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Neurobiology of Aging Feb 2020Repetitive transcranial magnetic stimulation (rTMS), a noninvasive brain stimulation technique, has emerged as a promising treatment for mild cognitive impairment (MCI)... (Meta-Analysis)
Meta-Analysis
Repetitive transcranial magnetic stimulation (rTMS), a noninvasive brain stimulation technique, has emerged as a promising treatment for mild cognitive impairment (MCI) and Alzheimer's disease (AD). Currently, however, the effectiveness of this therapy is unclear because of the low statistical power and heterogeneity of previous trials. The purpose of the meta-analysis was to systematically characterize the effectiveness of various combinations of rTMS parameters on different cognitive domains in patients with MCI and AD. Thirteen studies comprising 293 patients with MCI or AD were included in this analysis. Random-effects analysis revealed an overall medium-to-large effect size (0.77) favoring active rTMS over sham rTMS in the improvement of cognitive functions. Subgroup analyses revealed that (1) high-frequency rTMS over the left dorsolateral prefrontal cortex and low-frequency rTMS at the right dorsolateral prefrontal cortex significantly improved memory functions; (2) high-frequency rTMS targeting the right inferior frontal gyrus significantly enhanced executive performance; and (3) the effects of 5-30 consecutive rTMS sessions could last for 4-12 weeks. Potential mechanisms of rTMS effects on cognitive functions are discussed.
Topics: Alzheimer Disease; Cognition; Cognitive Dysfunction; Humans; Memory; Prefrontal Cortex; Transcranial Magnetic Stimulation
PubMed: 31783330
DOI: 10.1016/j.neurobiolaging.2019.08.020 -
Molecular Neurodegeneration Mar 2022Alzheimer's disease (AD) is the most common form of dementia, characterized by progressive cognitive impairment and neurodegeneration. Extensive clinical and genomic... (Review)
Review
Alzheimer's disease (AD) is the most common form of dementia, characterized by progressive cognitive impairment and neurodegeneration. Extensive clinical and genomic studies have revealed biomarkers, risk factors, pathways, and targets of AD in the past decade. However, the exact molecular basis of AD development and progression remains elusive. The emerging single-cell sequencing technology can potentially provide cell-level insights into the disease. Here we systematically review the state-of-the-art bioinformatics approaches to analyze single-cell sequencing data and their applications to AD in 14 major directions, including 1) quality control and normalization, 2) dimension reduction and feature extraction, 3) cell clustering analysis, 4) cell type inference and annotation, 5) differential expression, 6) trajectory inference, 7) copy number variation analysis, 8) integration of single-cell multi-omics, 9) epigenomic analysis, 10) gene network inference, 11) prioritization of cell subpopulations, 12) integrative analysis of human and mouse sc-RNA-seq data, 13) spatial transcriptomics, and 14) comparison of single cell AD mouse model studies and single cell human AD studies. We also address challenges in using human postmortem and mouse tissues and outline future developments in single cell sequencing data analysis. Importantly, we have implemented our recommended workflow for each major analytic direction and applied them to a large single nucleus RNA-sequencing (snRNA-seq) dataset in AD. Key analytic results are reported while the scripts and the data are shared with the research community through GitHub. In summary, this comprehensive review provides insights into various approaches to analyze single cell sequencing data and offers specific guidelines for study design and a variety of analytic directions. The review and the accompanied software tools will serve as a valuable resource for studying cellular and molecular mechanisms of AD, other diseases, or biological systems at the single cell level.
Topics: Alzheimer Disease; Animals; Computational Biology; DNA Copy Number Variations; Data Analysis; Mice; Single-Cell Analysis
PubMed: 35236372
DOI: 10.1186/s13024-022-00517-z -
GeroScience Jun 2022Vascular contribution to cognitive impairment and dementia (VCID) is a clinical label encompassing a wide range of cognitive disorders progressing from mild to major... (Meta-Analysis)
Meta-Analysis Review
Vascular contribution to cognitive impairment and dementia (VCID) is a clinical label encompassing a wide range of cognitive disorders progressing from mild to major vascular cognitive impairment (VCI), which is also defined as vascular dementia (VaD). VaD diagnosis is mainly based on clinical and imaging findings. Earlier biomarkers are needed to identify subjects at risk to develop mild VCI and VaD. In the present meta-analysis, we comprehensively evaluated the role of inflammatory biomarkers in differential diagnosis between VaD and Alzheimer's disease (AD), and assessed their prognostic value on predicting VaD incidence. We collected literature until January 31, 2021, assessing three inflammatory markers [interleukin(IL)-6, C-reactive protein (CRP), tumor necrosis factor (TNF)-α] from blood or cerebrospinal fluid (CSF) samples. Thirteen cross-sectional and seven prospective studies were included. Blood IL-6 levels were cross-sectionally significantly higher in people with VaD compared to AD patients (SMD: 0.40, 95% CI: 0.18 to 0.62) with low heterogeneity (I: 41%, p = 0.13). Higher IL-6 levels were also associated to higher risk of incident VaD (relative risk: 1.28, 95% CI: 1.03 to 1.59, I: 0%). IL-6 in CSF was significantly higher in people with VaD compared to healthy subjects (SMD: 0.77, 95% CI: 0.17 to 1.37, I: 70%), and not compared to AD patients, but due to limited evidence and high inconsistency across studies, we could not draw definite conclusion. Higher blood IL-6 levels might represent a useful biomarker able to differentiate people with VaD from those with AD and might be correlated with higher risk of future VaD.
Topics: Alzheimer Disease; Biomarkers; Cognitive Dysfunction; Cross-Sectional Studies; Dementia, Vascular; Humans; Interleukin-6; Prospective Studies
PubMed: 35486344
DOI: 10.1007/s11357-022-00556-w -
International Journal of Molecular... Mar 2021Alzheimer's disease (AD) is a complex and severe neurodegenerative disease that still lacks effective methods of diagnosis. The current diagnostic methods of AD rely on...
BACKGROUND
Alzheimer's disease (AD) is a complex and severe neurodegenerative disease that still lacks effective methods of diagnosis. The current diagnostic methods of AD rely on cognitive tests, imaging techniques and cerebrospinal fluid (CSF) levels of amyloid-β1-42 (Aβ42), total tau protein and hyperphosphorylated tau (p-tau). However, the available methods are expensive and relatively invasive. Artificial intelligence techniques like machine learning tools have being increasingly used in precision diagnosis.
METHODS
We conducted a meta-analysis to investigate the machine learning and novel biomarkers for the diagnosis of AD.
METHODS
We searched PubMed, the Cochrane Central Register of Controlled Trials, and the Cochrane Database of Systematic Reviews for reviews and trials that investigated the machine learning and novel biomarkers in diagnosis of AD.
RESULTS
In additional to Aβ and tau-related biomarkers, biomarkers according to other mechanisms of AD pathology have been investigated. Neuronal injury biomarker includes neurofiliament light (NFL). Biomarkers about synaptic dysfunction and/or loss includes neurogranin, BACE1, synaptotagmin, SNAP-25, GAP-43, synaptophysin. Biomarkers about neuroinflammation includes sTREM2, and YKL-40. Besides, d-glutamate is one of coagonists at the NMDARs. Several machine learning algorithms including support vector machine, logistic regression, random forest, and naïve Bayes) to build an optimal predictive model to distinguish patients with AD from healthy controls.
CONCLUSIONS
Our results revealed machine learning with novel biomarkers and multiple variables may increase the sensitivity and specificity in diagnosis of AD. Rapid and cost-effective HPLC for biomarkers and machine learning algorithms may assist physicians in diagnosing AD in outpatient clinics.
Topics: Aged; Alzheimer Disease; Biomarkers; Chromatography, High Pressure Liquid; Diagnosis, Computer-Assisted; Female; Humans; Machine Learning; Middle Aged
PubMed: 33803217
DOI: 10.3390/ijms22052761 -
Ageing Research Reviews Dec 2021Alzheimer's disease (AD) is the most prevalent neurodegenerative disease in ageing, affecting around 46 million people worldwide but few treatments are currently... (Review)
Review
Alzheimer's disease (AD) is the most prevalent neurodegenerative disease in ageing, affecting around 46 million people worldwide but few treatments are currently available. The etiology of AD is still puzzling, and new drugs development and clinical trials have high failure rates. Urgent outline of an integral (multi-target) and effective treatment of AD is needed. Accumulation of amyloid-β (Aβ) peptides is considered one of the fundamental neuropathological pillars of the disease, and its dyshomeostasis has shown a crucial role in AD onset. Therefore, many amyloid-targeted therapies have been investigated. Here, we will systematically review recent (from 2014) investigational, follow-up and review studies focused on anti-amyloid strategies to summarize and analyze their current clinical potential. Combination of anti-Aβ therapies with new developing early detection biomarkers and other therapeutic agents acting on early functional AD changes will be highlighted in this review. Near-term approval seems likely for several drugs acting against Aβ, with recent FDA approval of a monoclonal anti-Aβ oligomers antibody -aducanumab- raising hopes and controversies. We conclude that, development of oligomer-epitope specific Aβ treatment and implementation of multiple improved biomarkers and risk prediction methods allowing early detection, together with therapies acting on other factors such as hyperexcitability in early AD, could be the key to slowing this global pandemic.
Topics: Alzheimer Disease; Amyloid; Amyloid beta-Peptides; Biomarkers; Humans; Neurodegenerative Diseases
PubMed: 34687956
DOI: 10.1016/j.arr.2021.101496 -
Nutrients Jan 2023Cognitive impairment is a staggering personal and societal burden; accordingly, there is a strong interest in potential strategies for its prevention and treatment.... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Cognitive impairment is a staggering personal and societal burden; accordingly, there is a strong interest in potential strategies for its prevention and treatment. Nutritional supplements have been extensively investigated, and citicoline seems to be a promising agent; its role in clinical practice, however, has not been established. We systematically reviewed studies on the effect of citicoline on cognitive performance.
METHODS
We searched the PubMed and Cochrane Library databases for articles published between 2010 and 2022. Relevant information was extracted and presented following the PRISMA recommendations. Data were pooled using the inverse-variance method with random effects models.
RESULTS
We selected seven studies including patients with mild cognitive impairment, Alzheimer's disease or post-stroke dementia. All the studies showed a positive effect of citicoline on cognitive functions. Six studies could be included in the meta-analysis. Overall, citicoline improved cognitive status, with pooled standardized mean differences ranging from 0.56 (95% CI: 0.37-0.75) to 1.57 (95% CI: 0.77-2.37) in different sensitivity analyses. The overall quality of the studies was poor.
DISCUSSION
Available data indicate that citicoline has positive effects on cognitive function. The general quality of the studies, however, is poor with significant risk of bias in favor of the intervention. Other: PubMed and the Cochrane Library.
Topics: Humans; Cytidine Diphosphate Choline; Alzheimer Disease; Cognitive Dysfunction; Cognition Disorders; Cognition
PubMed: 36678257
DOI: 10.3390/nu15020386 -
International Journal of Molecular... Jan 2023Alzheimer's disease (AD) is a multifactorial, progressive, neurodegenerative disease typically characterized by memory loss, personality changes, and a decline in... (Review)
Review
Alzheimer's disease (AD) is a multifactorial, progressive, neurodegenerative disease typically characterized by memory loss, personality changes, and a decline in overall cognitive function. Usually manifesting in individuals over the age of 60, this is the most prevalent type of dementia and remains the fifth leading cause of death among Americans aged 65 and older. While the development of effective treatment and prevention for AD is a major healthcare goal, unfortunately, therapeutic approaches to date have yet to find a treatment plan that produces long-term cognitive improvement. Drugs that may be able to slow down the progression rate of AD are being introduced to the market; however, there has been no previous solution for preventing or reversing the disease-associated cognitive decline. Recent studies have identified several factors that contribute to the progression and severity of the disease: diet, lifestyle, stress, sleep, nutrient deficiencies, mental health, socialization, and toxins. Thus, increasing evidence supports dietary and other lifestyle changes as potentially effective ways to prevent, slow, or reverse AD progression. Studies also have demonstrated that a personalized, multi-therapeutic approach is needed to improve metabolic abnormalities and AD-associated cognitive decline. These studies suggest the effects of abnormalities, such as insulin resistance, chronic inflammation, hypovitaminosis D, hormonal deficiencies, and hyperhomocysteinemia, in the AD process. Therefore a personalized, multi-therapeutic program based on an individual's genetics and biochemistry may be preferable over a single-drug/mono-therapeutic approach. This article reviews these multi-therapeutic strategies that identify and attenuate all the risk factors specific to each affected individual. This article systematically reviews studies that have incorporated multiple strategies that target numerous factors simultaneously to reverse or treat cognitive decline. We included high-quality clinical trials and observational studies that focused on the cognitive effects of programs comprising lifestyle, physical, and mental activity, as well as nutritional aspects. Articles from PubMed Central, Scopus, and Google Scholar databases were collected, and abstracts were reviewed for relevance to the subject matter. Epidemiological, pathological, toxicological, genetic, and biochemical studies have all concluded that AD represents a complex network insufficiency. The research studies explored in this manuscript confirm the need for a multifactorial approach to target the various risk factors of AD. A single-drug approach may delay the progression of memory loss but, to date, has not prevented or reversed it. Diet, physical activity, sleep, stress, and environment all contribute to the progression of the disease, and, therefore, a multi-factorial optimization of network support and function offers a rational therapeutic strategy. Thus, a multi-therapeutic program that simultaneously targets multiple factors underlying the AD network may be more effective than a mono-therapeutic approach.
Topics: Humans; Alzheimer Disease; Neurodegenerative Diseases; Cognitive Dysfunction; Cognition; Memory Disorders
PubMed: 36675177
DOI: 10.3390/ijms24021659 -
Cells May 2023Blood biomarkers have been considered tools for the diagnosis, prognosis, and monitoring of Alzheimer's disease (AD). Although amyloid-β peptide (Aβ) and tau are... (Meta-Analysis)
Meta-Analysis Review
Blood biomarkers have been considered tools for the diagnosis, prognosis, and monitoring of Alzheimer's disease (AD). Although amyloid-β peptide (Aβ) and tau are primarily blood biomarkers, recent studies have identified other reliable candidates that can serve as measurable indicators of pathological conditions. One such candidate is the glial fibrillary acidic protein (GFAP), an astrocytic cytoskeletal protein that can be detected in blood samples. Increasing evidence suggests that blood GFAP levels can be used to detect early-stage AD. In this systematic review and meta-analysis, we aimed to evaluate GFAP in peripheral blood as a biomarker for AD and provide an overview of the evidence regarding its utility. Our analysis revealed that the GFAP level in the blood was higher in the Aβ-positive group than in the negative groups, and in individuals with AD or mild cognitive impairment (MCI) compared to the healthy controls. Therefore, we believe that the clinical use of blood GFAP measurements has the potential to accelerate the diagnosis and improve the prognosis of AD.
Topics: Humans; Alzheimer Disease; Amyloid beta-Peptides; Biomarkers; Cognitive Dysfunction; Glial Fibrillary Acidic Protein
PubMed: 37174709
DOI: 10.3390/cells12091309 -
Neurology Mar 2020To test the hypothesis that distinct subtypes of Alzheimer disease (AD) exist and underlie the heterogeneity within AD, we conducted a systematic review and... (Meta-Analysis)
Meta-Analysis
OBJECTIVE
To test the hypothesis that distinct subtypes of Alzheimer disease (AD) exist and underlie the heterogeneity within AD, we conducted a systematic review and meta-analysis on AD subtype studies based on postmortem and neuroimaging data.
METHODS
EMBASE, PubMed, and Web of Science databases were consulted until July 2019.
RESULTS
Neuropathology and neuroimaging studies have consistently identified 3 subtypes of AD based on the distribution of tau-related pathology and regional brain atrophy: typical, limbic-predominant, and hippocampal-sparing AD. A fourth subtype, minimal atrophy AD, has been identified in several neuroimaging studies. Typical AD displays tau-related pathology and atrophy both in hippocampus and association cortex and has a pooled frequency of 55%. Limbic-predominant, hippocampal-sparing, and minimal atrophy AD had a pooled frequency of 21%, 17%, and 15%, respectively. Between-subtype differences were found in age at onset, age at assessment, sex distribution, years of education, global cognitive status, disease duration, APOE ε4 genotype, and CSF biomarker levels.
CONCLUSION
We identified 2 core dimensions of heterogeneity: typicality and severity. We propose that these 2 dimensions determine individuals' belonging to one of the AD subtypes based on the combination of protective factors, risk factors, and concomitant non-AD brain pathologies. This model is envisioned to aid with framing hypotheses, study design, interpretation of results, and understanding mechanisms in future subtype studies. Our model can be used along the A/T/N classification scheme for AD biomarkers. Unraveling the heterogeneity within AD is critical for implementing precision medicine approaches and for ultimately developing successful disease-modifying drugs for AD.
Topics: Alzheimer Disease; Humans
PubMed: 32047067
DOI: 10.1212/WNL.0000000000009058 -
Atencion Primaria May 2020The objective of this review is to analyze through a the scientific evidence about the effects of physical activity in patients with Alzheimer's disease (AD) as a...
OBJECTIVE
The objective of this review is to analyze through a the scientific evidence about the effects of physical activity in patients with Alzheimer's disease (AD) as a preventive and non-pharmacological treatment.
DESIGN
Systematic review.
DATA SOURCES
We have identified articles from Pubmed, Science Direct, Medline and Scopus databases, with the keywords Alzheimer, Exercise, Neuroimaging, MRI, PET y Physical Activity. Selected articles: We included those studies that evaluated the effects of physical activity on Alzheimer's disease and those which also included magnetic resonance imaging or positron emission tomography with Pittsburg Compound B marker (PiB) analyzing brain atrophy or increase of the beta-amyloid deposit respectively. We excluded studies including other types of dementia, different of AD. We also excluded articles which not included neuroimaging tests, single cases or non-English language articles.
DATA EXTRACTION
The PRISMA quality scale was used for the critical lecture of the studies. The researchers independently assessed the articles and the discrepancies were resolved by consensus.
RESULTS
We identified 75 articles, of which 23 were finally included in the review.
CONCLUSIONS
Most of the studies included do not allow us to know the impact of physical exercise on cognition and the cerebral structural-functional changes in patients at risk of developing AD or in patients who already have the disease. Without being able to rule out a possible beneficial effect, more studies are needed with a better design and methodological rigor that allows a better known about this association.
Topics: Alzheimer Disease; Amyloid beta-Peptides; Atrophy; Brain; Exercise; Humans; Magnetic Resonance Imaging; Neuroimaging; Positron-Emission Tomography
PubMed: 31153668
DOI: 10.1016/j.aprim.2018.09.010