scholarly journals Lifelong Bilingualism Functions as an Alternative Intervention for Cognitive Reserve Against Alzheimer's Disease

2021 ◽  
Vol 12 ◽  
Author(s):  
Haiqing Liu ◽  
Longhuo Wu
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Cognitive Reserve ◽  
Early Stage ◽  
Brain Network ◽  
Pharmacological Intervention ◽  
Alternative Intervention ◽  
Confounding Variables ◽  
The Relationship

Bilingualism has been reported to significantly delay the onset of dementia and plays an important role in the management of Alzheimer's disease (AD), a condition inducing impairment in the brain network and cognitive decline. Cognitive reserve is associated with the adaptive maintenance of neural functions by protecting against neuropathology. Bilingualism acts as a beneficial environmental factor contributing to cognitive reserve, although some potential confounding variables still need further elucidation. In this article, the relationship between bilingualism and cognitive reserve is discussed, interpreting the advantage of bilingualism in protecting against cognitive decline. In addition, the possible brain and biochemical mechanisms, supporting the advantageous effects of bilingualism in delaying the onset of dementia, involved in bilingualism are reviewed. Effectively, bilingualism can be considered as a pharmacological intervention with no side effects. However, the investigation of the pharmacological parameters of bilingualism is still at an early stage.

scholarly journals Cognitive Reserve Proxies, Alzheimer Pathologies, and Cognition

2020 ◽  
Author(s):  
Kang Ko ◽  
Dahyun Yi ◽  
Min Soo Byun ◽  
Jun Ho Lee ◽  
So Yeon Jeon ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Cognitive Reserve ◽  
Cognitive Activity ◽  
Moderating Effect ◽  
Cortical Atrophy ◽  
Moderating Effects ◽  
The Relationship

Abstract BackgroundLimited information is available regarding which of the commonly used cognitive reserve (CR) proxies are more appropriate to precisely reflect moderation effect for the relationship between a specific Alzheimer’s disease (AD) pathology and cognitive decline. We examined the moderating effects of the frequently used four CR proxies [i.e., education, premorbid intelligence quotient (pIQ), occupational complexity (OC), and lifetime cognitive activity (LCA)] on the relationships between various in vivo AD pathologies and cognitive decline. MethodsThis study included 361 older adults (268 cognitively unimpaired, 52 mild cognitive impairment with beta-amyloid (Aβ) deposition, 41 AD dementia with Aβ deposition). All participants underwent multi-modal brain imaging including [11C] Pittsburgh Compound B positron emission tomography (PET), [18F] Fluorodeoxyglucose-PET, and magnetic resonance imaging to measure AD pathologies as well as comprehensive clinical and neuropsychological assessments. Information on education, pIQ estimated with an adult reading test, OC, and LCA was obtained. The Consortium to Establish a Registry for Alzheimer's Disease neuropsychological battery total score (CERAD-TS) was used as the cognitive measure. We used linear regression model predicting cognition to examine the interactions of each CR proxy and each AD pathology.ResultsAmong the CR proxies, only education significantly moderated the relationship between Aβ deposition and CERAD-TS. Education, pIQ, and LCA, but not OC, showed moderating effect on the relationship between AD-signature cerebral hypometabolism and CERAD-TS. In contrast, only OC had a significant moderating effect on the relationship between cortical atrophy of the AD-signature regions and CERAD-TS. ConclusionsThe present findings suggest that the proposed CR proxies have different moderating effects on the relationships between specific AD pathologies and cognitive decline. To investigate CR or related issues, it is necessary to select a proper CR proxy considering the target brain pathology.

scholarly journals Conversational System as Assistant Tool in Reminiscence Therapy for People with Early-Stage of Alzheimer’s

Healthcare ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 1036
Author(s):  
Victor Morales-de-Jesús ◽  
Helena Gómez-Adorno ◽  
María Somodevilla-García ◽  
Darnes Vilariño
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Life History ◽  
Patient Information ◽  
Early Stage ◽  
Care Center ◽  
Pharmacological Intervention ◽  
Emotional States ◽  
Reminiscence Therapy ◽  
Past Experiences

Reminiscence therapy is a non-pharmacological intervention that helps mitigate unstable psychological and emotional states in patients with Alzheimer’s disease, where past experiences are evoked through conversations between the patients and their caregivers, stimulating autobiographical episodic memory. It is highly recommended that people with Alzheimer regularly receive this type of therapy. In this paper, we describe the development of a conversational system that can be used as a tool to provide reminiscence therapy to people with Alzheimer’s disease. The system has the ability to personalize the therapy according to the patients information related to their preferences, life history and lifestyle. An evaluation conducted with eleven people related to patient care (caregiver = 9, geriatric doctor = 1, care center assistant = 1) shows that the system is capable of carrying out a reminiscence therapy according to the patient information in a successful manner.

scholarly journals Genetic Effects on Longitudinal Cognitive Decline During the Early Stages of Alzheimer's Disease

2021 ◽  
Author(s):  
Atul Kumar ◽  
Maryam Shoai ◽  
Sebastian Palmqvist ◽  
Erik Stomrud ◽  
John Hardy ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Genome Wide Association Study ◽  
Early Stage ◽  
Cognitive Change ◽  
Preclinical Ad ◽  
Genome Wide ◽  
A Genome ◽  
Polygenic Scores

Abstract Background Cognitive decline in early-stage Alzheimer’s disease (AD) may depend on genetic variability. Methods In the Swedish BioFINDER study, we used polygenic scores (PGS) (for AD, intelligence and educational attainment), and genetic variants (in a genome-wide association study [GWAS]) to predict longitudinal cognitive change (measured by MMSE) over a mean of 4.2 years. We included 555 β-amyloid (Aβ) negative cognitively unimpaired (CU) individuals, 206 Aβ-positive CU (preclinical AD), 110 Aβ-negative mild cognitive impairment (MCI) patients, and 146 Aβ-positive MCI patients (prodromal AD). Results Polygenic scores for AD (in Aβ-positive individuals) and intelligence (independent of Aβ-status) were associated with cognitive decline. Eight genes were associated with cognitive decline in GWAS (3 independent of Aβ-status). Conclusions AD risk genes may influence cognitive decline in early AD, while genes related to intelligence may modulate cognitive decline irrespective of disease. Therapies targeting the implicated biological pathways may modulate the clinical course of AD.

scholarly journals A Strategy for Identifying the Risk of Developing Alzheimer's Disease From Healthy Controls: Distance to Novelty Detection Boundary

2020 ◽  
Author(s):  
Jiangbing Mao ◽  
Qinyong Ye ◽  
Hongqing Yang ◽  
Magda Bucholc ◽  
Shuo Liu ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Cognitive Decline ◽  
Early Stage ◽  
Novelty Detection ◽  
Imaging Biomarkers ◽  
Support Vector ◽  
Support Vector Data Description ◽  
Healthy Controls

Abstract Background:Machine learning (ML) techniques are expected to tackle the problem of the high prevalence of Alzheimer’s disease (AD) we are facing worldwide. However, few studies of novelty detection (ND), a typical ML technique for safety-critical systems especially in healthcare, were engaged for identifying the risk of developing cognitive impairment from healthy controls (HC) population.Materials and Methods: Two independent datasets were used for this study, including the Australian Imaging Biomarkers and Lifestyle Study of Ageing (AIBL) and the Fujian Medical University Union Hospital (FMUUH), China datasets. Multiple feature selection methods were applied to identify the most relevant features for predicting the severity of AD. Four easily interpretable ND algorithms, including k nearest neighbor, Mixture of Gaussian (MoG), KMEANS, and support vector data description were used to construct predictive models. The models were visualized by drawing their decision boundaries tightly surrounding the HC data. A distance to boundary (DtB) strategy was proposed to differentiate individuals with mild cognitive impairment (MCI) and AD from HC. Results: The best overall MCI&AD detection performance in both AIBL and FMUUH was obtained on the cognitive and functional assessments (CFA) modality only using MoG-based ND with AUC of 0.8757 and 0.9443, respectively. The highest sensitivity of MCI was presented by using a combination of CFA and brain imaging modality. The DTB value reflects the risk of developing cognitive impairment for HC and the dementia severity of MCI/AD.Conclusions: Our findings suggest that applying some non-invasive and cost-effective features can significantly detect cognitive decline in an early stage. The visualized decision boundary and the proposed DtB strategy illustrated the severity of cognitive decline of potential MCI&AD patients in an early stage. The results would help inform future guidelines for developing a clinical decision-making support system aiming at an early diagnosis and prognosis of MCI&AD.

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