Genomic Insights into Myasthenia Gravis Identify Distinct Immunological Mechanisms in Early and Late Onset Disease

Abstract

Objective: The purpose of this study was to identify disease relevant genes and explore underlying immunological mechanisms that contribute to early and late onset forms of myasthenia gravis.

Methods: We used a novel genomic methodology to integrate genomewide association study (GWAS) findings in myasthenia gravis with cell-type specific information, such as gene expression patterns and promotor-enhancer interactions, in order to identify disease-relevant genes. Subsequently, we conducted additional genomic investigations, including an expression quantitative analysis of 313 healthy people to provide mechanistic insights.

Results: We identified several genes that were specifically linked to early onset myasthenia gravis including TNIP1, ORMDL3, GSDMB, and TRAF3. We showed that regulators of toll-like receptor 4 signaling were enriched among these early onset disease genes (fold enrichment = 3.85, p = 6.4 × 10^-3 ). In contrast, T-cell regulators CD28 and CTLA4 were exclusively linked to late onset disease. We identified 2 causal genetic variants (rs231770 and rs231735; posterior probability = 0.98 and 0.91) near the CTLA4 gene. Subsequently, we demonstrated that these causal variants result in low expression of CTLA4 (rho = -0.66, p = 1.28 × 10^-38 and rho = -0.52, p = 7.01 × 10^-22 , for rs231735 and rs231770, respectively).

Interpretation: The disease-relevant genes identified in this study are a unique resource for many disciplines, including clinicians, scientists, and the pharmaceutical industry. The distinct immunological pathways linked to early and late onset myasthenia gravis carry important implications for drug repurposing opportunities and for future studies of drug development. ANN NEUROL 2021;90:455-463.

FIGURE 1

Disease relevant genes in early and late onset myasthenia gravis. Prioritized genes with direct genomic evidence based on proximity to myasthenia gravis associated SNPs accounting for linkage disequilibrium (nGene), physical interaction between myasthenia gravis associated SNPs and enhancer‐promoter regions based on chromatin conformation (cGene) and modulation of gene expression based on expression quantitative trait mapping (eGene) in major immune cell types. The y‐axis shows the gene priority rating and the x‐axis shows their chromosome position. The diameter of the circle represents the ‐log10 (p‐value) and boxes represent genes with multiple layers of genomic evidence in myasthenia gravis. [Color figure can be viewed at www.annalsofneurology.org]

FIGURE 2

CTLA4 locus and myasthenia gravis Violin plots showing the allelic effect of likely causal SNPs (x‐axis) on the expression levels in CD4+ cells (yaxis) for three different probes corresponding to CTLA4 gene. The lower and upper border of the box correspond to the first and third quartiles, respectively, the central line depicts the median, and whiskers extends from the borders to ±1.5xInter‐quantile range. Significant eQTLs at FDR 5% are highlighted in bold. [Color figure can be viewed at www.annalsofneurology.org]

FIGURE 3

Immune pathways in early and late onset myasthenia gravis. Overview of prioritized Reactome Immune System Pathways based on the top 1% of disease relevant genes in EO and LO form of myasthenia gravis. This highlights both shared and unique pathways between EO and LO disease. The x‐axis is log‐transformed fold‐change (FC) in enrichment. All pathways presented met a FDR < 0.05 cutoff. [Color figure can be viewed at www.annalsofneurology.org]