基于新一代测序数据识别影响重症肌无力药物反应的miRNA多态及机制研究

Myasthenia.gravis(MG) is an autoimmune disease resulting from the failure of neuromuscular transmission due to binding of autoantibodies to proteins involved in signaling at the neuromuscular junction (NMJ). MiRNA polymorphisms(miRSNP)could lead to the aberrant expression of drug target genes， which will result in differently drug response. Identifying miRSNPs influence drug response and their potential mechanisms will have significant effect on tailor-made medical therapy in MG.In this study, we will systematically identify MG risk miRNAs, risk mRNAs and risk single nucleotide polymorphisms (SNPs) by combining bioinformatics methods with next generation sequencing data. Then we will identify miRNA polymorphisms influence drug resistance/sensitivity based on high-throughput data. MG specific drug targets network as well as miRSNP-drug targets regulatory network will be constructed based on Protein-Protein Interaction Network. We will also perform topological and functional analysis of the network from multiple perspectives to explore novel drug targets associated MG. Furthermore, we will identify miRNA polymorphisms influence drug response and associated drugs at the pathway levels, which were validated by biological experiments. Therefore, we will propose a holistic strategy for elucidating the mechanism of miRNA polymorphisms influence drug response in MG, which holds new possibilities for the drug development and tailor-made medical therapy.

重症肌无力(myasthenia gravis,MG)是神经-肌肉接头传递功能障碍的自身免疫疾病。miRNA多态(miRSNP)可引起MG药靶的异常表达，进而导致MG的不同药物反应。系统识别影响MG药物反应的miRNA多态并阐明其作用机制，对于探索MG的致病机理和合理用药等具有重要意义。本课题结合新一代测序技术和生物信息学方法，识别MG风险miRNA集、风险mRNA集及风险SNP位点集，通过整合药物数据库、SNP数据库、miRNA数据库，利用高通量测序数据识别影响MG药物敏感性/耐药性的miRNA多态。此外，将利用蛋白质互作数据，构建MG特异的药靶互作网络及miRSNP-药靶调控网络，识别新的MG药靶。利用生物学通路等知识，从通路水平挖掘miRNA多态调控MG的药靶及相关药物，并通过生物学实验验证，阐明miRNA多态影响MG药物反应机制，为临床个体化用药的发展和新药开发提供理论和应用基础。

重症肌无力(MG)是神经-肌肉接头传递功能障碍的获得性自身免疫疾病。研究表明疾病通路在揭示疾病的发病机制中发挥着重要作用。疾病的风险基因及风险miRNAs参与调控疾病的发病通路，因此基于MG及药物调控通路的药物重定位的研究为识别MG的候选药物具有重要意义。本研究首先开发神经系统疾病(NSD)相关的非编码RNA数据库平台NSDNA (The Nervous System Disease NcRNAome Atlas)，用于管理和储存神经系统疾病包括MG相关的miRNA数据。基于NSDNA平台数据，解析miRNA在神经系统疾病中的协同调控作用，包括miRNA协同调控作用、miRNA模块和神经系统疾病模块，优化MG相关的miRNA。进一步识别差异表达的MG的miRNA和基因，采用通路(pathway)富集分析方法识别MG的风险通路，并且整合药物及靶点数据库（DrugBank）识别药物相关的通路。识别影响MG通路的药物进而为MG进行药物重定位。最终，利用生物学实验验证MG相关的miRNA及其调控的药物靶点。本课题发现多个基因及miRNA在MG的发病过程中出现功能失调，并影响着MG风险通路。MG的发病通路多与免疫及癌症相关揭示了MG复杂的发病机制。多个药物可作用于MG的风险通路，基于通路的药物重定位策略可为MG识别潜在的候选治疗药物。