region, however, is no stranger to dealing with viral hemorrhagic fevers. Lassa fever is caused by infection with Lassa virus and is hyper-endemic in West Africa. Lassa fever is similar to Ebola in that infection with Lassa virus can lead to a severe hemorrhagic fever. Infections with both Lassa virus and Ebola virus can lead to deaths in more than 70% of hospitalized patients. It is estimated that tens of thousands of people die from Lassa fever each year. These numbers are likely underestimates, as the healthcare infrastructure in the a?ected countries is extremely weak, surveillance almost non-existent, and most patients never present in the hospital. Despite the high case fatality rates of hospitalized Ebola and Lassa fever patients, however, some people appear to be able to quickly ?ght the viruses, whereas others die quickly from infection. Yet, what distinguishes fatal from non-fatal disease and the development of symptomatic versus asymptomatic infection, remain largely unknown and severely understudied. The goal of the Consortium for Viral Systems Biology is to uncover the virus and human factors that determine how infected individuals are able to better ?ght the viruses. We will achieve this goal by investigating the following three broad aims:
Aim 1. De?ne virus and host factors responsible for survival and non-survival in Ebola and Lassa fever patients.
Aim 2. Identify factors that play roles in the development of severe long-term symptoms in survivors.
Aim 3. De?ne factors that determine whether human individuals develop symptomatic or asymptomatic disease. We will accomplish these aims by applying several ?omics? technologies, physiological measurements, and high-throughput experimental approaches to unique patient and survivor cohorts of Lassa fever and Ebola. We will develop novel predictive statistical models for identifying critical disease correlates and analyze large-scale data sets to pinpoint causal host-pathogen interactions. By elucidation the molecular networks that play critical roles in patient outcomes, this research will allow us to identify new targets for medicines and vaccines and inform personalized treatment strategies. Our study will also provide novel research frameworks and computational algorithms applicable to a wide range of other human pathogens.
Lassa and Ebola viruses are two of the most devastating human pathogens, yet some individuals are better able to ?ght infection than others. We will perform system-wide analyses of host and virus factors that contribute to the severity of human disease and clinical outcome. By creating large integrated data sets of genetic, immunological, biological, microbial, functional, and physiological features, we will build sophisticated predictive models that will reveal the molecular interactions underlying successful clearance of Lassa and Ebola viruses.
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