Genome-wide meta-analysis of myasthenia gravis uncovers new loci and provides insights into polygenic prediction

Abstract

Myasthenia gravis (MG) is a rare autoantibody-mediated disease affecting the neuromuscular junction. We performed a genome-wide association study of 5708 MG cases and 432,028 controls of European ancestry and a replication study in 3989 cases and 226,643 controls provided by 23andMe Inc. We identified 12 independent genome-wide significant hits (P < 5e^-8) across 11 loci. Subgroup analyses revealed two of these were associated with early-onset (at age <50) and four with late-onset MG (at age ≥ 50). Imputation of human leukocyte antigen alleles revealed inverse effect sizes for late- and early-onset, suggesting a potential modulatory influence on the time of disease manifestation. We assessed the performance of polygenic risk scores for MG, which significantly predicted disease status in an independent target cohort, explaining 4.21% of the phenotypic variation (P = 5.12e^-9). With this work, we aim to enhance our understanding of the genetic architecture of MG.

Fig. 1. Manhattan plots depicting GWAS results.

Plot a depicts the GWAS results for the full MG dataset, plot b shows the results of the early-onset MG GWAS, and plot c displays the results of the late-onset MG GWAS. The two-sided -log₁₀ P-values from the inverse-variance-weighted fixed-effects meta-analyses are plotted on the y-axis and the chromosomal position on the x-axis in ascending order from chromosome 1 through 22. The dashed red horizontal line marks the Bonferroni corrected genome-wide significance threshold (P < 5e⁻⁸). Diamonds represent the index SNPs of the discovery GWAS. Red downward triangles indicate the index SNPs with a higher P-value in the replication and discovery meta-analysis while green upward triangles represent index SNPs with a lower P-value. Asterisks (*) indicate associations not previously reported.

Fig. 2. HLA association analysis results.

The forest plot displays the top risk-conferring and protective HLA allele across all main analyses. The log₁₀ of the odds ratio (OR) from inverse-variance-weighted fixed-effects meta-analysis is indicated as diamonds for each HLA allele and dataset used along with the 95% confidence intervals (error bars). Different P-value significance levels are indicated by asterisks for nominally significant (P < 0.05*), Bonferroni-corrected (P < 3.70e⁻⁴**), and genome-wide (P < 5e⁻⁸***). MG myasthenia gravis; EOMG early-onset myasthenia gravis, LOMG late-onset myasthenia gravis.

Fig. 3. Performance of MG polygenic risk scores.

Results of polygenic risk scoring of the combined target sample of CCM and LUMC cases and controls across all 10 PTs. Panel a shows the proportion of variance explained through the logistic regression models for PTs 1-10. Panel b shows the density distribution of the z-transformed best-performing PT (P < 0.001) for cases (orange) and controls (blue). Panel c shows the odds ratios (OR) from logistic regression models for PT P < 0.001 across ten deciles of the PRS along with the corresponding 95% confidence intervals (error bars). The target sample was scored using the combined MG leave-one-out training dataset of 5318 cases and 431,304 controls.PRS polygenic risk score.