117 resultados para Enfermedad de alzheimer - Prevención
Resumo:
The relative contributions of Alzheimer disease (AD) and vascular lesion burden to the occurrence of cognitive decline are more difficult to define in the oldest-old than they are in younger cohorts. To address this issue, we examined 93 prospectively documented autopsy cases from 90 to 103 years with various degrees of AD lesions, lacunes, and microvascular pathology. Cognitive assessment was performed prospectively using the Clinical Dementia Rating scale. Neuropathologic evaluation included the Braak neurofibrillary tangle (NFT) and β-amyloid (Aβ) protein deposition staging and bilateral semiquantitative assessment of vascular lesions. Statistics included regression models and receiver operating characteristic analyses. Braak NFTs, Aβ deposition, and cortical microinfarcts (CMIs) predicted 30% of Clinical Dementia Rating variability and 49% of the presence of dementia. Braak NFT and CMI thresholds yielded 0.82 sensitivity, 0.91 specificity, and 0.84 correct classification rates for dementia. Using these threshold values, we could distinguish 3 groups of demented cases and propose criteria for neuropathologic definition of mixed dementia, pure vascular dementia, and AD in very old age. Braak NFT staging and severity of CMI allow for defining most of demented cases in the oldest-old. Most importantly, single cutoff scores for these variables that could be used in the future to formulate neuropathologic criteria for mixed dementia in this age group were identified.
Resumo:
In Alzheimer disease (AD) the involvement of entorhinal cortex, hippocampus, and associative cortical areas is well established. Regarding the involvement of the primary motor cortex the reported data are contradictory. In order to determine whether the primary motor cortex is involved in AD, the brains of 29 autopsy cases were studied, including, 17 cases with severe cortical AD-type changes with definite diagnoses of AD, 7 age-matched cases with discrete to moderate cortical AD-type changes, and 5 control cases without any AD-type cortical changes. Morphometric analysis of the cortical surface occupied by senile plaques (SPs) on beta-amyloid-immunostained sections and quantitative analysis of neurofibrillary tangles (NFTs) on Gallyas-stained sections was performed in 5 different cortical areas including the primary motor cortex. The percentage of cortical surface occupied by SPs was similar in all cortical areas, without significant difference and corresponded to 16.7% in entorhinal cortex, 21.3% in frontal associative, 16% in parietal associative, and 15.8% in primary motor cortex. The number of NFTs in the entorhinal cortex was significantly higher (41 per 0.4 mm2), compared with those in other cortical areas (20.5 in frontal, 17.9 in parietal and 11.5 in the primary motor cortex). Our findings indicate that the primary motor cortex is significantly involved in AD and suggest the appearance of motor dysfunction in late and terminal stages of the disease.
Resumo:
Sens de la mémoire... mémoire du sens chez l'adulte vieillissant - Les ressources adaptatives : de l'anticipation involontaire aux stratégies conscientes - Les ressources adaptatives : l'épreuve du vieillissement - Plasticité et dégénérescence des circuits cérébraux dans le vieillissement et la maladie d'Alzheimer - Facteurs de risque génétiques et mécanismes moléculaires dans la maladie d'Alzheimer - La mort neuronale : mécanismes d'un phénomène naturel ou pathologique - Facteurs de risque et de protection - Vieillissement cérébral pathologique : les pathologies démentielles - Prise en charge globale et thérapies actuelles de la démence de type Alzheimer - Regard anthropologique sur le veillissement cérébral et la maladie d'Alzheimer
Resumo:
In order to understand relationships between executive and structural deficits in the frontal cortex of patients within normal aging or Alzheimer's disease, we studied frontal pathological changes in young and old controls compared to cases with sporadic (AD) or familial Alzheimer's disease (FAD). We performed a semi-automatic computer assisted analysis of the distribution of beta-amyloid (Abeta) deposits revealed by Abeta immunostaining as well as of neurofibrillary tangles (NFT) revealed by Gallyas silver staining in Brodman areas 10 (frontal polar), 12 (ventro-infero-median) and 24 (anterior cingular), using tissue samples from 5 FAD, 6 sporadic AD and 10 control brains. We also performed densitometric measurements of glial fibrillary acidic protein, principal compound of intermediate filaments of astrocytes, and of phosphorylated neurofilament H and M epitopes in areas 10 and 24. All regions studied seem almost completely spared in normal old controls, with only the oldest ones exhibiting a weak percentage of beta-amyloid deposit and hardly any NFT. On the contrary, all AD and FAD cases were severely damaged as shown by statistically significant increased percentages of beta-amyloid deposit, as well as by a high number of NFT. FAD cases (all from the same family) had statistically more beta-amyloid and GFAP than sporadic AD cases in both areas 10 and 24 and statistically more NFT only in area 24. The correlation between the percentage of beta-amyloid and the number of NFT was significant only for area 24. Altogether, these data suggest that the frontal cortex can be spared by AD type lesions in normal aging, but is severely damaged in sporadic and still more in familial Alzheimer's disease. The frontal regions appear to be differentially vulnerable, with area 12 having the less amyloid burden, area 24 the less NFT and area 10 having both more amyloid and more NFT. This pattern of damage in frontal regions may represent a strong neuroanatomical support for the deterioration of attention and cognitive capacities as well as for the presence of emotional and behavioral troubles in AD patients.
Resumo:
Objective: To investigate personality traits in patients with Alzheimer disease, compared with mentally healthy control subjects. We compared both current personality characteristics using structured interviews as well as current and previous personality traits as assessed by proxies.Method: Fifty-four patients with mild Alzheimer disease and 64 control subjects described their personality traits using the Structured Interview for the Five-Factor Model. Family members filled in the Revised NEO Personality Inventory, Form R, to evaluate their proxies' current personality traits, compared with 5 years before the estimated beginning of Alzheimer disease or 5 years before the control subjects.Results: After controlling for age, the Alzheimer disease group presented significantly higher scores than normal control subjects on current neuroticism, and significantly lower scores on current extraversion, openness, and conscientiousness, while no significant difference was observed on agreeableness. A similar profile, though less accentuated, was observed when considering personality traits as the patients' proxies remembered them. Diachronic personality assessment showed again significant differences between the 2 groups for the same 4 domains, with important personality changes only for the Alzheimer disease group.Conclusions: Group comparison and retrospective personality evaluation are convergent. Significant personality changes follow a specific trend in patients with Alzheimer disease and contrast with the stability generally observed in mentally healthy people in their personality profile throughout their lives. Whether or not the personality assessment 5 years before the current status corresponds to an early sign of Alzheimer disease or real premorbid personality differences in people who later develop Alzheimer disease requires longitudinal studies.
Resumo:
Epidemiological and biochemical studies show that the sporadic forms of Alzheimer's disease (AD) are characterized by the following hallmarks: (a) An exponential increase with age; (b) Selective neuronal vulnerability; (c) Inverse cancer comorbidity. The present article appeals to these hallmarks to evaluate and contrast two competing models of AD: the amyloid hypothesis (a neuron-centric mechanism) and the Inverse Warburg hypothesis (a neuron-astrocytic mechanism). We show that these three hallmarks of AD conflict with the amyloid hypothesis, but are consistent with the Inverse Warburg hypothesis, a bioenergetic model which postulates that AD is the result of a cascade of three events-mitochondrial dysregulation, metabolic reprogramming (the Inverse Warburg effect), and natural selection. We also provide an explanation for the failures of the clinical trials based on amyloid immunization, and we propose a new class of therapeutic strategies consistent with the neuroenergetic selection model.
Resumo:
Machine learning and pattern recognition methods have been used to diagnose Alzheimer's disease (AD) and mild cognitive impairment (MCI) from individual MRI scans. Another application of such methods is to predict clinical scores from individual scans. Using relevance vector regression (RVR), we predicted individuals' performances on established tests from their MRI T1 weighted image in two independent data sets. From Mayo Clinic, 73 probable AD patients and 91 cognitively normal (CN) controls completed the Mini-Mental State Examination (MMSE), Dementia Rating Scale (DRS), and Auditory Verbal Learning Test (AVLT) within 3months of their scan. Baseline MRI's from the Alzheimer's disease Neuroimaging Initiative (ADNI) comprised the other data set; 113 AD, 351 MCI, and 122 CN subjects completed the MMSE and Alzheimer's Disease Assessment Scale-Cognitive subtest (ADAS-cog) and 39 AD, 92 MCI, and 32 CN ADNI subjects completed MMSE, ADAS-cog, and AVLT. Predicted and actual clinical scores were highly correlated for the MMSE, DRS, and ADAS-cog tests (P<0.0001). Training with one data set and testing with another demonstrated stability between data sets. DRS, MMSE, and ADAS-Cog correlated better than AVLT with whole brain grey matter changes associated with AD. This result underscores their utility for screening and tracking disease. RVR offers a novel way to measure interactions between structural changes and neuropsychological tests beyond that of univariate methods. In clinical practice, we envision using RVR to aid in diagnosis and predict clinical outcome.
Resumo:
The distribution of parvalbumin (PV), calretinin (CR), and calbindin (CB) immunoreactive neurons was studied with the help of an image analysis system (Vidas/Zeiss) in the primary visual area 17 and associative area 18 (Brodmann) of Alzheimer and control brains. In neither of these areas was there a significant difference between Alzheimer and control groups in the mean number of PV, CR, or CB immunoreactive neuronal profiles, counted in a cortical column going from pia to white matter. Significant differences in the mean densities (numbers per square millimeter of cortex) of PV, CR, and CB immunoreactive neuronal profiles were not observed either between groups or areas, but only between superficial, middle, and deep layers within areas 17 and 18. The optical density of the immunoreactive neuropil was also similar in Alzheimer and controls, correlating with the numerical density of immunoreactive profiles in superficial, middle, and deep layers. The frequency distribution of neuronal areas indicated significant differences between PV, CR, and CB immunoreactive neuronal profiles in both areas 17 and 18, with more large PV than CR and CB positive profiles. There were also significantly more small and less large PV and CR immunoreactive neuronal profiles in Alzheimer than in controls. Our data show that, although the brain pathology is moderate to severe, there is no prominent decrease of PV, CR and CB positive neurons in the visual cortex of Alzheimer brains, but only selective changes in neuronal perikarya.
Resumo:
To be diagnostically useful, structural MRI must reliably distinguish Alzheimer's disease (AD) from normal aging in individual scans. Recent advances in statistical learning theory have led to the application of support vector machines to MRI for detection of a variety of disease states. The aims of this study were to assess how successfully support vector machines assigned individual diagnoses and to determine whether data-sets combined from multiple scanners and different centres could be used to obtain effective classification of scans. We used linear support vector machines to classify the grey matter segment of T1-weighted MR scans from pathologically proven AD patients and cognitively normal elderly individuals obtained from two centres with different scanning equipment. Because the clinical diagnosis of mild AD is difficult we also tested the ability of support vector machines to differentiate control scans from patients without post-mortem confirmation. Finally we sought to use these methods to differentiate scans between patients suffering from AD from those with frontotemporal lobar degeneration. Up to 96% of pathologically verified AD patients were correctly classified using whole brain images. Data from different centres were successfully combined achieving comparable results from the separate analyses. Importantly, data from one centre could be used to train a support vector machine to accurately differentiate AD and normal ageing scans obtained from another centre with different subjects and different scanner equipment. Patients with mild, clinically probable AD and age/sex matched controls were correctly separated in 89% of cases which is compatible with published diagnosis rates in the best clinical centres. This method correctly assigned 89% of patients with post-mortem confirmed diagnosis of either AD or frontotemporal lobar degeneration to their respective group. Our study leads to three conclusions: Firstly, support vector machines successfully separate patients with AD from healthy aging subjects. Secondly, they perform well in the differential diagnosis of two different forms of dementia. Thirdly, the method is robust and can be generalized across different centres. This suggests an important role for computer based diagnostic image analysis for clinical practice.
Resumo:
The aim of this article is a critical review of the main pathogenetic issues debated in Alzheimer disease, with a focus on the clinical perspectives that could derive from. The pertinence of the amyloid cascade hypothesis as a unique and causal explanation of cognitive deterioration is challenged in the light of recent therapeutic failures of clinical trials and increasing role of tau protein in clinical expression. The detection of very early and possibly preclinical stages of the disease emerges as a necessary condition for the efficacy of future amyloid or tau-oriented curative strategies. In this respect, the possibility of finding individual vulnerability markers--in the group of patients with "mild cognitive impairment" or even in cognitively intact subjects--represents a major challenge of the clinical research in this field.
Resumo:
INTRODUCTION: Interindividual variations in regional structural properties covary across the brain, thus forming networks that change as a result of aging and accompanying neurological conditions. The alterations of superficial white matter (SWM) in Alzheimer's disease (AD) are of special interest, since they follow the AD-specific pattern characterized by the strongest neurodegeneration of the medial temporal lobe and association cortices. METHODS: Here, we present an SWM network analysis in comparison with SWM topography based on the myelin content quantified with magnetization transfer ratio (MTR) for 39 areas in each hemisphere in 15 AD patients and 15 controls. The networks are represented by graphs, in which nodes correspond to the areas, and edges denote statistical associations between them. RESULTS: In both groups, the networks were characterized by asymmetrically distributed edges (predominantly in the left hemisphere). The AD-related differences were also leftward. The edges lost due to AD tended to connect nodes in the temporal lobe to other lobes or nodes within or between the latter lobes. The newly gained edges were mostly confined to the temporal and paralimbic regions, which manifest demyelination of SWM already in mild AD. CONCLUSION: This pattern suggests that the AD pathological process coordinates SWM demyelination in the temporal and paralimbic regions, but not elsewhere. A comparison of the MTR maps with MTR-based networks shows that although, in general, the changes in network architecture in AD recapitulate the topography of (de)myelination, some aspects of structural covariance (including the interhemispheric asymmetry of networks) have no immediate reflection in the myelination pattern.