Intracranial atherosclerosis is linked to lower volume in hippocampal posterior body and tail.
Poster No:
166
Submission Type:
Abstract Submission
Authors:
Gulam Mahfuz Chowdhury1, Mahir Tazwar1, Arnold Evia2, Alifiya Kapasi2, Sonal Agrawal2, David Bennett2, Julie Schneider2, Konstantinos Arfanakis1,2
Institutions:
1Illinois Institute of Technology, Chicago, IL, 2Rush University Medical Center, Chicago, IL
First Author:
Co-Author(s):
Konstantinos Arfanakis
Illinois Institute of Technology|Rush University Medical Center
Chicago, IL|Chicago, IL
Illinois Institute of Technology|Rush University Medical Center
Chicago, IL|Chicago, IL
Introduction:
Intracranial atherosclerosis is a common age-related neuropathology that has been linked to cognitive decline and dementia[1–3]. Intracranial atherosclerosis is often mixed with Alzheimer's and other neuropathologies increasing the odds of dementia[4]. Despite its prevalence, its negative impact on cognitive function and its role in aging and dementia, the association of atherosclerosis with brain morphometric abnormalities has not been explored. Deformation-based morphometry (DBM) is an approach that allows investigation of brain morphometry at the voxel level[5]. Here, we combined DBM on ex-vivo MRI with detailed neuropathological examination in a large number of community-based older adults to investigate the association of intracranial atherosclerosis with brain morphometric anomalies.
Methods:
Participants, MRI, neuropathologic examination:
This work included 891 community-based older adults participating in four cohort studies of aging: the Rush Memory and Aging Project, Religious Orders Study[6], Minority Aging Research Study, and African American Clinical Core of the Rush Alzheimer's Disease Research Center[7]. All participants came to autopsy. Hemispheres from all participants were submerged in 4% formaldehyde solution and imaged approximately one month postmortem on 3T clinical MRI scanners using a multi-echo spin-echo sequence with a voxel size=0.6×0.6×1.5 mm3. All images were non-linearly registered to an ex vivo brain hemisphere template using ANTs[8]. The logarithm of the Jacobian determinant of the deformation fields was calculated in each voxel and the resulting maps(LogJ) were smoothed using a Gaussian filter with a FWHM=4mm. Following ex-vivo MRI, all hemispheres underwent detailed neuropathologic examination. The assessed pathologies included atherosclerosis, arteriolosclerosis, cerebral amyloid angiopathy, gross and microscopic infarcts, Alzheimer's pathology, Lewy bodies, limbic-predominant age-related TDP-43 encephalopathy neuropathological change(LATE-NC), and hippocampal sclerosis.
Statistical Analyses:
Voxel wise linear regression was used to test the association of atherosclerosis with deformations shown in the smoothed LogJ maps, controlling for other age-related neuropathologies(Alzheimer's pathology, Lewy bodies, limbic-predominant age-related TDP-43 encephalopathy(LATE), hippocampal sclerosis, arteriolosclerosis, cerebral amyloid angiopathy, gross infarcts, microscopic infarcts), demographics(age at death, sex, years of education), postmortem interval to fixation, postmortem interval to imaging, and scanner(Fig.1). The FSL PALM tool with 1000 permutations, threshold-free cluster enhancement, and tail acceleration was used for the statistical analysis[9]. Associations were considered significant at p<0.05 after family-wise error rate(FWER) correction for multiple comparisons.
This work included 891 community-based older adults participating in four cohort studies of aging: the Rush Memory and Aging Project, Religious Orders Study[6], Minority Aging Research Study, and African American Clinical Core of the Rush Alzheimer's Disease Research Center[7]. All participants came to autopsy. Hemispheres from all participants were submerged in 4% formaldehyde solution and imaged approximately one month postmortem on 3T clinical MRI scanners using a multi-echo spin-echo sequence with a voxel size=0.6×0.6×1.5 mm3. All images were non-linearly registered to an ex vivo brain hemisphere template using ANTs[8]. The logarithm of the Jacobian determinant of the deformation fields was calculated in each voxel and the resulting maps(LogJ) were smoothed using a Gaussian filter with a FWHM=4mm. Following ex-vivo MRI, all hemispheres underwent detailed neuropathologic examination. The assessed pathologies included atherosclerosis, arteriolosclerosis, cerebral amyloid angiopathy, gross and microscopic infarcts, Alzheimer's pathology, Lewy bodies, limbic-predominant age-related TDP-43 encephalopathy neuropathological change(LATE-NC), and hippocampal sclerosis.
Statistical Analyses:
Voxel wise linear regression was used to test the association of atherosclerosis with deformations shown in the smoothed LogJ maps, controlling for other age-related neuropathologies(Alzheimer's pathology, Lewy bodies, limbic-predominant age-related TDP-43 encephalopathy(LATE), hippocampal sclerosis, arteriolosclerosis, cerebral amyloid angiopathy, gross infarcts, microscopic infarcts), demographics(age at death, sex, years of education), postmortem interval to fixation, postmortem interval to imaging, and scanner(Fig.1). The FSL PALM tool with 1000 permutations, threshold-free cluster enhancement, and tail acceleration was used for the statistical analysis[9]. Associations were considered significant at p<0.05 after family-wise error rate(FWER) correction for multiple comparisons.
·Fig.1
Results:
Voxel-wise linear regression showed that intracranial atherosclerosis was significantly associated with lower volume in the posterior body and tail of the hippocampus(p<0.05), independently of the effects of other age-related neurodegenerative and vascular pathologies(Fig.2). No part of the brain showed significantly higher volume with atherosclerosis. This suggests that intracranial atherosclerosis is associated with focal neurodegeneration of the posterior portion of the hippocampus, sparing other brain tissues.
·Fig.2
Conclusions:
This work combined DBM on ex-vivo MRI with detailed neuropathologic examination in a large number of community-based older adults and demonstrated that intracranial atherosclerosis is associated with lower volume of the posterior body and tail of the hippocampus. Atherosclerosis is often mixed with Alzheimer's pathology and/or LATE neuropathological change, which have previously shown independent associations with lower hippocampal volume. Hippocampal volume by itself cannot serve as a reliable marker of any of the three pathologies, but more localized metrics of hippocampal atrophy may potentially provide higher specificity.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Lifespan Development:
Aging 2
Keywords:
Other - Blood vessels; Atherosclerosis; Brain; Pathology; Ex-vivo applications; Hippocampus; Neurodegeneration; Vascular
1|2Indicates the priority used for review
Provide references using author date format
2. Avants, Brian B., Nicholas J. Tustison, Gang Song, Philip A. Cook, Arno Klein, and James C. Gee. 2011. “A Reproducible Evaluation of ANTs Similarity Metric Performance in Brain Image Registration.” NeuroImage 54 (3): 2033–44.
3. Barnes, Lisa L., Raj C. Shah, Neelum T. Aggarwal, David A. Bennett, and Julie A. Schneider. 2012. “The Minority Aging Research Study: Ongoing Efforts to Obtain Brain Donation in African Americans without Dementia.” Current Alzheimer Research 9 (6): 734–45.
4. Bennett, David A., Aron S. Buchman, Patricia A. Boyle, Lisa L. Barnes, Robert S. Wilson, and Julie A. Schneider. 2018. “Religious Orders Study and Rush Memory and Aging Project.” Journal of Alzheimer’s Disease: JAD 64 (s1): S161–89.
5. Dearborn, Jennifer L., Yiyi Zhang, Ye Qiao, Muhammad Fareed K. Suri, Li Liu, Rebecca F. Gottesman, Andreea M. Rawlings, et al. 2017. “Intracranial Atherosclerosis and Dementia: The Atherosclerosis Risk in Communities (ARIC) Study.” Neurology 88 (16): 1556–63.
6. Gaser, C., I. Nenadic, B. R. Buchsbaum, E. A. Hazlett, and M. S. Buchsbaum. 2001. “Deformation-Based Morphometry and Its Relation to Conventional Volumetry of Brain Lateral Ventricles in MRI.” NeuroImage 13 (6 Pt 1): 1140–45.
7. Gorelick, Philip B., Angelo Scuteri, Sandra E. Black, Charles Decarli, Steven M. Greenberg, Costantino Iadecola, Lenore J. Launer, et al. 2011. “Vascular Contributions to Cognitive Impairment and Dementia: A Statement for Healthcare Professionals from the American Heart Association/American Stroke Association.” Stroke 42 (9): 2672–2713.
8. Kapasi, Alifiya, Charles DeCarli, and Julie A. Schneider. 2017. “Impact of Multiple Pathologies on the Threshold for Clinically Overt Dementia.” Acta Neuropathologica 134 (2): 171–86.
9. Winkler, Anderson M., Gerard R. Ridgway, Matthew A. Webster, Stephen M. Smith, and Thomas E. Nichols. 2014. “Permutation Inference for the General Linear Model.” NeuroImage 92 (100): 381–97.