Abstract
Background: Before the apparent cognitive decline, subjects on the course of Alzheimer's disease (AD) can have significantly altered spontaneous brain activity, which could be potentially used for early diagnosis. As previous studies investigating local brain activity may suffer from the problem of cortical signal aliasing during volume-based analysis, we aimed to investigate the cortical functional alterations in the AD continuum using a surface-based approach.Methods: Based on biomarker profile “A/T,” we included 11 healthy controls (HC, A–T–), 22 preclinical AD (CU, A+T+), 33 prodromal AD (MCI, A+T+), and 20 AD with dementia (d-AD, A+T+) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The amplitude of low-frequency fluctuation (ALFF) method was used to evaluate the changes of spontaneous brain activity, which was performed in the classic frequency band (0.01–0.08 Hz), slow-4 (0.027–0.073 Hz) band, and slow-5 (0.01–0.027 Hz) band.Results: Under classic frequency band and slow-4 band, analysis of covariance (ANCOVA) showed that there were significant differences of standardized ALFF (zALFF) in the left posterior cingulate cortex (PCC) among the four groups. The post-hoc analyses showed that under the classic frequency band, the AD group had significantly decreased zALFF compared with the other three groups, and the cognitively unimpaired (CU) group had decreased zALFF compared with the healthy control (HC) group. Under the slow-4 band, more group differences were detected (HC > CU/MCI > d-AD). The accuracy of classifying CU, mild cognitive impairment (MCI), and AD from HC by left PCC activity under the slow-4 band were 0.774, 0.744, and 0.920, respectively. Moreover, the zALFF values of the left PCC had significant correlations with cerebrospinal fluid (CSF) biomarkers and neuropsychological tests.Conclusions: Spontaneous brain activity in the left PCC may decrease in preclinical AD when cognitive functions were relatively normal. The combination of a surfaced-based approach and specific frequency band analysis may increase sensitivity for the identification of preclinical AD subjects.
Highlights
Alzheimer’s disease (AD) is a major neurodegenerative disease in elderly adults that causes memory decline, executive function impairment, and dementia (Masters et al, 2015)
We reviewed the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database and selected subjects with complete information, such as cerebrospinal fluid (CSF) biomarkers, 3D T1-weighted (T1w) images, resting-state functional magnetic resonance imaging (rsfMRI) images, and neuropsychological tests at the same time point
CSF was collected into collection tubes or syringes provided to each site, transferred into polypropylene transfer tubes within an hour after collection followed by frozen on dry ice, and transported overnight on dry ice to the ADNI Biomarker Core laboratory at the University of Pennsylvania Medical Center
Summary
Alzheimer’s disease (AD) is a major neurodegenerative disease in elderly adults that causes memory decline, executive function impairment, and dementia (Masters et al, 2015). According to cognitive status, they could be further classified into three groups: preclinical AD (cognitively unimpaired, CU), prodromal AD (mild cognitive impairment, MCI), and AD with dementia (dementia, d-AD) (Jack et al, 2018), representing different stages of the disease. These criteria provide an important basis for exploring early brain manifestations of the disease and developing early imaging markers. Few studies divided the classic frequency band into several sub-bands and found that subjects within the AD continuum had frequencydependent brain alterations, suggesting the unique contribution of AD pathologies (Liu et al, 2020; Yang et al, 2020). As previous studies investigating local brain activity may suffer from the problem of cortical signal aliasing during volume-based analysis, we aimed to investigate the cortical functional alterations in the AD continuum using a surface-based approach
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