Dataset Information

Structural insights into the molecular mechanisms of myasthenia gravis and their therapeutic implications.

ABSTRACT: The nicotinic acetylcholine receptor (nAChR) is a major target of autoantibodies in myasthenia gravis (MG), an autoimmune disease that causes neuromuscular transmission dysfunction. Despite decades of research, the molecular mechanisms underlying MG have not been fully elucidated. Here, we present the crystal structure of the nAChR ?1 subunit bound by the Fab fragment of mAb35, a reference monoclonal antibody that causes experimental MG and competes with ~65% of antibodies from MG patients. Our structures reveal for the first time the detailed molecular interactions between MG antibodies and a core region on nAChR ?1. These structures suggest a major nAChR-binding mechanism shared by a large number of MG antibodies and the possibility to treat MG by blocking this binding mechanism. Structure-based modeling also provides insights into antibody-mediated nAChR cross-linking known to cause receptor degradation. Our studies establish a structural basis for further mechanistic studies and therapeutic development of MG.

SUBMITTER: Noridomi K

PROVIDER: S-EPMC5404922 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Structural insights into the molecular mechanisms of myasthenia gravis and their therapeutic implications.

Noridomi Kaori K Watanabe Go G Hansen Melissa N MN Han Gye Won GW Chen Lin L

eLife 20170425

The nicotinic acetylcholine receptor (nAChR) is a major target of autoantibodies in myasthenia gravis (MG), an autoimmune disease that causes neuromuscular transmission dysfunction. Despite decades of research, the molecular mechanisms underlying MG have not been fully elucidated. Here, we present the crystal structure of the nAChR α1 subunit bound by the Fab fragment of mAb35, a reference monoclonal antibody that causes experimental MG and competes with ~65% of antibodies from MG patients. Our ...[more]

PMID: 28440223

Similar Datasets

Project description:Background: Approximately 50% of thymoma patients also show myasthenia gravis (MG), which is an autoimmune disease; however, the pathogenesis of MG-associated thymoma remains elusive. Our aim was to investigate immune-related lncRNA profiles of a set of candidate genes for better understanding of the molecular mechanism underlying the pathogenesis of thymoma with or without MG. Methods: Molecular profiles of thymoma with or without MG were downloaded from The Cancer Genome Atlas, and Pearson's correlation analysis was performed to identify immune-related lncRNAs. T test was used to examine the differential expression and differential methylation between thymoma patients with or without MG. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed to predict the function of target genes of immune-related lncRNAs. Results: Analyses of the 87 thymoma samples with complete MG information revealed that 205 mRNAs and 56 lncRNAs showed up-regulated expression in thymoma with MG patients, while 458 mRNAs and 84 lncRNAs showed down-regulated expression. The methylation level of three immune-related lncRNAs (AP000787.1, AC004943.1, WT1-AS, FOXG1-AS1) was significantly decreased in thymoma tissues, and the methylation level of these immune-related lncRNAs (WT1-AS: Cor = 0.368, p < 0.001; FOXG1-AS1: Cor = 0.288, p < 0.01; AC004943.1: Cor = -0.236, p < 0.05) correlated with their expression. GO and KEGG pathway analysis revealed that targets of the immune-related lncRNA FOXG1-AS1 were enriched in small GTPase binding and herpes simplex virus 1 infection. Transcription coregulator activity and cell cycle were the most enriched pathways for targets of lncRNA AC004943.1. LncRNA WT1-AS targets were most enriched in actin binding and axon guidance. Conclusion: Our results revealed the immune-related molecular profiling of thymoma with MG and without MG and identified key pathways involved in the underlying molecular mechanism of thymoma-related MG. These findings provide insights for further research of potential markers for thymoma-related MG.

Project description:Myasthenia gravis (MG) is an autoimmune disease affecting the neuromuscular junction, whose clinical hallmark is muscle weakness and early fatigability. Azathioprine (AZA) is commonly used in Myasthenia Gravis therapy. AZA is a purine antagonist, which inhibits the cell cycle in the resting and DNA synthesis phases. It is usually used as an immunosuppressant to block T- and B-cell proliferation. AZA, bioconverted to 6-mercaptopurine by glutathione S-transferase (GST), can be metabolized either through the hypoxanthine phosphoribosyl transferase pathway to active 6-thioguanine nucleotides (6-TGN) or through the thiopurine S-methyltransferase (TPMT) pathway to inactive methyl-thiopurine metabolites. The incorporation of active 6-TGNs into DNA, causing breaks in DNA strands resulting in interference with RNA production and thereby protein synthesis, is responsible for the drug effect. The response to AZA is determined by which metabolic pathway is being favored. While balanced use of both HPRT and TPMT pathways results in responsiveness to AZA, hyperactivity of TPMT skews the balance towards the TPMT pathway and results in unresponsiveness to AZA with no pharmacological effect. In contrast, low TPMT activity skews the balance towards the HPRT pathway, resulting in increasing side-effects due to the accumulation of 6-TGNs. Current treatments for MG therapy are often inadequate because less than 40% of patients achieve complete remission with available drugs. This reflects the lack of drugs acting on target sites for which there is strong evidence of pathogenicity and the inability to identify responder patients. No criteria for responsiveness are available, exposing patients to unpredictable failures and unpredictable side effects. These individuals are at particular risk for adverse drug reaction (ADRs) or therapeutic failure. Genetic profiling with the Affymetrix drug metabolizing enzymes and transports genotyping array offers the ability to determine 1,931 variants and 225 genes involved in drug metabolism and disposition. Accordingly, the study of well-known drug-metabolizing genes can be involved in the specific metabolic pathway of a drug, which is more likely to define genotype-phenotype association and thereby genotype profiles relevant to drug response that can be applied as predictive biomarkers for pharmacological treatment.

Dataset Information

Structural insights into the molecular mechanisms of myasthenia gravis and their therapeutic implications.

Publications

Structural insights into the molecular mechanisms of myasthenia gravis and their therapeutic implications.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure