More than just risk for Alzheimer's disease: APOE ε4's impact on the aging brain

Relationship Between Within-Session Digital Motor Skill Acquisition and Alzheimer Disease Risk Factors Among the MindCrowd Cohort: Cross-Sectional Descriptive Study

Background

Previous research has shown that in-lab motor skill acquisition (supervised by an experimenter) is sensitive to biomarkers of Alzheimer disease (AD). However, remote unsupervised screening of AD risk through a skill-based task via the web has the potential to sample a wider and more diverse pool of individuals at scale.

Objective

The purpose of this study was to examine a web-based motor skill game ("Super G") and its sensitivity to risk factors of AD (eg, age, sex, APOE ε4 carrier status, and verbal learning deficits).

Methods

Emails were sent to 662 previous MindCrowd participants who had agreed to be contacted for future research and have their APOE ε4 carrier status recorded and those who were at least 45 years of age or older. Participants who chose to participate were redirected to the Super G site where they completed the Super G task using their personal computer remotely and unsupervised. Once completed, different Super G variables were derived. Linear and logistic multivariable regression was used to examine the relationship between available AD risk factors (age, sex, APOE ε4 carrier status, and verbal learning) and distinct Super G performance metrics.

Results

Fifty-four participants (~8% response rate) from the MindCrowd web-based cohort (mean age of 62.39 years; 39 females; and 23 APOE ε4 carriers) completed 75 trials of Super G. Results show that Super G performance was significantly associated with each of the targeted risk factors. Specifically, slower Super G response time was associated with being an APOE ε4 carrier (odds ratio 0.12, 95% CI 0.02-0.44; P=.006), greater Super G time in target (TinT) was associated with being male (odds ratio 32.03, 95% CI 3.74-1192,61; P=.01), and lower Super G TinT was associated with greater age (β -3.97, 95% CI -6.64 to -1.30; P=.005). Furthermore, a sex-by-TinT interaction demonstrated a differential relationship between Super G TinT and verbal learning depending on sex (βmale:TinT 6.77, 95% CI 0.34-13.19; P=.04).

Conclusions

This experiment demonstrated that this web-based game, Super G, has the potential to be a skill-based digital biomarker for screening of AD risk on a large scale with relatively limited resources.

Assessing the causal role of lipid metabolites in Alzheimer's disease: A mendelian randomization study

BACKGROUND

The causal relationship between lipid metabolites and Alzheimer's disease (AD) remains unclear and contradictory. This study aimed to systematically assess the causal relationship between lipid metabolites and AD.

METHODS

A two-step bidirectional Mendelian Randomization (MR) study was employed. The principal analytical technique used to evaluate causation was inverse variance weighting (IVW). Furthermore, mediation analysis was conducted to evaluate the possible function of lipidomes as mediators in the lipid-AD pathway.

RESULTS

Among the 213 lipid metabolites analyzed, significant causal associations with AD were identified Cholesterol esters in large LDL(L-LDL-CE) (OR = 1.236, 95 %CI = 1.052-1.453, P = 0.010), Total cholesterol in large LDL(L-LDL-TC) (OR = 1.506, 95 %CI = 1.235-1.835, P < 0.001), Total cholesterol in medium LDL(M-LDL-TC) (OR = 1.378, 95 %CI = 1.132-1.677, P = 0.001). Mediation analysis further revealed ceramide (d42:2) and phosphatidylinositol (PI) (18:1_18:1) as potential mediators in this relationship.

CONCLUSION

The identification of specific lipid metabolites with causal effects on AD provides new insights into AD pathogenesis and highlights potential targets for preventive strategies.

Joint effect of polysocial risk score, lifestyle and genetic susceptibility with the risk of dementia: A prospective cohort study

OBJECTIVES

The comprehensive impact of polysocial risk score (PsRS)-encompassing multiple social determinants of health (SDoHs) with genetic and lifestyle factors on dementia incidence remains to be elucidated.

STUDY DESIGN

This study aimed to clear the associations between PsRS and dementia incidence and evaluated how genetic and lifestyle factors modified these associations in the UK Biobank cohort.

METHODS

The detailed prospective study involved over 500,000 participants when recruited in 2006-2010. The PsRS was calculated by 12 SDoHs across psychosocial factors, socioeconomic status, and neighborhood and living environment. A healthy lifestyle score was constructed from physical activities, alcohol consumption, smoking status, and diet. A genetic risk score (GRS) was computed via genotype data from UK Biobank. The Cox proportional hazards model was used to estimate hazard ratios (HRs) and 95 % confidence intervals (CIs) for the association between PsRS, lifestyle factors, GRS and dementia.

RESULTS

Results showed the participants with intermediate (HR = 1.32, 95%CI: 1.20-1.45) and high PsRS (HR = 2.10, 95 % CI: 1.91-2.32) were significantly associated with an increased risk of dementia compared with those with a low PsRS. Then, compared with participants with low PsRS and favorable lifestyle/low GRS, high PsRS and unfavorable lifestyle/high GRS had the highest risk of dementia (HR = 3.11,95%CI: 2.63-3.68)/(HR = 3.56, 95%CI: 2.62-4.85).

CONCLUSIONS

Both high PsRS and GRS were significantly associated with higher dementia risk. A favorable lifestyle could reduce dementia incidence regardless of high PsRS or GRS. Additionally, focusing on the intervention of SDoHs would be positive in preventing dementia.

Adherence to Life's Essential 8 is associated with delayed white matter aging

Importance

The American Heart Association introduced Life's Essential 8 (LE8) as a checklist of healthy lifestyle factors to help older individuals maintain and improve cardiovascular health and live longer. How LE8 can foster healthy brain aging and interact with genetic risk factors to render the aging brain less vulnerable to dementia is not well understood.

Objective

To investigate the impact of LE8 on the white matter brain aging and the moderating effects of the APOE4 allele.

Design Setting and Participants

This cross-sectional study uses genetic, imaging, and other health-related data collected in the UK Biobank cohort. Participants included non-pregnant whites with LE8 variables, diffusion tensor imaging data, and genetic data on APOE4 available, and excluded the extreme white matter hyperintensities. The baseline assessment was performed from 2006 to 2010. The diffusion tensor imaging data were collected since 2014.

Exposures

LE8 variables, encompassing diet, physical activity, smoking, sleep, body mass index, lipids, hemoglobin, and blood pressure.

Main Outcomes and Measures

The white matter brain age was predicted from regional fractional anisotropy measures derived from diffusion tensor imaging data using the random forest regression method. The outcome white matter brain age gap was calculated by subtracting individuals' chronological age from their predicted brain age.

Results

The analysis included 9,430 women and 9,387 men (mean age 55.45 [SD: 7.46] years). Higher LE8 scores were associated with lower white matter brain age gap, indicating delayed brain aging. The findings are consistent for each of the individual LE8 variables. The effect was stronger among non- APOE4 carriers (124 days younger per 10-point increase, 95% CI, 102 to 146 days; P<0.001) than APOE4 carriers (84 days younger per 10-point increase, 95% CI, 47 to 120 days; P<0.001). Notably, early middle-aged women with APOE4 showed significant interactions between LE8 scores and brain aging (P interaction = 0.048), not observed in men.

Conclusions and Relevance

Adherence to LE8 is associated with delayed brain aging, moderated by genetic factors such as APOE4 . These findings highlight the potential of behavioral and lifestyle interventions in reducing dementia risk, emphasizing tailored prevention plans for those with different genetic predispositions to dementia and sex.

Epigenetic biomarkers in Alzheimer's disease: Diagnostic and prognostic relevance

Alzheimer's disease (AD) is a leading cause of cognitive decline in the aging population, presenting a critical need for early diagnosis and effective prognostic tools. Epigenetic modifications, including DNA methylation, histone modifications, and non-coding RNAs, have emerged as promising biomarkers for AD due to their roles in regulating gene expression and potential for reversibility. This review examines the current landscape of epigenetic biomarkers in AD, emphasizing their diagnostic and prognostic relevance. DNA methylation patterns in genes such as APP, PSEN1, and PSEN2 are highlighted for their strong associations with AD pathology. Alterations in DNA methylation at specific CpG sites have been consistently observed in AD patients, suggesting their utility in early detection. Histone modifications, such as acetylation and methylation, also play a crucial role in chromatin remodelling and gene expression regulation in AD. Dysregulated histone acetylation and methylation have been linked to AD progression, making these modifications valuable biomarkers. Non-coding RNAs, including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), further contribute to the epigenetic regulation in AD. miRNAs can modulate gene expression post-transcriptionally and have been found in altered levels in AD, while lncRNAs can influence chromatin structure and gene expression. The presence of these non-coding RNAs in biofluids like blood and cerebrospinal fluid positions them as accessible and minimally invasive biomarkers. Technological advancements in detecting and quantifying epigenetic modifications have propelled the field forward. Techniques such as next-generation sequencing, bisulfite sequencing, and chromatin immunoprecipitation assays offer high sensitivity and specificity, enabling the detailed analysis of epigenetic changes in clinical samples. These tools are instrumental in translating epigenetic research into clinical practice. This review underscores the potential of epigenetic biomarkers to enhance the early diagnosis and prognosis of AD, paving the way for personalized therapeutic strategies and improved patient outcomes. The integration of these biomarkers into clinical workflows promises to revolutionize AD management, offering hope for better disease monitoring and intervention.

Cognitive synaptopathy: synaptic and dendritic spine dysfunction in age-related cognitive disorders

Cognitive impairment is a leading component of several neurodegenerative and neurodevelopmental diseases, profoundly impacting on the individual, the family, and society at large. Cognitive pathologies are driven by a multiplicity of factors, from genetic mutations and genetic risk factors, neurotransmitter-associated dysfunction, abnormal connectomics at the level of local neuronal circuits and broader brain networks, to environmental influences able to modulate some of the endogenous factors. Otherwise healthy older adults can be expected to experience some degree of mild cognitive impairment, some of which fall into the category of subjective cognitive deficits in clinical practice, while many neurodevelopmental and neurodegenerative diseases course with more profound alterations of cognition, particularly within the spectrum of the dementias. Our knowledge of the underlying neuropathological mechanisms at the root of this ample palette of clinical entities is far from complete. This review looks at current knowledge on synaptic modifications in the context of cognitive function along healthy ageing and cognitive dysfunction in disease, providing insight into differential diagnostic elements in the wide range of synapse alterations, from those associated with the mild cognitive changes of physiological senescence to the more profound abnormalities occurring at advanced clinical stages of dementia. I propose the term "cognitive synaptopathy" to encompass the wide spectrum of synaptic pathologies associated with higher brain function disorders.

Validation of the brain health index in the European Prevention of Alzheimer's Dementia cohort

Background

Brain Health Index (BHI) assimilates various MRI sequences, giving a quantitative measure of brain health. To date, BHI validation has been cross-sectional and limited to selected populations. Further large-scale validation and assessment of temporal change is required to understand its clinical utility.

Aim

Assess 1) relationships between variables associated with cognitive decline and BHI 2) associations between BHI and measures of cognition and 3) longitudinal changes in BHI and relationship with cognitive function.

Methods

BHI computation involved Gaussian mixture-model cluster analysis of T1, T2, T2*, and T2 FLAIR MRI data from participants within the European Prevention of Alzheimer's Dementia (EPAD) cohort. Group differences (gender- and health-based) were evaluated using independent samples Welch's t-tests. Relationships between BHI, age and cognitive tests used linear regression. Longitudinal analysis (12/24 months) utilised mixed linear regression models to examine BHI changes, and paired BHI/cognition associations.

Results

Data from N = 1496 predominantly Caucasian participants (50-88 years old, 43.32% male) were used. BHI scores were lower in those with diabetes (p < 0.001, d = 0.419), hypertension (p < 0.001, d = 0.375), hypercholesterolemia (p < 0.001, d = 0.193) and stroke (p < 0.05, d = 0.512). APOE was not significantly related to BHI scores. After correction for age, cross-sectional BHI scores were significantly associated with all measures of cognitive function in males, but only the Four Mountains Test (4MT) in females. Longitudinal change in BHI and cognition were not consistently related.

Conclusions

BHI is a valid marker of cognitive decline and relatively stable over 1-2 year follow-up periods. Further work should assess temporal changes over a longer duration and determine relationships between BHI and cognition in more diverse populations.

The Causal Relationship between Genetically Predicted Biological Aging, Alzheimer's Disease and Cognitive Function: A Mendelian Randomisation Study

Aging is one of the most important risk factors for Alzheimer's disease (AD). Biological aging is a better indicator of the body's functional state than age (chronological aging). Leukocyte telomere length (LTL) and epigenetic clocks constructed from DNA methylation patterns have emerged as reliable markers of biological aging. Recent studies have shown that it may be possible to slow down or even reverse biological aging, offering promising prospects for treating AD. Several observational studies have reported an association between biological aging, AD, and cognitive function, but the causality behind this association and the effects of different biological aging markers on AD risk and cognitive function remain unclear. Therefore, we explored the causal relationship between them by Mendelian randomization (MR) study. Inverse-variance weighted (IVW) method is the most dominant analytical method in MR studies, which is a weighted average of estimates from different genotype combinations, and this weighted average provides an overall estimate of the causal effect. The results of the IVW analyses showed that HannumAge acceleration and LTL shortening were able to increase the risk of late-onset AD (LOAD), but not early-onset AD (EOAD). Excellent prospective memory and fluid intelligence are potentially protective against GrimAge acceleration. GrimAge acceleration and HorvathAge acceleration increase the risk of LOAD through effects on LTL. Our findings provide important insights into the role of biological aging in the pathogenesis of AD, while also highlighting the interplay of different biological aging markers and their complexity in different AD subtypes.

Minding the Gap: Exploring Neuroinflammatory and Microglial Sex Differences in Alzheimer's Disease

Research into Alzheimer's Disease (AD) describes a link between AD and the resident immune cells of the brain, the microglia. Further, this suspected link is thought to have underlying sex effects, although the mechanisms of these effects are only just beginning to be understood. Many of these insights are the result of policies put in place by funding agencies such as the National Institutes of Health (NIH) to consider sex as a biological variable (SABV) and the move towards precision medicine due to continued lackluster therapeutic options. The purpose of this review is to provide an updated assessment of the current research that summarizes sex differences and the research pertaining to microglia and their varied responses in AD.