Next-Generation Medical Resequencing of Gout Disease Genes in the ARIC Cohort

ARIC 队列中痛风疾病基因的下一代医学重测序

• 批准号: 7945359
• 负责人: JAMES E. HIXSON
• 金额: $ 144.89万
• 依托单位: UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2012-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7945359
• 关键词: Accounting; Adult; Affect; African American; Age; Aging; Alleles; Amino Acids; Architecture; Arthritis; Atherosclerosis; Bioinformatics; Candidate Disease Gene; Cardiovascular system; Caucasians; Caucasoid Race; Clinical; Communities; Complex; DNA Resequencing; DNA Sequence; Data; Deposition; Disease; Disease Progression; Drug Delivery Systems; Educational workshop; Elements; Epidemiology; Etiology; Exons; Framingham Heart Study; Gene Expression; Gene Frequency; Gene Targeting; Genes; Genetic; Genomics; Genotype; Gout; Health; Heart; Human; Human Genome; Individual; Intercistronic Region; Investigation; Joints; Laboratories; Lead; Learning; Measures; Medical; Medical Technology; Messenger RNA; Molecular; Nonsense Codon; Outpatients; Pain; Phenotype; Prevention; Process; Promoter Regions; Quality Control; RNA Splicing; Research; Research Personnel; Resources; Risk; Risk Factors; Serum; Solid; Susceptibility Gene; System; Technology; Testing; Tissues; United States National Institutes of Health; Urate; Uric Acid; Variant; Visit; case control; cohort; cost; data management; database of Genotypes and Phenotypes; design; follow-up; genetic variant; genome sequencing; genome wide association study; improved; interest; multidisciplinary; next generation; novel; programs; protein structure; public health relevance; success; tool; trait

DESCRIPTION (provided by applicant): This proposal responds to the GO Program "ARRA Medical Sequencing Discovery Projects" to establish next-generation technologies for medical resequencing in smaller academic laboratories compared to larger facilities like the Genomic Sequencing Centers. In this application, we propose to use next-generation sequencing for medical resequencing of genes that have shown highly significant associations with gout and serum uric acid levels in genome-wide association studies (GWAS) in the "Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)". Resequencing will characterize the overall "genetic architecture" by identification of both common functional variants that underlie GWAS statistical associations, as well as rare variants with larger phenotypic effects. Our laboratories have established key elements of next-generation sequencing including a robust and cost-effective process for subgenomic capture to enrich gene targets for resequencing, as well as implementation of the SOLID System v.3 (Applied Biosystems) and associated pipelines for data management and quality control. We have selected 11 genes from CHARGE GWAS results for resequencing of functional regions (promoters, exons, conserved regions) in gout cases and controls (total n=1,199) from the "Atherosclerosis Risk in Communities (ARIC)" cohort. After resequencing, we will genotype variants in the entire ARIC cohort (n=16,000) to verify resequencing results, and to increase power for statistical analysis. Statistical analyses will include standard association studies for relatively common alleles, as well as analyses of rare variants by tests for differences in numbers of rare variant carriers in cases versus controls, and comparisons of mean uric acid concentrations in carriers versus the overall cohort. For both common and rare variants that show significant associations, we will use bioinformatics to identify possible functional consequences like non-conservative amino acid replacements and premature stop codons, disruption of normal mRNA splicing, or alterations in control elements that regulate gene expression. We propose to replicate our findings by genotyping and statistical analysis in two additional CHARGE cohorts including the "Framingham Health Study (FHS)" and the "Cardiovascular Health Study (CHS)". PUBLIC HEALTH RELEVANCE: We propose to use next-generation DNA sequencing technologies to identify genetic variants that influence gout, one of the most common forms of arthritis affecting nearly 3 million adults in the US. Our subjects are from the "Atherosclerosis Risk in Community (ARIC)" study, a large multi-ethnic epidemiological cohort (16,000 subjects) that has been measured for multiple disease-related risk factors and clinical endpoints. The identification of genetic variants will provide an improved understanding of molecular mechanisms that regulate serum levels of uric acid (the major risk factor for gout), and eventually lead to novel drug targets to improve treatment of gout.

描述（由申请人提供）：该提案对GO计划“ ARRA医学测序发现项目”做出响应，以建立与基因组测序中心（例如基因组测序中心）相比，在较小的学术实验室进行医学重新设备的下一代技术。在此应用中，我们建议在“基因组流行病学（CHALL）中心的心脏和衰老研究中，在基因组范围的关联研究（GWAS）中，在基因组范围的关联研究（GWAS）中使用痛风和血清尿酸水平非常重要的基因进行医学重新配置”。重新取证将通过鉴定GWAS统计关联的基础的常见功能变体以及具有较大表型效应的稀有变体来表征整体“遗传结构”。我们的实验室已经建立了下一代测序的关键要素，包括稳健且具有成本效益的子基因组捕获过程，以丰富基因靶标，以重新取代基因，并实施实心系统v.3（应用生物系统）和相关的数据管理和质量控制的相关管道。我们从电荷GWAS结果中选择了11个基因，用于在痛风病例和对照组（总n = 1,199）的功能区域（启动子，外显子，保守区域）的重新取证，从社区（ARIC）的“动脉粥样硬化风险”中。重新陈述后，我们将在整个ARIC队列中的基因型变体（n = 16,000）中验证重新陈述结果，并增加统计分析的功率。统计分析将包括针对相对常见的等位基因的标准关联研究，以及通过测试稀有变体的稀有变体分析，用于病例与对照组中稀有变体载体数量的差异，以及载体中平均尿酸浓度的比较与整体同胞的比较。对于表现出显着关联的常见变体和稀有变体，我们将使用生物信息学来识别可能的功能后果，例如非保守氨基酸替代品和过早的停止密码子，正常mRNA剪接的破坏或调节基因表达的控制元件的改变。我们建议通过基因分型和统计分析在包括“ Framingham Health研究（FHS）”和“心血管健康研究（CHS）”（CHS）中复制我们的发现。 公共卫生相关性：我们建议使用下一代DNA测序技术来识别影响痛风的遗传变异，这是影响美国近300万成年人的最常见的关节炎形式之一。我们的受试者来自“社区动脉粥样硬化风险（ARIC）”研究，这是一项大型多民族流行病学队列（16,000名受试者），已针对多种与疾病相关的危险因素和临床终点进行了衡量。遗传变异体的鉴定将提供对调节血清尿酸水平（痛风的主要危险因素）的分子机制的改进理解，并最终导致了新的药物靶标以改善痛风的治疗方法。