Abstract
Alzheimer’s disease (AD) is a progressive neurodegenerative disease, for which aging remains the major risk factor. Aging is under a consistent pressure of increasing brain entropy (BEN) due to the progressive brain deteriorations. Noticeably, the brain constantly consumes a large amount of energy to maintain its functional integrity, likely creating or maintaining a big “reserve” to counteract the high entropy. Malfunctions of this latent reserve may indicate a critical point of disease progression. The purpose of this study was to characterize BEN in aging and AD and to test an inverse-U-shape BEN model: BEN increases with age and AD pathology in normal aging but decreases in the AD continuum. BEN was measured with resting state fMRI and compared across aging and the AD continuum. Associations of BEN with age, education, clinical symptoms, and pathology were examined by multiple regression. The analysis results highlighted resting BEN in the default mode network, medial temporal lobe, and prefrontal cortex and showed that: (1) BEN increased with age and pathological deposition in normal aging but decreased with age and pathological deposition in the AD continuum; (2) AD showed catastrophic BEN reduction, which was related to more severe cognitive impairment and daily function disability; and (3) BEN decreased with education years in normal aging, but not in the AD continuum. BEN evolution follows an inverse-U trajectory when AD progresses from normal aging to AD dementia. Education is beneficial for suppressing the entropy increase potency in normal aging.
Highlights
Alzheimer’s disease (AD) is a neurodegenerative disease that has impacted millions of elderly people but still remains incurable (Ferri et al, 2005; Reitz and Mayeux, 2014)
In a pilot study (Wang, 2020a,b; full article under separate review) based on data from 862 healthy adults from the human connectome project (Van Essen et al, 2013), we found that brain entropy (BEN) in the default mode network (DMN) and the executive control network (ECN; including the dorsolateral prefrontal cortex and lateral parietal cortex) increases with age but decreases with education years and that lower BEN in DMN and ECN is associated with better performance of cognitive functions
The inverse-U shape model was evaluated by comparing BEN across normal aging and patients with different stages of disease in the AD continuum as well as by the neurobehavioral and pathological association analyses
Summary
Alzheimer’s disease (AD) is a neurodegenerative disease that has impacted millions of elderly people but still remains incurable (Ferri et al, 2005; Reitz and Mayeux, 2014). AD has been well characterized by AD pathology and clinical symptoms, a major barrier to research progress is the unclear mechanism for how and when normal aging progresses into AD dementia (Kumar and Singh, 2015; Mehta and Yeo, 2017) and why AD symptoms often emerge many years later than AD pathology This pathology vs symptom discrepancy (Jack et al, 2010; Jack and Holtzman, 2013) suggests that there may exist a reserve of brain function according to the seminal ‘‘cognitive reserve’’ (CR; Stern, 2006; Stern et al, 2018) model. One candidate is the resting-state brain activity which matches the latent function reserve in two perspectives: first, it is an ongoing process
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