TheEbolaepidemicthatravagedWestAfricafrom2013to2016isbyfarthelargestoutbreakeverrecorded. Weak healthcare infrastructure, community resistance, and a slow uncoordinated response, allowed the epidemic tospinoutofcontrol.Theregion,however,isnostrangertodealingwithviralhemorrhagicfevers. LassafeveriscausedbyinfectionwithLassavirusandishyper-endemicinWestAfrica.Lassafeverissimilar toEbolainthatinfectionwithLassaviruscanleadtoaseverehemorrhagicfever.InfectionswithbothLassa 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 thehospital.Despitethehighcasefatalityratesof hospitalized Ebola and Lassa fever patients, however, some people appear to be able to quickly ?ght the viruses,whereasothersdiequicklyfrominfection.Yet,whatdistinguishesfatalfromnon-fataldiseaseandthe development of symptomatic versus asymptomatic infection, remain largely unknown and severely understudied.ThegoaloftheConsortiumforViralSystemsBiologyistouncoverthevirusandhumanfactors 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 cohortsofLassafeverandEbola. 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 thatplaycriticalrolesinpatientoutcomes,thisresearchwillallowustoidentifynewtargetsformedicinesand vaccinesandinformpersonalizedtreatmentstrategies.Ourstudywillalsoprovidenovelresearchframeworks and computational algorithms applicable to a wide range of other human pathogens.

Public Health Relevance

Lassa and Ebola virusesaretwoofthemostdevastatinghumanpathogens,yetsomeindividualsarebetter 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 largeintegrateddatasetsof genetic, immunological, biological, microbial, functional, and physiological features, we will build sophisticatedpredictivemodelsthatwillrevealthemolecularinteractionsunderlyingsuccessfulclearanceof Lassa and Ebola viruses.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program--Cooperative Agreements (U19)
Project #
1U19AI135995-01
Application #
9455502
Study Section
Special Emphasis Panel (ZAI1)
Program Officer
Brown, Liliana L
Project Start
2018-02-01
Project End
2023-01-31
Budget Start
2018-02-01
Budget End
2019-01-31
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Scripps Research Institute
Department
Type
DUNS #
781613492
City
La Jolla
State
CA
Country
United States
Zip Code
92037
Siddle, Katherine J; Eromon, Philomena; Barnes, Kayla G et al. (2018) Genomic Analysis of Lassa Virus during an Increase in Cases in Nigeria in 2018. N Engl J Med 379:1745-1753
Saphire, Erica Ollmann; Schendel, Sharon L; Fusco, Marnie L et al. (2018) Systematic Analysis of Monoclonal Antibodies against Ebola Virus GP Defines Features that Contribute to Protection. Cell 174:938-952.e13
Holmes, Edward C; Rambaut, Andrew; Andersen, Kristian G (2018) Pandemics: spend on surveillance, not prediction. Nature 558:180-182
Suchard, Marc A; Lemey, Philippe; Baele, Guy et al. (2018) Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evol 4:vey016
Gunn, Bronwyn M; Yu, Wen-Han; Karim, Marcus M et al. (2018) A Role for Fc Function in Therapeutic Monoclonal Antibody-Mediated Protection against Ebola Virus. Cell Host Microbe 24:221-233.e5
Saphire, Erica Ollmann; Schendel, Sharon L; Gunn, Bronwyn M et al. (2018) Antibody-mediated protection against Ebola virus. Nat Immunol 19:1169-1178
Rambaut, Andrew; Drummond, Alexei J; Xie, Dong et al. (2018) Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7. Syst Biol 67:901-904