ADPKD: Disease Spectrum & Genotype-Phenotype Correlations

常染色体显性多囊肾病（ADPKD）是一种常见的单等位基因疾病， 进行性囊肿发展并导致50%的患者在60岁时发生终末期肾衰竭（ESRD）。 然而，有相当大的表型变异性，从子宫内发病的患者， 肾功能不全老年常染色体显性遗传性多囊肝病（ADPLD），如传统定义， 导致PLD伴最小肾囊肿。传统上认为存在两种ADPKD基因，PKD 1和PKD 2。 PKD 2，编码PC 1和PC 2，以及两个ADPLD基因，PRKCSH和SEC 63，但在过去的几年中， 已经描述了更大的遗传异质性，现在总共涉及9个基因。最近的数据也 表明ADPKD和ADPLD相关的病因和发病机制存在重叠， PC复合物的生物发生和定位对这两种疾病都至关重要。在上一个融资周期，我们 发现了一种新的基因，GANAB，它与这两种疾病有关，其中编码的蛋白质，GII抑制剂， 参与PC 1的成熟和运输。 在这项提案中，我们将利用下一代测序（NGS）的进展， 方法，以及已收集的ADPKD和ADPLD患者的大量人群， 筛选经典基因，寻找这些疾病的新基因（目的1）。相关的表型 将沿着其作用机制（目的2）来表征（目的3）。NGS方法将 完善筛选片段重复基因座PKD 1，并确定在已知的缺失突变， 基因座，包括由于嵌合现象而仅存在于某些细胞中的基因座（Aim 1）。许多PKD的意义1 非截短变体难以评估（归类为意义不明的变体; VUS），但 最近的证据表明，有些是不完全外显等位基因，部分解释了PKD 1的表型变异 人口。在目标2中，改进的计算机预测与机器学习相结合，将提高 了解VUS的致病性和耐药性。生物发生和运输的细胞测定 还将采用该PC复合物的量来定量VUS的迁移率。发病机制 将在具有超低渗透（ULP）Pkd 1或Pkd 2等位基因的动物模型中进行探索。雇用大型 将定义临床、影像学和遗传学明确定义的患者群体表型分组 然后将其与基因组和PKD 1等位基因组进行比较（目的3）。这种迭代过程将允许 与每个PKD 1 VUS相关的变异评分（VS）有待完善。在一个单独的人群中， 单独使用以及与临床、功能和成像数据结合使用，将用于生成 ADPKD的综合预测算法（目标3）。通过双等位基因对严重疾病的疾病修饰 ADPKD，以及由于其他基因座的等位基因，也将在细胞测定和体内试验中鉴定和表征 结合Pkd 1亚纯RC模型。最终目标将利用新发现的 一些PKD 1和PKD 2 VUS是可挽救的折叠突变， 环境可以正常运行和运行。基于细胞表面PC 1水平的筛选方案 将得到改进，并将与 桑福德·伯纳姆·普瑞比斯第二个突变组，将探讨治疗是无稽之谈 突变。正在开发一种用于通读效率的细胞测定法，并将用于筛选。 将在可用的小鼠模型中检测鉴定的分子伴侣或通读药物。总的来说，这项建议将 更好地解释ADPKD/ADPLD表型变异的病因和遗传原因， 用于个体选择患者进行治疗的预后工具，现在已经可用，并探索 基于等位基因的ADPKD治疗。

Autosomal dominant polycystic kidney disease (ADPKD) is a common monoallelic disorder associated with progressive cyst development and resulting in end stage renal failure (ESRD) in 50% of patients by 60y. However, there is considerable phenotypic variability, extending from in utero onset to patients with adequate renal function into old age. Autosomal dominant polycystic liver disease (ADPLD), as traditionally defined, results in PLD with minimal renal cysts. Classically there have been considered two ADPKD genes, PKD1 and PKD2, encoding PC1 and PC2, and two ADPLD genes, PRKCSH and SEC63, but in the past few years greater genetic heterogeneity has been described, with nine genes now implicated overall. Recent data also indicates an overlap in etiology and pathogenesis associated with ADPKD and ADPLD, with the efficient biogenesis and localization of the PC-complex central to both disorders. During the last funding period we identified a novel gene, GANAB, which is associated with both disorders, where the encoded protein, GII is involved in the maturation and trafficking of PC1. In this proposal we will take advantage of advances in next generation sequencing (NGS) methodologies, and large populations of ADPKD and ADPLD patients that have been assembled and screened for the classic genes, to hunt for novel genes for these disorders (Aim 1). The phenotype associated with these genes will be characterized (Aim 3) along with their mechanism of action (Aim 2). NGS methods will be perfected to screen the segmentally duplicated locus, PKD1, and to identify missed mutations at the known loci, including those present in just some cells due to mosaicism (Aim 1). The significance of many PKD1 nontruncating variants has been difficult to evaluate (classed as variants of unknown significance; VUS), but recently evidence that some are incompletely penetrant alleles partially explains phenotypic variability in PKD1 populations. In Aim 2 improved in silico predictions, in combination with machine learning, will improve the understanding of the pathogenicity and penetrance of VUS. A cellular assay of the biogenesis and trafficking of this PC-complex will also be employed to quantify the penetrance of VUS. The mechanism of pathogenesis will be explored in animal models with ultralow penetrant (ULP) Pkd1 or Pkd2 alleles. Employing the large clinically, imaging, and genetically well-defined populations phenotypic groupings of patients will be defined that will then be compared to the genic and PKD1 allelic groups (Aim 3). This iterative process will allow the Variant Score (VS) associated with each PKD1 VUS to be refined. In a separate population the revised VS, alone and in combination with clinical, functional, and imaging data, will be employed to generate a comprehensive, predictive algorithm for ADPKD (Aim 3). Disease modifiers to severe disease, via biallelic ADPKD, and due to alleles at other loci will also be identified and characterized in the cellular assay and in vivo in combination with the Pkd1 hypomorphic, RC model. The final aim will exploit the newly identified information that some PKD1 and PKD2 VUS are rescuable, folding mutations that in a maturation-fostering environment can traffic and function appropriately. A screening scheme based on the level of cell surface PC1 will be improved and new chaperone drugs specific for the PC complex will be sought in collaboration with Sanford Burnham Prebys. A second mutation group that will be explored therapeutically are nonsense mutations. A cellular assay for readthrough efficiency is being developed and will be used for screening. Identified chaperone or readthrough drugs will be tested in available mouse models. Overall this proposal will better explain the etiology and the genetic causes of phenotypic variability in ADPKD/ADPLD, develop better prognostic tools for individual selection of patients for treatment that are now becoming available, and explore allele based treatments for ADPKD.