Risk factors, neuroimaging correlates and prognosis of the motoric cognitive risk syndrome: A population-based comparison with mild cognitive impairment

BACKGROUND AND PURPOSE: This study was undertaken to compare risk factors, neuroimaging characteristics and prognosis between two clinical prodromes of dementia, namely, the motoric cognitive risk syndrome (MCRS) and mild cognitive impairment (MCI). METHODS: Between 2009 and 2015, dementia-free participants of the population-based Rotterdam Study were classified with a dementia prodrome if they had subjective cognitive complaints and scored >1 SD below the population mean of gait speed (MCRS) or >1.5 SD below the population mean of cognitive test scores (MCI). Using multinomial logistic regression models, we determined cross-sectional associations of risk factors and structural neuroimaging markers with MCRS and MCI, followed by subdistribution hazard models, to determine risk of incident dementia until 2016. RESULTS: Of 3025 included participants (mean age = 70.4 years, 54.7% women), 231 had MCRS (7.6%), 132 had MCI (4.4%), and 62 (2.0%) fulfilled criteria for both. Although many risk factors were shared, a higher body mass index predisposed to MCRS, whereas male sex and hypercholesterolemia were associated with MCI only. Gray matter volumes, hippocampal volumes, white matter hyperintensities, and structural white matter integrity were worse in both MCRS and MCI. During a mean follow-up of 3.9 years, 71 individuals developed dementia and 200 died. Five-year cumulative risk of dementia was 7.0% (2.5%-11.5%) for individuals with MCRS, versus 13.3% (5.8%-20.8%) with MCI and only 2.3% (1.5%-3.1%) in unaffected individuals. CONCLUSIONS: MCRS is associated with imaging markers of neurodegeneration and risk of dementia, even in the absence of MCI, highlighting the potential of motor function assessment in early risk stratification for dementia

The mediating role of the venules between smoking and ischemic stroke

Contains fulltext : 200463.pdf (Publisher’s version ) (Open Access)A potential mechanism by which smoking affects ischemic stroke is through wider venules, but this mediating role of wider venules has never been quantified. Here, we aimed to estimate to what extent the effect of smoking on ischemic stroke is possibly mediated by the venules via the recently developed four-way effect decomposition. This study was part of a population-based study including 9109 stroke-free persons participated in the study in 1990, 2004, or 2006 (mean age: 63.7 years; 58% women). Smoking behavior (smoking versus non-smoking) was identified by interview. Retinal venular calibers were measured semi-automatically on retinal photographs. Incident strokes were assessed until January 2016. A regression-based approach was used with venular calibers as mediator to decompose the total effect of smoking compared to non-smoking into four components: controlled direct effect (neither mediation nor interaction), pure indirect effect (mediation only), reference interaction effect (interaction only) and mediated interaction effect (both mediation and interaction). During a mean follow-up of 12.5 years, 665 persons suffered an ischemic stroke. Smoking increased the risk of developing ischemic stroke compared to non-smoking with an excess risk of 0.41 (95% confidence interval 0.10; 0.67). With retinal venules as a potential mediator, the excess relative risk could be decomposed into 77% controlled direct effect, 4% mediation only, 4% interaction only, and 15% mediated interaction. To conclude, in the pathophysiology of ischemic stroke, the effect of smoking on ischemic stroke may partly explained by changes in the venules, where there is both pure mediation and mediated interaction

Broadening the scope of epidemiologic dementia research

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Association of Retinal Neurodegeneration on Optical Coherence Tomography With Dementia A Population-Based Study

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Weighting training images by maximizing distribution similarity for supervised segmentation across scanners

Many automatic segmentation methods are based on supervised machine learning. Such methods have proven to perform well, on the condition that they are trained on a sufficiently large manually labeled training set that is representative of the images to segment. However, due to differences between scanners, scanning parameters, and patients such a training set may be difficult to obtain. We present a transfer-learning approach to segmentation by multi-feature voxelwise classification. The presented method can be trained using a heterogeneous set of training images that may be obtained with different scanners than the target image. In our approach each training image is given a weight based on the distribution of its voxels in the feature space. These image weights are chosen as to minimize the difference between the weighted probability density function (PDF) of the voxels of the training images and the PDF of the voxels of the target image. The voxels and weights of the training images are then used to train a weighted classifier. We tested our method on three segmentation tasks: brain-tissue segmentation, skull stripping, and white-matter-lesion segmentation. For all three applications, the proposed weighted classifier significantly outperformed an unweighted classifier on all training images, reducing classification errors by up to 42%. For brain-tissue segmentation and skull stripping our method even significantly outperformed the traditional approach of training on representative training images from the same study as the target image. (C) 2015 Elsevier B.V. All rights reserved

[Prion diseases in The Netherlands: twenty-nine years of surveillance]

Prion diseases are being monitored in The Netherlands since 29 years, the national registry is coordinated by Erasmus Medical Center. Since 2010, yearly on average 31 new patients are diagnosed with prion disease. There is a slight increase in incidence of prion diseases, probably due to better recognition and improved diagnostics. The most recent development in the diagnostic is the real-time quaking-induced conversion (RT-QuIC) test, which can detect prion proteins in cerebrospinal fluid with high sensitivity and specificity. The polymorphism of codon 129 of the prion gene (PRNP) determines the susceptibility for the different subtypes of Creutzfeldt-Jakob disease (CJD) and influences the clinical course. Awareness for atypical presentations of CJD and for CJD mimics is important, such as autoimmune encephalitis, which is often treatable and can resemble CJD

Inflammatory markers and the risk of dementia and Alzheimer's disease: A meta-analysis

Item does not contain fulltextINTRODUCTION: Inflammatory markers are often elevated in patients with dementia, including Alzheimer's disease (AD). However, it remains unclear whether inflammatory markers are associated with the risk of developing dementia. METHODS: We searched PubMed, Embase, and Cochrane library for prospective population-based studies reporting associations between inflammatory markers and all-cause dementia or AD. We used random effects meta-analyses to obtain pooled hazard ratios (HRs) and 95% confidence intervals of inflammatory markers (highest vs. lowest quantile) for all-cause dementia and AD. RESULTS: Fifteen articles from 13 studies in six countries reported data that could be meta-analyzed. C-reactive protein (HR = 1.37 [1.05; 1.78]), interleukin-6 (HR = 1.40 [1.13; 1.73]), alpha1-antichymotrypsin (HR = 1.54 [1.14; 2.80]), lipoprotein-associated phospholipase A2 activity (HR = 1.40 [1.03; 1.90]), and fibrinogen were each associated with all-cause dementia, but neither was significantly associated with AD. DISCUSSION: Several inflammatory markers are associated with an increased risk of all-cause dementia; however, these markers are not specific for AD. Whether inflammatory markers closely involved in AD pathology are associated with the risk of AD remains to be elucidated

Thinner retinal layers are associated with changes in the visual pathway: A population-based study

Item does not contain fulltextIncreasing evidence shows that thinner retinal nerve fiber layer (RNFL) and ganglion cell layer (GCL), assessed on optical coherence tomography (OCT), are reflecting global brain atrophy. Yet, little is known on the relation of these layers with specific brain regions. Using voxel-based analysis, we aimed to unravel specific brain regions associated with these retinal layers. We included 2,235 persons (mean age: 67.3 years, 55% women) from the Rotterdam Study (2007-2012) who had gradable retinal OCT images and brain magnetic resonance imaging (MRI) scans, including diffusion tensor (DT) imaging. Thicknesses of peripapillary RNFL and perimacular GCL were measured using an automated segmentation algorithm. Voxel-based morphometry protocols were applied to process DT-MRI data. We investigated the association between retinal layer thickness with voxel-wise gray matter density and white matter microstructure by performing linear regression models. We found that thinner RNFL and GCL were associated with lower gray matter density in the visual cortex, and with lower fractional anisotropy and higher mean diffusivity in white matter tracts that are part of the optic radiation. Furthermore, thinner GCL was associated with lower gray matter density of the thalamus. Thinner RNFL and GCL are associated with gray and white matter changes in the visual pathway suggesting that retinal thinning on OCT may be specifically associated with changes in the visual pathway rather than with changes in the global brain. These findings may serve as a basis for understanding visual symptoms in elderly patients, patients with Alzheimer's disease, or patients with posterior cortical atrophy