Lassa fever (LF), a severe hemorrhagic illness, is one of the most threatening infectious diseases known because of its unique status as both an immediate public health crisis and a bio-safety level 4 (BL-4) potential bioterror hazard. Endemic in large parts of West Africa, LF is estimated to hospitalize tens of thousands of individuals and cause several thousand deaths each year, with a case fatality rate in hospitalized patients that can reach 50% or more. Antibody-based surveys suggest that infection with the LF-causing agent, Lassa virus (LASV), is far more widespread than previously thought, with over 20% of Nigerians and Sierra Leoneans showing evidence of exposure. It is not known why many West Africans infected with LASV do not exhibit disease symptoms while others go on to suffer encephalitis, deafness and death, but recent genomic studies offer a hypothesis. A genome-wide survey of human genetic variation identified two genes biologically linked to LF infection among the strongest signals of recent human adaptation in West Africans. Further analysis of the LASV genome itself indicates that the virus has been circulating in West Africa for over a millennium. These findings-coupled with the high rates of disease, observed disease resistance, significant mortality and disability in affected individuals, and the widespread exposure to the rodent reservoir for the virus-suggest that LF is an ancient selective force, driving the emergence of genetic variants that confer resistance. LASV's unique status among BL-4 agents as a widespread, long-standing selective force is reflected in the serious global health risk it poses, but also provides a tremendous opportunity to study LF and the genetic mechanisms of resistance to it. Along with our partners in the US and Africa, we have built thriving clinical and research centers in Nigeria and Sierra Leone, and implemented diagnostics, training and infrastructure there to ensure safe, high-quality sample collection from patients hospitalized with LF. We have performed a preliminary genome scan and found several promising candidate adaptive and immune genetic variants associated with LF resistance. We have further developed a number of high-throughput technological approaches to rapidly validate and characterize these variants functionally. Based on our previous success in this area, we propose to pursue genetic determinants of resistance to LF through a larger patient collection, deeper diagnostic characterization, more extensive genetic studies, and functional characterization of candidate variants. Through our study, we hope to lay a foundation for the development of vaccines and diagnostics while also providing a path forward for further research into LASV and other BL-4 agents.

Public Health Relevance

Lassa fever, a severe hemorrhagic illness endemic in West Africa, poses perhaps the greatest potential threat among all infectious diseases due to its unique status as both an immediate public health crisis and a Biosafety Level 4 potential bioterror threat. Recent findings from genome scans suggest that Lassa fever is an ancient disease that over time has driven genetic variants conferring disease resistance to high prevalence in affected populations. We aim to identify and elucidate genetic factors in humans that underlie the wide variation in disease resistance, to provide insight into viral pathogenesis and potentially lead to new methods of intervention.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI114855-03
Application #
9189682
Study Section
Genetics of Health and Disease Study Section (GHD)
Program Officer
Repik, Patricia M
Project Start
2015-01-05
Project End
2019-12-31
Budget Start
2017-01-01
Budget End
2017-12-31
Support Year
3
Fiscal Year
2017
Total Cost
$756,479
Indirect Cost
$177,724
Name
Broad Institute, Inc.
Department
Type
Research Institutes
DUNS #
623544785
City
Cambridge
State
MA
Country
United States
Zip Code
02142
Colubri, Andres; Silver, Tom; Fradet, Terrence et al. (2016) Transforming Clinical Data into Actionable Prognosis Models: Machine-Learning Framework and Field-Deployable App to Predict Outcome of Ebola Patients. PLoS Negl Trop Dis 10:e0004549
Tewhey, Ryan; Kotliar, Dylan; Park, Daniel S et al. (2016) Direct Identification of Hundreds of Expression-Modulating Variants using a Multiplexed Reporter Assay. Cell 165:1519-29
Wohl, Shirlee; Schaffner, Stephen F; Sabeti, Pardis C (2016) Genomic Analysis of Viral Outbreaks. Annu Rev Virol 3:173-195
Yozwiak, Nathan L; Happi, Christian T; Grant, Donald S et al. (2016) Roots, Not Parachutes: Research Collaborations Combat Outbreaks. Cell 166:5-8
Andersen, Kristian G; Shapiro, B Jesse; Matranga, Christian B et al. (2015) Clinical Sequencing Uncovers Origins and Evolution of Lassa Virus. Cell 162:738-50