Catechol-O-methyltransferase, Cognition and Alzheimer's Disease

2018 ◽  
Vol 15 (5) ◽  
pp. 408-419 ◽  
Author(s):  
Matea Nikolac Perkovic ◽  
Dubravka Svob Strac ◽  
Lucija Tudor ◽  
Marcela Konjevod ◽  
Gordana Nedic Erjavec ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Processes ◽  
Cognitive Impairments ◽  
Complex Trait ◽  
Brain Regions ◽  
Dopamine Metabolism ◽  
Psychotic Symptoms ◽  
Brain Functions ◽  
Characteristic Features

Objective: Cognition is a complex trait representing a set of all mental abilities and processes related to knowledge. Although diverse brain regions are involved, most cognitive processes appear to engage cortical regions. The activity of dopaminergic neurons in prefrontal cortex represents a biological substrate underlying cognitive functions. Alzheimer's Disease (AD) is the most frequent dementia associated with cognitive impairments. Cognitive impairment in AD starts slowly with discrete deterioration in memory, language, thinking and reasoning, but it progresses into more severe and debilitating cognitive dysfunction. Cognitive function is affected by the complex interactions between various genetic, epigenetic, developmental and environmental factors. One of the most studied genes, associated with cognitive disturbances, is the gene coding for Catechol-O-methyltransferase (COMT), the enzyme with major role in dopamine metabolism and modulation of different brain functions. Therefore, COMT is studied as a target for many neuropsychiatric disorders, including dementias and AD. The COMT Val158/108Met functional polymorphism affects significantly the enzyme activity and consequently cognitive performance associated with altered dopamine function. The association of COMT Val158/108Met polymorphism with some cognitive domains and psychosis in AD was reported in some but not in all studies. Besides COMT Val158/108Met polymorphism, other risk genotypes or haplotypes should be evaluated to determine the association of COMT with cognitive decline in AD. Conclusion: Better understanding of the role of COMT in cognitive processes in AD, as well as integration of neurobiological, genetic, genomic and epigenetic data, might help in developing new potential therapies of cognitive impairments and psychotic symptoms, characteristic features of AD.

The ABC of Alzheimer's Disease: Behavioral Symptoms and Their Treatment

2002 ◽  
Vol 14 (S1) ◽  
pp. 27-49 ◽  
Author(s):  
George T. Grossberg
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Treatment Options ◽  
Lewy Body Dementia ◽  
Economic Cost ◽  
Brain Regions ◽  
Behavioral Symptoms ◽  
Psychotic Symptoms ◽  
Ache Inhibitors ◽  
Che Inhibitors

Behavioral and psychological symptoms of dementia (BPSD) are a common manifestation of Alzheimer's disease (AD) and other dementia syndromes. Patients experience prominent and multiple symptoms, which are both distressing and a source of considerable social, health, and economic cost. Development of symptoms is in part related to progressive neurodegeneration and cholinergic deficiency in brain regions important in the regulation of behavioral and emotional responses including the cortex, hippocampus, and limbic system. Cholinesterase (ChE) inhibitors offer a mechanism-based approach to therapy to enhance endogenous cholinergic neurotransmission. Studies using ChE inhibitors have demonstrated their clear potential to improve or stabilize existing BPSD. Differences have been noted between selective acetylcholinesterase (AChE) inhibitors (donepezil and galantamine) and dual ChE inhibitors (rivastigmine) in terms of treatment response. While donepezil has shown efficacy in moderate to severe noninstitutionalized AD patients, conflicting results have been obtained in mild to moderate patients and in nursing home patients. Galantamine has been shown to delay the onset of BPSD during a five-month study but has been otherwise poorly studied to-date. Both donepezil and galantamine have not as yet demonstrated efficacy in reducing psychotic symptoms or in reducing levels of concomitant psychotropic medication use. Studies with the dual ChE inhibitor rivastigmine in mild to moderately severe AD and in Lewy body dementia (LBD) have shown improvements in behavioral symptoms including psychosis. Improvements have been maintained over a period of up to two years. In addition, institutionalized patients with severe AD have shown symptomatic benefits with a reduction in the requirement for additional psychotropic drugs following treatment with rivastigmine. The psychotropic properties associated with rivastigmine may in part be mediated through effects on butyrylcholinesterase. Current treatment options are limited for patients with dementia syndromes other than AD. However, data concerning rivastigmine in patients with LBD and preliminary studies in Parkinson's disease dementia and vascular dementia suggest a role for ChE inhibitors across the spectrum of dementia syndromes. Finally, studies that incorporated a delayed start design demonstrate that ChE inhibitors may delay the progression of BPSD.

scholarly journals AD Course Map charts Alzheimer’s disease progression

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Igor Koval ◽  
Alexandre Bône ◽  
Maxime Louis ◽  
Thomas Lartigue ◽  
Simona Bottani ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Disease Progression ◽  
Cognitive Impairments ◽  
Brain Regions ◽  
Virtual Patients ◽  
Genetic Determinants ◽  
Compensatory Mechanisms ◽  
Brain Images ◽  
Neuropsychological Assessments

AbstractAlzheimer’s disease (AD) is characterized by the progressive alterations seen in brain images which give rise to the onset of various sets of symptoms. The variability in the dynamics of changes in both brain images and cognitive impairments remains poorly understood. This paper introduces AD Course Map a spatiotemporal atlas of Alzheimer’s disease progression. It summarizes the variability in the progression of a series of neuropsychological assessments, the propagation of hypometabolism and cortical thinning across brain regions and the deformation of the shape of the hippocampus. The analysis of these variations highlights strong genetic determinants for the progression, like possible compensatory mechanisms at play during disease progression. AD Course Map also predicts the patient’s cognitive decline with a better accuracy than the 56 methods benchmarked in the open challenge TADPOLE. Finally, AD Course Map is used to simulate cohorts of virtual patients developing Alzheimer’s disease. AD Course Map offers therefore new tools for exploring the progression of AD and personalizing patients care.

Psychotic Symptoms in Alzheimer's Disease Are Not Associated With More Severe Neuropathologic Features

2000 ◽  
Vol 12 (4) ◽  
pp. 547-558 ◽  
Author(s):  
Robert A. Sweet ◽  
Ronald L. Hamilton ◽  
Oscar L. Lopez ◽  
William E. Klunk ◽  
Stephen R. Wisniewski ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Functional Decline ◽  
Neurofibrillary Tangle ◽  
Temporal Cortex ◽  
Lewy Bodies ◽  
Occipital Cortex ◽  
Brain Regions ◽  
Neuritic Plaque ◽  
Psychotic Symptoms

Psychotic symptoms in Alzheimer's disease (AD) have been associated with increased rates of cognitive impairment and functional decline. Prior studies have been conflicting with regard to whether AD patients with psychosis (AD+P) have evidence of more severe neuropathologic findings at postmortem exam. We examined the severity of neuritic plaques and neurofibrillary tangles in six brain regions—middle frontal cortex, hippocampus, inferior parietal cortex, superior temporal cortex, occipital cortex, and transentorhinal cortex—in 24 AD+P subjects and 25 matched AD subjects without psychosis (AD-P). All analyses controlled for the presence of cortical Lewy bodies, and corrected for multiple comparisons. We found no significant associations between neuritic plaque and neurofibrillary tangle severity and AD+P, and no significant associations with any individual psychotic symptom. The association of AD+P with a more rapidly progressive course of AD appears to be mediated by a neuropathologic process other than increased severity of plaque and tangle formation.

scholarly journals 439 - Sex-dependent increase of cerebral blood flow in cortex and hippocampus as a compensatory mechanism in end-of-life dementia: A MRI-ASL translational approach in models of normal and pathological aging

2020 ◽  
Vol 32 (S1) ◽  
pp. 157-157
Author(s):  
A Muntsant-Soria ◽  
F Jiménez-Altayó ◽  
E Jiménez-Xarrié ◽  
L Giménez-Llort
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
End Of Life ◽  
Brain Region ◽  
Memory Performance ◽  
Brain Regions ◽  
Compensatory Mechanism ◽  
Functional Impairments ◽  
Time Asymmetry ◽  
Brain Functions

Alzheimer’s disease (AD) is associated with brain oxidative stress, inflammation, and cerebrovascular disease. Structural and functional abnormalities in cerebral microvasculature have been described in both patients and animals models. New tools and biomarkers for the detection of the disease are still emerging, such as Arterial Spin Labeling (ASL), a magnetic resonance imaging (MRI) technique for non-invasive measurements of cerebral blood blow (CBF) whose alteration may be involved in AD-pathogenesis. Nevertheless, more studies in the field are needed since both hypoperfusion and hyperperfusion in different brain areas are reported and can be involved in different brain functions. Recently, we reported in our colony of 3xTg-AD mice modeling Alzheimer’s disease a higher number of β-amyloid plaques in the hippocampus and entorhinal cortex in middle-aged females and extensive regions of hypoxia which were not seen in males. In the present study, we evaluated CBF in five different brain regions (hippocampus, cortex, striatum, caudate putamen and amygdala) in older male and female surviving until very advanced-stages of disease and as compared with age-matched counterparts with normal aging. AD-phenotype was evaluated by a comprehensive screening of three main functional impairments: physical (frailty), BPSD-like and cognitive deficits. CBF was measured using MRI-ASL and meaningful correlations between AD-phenotype and CBF were performed to better understand the relation between the level of perfusion and frailty, the BPSD-like behaviors and cognitive impairments. The results indicated sex- and brain region-associated changes in CBF. Among all, 3xTg-AD female mice survivors had increased CBF in cortex and hippocampus as compared with their wildtype counterparts. Here, we also report, for the first time, asymmetry between left -right hemispheres in the female’s cortex, in the hippocampus of control males and 3xTg-AD females, as well as in the striatum of control females. Cortex was the area that better correlated with behavior, with asymmetry being associated with worse memory performance. Moreover, hemisphere CBF asymmetry in limbic system was related with copying-with-stress strategies and associated locomotor activity in anxiety tests. The present study suggests a potential compensatory hemodynamic mechanism in end-of-life dementia which is sex- and brain region dependent and can be target for pharmacological and non-pharmacological interventions.

A Biomarker Combining Imaging and Neuropsychological Assessment for Tracking Early Alzheimer's Disease in Clinical Trials

2018 ◽  
Vol 15 (5) ◽  
pp. 429-442 ◽  
Author(s):  
Nishant Verma ◽  
S. Natasha Beretvas ◽  
Belen Pascual ◽  
Joseph C. Masdeu ◽  
Mia K. Markey ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Cognitive Impairment ◽  
Latent Variable ◽  
Brain Regions ◽  
Disease Assessment ◽  
Latent Variable Analysis ◽  
The Relationship ◽  
Selection Of

Background: Combining optimized cognitive (Alzheimer's Disease Assessment Scale- Cognitive subscale, ADAS-Cog) and atrophy markers of Alzheimer's disease for tracking progression in clinical trials may provide greater sensitivity than currently used methods, which have yielded negative results in multiple recent trials. Furthermore, it is critical to clarify the relationship among the subcomponents yielded by cognitive and imaging testing, to address the symptomatic and anatomical variability of Alzheimer's disease. Method: Using latent variable analysis, we thoroughly investigated the relationship between cognitive impairment, as assessed on the ADAS-Cog, and cerebral atrophy. A biomarker was developed for Alzheimer's clinical trials that combines cognitive and atrophy markers. Results: Atrophy within specific brain regions was found to be closely related with impairment in cognitive domains of memory, language, and praxis. The proposed biomarker showed significantly better sensitivity in tracking progression of cognitive impairment than the ADAS-Cog in simulated trials and a real world problem. The biomarker also improved the selection of MCI patients (78.8±4.9% specificity at 80% sensitivity) that will evolve to Alzheimer's disease for clinical trials. Conclusion: The proposed biomarker provides a boost to the efficacy of clinical trials focused in the mild cognitive impairment (MCI) stage by significantly improving the sensitivity to detect treatment effects and improving the selection of MCI patients that will evolve to Alzheimer’s disease.

Dehydroepiandrosterone (DHEA) and its Sulphate (DHEAS) in Alzheimer’s Disease

2020 ◽  
Vol 17 (2) ◽  
pp. 141-157 ◽  
Author(s):  
Dubravka S. Strac ◽  
Marcela Konjevod ◽  
Matea N. Perkovic ◽  
Lucija Tudor ◽  
Gordana N. Erjavec ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Large Scale ◽  
Therapeutic Potential ◽  
Relevant Literature ◽  
Comprehensive Overview ◽  
Brain Functions ◽  
Specific Effects ◽  
And Behavior

Background: Neurosteroids Dehydroepiandrosterone (DHEA) and Dehydroepiandrosterone Sulphate (DHEAS) are involved in many important brain functions, including neuronal plasticity and survival, cognition and behavior, demonstrating preventive and therapeutic potential in different neuropsychiatric and neurodegenerative disorders, including Alzheimer’s disease. Objective: The aim of the article was to provide a comprehensive overview of the literature on the involvement of DHEA and DHEAS in Alzheimer’s disease. Method: PubMed and MEDLINE databases were searched for relevant literature. The articles were selected considering their titles and abstracts. In the selected full texts, lists of references were searched manually for additional articles. Results: We performed a systematic review of the studies investigating the role of DHEA and DHEAS in various in vitro and animal models, as well as in patients with Alzheimer’s disease, and provided a comprehensive discussion on their potential preventive and therapeutic applications. Conclusion: Despite mixed results, the findings of various preclinical studies are generally supportive of the involvement of DHEA and DHEAS in the pathophysiology of Alzheimer’s disease, showing some promise for potential benefits of these neurosteroids in the prevention and treatment. However, so far small clinical trials brought little evidence to support their therapy in AD. Therefore, large-scale human studies are needed to elucidate the specific effects of DHEA and DHEAS and their mechanisms of action, prior to their applications in clinical practice.

scholarly journals Genome-wide analysis identifies a novel LINC-PINT splice variant associated with vascular amyloid pathology in Alzheimer’s disease

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Joseph S. Reddy ◽  
Mariet Allen ◽  
Charlotte C. G. Ho ◽  
Stephanie R. Oatman ◽  
Özkan İş ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genome Wide Association Study ◽  
Transcriptome Profiling ◽  
Brain Regions ◽  
Common Finding ◽  
Amyloid Angiopathy ◽  
Genome Wide ◽  
A Genome ◽  
Male Sex

AbstractCerebral amyloid angiopathy (CAA) contributes to accelerated cognitive decline in Alzheimer’s disease (AD) dementia and is a common finding at autopsy. The APOEε4 allele and male sex have previously been reported to associate with increased CAA in AD. To inform biomarker and therapeutic target discovery, we aimed to identify additional genetic risk factors and biological pathways involved in this vascular component of AD etiology. We present a genome-wide association study of CAA pathology in AD cases and report sex- and APOE-stratified assessment of this phenotype. Genome-wide genotypes were collected from 853 neuropathology-confirmed AD cases scored for CAA across five brain regions, and imputed to the Haplotype Reference Consortium panel. Key variables and genome-wide genotypes were tested for association with CAA in all individuals and in sex and APOEε4 stratified subsets. Pathway enrichment was run for each of the genetic analyses. Implicated loci were further investigated for functional consequences using brain transcriptome data from 1,186 samples representing seven brain regions profiled as part of the AMP-AD consortium. We confirmed association of male sex, AD neuropathology and APOEε4 with increased CAA, and identified a novel locus, LINC-PINT, associated with lower CAA amongst APOEε4-negative individuals (rs10234094-C, beta = −3.70 [95% CI −0.49—−0.24]; p = 1.63E-08). Transcriptome profiling revealed higher LINC-PINT expression levels in AD cases, and association of rs10234094-C with altered LINC-PINT splicing. Pathway analysis indicates variation in genes involved in neuronal health and function are linked to CAA in AD patients. Further studies in additional and diverse cohorts are needed to assess broader translation of our findings.

scholarly journals Deep-MEG: spatiotemporal CNN features and multiband ensemble classification for predicting the early signs of Alzheimer’s disease with magnetoencephalography

2021 ◽  
Author(s):  
Antonio Giovannetti ◽  
Gianluca Susi ◽  
Paola Casti ◽  
Arianna Mencattini ◽  
Sandra Pusil ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Brain Regions ◽  
Ensemble Classification ◽  
The Novel ◽  
Ensemble Classifiers ◽  
Deep Convolutional Neural Networks ◽  
Early Signs ◽  
Data Representations ◽  
The Brain

AbstractIn this paper, we present the novel Deep-MEG approach in which image-based representations of magnetoencephalography (MEG) data are combined with ensemble classifiers based on deep convolutional neural networks. For the scope of predicting the early signs of Alzheimer’s disease (AD), functional connectivity (FC) measures between the brain bio-magnetic signals originated from spatially separated brain regions are used as MEG data representations for the analysis. After stacking the FC indicators relative to different frequency bands into multiple images, a deep transfer learning model is used to extract different sets of deep features and to derive improved classification ensembles. The proposed Deep-MEG architectures were tested on a set of resting-state MEG recordings and their corresponding magnetic resonance imaging scans, from a longitudinal study involving 87 subjects. Accuracy values of 89% and 87% were obtained, respectively, for the early prediction of AD conversion in a sample of 54 mild cognitive impairment subjects and in a sample of 87 subjects, including 33 healthy controls. These results indicate that the proposed Deep-MEG approach is a powerful tool for detecting early alterations in the spectral–temporal connectivity profiles and in their spatial relationships.

scholarly journals Microcanonical and Canonical Ensembles for fMRI Brain Networks in Alzheimer’s Disease

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 216 ◽  
Author(s):  
Jianjia Wang ◽  
Xichen Wu ◽  
Mingrui Li ◽  
Hui Wu ◽  
Edwin Hancock
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Ensemble Methods ◽  
Brain Regions ◽  
Fmri Data ◽  
Thermal Systems ◽  
Network Construction ◽  
Network Characteristics ◽  
Network Entropy ◽  
Canonical Ensembles

This paper seeks to advance the state-of-the-art in analysing fMRI data to detect onset of Alzheimer’s disease and identify stages in the disease progression. We employ methods of network neuroscience to represent correlation across fMRI data arrays, and introduce novel techniques for network construction and analysis. In network construction, we vary thresholds in establishing BOLD time series correlation between nodes, yielding variations in topological and other network characteristics. For network analysis, we employ methods developed for modelling statistical ensembles of virtual particles in thermal systems. The microcanonical ensemble and the canonical ensemble are analogous to two different fMRI network representations. In the former case, there is zero variance in the number of edges in each network, while in the latter case the set of networks have a variance in the number of edges. Ensemble methods describe the macroscopic properties of a network by considering the underlying microscopic characterisations which are in turn closely related to the degree configuration and network entropy. When applied to fMRI data in populations of Alzheimer’s patients and controls, our methods demonstrated levels of sensitivity adequate for clinical purposes in both identifying brain regions undergoing pathological changes and in revealing the dynamics of such changes.

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