0399
Effects of transactive response DNA-binding protein 43 (TDP43) pathology on amygdala volume and shape, in a community cohort of older adults1Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, United States, 2Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, United States, 3Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, United States, 4Department of Pathology, Rush University Medical Center, Chicago, IL, United States, 5Department of Diagnostic Radiology, Rush University Medical Center, Chicago, IL, United States
Synopsis
TDP43 pathology is now recognized as a common and deleterious neuropathology of the aging brain. TDP43 pathology typically originates in the amygdala, which is, however, commonly affected by other age-related neurodegenerative pathologies. The purpose of this work was to investigate the effects of TDP43 pathology on the volume and shape of the amygdala in a large community cohort of older adults.
Purpose
Transactive response DNA-binding protein 43 (TDP43) pathology is the primary protein abnormality in the rare neurodegenerative diseases amyotrophic lateral sclerosis and frontotemporal lobar degeneration1. However, according to recent findings, TDP43 pathology is common in old age, with approximately 50% of older persons showing evidence of the pathology at autopsy2. TDP43 pathology has been reported in up to 55% of those with Alzheimer’s disease pathology3,4, 90% of hippocampal sclerosis cases5, 60% of Lewy body cases3, and in other neurodegenerative diseases6-15, yet has also been detected in normal older persons2. The effect of TDP43 pathology on cognition of older adults is devastating2,16,17. Thus, TDP43 pathology is now recognized as a common and deleterious neuropathology of the aging brain. TDP43 pathology typically originates in the amygdala18, which is, however, commonly affected by other age-related neurodegenerative pathologies19. The purpose of this work was to investigate the effects of TDP43 pathology on the volume and shape of the amygdala in a large community cohort of older adults.Methods
Cerebral hemispheres were obtained from 208 deceased participants of the Rush Memory and Aging Project20 and the Religious Orders Study21, two longitudinal, epidemiologic clinical-pathologic cohort studies of aging (Fig.1). Hemispheres were imaged ex-vivo on a 3T clinical MRI scanner, while immersed in 4% formaldehyde solution, using a 2D spin-echo sequence with multiple echo-times and 0.6 mm3 voxels. An experienced observer blinded to all clinical and pathologic findings manually segmented the amygdala on ex-vivo MR images (Fig.2). For each participant, the volume of the amygdala was measured and normalized by the height of the participant. Following ex-vivo MR imaging, hemispheres underwent neuropathologic examination by a board-certified neuropathologist blinded to all clinical and imaging findings (Fig.3). Multiple linear regression was used to investigate the association of amygdala volume with TDP43, Alzheimer’s pathology, hippocampal sclerosis, Lewy bodies, gross and microscopic infarcts, atherosclerosis, cerebral amyloid angiopathy, and arteriolosclerosis, controlling for age, sex, years of education, postmortem interval to fixation, and postmortem interval to imaging.
Shape analysis was also conducted using the spherical harmonic point distribution model (SPHARM- PDM) toolbox23. All left amygdalas were first mirrored to resemble right amygdalas, a 3D mesh model of the surface of the amygdala was generated for each participant, and an average mesh was calculated from the whole population. At every node on the amygdala surface of each participant, a distance vector from the corresponding node on the average mesh was calculated, which was then projected to the average surface normal vector to obtain a signed distance value. Multiple linear regression was then used to investigate the association of the signed distance value at each amygdala surface node with all neuropathologies and covariates considered in the volumetric analysis above. Statistical significance was set at p<0.05.
Results and Discussion
The normalized amygdala volume was negatively correlated with TDP43 (-25.5, p=0.006), Alzheimer’s pathology (-74.2, p<10-4), and hippocampal sclerosis (-92.0, p=0.0009), in multiple linear regression. This suggests that TDP43 has an independent contribution on atrophy of the amygdala above and beyond the contributions of Alzheimer’s pathology and hippocampal sclerosis. Shape analysis also demonstrated that the three pathologies are associated with atrophy of the amygdala (Fig.4). Furthermore, shape analysis showed that, although effects of TDP43 on the shape of the amygdala largely overlapped with those of hippocampal sclerosis, more differences existed between the effects of TDP43 and Alzheimer’s pathology (Fig.4). These findings suggest that neurodegeneration in the amygdala due to TDP43 pathology and hippocampal sclerosis may be sharing some common neurobiological mechanisms, while the effects of TDP43 and Alzheimer’s pathology may have somewhat different underlying mechanisms.Conclusion
This work in a community cohort of older adults demonstrated that TDP43 pathology is associated with atrophy of the amygdala, seen in both volumetric and shape analyses. The similarities observed between the effects of TDP43 and hippocampal sclerosis on the shape of the amygdala are intriguing considering the fact that 90% of hippocampal sclerosis cases also suffer by TDP435. The differences observed between the effects of TDP43 and Alzheimer’s pathology on the shape of the amygdala may be exploited towards the development of tools for distinguishing persons with only Alzheimer’s pathology from those with both Alzheimer’s and TDP43.Acknowledgements
National Institute of Neurological Disorders and Stroke (NINDS) UH2NS100599
National Institute on Aging (NIA) R01AG017917
National Institute on Aging (NIA) P30AG010161
National Institute on Aging (NIA) R01AG034374
National Institute on Aging (NIA) R01AG042210
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