Infection by a given virus can cause diverse neurological outcomes and disease pathologies, influenced by the genetic background of the host. In mice, Theiler's murine encephalomyelitis virus (TMEV) infection leads to heterogeneous neurological conditions, depending on mouse strain infected. Because of the relevance of TMEV infection as a tool for studying virally-influenced neurological conditions in humans, there is a critical need to determine genetic variants and their mechanisms that link TMEV infection to disease outcome. The long-term goal is to identify and characterize environmental and genetic interactions that contribute to individual variation in response to viral infection. The objective of this application is to determine how genetic background influences disease diversity following TMEV infection. The central hypothesis is that genetic background, as modeled by a new population-based mouse model, will differentially modify susceptibility to TMEV-induced diseases based upon genetic polymorphisms. The rationale for the proposed research is that a delineation of the genetic effects underlying the diverse outcomes of TMEV infection is likely to contribute new insights into the heterogeneity of virally induced human neurological conditions. The hypothesis will be tested with three specific aims: 1) Evaluate strains of the Collaborative Cross (CC) mouse resource for phenotypic variation in response to TMEV infection, 2) Evaluate host genome regions for associations with TMEV-induced phenotypes, and 3) Identify phenotypic modules governed by shared mechanisms.
Aim 1 is based on published and preliminary data showing that TMEV infection causes diverse outcomes depending on the genetic background of the mouse. Neurological and behavioral phenotyping tests, ELISAs, and histology will be used to test the hypothesis that the disease pathologies of TMEV infection in different CC mice demonstrate a hierarchy, to facilitate the identification of groups of mice with similar characteristics that can be linked to genetically-diverse CC lines.
For Aim 2, RNA sequencing and QTL analyses will be used to test the hypothesis that genomic diversity within CC mice influences variable disease phenotypes.
In Aim 3, cytokine analyses, modularity clustering and candidate gene allele association will be used to test the hypothesis that the phenotypic diversity among CC strains can be clustered into modules which can be used to identify shared mechanisms. Our contribution here is expected to be an understanding of the genetic determinants responsible for phenotypic diversity following TMEV infection using the CC population of mice. The proposed research is innovative because it uses an experimental mouse model that captures the breadth of genetic diversity typically found in human populations, thus comprehensively addressing host contributions to virally influenced neurological conditions. This research is significant because it is expected to constitute an early step in a continuum of research that will increase knowledge about virally influenced complex neurological conditions in humans and ultimately lead to the development of novel predictive models and therapies.

Public Health Relevance

The proposed research is relevant to public health because the identification of the genetic underpinnings behind variable host responses to infection with Theiler's murine encephalomyelitis virus (TMEV) will increase understanding of the contributions of viral infections to complex conditions. This knowledge will contribute to a framework for the subsequent development of preventive and/or treatment interventions for pathogenic viral infections. Thus the proposed research is relevant to the mission of the NIH pertaining to developing fundamental knowledge that will help reduce the burden of human disability.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS103934-04
Application #
10055969
Study Section
Genetic Variation and Evolution Study Section (GVE)
Program Officer
Wong, May
Project Start
2017-12-01
Project End
2022-11-30
Budget Start
2020-12-01
Budget End
2021-11-30
Support Year
4
Fiscal Year
2021
Total Cost
Indirect Cost
Name
Texas A&M University
Department
Veterinary Sciences
Type
Schools of Veterinary Medicine
DUNS #
020271826
City
College Station
State
TX
Country
United States
Zip Code
77845
Brinkmeyer-Langford, Candice L; Rech, Raquel; Amstalden, Katia et al. (2017) Host genetic background influences diverse neurological responses to viral infection in mice. Sci Rep 7:12194