Genetic Architecture of Aging-Related TDP-43 and Mixed Pathology Dementia

衰老相关 TDP-43 和混合病理痴呆的遗传结构

基本信息

批准号：
10658215
负责人：
David William Fardo
金额：
$ 171.45万
依托单位：
UNIVERSITY OF KENTUCKY
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：
2023-04-15 至 2026-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10658215
关键词：
Address Affect Aging Alzheimer&apos s Disease Alzheimer&apos s disease related dementia Arterioloscleroses Automobile Driving Autopsy Benign Bioinformatics Biological Biometry Brain Brain Diseases Brain Pathology Brain region Classification Clinical Collection Complex Data Data Collection Data Set Databases Dementia Detection Disease Genes Genetic Genetic Determinism Genetic Models Genetic Predisposition to Disease Genetic Risk Genomics Genotype Goals Hand Heritability Heterogeneity Human Individual Interdisciplinary Study Knowledge Link Maps Methodology Methods Multivariate Analysis Nerve Degeneration Outcome Pathogenesis Pathologic Pathology Pathway interactions Pattern Persons Phenotype Play Population Population Heterogeneity Prevention Public Health Quantitative Trait Loci Research Resources Risk Risk Factors Sample Size Sampling Studies Severities Single Nucleotide Polymorphism Statistical Methods Symptoms System Testing Variant Work age related aged analysis pipeline brain arteriolosclerosis burden of illness cerebrovascular pathology clinical risk comorbidity computerized data processing computing resources dementia risk digital disease phenotype endophenotype evidence base genetic architecture genetic risk factor genetic variant genome wide association study genome-wide genomic locus hippocampal sclerosis limbic-predominant age-related TDP-43 encephalopathy member mixed dementia multidisciplinary multimodal data neuropathology next generation sequencing nonalzheimer dementia novel protective factors protein TDP-43 risk variant

项目摘要

Aging-related dementia is highly heritable, yet a large proportion of this genetic risk remains unexplained. In >30% of aged individuals with clinical dementia, autopsy reveals TDP-43 pathology – an enormous and under- acknowledged public health problem. A term for this prevalent non-Alzheimer’s amnestic dementia-associated condition was recently proposed: limbic predominant age-related TDP-43 encephalopathy (LATE). There is great clinical and pathologic heterogeneity among individuals with LATE pathology. Some affected individuals have a rapid and devastating clinical course, whereas others have relatively benign symptoms. Both the severity of TDP-43 pathology and the presence of comorbid pathologies appear to be key determinants of clinical outcomes in LATE. We have generated exciting preliminary data that indicate distinct (and pleiotropic) genetic risk factors for LATE and associated pathologies. However, there is still an incomplete understanding of the genetic determinants of these brain diseases. To address this knowledge gap, we will develop a robust analysis pipeline (leveraging extensive prior work and resources) using data-driven methods to classify pathology progression and novel statistical methods to analyze genetic risk/protective factors. AIM 1: Assemble multimodal datasets (including clinical and genetics data) for testing novel hypotheses about LATE pathogenesis and develop rubrics for “pure” and “mixed” subtypes of pathology We will leverage extensive data processing resources to derive and test a pathological classification system optimal for research at the nexus between genetic risk and neuropathologic endophenotypes. Key endophenotypes in the dataset will include digital neuropathologic assessment of pathologies. Through these studies, we will gather and curate clinical, genetic, and pathological information on diverse populations. AIM 2: Identify genetic regions associated with aging-related TDP-43 brain pathology, i.e., LATE We will employ genome-wide and targeted association testing, predicted quantitative trait loci (QTL) detection, and subsequent colocalization. Preliminary results demonstrate that our goals are broadly achievable given our study sample sizes. A set of LATE risk factor genes has been discovered by us and others,2-6 including proof-of- concept: a LATE neuropathology gene previously linked to clinical Alzheimer’s disease (WWOX).7 AIM 3: Identify genetic regions and biologic pathways associated with LATE-associated neuropathologic endophenotypes: coexisting hippocampal sclerosis, arteriolosclerosis, and Alzheimer’s disease We will test the hypotheses that comorbid LATE-related phenotypes share genetic predisposition and can be treated as subtypes. Further, underlying pathways are discoverable with multivariate methodologies. We will expand our understanding of the genetic risk factors, disease-associated pathways, and the potential for modifying those pathways. We will develop and employ multivariate, clustering, and individual-specific network methods to infer pathways driving LATE-related pathologic phenotypes.

与衰老有关的痴呆症是高度遗传的，但这种遗传风险的很大一部分仍无法解释。 > 30％的临床痴呆患者尸检揭示了TDP-43病理学 - 一种巨大的和不足的病理公认的公共卫生问题。这个普遍的非阿尔茨海默氏症痴呆症相关的术语最近提出了条件：边缘主要与年龄相关的TDP-43脑病（晚）。有患有晚期病理的个体的临床和病理异质性很高。一些受影响的人具有快速而毁灭性的临床过程，而其他临床过程则相对良性。两种严重性 TDP-43病理学和合并症的存在似乎是临床的关键决定者结果很晚。我们产生了令人兴奋的初步数据，表明了独特的（和多效）通用迟到和相关病理的危险因素。但是，对这些脑疾病的遗传决定剂。为了解决这个知识差距，我们将制定强大的分析使用数据驱动方法对病理进行分类的管道（利用大量的先前工作和资源）进展和新的统计方法分析遗传风险/保护因素。 AIM 1：组装多模式数据集（包括临床和遗传学数据），以测试新假设关于病理的“纯”和“混合”亚型的晚期发病机理和制作专栏我们将利用广泛的数据处理资源来得出病理分类系统在遗传风险和神经病理学内表型之间进行下一个研究的最佳研究。钥匙数据集中的内表型将包括病理学的数字神经病理评估。通过这些研究，我们将收集并策划有关潜水员种群的临床，遗传和病理信息。目标2：确定与衰老相关的TDP-43脑病理学相关的遗传区域，即晚期我们将采用全基因组和靶向关联测试，预测定量性状位置（QTL）检测，和随后的共定位。初步结果表明，鉴于我们研究样本量。美国和其他人发现了一组晚期危险因素基因，其中2-6包括证明证明概念：以前与临床阿尔茨海默氏病（WWOX）相关的神经病理学基因。7 目标3：确定与晚期相关神经病理相关的遗传区域和生物学途径内表型：共存海马硬化症，小动脉粥样硬化和阿尔茨海默氏病我们将测试合并症晚期相关表型具有遗传易感性的假设，可以是被视为亚型。此外，通过多元方法可以发现潜在的途径。我们将扩展我们对遗传危险因素，疾病相关途径的理解以及潜力修改这些途径。我们将开发和使用多元，聚类和个人特定网络推断驱动与晚期病理表型的途径的方法。