scholarly journals Positive Effect of Cognitive Reserve on Episodic Memory, Executive and Attentional Functions Taking Into Account Amyloid-Beta, Tau, and Apolipoprotein E Status

2021 ◽  
Vol 13 ◽  
Author(s):  
Justinas Narbutas ◽  
Daphne Chylinski ◽  
Maxime Van Egroo ◽  
Mohamed Ali Bahri ◽  
Ekaterina Koshmanova ◽  
...  
Keyword(s):  
Episodic Memory ◽  
Apolipoprotein E ◽  
Amyloid Beta ◽  
Allostatic Load ◽  
Cognitive Reserve ◽  
Domain Specific ◽  
Attentional Functioning ◽  
Positron Emission ◽  
Modifiable Factors ◽  
Apolipoprotein E Genotype

Studies exploring the simultaneous influence of several physiological and environmental factors on domain-specific cognition in late middle-age remain scarce. Therefore, our objective was to determine the respective contribution of modifiable risk/protective factors (cognitive reserve and allostatic load) on specific cognitive domains (episodic memory, executive functions, and attention), taking into account non-modifiable factors [sex, age, and genetic risk for Alzheimer’s disease (AD)] and AD-related biomarker amount (amyloid-beta and tau/neuroinflammation) in a healthy late-middle-aged population. One hundred and one healthy participants (59.4 ± 5 years; 68 women) were evaluated for episodic memory, executive and attentional functioning via neuropsychological test battery. Cognitive reserve was determined by the National Adult Reading Test. The allostatic load consisted of measures of lipid metabolism and sympathetic nervous system functioning. The amyloid-beta level was assessed using positron emission tomography in all participants, whereas tau/neuroinflammation positron emission tomography scans and apolipoprotein E genotype were available for 58 participants. Higher cognitive reserve was the main correlate of better cognitive performance across all domains. Moreover, age was negatively associated with attentional functioning, whereas sex was a significant predictor for episodic memory, with women having better performance than men. Finally, our results did not show clear significant associations between performance over any cognitive domain and apolipoprotein E genotype and AD biomarkers. This suggests that domain-specific cognition in late healthy midlife is mainly determined by a combination of modifiable (cognitive reserve) and non-modifiable factors (sex and age) rather than by AD biomarkers and genetic risk for AD.

Amyloid-beta-induced Degeneration of Human Brain Pericytes Is Dependent on the Apolipoprotein E Genotype

2000 ◽  
Vol 903 (1 VASCULAR FACT) ◽  
pp. 187-199 ◽  
Author(s):  
MARCEL M. VERBEEK ◽  
WILLIAM E. VAN NOSTRAND ◽  
IRENE OTTE-HOLLER ◽  
PIETER WESSELING ◽  
ROBERT M. W. DE WAAL
Keyword(s):  
Human Brain ◽  
Apolipoprotein E ◽  
Amyloid Beta ◽  
Brain Pericytes ◽  
Apolipoprotein E Genotype

scholarly journals Cerebrospinal fluid biomarkers and apolipoprotein E genotype in cerebral amyloid angiopathy. A narrative review

2021 ◽  
Vol 2 ◽  
pp. 100010
Author(s):  
Aikaterini Theodorou ◽  
Ioanna Tsantzali ◽  
Elisabeth Kapaki ◽  
Vasilios C. Constantinides ◽  
Konstantinos Voumvourakis ◽  
...  
Keyword(s):  
Cerebrospinal Fluid ◽  
Apolipoprotein E ◽  
Cerebral Amyloid Angiopathy ◽  
Narrative Review ◽  
Amyloid Angiopathy ◽  
Cerebrospinal Fluid Biomarkers ◽  
Cerebral Amyloid ◽  
Apolipoprotein E Genotype

scholarly journals Interactions between Apolipoprotein E Metabolism and Retinal Inflammation in Age-Related Macular Degeneration

Life ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 635
Author(s):  
Monica L. Hu ◽  
Joel Quinn ◽  
Kanmin Xue
Keyword(s):  
Risk Factor ◽  
Apolipoprotein E ◽  
Macular Degeneration ◽  
Amyloid Beta ◽  
Complement System ◽  
Genetic Risk ◽  
Age Related Macular Degeneration ◽  
Age Related ◽  
Retinal Inflammation ◽  
The Complement System

Age-related macular degeneration (AMD) is a multifactorial retinal disorder that is a major global cause of severe visual impairment. The development of an effective therapy to treat geographic atrophy, the predominant form of AMD, remains elusive due to the incomplete understanding of its pathogenesis. Central to AMD diagnosis and pathology are the hallmark lipid and proteinaceous deposits, drusen and reticular pseudodrusen, that accumulate in the subretinal pigment epithelium and subretinal spaces, respectively. Age-related changes and environmental stressors, such as smoking and a high-fat diet, are believed to interact with the many genetic risk variants that have been identified in several major biochemical pathways, including lipoprotein metabolism and the complement system. The APOE gene, encoding apolipoprotein E (APOE), is a major genetic risk factor for AMD, with the APOE2 allele conferring increased risk and APOE4 conferring reduced risk, in comparison to the wildtype APOE3. Paradoxically, APOE4 is the main genetic risk factor in Alzheimer's disease, a disease with features of neuroinflammation and amyloid-beta deposition in common with AMD. The potential interactions of APOE with the complement system and amyloid-beta are discussed here to shed light on their roles in AMD pathogenesis, including in drusen biogenesis, immune cell activation and recruitment, and retinal inflammation.

Machine Learning for the Prediction of Amyloid Positivity in Amnestic Mild Cognitive Impairment

2021 ◽  
pp. 1-15
Author(s):  
Sung Hoon Kang ◽  
Bo Kyoung Cheon ◽  
Ji-Sun Kim ◽  
Hyemin Jang ◽  
Hee Jin Kim ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Apolipoprotein E ◽  
Cross Validation ◽  
Good Accuracy ◽  
External Validation ◽  
Amnestic Mild Cognitive Impairment ◽  
Temporal Region ◽  
Apolipoprotein E Genotype

Background: Amyloid (Aβ) evaluation in amnestic mild cognitive impairment (aMCI) patients is important for predicting conversion to Alzheimer’s disease. However, Aβ evaluation through amyloid positron emission tomography (PET) is limited due to high cost and safety issues. Objective: We therefore aimed to develop and validate prediction models of Aβ positivity for aMCI using optimal interpretable machine learning (ML) approaches utilizing multimodal markers. Methods: We recruited 529 aMCI patients from multiple centers who underwent Aβ PET. We trained ML algorithms using a training cohort (324 aMCI from Samsung medical center) with two-phase modelling: model 1 included age, gender, education, diabetes, hypertension, apolipoprotein E genotype, and neuropsychological test scores; model 2 included the same variables as model 1 with additional MRI features. We used four-fold cross-validation during the modelling and evaluated the models on an external validation cohort (187 aMCI from the other centers). Results: Model 1 showed good accuracy (area under the receiver operating characteristic curve [AUROC] 0.837) in cross-validation, and fair accuracy (AUROC 0.765) in external validation. Model 2 led to improvement in the prediction performance with good accuracy (AUROC 0.892) in cross validation compared to model 1. Apolipoprotein E genotype, delayed recall task scores, and interaction between cortical thickness in the temporal region and hippocampal volume were the most important predictors of Aβ positivity. Conclusion: Our results suggest that ML models are effective in predicting Aβ positivity at the individual level and could help the biomarker-guided diagnosis of prodromal AD.

scholarly journals Interaction between apolipoprotein E genotype and hypertension on cognitive function in older women in the Nurses’ Health Study

PLoS ONE ◽  
2019 ◽  
Vol 14 (11) ◽  
pp. e0224975 ◽  
Author(s):  
Iris Y. Kim ◽  
Francine Grodstein ◽  
Peter Kraft ◽  
Gary C. Curhan ◽  
Katherine C. Hughes ◽  
...  
Keyword(s):  
Cognitive Function ◽  
Apolipoprotein E ◽  
Older Women ◽  
Health Study ◽  
Apolipoprotein E Genotype
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