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

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.

Grant Number: 5R01AG064233-05
NIH Institute/Center: NIH
Principal Investigator: Konstantinos Arfanakis