Genetic predictors of response to anti-TNF therapy in rheumatoid arthritis

描述(由申请人提供)： 类风湿性关节炎(RA)患者的长期预后高度依赖于在病程早期对炎症进行积极的药物控制。尽管在疾病发作后不久选择最佳药物很重要，但没有临床或生物标志物预测药物治疗的反应。遗传生物标记物对于阻断炎性细胞因子肿瘤坏死因子-α(TNF-α)的药物特别有用，因为这些药物是一线生物疾病修改抗风湿药物DMARDS，但仅在~30%的患者中诱导缓解。在这个应用中，我们的中心假设是，效应大小适中的常见遗传变异预测抗肿瘤坏死因子治疗的反应。为了验证这一假设，我们建议扩展我们已建立的多中心合作和现有的GWAS数据，以开发(I)进行GWAS(估计由常见单核苷酸多态解释的方差)的新统计方法，(Ii)定义EMR中治疗反应的新信息学方法(这将使我们能够为GWAS收集更多的样本)，以及(Iii)直接在人类免疫细胞中测试机制的新框架。目的1：分析约1,200例类风湿性关节炎患者的GWAS数据，寻找预测抗肿瘤坏死因子治疗反应的常见变量。目的2：使用Partners Healthcare、Vanderbilt和西北大学的电子病历(EMR)来定义治疗反应，并对另外约1,200名接受抗肿瘤坏死因子治疗的RA患者进行GWAS。目的3：检测预测抗肿瘤坏死因子治疗反应的等位基因在人免疫细胞中的作用机制。 公共卫生相关性：了解类风湿性关节炎(RA)患者的遗传基础治疗反应的长期目标是改善对这种常见且使人衰弱的疾病患者的护理。从理论上讲，识别预测治疗反应的特定DNA片段(“等位基因”)应该有助于在骨骼破坏发生之前，在疾病过程的早期针对正确的个人进行靶向治疗。

DESCRIPTION (provided by applicant): Long-term outcome in patients with rheumatoid arthritis (RA) is highly dependent upon aggressive pharmacological control of inflammation early in the disease course. Despite the importance of selecting the optimal medication soon after disease onset, there is no clinical or biomarker predictor of drug treatment response. A genetic biomarker would be particularly useful for drugs that block the inflammatory cytokine TNF-alpha (TNF), as these drugs are first-line biological disease modifying anti-rheumatic drugs DMARDs, yet induce remission in only ~30% of patients. In this application, our central hypothesis is that common genetic variants of modest effect size predict response to anti-TNF therapy. To test this hypothesis, we propose to expand upon our established multi-center collaboration and available GWAS data to develop (i) new statistical methods for conducting GWAS (estimating variance explained by common single nucleotide polymorphisms, SNPs), (ii) new informatics methods for defining treatment response in the EMR (which will allow us to collect many more samples for GWAS), and (iii) a novel framework for testing mechanism directly in human immune cells. Aim 1: Analyze GWAS data on ~1,200 RA patients to search for common variants that predict response to anti-TNF therapy. Aim 2: Use electronic medical records (EMR) at Partners HealthCare, Vanderbilt and Northwestern to define treatment response, and conduct a GWAS on ~1,200 additional RA patients treated with anti-TNF therapy. Aim 3: Test mechanism of action of alleles that predict treatment response to anti-TNF therapy in human immune cells. PUBLIC HEALTH RELEVANCE: A long-term goal of understanding the genetic basis treatment response in patients with rheumatoid arthritis (RA) is to improve care of patients with this common and debilitating disease. In theory, identifying specific pieces of DNA ("alleles") that predict treatment response should aid in targeting therapy to the right individuals early in the course of disease before bone destruction occurs.