Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring最新文献

Introduction: This study aimed to identify demographic and cognitive differences based on amyloid status in older Japanese adults without dementia, addressing the lack of data in East Asian populations for early Alzheimer's disease (AD) detection.

Methods: Analyzed baseline data from 630 participants from the Japanese Trial-Ready Cohort (J-TRC) study, all with a Clinical Dementia Rating-Global Score (CDR-GS) of 0 or 0.5. Amyloid status (Aβ+ or Aβ-) was determined by amyloid positron emission tomography (PET) scans.

Results: Among participants, 24.8% were Aβ+. In the cognitively unimpaired (CDR-GS 0) group, Aβ+ individuals reported slightly greater self-perceived cognitive concerns (Cognitive Function Instrument [CFI-self]). For those with mild impairment (CDR-GS 0.5), Aβ+ status was associated with worse clinical scores, greater cognitive complaints, more depressive symptoms, and poorer memory and global cognition.

Discussion: These findings align with major Western studies, emphasizing that CFI-self is a valuable tool for identifying early AD pathology across diverse populations.

Highlights: Comparing characteristics by amyloid status in Japanese non-demented older adults.Positron emission tomography-positive (PET+) scans in cognitively unimpaired individuals were associated with Cognitive Function Instrument-negative (CFI-) participants.PET+ in mild cognitive impairment (MCI) was linked to functional, cognitive, and affective decline.CFI- participants will aid early Alzheimer's pathology detection in diverse groups.

Introduction: Antipsychotic medication (APM) use in nursing home (NH) patients with dementia is common but carries risks. This study assessed the association between APM use and mortality, stroke, and myocardial infarction (MI) compared to non-use, as well as differences between first- and second-generation APMs.

Methods: A serial cross-sectional study using Medicare data examined outcomes from 2012 to 2015 in a national sample of 328,138 US NH residents aged 50 and older with dementia. Multivariate logistic regressions were used to analyze risk.

Results: APM use was associated with increased mortality in all years (odds ratio [OR] range: 2.39 to 1.23, all p < 0.001) and stroke risk from 2012 to 2014 (OR range: 1.17 to 1.10, p < 0.01) but not MI. First-generation APMs posed a higher mortality risk than second-generation APMs, with no significant stroke or MI differences.

Discussion: Findings highlight the need for cautious APM use in dementia patients in NHs due to elevated mortality and stroke risks.

Highlights: Study provides insights into APM risks in underrepresented nursing home (NH) dementia population.APM use in NH dementia patients is linked to higher death risk.First-generation APMs showed higher mortality risk than second-generation APMs.Overall, APM use is associated with increased stroke risk.No association was found between APM use and MI risk overall.

Early detection of Alzheimer's disease (AD), Parkinson's disease (PD), and mild cognitive impairment (MCI) is crucial for timely intervention. Traditional cognitive screening tools lack ecological validity and sensitivity. Virtual reality (VR) provides realistic, controlled environments for assessing multidimensional cognition. This systematic review evaluated the diagnostic accuracy, feasibility, and applicability of immersive VR assessments for neurodegenerative screening. We searched PubMed, PsycINFO, and Embase for studies published June 2005 to April 2024. Eligible studies used head-mounted displays in adults with MCI, early AD/PD, or dementia. Ten studies (n = 472) met criteria. Tasks targeted spatial memory, executive function, attention, and navigation. Several reported strong discriminations (area under the curve up to 0.89) and, when combined with machine learning, accuracies of 87% to 100%. Immersive VR shows promise as an ecologically valid, engaging, and scalable screening approach; however, standardization of tasks and outcomes, real-world validation, and robust longitudinal evidence are needed to support clinical adoption.

Highlights: This review systematically describes the application of fully immersive virtual reality (VR) in the early screening of neurodegenerative diseases, with a focus on studies using head-mounted devices to simulate real-life tasks.Task types such as spatial memory, daily living simulations, and executive function assessments have demonstrated high sensitivity and specificity in diagnosing mild cognitive impairment (MCI) and early-stage Alzheimer's disease (AD).Approximately one third of studies combined machine learning techniques to analyze multimodal behavioral data (e.g., path deviations, task duration, and language responses), significantly improving diagnostic accuracy.This study highlights methodological heterogeneity, small sample sizes, and the lack of longitudinal studies as current research limitations, and calls for future standardized, multicenter, and long-term follow-up studies to validate the predictive validity and real-world applicability of VR tools.

Introduction: Cognitive decline is a global health concern, making the identification of early, modifiable risk factors essential. While apathy is a recognized prodromal marker, procrastination may also signal early executive dysfunction.

Methods: We used longitudinal secondary data from the United States Health and Retirement Study among adults aged 60+ $\left(n=549;\overline{x}=69.70;s=7.58\right)$ . Cognitive function, procrastination, depression, and a proxy measure of apathy were assessed. Transitions between normative cognitive function, mild cognitive impairment (MCI), and dementia were modeled using a discrete-time first-order Markov model.

Results: Procrastination scores were higher among individuals with MCI or dementia than those with normative cognitive function. Procrastination also interacted with age, disproportionately increasing the risk of decline in the oldest participants.

Discussion: Procrastination was associated with cognitive impairment and predicted transitions to MCI, suggesting it may serve as both an early behavioral marker and compounding risk factor.

Highlights: Procrastination predicts cognitive decline in older adults.Effects remain after accounting for apathy.Longitudinal study links everyday behavior to dementia risk.Procrastination may be a potentially modifiable early behavioral marker.

Introduction: The National Insitutes of Health Toolbox (NIHTB) measures may be useful for Alzheimer's disease (AD) risk detection. This study investigates whether cognitively normal older adults with and without elevated brain amyloid, an early AD biomarker, differed on NIHTB cognitive and motor subtests and whether inclusion of pTau-217 enhanced this differentiation. Motor measures were of interest based on past research reporting linkages to early AD pathology.

Methods: Data from 112 consensus-diagnosed cognitively normal older adults who completed amyloid-PET imaging, blood draw for pTau217 analysis, and NIHTB Cognition and Motor batteries were analyzed using linear regression.

Results: Amyloid positivity significantly predicted performance on only NIHTB Standing Balance (F(2,86) = 9.90, p < 0.001). Inclusion of pTau217 enhanced prediction of Standing Balance (F(4,84) = 5.88, p < 0.001) and Walking Endurance (F(4,88) = 9.70, p < 0.001) and Dominant-hand Grip Strength (F(2,92) = 51.59, p < 0.001).

Discussion: For AD-related detection research, findings support inclusion of NIHTB motor measures, which may prove more sensitive early in the disease course before overt cognitive change.

Highlights: The National Institutes of Health ToolBox motor performance may signal early Alzheimer's disease (AD) risk, even before memory change.Balance performance may be sensitive to early cumulative AD-neuropathology loading.Motor measures should be included in early AD-risk detection batteries.

Introduction: We explored the relationship between cognitive screening outcomes and everyday functioning in Alzheimer's disease (AD).

Methods: A total of 1228 amyloid-positive participants were included from the Amsterdam Dementia Cohort. Multiple linear regression analyses assessed the relationship between Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and everyday functioning (Amsterdam Instrumental Activities of Daily Living Questionnaire [A-IADL-Q-30]). To link cognitive screeners to functional impairment, we described difficulties across A-IADL-Q-30 items by MMSE and MoCA quartiles.

Results: Both MMSE (B = 0.96, 95% confidence interval [CI]0.87-1.04) and MoCA (B = 0.79, 95% CI 0.68-0.89) were associated with A-IADL-Q-30. In the lowest MMSE (0-20) and MoCA (0-16) quartiles, filling in forms (both 96%) and managing the household budget (95%-93%) were mostly affected, whereas working (74%) and using a computer (52%-50%) were primarily affected in the highest quartiles (MMSE 28-30/MoCA 25-30).

Discussion: In amyloid-positive participants, the association between cognition and daily functioning was moderate, reinforcing the importance of assessing both constructs in disease monitoring.

Highlights: Cognitive screening tools were moderately associated with daily functioning.Difficulties in complex daily tasks were present in the higher cognitive performance quartiles.Findings suggest that combining cognition and function is required for disease monitoring.

Introduction: We aimed to evaluate the potential of the microglial marker transmembrane protein 119 (TMEM119) in the cerebrospinal fluid (CSF) as a (differential) diagnostic biomarker for neurodegenerative diseases.

Methods: Following assay validation, we used enzyme-linked immunosorbent assay to measure CSF TMEM119 in 174 patients from six diagnostic groups: Alzheimer's disease (AD, n = 35), amyotrophic lateral sclerosis (ALS, n = 33), cerebral microangiopathy (CM, n = 25), frontotemporal lobar degeneration (FTLD, n = 28), Lewy body diseases (n = 21), and non-neurodegenerative controls (n = 33).

Results: CSF TMEM119 levels were elevated in the AD group compared to the control (p = 0.004), CM (p = 0.005), and FTLD (p = 0.023) groups. Levels were higher in both mild cognitive impairment (MCI-AD) and dementia (ADD) subgroups when compared to controls. For the discrimination of AD from controls, the area under the curve (AUC) was 0.78.

Discussion: Our results indicate that CSF TMEM119 may have potential as a biomarker representing microglial involvement in early and later stages of AD.

Highlights: Elevated levels of TMEM119 were observed in the CSF of patients with AD.Increased CSF TMEM119 was seen in MCI-AD patients compared to controls.Elevated levels in MCI-AD underscore early microglial involvement in AD.In the AD group, an association was found between CSF TMEM119 and CSF total tau.CSF TMEM119 may provide valuable information on neuroinflammation.

Alzheimer's disease (AD) pathology begins years before symptoms emerge, making early detection essential. Eye tracking offers a rapid, non-invasive means of identifying early cognitive decline through oculomotor disturbances. This Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)- and Population, Intervention, Comparison, and Outcome (PICO)-guided systematic review evaluated studies from PubMed, ACM Digital Library, and Google Scholar on eye tracking in mild cognitive impairment (MCI), AD, and related dementias. Seventy-one studies met the inclusion criteria. Antisaccade tasks consistently distinguished AD and MCI from healthy controls, with impaired accuracy, longer latencies, and reduced gain. Non-saccadic paradigms (e.g., visual search, free viewing) indicated diminished exploratory behavior in AD, with mixed findings in MCI. A major limitation was the lack of cohorts defined by current biological criteria, hindering clinical translation. In a subset, classical machine-learning (ML) models and deep neural networks reported accuracies of 0.72 to 0.97. Overall, antisaccade tasks show strong promise for early AD screening; future work should adopt biologically defined cohorts and scalable, accessible eye-tracking technologies.

Highlights: Antisaccade tasks best distinguish AD and MCI from HCs.Visual search/free-view tasks showed diminished exploratory behavior in AD.Most studies lack biomarker-based AD criteria, creating a major research gap.

Introduction: Mild cognitive impairment (MCI) is a known risk factor for dementia and presents an opportunity for early engagement in preventative strategies, treatment, and advanced planning. However, little is known about MCI diagnosis rates among Medicare beneficiaries.

Methods: Using data from the 2014 to 2022 rounds of the National Health and Aging Trends Study (NHATS) linked with Medicare claims data, we identified the proportion of beneficiaries with symptoms of MCI, as defined by an NHATS algorithm, who received a diagnosis according to International Classification of Diseases codes. Univariate and multivariate logistic regressions were used to identify predictors of diagnosed MCI.

Results: Of beneficiaries identified by the NHATS algorithm, 10.6% had a recorded diagnosis of MCI. Odds of diagnosis were higher among women and beneficiaries with a bachelor's degree or higher, and lower among beneficiaries who attended doctor visits alone.

Discussion: Targeted initiatives are needed to increase MCI diagnosis rates, particularly in the era of novel diagnostic tests and therapies.

Highlights: We linked National Health and Aging Trends Study data to Medicare claims to identify the prevalence of diagnosed mild cognitive impairment (MCI).We identified 10.6% of Medicare beneficiaries with symptoms of MCI who have a diagnosis.Women and people with a bachelor's degree were more likely to have an MCI diagnosis.People who visited the doctor alone were less likely to have an MCI diagnosis.

Introduction: Type 2 diabetes (T2D) is associated with cognitive decline, but the role of APOE ε4 - a known Alzheimer's risk allele - in cognition among admixed populations with T2D remains unclear.

Methods: We analyzed 883 Brazilian adults with T2D (median age 68 years) from primary care, excluding those with dementia. Cognitive function was assessed using Mini-Mental State Examination (MMSE), and APOE genotypes were determined. MMSE errors were modeled using negative binomial regression.

Results: APOE alleles showed no association with MMSE errors overall. Older age and self-reported Black/Brown race predicted more errors, whereas higher education and physical activity predicted fewer. Sensitivity analyses indicated a possible inverse association between APOE ε4 and MMSE errors among self-reported Black/Brown participants.

Discussion: APOE ε4 was not associated with cognition in this cohort. The suggestive protective effect observed in Black/Brown participants should be considered hypothesis-generating, underscoring the need for further research in admixed populations with T2D.

Highlights: APOE ε4 was not linked to cognitive errors in the full T2D Brazilian cohort.Trend toward fewer MMSE errors among self-reported Black/Brown APOE ε4 carriers.Higher education, physical activity, and BMI were protective against MMSE errors.Black/Brown race and older age were associated with more MMSE errors.Results support multifactorial assessment and more studies in admixed T2D populations.