scholarly journals Genetic Factors of Alzheimer’s Disease Modulate How Diet is Associated with Long-Term Cognitive Trajectories: A UK Biobank Study

2020 ◽  
Vol 78 (3) ◽  
pp. 1245-1257
Author(s):  
Brandon S. Klinedinst ◽  
Scott T. Le ◽  
Brittany Larsen ◽  
Colleen Pappas ◽  
Nathan J. Hoth ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
At Risk ◽  
Red Wine ◽  
Fluid Intelligence ◽  
Uk Biobank ◽  
Populations At Risk ◽  
Total Diet ◽  
Added Salt

Background: Fluid intelligence (FI) involves abstract problem-solving without prior knowledge. Greater age-related FI decline increases Alzheimer’s disease (AD) risk, and recent studies suggest that certain dietary regimens may influence rates of decline. However, it is uncertain how long-term food consumption affects FI among adults with or without familial history of AD (FH) or APOE4 (ɛ4). Objective: Observe how the total diet is associated with long-term cognition among mid- to late-life populations at-risk and not-at-risk for AD. Methods: Among 1,787 mid-to-late-aged adult UK Biobank participants, 10-year FI trajectories were modeled and regressed onto the total diet based on self-reported intake of 49 whole foods from a Food Frequency Questionnaire (FFQ). Results: Daily cheese intake strongly predicted better FIT scores over time (FH-: β= 0.207, p < 0.001; ɛ4–: β= 0.073, p = 0.008; ɛ4+: β= 0.162, p = 0.001). Alcohol of any type daily also appeared beneficial (ɛ4+: β= 0.101, p = 0.022) and red wine was sometimes additionally protective (FH+: β= 0.100, p = 0.014; ɛ4–: β= 0.59, p = 0.039). Consuming lamb weekly was associated with improved outcomes (FH-: β= 0.066, p = 0.008; ɛ4+: β= 0.097, p = 0.044). Among at risk groups, added salt correlated with decreased performance (FH+: β= –0.114, p = 0.004; ɛ4+: β= –0.121, p = 0.009). Conclusion: Modifying meal plans may help minimize cognitive decline. We observed that added salt may put at-risk individuals at greater risk, but did not observe similar interactions among FH- and AD- individuals. Observations further suggest in risk status-dependent manners that adding cheese and red wine to the diet daily, and lamb on a weekly basis, may also improve long-term cognitive outcomes.

scholarly journals Association between polygenic risk for Alzheimer’s disease, brain structure and cognitive abilities in UK Biobank.

2021 ◽  
Author(s):  
Rachana Tank ◽  
Joey Ward ◽  
Kristin E. Flegal ◽  
Daniel Smith ◽  
Mark E.S. Bailey ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Fluid Intelligence ◽  
Late Onset ◽  
Brain Mri ◽  
Brain Magnetic Resonance Imaging ◽  
Healthy Adults ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
Structural Brain

Background and purpose: Previous studies testing associations between polygenic risk for late-onset Alzheimer’s disease (LOAD-PGR) and brain magnetic resonance imaging (MRI) measures have been limited by small samples and inconsistent consideration of potential confounders. This study investigates whether higher LOAD-PGR is associated with differences in structural brain imaging and cognitive values in a relatively large sample of non-demented, generally healthy adults (UK Biobank). Method: Summary statistics were used to create PGR scores for n=32,790 participants using LDpred. Outcomes included 12 structural MRI volumes and 6 concurrent cognitive measures. Models were adjusted for age, sex, body mass index, genotyping chip, 8 principal components, lifetime smoking, apolipoprotein (APOE) e4 genotype and socioeconomic deprivation. We tested for statistical interactions between APOE e4 allele dose and LOAD-PGR vs. all outcomes. Results: In fully adjusted models, LOAD-PGR was associated with worse fluid intelligence (standardised beta [β] = -0.080 per LOAD-PGR standard deviation, p = 0.002), matrix completion (β = -0.102, p = 0.003), smaller left hippocampal total (β = -0.118, p = 0.002) and body (β = -0.069, p = 0.002) volumes, but not other hippocampal subdivisions. There were no significant APOE x LOAD-PGR score interactions for any outcomes in fully adjusted models. Discussion: This is the largest study to date investigating LOAD-PGR and non-demented structural brain MRI and cognition phenotypes. LOAD-PGR was associated with smaller hippocampal volumes and aspects of cognitive ability in healthy adults, and could supplement APOE status in risk stratification of cognitive impairment/LOAD.

scholarly journals Accelerated long-term forgetting in healthy older adults predicts cognitive decline over 1 year

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Alfie R. Wearn ◽  
Esther Saunders-Jennings ◽  
Volkan Nurdal ◽  
Emma Hadley ◽  
Michael J. Knight ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
At Risk ◽  
Older People ◽  
Cognitive Decline ◽  
Gold Standard ◽  
Medial Temporal Lobe ◽  
Delayed Recall ◽  
Better Than

Abstract Background Here, we address a pivotal factor in Alzheimer’s prevention—identifying those at risk early, when dementia can still be avoided. Recent research highlights an accelerated forgetting phenotype as a risk factor for Alzheimer’s disease. We hypothesized that delayed recall over 4 weeks would predict cognitive decline over 1 year better than 30-min delayed recall, the current gold standard for detecting episodic memory problems which could be an early clinical manifestation of incipient Alzheimer’s disease. We also expected hippocampal subfield volumes to improve predictive accuracy. Methods Forty-six cognitively healthy older people (mean age 70.7 ± 7.97, 21/46 female), recruited from databases such as Join Dementia Research, or a local database of volunteers, performed 3 memory tasks on which delayed recall was tested after 30 min and 4 weeks, as well as Addenbrooke’s Cognitive Examination III (ACE-III) and CANTAB Paired Associates Learning. Medial temporal lobe subregion volumes were automatically measured using high-resolution 3T MRI. The ACE-III was repeated after 12 months to assess the change in cognitive ability. We used univariate linear regressions and ROC curves to assess the ability of tests of delayed recall to predict cognitive decline on ACE-III over the 12 months. Results Fifteen of the 46 participants declined over the year (≥ 3 points lost on ACE-III). Four-week verbal memory predicted cognitive decline in healthy older people better than clinical gold standard memory tests and hippocampal MRI. The best single-test predictor of cognitive decline was the 4-week delayed recall on the world list (R2 = .123, p = .018, β = .418). Combined with hippocampal subfield volumetry, 4-week verbal recall identifies those at risk of cognitive decline with 93% sensitivity and 86% specificity (AUC = .918, p < .0001). Conclusions We show that a test of accelerated long-term forgetting over 4 weeks can predict cognitive decline in healthy older people where traditional tests of delayed recall cannot. Accelerated long-term forgetting is a sensitive, easy-to-test predictor of cognitive decline in healthy older people. Used alone or with hippocampal MRI, accelerated forgetting probes functionally relevant Alzheimer’s-related change. Accelerated forgetting will identify early-stage impairment, helping to target more invasive and expensive molecular biomarker testing.

A Simple Tool to Reach Populations at Risk for Developing Dementia and Alzheimer’s Disease

2015 ◽  
Vol 46 (1) ◽  
pp. 151-155
Author(s):  
Noa Bregman ◽  
Keren Regev ◽  
Orna Moore ◽  
Nir Giladi ◽  
Elissa Ash
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
At Risk ◽  
Simple Tool ◽  
Populations At Risk

scholarly journals Association between polygenic risk for Alzheimer’s disease, brain structure and cognitive abilities in UK Biobank

2021 ◽  
Author(s):  
Rachana Tank ◽  
Joey Ward ◽  
Kristin E. Flegal ◽  
Daniel J. Smith ◽  
Mark E. S. Bailey ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Fluid Intelligence ◽  
Late Onset ◽  
Brain Mri ◽  
Brain Magnetic Resonance Imaging ◽  
Healthy Adults ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
Structural Brain

AbstractPrevious studies testing associations between polygenic risk for late-onset Alzheimer’s disease (LOAD-PGR) and brain magnetic resonance imaging (MRI) measures have been limited by small samples and inconsistent consideration of potential confounders. This study investigates whether higher LOAD-PGR is associated with differences in structural brain imaging and cognitive values in a relatively large sample of non-demented, generally healthy adults (UK Biobank). Summary statistics were used to create PGR scores for n = 32,790 participants using LDpred. Outcomes included 12 structural MRI volumes and 6 concurrent cognitive measures. Models were adjusted for age, sex, body mass index, genotyping chip, 8 genetic principal components, lifetime smoking, apolipoprotein (APOE) e4 genotype and socioeconomic deprivation. We tested for statistical interactions between APOE e4 allele dose and LOAD-PGR vs. all outcomes. In fully adjusted models, LOAD-PGR was associated with worse fluid intelligence (standardised beta [β] = −0.080 per LOAD-PGR standard deviation, p = 0.002), matrix completion (β = −0.102, p = 0.003), smaller left hippocampal total (β = −0.118, p = 0.002) and body (β = −0.069, p = 0.002) volumes, but not other hippocampal subdivisions. There were no significant APOE x LOAD-PGR score interactions for any outcomes in fully adjusted models. This is the largest study to date investigating LOAD-PGR and non-demented structural brain MRI and cognition phenotypes. LOAD-PGR was associated with smaller hippocampal volumes and aspects of cognitive ability in healthy adults and could supplement APOE status in risk stratification of cognitive impairment/LOAD.

scholarly journals Identifying healthy individuals with Alzheimer neuroimaging phenotypes in the UK Biobank

2022 ◽  
Author(s):  
Tiago Azevedo ◽  
Richard A.I. Bethlehem ◽  
David J. Whiteside ◽  
Nol Swaddiwudhipong ◽  
James B. Rowe ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Neurodegenerative Disease ◽  
Fluid Intelligence ◽  
Structural Mri ◽  
Critical Issue ◽  
Healthy Population ◽  
Uk Biobank ◽  
Sporadic Disease ◽  
The Uk

Identifying prediagnostic neurodegenerative disease is a critical issue in neurodegenerative disease research, and Alzheimer's disease (AD) in particular, to identify populations suitable for preventive and early disease modifying trials. Evidence from genetic studies suggest the neurodegeneration of Alzheimer's disease measured by brain atrophy starts many years before diagnosis, but it is unclear whether these changes can be detected in sporadic disease. To address this challenge we train a Bayesian machine learning neural network model to generate a neuroimaging phenotype and AD-score representing the probability of AD using structural MRI data in the Alzheimer's Disease Neuroimaging Cohort (cut-off 0.5, AUC 0.92, PPV 0.90, NPV 0.93). We go on to validate the model in an independent real world dataset of the National Alzheimer's Coordinating Centre (AUC 0.74, PPV 0.65, NPV 0.80), and demonstrate correlation of the AD-score with cognitive scores in those with an AD-score above 0.5. We then apply the model to a healthy population in the UK Biobank study to identify a cohort at risk for Alzheimer's disease. This cohort have a cognitive profile in keeping with Alzheimer's disease, with strong evidence for poorer fluid intelligence, and with some evidence of poorer performance on tests of numeric memory, reaction time, working memory and prospective memory. We found some evidence in the AD-score positive cohort for modifiable risk factors of hypertension and smoking. This approach demonstrates the feasibility of using AI methods to identify a potentially prediagnostic population at high risk for developing sporadic Alzheimer's disease.

scholarly journals Therapeutic Potential of TNF-α Inhibition for Alzheimer’s Disease Prevention

2020 ◽  
Vol 78 (2) ◽  
pp. 619-626
Author(s):  
Noel Torres-Acosta ◽  
James H. O’Keefe ◽  
Evan L. O’Keefe ◽  
Richard Isaacson ◽  
Gary Small
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
At Risk ◽  
Cognitive Performance ◽  
Therapeutic Potential ◽  
Amyloid Β ◽  
Blocking Agents ◽  
Populations At Risk ◽  
Tnf Α ◽  
Factor Α

Background: Alzheimer’s disease (AD) is increasingly prevalent and over 99% of drugs developed for AD have failed in clinical trials. A growing body of literature suggests that potent inhibitors of tumor necrosis factor-α (TNF-α) have potential to improve cognitive performance. Objective: In this review, we summarize the evidence regarding the potential for TNF-α inhibition to prevent AD and improve cognitive function in people at risk for dementia. Methods: We conducted a literature review in PubMed, screening all articles published before July 7, 2019 related to TNF blocking agents and curcumin (another TNF-α inhibitor) in the context of AD pathology. The keywords in the search included: AD, dementia, memory, cognition, TNF-α, TNF inhibitors, etanercept, infliximab, adalimumab, golimumab, and curcumin. Results: Three large epidemiology studies reported etanercept treated patients had 60 to 70% lower odds ratio (OR) of developing AD. Two small-randomized control trials (RCTs) demonstrated an improvement in cognitive performance for AD patients treated with etanercept. Studies using animal models of dementia also reported similar findings with TNF blocking agents (etanercept, infliximab, adalimumab, Theracurmin), which appeared to improve cognition. A small human RCT using Theracurmin, a well-absorbed form of curcumin that lowers TNF-α, showed enhanced cognitive performance and decreased brain levels of amyloid-β plaque and tau tangles. Conclusion: TNF-α targeted therapy is a biologically plausible approach to the preservation of cognition, and warrants larger prospective RCTs to further investigate potential benefits in populations at risk of developing AD.

scholarly journals Gallery Game: Smartphone-based assessment of long-term memory in adults at risk of Alzheimer’s disease

2020 ◽  
Vol 42 (4) ◽  
pp. 329-343 ◽  
Author(s):  
Claire Lancaster ◽  
Ivan Koychev ◽  
Jasmine Blane ◽  
Amy Chinner ◽  
Christopher Chatham ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
At Risk ◽  
Long Term Memory ◽  
Term Memory
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