Dense module searching for gene networks associated with multiple sclerosis
Dense module searching for gene networks associated with multiple sclerosis
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DOI：
10.1186/s12920-020-0674-5
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发表时间：
2020-04-03
影响因子：
2.7
通讯作者：
Zhao, Zhongming
中科院分区：
文献类型：
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作者：
Manuel, Astrid M.;Dai, Yulin;Zhao, Zhongming
多发性硬化症（MS）是一种免疫系统攻击中枢神经系统的复杂疾病。对MS病因学的分子机制仍知之甚少。MS的全基因组关联研究（GWAS）已经确定了少量在基因组水平上显著的遗传位点，但它们主要是非编码变体。网络辅助分析可能有助于更好地解释具有关联信号的变体的功能作用和潜在的转化医学应用。我们的团队开发的密集模块搜索GWAS工具（dmGWAS版本2.4）应用于2个MS GWAS数据集（GeneMSA和IMSGC GWAS），使用人类蛋白质相互作用组作为参考网络。使用双重评价策略生成具有重现性的结果。结果每个独立的GWAS数据集识别出大约7500个重要的网络模块，从双重评估中识别出20个重要模块。其中，GRB 2、HDAC 1、JAK 2、MAPK 1和STAT 3为中心基因。顶部模块基因富含功能术语，如“神经胶质细胞分化的调节”（调整后的p值= 2.58 x 10（-3）），“T细胞共刺激”（调整后的p值= 2.11 x 10（-6））和“病毒受体活性”（调整后的p值= 1.67 x 10（-3））。有趣的是，顶级基因网络包括几个MS FDA批准的药物靶基因HDAC 1，IL 2 RA，KEAP 1和RELA。结论我们的dmGWAS网络分析突出了几个基因（GRB 2，HDAC 1，IL 2 RA，JAK 2，KEAP 1，MAPK 1，RELA和STAT 3）在顶级模块中，有希望解释GWAS信号和链接到MS药物靶点。富含胶质细胞分化的基因对于理解MS中的神经退行性过程和髓鞘再生治疗研究是重要的。重要的是，我们鉴定的富含T细胞共刺激和病毒受体活性的遗传信号支持MS的病毒感染发病假设。
Background Multiple sclerosis (MS) is a complex disease in which the immune system attacks the central nervous system. The molecular mechanisms contributing to the etiology of MS remain poorly understood. Genome-wide association studies (GWAS) of MS have identified a small number of genetic loci significant at the genome level, but they are mainly non-coding variants. Network-assisted analysis may help better interpret the functional roles of the variants with association signals and potential translational medicine application. The Dense Module Searching of GWAS tool (dmGWAS version 2.4) developed in our team is applied to 2 MS GWAS datasets (GeneMSA and IMSGC GWAS) using the human protein interactome as the reference network. A dual evaluation strategy is used to generate results with reproducibility. Results Approximately 7500 significant network modules were identified for each independent GWAS dataset, and 20 significant modules were identified from the dual evaluation. The top modules included GRB2, HDAC1, JAK2, MAPK1, and STAT3 as central genes. Top module genes were enriched with functional terms such as "regulation of glial cell differentiation" (adjusted p-value = 2.58 x 10(- 3)), "T-cell costimulation" (adjusted p-value = 2.11 x 10(- 6)) and "virus receptor activity" (adjusted p-value = 1.67 x 10(- 3)). Interestingly, top gene networks included several MS FDA approved drug target genes HDAC1, IL2RA, KEAP1, and RELA, Conclusions Our dmGWAS network analyses highlighted several genes (GRB2, HDAC1, IL2RA, JAK2, KEAP1, MAPK1, RELA and STAT3) in top modules that are promising to interpret GWAS signals and link to MS drug targets. The genes enriched with glial cell differentiation are important for understanding neurodegenerative processes in MS and for remyelination therapy investigation. Importantly, our identified genetic signals enriched in T cell costimulation and viral receptor activity supported the viral infection onset hypothesis for MS.