scholarly journals P4-289: BOLD SIGNAL VARIABILITY CHANGES IN THE DEFAULT MODE AND SALIENCE NETWORKS IN AMNESTIC MILD COGNITIVE IMPAIRMENT AND ALZHEIMER'S DISEASE AND THEIR ASSOCIATIONS WITH COGNITIVE DECLINE

2019 ◽  
Vol 15 ◽  
pp. P1398-P1399
Author(s):  
Liwen Zhang ◽  
Xinian Zuo ◽  
Kwun Kei Ng ◽  
Joanna Su Xian Chong ◽  
Hee Youn Shim ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Decline ◽  
Amnestic Mild Cognitive Impairment ◽  
Bold Signal ◽  
Default Mode ◽  
Signal Variability

scholarly journals A Metallomic Approach to Assess the Associations between Plasma Metal Levels with Amnestic Mild Cognitive Impairment and Alzheimer’s Disease: A Cross-sectional and Longitudinal Study

2021 ◽  
Author(s):  
Yu-Kai Lin ◽  
Chih-Sung Liang ◽  
Chia-Kuang Tsai ◽  
Chia-Lin Tsai ◽  
Jiunn-Tay Lee ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Trace Elements ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Decline ◽  
Amnestic Mild Cognitive Impairment ◽  
Cognitive Tests ◽  
Metal Levels ◽  
Baseline Levels

Abstract BACKGROUND Alzheimer’s disease (AD) involves the abnormal activity of transition metals and metal ion dyshomeostasis. The present study aimed to assess the potential of 36 trace elements in predicting cognitive decline in patients with amnestic mild cognitive impairment (aMCI) or AD. METHODS All participants (controls, aMCI, and AD) underwent baseline cognitive tests, which included the Mini-Mental State Examination (MMSE) and plasma biomarker examinations. We conducted a trend analysis for the cognitive tests and plasma trace elements and examined the correlations between the latter and annual MMSE changes during follow-up. RESULTS An increase in the disease severity was linked to lowered boron (B), bismuth (Bi), thorium (Th), and uranium (U) plasma concentrations (adjusted P < 0.05). “B”, mercury (Hg) and “Th” levels could detect different cognitive stages. “B” displayed high area under the receiver operating characteristic curves (AUCs) for aMCI and AD versus controls (97.6%, cut-off value: ≤73.1 ug/l and 100%, cut-off value: ≤47.1 ug/l, respectively). “Hg” displayed the highest AUC result to differentiate AD from aMCI (79.9%, cut-off value: ≤1.02 ug/l). Higher baseline levels of calcium (r = 0.50, p = 0.026) were associated with less annual cognitive decline. While higher baseline levels of “B” (r=-0.70, p = 0.001), zirconium (r=-0.58, p = 0.007), “Th” (r=-0.52, p = 0.020) were associated with rapid annual cognitive decline in the aMCI group, those of manganese (r=-0.91, p = 0.035) were associated with rapid annual cognitive decline in the AD group. CONCLUSION Plasma metal level biomarkers can be used as an in vivo tool to study and identify patients with aMCI and AD.

scholarly journals Divergent Connectivity Changes in Gray Matter Structural Covariance Networks in Subjective Cognitive Decline, Amnestic Mild Cognitive Impairment, and Alzheimer’s Disease

2021 ◽  
Vol 13 ◽  
Author(s):  
Zhenrong Fu ◽  
Mingyan Zhao ◽  
Yirong He ◽  
Xuetong Wang ◽  
Jiadong Lu ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Decline ◽  
Gray Matter ◽  
Amnestic Mild Cognitive Impairment ◽  
Subjective Cognitive Decline ◽  
Structural Covariance ◽  
Cholinergic Basal Forebrain

Alzheimer’s disease (AD) has a long preclinical stage that can last for decades prior to progressing toward amnestic mild cognitive impairment (aMCI) and/or dementia. Subjective cognitive decline (SCD) is characterized by self-experienced memory decline without any evidence of objective cognitive decline and is regarded as the later stage of preclinical AD. It has been reported that the changes in structural covariance patterns are affected by AD pathology in the patients with AD and aMCI within the specific large-scale brain networks. However, the changes in structural covariance patterns including normal control (NC), SCD, aMCI, and AD are still poorly understood. In this study, we recruited 42 NCs, 35 individuals with SCD, 43 patients with aMCI, and 41 patients with AD. Gray matter (GM) volumes were extracted from 10 readily identifiable regions of interest involved in high-order cognitive function and AD-related dysfunctional structures. The volume values were used to predict the regional densities in the whole brain by using voxel-based statistical and multiple linear regression models. Decreased structural covariance and weakened connectivity strength were observed in individuals with SCD compared with NCs. Structural covariance networks (SCNs) seeding from the default mode network (DMN), salience network, subfields of the hippocampus, and cholinergic basal forebrain showed increased structural covariance at the early stage of AD (referring to aMCI) and decreased structural covariance at the dementia stage (referring to AD). Moreover, the SCN seeding from the executive control network (ECN) showed a linearly increased extent of the structural covariance during the early and dementia stages. The results suggest that changes in structural covariance patterns as the order of NC-SCD-aMCI-AD are divergent and dynamic, and support the structural disconnection hypothesis in individuals with SCD.

scholarly journals Resting-state functional reorganisation in Alzheimer’s disease and amnestic mild cognitive impairment: protocol for a systematic review and meta-analysis

BMJ Open ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. e049798
Author(s):  
Diyang Lyu ◽  
Taoran Li ◽  
Xuanxin Lyu
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Decline ◽  
Resting State ◽  
Assessment Tool ◽  
Brain Regions ◽  
Amnestic Mild Cognitive Impairment ◽  
Subjective Cognitive Decline

IntroductionThe incidence of Alzheimer’s disease (AD) is increasing rapidly, causing a growing burden to health and economic worldwide. Several clinical trials in the past decade failed to find solutions, and there remains a lack of an effective treatment. The evidence suggests that early intervention for neurodegeneration would likely be effective in preventing cognitive decline. Cognitive decline in AD occurs continuously over a long period; however, there remains a lack of simple, rapid and accurate approach for diagnosis of amnestic mild cognitive impairment or subjective cognitive decline due to underlying Alzheimer’s pathology. Resting-state functional MRI (rs-fMRI) determines the functional activities of the human brain non-invasively. The amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF) and regional homogeneity (ReHo) are rs-fMRI indicators with high repeatability. They have been studied as early diagnostic imaging markers for other diseases and may be promising markers also for AD.Methods and analysisThe following electronic literature databases will be searched from inception to December 2021: Medline-Ovid, Medline-PubMed, EMBase-Ovid, Cochrane Central and ClinicalTrials.gov. Two independent reviewers will select studies with eligible criteria, extract data and assess the quality of the original studies with our quality assessment tool individually. Missing data will be requested by sending emails to the corresponding authors. Brain regions will be presented for ALFF/fALFF and ReHo by performing activation likelihood estimation with the Seed-based d Mapping-Permutation of subject images V.6.21 software. Meta-regression will be performed to determine the potential brain regions that may strongly correlate with cognitive decline progression. Subgroup analysis, funnel plot, Egger’s test and sensitivity analysis will be conducted to detect and explain potential heterogeneity.Ethics and disseminationThis study does not require formal ethical approval. The findings will be submitted to a peer-review journal.PROSPERO registration numberCRD42021229009.

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