Genetic Prediction for Treatment Resistance in Kawasaki Disease

项目总结/摘要 川崎病（KD）是儿童心血管疾病发病的主要原因。对IVIG反应差 仍然是KD冠状动脉风险的关键决定因素之一。无法预测这种反应 并且发展为持续性冠状动脉瘤的可能性是 强化治疗的进展和发展。目前可用的数据表明，KD易感性和 治疗反应以及冠状动脉疾病的倾向取决于个体患者的 遗传背景旨在鉴定适当遗传生物标志物的研究受到以下因素的影响：1） 表型分型缺乏严谨性，2）使用基因组广泛关联研究，通常采用芯片或阵列， 检测到常见变异，而不是低频率或罕见变异，3）机制不明确 IVIG在KD中抗炎作用的研究（指导大多数药物基因组学研究所必需的）4）关注基因 候选人，这是不切实际的临床测试，和5）模糊的种族分配方法 混淆药物基因组学。此外，外显子组测序和分析可能会错过潜在的 作为IVIG抗炎机制的重要变体包括基因间的转录调控， 地区我们假设，通过使用改进的和严格的表型分析技术， 全基因组测序（WGS）和分析，我们将能够确定选择的生物标志物， 预测KD治疗反应和冠状动脉瘤的发展。太平洋西北 川崎疾病数据-生物库，主要通过PI Portman，R21 HL 090558的资助建立， Thrasher研究基金会;和PI，Shrestha，东南AHA积累了DNA和临床 来自800多名KD患者的数据，符合药物基因组学分析的条件。我们将利用这些财富， DNA和临床数据沿着最近更新的AHA临床KD标准，以确定罕见和 常见变异，决定IVIG治疗反应。WGS还将允许a）识别 个体私有SNP（罕见变体），B）群体特异性私有SNP的鉴定，c）构建 包括结构变异（CNV和插入/缺失）在内的遗传变异的全貌，d）基因- 基于常见和罕见变体的分析，以及e）鉴定实际的功能性SNP， 连锁不平衡（LD）中常见的估算或SNP。此外，我们将考虑种族， KD的重要变异，通过使用祖先信息标记和主要 成分分析我们将使用严格的方法来实现以下具体目标1）执行 全基因组测序，以确定遗传变异，这可以作为IVIG的临床生物标志物 KD患者中的耐药。2)确定与巨大冠状动脉相关的新基因组变异 动脉瘤（GCA）的儿童与KD。3)准备评估非洲人的IVIG耐药性是否更高 如果这种反应取决于基于种族的遗传变异频率差异。

PROJECT SUMMARY/ABSTRACT Kawasaki Disease (KD) is a major contributor to cardiovascular morbidity in children. Poor response to IVIG remains one of the critical determinants of coronary artery risk in KD. The inability to predict this response and the potential for developing persistent coronary artery aneurysms serves as a major impediment to progress and development of intensified therapy. Currently available data indicate that KD susceptibility and treatment response, as well as the propensity for coronary artery disease, depend on an individual patient's genetic background. Studies directed at identifying appropriate genetic biomarkers have been impaired by: 1) phenotyping lacking rigor, 2) use of genome wide association studies often employing chips or arrays for detection of common variants rather than low frequency or rare variants, 3) lack of clarity for the mechanisms of IVIG anti-inflammation in KD (necessary for guiding most pharmacogenomics studies) 4) focus on gene candidates, which are impractical for clinical testing, and 5) vague racial assignment methodology confounding pharmacogenomics. Furthermore, exome sequencing and analyses likely would miss potential important variants as IVIG anti-inflammatory mechanism includes transcriptional regulation at intergenic regions. We hypothesize that, by using improved and rigorous phenotyping techniques in combination with whole genome sequencing (WGS) and analyses, we will be able to identify select biomarkers for accurate prediction of KD treatment response and development of coronary aneurysms. The Pacific Northwest Kawasaki Disease Data-Biobank, established mainly through funding via PI Portman, R21HL090558, Thrasher Research Foundation; and PI, Shrestha, Southeastern AHA has accumulated DNA and clinical data from over 800 KD patients, eligible for pharmacogenomics analyses. We will leverage this wealth of DNA and clinical data along with recently updated AHA clinical KD criteria in order to identify rare and common variants, which determine IVIG treatment response. WGS will also allow a) identification of individual private SNPs (rare variants), b) identification of population-specific private SNPs, c) building a complete picture of genetic variations including structural variants (CNVs and insertion/deletions), d) gene- based analysis of both common and rare variants, and e) identification of actual functional SNPs as opposed to common imputed or SNPs in linkage disequilibrium (LD). Additionally, we will account for race, an important variant in KD, by rigorous racial assignment using ancestry information markers and principal component analyses. We will use rigorous methodology to achieve the following specific aims 1) Perform whole genome sequencing to identify genetic variations, which could serve as clinical biomarkers for IVIG resistance in KD patients. 2) Determine novel genomic variants associated with giant coronary artery aneurysms (GCA) among children with KD. 3) Prepare to assess if IVIG resistance is greater among African Americans and if this response depends on racial based differences in the frequency of genetic variations.