716 resultados para Mild cognitive impairment, Dementia, Depression, n-3 Fatty acids, EPA, DHA
Resumo:
Mild cognitive impairment (MCI) often refers to the preclinical stage of dementia, where the majority develop Alzheimer's disease (AD). Given that neurodegenerative burden and compensatory mechanisms might exist before accepted clinical symptoms of AD are noticeable, the current prospective study aimed to investigate the functioning of brain regions in the visuospatial networks responsible for preclinical symptoms in AD using event-related functional magnetic resonance imaging (fMRI). Eighteen MCI patients were evaluated and clinically followed for approximately 3 years. Five progressed to AD (PMCI) and eight remained stable (SMCI). Thirteen age-, gender- and education-matched controls also participated. An angle discrimination task with varying task demands was used. Brain activation patterns as well as task demand-dependent and -independent signal changes between the groups were investigated by using an extended general linear model including individual performance (reaction time [RT]) of each single trial. Similar behavioral (RT and accuracy) responses were observed between MCI patients and controls. A network of bilateral activations, e.g. dorsal pathway, which increased linearly with increasing task demand, was engaged in all subjects. Compared with SMCI patients and controls, PMCI patients showed a stronger relation between task demand and brain activity in left superior parietal lobules (SPL) as well as a general task demand-independent increased activation in left precuneus. Altered brain function can be detected at a group level in individuals that progress to AD before changes occur at the behavioral level. Increased parietal activation in PMCI could reflect a reduced neuronal efficacy due to accumulating AD pathology and might predict future clinical decline in patients with MCI.
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Brain oscillations are closely correlated with human information processing and fundamental aspects of cognition. Previous literature shows that due to the relation between brain oscillations and memory processes, spectral dynamics during such tasks are good candidates to study and characterize memory related pathologies. Mild cognitive impairment (MCI), defined as a clinical condition characterized by memory impairment and/ or deterioration of additional cognitive domains, is considered a preliminary stage in the dementia process. In consequence, the study of its brain patterns could help to achieve an early diagnosis of Alzheimer Disease.
Resumo:
Alzheimer's disease (AD) is the most common cause of dementia. Over the last few years, a considerable effort has been devoted to exploring new biomarkers. Nevertheless, a better understanding of brain dynamics is still required to optimize therapeutic strategies. In this regard, the characterization of mild cognitive impairment (MCI) is crucial, due to the high conversion rate from MCI to AD. However, only a few studies have focused on the analysis of magnetoencephalographic (MEG) rhythms to characterize AD and MCI. In this study, we assess the ability of several parameters derived from information theory to describe spontaneous MEG activity from 36 AD patients, 18 MCI subjects and 26 controls. Three entropies (Shannon, Tsallis and Rényi entropies), one disequilibrium measure (based on Euclidean distance ED) and three statistical complexities (based on Lopez Ruiz–Mancini–Calbet complexity LMC) were used to estimate the irregularity and statistical complexity of MEG activity. Statistically significant differences between AD patients and controls were obtained with all parameters (p < 0.01). In addition, statistically significant differences between MCI subjects and controls were achieved by ED and LMC (p < 0.05). In order to assess the diagnostic ability of the parameters, a linear discriminant analysis with a leave-one-out cross-validation procedure was applied. The accuracies reached 83.9% and 65.9% to discriminate AD and MCI subjects from controls, respectively. Our findings suggest that MCI subjects exhibit an intermediate pattern of abnormalities between normal aging and AD. Furthermore, the proposed parameters provide a new description of brain dynamics in AD and MCI.
Resumo:
Previous studies of the dementia continuum have characterized the early disruption of the brain oscillatory activity at the stage of Mild cognitive impairment (MCI). Reduction in power in posterior regions in the alpha band has been one of the landmarks of the Alzheimer Disease accompanied by the anteriorization of the theta band power. However, little is known about the neurophysiological differences between single and multidomain MCI patients.Our goal is to study the differences in oscillatory magnetic activity between amnestic single and multidomain MCI. This will allow us to test whether the effect of the impairment in a single cognitive domain or in a more widespread functional impairment can be reflected in specific neurophysiological profiles.
Resumo:
Although progressive functional brain network disruption has been one of the hallmarks of Alzheimer?s Dis- ease, little is known about the origin of this functional impairment that underlies cognitive symptoms. We in- vestigated how the loss of white matter (WM) integrity disrupts the organization of the functional networks at different frequency bands. The analyses were performed in a sample of healthy elders and mild cognitive im- pairment (MCI) subjects. Spontaneous brain magnetic activity (measured with magnetoencephalography) was characterized with phase synchronization analysis, and graph theory was applied to the functional networks. We identified WM areas (using diffusion weighted magnetic resonance imaging) that showed a statistical de- pendence between the fractional anisotropy and the graph metrics. These regions are part of an episodic mem- ory network and were also related to cognitive functions. Our data support the hypothesis that disruption of the anatomical networks influences the organization at the functional level resulting in the prodromal dementia syndrome of MCI.
Resumo:
La investigación para el conocimiento del cerebro es una ciencia joven, su inicio se remonta a Santiago Ramón y Cajal en 1888. Desde esta fecha a nuestro tiempo la neurociencia ha avanzado mucho en el desarrollo de técnicas que permiten su estudio. Desde la neurociencia cognitiva hoy se explican muchos modelos que nos permiten acercar a nuestro entendimiento a capacidades cognitivas complejas. Aun así hablamos de una ciencia casi en pañales que tiene un lago recorrido por delante. Una de las claves del éxito en los estudios de la función cerebral ha sido convertirse en una disciplina que combina conocimientos de diversas áreas: de la física, de las matemáticas, de la estadística y de la psicología. Esta es la razón por la que a lo largo de este trabajo se entremezclan conceptos de diferentes campos con el objetivo de avanzar en el conocimiento de un tema tan complejo como el que nos ocupa: el entendimiento de la mente humana. Concretamente, esta tesis ha estado dirigida a la integración multimodal de la magnetoencefalografía (MEG) y la resonancia magnética ponderada en difusión (dMRI). Estas técnicas son sensibles, respectivamente, a los campos magnéticos emitidos por las corrientes neuronales, y a la microestructura de la materia blanca cerebral. A lo largo de este trabajo hemos visto que la combinación de estas técnicas permiten descubrir sinergias estructurofuncionales en el procesamiento de la información en el cerebro sano y en el curso de patologías neurológicas. Más específicamente en este trabajo se ha estudiado la relación entre la conectividad funcional y estructural y en cómo fusionarlas. Para ello, se ha cuantificado la conectividad funcional mediante el estudio de la sincronización de fase o la correlación de amplitudes entre series temporales, de esta forma se ha conseguido un índice que mide la similitud entre grupos neuronales o regiones cerebrales. Adicionalmente, la cuantificación de la conectividad estructural a partir de imágenes de resonancia magnética ponderadas en difusión, ha permitido hallar índices de la integridad de materia blanca o de la fuerza de las conexiones estructurales entre regiones. Estas medidas fueron combinadas en los capítulos 3, 4 y 5 de este trabajo siguiendo tres aproximaciones que iban desde el nivel más bajo al más alto de integración. Finalmente se utilizó la información fusionada de MEG y dMRI para la caracterización de grupos de sujetos con deterioro cognitivo leve, la detección de esta patología resulta relevante en la identificación precoz de la enfermedad de Alzheimer. Esta tesis está dividida en seis capítulos. En el capítulos 1 se establece un contexto para la introducción de la connectómica dentro de los campos de la neuroimagen y la neurociencia. Posteriormente en este capítulo se describen los objetivos de la tesis, y los objetivos específicos de cada una de las publicaciones científicas que resultaron de este trabajo. En el capítulo 2 se describen los métodos para cada técnica que fue empleada: conectividad estructural, conectividad funcional en resting state, redes cerebrales complejas y teoría de grafos y finalmente se describe la condición de deterioro cognitivo leve y el estado actual en la búsqueda de nuevos biomarcadores diagnósticos. En los capítulos 3, 4 y 5 se han incluido los artículos científicos que fueron producidos a lo largo de esta tesis. Estos han sido incluidos en el formato de la revista en que fueron publicados, estando divididos en introducción, materiales y métodos, resultados y discusión. Todos los métodos que fueron empleados en los artículos están descritos en el capítulo 2 de la tesis. Finalmente, en el capítulo 6 se concluyen los resultados generales de la tesis y se discuten de forma específica los resultados de cada artículo. ABSTRACT In this thesis I apply concepts from mathematics, physics and statistics to the neurosciences. This field benefits from the collaborative work of multidisciplinary teams where physicians, psychologists, engineers and other specialists fight for a common well: the understanding of the brain. Research on this field is still in its early years, being its birth attributed to the neuronal theory of Santiago Ramo´n y Cajal in 1888. In more than one hundred years only a very little percentage of the brain functioning has been discovered, and still much more needs to be explored. Isolated techniques aim at unraveling the system that supports our cognition, nevertheless in order to provide solid evidence in such a field multimodal techniques have arisen, with them we will be able to improve current knowledge about human cognition. Here we focus on the multimodal integration of magnetoencephalography (MEG) and diffusion weighted magnetic resonance imaging. These techniques are sensitive to the magnetic fields emitted by the neuronal currents and to the white matter microstructure, respectively. The combination of such techniques could bring up evidences about structural-functional synergies in the brain information processing and which part of this synergy fails in specific neurological pathologies. In particular, we are interested in the relationship between functional and structural connectivity, and how two integrate this information. We quantify the functional connectivity by studying the phase synchronization or the amplitude correlation between time series obtained by MEG, and so we get an index indicating similarity between neuronal entities, i.e. brain regions. In addition we quantify structural connectivity by performing diffusion tensor estimation from the diffusion weighted images, thus obtaining an indicator of the integrity of the white matter or, if preferred, the strength of the structural connections between regions. These quantifications are then combined following three different approaches, from the lowest to the highest level of integration, in chapters 3, 4 and 5. We finally apply the fused information to the characterization or prediction of mild cognitive impairment, a clinical entity which is considered as an early step in the continuum pathological process of dementia. The dissertation is divided in six chapters. In chapter 1 I introduce connectomics within the fields of neuroimaging and neuroscience. Later in this chapter we describe the objectives of this thesis, and the specific objectives of each of the scientific publications that were produced as result of this work. In chapter 2 I describe the methods for each of the techniques that were employed, namely structural connectivity, resting state functional connectivity, complex brain networks and graph theory, and finally, I describe the clinical condition of mild cognitive impairment and the current state of the art in the search for early biomarkers. In chapters 3, 4 and 5 I have included the scientific publications that were generated along this work. They have been included in in their original format and they contain introduction, materials and methods, results and discussion. All methods that were employed in these papers have been described in chapter 2. Finally, in chapter 6 I summarize all the results from this thesis, both locally for each of the scientific publications and globally for the whole work.
Resumo:
Increased variability in performance has been associated with the emergence of several neurological and psychiatric pathologies. However, whether and how consistency of neuronal activity may also be indicative of an underlying pathology is still poorly understood. Here we propose a novel method for evaluating consistency from non-invasive brain recordings. We evaluate the consistency of the cortical activity recorded with magnetoencephalography in a group of subjects diagnosed with Mild Cognitive Impairment (MCI), a condition sometimes prodromal of dementia, during the execution of a memory task. We use metrics coming from nonlinear dynamics to evaluate the consistency of cortical regions. A representation known as parenclitic networks is constructed, where atypical features are endowed with a network structure, the topological properties of which can be studied at various scales. Pathological conditions correspond to strongly heterogeneous networks, whereas typical or normative conditions are characterized by sparsely connected networks with homogeneous nodes. The analysis of this kind of networks allows identifying the extent to which consistency is affected in the MCI group and the focal points where MCI is especially severe. To the best of our knowledge, these results represent the first attempt at evaluating the consistency of brain functional activity using complex networks theory.
Resumo:
Background/Aims: The Mini Addenbrooke’s Cognitive Examination (M-ACE) is the abbreviated version of the widely-used Addenbrooke’s Cognitive Examination (ACE-III), a cognitive screening tool that is used internationally in the assessment of mild cognitive impairment (MCI) and dementia. The objectives of this study were to investigate the diagnostic accuracy of the M-ACE with individuals aged 75 and over to distinguish between those who do and do not have a dementia or MCI, and also to establish whether the cut-off scores recommended by Hsieh et al. (2014) [9] in the original validation study for the M-ACE are optimal for this age group. Methods: The M-ACE was administered to 58 participants (24 with a diagnosis of dementia, 17 with a diagnosis of MCI and 17 healthy controls). The extent to which scores distinguished between groups (dementia, MCI or no diagnosis) was explored using receiver operating characteristic curve analysis. Results: The optimal cut-off for detecting dementia was ≤ 21/30 (score ≤ 21/30 indicating dementia with a sensitivity of 0.95, a specificity of 1 and a positive predictive value of 1) compared to the original higher published cut-off of ≤ 25/30 (sensitivity of 0.95, specificity of 0.70 and a positive predictive value of 0.82 in this sample). Conclusions: The M-ACE has excellent diagnostic accuracy for the detection of dementia in a UK clinical sample. It may be necessary to consider lower cut-offs than those given in the original validation study.
Resumo:
Background: The aim of this study is to examine the influence of the catechol-O-methyltranferase (COMT) gene (polymorphism Val158 Met) as a risk factor for Alzheimer's disease (AD) and mild cognitive impairment of amnesic type (MCI), and its synergistic effect with the apolipoprotein E gene (APOE). A total of 223 MCI patients, 345 AD and 253 healthy controls were analyzed. Clinical criteria and neuropsychological tests were used to establish diagnostic groups. The DNA Bank of the University of the Basque Country (UPV-EHU) (Spain) determined COMT Val158 Met and APOE genotypes using real time polymerase chain reaction (rtPCR) and polymerase chain reaction (PCR), and restriction fragment length polymorphism (RFLPs), respectively. Multinomial logistic regression models were used to determine the risk of AD and MCI. Results: Neither COMT alleles nor genotypes were independent risk factors for AD or MCI. The high activity genotypes (GG and AG) showed a synergistic effect with APOE epsilon 4 allele, increasing the risk of AD (OR = 5.96, 95% CI 2.74-12.94, p < 0.001 and OR = 6.71, 95% CI 3.36-13.41, p < 0.001 respectivily). In AD patients this effect was greater in women. In MCI patients such as synergistic effect was only found between AG and APOE epsilon 4 allele (OR = 3.21 95% CI 1.56-6.63, p = 0.02) and was greater in men (OR = 5.88 95% CI 1.69-20.42, p < 0.01). Conclusion: COMT (Val158 Met) polymorphism is not an independent risk factor for AD or MCI, but shows a synergistic effect with APOE epsilon 4 allele that proves greater in women with AD.
Resumo:
This study combined high resolution mass spectrometry (HRMS), advanced chemometrics and pathway enrichment analysis to analyse the blood metabolome of patients attending the memory clinic: cases of mild cognitive impairment (MCI; n = 16), cases of MCI who upon subsequent follow-up developed Alzheimer's disease (MCI_AD; n = 19), and healthy age-matched controls (Ctrl; n = 37). Plasma was extracted in acetonitrile and applied to an Acquity UPLC HILIC (1.7μm x 2.1 x 100 mm) column coupled to a Xevo G2 QTof mass spectrometer using a previously optimised method. Data comprising 6751 spectral features were used to build an OPLS-DA statistical model capable of accurately distinguishing Ctrl, MCI and MCI_AD. The model accurately distinguished (R2 = 99.1%; Q2 = 97%) those MCI patients who later went on to develop AD. S-plots were used to shortlist ions of interest which were responsible for explaining the maximum amount of variation between patient groups. Metabolite database searching and pathway enrichment analysis indicated disturbances in 22 biochemical pathways, and excitingly it discovered two interlinked areas of metabolism (polyamine metabolism and L-Arginine metabolism) were differentially disrupted in this well-defined clinical cohort. The optimised untargeted HRMS methods described herein not only demonstrate that it is possible to distinguish these pathologies in human blood but also that MCI patients 'at risk' from AD could be predicted up to 2 years earlier than conventional clinical diagnosis. Blood-based metabolite profiling of plasma from memory clinic patients is a novel and feasible approach in improving MCI and AD diagnosis and, refining clinical trials through better patient stratification.
Resumo:
Aim: Substantial evidence links atherosclerosis and Alzheimer's disease (AD). Apolipoproteins, such as apolipoprotein E, have a causal relationship with both diseases. The rs11136000 SNP within the CLU gene, which encodes clusterin (apolipoprotein J), is also associated with increased AD risk. The aim of this study was to investigate the relationship between plasma clusterin and the rs11136000 genotype in mild cognitive impairment (MCI) and AD.
Methods: Plasma and DNA samples were collected from control, MCI and AD subjects (n=142, 111, 154, respectively). Plasma clusterin was determined by ELISA and DNA samples were genotyped for rs11136000 by TaqMan assay.
Results: Plasma clusterin levels were higher in MCI and AD subjects vs. controls (222.3 +/- 61.3 and 193.6 +/- 58.2 vs. 178.6 +/- 52.3 mu g/ml, respectively; p
Conclusion: This study examined control, MCI and AD subjects, identifying for the first time that plasma clusterin levels were influenced, not only by the presence of AD, but also the transitional stage of MCI, while rs11136000 genotype only influenced plasma clusterin levels in the control group. The increase in plasma clusterin in MCI and AD subjects may occur in response to the disease process and would be predicted to increase binding capacity for amyloid-beta peptides in plasma, enhancing their removal from the brain.
Resumo:
L’objectif principal de cette thèse est d’examiner et d’intervenir auprès des déficits de la mémoire de travail (MdeT) à l’intérieur de deux populations cliniques : la maladie d’Alzheimer (MA) et le trouble cognitif léger (TCL). La thèse se compose de trois articles empiriques. Le but de la première expérimentation était d’examiner les déficits de MdeT dans le vieillissement normal, le TCL et la MA à l’aide de deux versions de l’empan complexe : l’empan de phrases et l’empan arithmétique. De plus, l’effet de «l’oubli» (forgetting) a été mesuré en manipulant la longueur de l’intervalle de rétention. Les résultats aux tâches d’empan complexe indiquent que la MdeT est déficitaire chez les individus atteints de TCL et encore plus chez les gens ayant la MA. Les données recueillies supportent également le rôle de l’oubli à l’intérieur de la MdeT. L’augmentation de l’intervalle de rétention exacerbait le déficit dans la MA et permettait de prédire un pronostic négatif dans le TCL. L’objectif de la deuxième étude était d’examiner la faisabilité d’un programme d’entraînement cognitif à l’ordinateur pour la composante de contrôle attentionnel à l’intérieur de la MdeT. Cette étude a été réalisée auprès de personnes âgées saines et de personnes âgées avec TCL. Les données de cette expérimentation ont révélé des effets positifs de l’entraînement pour les deux groupes de personnes. Toutefois, l’absence d’un groupe contrôle a limité l’interprétation des résultats. Sur la base de ces données, la troisième expérimentation visait à implémenter une étude randomisée à double-insu avec groupe contrôle d’un entraînement du contrôle attentionnel chez des personnes TCL avec atteinte exécutive. Ce protocole impliquait un paradigme de double-tâche composé d’une tâche de détection visuelle et d’une tâche de jugement alpha-arithmétique. Alors que le groupe contrôle pratiquait simplement la double-tâche sur six périodes d’une heure chacune, le groupe expérimental recevait un entraînement de type priorité variable dans lequel les participants devaient gérer leur contrôle attentionnel en variant la proportion de ressources attentionnelles allouée à chaque tâche. Les résultats montrent un effet significatif de l’intervention sur une des deux tâches impliquées (précision à la tâche de détection visuelle) ainsi qu’une tendance au transfert à une autre tâche d’attention divisée, mais peu d’effets de généralisation à d’autres tâches d’attention. En résumé, les données originales rapportées dans la présente thèse démontrent un déficit de la MdeT dans les maladies neurodégénératives liées à l’âge, avec un gradient entre le TCL et la MA. Elles suggèrent également une préservation de la plasticité des capacités attentionnelles chez les personnes à risque de développer une démence.
Resumo:
Previous research demonstrates that dementia of the Alzheimer type (DAT) is characterised by deficits of episodic memory, especially in the acquisition of new material. As well as this deficit in acquisition, some researchers have also argued for a deficit in consolidation in DAT. We examined acquisition and consolidation by measuring the intertrial gained and lost access in DAT, Mild Cognitive Impairment (MCI) and controls. We report findings from a study of clinical data based on assessment of patients using three free recall trials of a word list. We found that both DAT and MCI groups showed a deficit in acquisition and consolidation of items between trials relative to controls. Moreover, the DAT group was significantly impaired relative to the MCI group for both acquisition and consolidation. Correlations within each group showed that there were strong relationships between intertrial measures and standard measures of memory function. Importantly in no group was there a significant correlation between our measures of acquisition and consolidation: we argue that these measures reflect different underlying processes, and the failure to consolidate in DAT and MCI is not related to the deficit in acquisition. Finally, we showed strong correlations between our measure and dementia severity, suggesting that acquisition and consolidation both get worse as the dementia progresses.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)