337 research outputs found
Genetic & Environmental risk factors for Obsessive-Compulsive Symptoms: Do they affect the same brain?
Genetic & Environmental risk factors for Obsessive-Compulsive Symptoms: Do they affect the same brain?
Geus, J.C.N. [Promotor]de Boomsma, D.I. [Promotor]Ent, D. van 't [Copromotor
The effect of a subcutaneous silicone rubber implant with shallow surface microgrooves on the surrounding tissues in rabbits
In vivo tau pathology is associated with synaptic loss and altered synaptic function
BACKGROUND: The mechanism of synaptic loss in Alzheimer’s disease is poorly understood and may be associated with tau pathology. In this combined positron emission tomography (PET) and magnetoencephalography (MEG) study, we aimed to investigate spatial associations between regional tau pathology ([{18}^F]flortaucipir PET), synaptic density (synaptic vesicle 2A [11C]UCB-J PET) and synaptic function (MEG) in Alzheimer’s disease. METHODS: Seven amyloid-positive Alzheimer’s disease subjects from the Amsterdam Dementia Cohort underwent dynamic 130-minV [{18}^F]flortaucipir PET, dynamic 60-min [{11}^C]UCB-J PET with arterial sampling and 2 × 5-min resting-state MEG measurement. [{18^}F]flortaucipir- and [{11}^C]UCB-J-specific binding (binding potential, BPND) and MEG spectral measures (relative delta, theta and alpha power; broadband power; and peak frequency) were assessed in cortical brain regions of interest. Associations between regional [{18}^F]flortaucipir BPND, [{11}^C]UCB-J BP_{ND} and MEG spectral measures were assessed using Spearman correlations and generalized estimating equation models. RESULTS: Across subjects, higher regional [{18}^F]flortaucipir uptake was associated with lower [{11}^C]UCB-J uptake. Within subjects, the association between [{11}^C]UCB-J and [{18}^F]flortaucipir depended on within-subject neocortical tau load; negative associations were observed when neocortical tau load was high, gradually changing into opposite patterns with decreasing neocortical tau burden. Both higher [{18}^F]flortaucipir and lower [{11}^C]UCB-J uptake were associated with altered synaptic function, indicative of slowing of oscillatory activity, most pronounced in the occipital lobe. CONCLUSIONS: These results indicate that in Alzheimer’s disease, tau pathology is closely associated with reduced synaptic density and synaptic dysfunction
Amyloid-driven disruption of default mode network connectivity in cognitively healthy individuals
Cortical accumulation of amyloid beta is one of the first events of Alzheimer's disease pathophysiology, and has been suggested to follow a consistent spatiotemporal ordering, starting in the posterior cingulate cortex, precuneus and medio-orbitofrontal cortex. These regions overlap with those of the default mode network, a brain network also involved in memory functions. Aberrant default mode network functional connectivity and higher network sparsity have been reported in prodromal and clinical Alzheimer's disease. We investigated the association between amyloid burden and default mode network connectivity in the preclinical stage of Alzheimer's disease and its association with longitudinal memory decline. We included 173 participants, in which amyloid burden was assessed both in CSF by the amyloid beta 42/40 ratio, capturing the soluble part of amyloid pathology, and in dynamic PET scans calculating the non-displaceable binding potential in early-stage regions. The default mode network was identified with resting-state functional MRI. Then, we calculated functional connectivity in the default mode network, derived from independent component analysis, and eigenvector centrality, a graph measure recursively defining important nodes on the base of their connection with other important nodes. Memory was tested at baseline, 2- and 4-year follow-up. We demonstrated that higher amyloid burden as measured by both CSF amyloid beta 42/40 ratio and non-displaceable binding potential in the posterior cingulate cortex was associated with lower functional connectivity in the default mode network. The association between amyloid burden (CSF and non-displaceable binding potential in the posterior cingulate cortex) and aberrant default mode network connectivity was confirmed at the voxel level with both functional connectivity and eigenvector centrality measures, and it was driven by voxel clusters localized in the precuneus, cingulate, angular and left middle temporal gyri. Moreover, we demonstrated that functional connectivity in the default mode network predicts longitudinal memory decline synergistically with regional amyloid burden, as measured by non-displaceable binding potential in the posterior cingulate cortex. Taken together, these results suggest that early amyloid beta deposition is associated with aberrant default mode network connectivity in cognitively healthy individuals and that default mode network connectivity markers can be used to identify subjects at risk of memory decline
Accelerated in vivo proliferation of memory phenotype CD4+ T-cells in human HIV-1 infection irrespective of viral chemokine co-receptor tropism.
CD4(+) T-cell loss is the hallmark of HIV-1 infection. CD4 counts fall more rapidly in advanced disease when CCR5-tropic viral strains tend to be replaced by X4-tropic viruses. We hypothesized: (i) that the early dominance of CCR5-tropic viruses results from faster turnover rates of CCR5(+) cells, and (ii) that X4-tropic strains exert greater pathogenicity by preferentially increasing turnover rates within the CXCR4(+) compartment. To test these hypotheses we measured in vivo turnover rates of CD4(+) T-cell subpopulations sorted by chemokine receptor expression, using in vivo deuterium-glucose labeling. Deuterium enrichment was modeled to derive in vivo proliferation (p) and disappearance (d*) rates which were related to viral tropism data. 13 healthy controls and 13 treatment-naive HIV-1-infected subjects (CD4 143-569 cells/ul) participated. CCR5-expression defined a CD4(+) subpopulation of predominantly CD45R0(+) memory cells with accelerated in vivo proliferation (p = 2.50 vs 1.60%/d, CCR5(+) vs CCR5(-); healthy controls; P<0.01). Conversely, CXCR4 expression defined CD4(+) T-cells (predominantly CD45RA(+) naive cells) with low turnover rates. The dominant effect of HIV infection was accelerated turnover of CCR5(+)CD45R0(+)CD4(+) memory T-cells (p = 5.16 vs 2.50%/d, HIV vs controls; P<0.05), naïve cells being relatively unaffected. Similar patterns were observed whether the dominant circulating HIV-1 strain was R5-tropic (n = 9) or X4-tropic (n = 4). Although numbers were small, X4-tropic viruses did not appear to specifically drive turnover of CXCR4-expressing cells (p = 0.54 vs 0.72 vs 0.44%/d in control, R5-tropic, and X4-tropic groups respectively). Our data are most consistent with models in which CD4(+) T-cell loss is primarily driven by non-specific immune activation
Retinal and Cerebral Microvasculopathy: Relationships and Their Genetic Contributions
PURPOSE: Retinal microvasculopathy may reflect small vessel disease in the brain. Here we test
the relationships between retinal vascular parameters and small vessel disease, the influence
of cardiovascular risk factors on these relationships, and their common genetic background in
a monozygotic twin cohort.
METHODS: We selected 134 cognitively healthy individuals (67 monozygotic twin pairs) aged
‡60 years from the Netherlands Twin Register for the EMIF-AD PreclinAD study. We measured
seven retinal vascular parameters averaged over both eyes using fundus images analyzed with
Singapore I Vessel Assessment. Small vessel disease was assessed on MRI by a volumetric
measurement of periventricular and deep white matter hyperintensities. We calculated
associations between RVPs and WMH, estimated intratwin pair correlations, and performed
twin-specific analyses on relationships of interest.
RESULTS: Deep white matter hyperintensities volume was positively associated with retinal
tortuosity in veins (P ¼ 0.004) and fractal dimension in arteries (P ¼ 0.001) and veins (P ¼
0.032), periventricular white matter hyperintensities volume was positively associated with
retinal venous width (P ¼ 0.028). Intratwin pair correlations were moderate to high for all
small vessel disease/retinal vascular parameter variables (r ¼ 0.49–0.87, P < 0.001). Crosstwin
cross-trait analyses showed that retinal venous tortuosity of twin 1 could predict deep
white matter hyperintensities volume of the co-twin (r ¼ 0.23, P ¼ 0.030). Within twin-pair
differences for retinal venous tortuosity were associated with within twin-pair differences in
deep white matter hyperintensities volume (r ¼ 0.39, P ¼ 0.001).
CONCLUSIONS: Retinal arterial fractal dimension and venous tortuosity have associations with
deep white matter hyperintensities volume. Twin-specific analyses suggest that retinal venous
tortuosity and deep white matter hyperintensities volume have a common etiology driven by
both shared genetic factors and unique environmental factors, supporting the robustness of
this relationship
Brain activation during cognitive planning in twins discordant or concordant for obsessive–compulsive symptoms
Neuroimaging studies have indicated abnormalities in cortico-striatal-thalamo-cortical circuits in patients with obsessive–compulsive disorder compared with controls. However, there are inconsistencies between studies regarding the exact set of brain structures involved and the direction of anatomical and functional changes. These inconsistencies may reflect the differential impact of environmental and genetic risk factors for obsessive–compulsive disorder on different parts of the brain. To distinguish between functional brain changes underlying environmentally and genetically mediated obsessive–compulsive disorder, we compared task performance and brain activation during a Tower of London planning paradigm in monozygotic twins discordant (n = 38) or concordant (n = 100) for obsessive–compulsive symptoms. Twins who score high on obsessive–compulsive symptoms can be considered at high risk for obsessive–compulsive disorder. We found that subjects at high risk for obsessive–compulsive disorder did not differ from the low-risk subjects behaviourally, but we obtained evidence that the high-risk subjects differed from the low-risk subjects in the patterns of brain activation accompanying task execution. These regions can be separated into those that were affected by mainly environmental risk (dorsolateral prefrontal cortex and lingual cortex), genetic risk (frontopolar cortex, inferior frontal cortex, globus pallidus and caudate nucleus) and regions affected by both environmental and genetic risk factors (cingulate cortex, premotor cortex and parts of the parietal cortex). Our results suggest that neurobiological changes related to obsessive–compulsive symptoms induced by environmental factors involve primarily the dorsolateral prefrontal cortex, whereas neurobiological changes induced by genetic factors involve orbitofrontal–basal ganglia structures. Regions showing similar changes in high-risk twins from discordant and concordant pairs may be part of compensatory networks that keep planning performance intact, in spite of cortico-striatal-thalamo-cortical deficits
Performance of a [18F]Flortaucipir PET Visual Read Method Across the Alzheimer Disease Continuum and in Dementia With Lewy Bodies
Background and Objectives:
Recently, the US Food and Drug Administration approved the tau-binding radiotracer [18F]flortaucipir and an accompanying visual read method to support the diagnostic process in cognitively impaired patients assessed for Alzheimer disease (AD). Studies evaluating this visual read method are limited. In this study, we evaluated the performance of the visual read method in participants along the AD continuum and dementia with Lewy bodies (DLB) by determining its reliability, accordance with semiquantitative analyses, and associations with clinically relevant variables.
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Methods:
We included participants who underwent tau-PET at Amsterdam University Medical Center. A subset underwent follow-up tau-PET. Two trained nuclear medicine physicians visually assessed all scans. Inter-reader agreement was calculated using Cohen κ. To examine the concordance of visual read tau positivity with semiquantification, we defined standardized uptake value ratio (SUVr) positivity using different threshold approaches. To evaluate the prognostic value of tau-PET visual read, we performed linear mixed models with longitudinal Mini-Mental State Examination (MMSE).
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Results:
We included 263 participants (mean age 68.5 years, 45.6% female), including 147 cognitively unimpaired (CU) participants, 97 amyloid-positive participants with mild cognitive impairment or AD dementia (AD), and 19 participants with DLB. The visual read inter-reader agreement was excellent (κ = 0.95, CI 0.91–0.99). None of the amyloid-negative CU participants (0/92 [0%]) and 1 amyloid-negative participant with DLB (1/12 [8.3%]) were tau-positive. Among amyloid-positive participants, 13 CU participants (13/52 [25.0%]), 85 with AD (85/97 [87.6%]), and 3 with DLB (3/7 [42.9%]) were tau-positive. Two-year follow-up visual read status was identical to baseline. Tau-PET visual read corresponded strongly to SUVr status, with up to 90.4% concordance. Visual read tau positivity was associated with a decline on the MMSE in CU participants (β = −0.52, CI −0.74 to −0.30, p < 0.001) and participants with AD (β = −0.30, CI −0.58 to −0.02, p = 0.04).
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Discussion:
The excellent inter-reader agreement, strong correspondence with SUVr, and longitudinal stability indicate that the visual read method is reliable and robust, supporting clinical application. Furthermore, visual read tau positivity was associated with prospective cognitive decline, highlighting its additional prognostic potential. Future studies in unselected cohorts are needed for a better generalizability to the clinical population.
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Classification of Evidence:
This study provides Class II evidence that [18F]flortaucipir visual read accurately distinguishes patients with low tau-tracer binding from those with high tau-tracer binding and is associated with amyloid positivity and cognitive decline.
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Glossary:
Aβ=β-amyloid; AD=Alzheimer disease; CU=cognitively unimpaired; DLB=dementia with Lewy bodies; US FDA=US Food and Drug Administration; GMM=Gaussian mixture model; LMM=linear mixed model; MCI=mild cognitive impairment; MMSE=Mini-Mental State Examination; OR=odds ratio; ROI=region of interest; SCD=subjective cognitive decline; SUVr=standardized uptake value ratio
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