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Characterizing the Role of Genetics in Neuropathology and Associated CNS Autoimmune Disease Severity Using Genetically Diverse Mice
Downs, Lauren
Downs, Lauren
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Abstract
Multiple Sclerosis (MS) is a heterogenous, autoimmune-driven disease of central nervous
system (CNS). To model MS disease course heterogeneity, we used the genetically diverse
Collaborative Cross (CC) mouse strain panel and experimental autoimmune encephalomyelitis
(EAE), a mouse model of MS. A range of disease presentations and severity were observed across
the 32 studied CC strains. Our published histopathologic analysis of CNS inflammation and
demyelination in two CC strains with high EAE severity demonstrated increased histopathology
scores relative to refence controls. To assess the hypothesis that EAE severity correlates with the
severity of CNS pathology, two low, medium, and high EAE severity CC strains were selected for
semi-quantitative histopathological analysis. This analysis revealed a positive correlation between
EAE severity and pathological severity, especially for spinal cord demyelination. Histopathological
analysis also revealed a distinct pattern of perivascular pathology in strains with distinct disease
courses, including CC043 mice which present with a secondary progressive disease subtype and
CC011 mice which have little to no symptomology. Additionally, to determine the genetic factors
associated with pathological severity, quantitative trait loci (QTL) mapping was performed on the
histopathology data for 9 of the CC strains, but no significant QTL were found, likely due to the
limited number of strain/samples. However, average percent weight change during EAE for all 32
CC strains was shown to be an improved quantitative trait variable (QTV) that was more continuous
and objective, compared to the disease scoring systems. This QTV revealed novel QTL and showed
higher significance from previous, score-based mapping attempts. Candidate genes determined
from weight change QTL mapping were found using single nucleotide polymorphism (SNP) analysis
and revealed potential connections to disease mechanisms.
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2026-04-28
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College of Engineering and Mathematical Sciences