Article

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: 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.
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    ABSTRACT: Objective Cerebrospinal fluid (CSF) neurofilament light chain (NfL) concentration is elevated in neurological disorders including frontotemporal degeneration (FTD). We investigated the clinical correlates of elevated CSF NfL levels in FTD. Methods CSF NfL, amyloid-β42 (Aβ42), tau and phosphorylated tau (ptau) concentrations were compared in 47 normal controls (NC), 8 asymptomatic gene carriers (NC2) of FTD-causing mutations, 79 FTD (45 behavioral variant frontotemporal dementia [bvFTD], 18 progressive nonfluent aphasia [PNFA], 16 semantic dementia [SD]), 22 progressive supranuclear palsy, 50 Alzheimer's disease, 6 Parkinson's disease and 17 corticobasal syndrome patients. Correlations between CSF analyte levels were performed with neuropsychological measures and the Clinical Dementia Rating scale sum of boxes (CDRsb). Voxel-based morphometry of structural MR images determined the relationship between brain volume and CSF NfL. Results Mean CSF NfL concentrations were higher in bvFTD, SD and PNFA than other groups. NfL in NC2 was similar to NC. CSF NfL, but not other CSF measures, correlated with CDRsb and neuropsychological measures in FTD, and not in other diagnostic groups. Analyses in two independent FTD cohorts and a group of autopsy verified or biomarker enriched cases confirmed the larger group analysis. In FTD, gray and white matter volume negatively correlated with CSF NfL concentration, such that individuals with highest NfL levels exhibited the most atrophy. Interpretation CSF NfL is elevated in symptomatic FTD and correlates with disease severity. This measurement may be a useful surrogate endpoint of disease severity in FTD clinical trials. Longitudinal studies of CSF NfL in FTD are warranted. ANN NEUROL 2013. © 2013 American Neurological Association.
    Annals of Neurology 11/2013; · 11.91 Impact Factor
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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; · 14.48 Impact Factor

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