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

基本信息

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
项目类别：
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

项目摘要

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.

项目概要/摘要肌萎缩侧索硬化症（ALS）是一种致命的神经退行性疾病，其特征是进行性进展大约 50% 的 ALS 患者出现额颞叶缺失。痴呆症 (“FTD”) 相关症状；大约 40% 的 FTD 患者表现出运动症状；神经元缺陷导致大约 15% 的人出现 ALS。鉴于 ALS 和 FTD 之间的重叠，两者存在重叠。近年来，我们和其他人已将病情视为代表一种疾病谱（ALS/FTD）。成功确定了 ALS/FTD 的几种遗传原因，这极大地促进了我们的理解不幸的是，三分之一的潜在遗传原因是家族性的，约 90% 是遗传性的。散发性的 ALS/FTD 仍然无法解释，因此迫切需要识别更多的遗传因素。最近的基因研究越来越多地表明罕见变异的重要作用，不幸的是，此类研究需要非常多的研究。为了克服这一未满足的需求，我们拥有大量来自病例和对照的统一 WGS 数据集。创立了 ALS/FTD 计算项目，将来自每个主要测序的原始 ALS/FTD WGS 数据结合起来此外，ALS/FTD Compute 已被 NHGRI 的 AnVIL 计划接受。为托管 ALS/FTD 计算并提供技术支持提供出色的平台。已从约 10,000 多个 ALS/FTD 病例中获取了原始 WGS 数据，并确定了约 35,000 个对照原始数据此应用程序的目的是协调我们的 WGS 队列，然后是二次数据。为实现这些目标，我们设计了分析以确定有助于 ALS/FTD 的新遗传因素。以下具体目标： R61 阶段 (1) 协调表型和 WGS 队列数据并识别 SNV/Indels 原始 WGS 数据将进行重新排列和联合基因分型调用以识别和在 AnVIL 平台上注释 SNV/indels (2) 识别其他变体。协调队列目标 #1 的协调数据将用于识别 SV/基因型 SV 并重复。 (RE) (3) 数据协调/变体调用的质量控制指标评估。将评估目标 #1/#2 的 QC 指标，以确保高质量的协调和变异识别 R33。阶段 (4) 与 ALS/FTD 相关的新型 SNV/Indel 的发现协调数据集将是。进行多项分析，包括 GWAS、罕见变异关联测试、遗传力估计和遗传 (5) 与 ALS/FTD 相关的新 SV/RE 的发现。将进行常见和罕见的 SV，包括多等位基因 CNV 的专门测试和扩展 (6) 将进行 ALS/FTD 分析的新型遗传修饰物的发现。发现与临床疾病亚型和定量结果测量相关的变异，以及预测将建立模型来模拟基因之间相互作用的影响。