Culture, Ethnicity, and Level of Education in Alzheimer's Disease

Risk and protective factors for cognitive decline in Brazilian lower educated older adults: A 15-year follow-up study using group-based trajectory modelling

BACKGROUND

Patterns of cognitive change and modifiable factors for cognitive decline versus stable cognitive trajectories have rarely been described in lower-educated older adults.

OBJECTIVES

We aimed to identify long-term trajectories of cognitive functioning and possible factors associated with cognitive decline.

DESIGN AND PARTICIPANTS

We used data from 1,042 adults aged ≥ 60 participating in the Health, Welfare and Aging Study (SABE), São Paulo, Brazil, without cognitive impairment at baseline. Data were collected across four waves (2000-2015). Group-based trajectory modelling was used to identify cognitive trajectories. Associations with socioeconomic variables, childhood background, lifestyle, and cardiovascular risk factors were explored using weighted multinomial logistic regressions.

MEASUREMENTS

The abbreviated Mini-Mental State Examination was used to measure cognition.

RESULTS

Three cognitive trajectories were identified: stable (n= 754, 68.6%), mild-decline (n= 183, 20.8%), and strong-decline (n= 105, 10.7%). At baseline, respondents in the strong-decline group were more likely to be older than those with stable and mild-decline trajectories. Furthermore, participants in both the mild and strong-decline groups were more likely to have no schooling, be divorced/separated, receive less than 4 monthly wages, and be underweight (BMI < 18.5) compared to the stable group. Finally, the mild-decline group was more likely to have lived in rural areas during childhood than participants located in a stable trajectory.

CONCLUSIONS

Our findings suggest that interventions to reduce cognitive decline for low-educated older adults might include strategies addressing inequalities and improving modifiable risk factor burden.

Short-term memory binding is insensitive to the socioeconomic status of older adults with and without mild cognitive impairment

Objective: The Visual Short-Term Memory Binding (VSTMB) Test is a useful tool in the assessment of Alzheimer's disease (AD). Research has suggested that short-term memory binding is insensitive to the sociocultural characteristics of the assessed individuals. Such earlier studies addressed this influence by considering years of education. The current study aims to determine the influence of sociocultural factors via a measure of Socioeconomic Status (SES) which provides a more holistic approach to these common confounders. Methods: A sample of 126 older adults, both with (n = 59) and without (n = 67) amnestic mild cognitive impairment (aMCI), underwent assessment using a neuropsychological protocol including VSTMB test. All participants were classified as either high SES or low SES, employing the Standard Demographic Classification from the European Society for Opinion and Marketing Research. Results: ANOVA/ANCOVA models confirmed that performance of healthy and aMCI participants on traditional neuropsychological tests were sensitive to SES whereas the VSTMB Test was not. The results add to the growing array of evidence suggesting that there are cognitive abilities which are unaffected by socioeconomic factors, regardless of clinical condition. Conclusions: The lack of sensitivity to sociocultural factors previously reported for the VSTMB test is accompanied by a lack of sensitivity to socioeconomic factors thus broadening the scope of this test to aid in the detection of dementia across populations with different backgrounds. Future studies should take these findings forward and explore the potential influences of AD biomarkers (A/T/N) on the association between cognitive functions and demographic variables.

Neuroimaging and biofluid biomarkers across race and ethnicity in older adults across the spectrum of cognition

Neuroimaging and biofluid biomarkers provide a proxy of pathological changes for Alzheimer's disease (AD) and are useful in improving diagnosis and assessing disease progression. However, it is not clear how race/ethnicity and different prevalence of AD risks impact biomarker levels. In this narrative review, we survey studies focusing on comparing biomarker differences between non-Hispanic White American(s) (NHW), African American(s) (AA), Hispanic/Latino American(s) (HLA), and Asian American(s) with normal cognition, mild cognitive impairment, and dementia. We found no strong evidence of racial and ethnic differences in imaging biomarkers after controlling for cognitive status and cardiovascular risks. For biofluid biomarkers, in AA, higher levels of plasma Aβ42/Aβ40, and lower levels of CSF total tau and p-tau 181, were observed after controlling for APOE status and comorbidities compared to NHW. Examining the impact of AD risks and comorbidities on biomarkers and their contributions to racial/ethnic differences in cognitive impairment are critical to interpreting biomarkers, understanding their generalizability, and eliminating racial/ethnic health disparities.

European cross-cultural neuropsychological test battery (CNTB) for the assessment of cognitive impairment in multiple sclerosis: Cognitive phenotyping and classification supported by machine learning techniques

BACKGROUND

The European Cross-Cultural Neuropsychological Test Battery (CNTB) has been proposed as a comprehensive battery for cognitive assessment, reducing the potential impact of cultural variables. In this validation study, we aimed to evaluate the diagnostic capacity of CNTB for the assessment of participants with multiple sclerosis (pwMS) compared to the Neuronorma battery (NN) according to the International Classification of Cognitive Disorders in MS criteria, and to develop machine learning (ML) algorithms to improve the diagnostic capacity of CNTB and to select the most relevant tests.

METHODS

Sixty pwMS and 60 healthy controls (HC) with no differences in sex, age, or years of education were enrolled. All participants completed the CNTB and pwMS were also examined with NN, depression, and fatigue scales. Impaired domains and cognitive phenotypes were defined following ICCoDiMS based on CNTB scores and compared to NN, according to -1SD and -1.5SD cutoff scores. To select the most relevant tests, random forest (RF) was performed for different binary classifications.

RESULTS

PwMS showed a lower performance compared to HC with medium-large effect sizes, in episodic memory, executive function, attention, and processing speed, in accordance with their characteristic cognitive profile. There were no differences in impaired domains or cognitive phenotypes between CNTB and NN, highlighting the role of episodic memory, executive function, attention, and processing speed tests. The most relevant tests identified by RF were consistent with inter-group comparisons and allowed a better classification than SD cutoff scores.

CONCLUSION

CNTB is a valid test for cognitive diagnosis in pwMS, including key tests for the most frequently impaired cognitive domains in MS. The use of ML techniques may also be useful to improve diagnosis, especially in some tests with lower sensitivity.

Understanding the impact of slowing disease progression for individuals with biomarker-confirmed early symptomatic Alzheimer's disease

Recent advances in development of amyloid-targeting therapies support the potential to slow the rate of progression of Alzheimer's disease. We conducted a narrative review of published evidence identified through a targeted search of the MEDLINE and EMBASE databases (2020-2023), recent presentations at disease-specific conferences, and data updates from cohort studies in Alzheimer's disease to describe the trajectory of the progression of Alzheimer's disease. Our findings enable the interpretation of clinical trial results and the value associated with slowing disease progression across outcomes of relevance to patients, care partners, clinicians, researchers and policymakers. Even at the earliest stages, Alzheimer's disease imposes a substantial burden on individuals, care partners, and healthcare systems. The magnitude of the burden increases with the rate of disease progression and symptom severity, as worsening cognitive decline and physical impairment result in loss of functional independence. Data from cohort studies also indicate that slowing disease progression is associated with decreased likelihood of needing extensive clinical care over at least 5 years, decreased care partner burden, and substantial individual and societal cost savings. Slowed disease progression is of significant benefit to individuals with Alzheimer's disease, their loved ones, and the healthcare system. As clinicians and policymakers devise strategies to improve access to treatment earlier in the disease spectrum, they should carefully weigh the benefits of slowing progression early in the disease (e.g. preservation of cognitive and functional abilities, as well as relative independence) to individuals, their loved ones, and broader society.

Educational disparities in brain health and dementia across Latin America and the United States

BACKGROUND

Education influences brain health and dementia. However, its impact across regions, specifically Latin America (LA) and the United States (US), is unknown.

METHODS

A total of 1412 participants comprising controls, patients with Alzheimer's disease (AD), and frontotemporal lobar degeneration (FTLD) from LA and the US were included. We studied the association of education with brain volume and functional connectivity while controlling for imaging quality and variability, age, sex, total intracranial volume (TIV), and recording type.

RESULTS

Education influenced brain measures, explaining 24%-98% of the geographical differences. The educational disparities between LA and the US were associated with gray matter volume and connectivity variations, especially in LA and AD patients. Education emerged as a critical factor in classifying aging and dementia across regions.

DISCUSSION

The results underscore the impact of education on brain structure and function in LA, highlighting the importance of incorporating educational factors into diagnosing, care, and prevention, and emphasizing the need for global diversity in research.

HIGHLIGHTS

Lower education was linked to reduced brain volume and connectivity in healthy controls (HCs), Alzheimer's disease (AD), and frontotemporal lobar degeneration (FTLD). Latin American cohorts have lower educational levels compared to the those in the United States. Educational disparities majorly drive brain health differences between regions. Educational differences were significant in both conditions, but more in AD than FTLD. Education stands as a critical factor in classifying aging and dementia across regions.

IGF1R and FLT1 in female endothelial cells and CHD2 in male microglia play important roles in Alzheimer's disease based on gender difference analysis

OBJECTIVE

This study investigated sex-specific pathogenesis mechanisms in Alzheimer's disease (AD) using single-nucleus RNA sequencing (snRNA-seq) data.

METHODS

Data from the Gene Expression Omnibus (GEO) were searched using terms "Alzheimer's Disease", "single cell", and "Homo sapiens". Studies excluding APOE E4 and including comprehensive gender information with 10× sequencing methods were selected, resulting in GSE157827 and GSE174367 datasets from human prefrontal cortex samples. Sex-stratified analyses were conducted on these datasets, and the outcomes of the analysis for GSE157827 were compared with those of GSE174367. The findings were validated using expression profiling from the mouse dataset GSE85162. Furthermore, real-time PCR experiments in mice further confirmed these findings. The Seurat R package was used to identify cell types, and batch effects were mitigated using the Harmony R package. Cell proportions by sex were compared using the Mann-Whitney-Wilcoxon test, and gene expression variability was displayed with an empirical cumulative distribution plot. Differentially expressed genes were identified using the FindMarkers function with the MAST test. Transcription factors were analyzed using the RcisTarget R package.

RESULTS

Seven cell types were identified: astrocytes, endothelial cells, excitatory neurons, inhibitory neurons, microglia, oligodendrocytes, and oligodendrocyte progenitor cells. Additionally, five distinct subpopulations of both endothelial and microglial cells were also identified, respectively. Key findings included: (1) In endothelial cells, genes involved in synapse organization, such as Insulin Like Growth Factor 1 Receptor (IGF1R) and Fms Related Receptor Tyrosine Kinase 1(FLT1), showed higher expression in females with AD. (2) In microglial cells, genes in the ribosome pathway exhibited higher expression in males without AD compared to females (with or without AD) and males with AD. (3) Chromodomain Helicase DNA Binding Protein 2 (CHD2) negatively regulated gene expression in the ribosome pathway in male microglia, suppressing AD, this finding was further validated in mice. (4) Differences between Asians and Caucasians were observed based on sex and disease status stratification.

CONCLUSIONS

IGF1R and FLT1 in endothelial cells contribute to AD in females, while CHD2 negatively regulates ribosome pathway gene expression in male microglia, suppressing AD in humans and mice.

Machine and deep learning algorithms for classifying different types of dementia: A literature review

The cognitive impairment known as dementia affects millions of individuals throughout the globe. The use of machine learning (ML) and deep learning (DL) algorithms has shown great promise as a means of early identification and treatment of dementia. Dementias such as Alzheimer's Dementia, frontotemporal dementia, Lewy body dementia, and vascular dementia are all discussed in this article, along with a literature review on using ML algorithms in their diagnosis. Different ML algorithms, such as support vector machines, artificial neural networks, decision trees, and random forests, are compared and contrasted, along with their benefits and drawbacks. As discussed in this article, accurate ML models may be achieved by carefully considering feature selection and data preparation. We also discuss how ML algorithms can predict disease progression and patient responses to therapy. However, overreliance on ML and DL technologies should be avoided without further proof. It's important to note that these technologies are meant to assist in diagnosis but should not be used as the sole criteria for a final diagnosis. The research implies that ML algorithms may help increase the precision with which dementia is diagnosed, especially in its early stages. The efficacy of ML and DL algorithms in clinical contexts must be verified, and ethical issues around the use of personal data must be addressed, but this requires more study.

A feature-aware multimodal framework with auto-fusion for Alzheimer's disease diagnosis

Alzheimer's disease (AD), one of the most common dementias, has about 4.6 million new cases yearly worldwide. Due to the significant amount of suspected AD patients, early screening for the disease has become particularly important. There are diversified types of AD diagnosis data, such as cognitive tests, images, and risk factors, many prior investigations have primarily concentrated on integrating only high-dimensional features and simple fusion concatenation, resulting in less-than-optimal outcomes for AD diagnosis. Therefore, We propose an enhanced multimodal AD diagnostic framework comprising a feature-aware module and an automatic model fusion strategy (AMFS). To preserve the correlation and significance features within a low-dimensional space, the feature-aware module employs a low-dimensional SHapley Additive exPlanation (SHAP) boosting feature selection as the initial step, following this analysis, diverse tiers of low-dimensional features are extracted from patients' biological data. Besides, in the high-dimensional stage, the feature-aware module integrates cross-modal attention mechanisms to capture subtle relationships among different cognitive domains, neuroimaging modalities, and risk factors. Subsequently, we integrate the aforementioned feature-aware module with graph convolutional networks (GCN) to address heterogeneous data in multimodal AD, while also possessing the capability to perceive relationships between different modalities. Lastly, our proposed AMFS autonomously learns optimal parameters for aligning two sub-models. The validation tests using two ADNI datasets show the high accuracies of 95.9% and 91.9% respectively, in AD diagnosis. The methods efficiently select features from multimodal AD data, optimizing model fusion for potential clinical assistance in diagnostics.

Neuropsychological tests associated with symptomatic HIV-associated neurocognitive disorder (HAND) in a cohort of older adults in Tanzania

OBJECTIVE

Human immunodeficiency virus (HIV)-associated neurocognitive disorder (HAND) prevalence is expected to increase in East Africa as treatment coverage increases, survival improves, and this population ages. This study aimed to better understand the current cognitive phenotype of this newly emergent population of older combination antiretroviral therapy (cART)-treated people living with HIV (PLWH), in which current screening measures lack accuracy. This will facilitate the refinement of HAND cognitive screening tools for this setting.

METHOD

This is a secondary analysis of 253 PLWH aged ≥50 years receiving standard government HIV clinic follow-up in Kilimanjaro, Tanzania. They were evaluated with a detailed locally normed low-literacy neuropsychological battery annually on three occasions and a consensus panel diagnosis of HAND by Frascati criteria based on clinical evaluation and collateral history.

RESULTS

Tests of verbal learning and memory, categorical verbal fluency, visual memory, and visuoconstruction had an area under the receiver operating characteristic curve >0.7 for symptomatic HAND (s-HAND) (0.70-0.72; p < 0.001 for all tests). Tests of visual memory, verbal learning with delayed recall and recognition memory, psychomotor speed, language comprehension, and categorical verbal fluency were independently associated with s-HAND in a logistic mixed effects model (p < 0.01 for all). Neuropsychological impairments varied by educational background.

CONCLUSIONS

A broad range of cognitive domains are affected in older, well-controlled, East African PLWH, including those not captured in widely used screening measures. It is possible that educational background affects the observed cognitive impairments in this setting. Future screening measures for similar populations should consider assessment of visual memory, verbal learning, language comprehension, and executive and motor function.

Identification of amnestic mild cognitive impairment among Black and White community-dwelling older adults using NIH Toolbox Cognition tablet battery

OBJECTIVES

Identify which NIH Toolbox Cognition Battery (NIHTB-CB) subtest(s) best differentiate healthy controls (HC) from those with amnestic mild cognitive impairment (aMCI) and compare the discriminant accuracy between a model using a priori "Norm Adjusted" scores versus "Unadjusted" standard scores with age, sex, race/ethnicity, and education controlled for within the model. Racial differences were also examined.

METHODS

Participants were Black/African American (B/AA) and White consensus-confirmed (HC = 96; aMCI = 62) adults 60-85 years old that completed the NIHTB-CB for tablet. Discriminant function analysis (DFA) was used in the Total Sample and separately for B/AA (n = 80) and White participants (n = 78).

RESULTS

Picture Sequence Memory (an episodic memory task) was the highest loading coefficient across all DFA models. When stratified by race, differences were noted in the pattern of the highest loading coefficients within the DFAs. However, the overall discriminant accuracy of the DFA models in identifying HCs and those with aMCI did not differ significantly by race (B/AA, White) or model/score type (Norm Adjusted versus Unadjusted).

CONCLUSIONS

Racial differences were noted despite the use of normalized scores or demographic covariates-highlighting the importance of including underrepresented groups in research. While the models were fairly accurate at identifying consensus-confirmed HCs, the models proved less accurate at identifying White participants with an aMCI diagnosis. In clinical settings, further work is needed to optimize computerized batteries and the use of NIHTB-CB norm adjusted scores is recommended. In research settings, demographically corrected scores or within model correction is suggested.

The Role of the Neural Exposome as a Novel Strategy to Identify and Mitigate Health Inequities in Alzheimer's Disease and Related Dementias

With the continuous increase of the elderly population, there is an urgency to understand and develop relevant treatments for Alzheimer's disease and related dementias (ADRD). In tandem with this, the prevalence of health inequities continues to rise as disadvantaged communities fail to be included in mainstream research. The neural exposome poses as a relevant mechanistic approach and tool for investigating ADRD onset, progression, and pathology as it accounts for several different factors: exogenous, endogenous, and behavioral. Consequently, through the neural exposome, health inequities can be addressed in ADRD research. In this paper, we address how the neural exposome relates to ADRD by contributing to the discourse through defining how the neural exposome can be developed as a tool in accordance with machine learning. Through this, machine learning can allow for developing a greater insight into the application of transferring and making sense of experimental mouse models exposed to health inequities and potentially relate it to humans. The overall goal moving beyond this paper is to define a multitude of potential factors that can increase the risk of ADRD onset and integrate them to create an interdisciplinary approach to the study of ADRD and subsequently translate the findings to clinical research.

The impact of COVID-19 post-infection on the cognition of adults from Peru

Introduction

The COVID-19 pandemic, with over 83 million confirmed cases and 1.8 million deaths, has raised concerns about long-term cognitive issues, especially in populations facing disparities. Despite a few years since Peru's first COVID-19 wave, the cognitive effects on adults remain unclear. This study is the first in Peru to explore COVID-19's impact on general cognition and executive function.

Methods

A retrospective cross-sectional study compared individuals with COVID-19 history to controls, assessing general cognition, verbal fluency, attention, and executive function. Among 240 assessed, 154 met the study inclusion criteria, with about 60% female and an average age of 38.89 ± 16.001 years. Groups included controls (n = 42), acute phase (AP, n = 74) (1-14 days of symptoms), and hyperinflammatory phase (HP, n = 38) (>14 days of symptoms).

Results

Significant cognitive differences were observed. The HP group exhibited lower general cognitive performance (p = 0.02), working memory (p = 0.01), and executive function (planning; p < 0.001; flexibility; p = 0.03) than controls. Those with <14 days of illness (AP vs. HP) had deficits in general cognitive performance (p = 0.02), working memory (p = 0.02), and planning (p < 0.001), mainly during the hyperinflammatory phase, showing differences in working memory (p = 0.003) and planning (p = 0.01). Gender differences emerged, with males in the HP phase having poorer working memory (p = 0.003) and planning (p = 0.01).

Discussion

This study underscores COVID-19's negative impact on cognitive function, even in mild cases, with potential heightened effects in men during acute or hyperinflammatory phases. The findings provide Peru's first evidence, highlighting the vulnerability of populations facing socioeconomic disparities.

The Beneficial, Formative Role of Lifetime Exposures across Cognitive Domains in Barbados Using Data from the SABE Study

This study tested the hypothesis that within older Barbadian adults, sex, education, and occupation type lessen age-related cognitive decline. The analyses used a cross-sectional data set from 1325 people collected in the 2006 SABE Study (Health, Well-being, and Aging). Cognition was assessed as scores in each subdomain of the Mini-Mental State Exam. The loss of a single point in each subdomain was predicted by sex, years of education, job type, and their interactions with age. Results demonstrated that age and protective factors affect each cognitive domain differently. High education combined with mentally complex employment helped maintain cognitive performance in later life. Beneficial lifetime exposures are additive, providing combined benefits. Findings provide insight into public policy aiming to minimize the number of adults with cognitive decline and dementia in Barbados and the Caribbean.

Caring for Individuals with Alzheimer's Disease: A Spotlight on Hispanic Caregivers

 A caregiver is a constantly evolving role that an individual most likely undertakes at some point in their lifetime. With discoveries and research in increasing life expectancy, the prevalence of neurological-related diseases, such as Alzheimer's disease (AD) and dementia, is certainly likely to require more caregivers. The demand for AD caregivers is escalating as the prevalence of the disease continues to rise. The projected rise in AD within the Hispanic population in the United States over the next few decades is expected to be the most significant among all ethnic groups. The Hispanic population faces unique dementia risks due to cultural factors like language barriers, lower education, and limited healthcare access. Higher rates of conditions such as diabetes and cardiovascular disease further elevate dementia risk. Family dynamics and caregiving responsibilities also differ, affecting dementia management within Hispanic households. Addressing these distinct challenges requires culturally sensitive approaches to diagnosis, treatment, and support for Hispanic individuals and their family's facing dementia. With AD and other dementia becoming more prevalent, this article will attempt to expand upon the status of caregivers concerning their economic, health, and cultural statuses. We will attempt to focus on the Hispanic caregivers that live in Texas and more specifically, West Texas due to the lack of current literature that applies to this area of Texas. Lastly, we discuss the ramifications of a multitude of factors that affect caregivers in Texas and attempt to provide tools that can be readily available for Hispanics and others alike.

Characterizing Neighborhood Vulnerabilities in Mild Cognitive Impairment using the Environmental Justice Index

Background

There is a need for integration and comprehensive characterization of environmental determinants of Alzheimer's disease. The Environmental Justice Index (EJI) is a new measure that consolidates multiple environmental health hazards.

Objective

This analysis aims to explore how environmental vulnerabilities vary by race/ethnicity and whether they predict cognitive outcomes in a clinical trial of mild cognitive impairment (MCI).

Methods

We used data from a clinical trial of 107 MCI participants (28% minorities). Using the EJI, we extracted 40 measures of neighborhood environmental and social vulnerability including air and water pollution, access to recreational spaces, exposure to coal and lead mines, and area poverty. We also examined the relationship of the EJI to the Area Deprivation Index (ADI). Data was analyzed using regressions, correlations, and t-tests.

Results

Environmental Burden Rank (EBR) across the sample (0.53±0.32) was near the 50th percentile nationally. When divided by race/ethnicity, environmental (p = 0.025) and social (p < 0.0001) vulnerabilities were significantly elevated for minorities, specifically for exposure to ozone, diesel particulate matter, carcinogenic air toxins, and proximity to treatment storage and disposal sites. ADI state decile was not correlated with the EBR. Neither EBR nor ADI were a significant predictor of cognitive decline.

Conclusions

To our knowledge, this is the first study to link the EJI to an MCI trial. Despite limitations of a relatively small sample size, the study illustrates the potential of the EJI to provide deeper phenotyping of the exposome and diversity in clinical trial subjects.

Diagnostic accuracy of cognitive screening tools validated for older adults in Iran: a systematic review and meta-analysis

BACKGROUND

This systematic review aims to comprehensively assess the diagnostic accuracy of cognitive screening tools validated for older adults in Iran, providing evidence-based recommendations for clinicians and researchers.

METHODS

A comprehensive search in March 2023 across Web of Science, PubMed, Scopus, ScienceDirect, SID, IranMedex, and IranDoc, enhanced by hand-searching references and Google Scholar, identified cross-sectional studies on cognitive screening in Iranian seniors. We assessed diagnostic accuracy, cognitive domains, and test strengths and weaknesses. A bivariate random-effects meta-analysis provided summary estimates and 95% confidence intervals, illustrated in forest plots.

RESULTS

Our review, derived from an initial screening of 38 articles, focused on 17 studies involving 14 cognitive screening tools and participant counts from 60 to 350, mostly from specialized clinics. The MMSE was the only tool examined in at least three studies, prompting a meta-analysis revealing its sensitivity at 0.89 and specificity at 0.77 for dementia detection, albeit amidst significant heterogeneity (I^2 > 80%). ACE-III demonstrated the highest diagnostic accuracy for MCI and dementia, while MoCA's performance was deemed adequate for MCI and excellent for dementia. High bias risk in studies limits interpretation.

CONCLUSION

This review identifies key cognitive tools for dementia and MCI in Iranian older adults, tailored to educational levels for use in primary and specialized care. It emphasizes the need for further validation to enhance diagnostic precision across diverse settings, within a concise framework prioritizing brevity and accuracy for clinical applicability.

Toward a cross-cultural understanding of intraindividual variability metrics

OBJECTIVE

Compare the construct validity and predictive utility of cognitive intraindividual variability (IIV) in a sample of community-dwelling Hispanic and non-Hispanic white (NHW) older adults.

METHODS

The present study included annual data from 651 older adult control participants (Hispanic = 293; NHW = 358) enrolled in the Texas Alzheimer's Research and Care Consortium for at least 5 years. Mean composite z-scores were calculated for attention, language, memory, and executive domains. IIV was calculated as was the standard deviation both within (IIV-Within) and between (IIV-Between) these domains.

RESULTS

At baseline, NHW individuals obtained significantly higher mean scores in each domain than their Hispanic counterparts. They also showed significantly greater variability within and between domains, except for IIV-Within the language domain which was significantly larger in the Hispanic group. IIV-Between domains was driven primarily by IIV-Within the executive function domain in the NHW cohort and by IIV-Within the language domain in the Hispanic cohort. In both groups, the addition of IIV-Within and IIV-Between cognitive domains at baseline significantly improved prediction of global cognitive status after 5 years above and beyond demographic characteristics, genetic and cardiovascular risk. However, IIV-Between domains was the strongest predictor in the NHW group, while IIV-Within the attention domain was the strongest predictor in the Hispanic group.

CONCLUSIONS

Findings suggest that, while IIV-Between domains is a promising adjunctive method for predicting future cognitive decline, its construct validity and predictive utility varies based on ethnic group.

Handicraft art leisure activities and cognitive reserve

ObjectiveOlder individuals face a higher likelihood of developing dementia. The rate of cognitive decline resulting from dementia is not equivalent for all, as some patients with dementia are able to function independently longer than others, despite having similar disease burden. The cognitive reserve (CR) theory provides one explanation for the differing rate of decline. CR suggests that there are factors-most notably, educational attainment and occupational attainment-that can protect against the cognitive decline. Although the beneficial effects of these notable CR factors are clear, not all are easily modifiable. Participation in leisure activities may represent a more easily modifiable factor. Some research hints at beneficial effects of leisure activities, although specific leisure activities have not been well examined. The present study examined the relations between handicraft art leisure activities (HALAs) and multiple cognitive domains. MethodArchival WAIS-IV and demographic data for 50 California retirement community residents were examined. ResultsHALA participation accounted for statistically significant variance in working memory performance (R2 = .40, β = .24%) over and above the established CR factors of age, depression, educational attainment, and occupational attainment. In addition, HALA participation was related to a better ability to perform abstract visual information tasks (Block Design subtest, r = .28, p = .05) and non-verbal reasoning tasks (Visual Puzzles subtest, r = .38, p = .008). ConclusionsHALA participation among older adults could contribute to the retention of cognitive function, supporting the role of HALA participation as a CR factor.

Analyzing direct effects of education level and estimated IQ between cognitively intact Mexican Americans and Non-Hispanic whites on a confrontational naming task

Confrontational naming is widely used in diagnosing neurodegenerative disorders like MCI and dementia, and previous research indicates that healthy Non-Hispanic Whites outperform Hispanics in such tasks. However, understanding the factors contributing to score differences among ethnic groups remains limited. This study focuses on cognitively intact Mexican Americans and Non-Hispanic White older adults from the TARCC Hispanic Cohort project. Hierarchical regression analyses reveal that sex, age, ethnicity, education level, and estimated IQ significantly predict performance on the Boston Naming Test (BNT). Notably, education level and estimated IQ more strongly influence BNT performance in Mexican Americans than in Non-Hispanic Whites. When controlling for education level, estimated IQ has a more pronounced impact on BNT performance in aging Mexican Americans compared to Non-Hispanic Whites. Conversely, after controlling for estimated IQ, the influence of education level is weaker for Mexican Americans than Non-Hispanic Whites. These findings emphasize the need for careful evaluation of confrontational naming task scores in diverse ethnic groups, emphasizing the critical role of education and estimated IQ in understanding performance disparities.

A qualitative exploration of 40 Hz sound and music for older adults with mild cognitive impairment

Emerging evidence suggests that 40 Hz auditory stimulation may benefit cognition. Nested within a randomized crossover trial, this qualitative study evaluates the acceptability and experience of three auditory interventions-self-selected music, 40 Hz sound, and a novel combination, termed 40 Hz music-in individuals with Mild Cognitive Impairment (MCI). Semi-structured interviews were conducted with individuals with MCI post-intervention exposure. Findings indicated a preference for self-selected music due to its memory-boosting and emotional benefits, while responses to 40 Hz sound were mixed, with several participants reporting discomfort. The composite 40 Hz music intervention showed promise, striking a balance by enhancing user experience and mitigating the 40 Hz sound's negative aspects. Engagement was influenced by personal music interests, listening routines, and support networks. This study highlights the potential of integrating 40 Hz sound with personalized music to offer a more acceptable 40 Hz auditory intervention for cognition in older adults with MCI.

Vivaria housing conditions expose sex differences in brain oxidation, microglial activation, and immune system states in aged hAPOE4 mice

Apolipoprotein E ε4 allele (APOE4) is the predominant genetic risk factor for late-onset Alzheimer's disease (AD). APOE4 mouse models have provided advances in the understanding of disease pathogenesis, but unaccounted variables like rodent housing status may hinder translational outcomes. Non-sterile aspects like food and bedding can be major sources of changes in rodent microflora. Alterations in intestinal microbial ecology can cause mucosal barrier impairment and increase pro-inflammatory signals. The present study examined the role of sterile and non-sterile food and housing on redox indicators and the immune status of humanized-APOE4 knock-in mice (hAPOe4). hAPOE4 mice were housed under sterile conditions until 22 months of age, followed by the transfer of a cohort of mice to non-sterile housing for 2 months. At 24 months of age, the redox/immunologic status was evaluated by flow cytometry/ELISA. hAPOE4 females housed under non-sterile conditions exhibited: (1) higher neuronal and microglial oxygen radical production and (2) lower CD68+ microglia (brain) and CD8+ T cells (periphery) compared to sterile-housed mice. In contrast, hAPOE4 males in non-sterile housing exhibited: (1) higher MHCII+ microglia and CD11b+CD4+ T cells (brain) and (2) higher CD11b+CD4+ T cells and levels of lipopolysaccharide-binding protein and inflammatory cytokines in the periphery relative to sterile-housed mice. This study demonstrated that sterile vs. non-sterile housing conditions are associated with the activation of redox and immune responses in the brain and periphery in a sex-dependent manner. Therefore, housing status may contribute to variable outcomes in both the brain and periphery.

Iron Overload in Brain: Transport Mismatches, Microbleeding Events, and How Nanochelating Therapies May Counteract Their Effects

Iron overload in many brain regions is a common feature of aging and most neurodegenerative diseases. In this review, the causes, mechanisms, mathematical models, and possible therapies are summarized. Indeed, physiological and pathological conditions can be investigated using compartmental models mimicking iron trafficking across the blood-brain barrier and the Cerebrospinal Fluid-Brain exchange membranes located in the choroid plexus. In silico models can investigate the alteration of iron homeostasis and simulate iron concentration in the brain environment, as well as the effects of intracerebral iron chelation, determining potential doses and timing to recover the physiological state. Novel formulations of non-toxic nanovectors with chelating capacity are already tested in organotypic brain models and could be available to move from in silico to in vivo experiments.

Artificial intelligence approaches for early detection of neurocognitive disorders among older adults

Introduction

Dementia is one of the major global health issues among the aging population, characterized clinically by a progressive decline in higher cognitive functions. This paper aims to apply various artificial intelligence (AI) approaches to detect patients with mild cognitive impairment (MCI) or dementia accurately.

Methods

Quantitative research was conducted to address the objective of this study using randomly selected 343 Saudi patients. The Chi-square test was conducted to determine the association of the patient's cognitive function with various features, including demographical and medical history. Two widely used AI algorithms, logistic regression and support vector machine (SVM), were used for detecting cognitive decline. This study also assessed patients' cognitive function based on gender and developed the predicting models for males and females separately.

Results

Fifty four percent of patients have normal cognitive function, 34% have MCI, and 12% have dementia. The prediction accuracies for all the developed models are greater than 71%, indicating good prediction capability. However, the developed SVM models performed the best, with an accuracy of 93.3% for all patients, 94.4% for males only, and 95.5% for females only. The top 10 significant predictors based on the developed SVM model are education, bedtime, taking pills for chronic pain, diabetes, stroke, gender, chronic pains, coronary artery diseases, and wake-up time.

Conclusion

The results of this study emphasize the higher accuracy and reliability of the proposed methods in cognitive decline prediction that health practitioners can use for the early detection of dementia. This research can also stipulate substantial direction and supportive intuitions for scholars to enhance their understanding of crucial research, emerging trends, and new developments in future cognitive decline studies.

Examining racial differences in the network structure and properties of specific cognitive domains among older adults

Older adults oftentimes experience cognitive aging which leads to varying degrees of cognitive impairment. Previous studies have found that racial and ethnic disparities exist in the prevalence and severity of cognitive impairment among older adults. Yet, little is known on the relationship among specific cognitive domains and how this relationship differs between African American and White older adults. This is a secondary data analysis of Wave II (2010-2011) data from the National Social Life, Health, and Aging Project (NSHAP). A total of 2,471 older adults aged between 65 and 85 years old (African American n = 452, White n = 2019) were included. Network analysis was used to visualize and characterize the network structure and to examine network stability. Then, network comparison test was conducted to compare the network properties of the cognitive network structure between African American and White older adults. African American older adults had a lower cognitive function in all cognitive domains than White older adults. While there was no significant difference in global strength, there was a significant difference in the network structure and strength centrality measure between the two groups (p < 0.05). The invariance edge strength test found the language-visuospatial edge to be significantly stronger in African American older adults. Clinicians need to understand the different cognitive function across multiple cognitive domains between African American and White older adults and routinely offer targeted and timely cognitive assessment and management in this population.

Shifting From Active to Passive Monitoring of Alzheimer Disease: The State of the Research

Most research using digital technologies builds on existing methods for staff-administered evaluation, requiring a large investment of time, effort, and resources. Widespread use of personal mobile devices provides opportunities for continuous health monitoring without active participant engagement. Home-based sensors show promise in evaluating behavioral features in near real time. Digital technologies across these methodologies can detect precise measures of cognition, mood, sleep, gait, speech, motor activity, behavior patterns, and additional features relevant to health. As a neurodegenerative condition with insidious onset, Alzheimer disease and other dementias (AD/D) represent a key target for advances in monitoring disease symptoms. Studies to date evaluating the predictive power of digital measures use inconsistent approaches to characterize these measures. Comparison between different digital collection methods supports the use of passive collection methods in settings in which active participant engagement approaches are not feasible. Additional studies that analyze how digital measures across multiple data streams can together improve prediction of cognitive impairment and early-stage AD are needed. Given the long timeline of progression from normal to diagnosis, digital monitoring will more easily make extended longitudinal follow-up possible. Through the American Heart Association-funded Strategically Focused Research Network, the Boston University investigative team deployed a platform involving a wide range of technologies to address these gaps in research practice. Much more research is needed to thoroughly evaluate limitations of passive monitoring. Multidisciplinary collaborations are needed to establish legal and ethical frameworks for ensuring passive monitoring can be conducted at scale while protecting privacy and security, especially in vulnerable populations.

Alzheimer's Disease and Related Dementias in Muslim Women: Recommendations for Culturally Sensitive Care

Alzheimer's disease and related dementias (ADRD) present significant challenges including cognitive and functional loss, behavioral disruption, emotional distress, and significant financial burden. These stressors are amplified in minority groups, who experience higher rates of ADRD but less frequent and later diagnosis. There is therefore a critical need to identify tangible approaches to culturally informed dementia assessment and care for patients from diverse communities. Muslim patients and particularly Muslim women are among the populations most understudied in the ADRD space. Muslim patients may hold unique religious, spiritual, and cultural beliefs and practices that can impact care-seeking for dementia symptoms, diagnostic accuracy, and treatment uptake. This paper outlines culturally informed approaches to assessing and treating Muslim women and families at each stage of ADRD care, though many recommendations extend to the broader Muslim community and others of diverse racial-ethnic backgrounds. We provide concrete suggestions for building rapport within and leveraging common family structures, respecting principles of modesty and privacy for all women including those who observe hijab or niqab, and communicating dementia diagnosis and care in the context of spiritual and ethical beliefs. While not intended as a comprehensive and prescriptive guide, this review provides important points of consideration and discussion with patients of Muslim backgrounds.

Assessment of Language Function in Older Mandarin-Speaking Adults with Mild Cognitive Impairment using Multifaceted Language Tests

BACKGROUND

Individuals with amnestic mild cognitive impairment (aMCI), especially for those with multidomain cognitive deficits, should be clinically examined for determining risk of developing Alzheimer's disease. English-speakers with aMCI exhibit language impairments mostly at the lexical-semantic level. Given that the language processing of Mandarin Chinese is different from that of alphabetic languages, whether previous findings for English-speakers with aMCI can be generalized to Mandarin Chinese speakers with aMCI remains unclear.

OBJECTIVE

This study examined the multifaceted language functions of Mandarin Chinese speakers with aMCI and compared them with those without cognitive impairment by using a newly developed language test battery.

METHODS

Twenty-three individuals with aMCI and 29 individuals without cognitive impairment were recruited. The new language test battery comprises five language domains (oral production, auditory and reading comprehension, reading aloud, repetition, and writing).

RESULTS

Compared with the controls, the individuals with aMCI exhibited poorer performance in the oral production and auditory and reading comprehension domains, especially on tests involving effortful lexical and semantic processing. Moreover, the aMCI group made more semantic naming errors compared with their counterparts and tended to experience difficulty in processing items belonging to the categories of living objects.

CONCLUSIONS

The pattern identified in the present study is similar to that of English-speaking individuals with aMCI across multiple language domains. Incorporating language tests involving lexical and semantic processing into clinical practice is essential and can help identify early language dysfunction in Mandarin Chinese speakers with aMCI.

Virtual reality and cognitive rehabilitation for older adults with mild cognitive impairment: A systematic review

Virtual Reality (VR) has been gaining increasing attention as a potential ecological and effective intervention system for treating Mild Cognitive Impairment (MCI). However, it remains unclear the efficacy and effectiveness of VR-based cognitive rehabilitation therapy (VR-CRT) in comparison with cognitive rehabilitation therapy (CRT). Consequently, a systematic review on Pubmed, Scopus, PsycInfo, and Web Of Science was conducted to assess the state of the art of the literature published between 2003 and April 2023. Only articles that adopted CRT as control group and that included some measure of at least one domain among overall cognitive function, executive function and functional status were included. Participants needed to be older adults aged 65 or over with a diagnosis of MCI. The risk of bias and the quality of evidence were assessed using the Version 2 of the Cochrane risk-of-bias tool for randomized trials. Initially, 6503 records were considered and screened after removing duplicates (n = 1321). Subsequently, 81 full texts were assessed for eligibility. Four articles met the inclusion criteria but 2 of them were merged as they were describing different outcomes of the same research project. Consequently, 3 overall studies with a total of 130 participants were included in the final analysis. Due to the high heterogeneity in the methodology and outcome measures employed, it was not possible to conduct a meta-analysis. Included studies used semi-immersive (k = 2) and full-immersive (k = 1) VR systems in their research. Two articles evaluated overall cognitive function through the MoCA together with specific tests for executive functions (n = 69), while one study adopted a comprehensive neuropsychological battery to evaluate both cognitive function and executive function (n = 61). Finally, one study evaluated functional status through instrumental activities of daily living (n = 34). A However, the limited number of studies, the small sample size, and the potential issues with the quality and methodology of these studies that emerged from the risk of bias assessment may raise doubts about the reliability of their results. Nevertheless, although scarce, results of the present review suggest that VR-CRT may be paramount in treating MCI for its additional ecological and adaptive advantages, as all of the studies highlighted that it was at least as effective as conventional CRT for all the outcome measures. Therefore, more rigorous research that compares VR-CRT and CRT is needed to understand the degree to which VR-CRT is effective with older adults with MCI and the potential role of immersion to influence its efficacy. Indeed, these preliminary findings highlight the need for the development of standardized VR protocols, as the integration of such technology into clinical practice may help improve the quality of life and cognitive outcomes for this growing demographic.

Mitochondrial Inherited Disorders and their Correlation with Neurodegenerative Diseases

Mitochondria are essential organelles for the survival of a cell because they produce energy. The cells that need more mitochondria are neurons because they perform a variety of tasks that are necessary to support brain homeostasis. The build-up of abnormal proteins in neurons, as well as their interactions with mitochondrial proteins, or MAM proteins, cause serious health issues. As a result, mitochondrial functions, such as mitophagy, are impaired, resulting in the disorders described in this review. They are also due to mtDNA mutations, which alter the heritability of diseases. The topic of disease prevention, as well as the diagnosis, requires further explanation and exploration. Finally, there are treatments that are quite promising, but more detailed research is needed.

Correlations between Dementia and Loneliness

This review describes associations between dementia and loneliness on the neurobiological and epidemiological levels according to the recent body of literature. The aim of this study was to highlight major lines of research in this field. Sociocognitive skills and social interactions present complex interdependencies with dementia which may be explained by two theories. According to the first one, not sufficiently engaging in social or cognitive activities results in brain atrophy. The second one claims that brain neurogenesis and synaptic density are being increased by social connections. The relationship between loneliness and dementia could be mediated by sensory loss, including hearing and visual impairment, as well as depression and psychotic symptoms. Loneliness itself might cause a depletion in sensory and cognitive stimulation which results in a decrease in neural reserve. Certain changes in the structures of the brain caused by loneliness were found in imaging examination. Loneliness appears to be a crucial risk factor for dementia in recent times due to the modern lifestyle and consequences of the outbreak of COVID-19. Additional studies are required to understand more completely the key tenets of this topic and therefore to improve the prevention and treatment of dementia.

Alzheimer`s disease mortality in the United States: Cross-sectional analysis of county-level socio-environmental factors

BACKGROUND

Geographical disparities in mortality among Alzheimer`s disease (AD) patients have been reported and complex sociodemographic and environmental determinants of health (SEDH) may be contributing to this variation. Therefore, we aimed to explore high-risk SEDH factors possibly associated with all-cause mortality in AD across US counties using machine learning (ML) methods.

METHODS

We performed a cross-sectional analysis of individuals ≥65 years with any underlying cause of death but with AD in the multiple causes of death certificate (ICD-10,G30) between 2016 and 2020. Outcomes were defined as age-adjusted all-cause mortality rates (per 100,000 people). We analyzed 50 county-level SEDH and Classification and Regression Trees (CART) was used to identify specific county-level clusters. Random Forest, another ML technique, evaluated variable importance. CART`s performance was validated using a "hold-out" set of counties.

RESULTS

Overall, 714,568 individuals with AD died due to any cause across 2,409 counties during 2016-2020. CART identified 9 county clusters associated with an 80.1% relative increase of mortality across the spectrum. Furthermore, 7 SEDH variables were identified by CART to drive the categorization of clusters, including High School Completion (%), annual Particulate Matter 2.5 Level in Air, live births with Low Birthweight (%), Population under 18 years (%), annual Median Household Income in US dollars ($), population with Food Insecurity (%), and houses with Severe Housing Cost Burden (%).

CONCLUSION

ML can aid in the assimilation of intricate SEDH exposures associated with mortality among older population with AD, providing opportunities for optimized interventions and resource allocation to reduce mortality among this population.

Association between cerebrospinal fluid clusterin and biomarkers of Alzheimer's disease pathology in mild cognitive impairment: a longitudinal cohort study

Background

Clusterin, a glycoprotein implicated in Alzheimer's disease (AD), remains unclear. The objective of this study was to analyze the effect of cerebrospinal fluid (CSF) clusterin in relation to AD biomarkers using a longitudinal cohort of non-demented individuals.

Methods

We gathered a sample comprising 86 individuals under cognition normal (CN) and 134 patients diagnosed with MCI via the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. To investigate the correlation of CSF clusterin with cognitive function and markers of key physiological changes, we employed multiple linear regression and mixed-effect models. We undertook a causal mediation analysis to inspect the mediating influence of CSF clusterin on cognitive abilities.

Results

Pathological characteristics associated with baseline Aβ42, Tau, brain volume, exhibited a correlation with initial CSF clusterin in the general population, Specifically, these correlations were especially prominent in the MCI population; CSF Aβ42 (PCN = 0.001; PMCI = 0.007), T-tau (PCN < 0.001; PMCI < 0.001), and Mid temporal (PCN = 0.033; PMCI = 0.005). Baseline CSF clusterin level was predictive of measurable cognitive shifts in the MCI population, as indicated by MMSE (β = 0.202, p = 0.029), MEM (β = 0.186, p = 0.036), RAVLT immediate recall (β = 0.182, p = 0.038), and EF scores (β = 0.221, p = 0.013). In MCI population, the alterations in brain regions (17.87% of the total effect) mediated the effect of clusterin on cognition. It was found that variables such as age, gender, and presence of APOE ε4 carrier status, influenced some of these connections.

Conclusion

Our investigation underscored a correlation between CSF clusterin concentrations and pivotal AD indicators, while also highlighting clusterin's potential role as a protective factor for cognitive abilities in MCI patients.

Systematic review: fluid biomarkers and machine learning methods to improve the diagnosis from mild cognitive impairment to Alzheimer's disease

Mild cognitive impairment (MCI) is often considered an early stage of dementia, with estimated rates of progression to dementia up to 80-90% after approximately 6 years from the initial diagnosis. Diagnosis of cognitive impairment in dementia is typically based on clinical evaluation, neuropsychological assessments, cerebrospinal fluid (CSF) biomarkers, and neuroimaging. The main goal of diagnosing MCI is to determine its cause, particularly whether it is due to Alzheimer's disease (AD). However, only a limited percentage of the population has access to etiological confirmation, which has led to the emergence of peripheral fluid biomarkers as a diagnostic tool for dementias, including MCI due to AD. Recent advances in biofluid assays have enabled the use of sophisticated statistical models and multimodal machine learning (ML) algorithms for the diagnosis of MCI based on fluid biomarkers from CSF, peripheral blood, and saliva, among others. This approach has shown promise for identifying specific causes of MCI, including AD. After a PRISMA analysis, 29 articles revealed a trend towards using multimodal algorithms that incorporate additional biomarkers such as neuroimaging, neuropsychological tests, and genetic information. Particularly, neuroimaging is commonly used in conjunction with fluid biomarkers for both cross-sectional and longitudinal studies. Our systematic review suggests that cost-effective longitudinal multimodal monitoring data, representative of diverse cultural populations and utilizing white-box ML algorithms, could be a valuable contribution to the development of diagnostic models for AD due to MCI. Clinical assessment and biomarkers, together with ML techniques, could prove pivotal in improving diagnostic tools for MCI due to AD.

Plasma biomarkers identify older adults at risk of Alzheimer's disease and related dementias in a real-world population-based cohort

INTRODUCTION

Plasma biomarkers-cost effective, non-invasive indicators of Alzheimer's disease (AD) and related disorders (ADRD)-have largely been studied in clinical research settings. Here, we examined plasma biomarker profiles and their associated factors in a population-based cohort to determine whether they could identify an at-risk group, independently of brain and cerebrospinal fluid biomarkers.

METHODS

We measured plasma phosphorylated tau181 (p-tau181), neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), and amyloid beta (Aβ)42/40 ratio in 847 participants from a population-based cohort in southwestern Pennsylvania.

RESULTS

K-medoids clustering identified two distinct plasma Aβ42/40 modes, further categorizable into three biomarker profile groups: normal, uncertain, and abnormal. In different groups, plasma p-tau181, NfL, and GFAP were inversely correlated with Aβ42/40, Clinical Dementia Rating, and memory composite score, with the strongest associations in the abnormal group.

DISCUSSION

Abnormal plasma Aβ42/40 ratio identified older adult groups with lower memory scores, higher dementia risks, and higher ADRD biomarker levels, with potential implications for population screening.

HIGHLIGHTS

Population-based plasma biomarker studies are lacking, particularly in cohorts without cerebrospinal fluid or neuroimaging data. In the Monongahela-Youghiogheny Healthy Aging Team study (n = 847), plasma biomarkers associated with worse memory and Clinical Dementia Rating (CDR), apolipoprotein E ε4, and greater age. Plasma amyloid beta (Aβ)42/40 ratio levels allowed clustering participants into abnormal, uncertain, and normal groups. Plasma Aβ42/40 correlated differently with neurofilament light chain, glial fibrillary acidic protein, phosphorylated tau181, memory composite, and CDR in each group. Plasma biomarkers can enable relatively affordable and non-invasive community screening for evidence of Alzheimer's disease and related disorders pathophysiology.

Education counteracts the genetic risk of Alzheimer's disease without an interaction effect

Background

Alzheimer's disease (AD) is a major cause of disability and mortality in older adults. This study aimed to investigate the association of AD with education and genetic factors.

Methods

We conducted a prospective cohort study using data from the UK Biobank. Genetic risk was assessed using a polygenic risk score for AD. The educational level was categorized as either low, intermediate, or high. AD was defined using the International Classification of Diseases and Related Health Problems, 10th revision. Logistic regression models were used to investigate the independent and combined effects of genetic factors and educational levels on the risk of AD.

Results

We included 318,535 participants in this study (age: 56.53 ± 8.09 years; male: 44.81%). Compared with a low genetic risk, a high genetic risk was associated with a significantly greater risk of AD (OR = 7.09, 95% CI: 6.09-8.26). A high educational level was associated with a 30% lower risk of AD compared with a low educational level (OR = 0.70, 95% CI: 0.60-0.81). Combining genetic risk and education categories, individuals with a low genetic risk and high educational level had a more than 90% (OR = 0.09, 95% CI: 0.05-0.16) lower risk of AD compared to those with a high genetic risk and low educational level. There was no significant interaction between genetic risk and educational level regarding AD risk (p for interaction = 0.359).

Conclusion

Education counteracts the genetic risk of AD, without an interaction effect. Increasing education to reduce the incidence of AD is of same importance across individuals with different genetic risk.

Iron metabolism: An emerging therapeutic target underlying the anti-Alzheimer's disease effect of ginseng

Finding neuroprotective drugs with fewer side effects and more efficacy has become a major problem as the global prevalence of Alzheimer's disease (AD) rises. Natural drugs have risen to prominence as potential medication candidates. Ginseng has a long history of use in China, and it has a wide range of pharmacological actions that can help with neurological issues. Iron loaded in the brain has been linked to AD pathogenesis. We reviewed the regulation of iron metabolism and its studies in AD and explored how ginseng might regulate iron metabolism and prevent or treat AD. Researchers utilized network pharmacology analysis to identify key factive components of ginseng that protect against AD by regulating ferroptosis. Ginseng and its active ingredients may benefit AD by regulating iron metabolism and targeting ferroptosis genes to inhibit the ferroptosis process. The results present new ideas for ginseng pharmacological studies and initiatives for further research into AD-related drugs. To provide comprehensive information on the neuroprotective use of ginseng to modulate iron metabolism, reveal its potential to treat AD, and provide insights for future research opportunities.

The influence of culture and cognitive reserve on the clinical presentation of behavioural-variant frontotemporal dementia

Characterisation of the clinical profile of behavioural-variant frontotemporal dementia (bvFTD) has predominantly been based on Western samples. Some small studies have suggested that the clinical profile may differ in culturally and linguistically diverse populations. Additionally, there is evidence that patients from non-English speaking backgrounds may have more cognitive reserve, allowing them to tolerate more disease pathology before clinical symptoms emerge. This study aims to characterise the clinical profiles of patients with bvFTD from culturally diverse backgrounds. BvFTD patients were classified as Australian-born (Australian) or Culturally and Linguistically Diverse-English-speaking (CALD-English) and Culturally and Linguistically Diverse-Language Other Than English (CALD-LOTE). Clinical features, cognitive test performance and cognitive reserve were compared between groups. Voxel-based morphometry was used to examine the neural correlates of cognitive reserve. 107 patients with bvFTD (53 Australian, 36 CALD-English, 18 CALD-LOTE) and 51 controls were included. Analysis of neuropsychiatric features revealed more elation in Australian patients compared to CALD-English patients, with trends for CALD-LOTE patients to report more irritability. CALD-LOTE patients also had higher cognitive reserve and showed relatively greater verbal than non-verbal cognitive impairment. Neuroimaging analyses revealed that higher cognitive reserve was associated with lower integrity in the frontal-temporal regions associated with typical disease pathology in bvFTD. Our findings support the hypothesis that cognitive reserve may delay early cognitive decline in culturally and linguistically diverse patients, although these patients may still show poor verbal performance due to cultural testing biases. Clinically, these results highlight the need to consider cultural and linguistic background to inform the assessment of dementia.

Validation of the cross-cultural dementia screening test in Alzheimer's disease and Parkinson's disease

Objective

The Cross-Cultural Dementia (CCD) is a new screening tool to evaluate cognitive impairment based on a cross-cultural perspective to reduce the bias of education, and language and cultural differences. We aimed to evaluate the diagnostic properties of the CCD in Spaniards for the assessment of patients with Alzheimer's disease in mild cognitive impairment (AD-MCI) and mild dementia stages (AD-D) and patients with mild cognitive impairment associated with Parkinson's disease (PD-MCI).

Methods

Sixty participants with AD (50% MCI) and thirty with PD-MCI were enrolled. Each clinical group was compared against a healthy control group (HC) with the same number of participants and no significant differences in age, education, and sex. A comprehensive neuropsychological test battery and CCD were completed. Intergroup comparisons, ROC curves, and cut-off scores were calculated for the study of diagnostic properties.

Results

Intergroup differences were found in accordance with the cognitive profile of each clinical condition. Memory measures (Objects test) were especially relevant for the classification between AD and HC. Memory and executive function scores (Sun-Moon and Dots tests) were useful in the case of PD-MCI and HC. Furthermore, CCD described differences in executive functions and speed scores comparing AD-MCI and PD-MCI. Correlations between standardized neuropsychological tests and CCD measures supported the convergent validity of the test.

Conclusion

CCD showed good discrimination properties and cut-off scores for dementia and extended its application to a sample of prodromal stages of AD and PD with mild cognitive impairment.

Race and Ethnicity in Lewy Body Dementia: A Narrative Review

Lewy body dementia is the third most common and costliest type of dementia. It is an umbrella term for dementia with Lewy bodies and Parkinson's disease dementia, both of which place a substantial burden on the person and society. Recent findings outline ethnoracial differences in dementia risk. Delayed and misdiagnosis across ethnoracial groups contribute to higher levels of burden. In this context, we aimed to summarize current knowledge, gaps, and unmet needs relating to race and ethnicity in Lewy body dementia. In this narrative review, we provide an overview of studies on Lewy body dementia focusing on differences across ethnoracial groups and outline several recommendations for future studies. The majority of the findings comparing different ethnoracial groups were from North American sites. There were no differences in clinical prevalence and progression across ethnoracial groups. Compared to people identifying as non-Hispanic White, co-pathologies were more common and clinical diagnostic accuracy was lower for people identifying as Black. Co-morbidities (e.g., diabetes, hypertension) were more common and medication use rates (e.g., antidepressants, antiparkinsonian agents) were lower for people identifying as Black or Hispanic compared to people identifying as White. More than 90% of clinical trial participants identified as non-Hispanic White. Despite increasing efforts to overcome disparities in Alzheimer's disease and related dementias, inclusion of individuals from minoritized communities in Lewy body dementia studies continues to be limited and the findings are inconclusive. Representation of diverse populations is crucial to improve the diagnostic and therapeutic efforts in Lewy body dementia.

Inter-Hospital Advanced and Mild Alzheimer's Disease Classification Based on Electroencephalogram Measurements via Classical Machine Learning Algorithms

BACKGROUND

In pursuit of diagnostic tools capable of targeting distinct stages of Alzheimer's disease (AD), this study explores the potential of electroencephalography (EEG) combined with machine learning (ML) algorithms to identify patients with mild or moderate AD (ADM) and advanced AD (ADA).

OBJECTIVE

This study aims to assess the classification accuracy of six classical ML algorithms using a dataset of 668 patients from multiple hospitals.

METHODS

The dataset comprised measurements obtained from 668 patients, distributed among control, ADM, and ADA groups, collected from five distinct hospitals between 2011 and 2022. For classification purposes, six classical ML algorithms were employed: support vector machine, Bayesian linear discriminant analysis, decision tree, Gaussian Naïve Bayes, K-nearest neighbor and random forest.

RESULTS

The RF algorithm exhibited outstanding performance, achieving a remarkable balanced accuracy of 93.55% for ADA classification and 93.25% for ADM classification. The consistent reliability in distinguishing ADA and ADM patients underscores the potential of the EEG-based approach for AD diagnosis.

CONCLUSIONS

By leveraging a dataset sourced from multiple hospitals and encompassing a substantial patient cohort, coupled with the straightforwardness of the implemented models, it is feasible to attain notably robust results in AD classification.

Validation of the European Cross-Cultural Neuropsychological Test Battery (CNTB) for the assessment of mild cognitive impairment due to Alzheimer's disease and Parkinson's disease

Background

The Cross-Cultural Neuropsychological Test Battery (CNTB) is a novel test battery specifically designed to reduce the impact of multiculturality in cognitive assessment.

Objective

We aimed to validate the CNTB in Spaniards in patients with Alzheimer's disease (AD), including patients at mild cognitive impairment (MCI) and mild dementia stages, and Parkinson's disease with MCI (PD-MCI).

Methods

Thirty patients with AD-MCI, 30 with AD-dementia (AD-D), and 30 with PD-MCI were recruited. Each clinical group was compared against a healthy control group (HC) with no differences in sex, age, or years of education. Intergroup comparisons, ROC analysis, and cut-off scores were calculated.

Results

AD-MCI scored lower than HC in those subtests associated with episodic memory and verbal fluency. AD-D also showed lower scores in executive functions and visuospatial tests. Effect sizes for all the subtests were large. PD-MCI showed lower performance than HC in memory and executive functions, particularly on error scores, with large effect sizes. Comparing AD-MCI and PD-MCI, AD-MCI had lower memory scores, while PD-MCI showed the worst performance in executive functions. CNTB showed appropriate convergent validity with standardized neuropsychological tests measuring the same cognitive domains. We obtained similar cut-off scores to previous studies performed in other populations.

Conclusions

The CNTB showed appropriate diagnostic properties in AD and PD, including those stages with mild cognitive impairment. This supports the utility of the CNTB for the early detection of cognitive impairment in AD and PD.

Normative Data in Cross-Cultural Neuropsychological Instruments in Spaniards and Colombians Living in Spain

BACKGROUND

Cross-Cultural Dementia Screening (CCD), Rowland Universal Dementia Assessment Scale (RUDAS), and European Cross-cultural Neuropsychological Test Battery (CNTB) are three novel neuropsychological instruments developed from a cross-cultural perspective to reduce the impact of culture in cognitive assessment and improve the assessment in diverse populations.

OBJECTIVE

We aimed to collect and present normative data on these tests in a majority population sample (Spaniards living in Spain) and in a minority population sample (Colombians living in Spain).

METHODS

CCD, RUDAS, and CNTB were administered to a group of 300 cognitively healthy participants (150 Spaniards and 150 Colombians). Linear regression modeling strategy was used to provide adjusted norms for demographic factors and to explore the influence of these factors on test performance.

RESULTS

Most of the CCD and CNTB scores were predicted by age and years of education, with some tests only predicted by age or showing a ceiling effect. The comparison of normative data between the two samples confirmed the favorable cross-cultural properties of these instruments, with only some differences in processing speed and executive functioning scores.

CONCLUSIONS

Our study finds a comparable influence of demographic factors in both populations on the performance of CCD, RUDAS, and CNTB, confirming their adequate cross-cultural properties. We provide normative data for these tests in Spaniards and Colombians living in Spain.

Education bias in typical brief cognitive tests used for the detection of dementia in elderly population with low educational level: a critical review

Dementia is a significant decline in cognition that interfere with independent, daily functioning. Dementia is a syndrome caused by a myriad and include primary neurologic, neuropsychiatric, and medical conditions. It has been projected that the prevalence of dementia will triple in the elderly population by the year 2050. Despite the benefits of early diagnosis, there is an effective under-detection of around 62% of people with mild cognitive impairment (MCI) or dementia. One of the factors associated with this problem is that diagnostic techniques are affected by the educational level of those evaluated. This is an important aspect to consider in the use of brief cognitive tests for the detection of dementia. This review presents and critically analyzes the available evidence regarding the effect of educational level on the diagnostic utility of three of the most widely used tools in the clinical setting: the Mini-mental Test Examination (MMSE), the Montreal Cognitive Assessment (MoCA), and the Addenbrooke's Cognitive Examination (ACE). Previous evidence shows that the tasks that require reading, writing, calculation, phonological fluency, and visuoconstruction are affected by educational level. These results lead to discourage the use of these tests in older people with less than 6 years of schooling. The development of brief cognitive tests appropriate for people with a low educational level is recommended. We posit that adequate cognitive tests should not consider tasks or items that resemble characteristics of academic contexts and should be more analogous to daily activities situations.

Validation of a digit symbol substitution test for use in supervised and unsupervised assessment in mild Alzheimer's disease

INTRODUCTION

The Digit-Symbol-Substitution Test (DSST) is used widely in neuropsychological investigations of Alzheimer's Disease (AD). A computerized version of this paradigm, the DSST-Meds, utilizes medicine-date pairings and has been developed for administration in both supervised and unsupervised environments. This study determined the utility and validity of the DSST-Meds for measuring cognitive dysfunction in early AD.

METHOD

Performance on the DSST-Meds was compared to performance on the WAIS Coding test, and a computerized digit symbol coding test (DSST-Symbols). The first study compared supervised performance on the three DSSTs versions in cognitively unimpaired (CU) adults (n = 104). The second compared supervised DSST performance between CU (n = 60) and mild-symptomatic AD (mild-AD, n = 79) groups. The third study compared performance on the DSST-Meds between unsupervised (n= 621) and supervised settings.

RESULTS

In Study 1, DSST-Meds accuracy showed high correlations with the DSST-Symbols accuracy (r = 0.81) and WAIS-Coding accuracy (r = 0.68). In Study 2, when compared to CU adults, the mild-AD group showed lower accuracy on all three DSSTs (Cohen's d ranging between 1.39 and 2.56) and DSST-Meds accuracy was correlated moderately with Mini-Mental State Examination scores (r = 0.44, p < .001). Study 3 observed no difference in DSST-meds accuracy between supervised and unsupervised administrations.

CONCLUSION

The DSST-Meds showed good construct and criterion validity when used in both supervised and unsupervised contexts and provided a strong foundation to investigate the utility of the DSST in groups with low familiarity to neuropsychological assessment.

White matter integrity mediates the associations between white matter hyperintensities and cognitive function in patients with silent cerebrovascular diseases

OBJECTIVE

To evaluate the relationships between cognitive function and white matter hyperintensity volume (WMHV) in patients with silent cerebrovascular disease and to investigate whether white matter integrity or brain atrophy play a role in this association.

METHODS

Automated Fiber Quantification and Voxel- based morphometry were used to track and identify the integrity of 20 well-defined white matter tracts and to measure the gray matter volume (GMV). A linear regression model was applied for examining the associations between cognitive function and WMHV and mediation analysis was used to identify the roles of white matter integrity or GMV in the influence of WMHV on cognitive function.

RESULTS

Two hundred and thirty-six individuals were included for analysis. Executive function was linearly associated with fractional anisotropy (FA) of the right interior frontal occipital fasciculus (IFOF) (β = 0.193; 95% CI, 0.126 to 1.218) and with WMHV (β = -0.188; 95% CI, -0.372 to -0.037). Information processing speed was linearly associated with WMHV (β = -0.357; 95% CI, -0.643 to -0.245), FA of the right anterior thalamic radiation (ATR) (β = 0.207; 95% CI, 0.116 to 0.920), and FA of the left superior longitudinal fasciculus (SLF) (β = 0.177; 95% CI, 0.103 to 1.315). The relationship between WMHV and executive function was mediated by FA of the right IFOF (effect size = -0.045, 95% CI, -0.015 to -0.092). Parallel mediation analysis showed that the association between WMHV and information processing speed was mediated by FA of the right ATR (effect size = -0.099, 95% CI, -0.198 to -0.038) and FA of the left SLF (effect size = -0.038, 95% CI, -0.080 to -0.003).

CONCLUSION

These findings suggest a mechanism by which WMH affects executive function and information processing speed by impairing white matter integrity. This may be helpful in providing a theoretical basis for rehabilitation strategies of cognitive function in patients with silent cerebrovascular diseases.

The effect of risk factors on cognition in adult cochlear implant candidates with severe to profound hearing loss

Hearing loss has been identified as a major modifiable risk factors for dementia. Adult candidates for cochlear implantation (CI) represent a population at risk of hearing loss-associated cognitive decline. This study investigated the effect of demographics, habits, and medical and psychological risk factors on cognition within such a cohort. Data from 34 consecutive adults with post-lingual deafness scheduled for CI were analyzed. Pure tone audiometry (PTA4) and Speech Discrimination Score (SDS) were recorded. The Repeatable Battery for Assessment of Neuropsychological Status for Hearing impaired individuals (RBANS-H) was used to measure cognition. Demographics (sex, age, years of education), habits (smoking, alcohol intake, physical inactivity), and medical factors (hypertension, diabetes, traumatic brain injury) were evaluated. Depression was measured using the Hospital Anxiety and Depression Scale (HADS), and social inhibition with the Type D questionnaire (DS14). All participants (mean age 62 ± 15 years) suffered from severe to profound hearing loss (PTA4:129 ± 60 dB; SDS:14 ± 24%). The mean RBANS-H total score was 83 ± 16. Participants reported a mean of years of formal education of 12 ± 5 years. The prevalence of habits and medical risk factors was: physical inactivity (29%), body mass index >30 (28%), traumatic brain injury (25%), hypertension (24%), heavy alcohol consumption (13%), smoking (13%), and diabetes (0%). Regarding psychological factors, the mean scores of social inhibition and depression were 10 ± 6 and 6 ± 5, respectively. The number of years of education was significantly correlated with the RBANS-H total score (p < 0.001), and with the domains “Immediate memory” (p = 0.003), “Visuospatial/constructional” (p < 0.001), and “Attention” (p < 0.001). The mean RBANS-H total score in participants who had university studies or higher level (12/34) was 97 ± 9, with the remaining participants reporting a mean score of 75 ± 15. Men performed better in the “Visuospatial/constructional” (p = 0.008). Physical inactivity was associated with lower scores in the “Delayed memory” (p = 0.031); hypertension correlated with lower RBANS-H total scores (p = 0.025) and “Attention” (p = 0.006). Depression and social inhibition were negatively correlated with RBANS-H total score and with the “Immediate memory,” “Visuospatial/constructional,” and “Attention” (all p < 0.05). In adults with late-onset deafness scheduled to CI, educational level has a significant effect. Additionally, sex, physical inactivity, hypertension, and psychological traits of social inhibition and depression may also influence cognitive status. Long-term studies with more participants would enable us better understand the effects different risk factors on cognitive status.