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

来自 ALS/FTD 计算项目的病例/对照全基因组测序数据的全面协调和分析

• 批准号: 10592917
• 负责人: JOHN E LANDERS
• 金额: $ 163.03万
• 依托单位: UNIV OF MASSACHUSETTS MED SCH WORCESTER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-01 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10592917
• 关键词: ALS patients; Alleles; Amyotrophic Lateral Sclerosis; Brain; Clinical; Communities; Data; Data Set; Development; Disease; Ensure; Etiology; Evaluation; Frontotemporal Dementia; Genes; Genetic; Genetic study; Genotype; Goals; Heritability; Joints; Location; Motor Neurons; National Human Genome Research Institute; Nature; Neurodegenerative Disorders; Outcome Measure; Pathogenesis; Patients; Phase; Phenotype; Process; Quality Control; Role; Sampling; Short Tandem Repeat; Spinal Cord; Testing; United States; Untranslated RNA; Variant; associated symptom; cohort; data harmonization; design; disorder subtype; frontotemporal lobar dementia amyotrophic lateral sclerosis; genetic element; genome sequencing; genome wide association study; human disease; improved; insertion/deletion mutation; model building; novel; predictive modeling; programs; rare variant; repository; secondary analysis; segregation; whole genome

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.

项目摘要 /摘要 肌萎缩性外侧硬化症（ALS）是一种致命的神经退行性疾病，其特征是进行性疾病 大脑和脊髓运动神经元（MN）的丧失。大约50％的ALS患者表现出额颞 痴呆症（“ FTD”） - 相关符号；相度地，大约40％的FTD患者显示电动机 神经元定义了大约15％的ALS。鉴于ALS和FTD之间的重叠，这两个 疾病被认为代表疾病谱（ALS/FTD）。近年来，我们和其他人有 成功地确定了ALS/FTD的几种遗传原因，这极大地有助于我们的理解 疾病发病机理。不幸的是，家庭的基本原因中有三分之一，约有90％ ALS/FTD的零星形式仍然未知。因此，有直接需要确定其他通用 导致ALS/FTD的因素。最近的遗传研究已经显示出稀有变体的重要作用， 人类疾病中的非编码区域和结构变体（SVS）。不幸的是，这样的研究需要非常 来自案例和控制的大量协调WGS数据集。为了克服这种未满足的需求，我们有 建立了ALS/FTD计算项目，以结合每个主要测序的原始ALS/FTD WGS数据 在美国的努力。此外，ALS/FTD计算已被接受为NHGRI的Anvil计划 为托管ALS/FTD计算并提供技术支持提供了一个绝佳的平台。迄今为止，我们 已从约10,000 ALS/FTD案例中获得了原始WGS数据，并确定了约35,000个对照RAW WGS数据。该应用的目的是数据协调我们的WGS队列，然后进行次要 分析以鉴定有助于ALS/FTD的新型遗传元素。朝着这些目标，我们设计了 以下具体目的：R61阶段（1）协调表型和WGS队列数据并识别 SNV/Indels。 RAW WGS数据将受到重新调整和联合基因分型呼吁，以识别和 在砧平台上注释SNV/Indels。 （2）确定在 协调的队列。 AIM＃1的统一数据将用于识别/基因型SV并重复 扩展（Res）。 （3）从数据协调/变体调用中评估质量控制指标。 将评估来自AIM＃1/＃2的QC指标，以确保高质量的协调和变体调用。 R33 阶段（4）发现与ALS/FTD相关的新型SNV/Indels。统一的数据集将是 进行多项分析，包括GWA，稀有变体关联测试，遗传性估计和遗传 相关测试。 （5）发现与ALS/FTD相关的新型SVS/RES。与 将执行常见和稀有的SV，包括用于多行CNV的专门测试和扩展 简短的串联重复。 （6）发现ALS/FTD的新型遗传修饰符。分析将进行 发现与临床疾病亚型和定量结果指标相关的变体和预测性 将建立模型，以建模基因之间相互作用的影响。