Identification of genetic risk loci and prioritization of genes and pathways for myasthenia gravis: a genome-wide association study

Abstract

Myasthenia gravis is a chronic autoimmune disease characterized by autoantibody-mediated interference of signal transmission across the neuromuscular junction. We performed a genome-wide association study (GWAS) involving 1,873 patients diagnosed with acetylcholine receptor antibody-positive myasthenia gravis and 36,370 healthy individuals to identify disease-associated genetic risk loci. Replication of the discovered loci was attempted in an independent cohort from the UK Biobank. We also performed a transcriptome-wide association study (TWAS) using expression data from skeletal muscle, whole blood, and tibial nerve to test the effects of disease-associated polymorphisms on gene expression. We discovered two signals in the genes encoding acetylcholine receptor subunits that are the most common antigenic target of the autoantibodies: a GWAS signal within the cholinergic receptor nicotinic alpha 1 subunit (CHRNA1) gene and a TWAS association with the cholinergic receptor nicotinic beta 1 subunit (CHRNB1) gene in normal skeletal muscle. Two other loci were discovered on 10p14 and 11q21, and the previous association signals at PTPN22, HLA-DQA1/HLA-B, and TNFRSF11A were confirmed. Subgroup analyses demonstrate that early- and late-onset cases have different genetic risk factors. Genetic correlation analysis confirmed a genetic link between myasthenia gravis and other autoimmune diseases, such as hypothyroidism, rheumatoid arthritis, multiple sclerosis, and type 1 diabetes. Finally, we applied Priority Index analysis to identify potentially druggable genes/proteins and pathways. This study provides insight into the genetic architecture underlying myasthenia gravis and demonstrates that genetic factors within the loci encoding acetylcholine receptor subunits contribute to its pathogenesis.

Keywords: genetic correlation; genome-wide association study; myasthenia gravis; pathway analysis.

Fig. 1.

Analysis workflow. The flow diagram gives an overview of the analyses performed in this study. The Left panel depicts the GWAS of 1) all, 2) early-onset, and 3) late-onset myasthenia gravis. The Manhattan plots and variant and gene names do not correspond to the actual results. The Right-hand panels depict the advanced analytical approaches applied to the data, including TWAS (Right Top) to identify genes whose expression may mediate the risk of developing myasthenia gravis, genetic correlation (Right Middle) to identify diseases that overlap with myasthenia gravis, and Priority Index (Right Bottom) to identify gene targets and pathways that may be amenable to therapeutic intervention. The image was generated using BioRender.com.

Fig. 2.

GWAS in myasthenia gravis. The Top (A), Middle (B), and Bottom (C) panels show the Manhattan plots depicting the GWAS results of the overall discovery cohort (n = 1,873 myasthenia gravis cases and 36,370 control individuals), the early-onset cohort (n = 595 cases and 2,718 controls), and the late-onset cohort (n = 1,278 cases and 33,652 controls). The x-axis denotes the chromosomal position for the autosomes in hg38, and the y-axis indicates the association P values on a −log₁₀ scale. Each dot represents a variant, where red dots denote variants that reached genome-wide significance and orange dots denote variants that are one log-fold lower than the significant threshold. A dashed line shows the conservative Bonferroni threshold for genome-wide significance (P = 5.0 × 10⁻⁸). Black font highlights known risk loci, while green font indicates association signals identified in this study not previously reported. The subsignificant hit on chromosome 17 corresponding to the CHRNB1 locus is marked with an asterisk.

Fig. 3.

TWAS in myasthenia gravis. Manhattan plots depicting the TWAS results of the overall discovery cohort (n = 1,873 myasthenia gravis cases and 36,370 control individuals) using expression data for skeletal muscle obtained from GTEx. The x-axis denotes the chromosomal position for the autosomes in hg38, and the y-axis indicates the association P values on a −log₁₀ scale. Each dot represents a variant, where red dots denote variants that reached genome-wide significance and permutation P values < 0.05. The significance threshold for skeletal muscle was 6.8 × 10⁻⁶ and is shown with the dashed line. The orange dots denote variants that are one log-fold lower than the significant threshold. The dots with a black diamond outline are variants with colocalization posterior prior probability H4 (PPH4) > 0.75.

Fig. 4.

Prioritization of immunological targets in myasthenia gravis based on Priority Index and druggability. (A) Autosomal genes were scored based on the gene-predictor matrix generated from the Priority Index pipeline. The x-axis denotes the chromosomal position in hg38, and the y-axis indicates the Priority Index rating on a scale of 0 to 5. Each dot represents a gene, and the red dots indicate the top 30 genes. Dots with a black diamond outline are druggable genes based on a Pocketome analysis. The red dashed line shows the threshold for the top 30 genes (scale > 3.9). (B) An enrichment analysis shows the prioritized target pathways in the immune and the signal transduction modules. The x-axis shows the REACTOME pathways that were significantly overrepresented by the top genes. The y-axis denotes the strength of the enrichment quantified by the OR on a log₂ scale. The 95% CIs are represented by lines flanking each dot. Enrichment significance was measured by calculating the false discovery rate (FDR) from a one-sided Fisher’s exact test.