Article Text
Abstract
Background Myasthenia gravis (MG) is a rare autoimmune disorder affecting the neuromuscular junction (NMJ). Here, we investigate the genetic architecture of MG via a genome-wide association study (GWAS) of the largest MG data set analysed to date.
Methods We performed GWAS meta-analysis integrating three different data sets (total of 1401 cases and 3508 controls). We carried out human leucocyte antigen (HLA) fine-mapping, gene-based and tissue enrichment analyses and investigated genetic correlation with 13 other autoimmune disorders as well as pleiotropy across MG and correlated disorders.
Results We confirmed the previously reported MG association with TNFRSF11A (rs4369774; p=1.09×10−13, OR=1.4). Furthermore, gene-based analysis revealed AGRN as a novel MG susceptibility gene. HLA fine-mapping pointed to two independent MG loci: HLA-DRB1 and HLA-B. MG onset-specific analysis reveals differences in the genetic architecture of early-onset MG (EOMG) versus late-onset MG (LOMG). Furthermore, we find MG to be genetically correlated with type 1 diabetes (T1D), rheumatoid arthritis (RA), late-onset vitiligo and autoimmune thyroid disease (ATD). Cross-disorder meta-analysis reveals multiple risk loci that appear pleiotropic across MG and correlated disorders.
Discussion Our gene-based analysis identifies AGRN as a novel MG susceptibility gene, implicating for the first time a locus encoding a protein (agrin) that is directly relevant to NMJ activation. Mutations in AGRN have been found to underlie congenital myasthenic syndrome. Our results are also consistent with previous studies highlighting the role of HLA and TNFRSF11A in MG aetiology and the different risk genes in EOMG versus LOMG. Finally, we uncover the genetic correlation of MG with T1D, RA, ATD and late-onset vitiligo, pointing to shared underlying genetic mechanisms.
- autoimmune diseases
- human genetics
- neuromuscular diseases
Data availability statement
Data are available in a public, open access repository. Data are available upon reasonable request. Summary statistics will become available upon publication of this study at the Paschou Lab website. De-identified raw genotype data can become available upon request by email to the corresponding author (ppaschou@purdue.edu).
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Data availability statement
Data are available in a public, open access repository. Data are available upon reasonable request. Summary statistics will become available upon publication of this study at the Paschou Lab website. De-identified raw genotype data can become available upon request by email to the corresponding author (ppaschou@purdue.edu).
Footnotes
MG and PP are joint senior authors.
MG and PP contributed equally.
Contributors PPasc and MG conceived and designed the study. PPasc, MG, AT, ZZ and FT acquired the samples and data. PPasc, AT, ACF, MBM, FT and ZY analysed the data. PPasc, MG, ZZ, FT, Y-PC, GL, EY, EZ-P, JT, KKo, EM, SP, NP, DP, PPass, AR, MT, ET, XT, JY, JS, KP, KKl and ST contributed to data acquisition, sample collection and clinical characterisation. All authors contributed to drafting the manuscript and provided critical comments and revisions.
Funding This work was supported by NSF award #1715202, the European Social Fund, and Greek funds through the National Strategic Reference Framework (NSRF) THALES Programme 2012–2015 and the NSRF ARISTEIA II Programme 2007–2013 to PPasc, and grants from the Association Francaise contre les Myopathies (AFM, grant no 80077) to ST.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
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