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

类风湿性关节炎抗 TNF 治疗反应的遗传预测因素

• 批准号: 8293200
• 负责人: ROBERT M PLENGE
• 金额: $ 159.6万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2015-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8293200
• 关键词: Alleles; Anti-Tumor Necrosis Factor Therapy; Antirheumatic Agents; Biological; Biological Markers; Cells; Clinical; Collaborations; Computerized Medical Record; DNA; Data; Disease; Disease remission; Disease-Modifying Second-Line Drugs; Genetic; Goals; Healthcare; Human; Immune; Individual; Inflammation; Inflammatory; Informatics; Methods; Onset of illness; Outcome; Patient Care; Patients; Pharmaceutical Preparations; Principal Investigator; Rheumatoid Arthritis; Sampling; Single Nucleotide Polymorphism; Statistical Methods; TNF gene; Testing; Tumor Necrosis Factor-alpha; Variant; base; bone; cytokine; genetic variant; genome wide association study; human TNF protein; improved; novel; public health relevance; response; theories; treatment response

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.

描述（由申请人提供）： 类风湿性关节炎（RA）患者的长期结局高度依赖于病程早期对炎症的积极药物控制。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反应。遗传生物标志物对于阻断炎性细胞因子TNF-α（TNF）的药物特别有用，因为这些药物是一线生物疾病缓解抗风湿药物DMARD，但仅在约30%的患者中诱导缓解。在本申请中，我们的中心假设是，中等效应大小的常见遗传变异预测对抗TNF治疗的反应。为了验证这一假设，我们建议扩展我们建立的多中心合作和可用的GWAS数据，以开发（i）进行GWAS的新统计方法（估计由常见的单核苷酸多态性（SNP）解释的方差），（ii）用于定义EMR中治疗反应的新信息学方法（这将使我们能够收集更多的样本GWAS），和（iii）一个新的框架，直接在人类免疫细胞中测试机制。目的1：分析约1,200例RA患者的GWAS数据，以寻找预测抗TNF治疗反应的常见变异。目标二：在Partners HealthCare、范德比尔特和西北大学使用电子病历（EMR）来定义治疗反应，并对另外约1,200名接受抗TNF治疗的RA患者进行GWAS。目的3：测试预测人类免疫细胞对抗TNF治疗的治疗应答的等位基因的作用机制。 公共卫生关系：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这种常见和衰弱疾病患者的护理。从理论上讲，识别预测治疗反应的特定DNA片段（“等位基因”）应该有助于在骨破坏发生之前，在疾病过程的早期将治疗靶向正确的个体。