Mahir Tazwar1, Arnold M Evia Jr.2, Ashish A Tamhane2, David A Bennett2, Julie A Schneider2, and Konstantinos Arfanakis1,2
1Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, United States, 2Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, United States
Synopsis
Limbic-predominant
age-related TDP-43 encephalopathy neuropathological change (LATE-NC) is now
recognized as a common age-related neuropathology that has been linked to
cognitive decline and dementia. In this work, the spatial pattern of R2
alterations associated with LATE-NC was investigated in a large (N=797)
community cohort of older adults. Voxel-wise analysis revealed a pattern of
lower R2 for greater LATE-NC burden, controlling for all other neuropathologies
and demographics. This pattern involved mainly the temporal, frontal, occipital
lobes and basal ganglia. To our knowledge this is the first R2 investigation in
LATE-NC.
Introduction
Limbic predominant age-related TDP-43
encephalopathy neuropathological change (LATE-NC) is a recently recognized
disease entity referring to the accumulation of transactive response DNA
binding protein of 43kDa (TDP-43) proteinopathy in older adults. LATE-NC is
detected at autopsy in 20-50% of individuals older than 80 years of age.
LATE-NC is associated with lower memory, cognitive decline and increased
likelihood of dementia above and beyond the contributions of other age-related
neuropathologies1–5. Moreover,
LATE-NC has been shown to account for nearly as much of the variance in
late-life cognitive decline as neurofibrillary tangles (hallmark pathology of
Alzheimer’s)6. Thus, LATE-NC
is now recognized as a common and deleterious neuropathology of the aging
brain. In this work, we hypothesized that neuronal changes caused by LATE-NC
may be detected through alterations in R2 relaxation rate, similar to the
effects of other neurodegenerative pathologies such as Alzheimer’s7,8. Therefore, the goal of this study
was to extract the spatial pattern of R2 alterations associated with LATE-NC in
a large community cohort of older adults.Methods
Cerebral
hemispheres were obtained from 797 deceased older adults participating in three
longitudinal, clinical-pathologic cohort studies of aging9,10: the Rush Memory and Aging Project
(MAP), the Religious Orders Study (ROS), and the Minority Aging Research Study
(MARS) (Fig. 1). Hemispheres were imaged ex-vivo on 3T clinical MRI scanners,
while immersed in 4% formaldehyde solution, using a 2D spin-echo sequence with
multiple echo times ranging from 11-83 ms and 0.6×0.6×1.5 mm3 voxel
size. The R2 relaxation rate was quantified voxel-wise by fitting a
monoexponential decay function S = S0∙exp(-R2∙t) to the multi-echo
spin-echo data. The images from one of the echoes were non-linearly registered
to an ex-vivo MRI brain template using ANTS11 and the transformations were applied to the
R2 maps to enable voxel-wise analysis7,12.
Following ex-vivo MRI, hemispheres underwent detailed neuropathologic
examination by a board-certified neuropathologist blinded to all clinical and
imaging findings (Fig. 2).
Voxel-wise linear regression was used to investigate the association of
R2 relaxation rate with LATE-NC controlling for other neuropathologies,
including Alzheimer’s pathology, Lewy bodies, gross and microscopic infarcts,
atherosclerosis, cerebral amyloid angiopathy, arteriolosclerosis, as well as
age at death, sex, years of education, postmortem interval to fixation and
postmortem interval to imaging, and scanner. The analysis was performed using
the PALM tool (FMRIB, Oxford, UK)13
with no acceleration, 10,000 permutations, threshold-free cluster enhancement,
and family-wise error correction for multiple comparisons. Statistical
significance was set at p<0.05.Results and Discussion
Voxel-wise
analysis demonstrated lower R2 for greater LATE-NC burden in a number of brain
regions in the temporal, frontal, occipital lobes and basal ganglia (Fig. 3).
The strongest effects were observed in the amygdala, hippocampus, and
neighboring temporal lobe regions. These findings are in agreement with
previous work showing that LATE-NC typically begins and is most commonly seen
in the amygdala14,15. In later
stages, LATE-NC is deposited in the hippocampus and entorhinal cortex, and then
the neocortex and other regions, especially in the frontal lobe4 where we also saw R2 shortening with
LATE-NC. In addition, lower R2 with greater LATE-NC burden was demonstrated in
the caudate, insular and occipital white matter regions which have been studied
less in terms of LATE-NC pathology14,16,17.
No brain regions showed positive associations of R2 with LATE-NC.
To
the best of our knowledge, this study is the first to reveal the spatial
pattern of R2 alterations linked to LATE-NC. The findings of this work suggest
that LATE-NC has an independent contribution to R2 shortening above and beyond
the contributions of other neuropathologies and demographics. The extracted
pattern of R2 shortening is rather consistent with the known distribution of
LATE-NC in the brain of older adults. This pattern may potentially aid in
in-vivo prediction of this devastating neuropathology which, currently, can
only be diagnosed at autopsy.
The
present study combined MRI and pathology data from a particularly large number
of community-based older adults which enhances the robustness and
generalization of the findings. Although MRI was conducted ex-vivo, we expect
the results to hold in-vivo since we have previously demonstrated that ex-vivo
R2 values are linearly linked to in-vivo R2 values for the tissue preparation
and imaging protocol used here7.Conclusion
The present study demonstrated a spatial pattern
of lower R2 relaxation rate for greater LATE-NC burden in a large community
cohort of older adults. This pattern involved mainly the temporal, frontal,
occipital lobes and basal ganglia, and the strongest effects were observed in
the amygdala, hippocampus, and neighboring temporal lobe regions. The link
between R2 and LATE-NC presented in this work may be exploited towards the
development of algorithms for the prediction of this devastating, recently
recognized disease entity.Acknowledgements
National
Institute of Neurological Disorders and Stroke (NINDS) UH2-UH3NS100599
National
Institute on Aging (NIA) R01AG064233
National
Institute on Aging (NIA) R01AG067482
National
Institute on Aging (NIA) R01AG017917
National
Institute on Aging (NIA) R01AG015819
National
Institute on Aging (NIA) RF1AG022018
National
Institute on Aging (NIA) R01AG056405
National
Institute on Aging (NIA) P30AG010161
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