In-vivo MRI-based prediction of TDP43 pathology in aging

点击翻译按钮获取中文摘要

ABSTRACT Transactive response DNA-binding protein 43 (TDP43) pathology, a primary protein abnormality in the rare diseases amyotrophic lateral sclerosis and frontotemporal lobar degeneration, is now recognized as a common age-related neuropathology, detected at autopsy in approximately 50% of older persons. According to recent evidence, TDP43 pathology in aging is associated with more rapid cognitive decline and higher odds of dementia, above and beyond contributions from Alzheimer’s and other age-related neuropathologies. In spite of its high frequency and deleterious effects, TDP43 can only be diagnosed at autopsy, and there is currently no approach that provides in-vivo accurate information about the presence of TDP43 pathology in aging. The overall goal of the proposed project is to develop and test an in-vivo MRI-based classifier of TDP43 pathology in aging by combining multimodal MRI and pathology in the same older persons from large community cohorts. Specifically, we propose to a) train TDP43 classifiers using machine learning based on ex- vivo MRI measurements of macro-structural, micro-structural and chemical brain characteristics of older persons, b) translate these classifiers in-vivo, and c) test them in-vivo using longitudinal clinical, in-vivo MRI, and pathology data on older adults enrolled without dementia. We have generated a unique ex-vivo and in-vivo multimodal MRI-pathology database within the infrastructure of the Rush Memory and Aging Project (MAP) (R01AG17917) and Religious Orders Study (ROS) (P30AG010161), two longitudinal, epidemiologic clinical- pathologic cohort studies of aging that recruit non-demented individuals and have high follow-up rates and high autopsy rates. Using our database, we have produced compelling preliminary results in support of our aims. First, we have demonstrated that ex-vivo brain MRI data can be linked to in-vivo MRI data. Second, we show that TDP43 pathology is related to specific brain MRI characteristics independent of other age-related pathologies. Third, we show high TDP43 classification performance (AUC=0.81) based on ex-vivo MRI features in persons with as well as without comorbid Alzheimer’s pathology (a common coexisting pathology). Fourth, we demonstrate that the confidence score obtained from ex-vivo MRI classification is linked to the progression of deposition of TDP43 pathology (i.e. TDP43 stages). Finally, we translated a preliminary ex-vivo TDP43 classifier for use in-vivo and demonstrated in a small sample that it has high in-vivo classification performance, and is independently associated with lower cognition. We propose to further develop and test this promising in-vivo MRI classifier of TDP43 pathology in aging.