Integrating large scale genomics and functional studies to accelerate FSGS/NS discovery

本项目的四位主要研究者已经收集了约10，000例局灶性和 节段性肾小球硬化（FSGS）和类固醇耐药肾病综合征（SRNS）。有了这个最大的 FSGS/NS队列中，绝大多数已经进行了全基因组测序， 我们建议共同努力，以了解这种疾病的遗传基础。的数量越来越多 鉴定出的基因在改变时可能导致FSGS/SRNS，表明这些表型在遗传上高度相关 复杂.了解FSGS和NS的遗传基础是重要的：（1）迄今为止的工作主要是 了解肾小球分子结构的驱动因素;（2）基因诊断影响治疗：一些 突变预测对类固醇治疗缺乏反应，其他预测对营养补充剂的反应; (3)遗传因素影响肾移植计划和结果。主要差距仍然存在：（1）大多数FSGS/NS病例仍然 （2）疾病的基础是复杂的，涉及不同的贡献。 在等位基因频率和等位基因频率谱上的变异;（3）我们宣布遗传因果关系的能力， 单个患者水平有限;（4）治疗选择有限。因此，我们将使用这一大型队列， 新的分析方法来解决这些差距。我们将对许多新的等位基因进行功能表征， 新的FSGS基因。我们将开发和分发试剂，包括患者来源的iPS细胞。 我们将通过汇总患者的外显子组和基因组测序数据来创建一个数据库， 这些数据可通过网络浏览器获得，以协助研究界。我们计划：目标1：了解 一系列罕见的遗传变异，导致人类FSGS和NS（或增加其风险）。通过利用 大样本量，我们可以使用的方法，否则不够强大的疾病基因 识别.我们将发现与FSGS/NS相关的新基因，以确定高度渗透的变体 （包括罕见序列变化和拷贝数变异的负荷测试），定义SNV的谱， 已知FSGS/NS基因的结构变异，并鉴定与疾病相关的肾小球基因共表达。 基因.目的2：定义疾病相关变异的功能效应。我们将测试 通过突变FSGS/NS基因开发新的斑马鱼模型，以及 从具有FSGS/NS相关突变的患者中产生一组iPS细胞。目标3：我们将携手 我们所有的基因分型数据，从SNP阵列，WES和WGS产生，以建立和维护一个公开的 可用的变体浏览器，“肾病综合征基因组门户网站”（NSGP）。NSGP将包括等位基因 FSGS/NS的频率数据、功能分类和临床相关性。我们将总结，在一个网站- 水平，SNV，插入缺失，结构变异（CNV），并提供质量 报告的变体度量。NSGP还将有能力接受和合并来自其他国家的数据。 研究人员和临床遗传学实验室。

SUMMARY The four lead investigators of this project have assembled ~10,000 patients with focal and segmental glomerulosclerosis (FSGS) and steroid-resistant nephrotic syndrome (SRNS). With this largest ever FSGS/NS cohort assembled, the vast majority whom have already undergone genome-wide sequencing, we propose a collaborative effort to understand the genetic basis of this disease. The increasing number of identified genes that can cause FSGS/SRNS when altered shows that these phenotypes are genetically highly complex. Understanding the genetic basis of FSGS and NS is important: (1) Work to date has been the major driver in understanding the molecular structure of the glomerulus; (2) Genetic diagnosis affects therapy: some mutations predict lack of response to steroid therapies, others predict response to nutritional supplementation; (3) Genetics affects renal transplant planning and outcome. Major gaps remain: (1) Most FSGS/NS cases still are genetically unresolved; (2) The basis of disease is complex and involves the contribution of different variants across the spectrum of allelic frequency and penetrance; (3) Our ability to declare genetic causality at the single-patient level is limited; (4) Therapeutic options are limited. Thus, we will use this large cohort and new analytic methods to address these gaps. We will functionally characterize many of the new alleles and new FSGS genes that we discover. We will develop and distribute reagents, including patient-derived iPS cells. We will create a database by aggregating exome and genome sequencing data from our patients, and make this data available via web browser to assist the research community. We plan to: Aim 1: Understand the spectrum of rare genetic variation that causes (or increases risk of) FSGS and NS in humans. By leveraging large sample sizes, we can use approaches that are not otherwise powerful enough for disease gene identification. We will discover novel genes associated with FSGS/NS to identify highly penetrant variants (including burden tests of rare sequence changes and copy-number variants), define the spectrum of SNV and structural variants in known FSGS/NS genes, and identify glomerular genes co-expressed with disease-related genes. Aim 2: Define functional effects of disease-associated variants. We will test effects of variants/mutations in cell-based assays, develop new zebrafish models by mutating FSGS/NS genes, and generate a panel of iPS cells from patients with FSGS/NS-associated mutations. Aim 3: We will bring together all of our genotyping data, generated from SNP arrays, WES, and WGS, to build and maintain a publicly available variant browser, the “Nephrotic Syndrome Genomic Portal” (NSGP). NSGP will include allele frequency data, functional classification, and clinical correlates for FSGS/NS. We will summarize, at a site- level, SNVs, insertion-deletions, structural variants (CNV) observed in our FSGS/NS cohort and provide quality metrics of variants reported. NSGP will also have the capability to accept and incorporate data from other investigators and clinical genetics laboratories.