scholarly journals APOE ε4/ε4 homozygotes with early Alzheimer's disease show accelerated hippocampal atrophy and cortical thinning that correlates with cognitive decline

Author(s):  
Susan Abushakra ◽  
Anton P. Porsteinsson ◽  
Marwan Sabbagh ◽  
Luc Bracoud ◽  
Joel Schaerer ◽  
...  
Author(s):  
Liang Zhang ◽  
Hao Wang ◽  
Glen M Abel ◽  
Daniel R Storm ◽  
Zhengui Xia

Abstract Cadmium (Cd) is a heavy metal of great public health concern. Recent studies suggested a link between Cd exposure and cognitive decline in humans. The ε4 allele, compared with the common ε3 allele, of the human apolipoprotein E gene (ApoE) is associated with accelerated cognitive decline and increased risks for Alzheimer’s disease (AD). To investigate the gene-environment interactions (GxE) between ApoE-ε4 and Cd exposure on cognition, we used a mouse model of AD that expresses human ApoE-ε3 (ApoE3-KI [knock-in]) or ApoE-ε4 (ApoE4-KI). Mice were exposed to 0.6 mg/l CdCl2 through drinking water for 14 weeks and assessed for hippocampus-dependent memory. A separate cohort was sacrificed immediately after exposure and used for Cd measurements and immunostaining. The peak blood Cd was 0.3–0.4 µg/l, within levels found in the U.S. general population. All Cd-treated animals exhibited spatial working memory deficits in the novel object location test. This deficit manifested earlier in ApoE4-KI mice than in ApoE3-KI within the same sex and earlier in males than females within the same genotype. ApoE4-KI but not ApoE3-KI mice exhibited reduced spontaneous alternation later in life in the T-maze test. Finally, Cd exposure impaired neuronal differentiation of adult-born neurons in the hippocampus of male ApoE4-KI mice. These data suggest that a GxE between ApoE4 and Cd exposure leads to accelerated cognitive impairment and that impaired adult hippocampal neurogenesis may be one of the underlying mechanisms. Furthermore, male mice were more susceptible than female mice to this GxE effect when animals were young.


2020 ◽  
Vol 29 (8) ◽  
pp. 460-469 ◽  
Author(s):  
Kevin Hope

A multidisciplinary advisory group of health professionals involved in dementia care assessed the current evidence base regarding modifiable risk factors (MRFs) for early Alzheimer's disease and mild cognitive impairment. Based on evidence from the published literature and clinical experience, MRFs in four areas were identified where there is evidence to support interventions that may help delay cognitive decline or reduce the risk of developing Alzheimer's disease: medical (eg cardiovascular risk factors), psychosocial (eg depression, anxiety, social isolation), lifestyle (eg lack of physical activity, smoking) and nutrition (eg poor diet, lack of micronutrients). Practical guidance on how health professionals, but in particular nurses, may actively seek to address these MRFs in clinical practice was also developed. Nurses are at the forefront of patient care and, as such, are ideally placed to offer advice to patients that may proactively help mitigate the risks of cognitive decline and the development of Alzheimer's disease.


2013 ◽  
Vol 9 ◽  
pp. P5-P5
Author(s):  
Emily Manning ◽  
Josephine Barnes ◽  
David Cash ◽  
Jonathan Bartlett ◽  
Kelvin Leung ◽  
...  

2021 ◽  
pp. 1-8
Author(s):  
Neda Shafiee ◽  
Mahsa Dadar ◽  
Simon Ducharme ◽  
D. Louis Collins ◽  

Background: While both cognitive and magnetic resonance imaging (MRI) data has been used to predict progression in Alzheimer’s disease, heterogeneity between patients makes it challenging to predict the rate of cognitive and functional decline for individual subjects. Objective: To investigate prognostic power of MRI-based biomarkers of medial temporal lobe atrophy and macroscopic tissue change to predict cognitive decline in individual patients in clinical trials of early Alzheimer’s disease. Methods: Data used in this study included 312 patients with mild cognitive impairment from the ADNI dataset with baseline MRI, cerebrospinal fluid amyloid-β, cognitive test scores, and a minimum of two-year follow-up information available. We built a prognostic model using baseline cognitive scores and MRI-based features to determine which subjects remain stable and which functionally decline over 2 and 3-year follow-up periods. Results: Combining both sets of features yields 77%accuracy (81%sensitivity and 75%specificity) to predict cognitive decline at 2 years (74%accuracy at 3 years with 75%sensitivity and 73%specificity). When used to select trial participants, this tool yields a 3.8-fold decrease in the required sample size for a 2-year study (2.8-fold decrease for a 3-year study) for a hypothesized 25%treatment effect to reduce cognitive decline. Conclusion: When used in clinical trials for cohort enrichment, this tool could accelerate development of new treatments by significantly increasing statistical power to detect differences in cognitive decline between arms. In addition, detection of future decline can help clinicians improve patient management strategies that will slow or delay symptom progression.


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