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Analysis of CNS autoimmunity in genetically diverse mice reveals unique phenotypes and mechanisms.
- Source :
-
JCI insight [JCI Insight] 2024 Nov 08; Vol. 9 (21). Date of Electronic Publication: 2024 Nov 08. - Publication Year :
- 2024
-
Abstract
- Multiple sclerosis (MS) is a complex disease with significant heterogeneity in disease course and progression. Genetic studies have identified numerous loci associated with MS risk, but the genetic basis of disease progression remains elusive. To address this, we leveraged the Collaborative Cross (CC), a genetically diverse mouse strain panel, and experimental autoimmune encephalomyelitis (EAE). The 32 CC strains studied captured a wide spectrum of EAE severity, trajectory, and presentation, including severe-progressive, monophasic, relapsing remitting, and axial rotary-EAE (AR-EAE), accompanied by distinct immunopathology. Sex differences in EAE severity were observed in 6 strains. Quantitative trait locus analysis revealed distinct genetic linkage patterns for different EAE phenotypes, including EAE severity and incidence of AR-EAE. Machine learning-based approaches prioritized candidate genes for loci underlying EAE severity (Abcc4 and Gpc6) and AR-EAE (Yap1 and Dync2h1). This work expands the EAE phenotypic repertoire and identifies potentially novel loci controlling unique EAE phenotypes, supporting the hypothesis that heterogeneity in MS disease course is driven by genetic variation.
- Subjects :
- Animals
Mice
Female
Male
Autoimmunity genetics
Collaborative Cross Mice genetics
Disease Models, Animal
Disease Progression
Central Nervous System immunology
Central Nervous System pathology
YAP-Signaling Proteins genetics
Genetic Linkage
Encephalomyelitis, Autoimmune, Experimental genetics
Encephalomyelitis, Autoimmune, Experimental immunology
Phenotype
Quantitative Trait Loci
Multiple Sclerosis genetics
Multiple Sclerosis immunology
Subjects
Details
- Language :
- English
- ISSN :
- 2379-3708
- Volume :
- 9
- Issue :
- 21
- Database :
- MEDLINE
- Journal :
- JCI insight
- Publication Type :
- Academic Journal
- Accession number :
- 39325545
- Full Text :
- https://doi.org/10.1172/jci.insight.184138