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

Background: Neurodegenerative diseases (NDs) lead to a progressive loss of neuronal cells and link to atrophy of subcortical brain structures, but the causal intermediates are not known. To test whether major NDs (Alzheimer's disease (AD), Parkinson's disease, multiple sclerosis, and amyotrophic lateral sclerosis) causally affects subcortical atrophy, and whether serum vitamin level play a mediating role in this process.

Methods: Using large-scale genome-wide association study (GWAS) summary data, we performed two-sample Mendelian randomization (MR) to assess the causal effect of NDs on the volume of seven subcortical structures, and then adopted two-step multivariable MR approach to quantify the proportion of the effect of NDs on the volume of subcortical regions mediated by serum vitamin level. Finally, we utilized animal experiments to validate results and explored the potential molecular mechanisms.

Results: Genetically predicted AD was associated with atrophy of the nucleus accumbens (NAc) (β = -0.09; p = 5.13 × 10^-5), amygdala (β = -0.07; p = 8.44 × 10^-4), and hippocampus (β = -0.07; p = 0.001), as well as with low serum vitamin D level (β = -0.02; p = 6.84 × 10^-6). Specifically, decreased serum vitamin D level mediated 3.99 % (95 % CI: -0.006 to -5.82 × 10^-5) and 3.97 % (95 % CI: -0.007 to -2.94 × 10^-4) of the total effect of AD on hippocampal and NAc atrophy, respectively. Animal experiments further confirmed significant delays in hippocampal and NAc atrophy, a significant reduction of β-amyloid deposits and an increase of vitamin D receptor expression in hippocampus in AD mice with high-dose vitamin D diet.

Conclusions: These findings provide important insights into the effect sizes of vitamin D-mediated roles in AD and atrophy of subcortical structures. Interventions to increase serum vitamin D levels at a population level might attenuate damage to hippocampus in patients with AD.

Background: Older adults with mild behavioral impairment (MBI) are at the higher risk of developing dementia compared to those without MBI, leading to decreased quality of life (QoL). Addressing MBI in older adults provides valuable opportunities to prevent dementia.

Objectives: This study aimed to determine the effects of traditional Thai folk dance combined with a cognitive stimulation program on MBI, QoL, subjective cognitive decline (SCD), and cognitive functioning in older Thai adults.

Design: Single-blinded, two-armed, randomized controlled trial, with a three-month follow-up period.

Setting: Outpatient chronic disease clinics at two districts in Suphan Buri province, Thailand.

Participants: One-hundred twenty-eight older adults with MBI were randomly assigned to either the experimental (n = 64) and cognitive education control group (n = 64).

Intervention: The 14-session, 7-week traditional Thai folk-dance program combined with cognitive stimulation focused on enhanced moderate intensity physical activity and cognitive stimulation engagement to improve MBI of older adults.

Measurements: The primary outcome was MBI assessed using Mild Behavioral Impairment Checklist. Secondary outcomes were QoL, SCD, and cognitive tests of memory and executive functions.

Results: Compared to the control group, participants in the experimental group demonstrated significantly reduced MBI (p <.01), improved QoL (p <.01), decreased SCD (p <.01), and enhanced cognitive functioning (p <.01) after the 7-week intervention and at the 12-week follow-up.

Conclusion: The traditional Thai folk dance combined with cognitive stimulation improved outcomes related to early signs of dementia and enhanced the overall QoL of older adults.

Background: The conditions under which samples were collected, processed, and stored in biobanks may influence Alzheimer's disease (AD) biomarker levels.

Objectives: This study aims to investigate whether a range of pre-analytical factors influence plasma levels of AD biomarkers.

Methods: Data were obtained from the ASPREE Healthy Ageing Biobank, a cohort of healthy community-dwelling older individuals aged 70+ years in Australia. Five biomarkers were measured using plasma from 11,868 individuals: phosphorylated-tau181 (p-tau181), neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), and amyloid-beta 42 and 40 (Aβ42/Aβ40). Linear regression examined the association between pre-analytical factors and biomarker levels.

Results: Participants were aged 70-96 years, and 54 % were female. The mean storage time for samples was 10.6 years (range: 7.7-13.5). Some significant associations were identified between pre-analytical factors and biomarkers, in particular for p-tau181, but the effect sizes were small. Weak negative associations were found between p-tau181 and the time from venepuncture to laboratory (transport) (β: -0.82, p = 0.03), laboratory processing to frozen storage (β:-1.56, p < 0.001), and total years of storage (β: -0.45, p = 0.007), while a positive association was found with intermediate storage at -20 °C/-30 °C compared to -80 °C (β: 2.24, p = 0.004). Longer fasting time was associated with higher levels of both NfL (β: 0.15, p < 0.001) and GFAP (β: 1.75, p < 0.001).

Conclusion: Following standard operating procedures, AD biomarkers can be measured in plasma from biobanks stored for up to 13 years, with minimal impact from long-term storage or other pre-analytical factors.

Background: Amyloid beta (Aβ) targeting immunotherapies have evolved as promising treatment options for patients with early symptomatic Alzheimer's disease (AD). Understanding how eligibilty criteria impact on the number of patients potentially qualifying for treatment is of high relevance for designing diagnostic workflows in clinical practice and for estimating required ressources and costs.

Objectives: We aimed at estimating the number of potentially eligible patients for treatment with the Aβ targeting antibodies aducanumab, lecanemab and donanemab in a specialized center real-world sample by the applying the phase 3 clinical trial and the appropriate use recommendations (AUR) inclusion and exclusion criteria to the data set. The post-mortem report was used for defining amyloid positivity and the presence of AD pathology in this study.

Design: Retrospective, descriptive study.

Setting: The multicenter National Alzheimer's Coordinating Center-Uniform Data Set (NACC-UDS) and Neuropathology Data Set (NACCNP).

Participants: We included all 3,343 participants of the NACC dataset with available post-mortem pathology reports.

Measurements/results: 887 participants were potential candidates for anti-Aβ immunotherapy as they presented with amnestic mild cognitive impairment or mild dementia and the clinical diagnosis of AD (amnestic AD syndrome). Applying the criterion of amyloid positivity (post mortem report) and the clinical trial inclusion and exclusion criteria to this sample resulted in 83 (9 %), 275 (31 %), and 172 (19 %) participants eligible for treatment with aducanumab, lecanemab, and donanemab, respectively. Applying the criteria of the AUR resulted in 242 (27 %) and 266 (30 %) participants eligible for treatment with aducanumab or lecanemab, respectively. The eligible participant groups for each antibody showed partial, but not full overlap. Co-pathologies were common.

Conclusions: The number of eligible participants varies between the different antibodies and the selected groups only partly overlap, indicating partly different groups of eligible participants for each antibody. Since not all inclusion and exclusion criteria can be extracted from the NACC-UDS dataset, the real number of eligible patients will be smaller.

Background: As literature suggests that Early-Onset Alzheimer's Disease (EOAD) and late-onset AD may differ in important ways, need exists for randomized clinical trials for treatments tailored to EOAD. Accurately measuring reliable cognitive change in individual patients with EOAD will have great value for these trials.

Objectives: The current study sought to characterize and validate 12-month reliable change from the Longitudinal Early-Onset Alzheimer's Disease Study (LEADS) neuropsychological battery.

Design: Standardized regression-based (SRB) prediction equations were developed from age-matched cognitively intact participants within LEADS, and applied to clinically impaired participants from LEADS.

Setting: Participants were recruited from outpatient academic medical centers.

Participants: Participants were enrolled in LEADS and diagnosed with amyloid-positive EOAD (n = 189) and amyloid-negative early-onset cognitive impairment not related to AD (EOnonAD; n = 43).

Measurement: 12-month reliable change (Z-scores) was compared between groups across cognitive domain composites, and distributions of individual participant trajectories were examined. Prediction of Z-scores by common AD biomarkers was also considered.

Results: Both EOAD and EOnonAD displayed significantly lower 12-month follow-up scores than were predicted based on SRB equations, with declines more pronounced for EOAD across several domains. AD biomarkers of cerebral β-amyloid, tau, and EOAD-specific atrophy were predictive of 12-month change scores.

Conclusions: The current results support including EOAD patients in longitudinal clinical trials, and generate evidence of validation for using 12-month reliable cognitive change as a clinical outcome metric in clinical trials in EOAD cohorts like LEADS. Doing so will enhance the success of EOAD trials and permit a better understanding of individual responses to treatment.

Background: Alzheimer's disease and vascular dementia are two of the most common causes of dementia. While early diagnosis and intervention are crucial, available treatments and research concerning the mild cognitive impairment stage remain limited. This study aimed to evaluate the real-world effectiveness and safety of L-α glycerylphosphorylcholine in this context.

Objectives: To investigate the impact of L-α glycerylphosphorylcholine on the risk of conversion from mild cognitive impairment to Alzheimer's disease dementia and vascular dementia, as well as its influence on stroke risk DESIGN: A nationwide, population-based cohort study SETTING: Data from South Korea's National Health Insurance Service PARTICIPANTS: Overall, 508,107 patients newly diagnosed with mild cognitive impairment between 2013 and 2016 were included.

Intervention: Patients were classified as users or non-users of L-α glycerylphosphorylcholine based on prescription records.

Measurements: The primary outcomes were the risk of progression to Alzheimer's disease dementia and vascular dementia. Stroke risk was examined as a secondary outcome. A time-dependent Cox regression analysis was used to adjust for demographic and clinical factors.

Results: Compared to non-users, L-α glycerylphosphorylcholine users had a lower risk of progression to Alzheimer's disease dementia (hazard ratio = 0.899, 95 % confidence interval: 0.882-0.918) and vascular dementia (hazard ratio = 0.832, 95 % confidence interval: 0.801-0.865) within 2,435,924 and 662,281.6 person-years, respectively. In patients under 65, L-α glycerylphosphorylcholine significantly reduced the risk of progression to Alzheimer's and vascular dementia. Stroke risk significantly decreased in patients who did not progress to dementia but not in those who did.

Conclusions: L-α Glycerylphosphorylcholine reduces dementia conversion and stroke risk in patients with mild cognitive impairment, making it a viable early intervention. Future large-scale randomized controlled studies should examine its effects on other dementia subtypes and long-term cognitive outcomes.

Objective: Due to the recognition for the importance of early intervention in Alzheimer's disease (AD), it is important to focus on prevention and treatment strategies for mild cognitive impairment (MCI). This study aimed to establish a risk prediction model for AD among MCI patients to provide clinical guidance for primary medical institutions.

Methods: Data from MCI subjects were obtained from the NACC. Importance ranking and the SHapley Additive exPlanations (SHAP) method for the Random Survival Forest (RSF) and Extreme Gradient Boosting (XGBoost) algorithms in ensemble learning were adopted to select the predictors, and hierarchical clustering analysis was used to mitigate multicollinearity. The RSF, XGBoost and Cox proportional hazard regression (Cox) models were established to predict the risk of AD among MCI patients. Additionally, the effects of the three models were evaluated.

Results: A total of 3674 subjects with MCI were included. Thirteen predictors were ultimately identified. In the validation set, the concordance indices were 0.781 (RSF), 0.781 (XGBoost), and 0.798 (Cox), and the Integrated Brier Score was 0.087 (Cox). The prediction effects of the XGBoost and RSF models were not better than those of the Cox model.

Conclusion: The ensemble learning method can effectively select predictors of AD risk among MCI subjects. The Cox proportional hazards regression model could be used in primary medical institutions to rapidly screen for the risk of AD among MCI patients once the model is fully clinically validated. The predictors were easy to explain and obtain, and the prediction of AD was accurate.