Utility of Genomic Diagnostics for Chronic Kidney Disease

基因组诊断在慢性肾脏病中的应用

• 批准号: 9767132
• 负责人: Emily Eve Groopman
• 金额: $ 3.83万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2021-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9767132
• 关键词: Academic Medical Centers; Advocate; Affect; American; Candidate Disease Gene; Caring; Categories; Child; Childhood; Chronic; Chronic Kidney Failure; Clinical; Complex; Copy Number Polymorphism; Data; Data Discovery; Detection; Diagnosis; Diagnostic; Disease; Disease model; End stage renal failure; Ethnic Origin; Etiology; Family; Follow-Up Studies; Gene Dosage; Genes; Genetic; Genetic Diseases; Genetic Models; Genomic approach; Genomics; Individual; Inherited; Investigation; Kidney; Kidney Diseases; Link; Medicare; Microarray Analysis; Modality; Molecular; Morbidity - disease rate; Nephrology; Patients; Phenotype; Physicians; Recording of previous events; Reporting; Research; Resources; Single Nucleotide Polymorphism; Subgroup; Technology; Testing; Variant; base; causal variant; clinical Diagnosis; clinical diagnostics; clinical subtypes; cohort; cost; exome; exome sequencing; follow-up; genetic disorder diagnosis; human disease; insight; kidney biopsy; kidney malformation; mortality; novel; targeted treatment; tool

PROJECT SUMMARY Over 20 million Americans suffer from chronic kidney disease (CKD)1,2, resulting in a 10-15-fold increase in morbidity and mortality and over $58 billion in Medicare spending.3 As early-stage CKD is often clinically silent, individuals can go undiagnosed until they reach end-stage renal disease (ESRD)1, and in more 1 in 10 ESRD cases, the cause is said to be “unknown”3. Available data suggest that, for many patients, CKD has a genetic component, with 10-29% of patients reporting a positive family history across ethnicities and clinical etiologies.4-6 Yet, hereditary and non-hereditary forms are frequently indistinguishable using the prevailing diagnostics of clinical history and renal biopsy. Thus, in many cases the precise etiology remains unidentified, hindering physicians from providing patients with a specific diagnosis and targeted treatment. Genomic technologies such as microarray and whole-exome sequencing (WES) have been used to unravel the molecular basis of many disorders, and have begun to be applied successfully at the bedside as well as at the bench. In studies of pediatric CKD cohorts, we and others have incorporated these technologies to detect diagnostic copy number variants (CNVs) and single-nucleotide variants (SNVs) and find novel causal genes. However, the broader utility of genomic diagnostics for CKD, across demographic and clinical subgroups, has yet to be assessed. Furthermore, the capacity of this integrated genomic approach to enable genetic discovery as well as diagnosis requires additional study. The proposed project aims to evaluate the diagnostic yield of microarray and WES in a large, diverse CKD cohort, and identify novel candidate genes for CKD through integrated analysis of CNVs and SNVs. My preliminary data demonstrate that these genetic diagnostics can identify causal variants in a substantial proportion of patients, supporting their value in nephrology. I hypothesize that rare genic CNVs and SNVs contribute to a substantial proportion of CKD, such that integrated analysis, using both microarray and WES data, will enable detection of both diagnostic variants and novel candidate genes. To test this hypothesis, I propose the following Aims. In Aim 1, I will assess the diagnostic yield of microarray and WES in a large, diverse CKD cohort. Assessing diagnostic yield overall and comparing yield between demographic and clinical subtypes will give insight into which groups of CKD patients may benefit most from these genomic diagnostics. In Aim 2, I will evaluate gene-level burden of rare functional SNVs and gene-disrupting CNVs in order to identify novel candidate genes for CKD. I will also conduct gene set-based burden tests to explore more complex genetic models of disease and to pinpoint additional candidate genes. These studies will help ascertain the diagnostic utility of microarray and WES for CKD and identify candidate causal loci for all-cause CKD and specific subtypes, informing use of genomic diagnostics in clinical nephrology and providing candidate genes for further study.

项目摘要 超过2000万美国人患有慢性肾脏疾病（CKD）1,2，导致10-15倍 发病率和死亡率的提高以及超过580亿美元的医疗保险支出。3作为早期CKD，通常是 从临床上讲，个人可以无诊断直到达到末期肾脏疾病（ESRD）1，而更多 1个ESRD案件中有1个，据说原因是“未知” 3。可用数据表明，对于许多患者，CKD 具有遗传成分，有10-29％的患者报告跨种族的积极家族病史， 临床病因4-6然而，遗传性和非遗传形式经常使用 临床病史和肾脏活检的主要诊断。在许多情况下，精确的病因仍然存在 身份不明的，阻碍医生为患者提供特定的诊断和靶向治疗。 基因组技术，例如微阵列和全外象征测序（WES）已用于 解散许多疾病的分子基础，并已开始在床边成功应用 以及在长凳上。在小儿CKD队列的研究中，我们和其他人都合并了这些技术 检测诊断拷贝数变体（CNV）和单核苷酸变体（SNV）并找到新的因果关系 基因。但是，在人口统计和临床上，基因组诊断对CKD的更广泛效用 亚组，尚未评估。此外，这种综合基因组方法的能力启用 遗传发现和诊断需要额外的研究。拟议的项目旨在评估 微阵列和WES的诊断产量，在大型的潜水CKD队列中，并确定新颖的候选基因 CKD通过CNV和SNV的集成分析。我的初步数据表明这些遗传 诊断可以在很大一部分患者中识别因果变异，从而支持其价值 肾脏科。 我假设罕见的基因CNV和SNV有助于CKD的很大一部分， 因此，使用微阵列和WES数据都可以检测到综合分析 诊断变体和新型候选基因。为了检验这一假设，我提出了以下目的。在 AIM 1，我将评估大型潜水CKD队列中微阵列和WES的诊断产量。评估 总体诊断产量和人口统计学和临床​​亚型之间的产量将使您深入了解 哪些CKD患者可能会受益于这些基因组诊断。在AIM 2中，我将评估 为了鉴定新型候选基因，稀有功能SNV的基因级Burnen和Distrupt的CNV 对于CKD。我还将进行基于基因集的燃烧测试，以探索更复杂的疾病遗传模型 并查明其他候选基因。这些研究将有助于确定微阵列的诊断效用 和CKD的WES，并确定全因CKD和特定子类型的候选因果区域，以告知使用 临床肾脏病的基因组诊断和提供候选基因以进行进一步研究。