Current Alzheimer research最新文献

Alzheimer's disease (AD) ranks first among the causes of dementia worldwide. AD can develop a psychotic manifest at a significant rate. AD prognosis worsens by added psychosis clinic. There is no treatment approved by the United States Food and Drug Administration (FDA) among antipsychotics for Alzheimer's disease Psychosis (ADP). However, pimavanserine, an atypical antipsychotic, has been approved by the FDA for Parkinson's psychosis. It is predicted that pimavanserin, a new antipsychotic, will fill an important gap in this area. In clinical trials, it appears to be effective in the treatment of delusions and hallucinations at psychosis in both Parkinson's and AD. In this systematic review, we evaluated the analysis of current literature data on pimavanserin used in ADP. We searched the existing literature on clinical studies on pimavanserin therapy used in ADP. Data were determined by systematically searching PubMed, MEDLINE, EMBASE, and Google Scholar until December 2022. A total of 35 citations were found and uploaded on the Mendeley program. Abstracts and full texts of literature data were examined. Pimavanserin was observed, and satisfactory results were obtained in treating ADP. Pimavanserin has a unique mechanism of action. Pimavanserin, an atypical antipsychotic drug, has a low affinity for 5-HT2C receptors and has selective 5-HT2A reverse agonist/antagonist action. Pimavanserin has no clinically significant affinity for dopaminergic, histaminergic, muscarinic or adrenergic receptors. This agent may also achieve significant positive results in resistant psychosis treatments.

Introduction: The purpose of this study is to identify the risk factors and risk classification associated with the conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia to facilitate early intervention and the design of clinical trials for AD.

Methods: The study comprised a prospective cohort study of 400 subjects with MCI who had annual follow-ups for 3 years.

Results: During an average follow-up period of 3.5 years, 109 subjects were diagnosed with all cause of dementia, of whom 104 subjects converted to Alzheimer's dementia and 5 subjects converted to other types of dementia. The cumulative conversion rate was 5.5% (95% CI: 3.4, 8.6), 16.3% (95% CI: 12.9, 21.1), and 31.0% (95% CI: 25.4, 36.5) in each of the first 3 follow-up years, respectively. The factors associated with a greater risk of conversion from MCI to AD included smoking status, ApoE4 carrier status, right hippocampal volume (rt. HV), left temporal lobe volume, and scores on the Revised Chinese version of the Alzheimer's Disease Assessment Scale-Cognitive Subscale 13 (ADAS-Cog-C). The risk classification of the ADAS-Cog-C or Preclinical Alzheimer Cognitive Composite (PACC) score combined with the rt. HV showed a conversion difference among the groups at every annual follow-up.

Conclusion: A simple risk classification using the rt. HV and neuropsychological test scores, including those from the ADAS-Cog-C and PACC, could be a practicable and efficient approach to indentify individuals at risk of all-cause dementia.

Background: Metformin, the first-line anti-diabetic drug treatment in patients with type 2 diabetes mellitus (T2DM), is suggested to be anti-inflammatory, antioxidative, and improve cognitive function, making it a promising contribution to treating Alzheimer´s disease (AD). However, the effect of metformin on behavioral and psychological symptoms of dementia (BPSD) in patients with AD has not been explored.

Objective: To investigate the associations between metformin and BPSD in patients with AD and T2DM and explore possible interaction with other antidiabetic drugs.

Methods: This cross-sectional study was based on data from the Swedish BPSD register. A total of 3745 patients with AD and antidiabetic drug treatment were included. Associations and interactions between antidiabetic drugs and BPSD were investigated by binary logistic regression.

Results: The use of metformin was associated with lower odds for symptoms of depression (OR 0.77, CI (95%) 0.61-0.96, p = 0.022) and anxiety (OR 0.74, CI (95%) 0.58-0.94, p = 0.015) after adjustment for age, gender, specific diagnosis, and drugs. We could not demonstrate this association with another antidiabetic drug. Interaction effects were limited to an increasing association in eating and appetite disorders using metformin and other antidiabetic drugs (i.e., drugs other than insulin, sulfonylurea, or dipeptidyl peptidase-4 inhibitors).

Conclusion: The result of this study suggests that metformin could be beneficial for patients diagnosed with AD, other than for blood glucose control. Although, more knowledge is needed before assigning metformin a role in treating BPSD.

Aim / Objective: This study aimed to investigate the levels of organochlorine pesticides (OCPs) in the serum of Alzheimer's disease (AD) patients.

Methods: 63 AD patients and 50 healthy individuals participated, and the levels of some OCPs derivatives (including; α-HCH, β-HCH, γ-HCH, 2,4-DDT, 4,4-DDT, 2,4-DDE, and 4,4-DDE), total antioxidant capacity (TAC), protein carbonyl (PC), malondialdehyde (MDA), Nitric oxide (NO) along with the activity of superoxide dismutase (SOD), glutathione peroxidase (GPx), paraoxonase 1(PON1), and acetylcholinesterase (AChE) were measured.

Results: The mean OCP level of OCPs in AD patients was significantly higher than in the control group. However, the patients' mean levels of TAC, PC, MDA and activity of SOD, GPx, PON1 and AChE were significantly lower than controls. A significant positive correlation was also observed between 2,4-DDE and MDA and between γ-HCH and PC in AD patients. These findings showed that pesticide exposure is associated with an increased risk of AD. Furthermore, the mean levels of oxidative stress markers, which may result from pesticide exposure, were significantly lower in AD patients compared to healthy individuals.

Conclusion: Therefore, it may conclude that pesticides, at least in part, contribute to AD development through several mechanisms, including the induction of oxidative stress.

Introduction: Alzheimer's disease (AD) is the most common form of dementia. There have been various proposed pharmacologic and non-pharmacologic treatments proposed for preventing cognitive decline in AD patients. Transcranial Direct Current Stimulation (tDCS) is a neuromodulation technique used to enhance cognitive functions and motor skills of the brain. Our study aimed to assess the effects of tDCS in AD patients, including effects on general cognitive status, memory, attention, executive functions, language, IQ, and neuropsychological effects, along with the factors influencing the outcomes.

Methods: Systematic searches were conducted for relevant evidence using PubMed, ScienceDirect, and Cochrane Library databases for (Transcranial Direct Current Stimulation) and (Alzheimer's). Duplicates were removed, and the remaining articles were screened for double-blind, placebo-controlled, randomized clinical trials (Phase III), case studies, and case series on patients diagnosed with AD using tDCS. The articles were assessed for full text, and studies were selected and analyzed to include in the review.

Results: Overall, 20 studies were reviewed. Cognitive status, executive function and working memory, recognition memory, and language function may improve following AtDCS depending on the stimulation polarity and area stimulated. No significant effects of tDCS were seen on attention, associative memory, recall memory, visuospatial ability, and neuropsychiatric symptoms.

Discussion: Therapy outcomes and the factors that could affect them were analyzed, which included the number of sessions taken, current density, stimulation polarity (cathodal/anodal/dual), area stimulated, training(s) given, and study timeline.

Conclusion: tDCS is a well-tolerated therapy that can be used for improving several cognitive domains in patients having Alzheimer's disease. Its treatment outcomes are affected by polarity (cathodal/ anodal), site of stimulation, number of sessions taken, and any training(s) given during the study.

Background: Alzheimer's disease (AD) is a well-known neurodegenerative disease that gradually induces neural network dysfunction and progressive memory deficits. Neural network activity is represented by rhythmic oscillations that influence local field potentials (LFPs). However, changes in hippocampal neural rhythmic oscillations in the early stage of AD remain largely unexplored.

Objective: This study investigated neural rhythmic oscillations in 3-month-old APP/PS1 and 5x- FAD mice to assess early neural connectivity in AD.

Methods: LFPs were recorded from the hippocampal CA1 region with implanted microelectrode arrays while the mice were in the awake resting stage. Welch fast Fourier transforms, continuous wavelet transforms, and phase-amplitude coupling analyses were used to compute the power density of different frequency bands and phase-amplitude modulation indices in the LFPs.

Results: Our results showed impaired theta, low gamma, and high gamma frequency band power in APP/PS1 and 5xFAD mice during the awake resting stage. AD mice also showed decreased delta, alpha, and beta frequency band power. Impaired theta-low gamma and theta-high gamma phaseamplitude coupling were observed in 5xFAD mice.

Conclusion: This study revealed neural network activity differences in oscillation power and cross-frequency coupling in the early stage of AD, providing a new perspective for developing biomarkers for early AD diagnosis.

Growing evidence supports that Alzheimer's disease (AD) could be regarded as a metabolic disease, accompanying central and peripheral metabolic disturbance. Nowadays, exploring novel and potentially alternative hallmarks for AD is needed. Peripheral metabolites based on blood and gut may provide new biochemical insights about disease mechanisms. These metabolites can influence brain energy homeostasis, maintain gut mucosal integrity, and regulate the host immune system, which may further play a key role in modulating the cognitive function and behavior of AD. Recently, metabolomics has been used to identify key AD-related metabolic changes and define metabolic changes during AD disease trajectory. This review aims to summarize the key blood- and microbial-derived metabolites that are altered in AD and identify the potential metabolic biomarkers of AD, which will provide future targets for precision therapeutic modulation.

Multiple studies have proposed important roles of T cells in the pathogenesis of Alzheimer's disease. Given the successful application of immune-based therapy for cancer and a variety of diseases, T cell-modifying therapy becomes an attractive way to develop new therapies for Alzheimer's disease and perhaps neurodegenerative diseases in general. However, most of these studies address peripheral T cell responses, while direct pathological evidence documenting T cell infiltration relative to Alzheimer's disease pathological markers (i.e., amyloid plaque and neurofibrillary tangle) is sparse and at best, very preliminary in both human subjects and relevant animal models. Here, we concisely summarize the available pathological data that directly corresponds to T cell infiltration, critically analyze the current knowledge gaps, and thoughtfully propose several key recommendations for future research.

Background: For decades, evidence from observational studies and randomized controlled trials has converged to suggest associations of dietary components, foods, and dietary patterns with dementia. With population aging and a projected exponential expansion of people living with dementia, formulating nutritional strategies for dementia prevention has become a research hotspot.

Objective: This review aimed to summarize available data on the roles of specific dietary components, food groups, and dietary patterns in dementia prevention among the elderly.

Methods: Database search was carried out using PubMed, the Cochrane Library, EMBASE, and Medline.

Results: Polyphenols, folate, vitamin D, omega-3 fatty acids, and β-carotene might decrease the risk of dementia. Consumption of green leafy vegetables, green tea, fish, and fruits is recommended. However, saturated fat, a diet rich in both dietary copper and saturated fat, aluminum from drinking water, and heavy drinking might increase dementia risk. Healthy dietary patterns, especially the Mediterranean diet, were proven to bring more cognitive benefits than single dietary components.

Conclusion: We discussed and summarized the evidence on the roles of dietary components and patterns in dementia prevention among the elderly and found that some factors were closely associated with dementia risk in elderly. This may pave the way for the identification of dietary components and patterns as new therapeutic targets for dementia prevention in the elderly population.

Introduction: A major gap in amyloid-centric theories of Alzheimer's disease (AD) is that even though amyloid fibrils per se are not toxic in vitro, the diagnosis of AD clearly correlates with the density of beta-amyloid (Aβ) deposits. Based on our proposed amyloid degradation toxicity hypothesis, we developed a mathematical model explaining this discrepancy. It suggests that cytotoxicity depends on the cellular uptake of soluble Aβ rather than on the presence of amyloid aggregates. The dynamics of soluble beta-amyloid in the cerebrospinal fluid (CSF) and the density of Aβ deposits is described using a system of differential equations. In the model, cytotoxic damage is proportional to the cellular uptake of Aβ, while the probability of an AD diagnosis is defined by the Aβ cytotoxicity accumulated over the duration of the disease. After uptake, Aβ is concentrated intralysosomally, promoting the formation of fibrillation seeds inside cells. These seeds cannot be digested and are either accumulated intracellularly or exocytosed. Aβ starts aggregating on the extracellular seeds and, therefore, decreases in concentration in the interstitial fluid. The dependence of both Aβ toxicity and aggregation on the same process-cellular uptake of Aβ-explains the correlation between AD diagnosis and the density of amyloid aggregates in the brain.

Methods: We tested the model using clinical data obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI), which included records of beta-amyloid concentration in the cerebrospinal fluid (CSF-Aβ42) and the density of beta-amyloid deposits measured using positron emission tomography (PET). The model predicts the probability of AD diagnosis as a function of CSF-Aβ42 and PET and fits the experimental data at the 95% confidence level.

Results: Our study shows that existing clinical data allows for the inference of kinetic parameters describing beta-amyloid turnover and disease progression. Each combination of CSF-Aβ42 and PET values can be used to calculate the individual's cellular uptake rate, the effective disease duration, and the accumulated toxicity. We show that natural limitations on these parameters explain the characteristic distribution of the clinical dataset for these two biomarkers in the population.

Conclusion: The resulting mathematical model interprets the positive correlation between the density of Aβ deposits and the probability of an AD diagnosis without assuming any cytotoxicity of the aggregated beta-amyloid. To the best of our knowledge, this model is the first to mechanistically explain the negative correlation between the concentration of Aβ42 in the CSF and the probability of an AD diagnosis. Finally, based on the amyloid degradation toxicity hypothesis and the insights provided by mathematical modeling, we propose new pathophysiology-relevant biomarkers to diagnose and predict AD.