Therapeutic target discovery in ADSP data via comprehensive whole-genome analysis incorporating ethnic diversity and systems approaches

通过结合种族多样性和系统方法的全面全基因组分析，在 ADSP 数据中发现治疗靶点

• 批准号: 10474531
• 负责人: ERIC A. BOERWINKLE
• 金额: $ 214.75万
• 依托单位: BOSTON UNIVERSITY MEDICAL CAMPUS
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-30 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10474531
• 关键词: Accounting; Admixture; African American; Aging; Alzheimer' s Disease; Alzheimer' s disease risk; Bioinformatics; Biological; Clinical; Clinical Research; Cognition; Cognitive; Collaborations; DNA Methylation; Data; Data Set; Development; Disease; Disease Pathway; Drug Targeting; Elderly; Ensure; Equilibrium; Ethnic Origin; Ethnic group; European; Evaluation; Follow-Up Studies; Gene Expression; Genes; Genetic; Genome; Genomics; Goals; Heart; Hispanic Americans; Human Biology; Information Retrieval; Infrastructure; Investments; Magnetic Resonance Imaging; Maps; Measures; Medicine; Meta-Analysis; Methodology; Methods; MicroRNAs; Participant; Pathway interactions; Phase; Phenotype; Population; Population Heterogeneity; Prevention; Procedures; Quality Control; Research; Research Personnel; Resources; Risk; Role; Sampling; Single Nucleotide Polymorphism; Structure; System; Trans-Omics for Precision Medicine; Validation; Variant; Work; admixture mapping; aging brain; bioinformatics network; bioinformatics tool; candidate validation; case control; cohort; endophenotype; ethnic diversity; exome; exome sequencing; experience; gene network; genetic variant; genome analysis; genome sequencing; genome wide association study; genome-wide analysis; genomic epidemiology; innovation; insertion/deletion mutation; member; metabolomics; multi-ethnic; network models; novel; pre-clinical; programs; protective allele; rare variant; risk variant; statistics; therapeutic target; whole genome; working group

Project Summary/Abstract: The Alzheimer Disease Sequencing Project (ADSP) seeks to identify new genomic variants contributing to increased risk for and protection from Alzheimer's Disease in multi-ethnic populations, and to identify new pathways for disease treatment and prevention. Whole genome and whole exome sequencing data (WGS and WES) are available from ADSP Discovery and Discovery-Extension Phases and WGS in diverse ethnic groups will be generated for the Follow-up Study (FUS). The investigators of this proposal have diverse but complementary expertise across the range of bioinformatics, applied statistics and methodological development, admixture and ethnic diversity, rare variant association, network modeling, preclinical validation of targets, and clinical expertise in AD and have been involved in the ADSP since its inception. Further they bring expertise on endophenotypes and additional WGS data through their role within the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) and TOPMed (Trans-Omics for Precision Medicine) consortia. We now propose the following aims to meet ADSP goals. Aim 1: To fully characterize known AD loci and to identify novel protective and risk variants for AD by exploiting the full range of genetic variability revealed by WGS including single nucleotide polymorphisms, small insertion/deletions, and structural variants. Analyses will include expanded association analyses of AD and endophenotypes, identification of novel protective variants via carefully selected “Wellderly” samples, and integration of findings across analyses. Aim 2: To leverage ethnically-diverse and admixed populations to identify novel variants for AD and endophenotypes. This will be achieved by estimating and accounting for global-scale population structure in association analyses across the three phases of ADSP. We additionally propose to perform admixture mapping in samples of admixed ancestry and to perform ethnic-specific analyses and trans-ethnic meta- analyses. Aim 2 analyses will be performed for AD, AD endophenotypes, and Wellderly status. Aim 3: To functionally characterize genes, gene networks, and systems, via bioinformatics and omics integrative analyses to identify putative therapeutic targets. The investigators will work closely with the Accelerating Medicines Partnership (AMP) projects. We propose to use a combination of bioinformatics tools and analysis of “omics” data, including DNA methylation, gene expression, miRNA and metabolomics data within AMP and in the CHARGE cohorts to predict function of specific variants or groups of variants, to apply network approaches across gene sets, to utilize a systems approach to understand the ADSP sequencing data in the larger context of human biology and to identify putative therapeutic targets. Our proposal provides a comprehensive, integrated plan, which we will implement within the existing ADSP infrastructure and in coordination with ADSP investigators.

项目总结/文摘: