Towards Better Understanding and Predicting Severe Dengue
Abstract
Dengue virus (DENV), the FY18 PRMRP Topic Area this project addresses, represents a major threat to military Service members and global health. Dengue has substantially weakened US military operations since the Spanish–American War and continues to represent a threat to military troops. Dengue infection is estimated to affect up to 400 million people annually in over 100 endemic countries and has become a leading cause of morbidity and mortality. With this global increase in dengue incidence and severity, a larger number of cases is already being reported among the active-duty personnel of the US Department of Defense and is expected to continue to increase. Approximately 5%-20% of symptomatic patients progress to severe dengue (SD), manifested by complications and sometimes death. Early administration of supportive care reduces mortality; however, there are no accurate means to predict which patients will progress to SD. There is thus critical need for biomarkers to effectively predict the development of severe complications and allow adequate patient triage. Moreover, there is critical need for drugs and effective vaccines to combat dengue and/or prevent it. Our overall goal is to understand the virus-host interplay involved in the development of SD more deeply and advance the development of both prognostic tools for early identification of patients at risk for progression to SD and antiviral strategies to prevent SD. We established a unique cohort in Colombia–dengue patients who present prior to progressing to SD. Moreover, we developed a novel platform, which transforms our ability to monitor the host response to dengue in thousands of individual cells. Additionally, we used a novel bioinformatics analysis of the publicly available gene expression data sets to identify a 20-gene set predictive of SD. Lastly, we demonstrated a proof-of-concept for the utility of targeting host factors (rather than viral factors) as an approach to combat DENV. The goals of this project are to (i) profile the host response to natural dengue infection in multiple cell subtypes in order to identify candidate biomarkers of dengue severity and novel targets for host-targeted anti-DENV agents and (ii) determine the feasibility for predicting SD by the novel 20-gene set. To achieve these goals, we will monitor the host response to natural dengue infection in blood samples from the Colombia cohort using our novel platform and advanced immune monitoring technologies. The functional relevance of prioritized biomarker and druggable host target candidates emerging from these studies will be probed and their roles in the development of SD and the DENV life cycle will be deciphered. In parallel, we will validate the 20-gene set predictive of SD in a recently published cohort and in the Colombia dengue cohort, monitor its dynamic during the disease course, and define its specificity. The predicted short-term impact is that this project will provide novel insights into how SD develops and how the immune system responds to natural dengue infection. It will also yield a validated gene set predictive of SD and host functions as candidate targets for antivirals. The long-term impact is that this project will advance the development of a paradigm-shifting molecular prognostic assay for predicting SD prior to its onset. Such an assay can help define the level of care for specific patients, thereby reducing morbidity and mortality while allocating resources more effectively. The latter is particularly important in the setting of an outbreak. Such a product can also be used to guide the design of therapeutic clinical trials and future treatment decisions once anti-DENV therapies (such as those we are developing) are approved. Lastly, this project will advance the development of antiviral approaches to combat DENV and possibly other emerging viruses. By advancing the development of dengue prognostic assays and antiviral strategies, this
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Nov 19, 2019
- Source ID
- W81XWH1910235
Entities
People
- Shirit Einav
Organizations
- Stanford University
- United States Army