# Consortium for Viral Systems Biology Data Management and Bioinformatics Core

> **NIH NIH U19** · SCRIPPS RESEARCH INSTITUTE, THE · 2020 · $250,000

## Abstract

Project Summary/Abstract
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 affected 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 fight 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 fight the viruses. We will achieve this goal by
investigating the following three broad aims:
Aim 1. Define 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. Define 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.

## Key facts

- **NIH application ID:** 10248830
- **Project number:** 3U19AI135995-03S2
- **Recipient organization:** SCRIPPS RESEARCH INSTITUTE, THE
- **Principal Investigator:** ANDREW I SU
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $250,000
- **Award type:** 3
- **Project period:** 2018-02-01 → 2023-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10248830

## Citation

> US National Institutes of Health, RePORTER application 10248830, Consortium for Viral Systems Biology Data Management and Bioinformatics Core (3U19AI135995-03S2). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10248830. Licensed CC0.

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