ADPKD: Disease Spectrum & Genotype-Phenotype Correlations

常染色体显性遗传性多囊肾病是一种常见的单等位基因疾病，与 到60岁时，50%的患者会逐渐发展成囊性病变并导致终末期肾功能衰竭(ESRD)。 然而，有相当大的表型变异，从宫内发病到足够的 肾功能进入老年。按照传统定义，常染色体显性遗传性多囊肝病(ADPLD) 结果：PLD伴有最小的肾囊肿。传统上认为有两个ADPKD基因，即PKD1和 PKD2，编码PC1和PC2，以及两个ADPLD基因，PRKCSH和SEC63，但在过去几年中 已经描述了更大的遗传异质性，目前总共涉及9个基因。最近的数据还 提示ADPKD和ADPLD的病因和发病机制存在重叠，有效 这两种疾病的中心PC复合体的生物发生和定位。在上一个资助期内，我们 发现了一个与这两种疾病相关的新基因GANAB，其中编码蛋白GII 参与PC1的成熟和运输。 在这项提案中，我们将利用下一代测序(NGS)方面的进展 方法，以及大量ADPKD和ADPLD患者已经组装和 筛选经典基因，寻找这些疾病的新基因(目标1)。与之相关的表型 将描述这些基因的特征(目标3)及其作用机制(目标2)。NGS方法将 完善以筛选节段性重复的基因座PKD1，并在已知的位置识别缺失的突变 基因座，包括仅存在于某些细胞中的嵌合体基因(目标1)。许多PKD_1的意义 非截断变异很难评估(被归类为意义未知的变异；vus)，但 最近有证据表明，有些是不完全穿透的等位基因，这部分解释了PKD1的表型变异 人口。在目标2中，计算机预测的改进，与机器学习相结合，将改善 了解VUS的致病性和外显性。生物发生和贩运的细胞分析 这一PC复合体的特征也将被用于量化VU的外显。致病机理探讨 将在具有超低渗透蛋白(ULP)PKD1或PKD2等位基因的动物模型中进行探索。雇佣大型企业 临床上、影像上和遗传上定义良好的人群表型患者分组将被定义 然后将其与基因组和PKD1等位基因组(目标3)进行比较。这一迭代过程将允许 与要细化的每个PKD1VU相关联的变量分数(VS)。在单独的种群中，修正后的VS， 将单独使用并结合临床、功能和成像数据来生成 ADPKD的综合预测算法(目标3)。通过双等位基因对严重疾病进行疾病修饰 ADPKD，以及由于其他基因座上的等位基因，也将在细胞检测和体内鉴定和表征 结合PKD1亚型，RC模型。最终目标将利用新确定的 一些PKD1和PKD2 VU是可挽救的，在成熟培养过程中折叠突变的信息 环境可以适当地传输和发挥作用。一种基于细胞表面PC1水平的筛选方案 将得到改进，并将与以下公司合作寻找针对PC复合体的新伴侣药物 桑福德·伯纳姆·普雷比。将在治疗上探索的第二个突变组是无稽之谈 突变。正在开发一种检测通读效率的细胞测试方法，并将用于筛选。 已确定的伴侣或直读药物将在现有的小鼠模型中进行测试。总体而言，这项提案将 更好地解释ADPKD/ADPLD表型变异的病因和遗传原因，更好地发展 用于个人选择治疗患者的预后工具现已可用，并探索 ADPKD的等位基因治疗。

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.