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

摘要 对类风湿性关节炎等自身免疫性疾病的致病性认识有限， （RA）。全基因组关联研究（GWAS）已经确定了约200个RA相关基因座。这些基因座 代表~4573个遗传变异，在大多数情况下是连锁中的单核苷酸多态性（SNP 不平衡（LD）。理论上，在每个LD中只有一个功能性SNP（fSNP）负责基因的转录。 RA的发病机制。然而，GWAS没有揭示哪一个是每个LD中的fSNP。本技术 一个缺点在GWAS和一个特定的机制之间留下了差距， 生物学洞察力和治疗干预。为了克服这一限制，我们开发了两种新的 技术：功能性单核苷酸多态性-下一代测序（fSNP-seq）和DNA 竞争下拉质谱法（DCP-MS）。fSNP-seq是一种高通量的方法， 通过实验确定哪些SNP可能结合调节蛋白，因此可能是fSNP。DCP-MS用途 fSNP序列作为“诱饵”，以半高通量方式鉴定相关的调节蛋白。使用 这些技术在试点筛选中，我们已经确定了RA相关CD 40基因座上的三个fSNP， 通过EMSA和等位基因特异性荧光素酶报告基因测定证实。我们还发现了四个 通过这些fSNP调节CD 40表达的蛋白质。根据这些初步数据，我们建议 第二个目标是将我们的新方法应用于RA的GWAS数据。首先，我们将使用fSNP-seq筛选1218 最近的一项研究揭示了101个RA风险位点的fSNPs。然而，由于高度的努力， 在这一过程中，我们将限制fSNPs的识别和表征，只有七个RA风险 参与CD 40/NF-kB通路的基因座。其次，我们将采用DCP-MS筛查RA风险基因 在CD 40/NF-kB通路中的这七个RA风险基因座中，对经验证的fSNP进行调控。这种方法 可以导致建立一个可持续的，长期的研究计划，以应用这一战略的整个RA基因座。 长期目标将是确定最佳药物靶点，以开发个性化药物， 整个RA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.