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Ageing Research Reviews Aug 2022Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation technique. When stimulation is applied over the primary motor cortex and coupled with... (Meta-Analysis)
Meta-Analysis Review
Cortical excitability and plasticity in Alzheimer's disease and mild cognitive impairment: A systematic review and meta-analysis of transcranial magnetic stimulation studies.
BACKGROUND
Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation technique. When stimulation is applied over the primary motor cortex and coupled with electromyography measures, TMS can probe functions of cortical excitability and plasticity in vivo. The purpose of this meta-analysis is to evaluate the utility of TMS-derived measures for differentiating patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI) from cognitively normal older adults (CN).
METHODS
Databases searched included PubMed, Embase, APA PsycInfo, Medline, and CINAHL Plus from inception to July 2021.
RESULTS
Sixty-one studies with a total of 2728 participants (1454 patients with AD, 163 patients with MCI, and 1111 CN) were included. Patients with AD showed significantly higher cortical excitability, lower cortical inhibition, and impaired cortical plasticity compared to the CN cohorts. Patients with MCI exhibited increased cortical excitability and reduced plasticity compared to the CN cohort. Additionally, lower cognitive performance was significantly associated with higher cortical excitability and lower inhibition. No seizure events due to TMS were reported, and the mild adverse response rate is approximately 3/1000 (i.e., 9/2728).
CONCLUSIONS
Findings of our meta-analysis demonstrate the potential of using TMS-derived cortical excitability and plasticity measures as diagnostic biomarkers and therapeutic targets for AD and MCI.
Topics: Aged; Alzheimer Disease; Cognitive Dysfunction; Cortical Excitability; Humans; Neuronal Plasticity; Transcranial Magnetic Stimulation
PubMed: 35680080
DOI: 10.1016/j.arr.2022.101660 -
International Journal of Environmental... Jul 2022Aging is characterized by changes in the structure and quality of sleep. When the alterations in sleep become substantial, they can generate or accelerate cognitive... (Review)
Review
Aging is characterized by changes in the structure and quality of sleep. When the alterations in sleep become substantial, they can generate or accelerate cognitive decline, even in the absence of overt pathology. In fact, impaired sleep represents one of the earliest symptoms of Alzheimer's disease (AD). This systematic review aimed to analyze the studies on sleep quality in aging, also considering mild cognitive impairment (MCI) and AD. The review process was conducted according to the PRISMA statement. A total of 71 studies were included, and the whole sample had a mean age that ranged from 58.3 to 93.7 years (62.8-93.7 healthy participants and 61.8-86.7 pathological populations). Of these selected studies, 33 adopt subjective measurements, 31 adopt objective measures, and 10 studies used both. Pathological aging showed a worse impoverishment of sleep than older adults, in both subjective and objective measurements. The most common aspect compromised in AD and MCI were REM sleep, sleep efficiency, sleep latency, and sleep duration. These results underline that sleep alterations are associated with cognitive impairment. In conclusion, the frequency and severity of sleep disturbance appear to follow the evolution of cognitive impairment. The overall results of objective measures seem more consistent than those highlighted by subjective measurements.
Topics: Aged; Aged, 80 and over; Aging; Alzheimer Disease; Cognitive Dysfunction; Humans; Middle Aged; Sleep Quality; Sleep Wake Disorders
PubMed: 35886309
DOI: 10.3390/ijerph19148457 -
International Journal of Environmental... Nov 2022A growing body of research has examined the effect of aerobic exercise on cognitive function in people with Alzheimer's Disease (AD), but the findings of the available... (Meta-Analysis)
Meta-Analysis Review
A growing body of research has examined the effect of aerobic exercise on cognitive function in people with Alzheimer's Disease (AD), but the findings of the available studies were conflicting. The aim of this study was to explore the effect of aerobic exercise on cognitive function in AD patients. Searches were performed in PubMed, Web of Science, and EBSCO databases from the inception of indexing until 12 November 2021. Cochrane risk assessment tool was used to evaluate the methodological quality of the included literature. From 1942 search records initially identified, 15 randomized controlled trials (RCTs) were considered eligible for systematic review and meta-analysis. Included studies involved 503 participants in 16 exercise groups (mean age: 69.2-84 years) and 406 participants (mean age: 68.9-84 years) in 15 control groups. There was a significant effect of aerobic exercise on increasing mini-mental state examination (MMSE) score in AD patients [weighted mean difference (WMD), 1.50 (95% CI, 0.55 to 2.45), = 0.002]. Subgroup analyses showed that interventions conducted 30 min per session [WMD, 2.52 (95% CI, 0.84 to 4.20), = 0.003], less than 150 min per week [WMD, 2.10 (95% CI, 0.84 to 3.37), = 0.001], and up to three times per week [WMD, 1.68 (95% CI, 0.46 to 2.89), = 0.007] increased MMSE score significantly. In addition, a worse basal cognitive status was associated with greater improvement in MMSE score. Our analysis indicated that aerobic exercise, especially conducted 30 min per session, less than 150 min per week, and up to three times per week, contributed to improving cognitive function in AD patients. Additionally, a worse basal cognitive status contributed to more significant improvements in cognitive function.
Topics: Humans; Aged; Aged, 80 and over; Alzheimer Disease; Randomized Controlled Trials as Topic; Cognition; Exercise
PubMed: 36497772
DOI: 10.3390/ijerph192315700 -
Psychogeriatrics : the Official Journal... May 2023Aducanumab is a novel disease-modifying anti-amyloid-beta (Aβ) human monoclonal antibody specifically targeted to the pathophysiology of Alzheimer's disease (AD). It... (Review)
Review
Aducanumab is a novel disease-modifying anti-amyloid-beta (Aβ) human monoclonal antibody specifically targeted to the pathophysiology of Alzheimer's disease (AD). It was granted for treating AD in June 2021 by the United States Food and Drug Administration. We systematically analyzed available trials to evaluate the efficacy and safety of aducanumab treating AD. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines. We conducted an extensive literature search using the electronic databases MEDLINE through PubMed, EMBASE, Cochrane, Web of Science, and Scopus for suitable studies on aducanumab. We considered human clinical trials of aducanumab, assessing its efficacy and adverse effects in treating AD, excluding any experimental animal studies. We included three randomised controlled trials. Studies reported that aducanumab reduced brain amyloid-beta plaques in a time- and dose-dependent manner (dose-response, P < 0.05) and a slowed decline in cognition (22% reduction) in the high-dose treated group, difference of -0.39 versus placebo in Clinical Dementia Rating Scale Sum Boxes (95% CI, -0.69 to -0.09; P = 0.012) along with a reduced amyloid positron emission tomography standard uptake value ratio score (P < 0.001) and plasma p181-tau (phosphorylated tau) level. Amyloid-related imaging abnormality was reported as a serious adverse event and was profound in high-dose treated group (425/1029 in 10 mg/kg). Aducanumab has been reported to affect two main pathophysiologic hallmarks (Aβ and tau) of AD. We suggest future studies addressing aducanumab's efficacy and safety to confirm that the benefit of this drug outweighs the risk.
Topics: Animals; Humans; Alzheimer Disease; Tomography, X-Ray Computed; Antibodies, Monoclonal, Humanized; Amyloid beta-Peptides
PubMed: 36775284
DOI: 10.1111/psyg.12944 -
Ageing Research Reviews Sep 2021Alterations in olfactory functions are proposed to be early biomarkers for neurodegeneration. Many neurodegenerative diseases are age-related, including two of the most... (Review)
Review
Alterations in olfactory functions are proposed to be early biomarkers for neurodegeneration. Many neurodegenerative diseases are age-related, including two of the most common, Parkinson's disease (PD) and Alzheimer's disease (AD). The establishment of biomarkers that promote early risk identification is critical for the implementation of early treatment to postpone or avert pathological development. Olfactory dysfunction (OD) is seen in 90% of early-stage PD patients and 85% of patients with early-stage AD, which makes it an attractive biomarker for early diagnosis of these diseases. Here, we systematically review widely applied smelling tests available for humans as well as olfaction assessments performed in some animal models and the relationships between OD and normal aging, PD, AD, and other conditions. The utility of OD as a biomarker for neurodegenerative disease diagnosis and future research directions are also discussed.
Topics: Aging; Alzheimer Disease; Animals; Humans; Neurodegenerative Diseases; Olfaction Disorders; Parkinson Disease; Smell
PubMed: 34325072
DOI: 10.1016/j.arr.2021.101416 -
Journal of the Neurological Sciences Mar 2022Alzheimer's disease (AD) and Parkinson's disease (PD) are the two most prevalent neurodegenerative diseases, both without prevention or cure. The Mediterranean diet... (Review)
Review
Alzheimer's disease (AD) and Parkinson's disease (PD) are the two most prevalent neurodegenerative diseases, both without prevention or cure. The Mediterranean diet (MeDi) may be neuroprotective by modulating gut microbiota. We aimed to assess the effects of adherence to MeDi on the gut microbiota in relation to AD or PD risk. A search from inception to November 2020 was conducted in PubMed, CINAHL, EMBASE, Web of Science, Global Health, Biological Abstracts, and Grey Literature Report databases. Two searches were conducted: 1) (MeDi or Microbiota) and (PD or AD) and 2) MeDi and microbiota. Inclusion criteria for papers were specified prior to review. Of 4672 studies identified, 64 were eligible for inclusion. These studies were divided into five groups: MeDi and AD risk (n = 4), MeDi and PD risk (n = 2), MeDi and microbial composition or metabolomics (n = 21), AD and microbial composition or metabolomics (n = 7), and PD and microbial composition or metabolomics (n = 30). Adherence to the MeDi was associated with a lower risk of AD and PD development. Eight genera and two species of bacteria had an inverse relationship with MeDi and AD, and one family, eight genera and three species of bacteria had an inverse relationship with MeDi and PD. More studies are needed to investigate if MeDi, gut microbiota, and neurodegeneration are causally related.
Topics: Alzheimer Disease; Diet, Mediterranean; Gastrointestinal Microbiome; Humans; Parkinson Disease; Risk
PubMed: 35144237
DOI: 10.1016/j.jns.2022.120166 -
Journal of Neurology Feb 2023During the last decade, physical activity (PA) (or "exercise") has been identified as one of the main modifiable factors that influence the development of Alzheimer's... (Review)
Review
INTRODUCTION
During the last decade, physical activity (PA) (or "exercise") has been identified as one of the main modifiable factors that influence the development of Alzheimer's disease (AD) pathophysiology. We performed an umbrella review to summarize the evidence on the association between PA/exercise and the risk of developing AD risk, and the effect of exercise interventions on the progression of AD.
METHODS
A systematic search was performed in PubMed, SportDiscus, Cochrane Library and Web of Science (March 2022) to identify meta-analyses assessing the association between PA and the incidence of AD, and assessing the effect of exercise interventions on patients with AD.
RESULTS
Twenty-one studies were included. The results with strongest evidence revealed the positive effects of PA on AD risk. Specifically, meeting the WHO recommendations for PA was associated with a lower risk of AD. They also revealed positive effects of exercise on cognitive function, physical performance, and functional independence.
CONCLUSIONS
There is strong evidence of a protective effect of regular PA against AD risk; however, the dose-response association remains unclear. Physical exercise seems to improve several dimensions in patients with AD, although research is warranted to elucidate the exercise characteristics that promote the greatest benefits.
Topics: Humans; Alzheimer Disease; Cognition; Exercise; Exercise Therapy; Meta-Analysis as Topic
PubMed: 36342524
DOI: 10.1007/s00415-022-11454-8 -
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 -
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