Comprehensive Harmonization and Analysis of Case/Control Whole Genome Sequencing Data from the ALS/FTD Compute Project

项目摘要/摘要 肌萎缩侧索硬化症(ALS)是一种致命的神经退行性疾病，其特征是进行性 大脑和脊髓运动神经元(MN)丢失。约50%的肌萎缩侧索硬化症患者显示额颞部 痴呆症(FTD)相关症状；反过来，大约40%的FTD患者表现出运动 神经元缺陷，大约15%的人发展为ALS。鉴于ALS和FTD之间的重叠，两者 疾病被认为代表一种疾病谱(ALS/FTD)。近年来，我们和其他人已经 成功地确定了ALS/FTD的几个遗传原因，这对我们理解ALS/FTD有很大帮助 疾病发病机制的研究。不幸的是，三分之一的家族性遗传病和约90%的 零星形式的ALS/FTD仍未得到解释。因此，迫切需要确定更多的基因 ALS/FTD的致病因素。最近的遗传学研究越来越多地表明稀有变异的强大作用， 人类疾病中的非编码区和结构变异(SVS)。不幸的是，这样的研究需要非常多的 来自病例和对照的WGS协调数据集的大量队列。为了克服这一未得到满足的需求，我们有 创建了ALS/FTD计算项目，以结合来自每个主要测序的原始ALS/FTD WGS数据 在美国的努力。此外，ALS/FTD计算已被NHGRI的Anvil程序接受 提供托管ALS/FTD计算的优秀平台，并提供技术支持。迄今为止，我们 已从超过10,000例ALS/FTD病例中获得原始WGS数据，并确定了约35,000例对照原始数据 WGS数据。此应用程序目标是协调我们的WGS队列的数据，然后是次要数据 分析以确定导致ALS/FTD的新的遗传因素。为了实现这些目标，我们设计了 以下具体目标：R61阶段(1)协调表型和WGS队列数据并确定 SNV/INDELS。WGS原始数据将接受重新比对和联合基因分型呼叫，以确定和 对铁锤平台上的SNV/INDELS进行注释。(2)识别新的变种 和谐的队列。来自AIM#1的协调数据将用于识别/分型SVS并重复 扩展(RE)。(3)从数据协调/变量调用角度对质量控制指标进行评估。 将对目标1/2的QC指标进行评估，以确保高质量的协调和变体调用。R33 阶段(4)发现与ALS/FTD相关的新SNV/INDELs。协调后的数据集将是 受制于几项分析，包括GWAS、稀有变异关联测试、遗传力估计和遗传 相关性检验。(5)发现与ALS/FTD相关的新的SVS/RES。分析与之关联 将进行常见和罕见的SVS，包括对多等位CNV的专门测试和对 短串联重复。(6)发现ALS/FTD的新型遗传修饰剂。将执行分析以 发现与临床疾病亚型和量化结果衡量标准相关的变异，并预测 将建立模型，对基因之间相互作用的影响进行建模。

Project Summary / Abstract Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disorder characterized by the progressive loss of brain and spinal cord motor neurons (MNs). Approximately 50% of ALS patients display Frontotemporal Dementia (“FTD”)-associated symptoms; reciprocally, approximately 40% of FTD patients display motor neuron deficits with approximately 15% developing ALS. Given the overlap between ALS and FTD, the two conditions are considered to represent a disease spectrum (ALS/FTD). In recent years, we and others have successfully identified several genetic causes of ALS/FTD which has greatly contributed to our understanding of disease pathogenesis. Unfortunately, one-third of the underlying genetic causes of familial and ~90% of sporadic forms of ALS/FTD still remain unexplained. As such, there is a dire need to identify additional genetic factors contributing to ALS/FTD. Recent genetic studies have increasingly shown a strong role of rare variants, non-coding regions and structural variants (SVs) in human diseases. Unfortunately, such studies require very large cohorts of harmonized WGS data sets from cases and controls. To overcome this unmet need, we have founded the ALS/FTD Compute project to combine the raw ALS/FTD WGS data from every major sequencing effort in the United States. Further, ALS/FTD Compute has been accepted into NHGRI’s AnVIL program providing an excellent platform for hosting ALS/FTD Compute and providing technical support. To date, we have obtained the raw WGS data from over ~10,000 ALS/FTD cases and have identified ~35,000 control raw WGS data. The objective of this application is to data harmonize our WGS cohort followed by secondary analyses to identify novel genetic elements contributing to ALS/FTD. Toward these goals, we have designed the following specific aims: R61 Phase (1) Harmonize the Phenotypic and WGS Cohort Data and Identify SNVs/Indels. Raw WGS data will be subject to re-alignment and joint genotyping calling to identify and annotate SNVs/indels on the AnVIL platform. (2) Identification of Additional Variants Within the Harmonized Cohort. The harmonized data from Aim #1 will be used to identify/genotype SVs and repeat expansions (REs). (3) Evaluation of Quality Control Metrics from the Data Harmonization/Variant Calling. QC metrics from Aim #1/#2 will be evaluated to ensure high quality harmonization and variant calling. R33 Phase (4) Discovery of Novel SNVs/Indels Associated with ALS/FTD. The harmonized data set will be subject to several analyses including GWAS, rare variant association testing, heritability estimates, and genetic correlation tests. (5) Discovery of Novel SVs/REs Associated with ALS/FTD. Analyses of association with common and rare SVs will be performed, including specialized test for multi-allelic CNVs and expansion of short tandem repeats. (6) Discovery of Novel Genetic Modifiers of ALS/FTD. Analyses will be performed to discover variants associated with clinical disease subtypes and quantitative outcome measures, and predictive models will be built that model the effects of interactions between genes.