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

O-GlcNAcase inhibitors (OGAi) have emerged as a promising therapeutic strategy in Alzheimer's disease (AD) by enhancing O-GlcNAcylation, which competes with tau phosphorylation and reduces tau aggregation. However, the Phase II clinical trial failure of ceperognastat, marked by accelerated cognitive decline in the treatment group, has raised significant safety concerns. Here, we examined the acute synaptic effects of three structurally distinct OGAi compounds-ceperognastat, ASN90, and MK8719-in mouse hippocampal slices. Electrophysiological recordings revealed suppression of both short- and long-term synaptic plasticity, including paired-pulse facilitation/depression and long-term potentiation. Immunohistochemical analysis confirmed disrupted synaptic protein levels (increased PSD-95, reduced Synaptophysin 1) and a biphasic shift in tau phosphorylation. These convergent findings suggest a class-wide synaptotoxic mechanism and call for a great caution in the development of disease-modifying therapies in AD. We argue that preclinical drug screening for synaptic functionality is essential in CNS-targeted therapeutic pipelines.

Background: The global prevalence of dementia is rapidly expanding and is expected to triple by 2050. Approximately 45 % of dementia cases are estimated to be attributable to potentially modifiable risk factors. Identifying how these factors contribute to specific brain pathologies may improve strategies to reduce dementia incidence.

Objectives, design, setting: The aim of this study was to identify both non-modifiable and modifiable risk factors associated with longitudinal changes in white matter hyperintensities (WMH), amyloid-beta (Aβ) and tau. Data were acquired in the prospective observational Swedish BioFINDER-2 study between May 2017-January 2025. All participants underwent clinical assessments, questionnaires and at least two magnetic resonance imaging (MRI), Aβ Positron Emission Tomography (PET) and tau PET scans, respectively. Mixed-effects models were used to assess the associations between non-modifiable and modifiable risk factors and WMH (MRI), Aβ (PET) and tau (PET).

Participants: A total of 494 cognitively unimpaired participants were included, of whom 365 were amyloid-negative (CU Aβ-) and 129 were amyloid-positive (CU Aβ+).

Measurements and main outcomes: Non-modifiable (age, apolipoprotein E (APOE) ɛ4 genotype and sex) and modifiable risk factors (co-morbidities at baseline, such as hypertension and cardiovascular disease, BMI, and sleep duration) were analyzed with mixed-effects models, adjusted for age and sex, to predict longitudinal measurements of WMH, Aβ and tau.

Results: Mean age was 64.8 (SD 13.3) years and mean follow-up was 3.9 (SD 1.5) years. Predictors represent baseline data, both predictors and outcomes are on standardized scales. Linear mixed-effects models, adjusted for age and sex, showed that higher blood pressure (β = 0.02, 95 % CI :0.01-0.02), presence of hyperlipidemia (β = 0.03, 0.01-0.05), ischemic heart disease (β = 0.06, 0.03-0.09), smoking (β = 0.02, 0.00-0.03) and lower education (β = -0.01, -0.02- -0.01) were associated with a longitudinal increase in WMH. Presence of the APOE ε4 allele was linked to faster Aβ accumulation (β = 0.03, 0.02-0.04) and tau (β = 0.01, 0.00-0.03), but only to Aβ among Aβ+ positive participants. Higher depression score (β = 0.01, 0.00-0.01) and diabetes (β = 0.02, 0.00-0.04) were associated with faster Aβ accumulation. Lower BMI was associated with faster accumulation of tau (β = -0.01, -0.02- -0.01).

Conclusions: Modifiable risk factors of future dementia primarily affect accumulation of cerebral vascular pathology, although lower BMI was associated with tau accumulation and diabetes with Aβ accumulation.

Background: Neighborhood-level factors, measured by the Area Deprivation Index (ADI), are linked to comorbidities of Alzheimer's disease and related dementias (ADRD). However, their direct association with AD neuropathology is unclear. The accessibility of blood-based biomarkers (BBMs) like p-tau217 and Aβ42/40 offers a scalable way to investigate these relationships.

Objectives: To examine the relationship between ADI and levels of key BBMs (p-tau217/Aβ42, p-tau217, and Aβ42/40). We also aimed to assess whether the performance of these BBMs in predicting amyloid PET positivity is consistent across different levels of neighborhood disadvantage.

Design: A cross-sectional analysis using data from an observational cohort study of the Alzheimer's Disease Neuroimaging Initiative (ADNI).

Setting: Multicenter observational cohort conducted at 55 sites across the United States.

Participants: The study included 755 ADNI participants with ADI and amyloid PET data. A sub-cohort of 438 participants also had BBM data available.

Measurements: National ADI scores were used to stratify participants into least, intermediately, and most disadvantaged groups. Amyloid PET positivity was determined using Centiloid values. Plasma levels of p-tau217, Aβ42, and Aβ40 were measured using Fujirebio assays.

Results: ADI groups differed by sex, ethnoracial background, and MMSE scores. The intermediately disadvantaged group had 1.55 times higher odds of being amyloid PET positive compared to the least disadvantaged group. While this group also showed higher levels of plasma p-tau217/Aβ42 and p-tau217, these differences were no longer significant after accounting for the higher prevalence of amyloid positivity. Critically, the predictive accuracy of all three BBMs for amyloid PET status did not differ across the ADI groups. The p-tau217/Aβ42 ratio performed best, yielding the fewest indeterminate cases in a two-cut-point classification model.

Conclusions: The diagnostic performance of plasma AD biomarkers is robust and is not compromised by neighborhood-level disadvantage. These findings support the generalizability and equitable clinical utility of biomarkers like p-tau217/Aβ42 for AD diagnosis across diverse socioeconomic settings.

Background: The magnitude of cognitive change before and after incident heart failure (HF) is unclear. We investigated whether incident HF is associated with changes in cognitive function at the time of diagnosis and accelerated trajectory in cognitive decline in the subsequent years.

Methods: We used data from the Health and Retirement Study, a nationally representative survey of US adults aged 50 years or older. Participants underwent a cognitive assessment at baseline (wave 5, 2000), and at least 1 other time point (from wave 6 [2002] to wave 15 [2020]). The outcomes were change in global cognition, memory, and executive function. Outcomes were standardized into Z-scores, with higher scores indicating better cognitive performance. Linear mixed-effects models estimated changes in cognition at the time of HF (change in the intercept) and the rate of cognitive change over the years after HF (change in the slope), after adjusting for pre-HF cognitive trajectories and potential confounders.

Results: We included 12 850 adults (mean [SD] age, 66.1 [9.4] years; 61.8 % women). Over a median follow-up of 16 years (interquartile range: 8 to 20 years), 1457 participants had incident HF. The annual rate of cognitive decline before HF diagnosis among individuals with incident HF was similar to that of participants who remained HF-free throughout follow-up. However, incident HF was associated with subsequent decreases in global cognition (-0.073 SD [95 % CI -0.109 to -0.038]), memory (-0.070 SD [95 % CI -0.108 to -0.032]), and executive function (-0.054 SD [95 % CI -0.092 to -0.016]) around the time of the HF diagnosis. Moreover, individuals with incident HF vs those without HF demonstrated faster and long-term declines in global cognition (-0.011 SD/year [95 % CI -0.018 to -0.004]) and executive function (-0.008 SD/year [95 % CI -0.015 to -0.001]), but not in memory (-0.006 SD/year [95 % CI -0.013 to 0.001]) over the years after HF compared with pre-HF slopes.

Conclusions: Incident HF was associated with subsequent decreases in cognitive function at the time of diagnosis and accelerated cognitive decline over the following years.

Background: White matter hyperintensities (WMHs) represent a cardinal feature of cerebral small vessel disease (CSVD), yet iron dysregulation alterations within these lesions and their relationship to cognitive decline remains poorly understood.

Objectives: To characterize iron dysregulation in WMH using quantitative susceptibility mapping (QSM) and examine their relationship with CSVD severity and cognitive function.

Design: Cross-sectional study with longitudinal follow-up component.

Setting: Single-center study at Shandong Provincial Hospital Affiliated with Shandong First Medical University, China.

Participants: 299 participants recruited from January 2021 to September 2023, with 71 participants completing longitudinal follow-up (mean interval 20.6 months). Participants were categorized into early CSVD (0 points, n = 171), mild CSVD (1 point, n = 70), and severe CSVD (≥2 points, n = 58) groups based on total burden scoring.

Intervention: None (observational study).

Measurements: 3.0T MRI with quantitative susceptibility mapping and diffusion tensor imaging. Spatial analysis examined susceptibility values in WMH cores and perilesional zones (0-2 mm, 2-4 mm, 4-6 mm). Cognitive assessments included Montreal Cognitive Assessment (MoCA), Symbol Digit Modalities Test (SDMT), and other neuropsychological tests.

Results: WMH susceptibility values were significantly lower than normal-appearing white matter (-14.55 vs -7.77 ppb, P < 0.001) with progressive increases correlating with CSVD severity (P < 0.001). Cross-sectionally, higher WMH susceptibility values correlated with lower MoCA scores (r = -0.155, P = 0.045). Longitudinally, WMH susceptibility values predicted decline in information processing speed (SDMT: β = -0.247, P = 0.042). Spatial analysis revealed distinct patterns with perilesional regions showing intermediate susceptibility values.

Conclusions: Iron dysregulation alterations within WMH provide independent information about cognitive risk in CSVD. QSM emerges as a promising biomarker for monitoring cognitive trajectory and may facilitate early identification of patients at risk for cognitive decline.

Human cognition and behavior rely on the integration of large-scale neural networks that connect the cerebral cortex and subcortical structures. Emerging evidence suggests that alterations in the functional connectivity (FC) between the cortical and subcortical regions in Alzheimer's disease (AD) may influence the onset and progression of both cognitive and noncognitive symptoms at the group level. However, an individualized and longitudinal framework to capture deviations in subcortico-cortical FC from normative brain aging remains underexplored. We addressed this gap by leveraging large-scale longitudinal neuroimaging datasets and applying a normative modeling approach to characterize subcortical FC trajectories across the adult lifespan. First, we quantified individual deviations in the subcortical FC in individuals with cognitive impairment (CI) relative to a normative aging group using centile scores and tracked longitudinal changes across multiple follow-ups. We examined the relationship between changes in subcortical FC and clinical measures of cognitive function, including episodic memory, executive function, and language. Our findings revealed widespread decreases in the subcortical FC in individuals with CI, except in the limbic network, which diverged from the patterns observed in normal aging. These alterations are significantly associated with a decline in memory and executive functions. Collectively, our results may advance our understanding of AD-related connectopathy and provide a direction for profiling individualized longitudinal FC changes in individuals with CI. Furthermore, our results could inform individualized prognosis and targeted interventions.

Background: Predicting the transition from subjective cognitive decline (SCD) to mild cognitive impairment (MCI) is critical for dementia prevention.

Objective: Comprehensive assessment of MRI-based macro-/micro-structural and functional brain changes in SCD to develop an individualized model predicting transition to MCI.

Design, setting, and participants: Patients with SCD were screened from the ADNI, NACC, and OASIS-3 databases. 89 patients met the inclusion criteria and underwent structural magnetic resonance imaging (sMRI) and resting-state functional MRI (rs-fMRI). Over a 10-year follow-up, 49 patients progressed to MCI, while 40 remained stable.

Measurements: The VB-net automated brain segmentation, extracting hippocampal radiomics and whole brain subregion volume features. Brain functional features were extracted based on rs-fMRI. Cox regression was used to develop predictive models, which were independently validated with the testing set. The nomogram was constructed to estimate the probability of transition to MCI at 5-/7-/10-year. The nomogram's accuracy was assessed using calibration curves and concordance index (C-index), and clinical utility was evaluated through decision curve analysis.

Results: The model incorporating age, brain volume, functional, and radiomics features demonstrated the highest predictive performance for SCD progression in training (C-index: 0.962; 95 % CI: 0.95-0.98) and testing (C-index: 0.911; 95 % CI: 0.861-0.968) sets. A nomogram comprising 10 predictors was constructed to estimate individualized risk of progression to MCI at 5-/7-/10-year. The calibration curve showed good agreement between predicted and observed values. Decision curve analysis demonstrated the nomogram had substantial clinical value.

Conclusions: This multivariate model and nomogram could accurately predict the individual progression from SCD to MCI.

Background and objectives: Multiple lifestyle and health factors could contribute to cognitive health, while not many studies examined the factors in a combined way, especially in Asian population. This study aims to examine the association of Life's Simple 7 (LS7) with cognitive function and its change in a multi-ethnic Asian population.

Methods: Longitudinal data were drawn from the Singapore Multi-Ethnic Cohort, involving 2601 participants (45-86 years). LS7 at baseline was calculated by summing seven metrics, and a higher LS7 (range: 0-7) score indicates a healthier lifestyle. Cognitive function was measured at two revisits with Mini-Mental State Examination (MMSE). Association of baseline LS7 with MMSE percentiles (10th, 30th and 50th) and its change over time were examined using linear quantile mixed model. Interactions between LS7 and age group, sex, ethnicity, education level and marital status were also explored.

Results: Higher LS7 was significantly associated with higher MMSE scores at 10th (β = 0.11, 95% CI 0.01, 0.20), 30th (β = 0.12, 95% CI 0.05, 0.19), and 50th (β = 0.07, 95% CI 0.03, 0.11) percentiles. These associations were particularly pronounced among currently unmarried individuals, participants aged 60 and above, those with education above primary school and Chinese ethnicity. No significant association was found between LS7 and MMSE change over time.

Discussion: Higher LS7 was significantly associated with better cognition particularly among older, unmarried individuals and participants with higher education or of Chinese ethnicity. These findings highlight the value of composite lifestyle scores for cognitive impairment risk modification in Asian populations.

Alzheimer's disease is a complex and multifactorial disease characterized by two key pathological hallmarks: amyloid-beta plaques and tau neurofibrillary tangles. Recent progress has led to the development and approval of disease-targeted therapies for Alzheimer's disease in the form of anti-amyloid-beta monoclonal antibodies. However, findings suggest that amelioration of multiple pathological drivers may be required to maximize clinical effect. An increasing body of evidence suggests that tau is a critical player in Alzheimer's disease pathophysiology, contributing significantly to neurodegeneration and cognitive decline. There are now several tau-targeting drugs in clinical development. In this review, we build on research and advancements in the field of tau to envision how an increasing focus on tau could shape the future Alzheimer's disease patient journey. We highlight the potential of tau as both a promising therapeutic target and a valuable biomarker, with the potential to inform treatment decisions and provide insight into disease trajectories. We also consider what a greater focus on tau may bring to an already evolving patient care pathway characterized by an increased influx of patients presenting earlier in the disease continuum, changes in workflow and infrastructural requirements, and increased complexity in treatment decision-making, treatment administration, treatment monitoring, and patient tracking. This review underscores the critical changes that may be required and knowledge gaps to be elucidated to ensure healthcare system preparedness for additional classes of disease-targeted therapy to move toward a next-generation, individualized treatment approach to Alzheimer's disease diagnosis and care.