Genetic Architecture of Pure Alzheimer's Disease and Mixed Pathology

纯阿尔茨海默病和混合病理学的遗传结构

基本信息

批准号：
10712591
负责人：
David William Fardo
金额：
$ 100.15万
依托单位：
UNIVERSITY OF WASHINGTON
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：
2023-09-01 至 2028-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10712591
关键词：
Address Aging Alzheimer&apos s Disease Alzheimer&apos s disease brain Alzheimer&apos s disease pathology Alzheimer&apos s disease related dementia Atlases Autopsy Bioinformatics Biological Brain Pathology Brain region Cerebrovascular Trauma Chromatin Clinical Clinical Data Clinical Trials Clinical Trials Design Cognitive Data Dementia Development Disease Progression Drug Targeting Exhibits Future Genetic Genetic study Genomic Segment Genotype Goals Hand Heterogeneity Human Individual Infarction Knowledge Lead Lewy Bodies Machine Learning Memory Mendelian randomization Molecular Multiomic Data Participant Pathology Pathway Analysis Pattern Persons Phenotype Research Resolution Risk Factors Sample Size Stratification Tissue-Specific Gene Expression Variant biobank brain cell case control cell type clinical risk data resource disorder control epidemiology study follow-up gene network genetic analysis genetic architecture genome wide association study genome-wide hippocampal sclerosis improved insight neuropathology novel novel strategies pleiotropism prevent protein TDP-43 religious order study risk variant single nucleus RNA-sequencing trait transcriptome

项目摘要

Co-occurring neuropathologies such as Lewy bodies, hippocampal sclerosis, and microinfarcts likely influence heterogeneity in genetic studies of Alzheimer’s disease (AD). The genetic architecture of these co-occurring neuropathologies is not clear. Most AD genetic analyses use clinical AD dementia phenotypes and are limited by phenotype misclassification: many clinical AD “controls” harbor AD pathology while clinical AD “cases” have no or minimal AD pathology. Only 20% of pathology confirmed AD dementia cases have only AD pathology (“pure AD”); 80% have co-occurring neuropathologies (“mixed AD”). A complementary strategy is to perform genome-wide association studies (GWAS) specifically distinguishing between pure and mixed AD. The overarching goal of this proposal is to further scientific understanding of pure AD and mixed AD by integrating neuropathology together with advanced statistical approaches and extensive multi-omics data. Aim 1: Distinguish the genetic architecture of pure AD vs. mixed AD vs. pathology-free controls and determine how associations are driven by particular neuropathological patterns. 1a. Perform GWAS of pathology-confirmed AD controls vs. pure AD vs. mixed AD using a multinomial regression framework. We will also examine how associations are driven by particular neuropathological features furthering our understanding of underlying mechanisms. 1b. Infer possible mechanisms by integrating biological knowledge. We will perform transcriptome- wide analyses and gene-network analyses of pure AD and mixed AD, integrating human PPI data. Aim 2: Identify factors specific to pure AD or mixed AD. 2a. Use machine learning and harmonized clinical data to isolate factors associated with pure or mixed AD. Identified clinical risk factors could be used for future clinical trial stratification. 2b. Perform genetic correlation analysis and Mendelian randomization to estimate correlated genetic effects and potential causal effects between candidate risk factor traits and pure or mixed AD. Genetic correlation analysis will gain novel insights into the shared genetic basis between biobank-scale GWAS traits and pure AD and mixed AD. We will follow-up significant correlations with local genetic correlation and Mendelian randomization (MR) to identify specific genomic regions contributing to the correlation and quantify causal effects of these traits on pure AD and mixed AD. Aim 3. Characterize the cellular and molecular consequences of pure AD vs mixed AD. We will harness the data generated by the SEA-AD and the ROS-MAP studies to characterize the molecular changes occurring for our phenotypes at cell type resolution. We will perform abundance analyses (3a), differential gene expression (3b), and differential chromatin accessibility (3c) in each cell type across multiple brain regions. We will investigate loci from recent GWASs of AD dementia and candidates from Aim 1.

同时发生的神经病理学，例如路易体、海马硬化和微梗塞可能会影响阿尔茨海默病（AD）遗传研究的异质性这些同时发生的遗传结构。大多数 AD 基因分析使用临床 AD 痴呆表型，但其神经病理学研究尚不明确。按表型错误分类：许多临床 AD“对照”具有 AD 病理学，而临床 AD“病例”则具有 AD 病理学特征没有或仅有极少的 AD 病理，只有 20% 的病理证实的 AD 痴呆病例仅有 AD 病理。（“纯 AD”）；80% 患有同时发生的神经病理学（“混合 AD”）。全基因组关联研究 (GWAS) 特别区分纯 AD 和混合 AD。该提案的总体目标是通过整合进一步对纯 AD 和混合 AD 的科学理解神经病理学以及先进的统计方法和广泛的多组学数据。目标 1：区分纯 AD 与混合 AD 与无病理对照的遗传结构，以及确定特定神经病理模式如何驱动关联。 1a. 使用病理学确认的 AD 对照与纯 AD 与混合 AD 进行 GWAS 我们还将研究特定的关联是如何驱动的。神经病理学特征加深了我们对潜在机制的理解。 1b. 通过整合生物学知识推断可能的机制。对纯 AD 和混合 AD 进行广泛分析和基因网络分析，整合人类 PPI 数据。目标 2：确定纯 AD 或混合 AD 的特有因素。 2a. 使用机器学习和统一的临床数据来分离与纯或相关的因素已确定的临床危险因素可用于未来的临床试验分层。 2b. 执行遗传相关分析和孟德尔随机化以估计相关遗传候选危险因素特征与纯或混合 AD 之间的影响和潜在因果效应。遗传相关分析将对生物样本库规模之间的共享遗传基础获得新的见解 GWAS性状与纯AD和混合AD的显着相关性我们将进行追踪。相关性和孟德尔随机化（MR）来识别特定的基因组区域有助于相关性并量化这些特征对纯 AD 和混合 AD 的因果影响。目标 3. 表征纯 AD 与混合 AD 的细胞和分子后果。 SEA-AD 和 ROS-MAP 研究生成的数据来表征发生的分子变化对于细胞类型分辨率的表型，我们将进行丰度分析 (3a)，差异基因。跨多个大脑区域的每种细胞类型的表达 (3b) 和差异染色质可及性 (3c)。将调查 AD 痴呆症的近期 GWAS 基因座和目标 1 的候选基因座。