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

{"title":"Reply to: Enhancing Statin Research for Alzheimer's Prevention: Suggestions for Future Studies and Policy Implications.","authors":"Zirong Ye, Jiahe Deng, Xiuxia Wu, Jingwen Cai, Sicheng Li, Xiaochun Chen, Jiawei Xin","doi":"10.1016/j.tjpad.2025.100119","DOIUrl":"https://doi.org/10.1016/j.tjpad.2025.100119","url":null,"abstract":"","PeriodicalId":22711,"journal":{"name":"The Journal of Prevention of Alzheimer's Disease","volume":" ","pages":"100119"},"PeriodicalIF":4.3,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143639825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reply to: Mitochondrial dysfunction as the missing link between circadian syndrome and dementia.","authors":"Linling Yu, Xiong Wang","doi":"10.1016/j.tjpad.2025.100126","DOIUrl":"https://doi.org/10.1016/j.tjpad.2025.100126","url":null,"abstract":"","PeriodicalId":22711,"journal":{"name":"The Journal of Prevention of Alzheimer's Disease","volume":" ","pages":"100126"},"PeriodicalIF":4.3,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143606354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Longitudinal associations of carotid artery stiffness with progression of cerebrovascular disease, incident dementia and cognitive decline in older adults.","authors":"Caroline Robert, Lieng-Hsi Ling, Eugene S J Tan, Narayanaswamy Venketasubramanian, Shir Lynn Lim, Lingli Gong, Josephine Lunaria Berboso, Arthur Mark Richards, Christopher Chen, Saima Hilal","doi":"10.1016/j.tjpad.2025.100127","DOIUrl":"https://doi.org/10.1016/j.tjpad.2025.100127","url":null,"abstract":"<p><strong>Background: </strong>Carotid artery stiffness is associated with cerebrovascular disease (CeVD) and cognitive impairment, but evidence for its longitudinal effects on progression of CeVD and cognitive decline are limited.</p><p><strong>Objectives: </strong>To evaluate the longitudinal associations of carotid artery stiffness with CeVD progression, incident dementia, and cognitive decline.</p><p><strong>Design: </strong>Longitudinal analyses from a memory-clinic cohort with a follow-up of 2 years.</p><p><strong>Setting: </strong>A memory-clinic study.</p><p><strong>Participants: </strong>194 participants (mean age=80, 63 % female) with or without cognitive impairments provided consent to take part in the study.</p><p><strong>Measurements: </strong>Participants underwent carotid ultrasonography, brain MRI, and neuropsychological assessments were at baseline and follow-up. Carotid stiffness measures included ß-index, elastic modulus (Ep), and pulse wave velocity-ß (PWV-ß). CeVD markers included white matter hyperintensities (WMH), lacunes, cerebral microbleeds (CMBs) and cortical infarcts. Cognition was assessed with a neuropsychological battery.</p><p><strong>Results: </strong>After 2 years, incident CeVD cases included lacunes (15.7 %), CMBs (23.8 %), and cortical infarcts (7.6 %). ß-index (ß=0.78, p < 0.001), Ep (ß=0.94, p < 0.001), and PWV-ß (ß=0.15, p = 0.003) were independently associated with WMH progression. Ep (ß=-0.15, p = 0.007) and PWV-ß (ß=-3.68, p = 0.007) were independently associated with visuomotor speed decline. No association was found with incident lacunes, CMBs or dementia.</p><p><strong>Conclusion: </strong>Carotid stiffness progression is associated with WMH progression and visuomotor speed decline.</p>","PeriodicalId":22711,"journal":{"name":"The Journal of Prevention of Alzheimer's Disease","volume":" ","pages":"100127"},"PeriodicalIF":4.3,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143597728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Opposite causal effects of type 2 diabetes and metformin on Alzheimer's disease.","authors":"Dongming Liu, Hongbao Cao, Ancha Baranova, Chenxin Xu, Fuquan Zhang","doi":"10.1016/j.tjpad.2025.100129","DOIUrl":"https://doi.org/10.1016/j.tjpad.2025.100129","url":null,"abstract":"<p><strong>Background: </strong>Type 2 diabetes (T2D) is commonly co-morbid with Alzheimer's disease (AD). However, it remains unclear whether T2D itself or the antidiabetic drug metformin contributes to the progression of AD.</p><p><strong>Objective: </strong>This study aimed to investigate the overall and independent effects of T2D and metformin use on the risk of AD.</p><p><strong>Methods: </strong>Summary genome-wide association study datasets were utilized for the Mendelian randomization (MR) and multivariable MR (MVMR) analyses, including ones for T2D (N = 455,017), metformin (N = 456,276), and AD (N = 453,733). Additionally, using the proportional imbalance method, we analyzed AD-related adverse drug events in the FDA Adverse Event Reporting System (FAERS) database (covering Q1 2004 to Q2 2024).</p><p><strong>Results: </strong>Our two-sample MR analysis indicated that T2D is not associated with the risk of AD (OR: 1.03, CI: 0.99-1.08, P = 0.128). However, while not statistically significant, genetic signature for metformin exposure demonstrated a trend toward an increased risk of AD (OR: 1.05, CI: 1.00-1.09, P = 0.053). Interestingly, in MVMR analysis, which evaluates independent effects of T2D and metformin exposure on T2D, we found a robust association of T2D with a decrease in the risk of AD (OR: 0.82, CI: 0.68-0.98, P = 0.031), while the use of metformin was associated with a higher risk of AD (OR: 1.26, CI: 1.06-1.50, P = 9.45E-3). In the FAERS database, a total of 228,283 metformin-related adverse event reports from 67,742 cases were found. For metformin as the target drug and AD as the target adverse event, signal analysis reported 29 cases of AD (ROR: 0.83, 95 % CI: 0.58-1.19, P = 0.3126).</p><p><strong>Conclusions: </strong>Our study reveals the opposite independent causal effects of T2D and metformin exposure on AD. These findings highlight the importance of assessing AD risk when prescribing metformin to patients with T2D.</p>","PeriodicalId":22711,"journal":{"name":"The Journal of Prevention of Alzheimer's Disease","volume":" ","pages":"100129"},"PeriodicalIF":4.3,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143597785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The disease burden, risk factors and future predictions of Alzheimer's disease and other types of dementia in Asia from 1990 to 2021.","authors":"Jinxuan Guo, Pin Wang, Jin Gong, Wenxian Sun, Xiaodong Han, Chang Xu, Aidi Shan, Xin Wang, Heya Luan, Shaoqi Li, Ruina Li, Boye Wen, Runqi Chen, Sirong Lv, Cuibai Wei","doi":"10.1016/j.tjpad.2025.100122","DOIUrl":"https://doi.org/10.1016/j.tjpad.2025.100122","url":null,"abstract":"<p><strong>Background: </strong>There is a lack of analysis and prediction of the disease burden of Alzheimer's disease and other dementias (ADOD) in Asia.</p><p><strong>Objectives: </strong>This study aims to explore the impact of ADOD on the Asian region during the period from 1990 to 2021.</p><p><strong>Design: </strong>Data on ADOD in Asia from 1990 to 2021 were collected from the Global Burden of Disease (GBD) Study 2021. We analyzed the number and age-standardized rates (ASRs) of incidence, prevalence, mortality, and disability-adjusted life-years (DALYs) of ADOD from 1990 to 2021. Joinpoint regression analysis was performed, and the average annual percent changes (AAPCs) were calculated to evaluate the trends during this period. Subsequently, an auto - regressive integrated moving average (ARIMA) prediction model analysis was conducted to assess the trends in the next 30 years, aiming to report the epidemiology and disease burden of ADOD in Asia.</p><p><strong>Results: </strong>According to the analysis of the GBD database in 2021, the deaths, DALYs, incidence, and prevalence of ADOD increased by 297.34 %, 249.54 %, 244.73 %, and 250.44 % in Asia from 1990 to 2021. The ASRs of incidence, prevalence, death, and DALYs in both males and females, which consistently increased over the study period, showed that the ASRs of all females were consistently higher than those of males in Asia from 1990 to 2021. During the period from 1990 to 2021, Qatar and the United Arab Emirates witnessed the greatest changes in the number of DALYs, incidence, and prevalence. Afghanistan and China had the highest age-standardized mortality rate (ASMR) in 2021. It is worth noting that high fasting blood glucose is the top risk factor for the onset of ADOD. Females are more susceptible to the risk factor of high body-mass index (BMI), while males are more likely to be affected by smoking. According to the analysis of the ARIMA prediction model, the disease burden of ADOD in Asia will continue to show an upward trend in the next 30 years.</p><p><strong>Conclusions: </strong>We should pay attention to the issue of population aging, attach importance to the intervention measures targeting the risk factors of ADOD, and formulate action plans to address the rising incidence of ADOD.</p>","PeriodicalId":22711,"journal":{"name":"The Journal of Prevention of Alzheimer's Disease","volume":" ","pages":"100122"},"PeriodicalIF":4.3,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143587056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distinct trajectories of subjective cognitive decline before diagnosis of neurocognitive disorders: Longitudinal modelling over 18 years.","authors":"Tau Ming Liew","doi":"10.1016/j.tjpad.2025.100123","DOIUrl":"https://doi.org/10.1016/j.tjpad.2025.100123","url":null,"abstract":"<p><strong>Background: </strong>Subjective cognitive decline (SCD) is an established predictor of neurocognitive disorders (NCD) (i.e. mild cognitive impairment and dementia). Yet, its construct remains contentious. Many individuals with SCD do not progress to NCD, leading to an alternative term in the literature - 'functional cognitive disorders' - to describe the SCD experience in these individuals.</p><p><strong>Objectives: </strong>To examine the distinct differences in trajectories of SCD between those who did and did not eventually develop NCD.</p><p><strong>Design: </strong>Case-control study.</p><p><strong>Setting: </strong>Alzheimer's Disease Centers across USA.</p><p><strong>Participants: </strong>A total of 5,167 participants aged ≥50 years were followed up near-annually to evaluate for SCD and NCD (median follow-up=8.1 years; range=1.0-18.0). Cases were defined as those who developed incident NCD during follow-up; controls completed ≥10 years of follow-up and had normal cognition throughout follow-up period.</p><p><strong>Measurements: </strong>SCD was evaluated with a yes/no question based on \"perceived decline in memory relative to previously attained abilities\". The trajectories of SCD were modelled with mixed-effect logistic regression, using a backward timescale.</p><p><strong>Results: </strong>Those who developed NCD (cases) had new onset of SCD within past 20 years, which became particularly noticeable 13-14 years before diagnosis, and became even more evident in the last 4 years. Those who did not develop NCD (controls) reported SCD since younger age, with the probability of SCD remaining constant over time. The distinctive trajectories were consistent across Alzheimer's and non-Alzheimer's disease, and among those with higher baseline rates of SCD due to psychiatric conditions.</p><p><strong>Conclusions: </strong>SCD exhibits distinctive trajectories among those who do and do not progress to NCD. These distinctive trajectories can inform NCD risk for early interventions, and guide public health messaging to distinguish high-risk SCD from normal ageing. Future SCD scales may possibly need to evaluate symptom changes over a longer, 20-year horizon to better capture the new onset of SCD within this longer timeframe.</p>","PeriodicalId":22711,"journal":{"name":"The Journal of Prevention of Alzheimer's Disease","volume":" ","pages":"100123"},"PeriodicalIF":4.3,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143586941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning to detect Alzheimer's disease with data on drugs and diagnoses.","authors":"Johanna Wallensten, Caroline Wachtler, Nenad Bogdanovic, Anna Olofsson, Miia Kivipelto, Linus Jönsson, Predrag Petrovic, Axel C Carlsson","doi":"10.1016/j.tjpad.2025.100115","DOIUrl":"https://doi.org/10.1016/j.tjpad.2025.100115","url":null,"abstract":"<p><strong>Background: </strong>Integrating machine learning with medical records offers potential for early detection of Alzheimer's disease (AD), enabling timely interventions.</p><p><strong>Objectives: </strong>This study aimed to evaluate the effectiveness of machine learning in constructing a predictive model for AD, designed to predict AD with data up to three years before diagnosis. Using clinical data, including prior diagnoses and medical treatments, we sought to enhance sensitivity and specificity in diagnostic procedures. A second aim was to identify the most important factors in the machine learning models, as these may be important predictors of AD.</p><p><strong>Design: </strong>The study employed Stochastic Gradient Boosting, a machine learning method, to identify diagnoses predictive of AD using primary healthcare data. The analyses were stratified by sex and age groups.</p><p><strong>Setting: </strong>The study included individuals within Region Stockholm, Sweden, using medical records from 2010 to 2022.</p><p><strong>Participants: </strong>The study analyzed clinical data for individuals over the age of 40. Patients with an AD diagnosis (ICD-10-SE codes F00 or G30) during 2010-2012 were excluded to ensure prospective modeling. In total, AD was identified in 3,407 patients aged 41-69 years and 25,796 patients aged over 69.</p><p><strong>Measurements: </strong>The machine learning model ranked predictive diagnoses, with performance assessed by the area under the receiver operating characteristic curve (AUC). Known and novel predictors were evaluated for their contribution to AD risk.</p><p><strong>Results: </strong>AUC values ranged from 0.748 (women aged 41-69) to 0.816 (women over 69), with men across age groups falling within this range. Sensitivity and specificity ranged from 0.73 to 0.79 and 0.66 to 0.79, respectively, across age and gender groups. Negative predictive values were consistently high (≥0.954), while positive predictive values were lower (0.199-0.351). Additionally, we confirmed known risk factors as predictors and identified novel predictors that warrant further investigation. Key predictors included medical observations, cognitive symptoms, antidepressant treatment, visit frequency, and vitamin B12/folic acid treatment.</p><p><strong>Conclusions: </strong>Machine learning applied to clinical data shows promise in predicting AD, with robust model performance across age and sex groups. The findings confirmed known risk factors, such as depression and vitamin B12 deficiency, while also identifying novel predictors that may guide future research. Clinically, this approach could enhance early detection and risk stratification, facilitating timely interventions and improving patient outcomes.</p>","PeriodicalId":22711,"journal":{"name":"The Journal of Prevention of Alzheimer's Disease","volume":" ","pages":"100115"},"PeriodicalIF":4.3,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143587005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Healthy dietary patterns in relation to cognitive performance and Alzheimer's disease mortality.","authors":"Yiying Gong, Hui Chen, Yuxuan Gu, Jie Shen, Ting Shen, Yihong Ding, Mengxi Lu, Liyan Huang, Minqing Yan, Peige Song, Yajie Zhu, Shuang Rong, Changzheng Yuan","doi":"10.1016/j.tjpad.2025.100100","DOIUrl":"https://doi.org/10.1016/j.tjpad.2025.100100","url":null,"abstract":"<p><strong>Background: </strong>Dietary factors play a major role in cognitive aging, but few studies have assessed and compared the associations between specific dietary patterns and Alzheimer's disease (AD) mortality.</p><p><strong>Methods: </strong>We included 27,773 U.S. participants (mean age = 59.8 years, 51.4 % female) from the National Health and Nutrition Examination Survey (NHANES) between 1998 and 2016, with follow-up for AD mortality until December 2019. Five dietary pattern scores were calculated utilizing one (1999-2002) or two repeated (2003-2016) 24hr dietary recalls, including the Healthy Eating Index (HEI-2015), the healthful plant-based diet index (hPDI), the alternate Mediterranean diet (aMED), the Dietary Approach to Stop Hypertension diet (DASH), and the Mediterranean-DASH Intervention for Neurodegeneration Delay diet (MIND) scores. We utilized Cox proportional hazard models to evaluate the associations of these dietary pattern scores with AD mortality.</p><p><strong>Results: </strong>A total of 260 AD deaths occurred during a median follow-up of 9.8 years. Higher aMED score was associated with a lower risk of AD mortality (HR_T3_{vs T1}: 0.72, 95 % CI, 0.52-1.00, p-trend = 0.041). In a sub-sample of 2,713 participants in NHANES 2011-2014, 432 individuals had prevalent psychometric mild cognitive impairment (p-MCI). Higher aMED, MIND, HEI-2015, and hPDI were associated with lower odds of p-MCI. The potential contributors to these associations included higher intake levels of vegetables and nuts, moderate alcohol consumption, and lower intake level of sweets.</p><p><strong>Conclusions: </strong>The Mediterranean dietary pattern was associated with more favorable cognitive outcomes among middle-aged and older adults, underscoring the importance of a healthy diet for long-term benefits in cognitive and brain health.</p>","PeriodicalId":22711,"journal":{"name":"The Journal of Prevention of Alzheimer's Disease","volume":" ","pages":"100100"},"PeriodicalIF":4.3,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143586980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mitochondrial dysfunction as the missing link between circadian syndrome and dementia.","authors":"Yu-Hsiang Lin, Kuo-Jen Lin, Po-Ting Lin","doi":"10.1016/j.tjpad.2025.100125","DOIUrl":"https://doi.org/10.1016/j.tjpad.2025.100125","url":null,"abstract":"","PeriodicalId":22711,"journal":{"name":"The Journal of Prevention of Alzheimer's Disease","volume":" ","pages":"100125"},"PeriodicalIF":4.3,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143587094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing statin research for Alzheimer's prevention: Suggestions for future studies and policy implications.","authors":"Yumei Zhong, Shanshan Liu, Xiaofeng Lv","doi":"10.1016/j.tjpad.2025.100118","DOIUrl":"https://doi.org/10.1016/j.tjpad.2025.100118","url":null,"abstract":"","PeriodicalId":22711,"journal":{"name":"The Journal of Prevention of Alzheimer's Disease","volume":" ","pages":"100118"},"PeriodicalIF":4.3,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143634500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}