Myasthenia Gravis (MG) is an autoimmune disease of the neuromuscular junction. The purpose of this study was to analyze the biological pathways and key genetic contributors that lead to MG. In this study, we performed functional annotation of the significant variants from the results of an MG Genome-Wide Association (GWAS) study on a Southeastern European population. Furthermore, the three approaches used were positional mapping of the SNPs, pathway analysis, and eQTL mapping. The positional and eQTL mapping were performed through FUMA. We annotated the SNPs to genes based on their physical position, and for the eQTL we used data from public repositories to test whether the expression of the gene is associated with allelic variation at the SNP. For the pathway analysis we used MAGMA; first, gene-analysis was performed in order to determine the p-value per gene based on whether the SNPs included in a gene were significantly associated with MG. Thirty-five genes were detected by all three approaches using the early-onset MG cases; all of them are located in the Major Histocompatibility Complex (MHC) region, which is reported to be associated with MG in previous studies. Five genes in the dataset including both early and late onset cases were detected by all three approaches, one being THEMIS and the other four are located in the MHC region. Overall, our study supports the results of previous studies as well as identifying novel risk factors. Further studies into the functions and mechanisms of these novel genes may allow researchers to develop therapeutics and treatments which would delay the progression of the disease or lessen the symptoms
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