Alzheimer's Research & Therapy最新文献

Background: Several health conditions are known to increase the risk of Alzheimer's disease (AD). We aim to systematically identify medical conditions that are associated with subsequent development of AD by leveraging the growing resources of electronic health records (EHRs).

Methods: This retrospective cohort study used de-identified EHRs from two independent databases (MarketScan and VUMC) with 153 million individuals to identify AD cases and age- and gender-matched controls. By tracking their EHRs over a 10-year window before AD diagnosis and comparing the EHRs between AD cases and controls, we identified medical conditions that occur more likely in those who later develop AD. We further assessed the genetic underpinnings of these conditions in relation to AD genetics using data from two large-scale biobanks (BioVU and UK Biobank, total N = 450,000).

Results: We identified 43,508 AD cases and 419,455 matched controls in MarketScan, and 1,320 AD cases and 12,720 matched controls in VUMC. We detected 406 and 102 medical phenotypes that are significantly enriched among the future AD cases in MarketScan and VUMC databases, respectively. In both EHR databases, mental disorders and neurological disorders emerged as the top two most enriched clinical categories. More than 70 medical phenotypes are replicated in both EHR databases, which are dominated by mental disorders (e.g., depression), neurological disorders (e.g., sleep orders), circulatory system disorders (e.g. cerebral atherosclerosis) and endocrine/metabolic disorders (e.g., type 2 diabetes). We identified 19 phenotypes that are either associated with individual risk variants of AD or a polygenic risk score of AD.

Conclusions: In this study, analysis of longitudinal EHRs from independent large-scale databases enables robust identification of health conditions associated with subsequent development of AD, highlighting potential opportunities of therapeutics and interventions to reduce AD risk.

Background: Few population-based studies have investigated how the prevalence, incidence, and survival rate of dementia have changed since the 2010s in Asian communities. We investigated this issue using 37 years of epidemiological data in a Japanese community.

Methods: Seven cross-sectional surveys of dementia were conducted among residents aged ≥ 65 years in a Japanese community in 1985, 1992, 1998, 2005, 2012, 2017, and 2022. We also established three cohorts in the residents aged ≥ 65 years without dementia in 1988 (n = 803), 2002 (n = 1,231), and 2012 (n = 1,519), each of which was followed for 10 years. Trends in the prevalence of dementia were tested using a logistic regression model. The age- and sex-adjusted incidence of dementia and survival rate after dementia onset were compared across cohorts using a Cox proportional hazards model.

Results: The crude prevalence of dementia significantly increased from 1985 to 2012 (6.7% in 1985, 5.7% in 1992, 7.1% in 1998, 12.5% in 2005, and 17.9% in 2012, p for trend < 0.01), but then decreased significantly from 2012 to 2022 (15.8% in 2017 and 12.1% in 2022; p for trend < 0.01). A similar trend was observed after adjusting for age and sex. Moreover, the age- and sex-adjusted incidence of dementia increased significantly from the 1988 to the 2002 cohort (adjusted hazard ratio [aHR] 1.68, 95% confidence intervals [CI] = 1.38-2.06), but decreased significantly from the 2002 to the 2012 cohort (aHR = 0.60, 95% CI = 0.51-0.70). The age- and sex-adjusted 5-year survival rate after dementia onset increased significantly from the 1988 to the 2002 cohort (47.3% to 65.2%; p < 0.01), while no significant change was observed from the 2002 to the 2012 cohort (65.2% to 58.9%; p = 0.42).

Conclusions: Decreasing trends in the prevalence and incidence of dementia were observed since 2012 in a Japanese community. The decline in the incidence of dementia may be due to the prevention and improved management of lifestyle-related diseases, such as hypertension and diabetes, as well as increased awareness and promotion of healthy lifestyle behaviors.

Introduction: Alzheimer's disease (AD) is the leading cause of dementia in China, but deeply phenotyped clinical cohorts remain limited. The Biomarker and Clinical changes across the Alzheimer's continuum Study (BCAS) was established at the First Affiliated Hospital, Zhejiang University School of Medicine to capture biological and clinical changes across the AD spectrum.

Methods: BCAS is an ongoing, longitudinal memory clinic-based cohort initiated in 2016 in Zhejiang, one of China's most economically vigorous and rapidly aging regions. Individuals aged ≥ 40 years with cognitive concerns are recruited and undergo standardized clinical evaluation, comprehensive neuropsychological testing, biospecimen collection, and multimodal neuroimaging including MRI and amyloid and tau PET in subsets. Participants are followed every 1-2 years with repeat assessments. This paper reports baseline characteristics and preliminary findings from the first 1,013 participants enrolled up to January 2025.

Results: Participants had a mean age of 66.5 years (SD 9.6), with 49.8% women and an average of 9.7 years of education. Hypertension (41.4%), diabetes (14.6%), and hypercholesterolemia (12.0%) were the most prevalent comorbidities. The mean MoCA score was 19.2 (SD 6.1). Mean cognitive scores showed gradient decline across diagnostic groups from cognitively unimpaired, mild cognitive impairment to dementia, consistent with expected disease severity. Tau PET positivity showed a numerically larger cognitive z-score difference (-0.973 for T + vs. T-) compared with amyloid PET positivity (-0.530 for A + vs. A-). Among risk factors, higher age and diabetes were linked to lower scores, whereas higher education, tea consumption, and higher BMI were associated with better cognitive performance.

Conclusions: The BCAS served as a biomarker-rich and multimodal resource to study the clinical and biological progression of AD in China. Preliminary analyses demonstrate expected associations and support the data quality. BCAS will act as a platform for biomarker validation and precision approaches to AD diagnosis and intervention.