scholarly journals Screening characteristics of PSEN1 E280A mutation carriers and non‐carriers in the API Autosomal Dominant Alzheimer’s Disease Colombia Trial

2020 ◽  
Vol 16 (S6) ◽  
Author(s):  
Silvia Rios‐Romenets ◽  
Margarita Giraldo‐Chica ◽  
Natalia Acosta‐Baena ◽  
Carlos Tobon ◽  
Claudia Ramos P ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Autosomal Dominant ◽  
Mutation Carriers ◽  
Autosomal Dominant Alzheimer’S Disease

scholarly journals Impairment of memory generalization in preclinical autosomal dominant Alzheimer's disease mutation carriers

2018 ◽  
Vol 65 ◽  
pp. 149-157 ◽  
Author(s):  
Jessica R. Petok ◽  
Catherine E. Myers ◽  
Judy Pa ◽  
Zachary Hobel ◽  
David M. Wharton ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Autosomal Dominant ◽  
Disease Mutation ◽  
Mutation Carriers ◽  
Autosomal Dominant Alzheimer’S Disease

scholarly journals Single-subject grey matter network trajectories over the disease course of autosomal dominant Alzheimer’s disease

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Lisa Vermunt ◽  
Ellen Dicks ◽  
Guoqiao Wang ◽  
Aylin Dincer ◽  
Shaney Flores ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Symptom Onset ◽  
Grey Matter ◽  
Autosomal Dominant ◽  
Single Subject ◽  
Mutation Carriers ◽  
Autosomal Dominant Alzheimer’S Disease ◽  
Network Properties ◽  
Over Time

Abstract Structural grey matter covariance networks provide an individual quantification of morphological patterns in the brain. The network integrity is disrupted in sporadic Alzheimer’s disease, and network properties show associations with the level of amyloid pathology and cognitive decline. Therefore, these network properties might be disease progression markers. However, it remains unclear when and how grey matter network integrity changes with disease progression. We investigated these questions in autosomal dominant Alzheimer’s disease mutation carriers, whose conserved age at dementia onset allows individual staging based upon their estimated years to symptom onset. From the Dominantly Inherited Alzheimer Network observational cohort, we selected T1-weighted MRI scans from 269 mutation carriers and 170 non-carriers (mean age 38 ± 15 years, mean estimated years to symptom onset −9 ± 11), of whom 237 had longitudinal scans with a mean follow-up of 3.0 years. Single-subject grey matter networks were extracted, and we calculated for each individual the network properties which describe the network topology, including the size, clustering, path length and small worldness. We determined at which time point mutation carriers and non-carriers diverged for global and regional grey matter network metrics, both cross-sectionally and for rate of change over time. Based on cross-sectional data, the earliest difference was observed in normalized path length, which was decreased for mutation carriers in the precuneus area at 13 years and on a global level 12 years before estimated symptom onset. Based on longitudinal data, we found the earliest difference between groups on a global level 6 years before symptom onset, with a greater rate of decline of network size for mutation carriers. We further compared grey matter network small worldness with established biomarkers for Alzheimer disease (i.e. amyloid accumulation, cortical thickness, brain metabolism and cognitive function). We found that greater amyloid accumulation at baseline was associated with faster decline of small worldness over time, and decline in grey matter network measures over time was accompanied by decline in brain metabolism, cortical thinning and cognitive decline. In summary, network measures decline in autosomal dominant Alzheimer’s disease, which is alike sporadic Alzheimer’s disease, and the properties show decline over time prior to estimated symptom onset. These data suggest that single-subject networks properties obtained from structural MRI scans form an additional non-invasive tool for understanding the substrate of cognitive decline and measuring progression from preclinical to severe clinical stages of Alzheimer’s disease.

scholarly journals The APOE ε4 Allele Affects Cognitive Functions Differently in Carriers of APP Mutations Compared to Carriers of PSEN1 Mutations in Autosomal-Dominant Alzheimer’s Disease

Genes ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1954
Author(s):  
Ove Almkvist ◽  
Caroline Graff
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Functions ◽  
Autosomal Dominant ◽  
Gene Interaction ◽  
Apoe Ε4 ◽  
Mutation Carriers ◽  
Autosomal Dominant Alzheimer’S Disease ◽  
Significant Difference ◽  
Ε4 Allele

Mounting evidence shows that the APOE ε4 allele interferes with cognition in sporadic Alzheimer’s disease. Less is known about APOE in autosomal-dominant Alzheimer’s disease (adAD). The present study explored the effects on cognition associated with the gene–gene interactions between the APOE gene and the APP and PSEN1 genes in adAD. This study includes mutation carriers (MC) and non-carriers (NC) from adAD families with mutations in APP (n = 28 and n = 25; MC and NC, respectively) and PSEN1 (n = 12 and n = 15; MC and NC, respectively) that represent the complete spectrum of disease: AD dementia (n = 8) and mild cognitive impairment (MCI, n = 15 and presymptomatic AD, n = 17). NC represented unimpaired normal aging. There was no significant difference in the distribution of APOE ε4 (absence vs. presence) between the APP vs. PSEN1 adAD genes and mutation status (MC vs. NC). However, episodic memory was significantly affected by the interaction between APOE and the APP vs. PSEN1 genes in MC. This was explained by favorable performance in the absence of APOE ε4 in PSEN1 compared to APP MC. Similar trends were seen in other cognitive functions. No significant associations between APOE ε4 and cognitive performance were obtained in NC. In conclusion, cognitive effects of APOE–adAD gene interaction were differentiated between the PSEN1 and APP mutation carriers, indicating epistasis.

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