Identifying and Characterizing the Functional SNPs on RA-Associated loci involved in CD40/NF-kB Signal

摘要 对自身免疫性疾病如类风湿性关节炎的致病机理了解有限，也没有治愈方法。 (RA)。全基因组关联研究已确定了约200个RA相关基因座。这些基因座 代表约4573个遗传变异，在大多数情况下是连锁中的单核苷酸多态(SNP) 不平衡(LD)。理论上，每个LD中只有一个功能性SNP(FSNP)负责 类风湿关节炎的发病机制。然而，Gwas没有透露哪个是每个LD中的fSNP。这是技术上的 缺陷在GWAS和特定机制之间留下了一个缺口，该机制将为 生物学洞察力和治疗干预。为了克服这一局限，我们开发了两部小说 技术：功能性单核苷酸多态-下一代测序(fSNP-seq)和DNA 竞争下拉-质谱仪(DCP-MS)。FSNP-SEQ是一种高通量的识别方法 在实验上，哪些SNPs可能与调节蛋白结合，因此很可能是fSNPs。DCP-MS使用 以fSNP序列作为诱饵，以半高通量的方式识别相关的调控蛋白。vbl.使用 这些技术在试点筛查中，我们已经在RA相关的CD40基因座上识别了三个fSNP，它们具有 已被EMSA和等位基因特异性荧光素酶报告试验证实。我们还确认了四个 通过这些fSNPs调节CD40表达的蛋白质。根据这些初步数据，我们建议 两个目标是将我们的新方法应用于Gwas关于RA的数据。首先，我们将使用fSNP-seq来筛选1218 最近的一项研究揭示了101个RA危险基因上的FSNPs的SNP。然而，由于高水平的努力， 在这一过程中，我们将把fSNPs的识别和表征限制在只有7个RA风险 CD40/NF-kB信号转导通路中涉及的基因位点。其次，我们将使用DCP-MS来筛选RA风险基因 调节CD40/NF-kB通路中这七个RA风险基因座中有效的fSNPs。这种方法论 可能导致建立一个可持续的、长期的研究计划，将这一战略应用于整个RA基因座。 长期目标将是在以下背景下确定开发个性化药物的最佳药物靶点 整个类风湿性关节炎相关风险基因调控网络。

ABSTRACT There is limited pathogenic understanding and no cure for autoimmune diseases such as rheumatoid arthritis (RA). Genome wide association studies (GWAS) have identified ~200 RA-associated loci. These loci represent ~4573 genetic variants, which in most cases is a single nucleotide polymorphism (SNP) in linkage disequilibrium (LD). In theory, there is only one functional SNP (fSNP) in each LD that is responsible for the pathogenesis of RA. However, GWAS don't reveal which one is the fSNP in each LD. This technical drawback leaves a gap between GWAS and a specific mechanism that would provide into opportunities for biological insight and therapeutic intervention. To overcome this limitation, we have developed two novel techniques: functional Single Nucleotide Polymorphism-next generation sequencing (fSNP-seq) and DNA competition pulldown-mass spectrometry (DCP-MS). fSNP-seq is a high throughput method to identify experimentally which SNPs are likely to bind regulatory proteins and thus to likely be fSNPs. DCP-MS uses an fSNP sequence as “bait” to identify associated regulatory proteins in a semi-high throughput way. Using these techniques in a pilot screen, we have identified three fSNPs on a RA-associated CD40 locus that have been confirmed by EMSA and an allele-specific luciferase reporter assay. We have also identified four proteins that regulate CD40 expression via these fSNPs. On the basis of these preliminary data, we propose two aims to apply our new methods to the GWAS data on RA. First, we will use fSNP-seq to screen 1218 SNPs for fSNPs on 101 RA risk loci revealed by a recent study. However, due to the high level of effort involved in this process, we will limit the identification and characterization of fSNPs to only seven RA risk loci involved in the CD40/NF-kB pathway. Second, we will employ DCP-MS to screen for the RA risk gene regulators on the validated fSNPs in these seven RA risk loci in the CD40/NF-kB pathway. This methodology could lead to building a sustainable, long-term research program t o apply this strategy to the entire RA loci. The long-term goal would be to identify the best drug targets for developing personalized drugs in a context of the entire RA-associated risk gene regulation network.