Journal of Alzheimer's Disease最新文献

Background: With increasing age, dementia is a common disease in the elderly population，especially Alzheimer's disease. Owing to the nature of the disease, the function of patients deteriorates, which places a heavy burden on the country and family. Home-based training programs have been shown to improve cognitive function in patients with dementia.

Objective: To examine the effects and methods of home-based interventions on the cognitive performance of patients with dementia.

Methods: This systematic review and meta-analysis was conducted on the basis of the PRISMA statement. This protocol was registered in advance at PROSPERO (CRD42021277269). Six English electronic databases, including PubMed, EMBASE, the Cochrane Library, Web of Science, SCOPUS, and OTseeker, were searched and updated to January 31, 2024. Two researchers independently completed the literature retrieval and data extraction. RevMan 5.3 software was used to analyze the data. The standardized mean difference and the 95% confidence interval were used for statistical analysis. Subgroup analyses were performed by assessment tools, intervention duration and intervention methods.

Results: Twenty randomized controlled trials with 3543 participants were included in the qualitative synthesis, and 17 studies were included in the meta-analysis. Compared with the control intervention, the home-based intervention significantly improved cognitive performance (SMD = 0.45; 95% CI = [0.17, 0.74]; p = 0.002).

Conclusions: Moderate to high evidence shows that home-based interventions significantly improve the cognitive performance of patients with dementia, especially their comprehensive cognitive function.

Background: Lecanemab, a novel monoclonal antibody targeting amyloid-β, has shown promise in treating Alzheimer's disease. Comprehensive post-marketing safety data analysis is crucial to understand its real-world risk profile.

Objective: This study aimed to evaluate the safety profile of lecanemab using data from the FDA Adverse Event Reporting System (FAERS), with a focus on nervous system disorders and amyloid-related imaging abnormalities.

Methods: We conducted a disproportionality analysis using the FAERS database to evaluate the safety signals associated with lecanemab. Reporting odds ratio (ROR), proportional reporting ratio, empirical Bayesian geometric mean, and information component were calculated at both system organ class (SOC) and preferred term (PT) levels. Additionally, we performed a time-to-onset analysis using Weibull shape parameter estimation.

Results: Analysis at the SOC level revealed significant signals for nervous system disorders (ROR: 7.32, 95% CI: 6.69-8.00). At the PT level, strong signals were observed for amyloid-related imaging abnormalities, particularly those associated with microhemorrhages and oedema (ROR: 4122.81 and 3922.78, respectively). Headache was the most frequently reported adverse event (200 cases), followed by chills (107 cases) and fatigue (97 cases). Time-to-onset analysis showed a median time of 33 days (range: 1-1283) for all adverse events, with neurological events occurring slightly later (median: 42 days, range: 1-1260).

Conclusions: Our findings highlight a distinct safety profile for lecanemab, with a predominant impact on the nervous system and a notable association with imaging abnormalities. These results underscore the importance of vigilant monitoring and further research to optimize the risk-benefit profile of lecanemab in clinical practice.

Background: Single-subject voxel-based morphometry (VBM) is a powerful technique for reader-independent detection of brain atrophy in structural magnetic resonance imaging (MRI) to support the (differential) diagnosis and staging of neurodegenerative diseases in individual patients. However, VBM is sensitive to the MRI scanner platform and details of the acquisition sequence. To mitigate this limitation, we recently proposed and technically validated a convolutional neural network (CNN)-based VBM which does not rely on a normative reference database.

Objective: Clinical validation of CNN-based VBM.

Methods: CNN-based VBM was compared with conventional VBM based on a mixed-scanner normative database in 227 consecutive patients (66.0 ± 9.6 years, 53.3% female) with suspected dementing neurodegenerative disease. VBM maps were interpreted visually by two experienced readers, first with respect to the presence of any neurodegenerative disease, then for the differentiation between Alzheimer's disease (AD)-typical and non-AD atrophy patterns. A Likert 6-score was used for both tasks. Simultaneously acquired positron emission tomography (PET) with ¹⁸F-fluorodeoxyglucose (FDG) served as reference standard.

Results: Repeated-measures ANOVA revealed a significant impact of the VBM method on the visual detection of any neurodegenerative disease (p < 0.001). Balanced accuracy/sensitivity/specificity were 80.4/86.3/74.5% for CNN-based VBM versus 75.7/79.5/71.8% for conventional VBM. Differentiation between AD and non-AD typical atrophy patterns did not differ between both VBM methods (p = 0.871).

Conclusions: CNN-based VBM provides clinically useful accuracy for the detection of neurodegeneration-suspect atrophy with higher sensitivity than conventional VBM with a mixed-scanner normative reference database and without compromising specificity.

Background: Although previous studies have shown that cognitive decline in Alzheimer's disease (AD) is associated with various risk factors, they primarily focused on late-onset AD (LOAD).

Objective: We aim to evaluate the differential impact of risk factors on the cognitive decline between early-onset AD (EOAD, onset < 65 years) and LOAD (onset $\ge$ 65 years) and explore the longitudinal effect of Apolipoprotein E allele 4 (APOE ε4) on cortical atrophy in both cohorts.

Methods: Using data from 212 EOAD and 1101 LOAD participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI), we conducted multivariable mixed-effect models to evaluate the impact of APOE ε4, education, hypertension, diabetes, dyslipidemia, and body mass index on cognitive performance. Preprocessed MRI data were utilized for longitudinal parametric mapping.

Results: APOE ε4 carriers in both groups showed significantly accelerated declines in language, verbal memory, executive function, and general cognition. By controlling other significant risk factors, APOE ε4 carriers showed faster declines in language and verbal memory in both groups. Females exhibited accelerated declines in Language and verbal memory in the EOAD and LOAD cohorts respectively. LOAD individuals with hypertension showed faster declines while overweight and obese participants displayed slower declines in both cohorts across all domains except visuospatial. Notably, APOE ε4 status was associated with longitudinal cortical atrophy in the LOAD cohort but not in the EOAD cohort.

Conclusions: Known risk factors for AD were associated with cognitive decline in both EOAD and LOAD cohorts.

Background: Pharmacological treatment of behavioral and psychological symptoms of dementia is of limited benefit. The addition of non-pharmacological interventions is often essential for optimal symptom control. Music is a viable way to help patients communicate and improve their quality of life.

Objective: This study aims to find the most effective way to use music in a busy dementia ward.

Methods: 17 inpatients (aged 63-93 years) with a clinical diagnosis of Alzheimer's disease and dementia took part over five weeks. Music lyrics presented via free-field speakers were individualized to personal preferences. Instruments (e.g., maracas) were used in some group sessions. We used the Neuropsychiatric Inventory Questionnaire (NPI-Q) and Music in Dementia Assessment Scales (MiDAS) to evaluate patients' behavior before and after musical intervention.

Results: There was a significant difference in mean NPI-Q scores before and after the music intervention. Specifically, Delusion, Motor Disturbances, and Agitation scores were significantly reduced after music intervention. This was accompanied by significant improvements in Interest, Response, and Enjoyment of MiDAS items during specific intervals.

Conclusions: Clinical professionals can successfully deliver music-based intervention to inpatients with advanced dementia to help manage their behavioral symptoms in the short term. Music-based interventions' use for inpatient wards must be further investigated as an economical and personalized non-pharmacological therapeutic tool for patients with dementia.

Background: Sensory impairments have been linked to dementia. However, the impact of dual sensory impairment (DSI), combining both vision impairment and hearing impairment, on dementia has shown inconsistent results.

Objective: To systematically review the evidence on the association DSI and dementia.

Methods: A systematic literature search was conducted using MEDLINE, EMBASE, and the Cochrane Library databases. Included studies were prospective or retrospective cohort studies and a case-control study. The primary outcome was the onset of dementia or its various subtypes, including Alzheimer's disease (AD) and vascular dementia (VaD). Effect sizes, including hazard ratios (HRs), were pooled through a random-effects model.

Results: A total of 11 observational studies with 346,659 participants were included. DSI was significantly associated with the incidence of dementia compared to no sensory impairment (9 studies; HR: 1.46; 95% confidence interval [CI]: 1.29-1.65). Among subtypes of dementia, DSI was associated with AD onset (4 studies; HR: 2.07; 95% CI: 1.45-2.94); however, this association was not found in VaD (2 studies; HR: 1.65; 95% CI: 0.96-2.85).

Conclusions: These findings suggest that DSI is significantly associated with an increased risk of dementia. Further research is required to identify preventive strategies to decrease the incidence of dementia in individuals with sensory impairment.

Background: Alzheimer's disease (AD) is a complex neurodegenerative disease marked by increased amyloid-β (Aβ) deposition, tau hyperphosphorylation, impaired energy metabolism, and chronic ischemia-type injury. Cerebral microvascular dysfunction likely contributes to AD pathology, but its precise pathogenic role has been poorly defined.

Objective: To examine microvascular reactivity to endothelium-dependent vasodilators and small conductance calcium-activated potassium (SK) channel activity in an intracerebral streptozotocin (STZ)-induced AD mouse model.

Methods: Control and STZ-AD mice underwent Morris Water Maze and Barnes testing, after which cerebral microvascular and brain microvascular endothelial cells (MBMECs) were dissected to assess microvascular reactivity, responses to SK channel activator NS309, and ion-channel current recordings using whole-cell patch clamp methodology. Control mouse cerebral microvascular and human brain microvascular endothelial cells (HBMECs) were treated with soluble Aβ_1-42 peptide to characterize microvascular reactivity and endothelial potassium currents.

Results: STZ-AD mice exhibited impaired performance vs control mice in behavioral testing. STZ-AD mice also exhibited diminished cerebral microvascular responsiveness and MBMECs potassium current augmentation in response to NS309 compared with control mice. Incubation of control mouse cerebral micro-vessels and HBMECs with soluble Aβ (1 µM) for 2 h attenuated relaxation responses to NS309 and diminished NS309-sensitive endothelial potassium currents.

Conclusions: STZ-AD mice exhibited impaired microvascular relaxation responses to endothelium-dependent vasodilators; SK/IK channel dysfunction may be involved in the mechanism of this impairment. Acute treatment with Aβ produced dysregulated cerebrovascular endothelial SK/IK channels. Further elucidation of the role of microvascular dysfunction in AD is needed to prevent the chronic ischemia-type injury that contributes to cognitive decline.

Background: The aim of this study was to examine the potential added value of including neuropsychiatric symptoms (NPS) in machine learning (ML) models, along with demographic features and Alzheimer's disease (AD) biomarkers, to predict decline or non-decline in global and domain-specific cognitive scores among community-dwelling older adults.

Objective: To evaluate the impact of adding NPS to AD biomarkers on ML model accuracy in predicting cognitive decline among older adults.

Methods: The study was conducted in the setting of the Mayo Clinic Study of Aging, including participants aged ≥ 50 years with information on demographics (i.e., age, sex, education), NPS (i.e., Neuropsychiatric Inventory Questionnaire; Beck Depression and Anxiety Inventories), at least one AD biomarker (i.e., plasma-, neuroimaging- and/or cerebrospinal fluid [CSF]-derived), and at least 2 repeated neuropsychological assessments. We trained and tested ML models using a stepwise feature addition approach to predict decline versus non-decline in global and domain-specific (i.e., memory, language, visuospatial, and attention/executive function) cognitive scores.

Results: ML models had better performance when NPS were included along with a) neuroimaging biomarkers for predicting decline in global cognition, as well as language and visuospatial skills; b) plasma-derived biomarkers for predicting decline in visuospatial skills; and c) CSF-derived biomarkers for predicting decline in attention/executive function, language, and memory.

Conclusions: NPS, added to ML models including demographic and AD biomarker data, improves prediction of downward trajectories in global and domain-specific cognitive scores among community-dwelling older adults, albeit effect sizes are small. These preliminary findings need to be confirmed by future cohort studies.

Background: Urinary formic acid (FA) has been reported to be a biomarker for Alzheimer's disease (AD). However, the association between FA and pathological changes in memory clinic patients is currently unclear.

Objective: This study aims to investigate associations between FA and pathological changes across different cognitive statuses in memory clinic patients.

Methods: A cohort of patients with mild cognitive impairment (MCI-Aβ- n = 37, MCI-Aβ+ n = 33), AD dementia (n = 39), and cognitively normal subjects (CN-Aβ- n = 98, CN-Aβ+ n = 50) were included. Comprehensive neuropsychological assessment, urinary FA, AD-related plasma biomarkers, MRI scans, [¹⁸F]-flurbetapir and [¹⁸F]-FDG PET scan data were collected from all participants.

Results: Urinary FA levels were higher in patients with MCI and AD than in CN subjects and higher in Aβ+ (CN- Aβ+, MCI-Aβ+, AD dementia) subjects than in Aβ-subjects (CN- Aβ-, MCI-Aβ-). Urinary FA was positively associated with cerebral Aβ deposition and negatively associated with glucose metabolism, both at the global level and in multiple regions of interest cortical regions in participants with different cognitive statuses. Additionally, urinary FA levels were positively correlated with the severity of white matter hyperintensities and hippocampal atrophy. Urinary FA combined with age, Mini-Mental State Examination, plasma p-tau181, and neurofilament light chain could be used to predict Aβ deposition in the brain.

Conclusions: Urinary FA is associated with brain pathological changes in memory clinic patients, including cerebral Aβ deposition, glucose metabolism, white matter hyperintensities, and hippocampal atrophy. It could be used as a biomarker for the early diagnosis of AD and predicting Aβ deposition.

Background: Cerebral small vessel disease (SVD) is the leading cause of vascular dementia. However, it is unclear whether the individual SVD or global SVD progression correlates with cognitive decline across mild cognitive impairment (MCI) subjects.

Objective: To investigate the association of small vessel disease progression with longitudinal cognitive decline across MCI.

Methods: We included 432 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, with 151 participants in the cognitively normal (CN) group and 281 participants in the MCI group. We evaluated magnetic resonance imaging-based SVD markers in both CN and MCI groups and explored their associations with 12-and 24-month cognitive decline using linear mixing effect (LME) models.

Results: In the CN group, cerebral microbleed (CMB) progression was associated with the decline in language function (p < 0.05), and deep white matter hyperintensity (WMH) progression was associated with a decline in memory function (p < 0.05). In the MCI group, CMB progression was associated with a decline in memory function (p < 0.05) and lacunes progression was associated with executive function (p < 0.05), whereas the progression of global SVD score was not related to longitudinal cognitive function.

Conclusions: The progression of CMB and WMH had an impact on cognitive decline in both CN and MCI groups, and lacunes progression only had an association with cognitive decline in the MCI group. Our study suggested that individual SVD markers may have a higher predictive value in longitudinal cognition compared with global SVD burden.