Alzheimer's disease: progress in prediction.

Alzheimer's Disease Research Center, Mayo Clinic College of Medicine, Rochester, MN, USA.
The Lancet Neurology (Impact Factor: 21.82). 01/2010; 9(1):4-5. DOI: 10.1016/S1474-4422(09)70330-8
Source: PubMed
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    ABSTRACT: Objective. Current diagnostic guidelines encourage further research for the development of novel Alzheimer's disease (AD) biomarkers, especially in its prodromal form (i.e. mild cognitive impairment, MCI). Magnetoencephalography (MEG) can provide essential information about AD brain dynamics; however, only a few studies have addressed the characterization of MEG in incipient AD. Approach. We analyzed MEG rhythms from 36 AD patients, 18 MCI subjects and 27 controls, introducing a new wavelet-based parameter to quantify their dynamical properties: the wavelet turbulence. Main results. Our results suggest that AD progression elicits statistically significant regional-dependent patterns of abnormalities in the neural activity (p < 0.05), including a progressive loss of irregularity, variability, symmetry and Gaussianity. Furthermore, the highest accuracies to discriminate AD and MCI subjects from controls were 79.4% and 68.9%, whereas, in the three-class setting, the accuracy reached 67.9%. Significance. Our findings provide an original description of several dynamical properties of neural activity in early AD and offer preliminary evidence that the proposed methodology is a promising tool for assessing brain changes at different stages of dementia.
    Journal of Neural Engineering 03/2014; 11(2):026010. DOI:10.1088/1741-2560/11/2/026010
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    ABSTRACT: Background This study examined the predictive value of different classes of markers in the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) over an extended 4-year follow-up in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Methods MCI patients were assessed for clinical, cognitive, magnetic resonance imaging (MRI), positron emission tomography–fluorodeoxyglucose (PET-FDG), and cerebrospinal fluid (CSF) markers at baseline and were followed on a yearly basis for 4 years to ascertain progression to AD. Logistic regression models were fitted in clusters, including demographics, APOE genotype, cognitive markers, and biomarkers (morphometric, PET-FDG, CSF, amyloid-β, and tau). Results The predictive model at 4 years revealed that two cognitive measures, an episodic memory measure and a Clock Drawing screening test, were the best predictors of conversion (area under the curve = 0.78). Conclusions This model of prediction is consistent with the previous model at 2 years, thus highlighting the importance of cognitive measures in progression from MCI to AD. Cognitive markers were more robust predictors than biomarkers.
    Alzheimer's & dementia: the journal of the Alzheimer's Association 11/2014; 10(6). DOI:10.1016/j.jalz.2013.11.009
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    ABSTRACT: Background The Parelsnoer Institute is a collaboration between 8 Dutch University Medical Centers in which clinical data and biomaterials from patients suffering from chronic diseases (so called ¿Pearls¿) are collected according to harmonized protocols. The Pearl Neurodegenerative Diseases focuses on the role of biomarkers in the early diagnosis, differential diagnosis and in monitoring the course of neurodegenerative diseases, in particular Alzheimer¿s disease.The objective of this paper is to describe the design and methods of the Pearl Neurodegenerative Diseases, as well as baseline descriptive variables, including their biomarker profile.Methods The Pearl Neurodegenerative Diseases is a 3-year follow-up study of patients referred to a memory clinic with cognitive complaints. At baseline, all patients are subjected to a standardized examination, including clinical data and biobank materials, e.g. blood samples, MRI and cerebrospinal fluid.ResultsAt present, in total more than 1000 patients have been included, of which cerebrospinal fluid and DNA samples are available of 211 and 661 patients, respectively. First descriptives of a subsample of the data (n¿=¿665) shows that patients are diagnosed with dementia (45%), mild cognitive impairment (31%), and subjective memory complaints (24%).DiscussionThe Pearl Neurodegenerative Diseases is an ongoing large network collecting clinical data and biomaterials of more than 1000 patients with cognitive impairments. The project has started with data analyses of the baseline characteristics and biomarkers, which will be the starting point of future specific research questions that can be answered by this unique dataset.
    BMC Neurology 12/2014; 14(1):1060. DOI:10.1186/s12883-014-0254-4


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