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GeroScience Jun 2024Aging is a multifactorial biological process that may be associated with cognitive decline. Photobiomodulation (PBM) is a non-pharmacological therapy that shows... (Review)
Review
Aging is a multifactorial biological process that may be associated with cognitive decline. Photobiomodulation (PBM) is a non-pharmacological therapy that shows promising results in the treatment or prevention of age-related cognitive impairments. The aim of this review is to compile the preclinical and clinical evidence of the effect of PBM during aging in healthy and pathological conditions, including behavioral analysis and neuropsychological assessment, as well as brain-related modifications. 37 studies were identified by searching in PubMed, Scopus, and PsycInfo databases. Most studies use wavelengths of 800, 810, or 1064 nm but intensity and days of application were highly variable. In animal studies, it has been shown improvements in spatial memory, episodic-like memory, social memory, while different results have been found in recognition memory. Locomotor activity improved in Parkinson disease models. In healthy aged humans, it has been outlined improvements in working memory, cognitive inhibition, and lexical/semantic access, while general cognition was mainly enhanced on Alzheimer disease or mild cognitive impairment. Anxiety assessment is scarce and shows mixed results. As for brain activity, results outline promising effects of PBM in reversing metabolic alterations and enhancing mitochondrial function, as evidenced by restored CCO activity and ATP levels. Additionally, PBM demonstrated neuroprotective, anti-inflammatory, immunomodulatory and hemodynamic effects. The findings suggest that PBM holds promise as a non-invasive intervention for enhancing cognitive function, and in the modulation of brain functional reorganization. It is necessary to develop standardized protocols for the correct, beneficial, and homogeneous use of PBM.
PubMed: 38861125
DOI: 10.1007/s11357-024-01231-y -
Journal of Alzheimer's Disease : JAD 2024To date, the magnitude of association and the quality of evidence for cognitive decline (mild cognitive impairment, Alzheimer's disease, and dementia) in couples and... (Meta-Analysis)
Meta-Analysis
BACKGROUND
To date, the magnitude of association and the quality of evidence for cognitive decline (mild cognitive impairment, Alzheimer's disease, and dementia) in couples and risk factors for outcomes have not been reviewed and analyzed systematically.
OBJECTIVE
The aim of this study was to investigate the concordance of cognitive impairment in unrelated spouses and to qualitatively describe potential risk factors.
METHODS
Eight databases were searched from inception to October 20, 2023. Eligible studies were independently screened and assessed for quality. Statistical analysis was conducted using Stata 15.1 software. The study was preregistered with PROSPERO (CRD42023488024).
RESULTS
Eleven studies involving couples were included, with moderate to high evidence quality. Compared to controls, spouses of individuals with cognitive impairment had lower cognitive scores (Cohen's d: 0.18-0.62) and higher risk of cognitive decline (OR = 1.42, 95% CI: 1.15-1.76). The consistency of cognitive impairment between spouses was attributed to three theories: 1) the impact of caregiving stress experienced by the spouse; 2) assortative mating, which suggests that individuals select partners with similar characteristics; and 3) the influence of shared living environments and lifestyles.
CONCLUSIONS
The cognitive status of one spouse can affect the cognitive function of the other spouse. It is important to consider shared lifestyle, environmental, and psychobehavioral factors, as they may contribute to the risk of cognitive decline by couples. Identifying these factors can inform the development of targeted recommendations for interventions and preventive measures.
Topics: Humans; Cognitive Dysfunction; Spouses; Risk Factors; Male; Alzheimer Disease
PubMed: 38848191
DOI: 10.3233/JAD-240325 -
Journal of Alzheimer's Disease : JAD 2024Dementia is a general term for several progressive neurodegenerative disorders including Alzheimer's disease. Timely and accurate detection is crucial for early...
BACKGROUND
Dementia is a general term for several progressive neurodegenerative disorders including Alzheimer's disease. Timely and accurate detection is crucial for early intervention. Advancements in artificial intelligence present significant potential for using machine learning to aid in early detection.
OBJECTIVE
Summarize the state-of-the-art machine learning-based approaches for dementia prediction, focusing on non-invasive methods, as the burden on the patients is lower. Specifically, the analysis of gait and speech performance can offer insights into cognitive health through clinically cost-effective screening methods.
METHODS
A systematic literature review was conducted following the PRISMA protocol (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). The search was performed on three electronic databases (Scopus, Web of Science, and PubMed) to identify the relevant studies published between 2017 to 2022. A total of 40 papers were selected for review.
RESULTS
The most common machine learning methods employed were support vector machine followed by deep learning. Studies suggested the use of multimodal approaches as they can provide comprehensive and better prediction performance. Deep learning application in gait studies is still in the early stages as few studies have applied it. Moreover, including features of whole body movement contribute to better classification accuracy. Regarding speech studies, the combination of different parameters (acoustic, linguistic, cognitive testing) produced better results.
CONCLUSIONS
The review highlights the potential of machine learning, particularly non-invasive approaches, in the early prediction of dementia. The comparable prediction accuracies of manual and automatic speech analysis indicate an imminent fully automated approach for dementia detection.
Topics: Humans; Machine Learning; Dementia; Speech; Gait Analysis
PubMed: 38848181
DOI: 10.3233/JAD-231459 -
European Journal of Pharmacology Aug 2024Astaxanthin is a potent lipid-soluble carotenoid produced by several different freshwater and marine microorganisms, including microalgae, bacteria, fungi, and yeast.... (Review)
Review
Astaxanthin is a potent lipid-soluble carotenoid produced by several different freshwater and marine microorganisms, including microalgae, bacteria, fungi, and yeast. The proven therapeutic effects of astaxanthin against different diseases have made this carotenoid popular in the nutraceutical market and among consumers. Recently, astaxanthin is also receiving attention for its effects in the co-adjuvant treatment or prevention of neurological pathologies. In this systematic review, studies evaluating the efficacy of astaxanthin against different neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, multiple sclerosis, cerebrovascular diseases, and spinal cord injury are analyzed. Based on the current literature, astaxanthin shows potential biological activity in both in vitro and in vivo models. In addition, its preventive and therapeutic activities against the above-mentioned diseases have been emphasized in studies with different experimental designs. In contrast, none of the 59 studies reviewed reported any safety concerns or adverse health effects as a result of astaxanthin supplementation. The preventive or therapeutic role of astaxanthin may vary depending on the dosage and route of administration. Although there is a consensus in the literature regarding its effectiveness against the specified diseases, it is important to determine the safe intake levels of synthetic and natural forms and to determine the most effective forms for oral intake.
Topics: Xanthophylls; Neuroprotective Agents; Humans; Animals; Neurodegenerative Diseases; Antioxidants; Aquatic Organisms
PubMed: 38843946
DOI: 10.1016/j.ejphar.2024.176706 -
Frontiers in Aging Neuroscience 2024Soluble triggering receptor expressed on myeloid cells 2 (sTREM2) is a potential neuroinflammatory biomarker linked to the pathogenesis of Alzheimer's disease (AD) and...
OBJECTIVE
Soluble triggering receptor expressed on myeloid cells 2 (sTREM2) is a potential neuroinflammatory biomarker linked to the pathogenesis of Alzheimer's disease (AD) and mild cognitive impairment (MCI). Previous studies have produced inconsistent results regarding sTREM2 levels in various clinical stages of AD. This study aims to establish the correlation between sTREM2 levels and AD progression through a meta-analysis of sTREM2 levels in cerebrospinal fluid (CSF) and blood.
METHODS
Comprehensive searches were conducted in PubMed, Embase, Web of Science, and the Cochrane Library to identify observational studies reporting CSF and blood sTREM2 levels in AD patients, MCI patients, and healthy controls. A random effects meta-analysis was used to calculate the standardized mean difference (SMD) and 95% confidence intervals (CIs).
RESULTS
Thirty-six observational studies involving 3,016 AD patients, 3,533 MCI patients, and 4,510 healthy controls were included. CSF sTREM2 levels were significantly higher in both the AD [SMD = 0.28, 95% CI (0.15, 0.41)] and MCI groups [SMD = 0.30, 95% CI (0.13, 0.47)] compared to the healthy control group. However, no significant differences in expression were detected between the AD and MCI groups [SMD = 0.09, 95% CI (-0.09, 0.26)]. Furthermore, increased plasma sTREM2 levels were associated with a higher risk of AD [SMD = 0.42, 95% CI (0.01, 0.83)].
CONCLUSION
CSF sTREM2 levels are positively associated with an increased risk of AD and MCI. Plasma sTREM2 levels were notably higher in the AD group than in the control group and may serve as a promising biomarker for diagnosing AD. However, sTREM2 levels are not effective for distinguishing between different disease stages of AD. Further investigations are needed to explore the longitudinal changes in sTREM2 levels, particularly plasma sTREM2 levels, during AD progression.
SYSTEMATIC REVIEW REGISTRATION
https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024514593.
PubMed: 38841103
DOI: 10.3389/fnagi.2024.1407980 -
Journal of Stroke May 2024Possible differences in the prevalence of cerebral amyloid angiopathy (CAA) in East-Asian compared to Western populations have received little attention, and results so... (Review)
Review
BACKGROUND AND PURPOSE
Possible differences in the prevalence of cerebral amyloid angiopathy (CAA) in East-Asian compared to Western populations have received little attention, and results so far have been ambiguous. Our aim is to compare the prevalence of CAA neuropathology and magnetic resonance imaging markers of CAA in East-Asian and Western cohorts reflecting the general population, cognitively normal elderly, patients with Alzheimer's disease (AD), and patients with (lobar) intracerebral hemorrhage (ICH).
METHODS
We performed a systematic literature search in PubMed and Embase for original research papers on the prevalence of CAA and imaging markers of CAA published up until February 17th 2022. Records were screened by two independent reviewers. Pooled estimates were determined using random-effects models. We compared studies from Japan, China, Taiwan, South Korea (East-Asian cohorts) to studies from Europe or North America (Western cohorts) by meta-regression models.
RESULTS
We identified 12,257 unique records, and we included 143 studies on Western study populations and 53 studies on East-Asian study populations. Prevalence of CAA neuropathology did not differ between East-Asian and Western cohorts in any of the investigated patient domains. The prevalence of strictly lobar microbleeds was lower in East-Asian cohorts of population-based individuals (5.6% vs. 11.4%, P=0.020), cognitively normal elderly (2.6% vs. 11.4%, P=0.001), and patients with ICH (10.2% vs. 24.6%, P<0.0001). However, age was in general lower in the East-Asian cohorts.
CONCLUSION
The prevalence of CAA neuropathology in the general population, cognitively normal elderly, patients with AD, and patients with (lobar) ICH is similar in East-Asian and Western countries. In East-Asian cohorts reflecting the general population, cognitively normal elderly, and patients with ICH, strictly lobar microbleeds were less prevalent, likely due to their younger age. Consideration of potential presence of CAA is warranted in decisions regarding antithrombotic treatment and potential new anti-amyloid-β immunotherapy as treatment for AD in East-Asian and Western countries alike.
PubMed: 38836267
DOI: 10.5853/jos.2023.04287 -
Neurology Jul 2024Clinical trials in neurodegenerative diseases often encounter selective enrollment and under-representation of certain patient populations. This delays drug development... (Meta-Analysis)
Meta-Analysis
BACKGROUND AND OBJECTIVES
Clinical trials in neurodegenerative diseases often encounter selective enrollment and under-representation of certain patient populations. This delays drug development and substantially limits the generalizability of clinical trial results. To inform recruitment and retention strategies, and to better understand the generalizability of clinical trial populations, we investigated which factors drive participation.
METHODS
We reviewed the literature systematically to identify barriers to and facilitators of trial participation in 4 major neurodegenerative disease areas: Alzheimer disease, Parkinson disease, amyotrophic lateral sclerosis, and Huntington disease. Inclusion criteria included original research articles published in a peer-reviewed journal and evaluating barriers to and/or facilitators of participation in a clinical trial with a drug therapy (either symptomatic or disease-modifying). The Critical Appraisal Skills Program checklist for qualitative studies was used to assess and ensure the quality of the studies. Qualitative thematic analyses were employed to identify key enablers of trial participation. Subsequently, we pooled quantitative data of each enabler using meta-analytical models.
RESULTS
Overall, we identified 36 studies, enrolling a cumulative sample size of 5,269 patients, caregivers, and health care professionals. In total, the thematic analysis resulted in 31 unique enablers of trial participation; the key factors were patient-related (own health benefit and altruism), study-related (treatment and study burden), and health care professional-related (information availability and patient-physician relationship). When meta-analyzed across studies, responders reported that the reason to participate was mainly driven by (1) the relationship with clinical staff (70% of the respondents; 95% CI 53%-83%), (2) the availability of study information (67%, 95% CI 38%-87%), and (3) the use or absence of a placebo or sham-control arm (53% 95% CI 32%-72%). There was, however, significant heterogeneity between studies (all < 0.001).
DISCUSSION
We have provided a comprehensive list of reasons why patients participate in clinical trials for neurodegenerative diseases. These results may help to increase participation rates, better inform patients, and facilitate patient-centric approaches, thereby potentially reducing selection mechanisms and improving generalizability of trial results.
Topics: Humans; Neurodegenerative Diseases; Clinical Trials as Topic; Patient Participation; Patient Selection
PubMed: 38830181
DOI: 10.1212/WNL.0000000000209503 -
Cognitive Neurodynamics Jun 2024In recent years, Alzheimer's disease (AD) has been a serious threat to human health. Researchers and clinicians alike encounter a significant obstacle when trying to... (Review)
Review
In recent years, Alzheimer's disease (AD) has been a serious threat to human health. Researchers and clinicians alike encounter a significant obstacle when trying to accurately identify and classify AD stages. Several studies have shown that multimodal neuroimaging input can assist in providing valuable insights into the structural and functional changes in the brain related to AD. Machine learning (ML) algorithms can accurately categorize AD phases by identifying patterns and linkages in multimodal neuroimaging data using powerful computational methods. This study aims to assess the contribution of ML methods to the accurate classification of the stages of AD using multimodal neuroimaging data. A systematic search is carried out in IEEE Xplore, Science Direct/Elsevier, ACM DigitalLibrary, and PubMed databases with forward snowballing performed on Google Scholar. The quantitative analysis used 47 studies. The explainable analysis was performed on the classification algorithm and fusion methods used in the selected studies. The pooled sensitivity and specificity, including diagnostic efficiency, were evaluated by conducting a meta-analysis based on a bivariate model with the hierarchical summary receiver operating characteristics (ROC) curve of multimodal neuroimaging data and ML methods in the classification of AD stages. Wilcoxon signed-rank test is further used to statistically compare the accuracy scores of the existing models. With a 95% confidence interval of 78.87-87.71%, the combined sensitivity for separating participants with mild cognitive impairment (MCI) from healthy control (NC) participants was 83.77%; for separating participants with AD from NC, it was 94.60% (90.76%, 96.89%); for separating participants with progressive MCI (pMCI) from stable MCI (sMCI), it was 80.41% (74.73%, 85.06%). With a 95% confidence interval (78.87%, 87.71%), the Pooled sensitivity for distinguishing mild cognitive impairment (MCI) from healthy control (NC) participants was 83.77%, with a 95% confidence interval (90.76%, 96.89%), the Pooled sensitivity for distinguishing AD from NC was 94.60%, likewise (MCI) from healthy control (NC) participants was 83.77% progressive MCI (pMCI) from stable MCI (sMCI) was 80.41% (74.73%, 85.06%), and early MCI (EMCI) from NC was 86.63% (82.43%, 89.95%). Pooled specificity for differentiating MCI from NC was 79.16% (70.97%, 87.71%), AD from NC was 93.49% (91.60%, 94.90%), pMCI from sMCI was 81.44% (76.32%, 85.66%), and EMCI from NC was 85.68% (81.62%, 88.96%). The Wilcoxon signed rank test showed a low P-value across all the classification tasks. Multimodal neuroimaging data with ML is a promising future in classifying the stages of AD but more research is required to increase the validity of its application in clinical practice.
PubMed: 38826669
DOI: 10.1007/s11571-023-09993-5 -
BMC Geriatrics Jun 2024Research the dose-response relationship between overall and certain types of exercise and cognitive function in older adults with Alzheimer's disease and dementia. (Meta-Analysis)
Meta-Analysis
Effective dosage and mode of exercise for enhancing cognitive function in Alzheimer's disease and dementia: a systematic review and Bayesian Model-Based Network Meta-analysis of RCTs.
OBJECTIVE
Research the dose-response relationship between overall and certain types of exercise and cognitive function in older adults with Alzheimer's disease and dementia.
DESIGN
Systemic and Bayesian Model-Based Network Meta-Analysis.
METHODS
In our study, we analyzed data from randomized controlled trials investigating the effects of different exercises on cognitive outcomes in older adults with AD. We searched the Web of Science, PubMed, Cochrane Central Register of Controlled Trials, and Embase up to November 2023. Using the Cochrane Risk of Bias tool (Rob2) for quality assessment and R software with the MBNMA package for data analysis, we determined standard mean differences (SMDs) and 95% confidence intervals (95%CrI) to evaluate exercise's impact on cognitive function in AD.
RESULTS
Twenty-seven studies with 2,242 AD patients revealed a nonlinear relationship between exercise and cognitive improvement in AD patients. We observed significant cognitive enhancements at an effective exercise dose of up to 1000 METs-min/week (SMDs: 0.535, SD: 0.269, 95% CrI: 0.023 to 1.092). The optimal dose was found to be 650 METs-min/week (SMDs: 0.691, SD: 0.169, 95% CrI: 0.373 to 1.039), with AE (Aerobic exercise) being particularly effective. For AE, the optimal cognitive enhancement dose was determined to be 660 METs-min/week (SMDs: 0.909, SD: 0.219, 95% CrI: 0.495 to 1.362).
CONCLUSION
Nonlinear dose-response relationship between exercise and cognitive improvement in Alzheimer's disease, with the optimal AE dose identified at 660 METs-min/week for enhancing cognitive function in AD.
Topics: Humans; Alzheimer Disease; Bayes Theorem; Randomized Controlled Trials as Topic; Cognition; Network Meta-Analysis; Exercise Therapy; Dementia; Aged
PubMed: 38824515
DOI: 10.1186/s12877-024-05060-8 -
Alzheimer Disease and Associated...The overall goal of this review was to identify what is known about triadic (clinician-patient-caregiver) communication in mild cognitive impairment (MCI) and dementia... (Review)
Review
PURPOSE
The overall goal of this review was to identify what is known about triadic (clinician-patient-caregiver) communication in mild cognitive impairment (MCI) and dementia care settings throughout the care continuum.
METHODS
Using a structured search, we conducted a systematic scoping review of relevant published journal articles across 5 databases. Study titles/abstracts and selected full-text articles were screened by 2 investigators in Covidence systematic review software. Articles were excluded if they were not about clinical communication, focused only on caregiver-patient communication or communication in residential care, were interventional, lacked empirical data, or were not in English. Extracted data were documented using Google Forms.
RESULTS
The study team screened 3426 article titles and abstracts and 112 full-text articles. Forty-four articles were included in the final review. Results were categorized by 3 communication scenarios: diagnostic communication (n=22), general communication (n=16), and advanced care planning communication (n=6).
CONCLUSIONS AND RELEVANCE
Across the included articles, the conceptualization and assessment of communication lacked homogeneity. Future directions include addressing these research gaps, establishing recommendations for clinicians to effectively communicate with individuals with dementia and caregivers, and creating and testing communication skills trainings for caregivers/family members, clinicians, and/or individuals with dementia to facilitate effective communication.
Topics: Humans; Dementia; Communication; Caregivers; Cognitive Dysfunction; Physician-Patient Relations
PubMed: 38812448
DOI: 10.1097/WAD.0000000000000626