Identifying genetic modifiers of severity in ADPKD

识别 ADPKD 严重程度的遗传修饰因子

• 批准号: 7885072
• 负责人: Peter C. Harris
• 金额: $ 99.36万
• 依托单位: MAYO CLINIC ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7885072
• 关键词: Autosomal Dominant Polycystic Kidney; Biological Assay; Caucasians; Caucasoid Race; Clinical; Computer Retrieval of Information on Scientific Projects Database; Cystic Kidney Diseases; Data; Data Analyses; Development; Disease; Family; Funding; Future; Genes; Genetic; Genomics; Genotype; Hereditary Disease; Human Genome; Image; Impaired Renal Function; Kidney; Kidney Diseases; Magnetic Resonance Imaging; Maps; Measurement; Measures; Methodology; Methods; National Institute of Diabetes and Digestive and Kidney Diseases; Natural History; Pathogenesis; Patients; Phenotype; Population; Population Analysis; Quantitative Trait Loci; Recruitment Activity; Renal function; Resolution; Severities; Severity of illness; Staging; Testing; Therapeutic; Therapeutic Intervention; base; cohort; density; design; disease phenotype; genetic variant; genome wide association study; indexing; prognostic; public health relevance

DESCRIPTION (provided by applicant): The phenotype associated with the Mendelian disease autosomal dominant polycystic kidney disease (ADPKD) is highly variable. Of paramount importance clinically is the severity of the renal cystic disease. Previous studies have shown that genic (PKD1 or PKD2) and (to a less extent) allelic factors influence the phenotype, but one of the most important modulating factors is genetic background. Identifying quantitative trait loci (QTL) that significantly influence the severity of disease would help understand pathogenesis, be of prognostic importance and may guide therapeutics. The development of high-density SNP arrays provides a means to map these QTL in large, clinically and genetically well-characterized populations, employing a genome-wide association study (GWAS). The NIDDK-funded CRISP and HALT PKD studies have a combined cohort of >1,000 ADPKD patients who are highly characterized clinically and genetically; >700 have renal MR imaging data. MR calculated total kidney volume (TKV) has been shown to be a good measure of disease severity, informative before a decline in GFR is detectable. Additionally, well characterized PKD1 populations are available at UCHSC, Emory, Mayo, KUMC, Toronto, Cambridge and Oxford to aid the discovery, replication and verification steps that are required to differentiate genuine QTL from false positive associations. Here, we propose a GWAS employing the Illumina Human660w-quad Genotyping BeadChip (658,000 SNPs), in 1600 PKD1 Caucasians (Aim 1). Total kidney volumes (TKV) data will be available in ~1100 of these patients and informative eGFR data in ~900 cases. The 7600 most likely associated SNPs detected with these endpoints will be further assayed using a customized array in a replicate population of 1600 PKD1 patients with the TKV and eGFR phenotypic endpoints, as above (Aim 2). A final verification step will analyze the 30 most promising loci in a population of 1216 patients with the same endpoints (Aim 3). The 30 loci will each be tested with ~12 SNPs (total of 348) to refine the QTL and highlight possible causative genes. To maximize the power of the study we will analyze the data as a combined population and family-based association study. In summary, this consortium of groups will perform the first GWAS in ADPKD to identify modifiers of disease severity. A three-stage design; discovery, replication and verification steps are to be employed to maximize the chance to identify QTL and minimize false positives. PUBLIC HEALTH RELEVANCE: This project proposes to identify genetic variants in the human genome that influence the severity of the kidney disease in the genetic disease autosomal dominant polycystic kidney disease (ADPKD). The study will use new array-based genomic mapping methods and analyze a number of large ADPKD populations from US and around the world that have been clinical and genetically characterized in detail. Positive results will be of prognostic importance and identify targets for therapeutic intervention.

描述（由申请人提供）： 与孟德尔病常染色体显性多囊性肾脏疾病（ADPKD）相关的表型高度可变。在临床上至关重要的是肾囊性疾病的严重程度。先前的研究表明，基因（PKD1或PKD2）和（在较小程度上）等位基因因素会影响表型，但最重要的调节因素之一是遗传背景。确定显着影响疾病严重程度的定量性状基因座（QTL）将有助于理解发病机理，并具有预后的重要性，并可能指导治疗疗法。高密度SNP阵列的发展提供了一种手段，该方法采用了全基因组关联研究（GWAS），以大型，临床和遗传性良好的人群绘制这些QTL。 NIDDK资助的Crisp和Halt PKD研究的组合组合> 1,000名ADPKD患者，这些患者在临床和遗传上具有高度的特征。 > 700具有肾脏MR成像数据。 MR计算的总肾脏体积（TKV）已被证明是疾病严重程度的良好量度，在可检测到GFR之前的信息量很大。此外，在UCHSC，Emory，Mayo，Kumc，Toronto，Toronto，Cambridge和Oxford上还可以提供良好的PKD1种群，以帮助发现，复制和验证步骤，这些步骤将真正的QTL与假阳性关联区分开。在这里，我们在1600 pkd1高加索人（AIM 1）中提出了使用Illumina Human660w-Quad Quad Quad基因分型Beadchip（658,000 SNP）的GWA。在这些患者中，将提供约1100例肾脏总量（TKV）数据，并在约900例中提供信息的EGFR数据。如上所述（AIM 2），最有可能使用这些终点检测到的7600个相关的SNP将在1600名具有TKV和EGFR表型终点的PKD1患者的重复群体中进一步测定（AIM 2）。最终验证步骤将分析1216名具有相同终点的患者人群中的30个最有希望的基因座（AIM 3）。每个30个基因座将用〜12个SNP（总计348）进行测试，以完善QTL并突出可能的病因基因。为了最大程度地提高研究的力量，我们将把数据分析为总人群和基于家庭的关联研究。总而言之，该组将在ADPKD中执行第一个GWAS，以识别疾病严重程度的修饰符。三阶段的设计；将采用发现，复制和验证步骤来最大程度地识别QTL并最大程度地减少误报。 公共卫生相关性：该项目建议在人类基因组中识别影响肾脏疾病严重性在遗传疾病常染色体显性多囊性肾脏疾病（ADPKD）中的遗传变异。该研究将使用新的基于阵列的基因组映射方法，并分析来自我们和世界各地的许多大量ADPKD种群，这些种群在临床上是临床和遗传表征的。积极的结果将具有预后的重要性，并确定治疗干预的靶标。