Analysis of CNS autoimmunity in genetically diverse mice reveals unique phenotypes and mechanisms
Emily A. Nelson, Anna L. Tyler, Taylor Lakusta-Wong, Karolyn G. Lahue, Katherine C. Hankes, Cory Teuscher, Rachel M. Lynch, Martin T. Ferris, J. Matthew Mahoney, Dimitry N. Krementsov
Emily A. Nelson, Anna L. Tyler, Taylor Lakusta-Wong, Karolyn G. Lahue, Katherine C. Hankes, Cory Teuscher, Rachel M. Lynch, Martin T. Ferris, J. Matthew Mahoney, Dimitry N. Krementsov
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Research Article Genetics

Analysis of CNS autoimmunity in genetically diverse mice reveals unique phenotypes and mechanisms

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.

Authors

Emily A. Nelson, Anna L. Tyler, Taylor Lakusta-Wong, Karolyn G. Lahue, Katherine C. Hankes, Cory Teuscher, Rachel M. Lynch, Martin T. Ferris, J. Matthew Mahoney, Dimitry N. Krementsov

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Figure 6

Peripheral immune and CNS intrinsic factors drive RR-EAE in CC002 mice.

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Peripheral immune and CNS intrinsic factors drive RR-EAE in CC002 mice. ...
(A) B6 and CC002 mice were subjected to BM ablation and reconstitution to create reciprocal BM chimeric mice, designated as B6→B6 (7M, 4F), B6→02 (7M, 1F), 02→B6 (6M, 4F), 02→02 (6M, 1F) and illustrated in the schematic. Mice were rested for a total of 8 weeks prior to EAE induction as described in Figure 1. Mice were observed for a total of 34 days. On D34, spleen (B6→B6: 7M, 4F; B6→02: 7M, 1F; 02→B6: 6M, 4F; 02→02: 6M, 1F), and spinal cord (n = 4 males/chimera) tissues were collected and processed for flow cytometric staining. (B–G) Percent chimerism was assessed in B6→B6, B6→02, and 02→B6 for splenic CD11b+ cells (CD45+CD11b+CD19–) (B), CD19+ cells (CD45+CD11b–CD19+) (C), CD4+ T cells (CD45+CD11b–CD19–TCRβ+CD4+) (D), and CD8+ T cells (CD45+CD11b–CD19–TCRβ+CD8+) (E), as well as infiltrating CD4+ (F) and CD8+ (G) T cells in the spinal cord. Bars in B–G represent average percent chimerism for donor (dark gray) and host (light gray), while corresponding colored dots demonstrate individual samples. (H) Disease course profiles for B6→B6, B6→02, 02→B6, and 02→02 displayed as classic-EAE. (I–K) Comparison of spinal cord infiltrating immune cell populations in B6→B6, B6→02, 02→B6, and 02→02 for CD11b+ cells (I), CD19+ cells (J), CD4+ T cells (K), and CD8+ T cells (L). Significance of differences between groups was determined via 1-way ANOVA with Tukey’s multiple-comparison test and indicated by brackets and asterisks where significant. P ≤ 0.05.