ADSP Follow-up in Multi-Ethnic Cohorts via Endophenotypes, Omics & Model Systems

描述(由申请人提供)：ADSP发现阶段将识别可能的新AD基因/变种。然而，为了令人信服地建立新的迟发性AD(LOAD)基因座，复制是必不可少的，NHGRI将资助14,000至30,000人的复制测序。样本选择和分析战略将由亚洲及太平洋战略规划指导委员会与http://grants.nih.gov/grants/guide/rfa-files/RFA-AG-16-002.html的获奖者共同确定。在这里，我们提出了一种具有成本效益的策略来利用表型、内表型、基因组和多维组学数据，这些数据可以通过基因组流行病学心脏和衰老研究队列(CHARD)及其庞大的合作者网络获得。在目标1中，我们将协调来自发现和复制阶段的表型和遗传数据，以验证变异和基因水平的AD关联，并用于新基因发现，以补充U54的努力。样本将从非洲、西班牙裔、亚洲和欧洲血统的社区队列中提取(15,000例病例和100,000名对照，其中60,000名年龄在65岁以上)。四分之一的样本已经有了序列数据(整个外显子组，全基因组)；其余的将有资格进行NHGRI复制测序。全基因组阵列数据可在&gt；65,000中获得，我们建议使用具有定制AD含量的Illumina多种族基因阵列(MEGA)芯片，对另外约10,000个表型丰富的样本进行基因分型，这些样本被选为非欧洲或欧洲样本，但具有独特的测量方法(例如，使用淀粉样蛋白PET扫描)。我们将整合阵列和序列数据，使用代表研究样本祖先多样性的改进参照板来执行常见和中等罕见变异的归属。在目标2中，我们将利用多种族和混合样本中的精细群体结构来验证和精细定位发现阶段的基因座，并通过跨种族荟萃分析和混合作图来识别新的AD基因座。此外，我们将通过研究先前协调的和新的、敏感的内表型来确定与AD相关的新的生物学途径，包括(1)脑MRI：海马体体积、脑白质微结构损伤和皮质萎缩的“广告信号”模式；(2)认知：一般认知表现和言语记忆；(3)生物标记物：宠物淀粉样蛋白负荷和循环中的β-淀粉样蛋白水平。在目标3中，我们将对生物学有更多的了解，并为实验后续和药物开发确定基因座的优先顺序。具体地说，我们将利用生物信息学工具和“组学”数据，包括可用的DNA甲基化、基因表达、miRNA和来自Charge的代谢组学，并通过加速药物伙伴关系-AD(AMP-AD)项目来创建和验证AD特异性的联合注释依赖耗竭工具(AD-CADD)，最后，我们将解析最有希望的基因座，用于使用果蝇基因敲除模型进行进一步的功能探索。

DESCRIPTION (provided by applicant): The ADSP discovery phase will identify putative novel AD genes/variants. Nevertheless, to convincingly establish new late-onset AD (LOAD) loci, replication is essential and NHGRI will fund replication sequencing in 14,000 to 30,000 persons. Sample selection and analytical strategies will be determined by the ADSP Steering Committee in conjunction with grant awardees of RFA http://grants.nih.gov/grants/guide/rfa-files/RFA- AG-16-002.html. Here, we propose a cost-effective strategy to leverage phenotypic, endophenotypic, genomic and multi-dimensional omics data available through the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) and its large network of collaborators. In Aim 1, we will perform harmonization of phenotypic and genetic data from discovery and replication phases for validation of variant- and gene-level AD associations, and for novel gene discovery, supplementing U54 efforts. Samples will be drawn from community-based cohorts of African, Hispanic, Asian, and European ancestry (>15,000 cases & 100,000 controls, of whom >60,000 are over age 65). One quarter of the sample already has sequence data (whole exome, whole genome) available; the others will be eligible for the NHGRI replication sequencing. Genome- wide array data are available in >65,000 and we propose to use the Illumina Multi-Ethnic Genotype Array (MEGA) chip, with custom AD content, to genotype an additional ~10,000 richly phenotyped samples, selected for being non-European or European but with unique measures (e.g., with amyloid PET scans). We will integrate array- and sequence data to perform imputation of common and moderately rare variants using improved reference panels that represent the ancestral diversity of the study samples. In Aim 2, we will leverage fine-scale population structure in multi-ethnic and admixed samples to validate and fine-map discovery phase loci, and also identify novel AD loci through trans-ethnic meta-analyses and admixture mapping. In addition, we will identify novel AD-relevant associations and interrogate biological pathways by studying previously-harmonized and new, sensitive endophenotypes including (1) Brain MRI: hippocampal volumes, white matter microstructural injuries and `AD signature' patterns of cortical atrophy; (2) Cognition: general cognitive performance and verbal memory; (3) Biomarker: PET amyloid burden and circulating beta- amyloid levels. In Aim 3, we will gain additional insight into biology and prioritize loci for experimental follow-up and drug development. Specifically, we will utilize bioinformatic tools and "omics" data, including available DNA methylation, gene expression, miRNA and metabolomics from CHARGE and through the Accelerated Medicine Partnerships-AD (AMP-AD) project to create and validate an AD-specific Combined Annotation Dependent Depletion tool (AD-CADD), finally, we will parse the most promising loci for further functional exploration using Drosophila knockdown models.