Bundle-wise functional connectivity density and fractional amplitude of low-frequency fluctuations decrease in white matter in preclinical Alzheimer's disease and are associated with Aβ levels and cognition.
Yukie Chang, Lyuan Xu, Chenyu Gao, Nazirah Mohd Khairi, John C Gore, Bennett A Landman, Yurui Gao
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引用次数: 0
Abstract
Neurophysiological changes associated with Alzheimer's disease (AD) begin decades before clinical symptoms emerge, during preclinical AD. Functional abnormalities in white matter (WM) at this preclinical stage remain largely unexplored. We obtained resting-state functional magnetic resonance imaging (rs-fMRI) data of 295 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and evaluated bundle-wise functional connectivity density (FCD) and fractional amplitude of low-frequency fluctuations (fALFF) across 46 bundles, which reflects the strength of synchronizations of BOLD dynamics between each WM bundle and whole-brain 200 GM parcels, and spontaneous neural activity of each WM bundle, respectively. To mitigate site/scanner effects on the metrics, ComBat harmonization was applied to the data. We then performed permutation tests (n=5,000) on each harmonized metric for each bundle to determine differences in FCD and fALFF in preclinical AD relative to controls, adjusting for sex, age, and education using multiple linear regression. Linear correlations of the metrics with the pathological biomarker beta-amyloid (Aβ) and cognitive scores (mPACC and ADAS11) were assessed using general linear models. Multiple comparisons were corrected via a false discovery rate (FDR). We found that preclinical AD patients had reduced FCD and fALFF in specific WM bundles, such as cingulate and hippocampal cingulum, compared to controls (FDR corrected p < 0.05), some of which were associated with poorer cognitive performance and greater Aβ accumulation (FDR corrected p < 0.05). This study, to the best of our knowledge, is the first to examine bundle-wise FCD and fALFF of WM in preclinical AD using a large-scale, multi-site, cross-sectional dataset, suggesting potential applications of these metrics for assessing preclinical AD with rs-fMRI.