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

与衰老相关的痴呆症具有高度遗传性，但这种遗传风险的很大一部分仍然无法解释。在 >30%的老年人患有临床痴呆症，尸检显示TDP-43病理-一个巨大的和不足- 公认的公共卫生问题。一个流行的非阿尔茨海默氏遗忘性痴呆相关的术语 最近提出了一种新的疾病：边缘系统主导的年龄相关性TDP-43脑病（LATE）。有 晚期病理学个体之间存在很大的临床和病理异质性。一些受影响的人 有一个快速和毁灭性的临床过程，而其他人有相对良性的症状。无论是严重性 TDP-43病理学和共病病理学的存在似乎是临床预后的关键决定因素。 后期的成果。我们已经产生了令人兴奋的初步数据，表明不同的（和多效性）遗传 晚期和相关病理的风险因素。然而，人们对这一问题的认识仍然不完全。 这些脑部疾病的遗传决定因素为了解决这一知识差距，我们将开发一个强大的分析， 管道（利用大量的先前工作和资源）使用数据驱动的方法对病理进行分类 研究进展和新的统计方法来分析遗传风险/保护因素。 目的1：组装多模态数据集（包括临床和遗传学数据），用于测试新假设 关于晚期发病机制，并为病理学的“纯”和“混合”亚型制定规则 我们将利用广泛的数据处理资源来推导和测试病理分类系统 最适合研究遗传风险和神经病理学内表型之间的关系。关键 数据集中的内表型将包括病理学的数字神经病理学评估。通过这些 研究，我们将收集和策划不同人群的临床，遗传和病理信息。 目的2：确定与衰老相关的TDP-43脑病理学相关的遗传区域，即，晚 我们将采用全基因组和有针对性的关联测试，预测数量性状位点（QTL）检测， 以及随后的共定位。初步结果表明，我们的目标是可以实现的， 研究样本量。我们和其他人已经发现了一组晚期风险因素基因，2-6包括证据- 概念：LATE神经病理学基因先前与临床阿尔茨海默病（WWOX）有关。 目的3：确定与LATE相关神经病理学改变相关的遗传区域和生物学通路。 内表型：海马硬化、小动脉硬化和阿尔茨海默病共存 我们将检验共病LATE相关表型共享遗传易感性， 被视为子类型。此外，潜在的途径是可与多变量方法学。我们将 扩大我们对遗传风险因素，疾病相关途径的理解，以及 改变这些路径。我们将开发和采用多元，集群和个人特定的网络 推断驱动LATE相关病理表型的途径的方法。

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.