Jpad-Journal of Prevention of Alzheimers Disease最新文献

Background: Aging is considered a key risk factor for Alzheimer's disease (AD). This study aimed to identify and validate potential aging-related genes associated with AD using bioinformatics analysis.

Methods: Datasets GSE36980 and GSE5281 were selected to screen differentially expressed genes (DEGs), and the immune cell correlation analysis and GSEA analysis of DEGs were performed. The intersection with senescence genes was taken as differentially expressed senescence-related genes (DESRGs), and the GSE44770 dataset was used for further validation. The potential biological functions and signaling pathways were determined by GO and KEGG, and the hub genes were identified by 12 algorithms in Cytohubba. The expression of 10 hub genes in different brain regions was determined and single-cell sequencing analysis was performed, and diagnostic genes were further screened by gene expression and receiver operating characteristic (ROC) curve. Finally, a miRNA-gene network of diagnostic genes was constructed and targeted drug prediction was performed.

Results: A total of 2137 DEGs were screened from the GSE36980 and GSE5281 datasets, and 278 SRGs were identified from the CellAge database. The overlapping DEGs and SRGs constituted 29 DESRGs, including 14 senescence suppressor genes and 15 senescence inducible genes. The top 10 hub genes, including MDH1, CKB, PSMD14, SMARCA4, PEBP1, DDB2, ITPKB, ATF7IP, YAP1, and EWSR1 were screened. Furthermore, four diagnostic genes were identified: PMSD14, PEBP1, ITPKB, and ATF7IP. The ROC analysis showed that the respective area under the curves (AUCs) of PMSD14, PEBP1, ITPKB, and ATF7IP were 0.732, 0.701, 0.747, and 0.703 in the GSE36980 dataset and 0.870, 0.817, 0.902, and 0.834 in the GSE5281 dataset. In the GSE44770 dataset, PMSD14 (AUC, 0.838) and ITPKB (AUC, 0.952) had very high diagnostic values in the early stage of AD. Finally, based on these diagnostic genes, we found that the drug Abemaciclib is a targeted drug for the treatment of age-related AD. Flutamide can aggravate aging-related AD.

Conclusion: The results of this study suggest that cellular SRGs might play an important role in AD. PMSD14, PEBP1, ITPKB, and ATF7IP have the potential as specific biomarkers for the early diagnosis of AD.

Background: Longitudinal changes in volumetric MRI outcome measures have been shown to correlate well with longitudinal changes in clinical instruments and have been widely used as biomarker outcomes in clinical trials for Alzheimer's disease (AD). While instances of discordant findings have been noted in some trials, especially the recent amyloid-removing therapies, the overall relationship between treatment effects on brain atrophy and clinical outcomes, and how it might depend on treatment target or mechanism, clinical instrument or imaging variable is not yet clear.

Objective: To systematically assess the consistency and therapeutic class-dependence of treatment effects on clinical outcomes and on brain atrophy in published reports of clinical trials conducted in mild cognitive impairment (MCI) and/or AD.

Design: Quantitative review of the published literature. The consistency of treatment effects on clinical and brain atrophy outcomes was assessed in terms of statistical agreement with hypothesized equal magnitude effects (e.g., 30% slowing of both) and nominal directional concordance, as a function of therapeutic class.

Setting: Interventional randomized clinical trials.

Participants: MCI or AD trial participants.

Intervention: Treatments included were those that involved ingestion or injection of a putatively active substance into the body, encompassing both pharmacological and controlled dietary interventions.

Measurements: Each trial included in the analysis reported at least one of the required clinical outcomes (ADAS-Cog, CDR-SB or MMSE) and at least one of the required imaging outcomes (whole brain, ventricular or hippocampal volume).

Results: Data from 35 trials, comprising 185 pairwise comparisons, were included. Overall, the 95% confidence bounds overlapped with the line of identity for 150/185 (81%) of the imaging-clinical variable pairs. The greatest proportion of outliers was found in trials of anti-amyloid antibodies that have been shown to dramatically reduce the level of PET-detectable amyloid plaques, for which only 13/33 (39%) of observations overlapped the identity line. A Deming regression calculated using all data points yielded a slope of 0.54, whereas if data points from the amyloid remover class were excluded, the Deming regression line had a slope of 0.92. Directional discordance of treatment effects was also most pronounced for the amyloid-removing class, and for comparisons involving ventricular volume.

Conclusion: Our results provide a frame of reference for the interpretation of clinical and brain atrophy results from future clinical trials and highlight the importance of mechanism of action in the interpretation of imaging results.

Background: While the amyloid/tau/neurodegeneration (ATN) framework has found wide application in Alzheimer's disease research, it is unclear if thresholds obtained using distinct thresholding methods are concordant within the same dataset and interchangeable across cohorts.

Objectives: To investigate the robustness of data-driven thresholding methods and ATN profiling across cohort datasets.

Design and setting: We evaluated the impact of thresholding methods on ATN profiles by applying five commonly-used methodologies across cohort datasets. We assessed the generalizability of disease patterns discovered within ATN profiles by clustering individuals from different cohorts who were assigned to the same ATN profile.

Participants and measurements: Participants with available CSF amyloid-β 1-42, phosphorylated tau, and total tau measurements were included from eleven AD cohort studies.

Results: We observed high variability among obtained ATN thresholds, both across methods and datasets that impacted the resulting profile assignments of participants significantly. Clustering participants from different cohorts within the same ATN category indicated that identified disease patterns were comparable across most cohorts and biases introduced through distinct thresholding and data representations remained insignificant in most ATN profiles.

Conlusion: Thresholding method selection is a decision of statistical relevance that will inevitably bias the resulting profiling and affect its sensitivity and specificity. Thresholds are likely not directly interchangeable between independent cohorts. To apply the ATN framework as an actionable and robust profiling scheme, a comprehensive understanding of the impact of used thresholding methods, their statistical implications, and a validation of results is crucial.

Background: To investigate the causal relationship between testosterone (BT) levels and Alzheimer's disease (AD) risk and to quantify the role of obesity and lipid metabolism as potential mediators.

Methods: We used a two-sample, two-step MR to determine:1) the causal effect of BT levels on AD; 2) the causal effect of two lipid metabolites, obesity and LDLc on AD; and 3) the mediating effects of these metabolites. Pooled data for BT levels and lipid metabolism were obtained from the UK Biobank. AD data were obtained from the Alzheimer's Disease Project International Genomics Consortium, FinnGen Consortium, and UK Biobank study. Effect estimates from external genome-wide association study (GWAS) pooled statistics were obtained using inverse variance-weighted (IVW) MR analysis.

Results: Higher levels of BT were associated with a reduced risk of AD (odds ratio [OR] 0.9992, 95% CI 0.9985-0.9998, P = 0.019), and there was a negative correlation with LDLc (OR 0.9208, 95% CI 0.8569-0.9895, P = 0.024) and obesity class 2 (OC2) (OR 0.7445, 95% CI 0.5873-0.9437, P = 0.014). Conversely, there was a positive correlation between LDLc (OR 1.0014, 95% CI 1.0000-1.0029, P = 0.043) and OC2 (OR 1.0005, 95% CI 1.0001-1.0009, P = 0.003) and AD. Mediation analysis showed that the indirect effect of BT levels on AD was achieved through LDLc and OC2, which accounted for 17% and 17% of the total effect, respectively.

Conclusion: Our study identified a causal role of BT levels in LDLc and OC2. BT levels may affect AD through LDLc and OC2 metabolic processes.

In patients with Alzheimer's disease pathophysiological changes of the brain that initiate the onset of Alzheimer's disease include accumulation of amyloid-β plaques and phosphorylation of tau-tangles. A rather recently considered risk factor for the onset of Alzheimer's disease is poor oral health. The aim of this systematic review of the literature was to assess the potential association(s) of oral health as a risk factor for the onset of Alzheimer's disease. After a systematic search of Pubmed, Embase and Web of Science. A total of 1962 studies were assessed, of which 17 studies demonstrated possible associations between oral health diseases and Alzheimer's disease. 4 theories could be distinguished that describe the possible links between oral health and the development or onset of Alzheimer's disease; 1) role of pathogens, 2) role of inflammatory mediators, 3) role of APOE alleles and 4) role of Aβ peptide. The main common denominator of all the theories is the neuroinflammation due to poor oral health. Yet, there is insufficient evidence to prove a link due to the diversity of the designs used and the quality of the study design of the included studies. Therefore, further research is needed to find causal links between oral health and neuroinflammation that possibly can lead to the onset of Alzheimer's disease with the future intention to prevent cognitive decline by better dental care.

Background: Alzheimer's disease (AD) is the leading cause of dementia in older adults, but most people are not diagnosed until significant neuronal loss has likely occurred along with a decline in cognition. Non-invasive and cost-effective digital biomarkers for AD have the potential to improve early detection.

Objective: We examined the validity of DCTclockTM (a digitized clock drawing task) as an AD susceptibility biomarker.

Design: We used two primary independent variables, Apolipoprotein E (APOE) ε4 allele carrier status and polygenic risk score (PRS). We examined APOE and PRS associations with DCTclockTM composite scores as dependent measures.

Setting: We used existing data from the Framingham Heart Study (FHS), a community-based study with the largest dataset of digital clock drawing data to date.

Participants: The sample consisted of 2,398 older adults ages 60-94 with DCTclockTM data (mean age of 72.3, 55% female and 92% White).

Measurements: PRS was calculated using 38 variants identified in a recent large genome-wide association study (GWAS) and meta-analysis of late-onset AD (LOAD).

Results: Results showed that DCTclockTM performance decreased with advancing age, lower education, and the presence of one or more copies of APOE ε4. Lower DCTclockTM Total Score as well as lower composite scores for Information Processing Speed (both command and copy conditions) and Drawing Efficiency (command condition) were significantly associated with higher PRS levels and more copies of APOE ε4. APOE and PRS associations displayed similar effect sizes in both men and women.

Conclusions: Our results indicate that higher AD genetic risk is associated with poorer DCTclockTM performance in older adults without dementia. This is the first study to demonstrate significant differences in clock drawing performance on the basis of APOE status or PRS.

Background: Several lifestyle, cardiovascular and psychosocial factors are associated with risk of cognitive decline and dementia. We studied the independent associations of a broad set of modifiable risk factors with decline in processing speed in three large population-based cohorts with up to 23 years of follow-up.

Methods: We used data of 9,666 participants from the Doetinchem Cohort Study, the Longitudinal Aging Study Amsterdam, and the Maastricht Aging Study. Decline in processing speed was measured with the letter digit substitution task or the alphabet coding task and modeled using quadratic latent growth curves. Associations of modifiable risk factors with level and rate of decline in processing speed were investigated by estimating associations with level of processing speed at different centering ages.

Results: Latent growth curves showed that decline in processing speed accelerated with age. Smoking, not drinking alcohol and depressive symptoms were associated with a lower level of processing speed in all cohorts. In two of the cohorts, more physical activity, drinking more than two glasses of alcohol per day, higher BMI and diabetes were associated with a lower level of processing speed. Depressive symptoms and diabetes were also associated with faster decline in processing speed.

Conclusion: Several modifiable risk factors are associated with the level of processing speed in older age, while few are also related to the rate of decline.

Background: Alzheimer's disease (AD) and vascular cognitive impairment (VCI) are the two main causes of dementia. AD and VCI share similar symptoms of cognitive decline and may be attributable to similar risk factors. Establishing a prospective cohort to compare VCI and AD would help to understand vascular risk factors related to dementia.

Objectives: China Alzheimer's disease and Neurodegenerative Disorder Research (CANDOR) study is a prospective multicenter cohort study. It aims to study the similarities and differences between AD and post stroke cognitive impairment (PSCI) in neuroimaging changes, disease progression, and multiple omics studies.

Design: This is an ongoing study. From July 31, 2019, to August 1, 2022, we recruited 1449 participants with ages between 40 and 100 years. The cohort included three groups: AD group, PSCI group, and normal cognitive (NC) group. Data were collected in face-to-face interviews at baseline, and will be followed up every year for 4 years. The PSCI group had additional follow-ups at 3-month and 6-month after enrollment. Brain Magnetic Resonance Imaging (MRI) included high-resolution sequences for intracranial arteries. Cognitive assessments and follow-up information will be prospectively collected. Biological specimens including blood and urine at baseline were collected and tested.

Participants: The targeted sample size of PSCI group was 500, AD group with 600 and NC group with 2000. There were 1449 participants enrolled. Include 508 participants were in NC group, 387 in AD group and 554 in PSCI group.

Measurements: Demographics, clinical parameters, and medical examinations were collected and performed. Cognitive assessment was performed to assess all cognitive domains including memory, language, executive function, and orientation function.

Conclusions: The CANDOR study is a prospective cohort study. Data from this cohort provide us an opportunity to investigate the contribution of vascular factors to dementia pathogenesis.