scholarly journals Altered Frequency-Dependent Brain Activation and White Matter Integrity Associated With Cognition in Characterizing Preclinical Alzheimer’s Disease Stages

2021 ◽  
Vol 15 ◽  
Author(s):  
Siyu Wang ◽  
Jiang Rao ◽  
Yingying Yue ◽  
Chen Xue ◽  
Guanjie Hu ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
White Matter ◽  
Cognitive Decline ◽  
Brain Activation ◽  
Amnestic Mild Cognitive Impairment ◽  
White Matter Integrity ◽  
Correlation Analyses ◽  
Preclinical Ad

BackgroundSubjective cognitive decline (SCD), non-amnestic mild cognitive impairment (naMCI), and amnestic mild cognitive impairment (aMCI) are regarded to be at high risk of converting to Alzheimer’s disease (AD). Amplitude of low-frequency fluctuations (ALFF) can reflect functional deterioration while diffusion tensor imaging (DTI) is capable of detecting white matter integrity. Our study aimed to investigate the structural and functional alterations to further reveal convergence and divergence among SCD, naMCI, and aMCI and how these contribute to cognitive deterioration.MethodsWe analyzed ALFF under slow-4 (0.027–0.073 Hz) and slow-5 (0.01–0.027 Hz) bands and white matter fiber integrity among normal controls (CN), SCD, naMCI, and aMCI groups. Correlation analyses were further utilized among paired DTI alteration, ALFF deterioration, and cognitive decline.ResultsFor ALFF calculation, ascended ALFF values were detected in the lingual gyrus (LING) and superior frontal gyrus (SFG) within SCD and naMCI patients, respectively. Descended ALFF values were presented mainly in the LING, SFG, middle frontal gyrus, and precuneus in aMCI patients compared to CN, SCD, and naMCI groups. For DTI analyses, white matter alterations were detected within the uncinate fasciculus (UF) in aMCI patients and within the superior longitudinal fasciculus (SLF) in naMCI patients. SCD patients presented alterations in both fasciculi. Correlation analyses revealed that the majority of these structural and functional alterations were associated with complicated cognitive decline. Besides, UF alterations were correlated with ALFF deterioration in the SFG within aMCI patients.ConclusionsSCD shares structurally and functionally deteriorative characteristics with aMCI and naMCI, and tends to convert to either of them. Furthermore, abnormalities in white matter fibers may be the structural basis of abnormal brain activation in preclinical AD stages. Combined together, it suggests that structural and functional integration may characterize the preclinical AD progression.

Early Microstructure Changes of White Matter Fiber Bundles in Patients with Amnestic Mild Cognitive Impairment Predicts Progression of Mild Cognitive Impairment to Alzheimer’s Disease

2021 ◽  
pp. 1-14
Author(s):  
Fangmei He ◽  
Yuchen Zhang ◽  
Xiaofeng Wu ◽  
Youjun Li ◽  
Jie Zhao ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
White Matter ◽  
Brain Regions ◽  
Amnestic Mild Cognitive Impairment ◽  
Microstructure Changes ◽  
Disease Trajectory ◽  
Development Trajectory ◽  
The Right

Background: Amnestic mild cognitive impairment (aMCI) is the transitional stage between normal aging and Alzheimer’s disease (AD). Some aMCI patients will progress into AD eventually, whereas others will not. If the trajectory of aMCI can be predicted, it would enable early diagnosis and early therapy of AD. Objective: To explore the development trajectory of aMCI patients, we used diffusion tensor imaging to analyze the white matter microstructure changes of patients with different trajectories of aMCI. Methods: We included three groups of subjects:1) aMCI patients who convert to AD (MCI-P); 2) aMCI patients who remain in MCI status (MCI-S); 3) normal controls (NC). We analyzed the fractional anisotropy and mean diffusion rate of brain regions, and we adopted logistic binomial regression model to predicate the development trajectory of aMCI. Results: The fraction anisotropy value is significantly reduced, the mean diffusivity value is significantly increased in the two aMCI patient groups, and the MCI-P patients presented greater changes. Significant changes are mainly located in the cingulum, fornix, hippocampus, and uncinate fasciculus. These changed brain regions significantly correlated with the patient’s Mini-Mental State Examination scores. Conclusion: The study predicted the disease trajectory of different types of aMCI patients based on the characteristic values of the above-mentioned brain regions. The prediction accuracy rate can reach 90.2%, and the microstructure characteristics of the right cingulate band and the right hippocampus may have potential clinical application value to predict the disease trajectory.

P2-065: Volume loss and parahippocampal white matter integrity in amnestic mild cognitive impairment

2008 ◽  
Vol 4 ◽  
pp. T386-T386
Author(s):  
Emily J. Rogalski ◽  
Chris M. Murphy ◽  
Leyla de Toledo-Morrell ◽  
Raj C. Shah ◽  
Mehul A. Trivedi ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
White Matter ◽  
Amnestic Mild Cognitive Impairment ◽  
White Matter Integrity ◽  
Volume Loss

[P4-245]: WHITE MATTER FRACTIONAL ANISOTROPY ANALYSIS OF BEHAVIOURAL AND COGNITIVE DYSEXECUTIVE SYNDROMES IN AMNESTIC MILD COGNITIVE IMPAIRMENT AND ALZHEIMER'S DISEASE: A MEXICAN PILOT STUDY

2017 ◽  
Vol 13 (7S_Part_28) ◽  
pp. P1371-P1372
Author(s):  
Juan Francisco Flores-Vazquez ◽  
Oscar René Marrufo-Melendez ◽  
Yaneth Rodriguez Agudelo ◽  
Gilberto Isaac Acosta-Castillo ◽  
Daniel Alejandro Lopez Ramos ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
White Matter ◽  
Pilot Study ◽  
Fractional Anisotropy ◽  
Amnestic Mild Cognitive Impairment

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.

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