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 Breast Cancer, Alzheimer’s Disease, and APOE4 Allele in the UK Biobank Cohort

2021 ◽  
Vol 5 (1) ◽  
pp. 49-53
Author(s):  
Steven Lehrer ◽  
Peter H. Rheinstein
Keyword(s):  
Breast Cancer ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Apoe Genotype ◽  
Uk Biobank ◽  
Breast Cancer Patients ◽  
Apoe4 Allele ◽  
Significant Difference ◽  
The Uk ◽  
Cognitive Problems

Background: Cognitive problems are common in breast cancer patients. The apolipoprotein E4 (APOE4) gene, a risk factor for Alzheimer’s disease (AD), may be associated with cancer-related cognitive decline. Objective: To further evaluate the effects of the APOE4 allele, we studied a cohort of patients from the UK Biobank (UKB) who had breast cancer; some also had AD. Methods: Our analysis included all subjects with invasive breast cancer. Single nucleotide polymorphism (SNP) data for rs 429358 and rs 7412 was used to determine APOE genotypes. Cognitive function as numeric memory was assessed with an online test (UKB data field 20240). Results: We analyzed data from 2,876 women with breast cancer. Of the breast cancer subjects, 585 (20%) carried the APOE4 allele. Numeric memory scores were significantly lower in APOE4 carriers and APOE4 homozygotes than non-carriers (p = 0.046). 34 breast cancer subjects (1.1%) had AD. There was no significant difference in survival among genotypes ɛ3/ɛ3, ɛ3/ɛ4, and ɛ4/ɛ4. Conclusion: UKB data suggest that cognitive problems in women with breast cancer are, for the most part, mild, compared with other sequelae of the disease. AD, the worst cognitive problem, is relatively rare (1.1%) and, when it occurs, APOE genotype has little impact on survival.

scholarly journals Genetic overlap between Alzheimer’s disease and depression mapped onto the brain

2021 ◽  
Author(s):  
Jennifer Monereo Sánchez ◽  
Miranda T. Schram ◽  
Oleksandr Frei ◽  
Kevin O’Connell ◽  
Alexey A. Shadrin ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genome Wide Association Study ◽  
Brain Mri ◽  
Genetic Correlations ◽  
Gaussian Mixture ◽  
Brain Morphology ◽  
Uk Biobank ◽  
Genetic Overlap ◽  
The Uk

ABSTRACTBackgroundAlzheimer’s disease (AD) and depression are debilitating brain disorders that are often comorbid. Shared brain mechanisms have been implicated, yet findings are inconsistent, reflecting the complexity of the underlying pathophysiology. As both disorders are (partly) heritable, characterizing their genetic overlap may provide etiological clues. While previous studies have indicated negligible genetic correlations, this study aims to expose the genetic overlap that may remain hidden due to mixed directions of effects.MethodsWe applied Gaussian mixture modelling, through MiXeR, and conjunctional false discovery rate (cFDR) analysis, through pleioFDR, to genome-wide association study (GWAS) summary statistics of AD (n=79,145) and depression (n=450,619). The effects of identified overlapping loci on AD and depression were tested in 403,029 participants of the UK Biobank (mean age 57.21 52.0% female), and mapped onto brain morphology in 30,699 individuals with brain MRI data.ResultsMiXer estimated 98 causal genetic variants overlapping between the two disorders, with 0.44 concordant directions of effects. Through pleioFDR, we identified a SNP in the TMEM106B gene, which was significantly associated with AD (B=-0.002, p=9.1×10−4) and depression (B=0.007, p=3.2×10−9) in the UK Biobank. This SNP was also associated with several regions of the corpus callosum volume anterior (B>0.024, p<8.6×10−4), third ventricle volume ventricle (B=-0.025, p=5.0×10−6), and inferior temporal gyrus surface area (B=0.017, p=5.3×10−4).DiscussionOur results indicate there is substantial genetic overlap, with mixed directions of effects, between AD and depression. These findings illustrate the value of biostatistical tools that capture such overlap, providing insight into the genetic architectures of these disorders.

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 Heterogeneous effects of genetic risk for Alzheimer’s disease on the phenome

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hei Man Wu ◽  
Alison M. Goate ◽  
Paul F. O’Reilly
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genetic Risk ◽  
Familial Risk ◽  
Psychosocial Health ◽  
Uk Biobank ◽  
Multiple Forms ◽  
Heterogeneous Effects ◽  
The Difference ◽  
The Uk

AbstractHere we report how four major forms of Alzheimer’s disease (AD) genetic risk—APOE-ε4, APOE-ε2, polygenic risk and familial risk—are associated with 273 traits in ~500,000 individuals in the UK Biobank. The traits cover blood biochemistry and cell traits, metabolic and general health, psychosocial health, and cognitive function. The difference in the profile of traits associated with the different forms of AD risk is striking and may contribute to heterogenous presentation of the disease. However, we also identify traits significantly associated with multiple forms of AD genetic risk, as well as traits showing significant changes across ages in those at high risk of AD, which may point to their potential roles in AD etiology. Finally, we highlight how survivor effects, in particular those relating to shared risks of cardiovascular disease and AD, can generate associations that may mislead interpretation in epidemiological AD studies. The UK Biobank provides a unique opportunity to powerfully compare the effects of different forms of AD genetic risk on the phenome in the same cohort.

scholarly journals Dietary Patterns, Genetic Predisposition, and Cognitive Function in the UK Biobank

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 1090-1090
Author(s):  
Christina-Alexandra Schulz ◽  
Leonie Weinhold ◽  
Matthias Schmid ◽  
Ute Nöthlings ◽  
Marcus M Nöthen
Keyword(s):  
Cognitive Function ◽  
Neurodegenerative Disease ◽  
Genetic Predisposition ◽  
Dietary Patterns ◽  
Fluid Intelligence ◽  
Processed Meat ◽  
Uk Biobank ◽  
Genetic Disposition ◽  
The Uk ◽  
Diet Score

Abstract Objectives Elucidating the role of dietary intake in cognitive function, and neurodegenerative disease development is important for prevention. The Mediterranean diet has shown to be beneficial for cognitive function and prevention of neurodegenerative disease. Yet, evidence for other dietary patterns are inconclusive. Since heritability of cognitive functions is substantial, a beneficial diet might mitigate genetic disposition. Therefore, we investigate if dietary patterns are associated with general cognitive function, considering individual genetic disposition. This research has been conducted using the UK Biobank Resource. Methods At baseline, participants reported the frequency of consumption of main foods via a dietary touchscreen questionnaire and filled in a verbal-numerical reasoning (VNR) test, which measures fluid intelligence. A diet score including 7 components: vegetables, fruit, fish, processed meat, unprocessed meat, whole grain, and refined grain was constructed. Participants were categorized into a low (0–1), intermediate (2–5), and high (6–7) diet score. A polygenic score (PGS), previously associated in GWAS with general cognitive function, was constructed. Participants were categorized into low (Quintile 1), intermediate (Q 2–4), and high (Q 5) PGS group. Linear regression was used to test whether the diet score associates with fluid intelligence, and to test if genetic predisposition modifies the association. Results The mean diet score of the 104,898 participants (46% male, mean age 57.1 (SD 8.0) years) was 3.9 (SD 1.4) points. In the VNR-test on average 6.1 (SD 2.1) questions were answered correctly. After multivariate adjustment a positive association between fluid intelligence and the PGS (P &lt; 0.001), but no association between fluid intelligence and the diet score (P = 0.703) was observed. When stratified according to PGS groups, similar results were observed for the association between fluid intelligence and the diet score. Conclusions No evidence was found that the investigated diet score was associated with fluid intelligence. As previously reported, genetic disposition was strongly associated with cognitive performance. Funding Sources This work was partly supported by Diet–Body–Brain (DietBB), the Competence Cluster in Nutrition Research funded by the Federal Ministry of Education and Research (FKZ: 01EA1410A).

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 Characterizing brain age in the Alzheimer's disease connectome project using a deep neural network pre‐trained on the UK Biobank

2021 ◽  
Vol 17 (S5) ◽  
Author(s):  
Nagesh Adluru ◽  
Veena A. Nair ◽  
Vivek Prabhakaran ◽  
Vishnu Bashyam ◽  
Shi‐Jiang Li ◽  
...  
Keyword(s):  
Neural Network ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Deep Neural Network ◽  
Uk Biobank ◽  
The Uk ◽  
Brain Age

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 Exploration of Alzheimer's Disease MRI Biomarkers Using APOE4 Carrier Status in the UK Biobank

2021 ◽  
Author(s):  
Jingnan Du ◽  
Zhaowen Liu ◽  
Lindsay C Hanford ◽  
Kevin M Anderson ◽  
Jianfeng Feng ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
White Matter ◽  
Large Scale ◽  
Vascular Dysfunction ◽  
Hippocampal Volume ◽  
Carrier Status ◽  
Amyloid Angiopathy ◽  
Uk Biobank ◽  
The Uk

Large-scale datasets enable novel strategies to refine and discover relations among biomarkers of disease. Here 30,863 individuals ages 44-82 from the UK Biobank were analyzed to explore MRI biomarkers associated with Alzheimer's disease (AD) genetic risk as contrast to general effects of aging. Individuals homozygotic for the E4 variant of apolipoprotein E (APOE4) overlapped non-carriers in their 50s but demonstrated neurodegenerative effects on the hippocampal system beginning in the seventh decade (reduced hippocampal volume, entorhinal thickness, and hippocampal cingulum integrity). Phenome-wide exploration further nominated the posterior thalamic radiation (PTR) as having a strong effect, as well as multiple diffusion MRI (dMRI) and white matter measures consistent with vascular dysfunction. Effects on the hippocampal system and white matter could be dissociated in the homozygotic APOE4 carriers supporting separation between AD and cerebral amyloid angiopathy (CAA) patterns. These results suggest new ways to combine and interrogate measures of neurodegeneration.

Lighting and Alzheimer’s disease and related dementias: Spotlight on sleep and depression

2021 ◽  
Vol 53 (5) ◽  
pp. 405-422
Author(s):  
MG Figueiro ◽  
HC Kales
Keyword(s):  
Alzheimer’S Disease ◽  
Older Adults ◽  
Alzheimer's Disease ◽  
Neurodegenerative Disease ◽  
Sleep Disturbances ◽  
Well Being ◽  
Pharmacological Intervention ◽  
Negative Effects ◽  
Health And Well Being ◽  
Positive Results

Alzheimer’s disease and related dementias is the collective term for a progressive neurodegenerative disease for which there is presently no cure. This paper focuses on two symptoms of the disease, sleep disturbances and depression, and discusses how light can be used as a non-pharmacological intervention to mitigate their negative effects. Bright days and dark nights are needed for health and well-being, but the present components of the built environment, especially those places where older adults spend most of their days, are too dimly illuminated during the day and too bright at night. To be effective light needs to be correctly specified, implemented and measured. Yet, without the appropriate specification and measurement of the stimulus, researchers will not be able to successfully demonstrate positive results in the field, nor will lighting designers and specifiers have the confidence to implement lighting solutions for promoting better sleep and mood in this population.

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