The Journal of Prevention of Alzheimer's Disease最新文献

Background: This analysis evaluated the potential cost-effectiveness of the Japan-Multimodal Intervention Trial for the prevention of dementia (J-MINT), targeting older adults with mild cognitive impairment (MCI) from a societal perspective.

Methods: Using a time-dependent cohort state-transition model, we estimated the long-term economic impact of J-MINT. Costs included medical, long-term, and informal care. Incremental cost-effectiveness ratios (ICERs) were calculated based on simulated costs and quality-adjusted life years (QALYs).

Results: The base-case analysis indicated that the J-MINT was dominant, demonstrating cost saving and more effective compared to usual care. Over 35 years, J-MINT was projected to achieve cost savings of JPY 452,826 per person and a gain of 0.08 QALYs. Deterministic and probabilistic sensitivity analyses confirmed the robustness of these findings. Scenario analysis suggested that targeting APOE ε4 carriers or individuals with high adherence to exercise yielded even greater benefits.

Conclusion: J-MINT demonstrates cost-effectiveness by reducing overall care costs while improving QALYs in individuals with MCI.

Background: Donanemab significantly slowed clinical progression in participants with early symptomatic Alzheimer's disease (AD) during the 76-week placebo-controlled period of TRAILBLAZER-ALZ 2.

Methods: Participants who completed the placebo-controlled period were eligible for the 78-week, double-blind, long-term extension (LTE). Early-start participants were randomized to donanemab in the placebo-controlled period. Delayed-start participants (randomized to placebo) started donanemab in the LTE. Participants who met amyloid treatment course completion criteria were switched to placebo. An external control cohort comprised participants from the AD Neuroimaging Initiative (ADNI).

Results: At 3 years, donanemab slowed disease progression on the Clinical Dementia Rating Scale (CDR)-Sum of Boxes (CDR-SB) in early-start participants versus a weighted ADNI control (-1.2 points; 95 % confidence interval [CI], -1.7, -0.7). Seventy-six weeks after initiating donanemab, delayed-start participants also demonstrated slower CDR-SB progression versus a weighted ADNI control (-0.8 points; 95 % CI, -1.3, -0.3). Participants who completed treatment by 52 weeks demonstrated similar slowing of CDR-SB progression at 3 years. Compared with delayed-start participants, early-start participants demonstrated a significantly lower risk of disease progression on the CDR-Global over 3 years (hazard ratio=0.73; p < 0.001). In both groups, >75 % of participants assessed by positron emission tomography 76 weeks after starting donanemab achieved amyloid clearance (<24.1 Centiloids). The addition of LTE data to prior modeling predicted a median reaccumulation rate of 2.4 Centiloids/year. No new safety signals were observed compared to the established donanemab safety profile.

Conclusions: Over 3 years, donanemab-treated participants with early symptomatic AD demonstrated increasing clinical benefits and a consistent safety profile, with limited-duration dosing.

Trial registration: ClinicalTrials.gov identifier NCT04437511.

Background: Cognitive resilience, the ability to maintain better than expected cognitive function despite neuropathological burden, is a key contributor to clinical outcomes in Alzheimer's disease (AD), though the underlying neurobiological mechanisms remain poorly understood.

Objectives: To determine whether hippocampal volume and microstructure moderate the relationship between early tau pathology and cognitive performance, thereby serving as potential markers of cognitive resilience.

Design: Cross-sectional observational study.

Setting: Participant data was obtained from the longitudinal BIOCARD Study, a volunteer-based research cohort.

Participants: The sample included 190 dementia-free adults (mean age = 68 years), comprising 176 cognitively unimpaired individuals and 14 with mild cognitive impairment (MCI).

Measurements: Hippocampal volume and microstructure (mean diffusivity (MD)) were measured using structural magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI), respectively. Tau pathology was measured using FMK-6240 tau PET imaging across Braak stages I-III. Cognitive performance was indexed using global and domain-specific composite scores. Regression models tested the interactions between hippocampal volume or MD and tau burden, adjusting for demographics, APOE genotype, amyloid status, and diagnostic status.

Results: Lower hippocampal MD (indicative of better microstructural integrity) attenuated the negative association between tau burden in Braak stages II-III and both global cognition and episodic memory (ps < 0.010). Logistic regression models indicated that lower hippocampal MD was associated with a weaker relationship between tau burden in Braak stages II-III and the likelihood of MCI diagnosis (ps < 0.050). In contrast, hippocampal volume did not moderate the relationship between tau and any cognitive outcome (ps > 0.250).

Conclusions: Hippocampal MD may serve as a promising imaging marker of cognitive resilience to early tau pathology, with potential utility for risk stratification and as a target for preventive interventions in AD.

Background and objectives: Estimated glucose disposal rate (eGDR) is a novel and reliable marker of insulin resistance (IR), yet its association with white matter hyperintensities (WMH) remains unclear. This study investigates the relationship between eGDR and WMH in a cohort from the UK Biobank.

Methods: We included 34,789 participants without a history of stroke or dementia at baseline. WMH volume was estimated from T2-FLAIR brain magnetic resonance imaging (MRI) scans acquired in 2014, normalized to intracranial volume, and log-transformed. Multiple linear regression models were used to examine the association between eGDR and WMH volume. Additionally, restricted cubic spline (RCS) analysis was employed to explore the dose-response relationship between eGDR and WMH volume.

Results: Each 1-SD increase in eGDR was significantly associated with a reduction in WMH volume (β = -0.057; 95% CI: -0.062 to -0.051; p < 0.001). Compared to participants in the lowest eGDR quartile (Q1), those in quartiles Q2, Q3, and Q4 exhibited progressively lower WMH volumes, with β coefficients of -0.068 (95% CI: -0.097 to -0.039), -0.199 (95% CI: -0.228 to -0.169), and -0.295 (95% CI: -0.330 to -0.259), respectively (p for trend < 0.001). RCS analysis demonstrated a significant linear inverse relationship between eGDR and WMH volume (p for nonlinearity > 0.05). Subgroup analyses indicated consistent associations across most predefined groups.

Conclusion: Lower eGDR levels are associated with a greater burden of WMH, suggesting that eGDR may serve as a potential marker for predicting WMH burden in future clinical practice.

Background and aim: Fasting insulin variability has emerged as a potential marker of metabolic dysregulation, but its long-term implications for cognitive function remain unclear. This study aimed to clarify the role of long-term fasting insulin variability in predicting individual cognitive function risk.

Methods: We analyzed data from CARDIA study participants who underwent cognitive testing and had at least three insulin measurements. Fasting insulin was measured at 7 timepoints over 30 years. Intra-individual insulin variability was assessed using standard deviation (SD), coefficient of variation (CV), and average real variability (ARV). Cognitive function was evaluated using the Digit Symbol Substitution Test (DSST), Stroop Test, and Rey Auditory Verbal Learning Test (RAVLT), with results standardized to z-scores and combined into a global cognitive z-score. Multivariable linear models were used to assess associations with cognitive performance.

Results: In the 25-year analysis (n = 2712), higher long-term insulin variability was significantly associated with poorer global cognitive performance at year 25 after adjustment for demographic, lifestyle, and cardiometabolic covariates (CV-insulin: β=-0.719; 95% CI: -1.161 to -0.276; P < 0.01; SD-insulin: β=-0.019; 95% CI: -0.036 to -0.002; P < 0.05). These associations remained significant after additional adjustment for either concurrent insulin at year 25 or mean insulin levels over 25 years. Domain-specific analyses showed that higher insulin variability was associated with lower DSST z-scores (worse attention) and higher Stroop interference z-scores (worse executive function). Extended analyses over 30 years (n = 2069) yielded consistent results: higher CV-insulin was inversely associated with global cognitive z-scores (β=-0.837; 95% CI: -1.347 to -0.327), as well as with DSST (β=-0.347; 95% CI: -0.581 to -0.112) and RAVLT z-scores (β=-0.276; 95% CI: -0.522 to -0.031). These associations persisted after full adjustment for year 30 covariates and time-varying confounders across the follow-up, supporting the temporal robustness and clinical relevance of insulin variability as an independent predictor of cognitive function.

Conclusions: Greater long-term insulin variability is independently associated with poorer midlife cognitive performance. These findings highlight insulin variability as a potential marker of cognitive health risk.

Background: The growing burden of cognitive decline represents a significant public health concern in aging populations, particularly in China. Social participation is a modifiable factor that may protect against cognitive decline, yet its long-term dynamic association with cognitive impairment remains insufficiently characterized.

Objectives: This study aimed to delineate long-term trajectories of social participation and determine their association with cognitive impairment in Chinese older adults.

Design: Longitudinal cohort study.

Setting: The study utilized data collected in 2013, 2015, and 2018 from the China Health and Retirement Longitudinal Study.

Participants: We included 3074 Chinese adults aged ≥60 years who were free of cognitive impairment in 2013, had complete social participation data in 2013/2015/2018, and completed cognitive assessments in 2018 INTERVENTION(S): Not applicable.

Measurements: Social participation was derived from CHARLS self-reported activity items and frequency and summed into a composite score (range 0-33). Cognitive performance was assessed using episodic memory (immediate and delayed 10-word recall) and mental status (orientation, serial subtraction, and figure drawing), yielding a global score (range 0-31); cognitive impairment was defined as a score <11. Group-based trajectory modeling identified five social participation trajectories. Multivariable logistic regression estimated odds ratios (ORs) for cognitive impairment adjusting for sociodemographic, health, and behavioral covariates.

Results: Five distinct social participation trajectories were identified. In the fully adjusted model, relative to the "stable low" group, those in the "low baseline-increasing" (OR = 0.66, 95% CI: 0.47-0.92), "stable intermediate" (OR = 0.75, 95% CI: 0.58-0.97), and "stable high" (OR = 0.41, 95% CI: 0.22-0.76) groups had markedly reduced chances of cognitive impairment, while no significant link was found for the "moderate decline" group (OR = 0.90, 95% CI: 0.71-1.17).

Conclusions: Maintaining or increasing one's social activities was linked to a notably lower likelihood of cognitive decline. These results highlight the importance of social involvement patterns as a modifiable factor for fostering cognitive strength. Interventions to maintain or enhance participation are therefore a viable strategy for the primary prevention of cognitive decline in older adults.

Neurodegeneration on demand represents a groundbreaking approach to modeling Alzheimer's disease (AD) in animals, enabling precise study of its molecular and behavioral hallmarks. Novel techniques, including optogenetic activation of amyloidogenic pathways, viral vector-mediated delivery of mutated human genes (e.g., APP, MAPT), and synthetic tau fibril analogs, induce AD-like pathology, including amyloid-beta plaques, tau hyperphosphorylation, neuroinflammation, and synaptic loss in diverse species, ranging from transgenic rodents to cephalopods and cannies. Emerging platforms, such as bioengineered neural organoids grafted into immunocompromised hosts, allowed for the controlled onset of AD-like features, providing unique insights into disease progression. Advanced tools like real-time neuroimaging and single-cell multi-omics help elucidate the temporal and cellular dynamics of neurodegeneration. These models provided unparalleled opportunities to dissect AD's complex mechanisms, including protein misfolding, glial dysregulation, and cognitive decline. However, challenges remained, including interspecies molecular disparities, incomplete replication of human AD complexity, and ethical concerns surrounding cognitive impairment in sentient models. This review explores these innovative strategies, their contributions to understanding AD's pathogenesis, and their potential to accelerate the development of transformative therapies, while also addressing limitations and future directions for refining these pioneering models.