Introduction

Brain arteriolosclerosis is characterized by thickening of vessel walls and arteriolar stenosis and is one of the primary pathologies of cerebral small vessel disease¹. It has a higher occurrence among older adults and is more severe in women² and black individuals³. Arteriolosclerosis is linked to lower cognitive and motor function⁴, as well as an elevated risk of dementia⁵. Despite its prevalence and deleterious effects, the impact of arteriolosclerosis on brain macrostructure has not been investigated. Therefore, the aim of this study was to investigate the association of brain arteriolosclerosis with regional gray matter volumes in a large number of community-based older adults.

Methods

Participants, MRI, neuropathology

Ex-vivo MRI and detailed neuropathological evaluation were combined in 882 older adults participating in four longitudinal, clinical-pathologic cohort studies of aging^6,7: Rush Memory and Aging Project (MAP), Religious Orders Study (ROS), Minority Aging Research Study (MARS), and Clinical Core (CC) of the Rush Alzheimer’s Disease Research Center (Fig.1). Cerebral hemispheres from all participants were obtained at autopsy and imaged ex-vivo with a multi-echo spin-echo (ME-SE) sequence on 3T clinical MRI scanners approximately one month postmortem⁸. The acquired voxel size was 0.6mm × 0.6mm × 1.5mm, and the scan time was approximately 30 minutes⁸. Gray and white matter were segmented in the ex-vivo MRI data, and gray matter was further divided into 42 cortical and subcortical regions using multi-atlas segmentation⁹. The volume of each region was measured and normalized by the participant’s cerebral hemisphere volume¹⁰. Following ex-vivo MRI, all hemispheres underwent detailed neuropathologic examination. The assessed pathologies included arteriolosclerosis¹¹, atherosclerosis, 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 (Fig. 2).

Statistical analysis

Linear regression was used to investigate the association of brain arteriolosclerosis with regional gray matter volumes (normalized by cerebral hemisphere volume) controlling for all other neuropathologies (Fig. 2), demographics (age at death, sex, years of education), postmortem intervals, and scanner (Fig. 1). Statistical analysis was conducted using FSL’s PALM tool, with 10,000 permutations¹². After correcting for multiple testing using the false discovery rate (FDR), significance was set at p<0.05.

Results & Discussion

More severe brain arteriolosclerosis was associated with lower volume in a number of gray matter regions, including medial orbitofrontal, superior frontal, pericalcarine, cuneus, and lateral occipital areas, independently of the effects of other neuropathologies (Figs. 3,4). No regions showed higher volume with more severe arteriolosclerosis. These findings substantially expand our understanding of arteriolosclerosis-related brain anomalies since, so far, arteriolosclerosis was known to be associated mainly with white matter hyperintensities⁸. The present work in a large number of community-based older adults provides strong evidence that arteriolosclerosis is also related to neurodegenerative changes in gray matter. Furthermore, the brain regions involved are distributed in both anterior and posterior parts of the brain in line with the more widespread distribution of arteriolosclerosis pathology in the brain.

Conclusion

The present work combined ex-vivo MRI and detailed neuropathological examination in a large number of community-based older adults and demonstrated that brain arteriolosclerosis is associated with lower volume in multiple gray matter regions independently of the effects of other vascular or neurodegenerative pathologies. This link between one of the main small vessel disease pathologies with neurodegeneration in gray matter is a novel finding that enhances our understanding of the impact of arteriolosclerosis on the brain. Finally, the regional volumes that are linked to arteriolosclerosis may be used as additional features in ARTS¹³, a recently-developed in-vivo marker of arteriolosclerosis, which may enhance its performance in predicting the pathology in-vivo.

References

1. Blevins BL, Vinters HV, Love S, et al. Brain arteriolosclerosis. Acta Neuropathol (Berl). 2021;141(1):1-24.
2. Oveisgharan S, Arvanitakis Z, Yu L, Farfel J, Schneider JA, Bennett DA. Sex differences in Alzheimer’s disease and common neuropathologies of aging. Acta Neuropathol (Berl). 2018;136(6):887-900.
3. Barnes LL, Leurgans S, Aggarwal NT, et al. Mixed pathology is more likely in black than white decedents with Alzheimer dementia. Neurology. 2015;85(6):528-534.
4. Buchman AS, Yu L, Boyle PA, et al. Microvascular brain pathology and late-life motor impairment. Neurology. 2013;80(8):712-718.
5. Arvanitakis Z, Capuano AW, Leurgans SE, Bennett DA, Schneider JA. Relation of cerebral vessel disease to Alzheimer’s disease dementia and cognitive function in elderly people: a cross-sectional study. Lancet Neurol. 2016;15(9):934-943.
6. Bennett DA, Buchman AS, Boyle PA, Barnes LL, Wilson RS, Schneider JA. Religious Orders Study and Rush Memory and Aging Project. Perry G, Avila J, Moreira PI, Sorensen AA, Tabaton M, eds. J Alzheimers Dis. 2018;64(s1):S161-S189.
7. L. Barnes L, C. Shah R, T. Aggarwal N, A. Bennett D, A. Schneider J. The Minority Aging Research Study: Ongoing Efforts to Obtain Brain Donation in African Americans without Dementia. Curr Alzheimer Res. 2012;9(6):734-745.
8. Arfanakis K, Evia AM, Leurgans SE, et al. Neuropathologic Correlates of White Matter Hyperintensities in a Community-Based Cohort of Older Adults. Flanagan M, ed. J Alzheimers Dis. 2020;73(1):333-345.
9. Kotrotsou A, Bennett DA, Schneider JA, et al. Ex vivo MR volumetry of human brain hemispheres. Magn Reson Med. 2014;71(1):364-374.
10. Dawe RJ, Bennett DA, Schneider JA, Arfanakis K. Neuropathologic Correlates of Hippocampal Atrophy in the Elderly: A Clinical, Pathologic, Postmortem MRI Study. Pant H, ed. PLoS ONE. 2011;6(10):e26286.
11. Buchman AS, Leurgans SE, Nag S, Bennett DA, Schneider JA. Cerebrovascular Disease Pathology and Parkinsonian Signs in Old Age. Stroke. 2011;42(11):3183-3189.
12. Winkler AM, Ridgway GR, Webster MA, Smith SM, Nichols TE. Permutation inference for the general linear model. NeuroImage. 2014;92:381-397.
13. Makkinejad N, Evia AM, Tamhane AA, et al. ARTS: A novel In-vivo classifier of arteriolosclerosis for the older adult brain. NeuroImage Clin. 2021;31:102768.
14. Wu Y, Ridwan AR, Niaz MR, Bennett DA, Arfanakis K. High resolution 0.5mm isotropic T1-weighted and diffusion tensor templates of the brain of non-demented older adults in a common space for the MIITRA atlas. NeuroImage. 2023;282:120387.