Genetics of Gout

描述(由申请人提供)：痛风是一种常见且极度疼痛的炎症性关节炎，与高尿酸血症有关。新出现的证据表明，痛风可能会增加心肌梗死、糖尿病和过早死亡的风险。除了痛风的各种饮食和生活方式的危险因素外，痛风的实质性遗传易感性已经被认识到。有痛风家族史的人患痛风的风险增加九倍，据报道，痛风患者中有高达80%的阳性家族史。血清尿酸水平是痛风的前兆，也显示出很高的遗传度(0.63)。然而，导致这种强烈易感性的遗传因素仍不清楚。该项目将通过研究痛风和血清尿酸与特定遗传因素和基因-环境相互作用之间的关系，进一步扩展我们之前的工作(研究痛风的环境风险因素)。我们将利用三项大型队列研究中收集的数据：护士健康研究(NHS)I(n=121,000名女性)、护士健康研究II(n=116,000名女性)和卫生专业人员后续研究(HPFS)(n=51,000名男性)。我们将进行一项分两个阶段的全基因组关联(GWA)研究，以确定影响痛风风险的基因。在第一阶段，我们将进行GWA研究，检查1,200名痛风患者和1,200名匹配对照中的550,000个SNP。我们将以10-7的全基因组显着水平发布这些结果，并选择前1%的人进行后续的基因分型。在第二阶段，我们将使用25k定制芯片对这些前1%的基因(以及其他候选基因和验证标记)进行分型，从我们的队列中获得1200例痛风病例和1200例对照的独立样本。我们将执行两个阶段的联合分析，在不牺牲功率的情况下实现效率。接下来，我们将检查联合分析中排名前50位的SNP与所有4800名参与者中的关键环境风险因素(富含嘌呤的食物、酒精和肥胖)之间的基因-环境交互作用。我们还将确定与高尿酸血症相关的基因作为次要结果。在拟议的四年研究期内，我们将继续根据美国风湿病学会的痛风标准确认痛风事件。当前建议的意义和优点包括：1)研究主题的重要性(即常见、疼痛、风湿[痛风]的关键风险因素)，2)全面的调查方法，3)我们在痛风研究方面的丰富持续经验，4)理想的遗传流行病学研究环境(即钱宁实验室和哈佛大学公共卫生学院)，5)经过充分验证的、预期收集的饮食和其他环境暴露数据，6)大样本，为拟议的估计提供高精度和力量，7)预期事件结果分析，8)使用可靠、有效的数据进行经济高效的研究设计。这项研究将填补我们在痛风遗传风险因素方面的主要知识空白，这可能会导致新的治疗方法。与公共卫生相关：痛风是一种常见且极度疼痛的炎症性关节炎，与尿酸水平升高有关。几个世纪以来，痛风的遗传易感性已经被认识到，但其中涉及的机制仍不清楚。这个项目将使我们能够研究痛风与特定遗传因素的关系，从而建立和扩展我们以前的努力(检查痛风发病的环境风险因素)。我们将利用在四项大型队列研究中收集的前瞻性数据和DNA样本：护士健康研究(NHS)I(n=121,000名女性)、护士健康研究II(n=116,000名女性)和卫生专业人员后续研究(HPFS)(n=51,000名男性)。

DESCRIPTION (provided by applicant): Gout is a common and excruciatingly painful inflammatory arthritis associated with hyperuricemia. Emerging evidence suggests that gout may increase the risk of myocardial infarction, diabetes, and premature death. In addition to various dietary and life-style risk factors for gout, substantial genetic predisposition of gout has been recognized. A family history of gout increases an individual's risk of developing gout nine-fold and a positive family history has been reported as high as 80% among gout patients. Serum uric acid levels, the precursor of gout, also show a high degree of heritability (0.63). However, the genetic factors responsible for this strong predisposition remain unknown. This project will build on and extend our previous efforts (examining environmental risk factors for gout) by allowing us to study the relation of gout and serum uric acid to specific genetic factors and gene-environment interactions. We will take advantage of data collected in three large cohort studies: Nurses' Health Study (NHS) I (n=121,000 women), Nurses' Health Study II (n=116,000 women), and Health Professionals Follow-up Study (HPFS) (n=51,000 men). We will perform a two-stage genome-wide association (GWA) study to identify genes that affect the risk of gout. In Stage 1, we will perform a GWA study examining 550,000 SNPs in 1,200 participants with gout and 1,200 matched controls. We will release these results with a genome-wide significance level of 10-7 and select the top 1% for subsequent genotyping. In Stage 2, we will genotype these top 1% genes (and other candidate genes and validation markers) using 25k custom chips in an independent sample of 1,200 gout cases and 1,200 controls from our cohorts. We will perform a two-stage joint analysis, which achieves efficiency without sacrificing power. Next, we will exam gene- environment interactions between the top 50 SNPs from the joint analysis and key environmental risk factors (purine-rich food, alcohol, and adiposity) in all 4,800 participants. We will also identify genes associated with hyperuricemia as a secondary outcome. During the proposed 4-year study period, we will continue to confirm incident cases of gout according to the American College of Rheumatology gout criteria. The significance and strengths of the current proposal include: 1) importance of the study topic (i.e. a key risk factor [genes] for a common, painful, rheumatic condition [gout]), 2) comprehensive investigative approach, 3) our extensive ongoing experience in gout research, 4) an ideal environment for a genetic epidemiology study (i.e. Channing laboratory and Harvard School of Public Health), 5) well-validated, prospectively collected dietary and other environmental exposure data, 6) large sample size providing high precision and power for the proposed estimates, 7) prospective incident outcome analysis, and 8) cost- efficient study design using well-established, validated data. This study will fill the major gaps in our knowledge on the genetic risk factors for gout, which may lead to new approaches to treatment. Public Health Relevance: Gout is a common and excruciatingly painful inflammatory arthritis associated with elevated uric acid levels. A strong genetic predisposition to gout has been recognized for centuries, but the mechanisms involved remain unknown. This project will build on and extend our previous efforts (examining environmental risk factors for developing gout) by allowing us to study the relation of gout to specific genetic factors. We will take advantage of prospective data and DNA samples collected in four large cohort studies: Nurses' Health Study (NHS) I (n=121,000 women), Nurses' Health Study II (n=116,000 women), and Health Professionals Follow-up Study (HPFS) (n=51,000 men).