Synopsis

Keywords: Dementia, Vessels, Alzheimer's disease, Aging, Hypertension

Brain arteriolosclerosis is one of the main pathologies of cerebral small vessel disease, is common in older adults, and is associated with lower cognitive and motor function and higher odds of dementia. This work combined in-vivo MRI and pathology in a community-cohort of older adults to investigate the independent association of brain arteriolosclerosis with diffusion abnormalities in white matter. Brain arteriolosclerosis was shown to be associated with lower FA and higher trace of the diffusion tensor that extended throughout white matter, and these associations were independent of the effects of other neuropathologies or white matter hyperintensities.

Introduction

Brain arteriolosclerosis is one of the main pathologies of cerebral small vessel disease and involves thickening of the vessel wall and stenosis of arterioles¹. Arteriolosclerosis is common in older adults and is more severe in women² and black older adults³. It is associated with lower cognitive and motor function⁴, and higher odds of dementia⁵. Arteriolosclerosis is strongly associated with white matter hyperintensities (WMH) in the brain⁶. However, the association of arteriolosclerosis with anomalies in the diffusion properties of white matter above and beyond the effects of visible WMH has not been studied. Therefore, the aim of this work was to investigate the independent association of brain arteriolosclerosis with diffusion abnormalities in white matter of community-based older adults.

Methods

Participants, MRI, neuropathology
Community-dwelling older adults (N=175) participating in four longitudinal cohort studies of aging^7,8 (Rush Memory and Aging Project, Religious Orders Study, Minority Aging Research Study, and Clinical Core of the Rush Alzheimer’s Disease Research Center) were included in this work (Fig.1). Whole brain 3D T1w MPRAGE (1×1×1mm³), T2w FLAIR (0.9×0.9×4mm³), and diffusion-weighted MRI (2×2×2mm³, b=1,000s/mm² for 40 diffusion gradient directions, and 6 b=0s/mm₂ volumes) data were acquired in-vivo on all participants using 3T MRI scanners. The intracranial space was segmented on the MRPAGE images using CAT12⁹ and the intracranial volume was calculated. WMH were automatically segmented based on MPRAGE and FLAIR information¹⁰. The total volume of WMH was normalized with the intracranial volume, multiplied by 100 and converted by the logarithm base 10 to make it more normally distributed. TORTOISE was used on the diffusion data to correct eddy-current distortions and bulk-motion, reorient the B-matrix, calculate diffusion tensors, and generate maps of fractional anisotropy (FA) and trace of the diffusion tensor¹¹. The FA and trace maps were transformed to the space of the IIT Human Brain Atlas v.5.0¹² using tensor-based registration (DR-TAMAS)¹³, and white matter FA and trace information was projected onto the white matter skeleton of the IIT atlas¹⁴. Participants died at an average of 3 years after in-vivo MRI (Fig.1). Following a participant’s death, the brain was extracted and underwent detailed neuropathologic evaluation by a board-certified neuropathologist (Fig.2). Severity of arteriolosclerosis was summarized in 4 levels (0-none, 1-mild, 2-moderate, and 3-severe)¹⁵. Other neuropathologies that were assessed included: Alzheimer's pathology, Lewy bodies, limbic-predominant age-related TDP-43 encephalopathy neuropathological change (LATE-NC), gross and microscopic infarcts, atherosclerosis, and cerebral amyloid angiopathy.

Statistical analysis
Linear regression was used in voxels of the white matter skeleton to test the association of FA or trace with the severity of arteriolosclerosis controlling for all other neuropathologies, WMH, demographic variables (age at MRI, sex, years of education), antemortem interval, and scanner. The statistical analyses were carried out using FSL’s PALM tool with 5,000 permutations and threshold-free cluster enhancement¹⁶. The significance level was set at p<0.05, after family-wise error rate (FWER) correction for multiple testing.

Results

Arteriolosclerosis score was associated with lower FA and higher trace of the diffusion tensor in multiple white matter regions throughout the brain (Figs.3,4). These associations were independent of other neuropathologies or the effects of WMH on diffusion properties and were present even in white matter regions that are commonly free of WMH.

Discussion

This study demonstrated that brain arteriolosclerosis in older adults is linked to diffusion abnormalities that extend throughout white matter, independently of the effects of other neuropathologies or visible WMH. These findings enhance our understanding of the mechanisms through which arteriolosclerosis impacts the older adult brain. Additionally, this study suggests that by adding diffusion properties such as mean diffusivity to ARTS¹⁷, a recently introduced marker of arteriolosclerosis, we may be able to further increase its performance in predicting arteriolosclerosis in-vivo. The strengths of the present work include a) short antemortem intervals reducing the possibility of additional pathologies developing after in-vivo MRI, b) detailed neuropathology which allows for a better control for the effects of comorbid pathologies, c) a community cohort which enhances generalizability of findings, and d) good quality neuroimaging data and careful image processing.

Conclusion

The present work demonstrated that brain arteriolosclerosis in older adults is linked to diffusion abnormalities that extend throughout white matter, independently of the effects of other neuropathologies or visible WMH. These findings enhance our understanding of the impact of arteriolosclerosis on the older adult brain, and may aid in improving the performance of available in-vivo markers of arteriolosclerosis such as ARTS¹⁷.

Acknowledgements

This study was supported by the following grants:

National Institute on Aging (NIA): R01AG064233, R01AG067482, R01AG017917, R01AG015819, RF1AG022018, R01AG056405, R01AG052200, P30AG010161, P30AG072975

National Institute of Neurological Disorders and Stroke (NINDS): UH2-UH3NS100599, UF1NS100599, R21NS076827

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