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

Background: Utilizing non-invasive neuroimaging for characterization of blood brain barrier (BBB) changes and perfusion deficits underlying small vessel disease pathobiology including white matter hyperintensities (WMH) remains largely unexplored.

Objectives: We examined the underlying haemodynamics of WMH by assessing complex relationships between cerebral blood flow, BBB permeability and WMH burden.

Design, setting, participants: Cross-sectional data from study participants belonging to the community-based Biomarker and Cognition Cohort Study, Singapore was obtained.

Measurements: Brain structural and novel non-invasive multi-echo Arterial Spin Labeling data was obtained from 128 participants to derive cerebral blood flow (CBF), arterial transit time (ATT) and BBB time of exchange (T_ex).

Results: Neurovascular measures from BBB imaging comprising lower CBF (β=-0.005; p = 0.0139), longer ATT (β=0.644; p = 0.0132) and shorter BBB T_ex (β=-0.002; p = 0.0023) were independently associated with higher WMH and higher age-at-visit. Model fit statistics indicated good fit for the structural equation model with a comparative fit index of 0.975 and Standardized Root Mean Square Residual of 0.074. Structural equation modelling revealed CBF (β=0.533; p < 0.001) and ATT (β=-0.254; p = 0.001) as predictors of BBB permeability. Subsequently higher BBB permeability predicted higher WMH burden (β=-0.387; p < 0.001). Additionally, vascular risk factors comprising higher blood pressure and haemoglobinA1C related to lower CBF and shorter BBB T_ex.

Conclusions: Our study highlights that CBF and ATT contribute to BBB permeability, which in turn impacts WMH burden. Vascular risk factors also impact neurovascular measures. These findings add to the growing evidence on the potential role of BBB and perfusion deficits underlying small vessel disease burden.

Objectives: We aimed to evaluate the cost-effectiveness of blood-based biomarker (BBM) testing vs amyloid positron emission tomography (PET) in patients with signs and symptoms of cognitive decline in a neurologist/specialist care setting.

Methods: We constructed a decision-tree model to compare diagnostic outcomes and costs of two testing strategies: BBM testing with confirmatory PET scan vs PET scan alone. Their cost-effectiveness was evaluated from a payer perspective with test performance taken from a clinical study and costs including testing/imaging and physician fees.

Results: When access to PET scans is unlimited, BBM triage testing would identify 98.2 % of PET+ patients with a lower average cost per diagnosis compared with PET scan alone ($8868 vs 10,345 per PET+ diagnosis). In terms of incremental cost-effectiveness, BBM triage testing would save $93,984 for each loss of PET+ diagnosis (9.1 times the average cost per PET+ diagnosis by PET scan). Under limited capacity of PET scans, more test-positive patients could be identified using BBM testing than PET scan alone. When access to PET scans is limited to 50 % of the patients, BBM testing would identify 90.6 % more test-positive patients (at 93 % sensitivity) at an incremental cost-effectiveness ratio of $3484 per gain of positive diagnosis, lower than the average cost of a PET+ diagnosis by PET scan ($10,938).

Conclusion: BBM testing, compared with PET scan alone, is more efficient in the utilization of available amyloid PET scans and is cost-effective for assessment of Alzheimer's disease pathology in patients with signs and symptoms of cognitive decline.

Background: This study aimed to investigate the link between head injury (HI)/traumatic brain injury (TBI) and dementia risk, as it remains unclear.

Methods: We examined the associations between HI/TBI-related factors, including the frequency of HIs and the severity of TBI, and the risk of dementia (n = 397,581), as well as neuroimaging outcomes (n = 42,380) using prospective data (50 years at baseline) from the UK Biobank. In the observational analyses, Cox proportional-hazards modeling and logistic regression were used to estimate the associations between factors. Mendelian randomization (MR) was conducted to investigate the underlying causality between TBI (n = 392,423, n_cases=19,842) and Alzheimer's disease (AD) (n = 41,944, n_cases=21,982).

Results: During the 12.5-year follow-up period, 7524 participants developed dementia. HI and TBI conferred an increased dementia risk (hazard ratio (HR)=1.72, 95 % confidence interval (CI): 1.50-1.97; HR=1.86, 95 % CI: 1.46-2.38, respectively). The risk increased in relation to recurrent HIs (HR=4.05, 95 % CI: 2.24-7.32) or severe TBI (HR=4.50, 95 % CI: 3.18-6.37). Dementia risk was highest during the first 30 months following HI occurrence (HR=2.20, 95 % CI: 1.66-2.92), whereas there was no association after 40 years post-HI. Patients with recurrent HIs also exhibited reduced hippocampal volumes and increased white matter hyperintensity. HI was additionally associated with poorer reasoning ability and longer reaction time. Besides, the MR analysis supported a causal association between TBI and AD (odds ratio (OR)=1.17, 95 % CI: 1.01-1.37).

Conclusion: These results imply that HI/TBI is associated with increased dementia risk. Strategies are needed to mitigate the impact of subsequent dementia.

Introduction: Functional impairment is central to dementia diagnosis, typically assessed through basic and instrumental activities of daily living (ADLs/IADLs) reported by participants or informants. However, it remains unclear which items and reporting sources best capture cognition-related functional impairment.

Methods: We analysed data from 1,050 adults aged ≥65 years in the English Longitudinal Study of Ageing Harmonised Cognitive Assessment Protocol. Self- and informant-reported ADL and IADL impairments were examined at overall and item levels. Associations with general and domain-specific cognition were estimated using linear regression, and with incident dementia over 6.7 years using Cox models, both adjusted for socioeconomic, lifestyle, and health factors.

Results: ADL and IADL impairment proportions were similar across self- and informant-reports, with modest concordance. Informant-reported, but not self-reported, impairments were consistently associated with poorer cognition across domains, particularly executive function (informant-reported ADL: β = -0.71 SD, 95% CI -0.89 to -0.53) and memory (informant-reported IADL: β = -0.46 SD, 95% CI -0.60 to -0.32), and higher dementia risk (ADL: HR = 3.13, 95% CI 1.23 to 7.96; IADL: HR = 5.00, 95% CI 2.40 to 10.43). The strongest associations were observed for managing money and tasks involving episodic or visuospatial memory, especially among individuals with intermediate education and when informants had higher education or daily contact.

Discussion: Informant-reported IADLs, particularly those involving financial management and memory, may be strong indicators of cognitive impairment and dementia risk. Emphasising these items and informant characteristics may improve population surveillance of dementia and inform outcome selection in preclinical dementia trials targeting early functional decline. These findings should be interpreted in the context of a population-based sample with attrition.

Background: Young-onset dementia (YOD) directly affects the working-age population. The premature onset of dementia intensifies peer caregiving responsibilities and diverts medical and nursing resources. While modifiable risk factors for late-onset dementia have been well established, uncertainty remains regarding the applicability of these findings to YOD. We aim to identify modifiable risk factors for YOD and evaluate the strength of evidence.

Methods: We searched PubMed, Embase, Web of Science, and Ovid Medline from inception to 22 May 2025 for epidemiological studies on non-genetic risk factors for YOD. We used random-effects meta-analyses with the inverse variance method to pool relative risks (RRs) and 95% confidence intervals (CIs). A series of statistical tests were designed to classify the strength of evidence of significant associations as convincing, highly suggestive, suggestive, or weak evidence.

Results: From 25,731 initial and 2289 updated search records, 36 studies examining 31 non-genetic risk factors for YOD were identified. Of the 31 associations examined, 21 were nominally statistically significant at P < 0.05 based on random-effects models. Prior stroke was convincingly associated with an increased risk of YOD. Evidence of association was highly suggestive for alcohol use disorders, diabetes, depression, mood disorders, Parkinson's disease, multiple sclerosis, use of antidepressants/antipsychotics, and asthma.

Conclusion: We found that the risk of dementia in young individuals may be closely related to neuropsychiatric symptoms and clinical alcohol disorders. Future research should further validate these findings and explore intervention strategies to reduce dementia risk in younger individuals.

Background: Plasma phosphorylated tau (p-tau) and β-amyloid (Aβ) are promising biomarkers for Alzheimer's disease (AD). However, it remains unclear whether combining p-tau with Aβ provides better predictive performance than using p-tau alone.

Objectives: To evaluate the predictive utility of plasma p-tau and Aβ combinations for AD-related pathology, brain atrophy, and cognitive decline.

Design, setting, and participants: This study included 352 participants from the Greater-Bay Area Healthy Aging Brain Study (GHABS) cohort in China, classified into 227 Aβ-negative and 125 Aβ-positive individuals.

Measurements: Participants underwent Aβ positron emission tomography (PET) and plasma biomarker assessments. Plasma concentrations of p-tau181, p-tau217, p-tau231, Aβ42, and Aβ40 were quantified on the Quanterix HD-X and Lumipulse G1200 platform.

Results: Among the individual plasma p-tau variants, p-tau217 consistently outperformed p-tau181 and p-tau231. The combination of p-tau biomarkers (p-tau181, p-tau217, and p-tau231) with Aβ42 or the Aβ42/40 ratio further improved discrimination between Aβ+/CU (cognitively unimpaired) and Aβ-/CU individuals. Both p-tau/Aβ42 and p-tau/(Aβ42/40) exhibited slightly stronger or comparable associations with Aβ PET burden, baseline and longitudinal measures of hippocampal atrophy, AD-typical cortical thinning, and cognitive decline, relative to p-tau alone.

Conclusions: The head-to-head comparisons indicate that p-tau217 is the most robust biomarker among the variants tested, and p-tau/Aβ ratios perform comparably or slightly better than p-tau alone in reflecting AD pathology, potentially providing complementary information for early detection and monitoring of disease progression.

This study explored the association between plasma levels of multiple metals and cognitive impairment (CI) in 455 aluminum electrolysis workers from a northern Chinese plant, divided into CI (256) and control (199) groups by MoCA scores. Using inductively coupled plasma mass spectrometry, 11 metals were measured, with analyses via conditional logistic regression,generalized linear models (GLM), Bayesian kernel machine regression (BKMR), and age stratification (40 years). Plasma aluminum (Al), lead (Pb), lithium (Li), manganese, cobalt, and copper were significantly higher in the CI group (all P < 0.05), while zinc showed no difference. Single-element analysis found Al, Pb, and Li negatively correlated with MoCA total and subscores (e.g., visuospatial function; P < 0.05), and zinc positively correlated with attention (β = 1.10, P < 0.05). BKMR confirmed metal mixtures above the 25th percentile reduced MoCA scores (β = -0.875, 95 % CI: -1.379 to -0.371), with Al, Pb, and Li as key contributors (PIP > 0.6). Subgroup analysis showed Al primarily affected those <40, while Pb had greater impact in those >40. Findings indicate elevated Al, Pb, and Li associate with higher CI risk, metal mixtures synergistically exacerbate impairment, and age modifies these effects, aiding occupational cognitive impairment prevention.

Purpose: To investigate the cross-sectional and longitudinal alterations in cortical thickness and surface area and Cognitive Impairment among patients with preeclampsia.

Methods: The thickness and surface area of the cerebral cortex were systematically segmented from MRI using the automated cortical segmentation software FreeSurfer, and the corresponding values for each brain region were accurately quantified. Data collection includes the clinical characteristics, serological markers of proteins associated with cognitive function, and cognitive assessments.

Results: Compared with healthy pregnancies, the cortical thicknesses of the right caudal anterior cingulate (R-CACg), right posterior cingulate (R-PoCg), right rostral anterior cingulate (R-RoACg), and right superior frontal (R-SF) in the preeclampsia group exhibited significant alterations. Notably, the change in the R-SF was specific to preeclampsia and was not associated with normal physiological pregnancies. Mediation analysis further confirmed that elevated prepregnancy BMI was directly associated with reduced Symbol Digit Modalities Test scores and indirectly contributed to cognitive decline through an increase in MAP. The cortical thickness of left pars opercularis was identified as a key component in this underlying mechanism. No statistically significant changes in cortical surface area were observed in patients with preeclampsia. Follow-up studies have indicated that cortical thickness alterations in brain regions associated with preeclampsia demonstrate signs of recovery. Among cognitive-related test indicators, only the Auditory Word Learning Test exhibited a statistically significant improvement.

Conclusion: The cortical thickness alterations in the R-CACg, R-PoCg, R-RoACg, and R-SF of patients with preeclampsia may represent the structural basis for cognitive impairment. Longitudinal studies have confirmed the neuroplasticity of cortical thickness changes and the potential for recovery from preeclampsia-related memory deficits.