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

Background: Using the Diffusion Tensor Image Analysis Along the Perivascular Space (ALPS) method and perivascular space (PVS) burden to study glymphatic function in high-risk Alzheimer's disease (AD) populations, this research investigates the correlation between ALPS index and PVS volume with cognitive function respectively.

Methods: This study enrolled 126 participants, including 21 cognitively unimpaired (CU) individuals, 68 with subjective cognitive decline (SCD), and 37 with mild cognitive impairment (MCI). All participants underwent MRI and cognitive assessments. MRI measures, including the PVS burden and the ALPS index, were compared across SCD, MCI, and CU groups. Additionally, correlations among the ALPS index, PVS burden, and cognitive scales were analyzed.

Results: The PVS in the basal ganglia volume fraction (PVSVF-BG) in patients with MCI was significantly larger than the fraction in CUs (p < 0.05) and a higher PVSVF-BG was associated with poorer performance on the Trail Making Test A (TMTA) (r = 0.29, p < 0.05). Compared with the CU and SCD groups, patients with MCI exhibited a significantly lower ALPS index in both the left (p < 0.05) and right hemispheres (p < 0.001). Lower whole brain ALPS index in patients with MCI was correlated with worse performance in the Auditory Verbal Learning Test(AVLT) (N4, r = 0.33, p < 0.05; N7, r = 0.56, p < 0.001).

Conclusions: An increased PVS burden and a decreased ALPS index can be observed in the preclinical stage of AD, which may suggest impaired glymphatic system function. These impairments were further correlated with worse cognitive performance in terms of attention in SCD and memory in MCI.

Background and objective: Cumulative blood pressure (cBP), reflecting long-term BP exposure, is increasingly used to examine risk associations with dementia and cognitive function, but findings to date are inconsistent. This systematic review aimed to synthesize existing evidence to clarify risk associations in adults.

Methods: We searched for articles in Medline, Embase (Ovid), Web of Science, Cochrane Library, and China National Knowledge Infrastructure from inception to January 2025 in any language. Longitudinal, observational studies involving participants aged over 18 years at the time of initial BP assessment were eligible for inclusion. cBP was defined as the area under the curve of BP values over time or an equivalent method, expressed in units of mmHg × time. Study outcomes were dementia, cognitive function assessments, and neuroimaging markers. This review is registered in PROSPERO (CRD42025640637).

Results: From 6334 records identified, 10 independent prospective cohort studies from 9 publications were included in the review, of which four cohort studies were eligible for meta-analysis. Meta-analysis showed that higher cumulative systolic BP (cSBP) was associated with an increased risk of incident dementia (odds ratio [OR] 1.21, 95% CI 1.00-1.45; I² = 92.4%, P for heterogeneity<0.001), while cumulative diastolic BP (cDBP) was not associated with dementia risk (OR 0.97, 95% CI 0.72-1.32; I²=97.3%, P for heterogeneity<0.001). Among eight studies on cognitive function, five reported that higher cSBP was associated with poorer cognitive performance, while three reported non-significant results. In contrast, findings for higher cDBP were mixed, with two studies reporting adverse associations, two reporting protective associations, and three reporting null associations. Two studies linked higher cSBP and cDBP to greater white matter hyperintensity burden. Sensitivity and subgroup analyses suggested that the positive association between cSBP and dementia-related outcomes were more pronounced among middle-aged adults, whereas inverse or null associations for higher cDBP was observed in some cohorts among individuals aged ≥60 years.

Conclusion: Higher cSBP is associated with increased risk of incident dementia and cognitive decline, whereas associations for cDBP are mixed. Given the limited evidence, future studies should incorporate age-stratified analyses and consider including cumulative pulse pressure and mean arterial pressure to further clarify the relationship between cBP and cognition.

Background and objectives: Plasma phosphorylated tau 217 (p-tau217) has shown strong potential as a blood-based biomarker for detecting amyloid pathology in Alzheimer's disease. This study evaluated the diagnostic and prognostic utility of plasma biomarkers, including p-tau217, in participants from the Japanese Alzheimer's Disease Neuroimaging Initiative (J-ADNI) cohort.

Methods: We analyzed paired plasma and CSF samples from 172 J-ADNI participants. CSF and plasma biomarkers were quantified using the LUMIPULSE platform, and the same plasma samples were analyzed using the Simoa platform. The diagnostic accuracy for detecting amyloid pathology and the prognostic value of plasma p-tau217 biomarkers were assessed. Associations between plasma p-tau217 and polygenic risk scores (PRS), as well as potential confounding factors, were examined.

Results: Plasma p-tau217 levels measured using Lumipulse and Simoa assays were highly correlated (p < 0.001). All plasma p-tau217 assays showed high diagnostic accuracy for CSF Aβ42/Aβ40-defined amyloid pathology (AUC = 0.98). A single cutoff point based on the Youden index for p-tau217 and p-tau217/Aβ42 achieved >90% specificity and >90% sensitivity. The predefined FDA-approved two-cutoff model for p-tau217/Aβ42 was applicable to this cohort. PRS was significantly associated with plasma p-tau217 independently of APOE genotypes. Subjects with higher plasma p-tau217 levels showed a significantly increased risk of conversion to dementia and larger longitudinal cognitive declines. Plasma p-tau217 levels were significantly influenced by the body mass index, estimated glomerular filtration rate, and high-density lipoprotein cholesterol.

Conclusions: Plasma p-tau217 and p-tau217/Aβ42 are robust biomarkers for AD diagnosis and prognosis in the Japanese population.

Background: Brain age gap (BAG)-the difference between predicted and chronological age-captures neurobiological aging, but MRI-only models insufficiently reflect Alzheimer's disease (AD) pathology. Whether incorporating regional amyloid-β (Aβ) positron emission tomography (PET) improves sensitivity to early AD processes remains unknown.

Objectives: To develop an amyloid-informed multimodal BAG model and examine its associations with cognition, plasma biomarkers, and functional connectivity across the AD continuum.

Design: Cross-sectional analysis using integrated machine-learning models.

Setting: Chinese Preclinical Alzheimer's Disease Study (CPAS), a cohort recruited from community settings and memory clinics.

Participants: Nine hundred ninety community-dwelling adults spanning normal cognition, subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia.

Measurements: Regional Aβ-PET and structural MRI informed BAG estimation. Cognitive tests, plasma biomarkers (p-tau217, p-tau181, neurofilament light [NfL], glial fibrillary acidic protein [GFAP], Aβ42/40), and hippocampus-default mode network (DMN) connectivity from resting-state fMRI were assessed.

Results: Higher BAG was associated with greater odds of SCD, MCI, or dementia across the cohort, with stronger effects in Aβ-positive individuals. BAG explained more cognitive variance than global Aβ burden and was linked to multidomain cognitive deficits. Elevated BAG corresponded to higher p-tau217, p-tau181, NfL, and GFAP and lower Aβ42/40, indicating early biomarker alterations. BAG was also associated with reduced hippocampus-DMN connectivity.

Conclusions: An amyloid-informed multimodal BAG model captures convergent AD-related pathology, biomarker alterations, and cognitive vulnerability beyond amyloid burden alone, supporting its value for individualized risk s2tratification and prevention-focused assessment.

Background: Preclinical Alzheimer's disease (AD) trials enroll cognitively unimpaired, amyloid-positive older adults; however, most remain clinically stable over typical trial durations. Limited near-term decline reduces statistical power and drives large sample sizes and high costs. Scalable enrichment strategies capable of identifying individuals most likely to decline are critically needed.

Objectives: To determine whether a brief digital memory assessment (DMA) and plasma phosphorylated tau 217 (pTau217), individually or combined, identify preclinical AD participants at elevated risk for cognitive and biological progression, and whether such enrichment reduces clinical trial sample-size requirements.

Design: Analysis of data from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) Study, a multicenter randomized clinical trial with 240 weeks of follow-up.

Setting: Secondary-prevention trial conducted across sites in the United States, Canada, Australia, and Japan.

Participants: A total of 1,169 cognitively unimpaired adults aged 65-85 years who were amyloid-positive and completed both a baseline DMA and plasma pTau217 measurement.

Measurements: Primary outcome was change in the Preclinical Alzheimer Cognitive Composite (PACC) over 240 weeks. Secondary outcomes included Clinical Dementia Rating-Sum of Boxes, Mini-Mental State Examination, Cognitive Function Instrument, and annualized change in amyloid PET, plasma pTau217, and tau PET.

Results: Participants with both elevated pTau217 and low DMA exhibited the greatest cognitive decline and reached the 240-week PACC decline of the overall cohort 83 weeks earlier. Participants with neither marker showed minimal decline. Dual enrichment reduced sample-size estimates for a clinical trial from 3,252 to 818 participants per arm (75 % reduction). These individuals also demonstrated faster increases in plasma pTau217 and neocortical tau PET.

Conclusions: A brief DMA combined with plasma pTau217 identifies a subset of cognitively unimpaired, amyloid-positive older adults at highest risk for cognitive and biomarker progression. This dual-marker enrichment strategy enables smaller, shorter, and more cost-efficient preclinical AD trials and supports more targeted evaluation of preventive therapies.

Background: The rapid increase in the incidence of Alzheimer's disease (AD) has raised concerns, given its profound effects on both society and the economy. Despite extensive research efforts in this area, there are no existing treatments that have the ability to change the progression of the disease.

Methods: To identify the distinct subtypes of AD, consensus clustering was employed. Following this, module genes were identified through the implementation of WGCNA. In addition, the investigation included the identification of hub genes through the application of machine learning. Ultimately, a thorough analysis was performed utilizing a methodical strategy to perform post-translational modification (PTM) genome wide.

Results: GO and KEGG analyses were conducted by examining of 21 different types of PTMs, revealing that the majority of these genes play key roles in the PTM pathways, as well as AD-related pathways. Correlation analysis revealed that these PTM were significantly correlated with gamma secretase activity, beta secretase activity, amyloid-beta 42, clinical dementia rating, Braak stage, plaque, and neurofibrillary tangle. Then, two distinct subtypes of PTM were identified, each characterized by unique clinical characteristic. By utilizing machine learning, we developed an PTM.score, and has shown impressive predictive capabilities for AD when tested against various datasets (brain AUC: 0.859, blood AUC: 0.898), indicating its potential utility in clinical settings for risk stratification and therapeutic decision-making. Moreover, our investigation led to the identification of two genes (TRIM47 and LNX1) that may represent potential drug targets for AD (brain tissues or blood samples). Research further indicated a potential correlation between TRIM47 and concentrations of CSF Aβ (OR 1.068 (1.029-1.108)), CSF p-tau (OR 1.315 (1.136-1.524)), and total hippocampal (OR 1.176 (1.058-1.307)).

Conclusions: The findings from this study not only enhance our comprehension of the underlying mechanisms of AD but also serve to inform and direct future initiatives in drug discovery. By focusing on TRIM47, the work paves the way for identifying innovative therapeutic strategies.

Background: Plant-based diets are increasingly advocated for their health benefits, yet their associations with dementia risk remains inconclusive. We evaluated the associations between plant-based dietary patterns and dementia risk across three prospective cohorts and a meta-analysis.

Methods: Cohort analyses included the Health and Retirement Study (HRS; N = 6642), Framingham Heart Study Offspring cohort (FOS; N = 3045), and Whitehall II study (WHII; N = 8219). Participants were aged ≥45 years and free of dementia at baseline. The overall plant-based diet index (PDI), healthful plant-based diet index (hPDI) and unhealthful plant-based diet index (uPDI) were calculated from validated food frequency questionnaires. Further, a meta-analysis was conducted incorporating data from 5 cohort studies (N = 207,981).

Results: In the cohort analyses, 891 incident dementia cases were identified over 166,762 person-years. In multivariable-adjusted Cox proportional hazard models, higher scores in PDI and hPDI were associated with lower risk of dementia (highest vs. lowest tertile: pooled HR for PDI = 0.70, 95% CI, 0.53-0.92, p for trend <0.001; pooled HR for hPDI = 0.71, 0.48-1.06, p for trend = 0.03). Main contributors to lower risk were higher intake of vegetables, nuts, tea or coffee, and legumes. Conversely, higher uPDI was associated with higher dementia risk (highest vs. lowest tertile: pooled HR = 1.42, 1.19-1.70, p for trend <0.001). In the meta-analysis, individuals in the highest hPDI tertile had 21% lower dementia risk, and those in the highest uPDI tertile had 24% higher risk.

Conclusions: The healthful plant-based diet was associated with lower risk of dementia, whereas the unhealthful plant-based diet was linked to higher risk. These findings support recommendations to adopt diets rich in healthy plant foods for dementia prevention.

Background: The agreement between plasma Aβ42/40 and Aβ positron emission tomography (PET) is approximately 75 %, with ∼85 % of discrepancies due to positive plasma but negative PET results. It is unclear whether this reflects Aβ changes in plasma before PET-detectable.

Objectives: To assess the influence of Aβ42/40 positivity on risk of progression to Aβ PET positivity, and feasibility of using plasma Aβ42/40 tests to enrich a primary prevention trial.

Design: A prospective longitudinal cohort study.

Setting: Participants of Australian Imaging, Biomarkers and Lifestyle study (AIBL), Alzheimer's Disease Neuroimaging Initiative (ADNI), and Open Access Series of Imaging Studies 3 (OASIS3).

Participants: 507 cognitively unimpaired adults at baseline, with a baseline Aβ PET < 20 Centiloid (CL) and available longitudinal Aβ PET data.

Measurements: Baseline Aβ PET and plasma Aβ42/40 measurement by mass-spectrometry, followed by 1-6 additional Aβ PET scans every 1.5-3 years. Those < 5 CL were classified as PET- and 5-20 CL as PET_Low. Plasma -/+ was defined using the Aβ42/40 Youden's Index threshold (0.119), corresponding to Aβ PET status.

Results: At baseline, 283 were Plasma-/PET-, 97 Plasma+/PET-, 76 Plasma-/PET_Low, and 51 Plasma+/PET_Low. Among Plasma+/PET- individuals, 19 % progressed to PET+ (>20 CL), indicating a higher risk of progression, compared to Plasma-/PET- (HR: 3.90 [90 % CI: 2.00-7.61], p < 0.001). This elevated risk remained significant after matching the groups' baseline CL (3.43 [1.43-8.26], p = 0.010), or adjustment for age, sex, APOE ε4 and baseline CL (2.48 [1.22 - 5.07], p = 0.013). Plasma+/PET- individuals accumulated Aβ ∼8 times faster (1.14 CL/year) than Plasma-/PET- (0.15 CL/year, p < 0.001). Plasma+/PET- progressors became PET+ two years earlier than Plasma-/PET- progressors. Among the Plasma+/PET_Low individuals, 67 % progressed to PET+. Their progression was faster and earlier than in the Plasma-/PET_Low group (HR: 20.82 [11.28 - 38.42], p < 0.001 vs. 6.67 [3.51 - 12.65], p < 0.001; reference: Plasma-/PET-), largely driven by higher baseline CL in the Plasma+ group. In a primary prevention paradigm targeting high-risk PET_Low individuals, pre-screening with Aβ42/40 blood test reduced the number of PET scans by 49 %, compared to a PET-only strategy.

Conclusions: Cognitively unimpaired individuals with abnormal Aβ42/40 are at increased risk for future Aβ PET positivity. In the 5-20 CL subgroup, baseline CL is the main driver of this risk. Combining blood-based pre-screening with PET imaging may help efficiently enrich primary prevention trials.