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

University Of Kentucky, Lexington KY

Investigators

Linked publications, trials & patents

Abstract

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.