Healthy Elderly Control Subjects Research Articles

Differential diagnosis of neurodegenerative diseases using an innovative deep learning approach

AbstractBackgroundNeurodegenerative diseases lead to memory disorders and cognitive impairments with major impacts on day‐to‐day function. Early detection of patients is essential for an efficient care approach, and differential diagnosis is essential for determining prognosis and tailoring management. Most research studies compare patients by pairwise comparison methods, but this does not correspond to daily clinical practice, in which clinicians need to distinguish many different possible types of dementia concomitantly. It has been shown that magnetic resonance imaging (MRI) can mark with good accuracy the different types of dementia, such as: Alzheimer’s disease (AD), Frontotemporal dementia (FTD), Parkinson’s disease (PD), dementia with Lewy bodies (DLB). Recently, Deep Learning approaches have started being used although differential diagnosis is still almost ignored. The aim of this study was to develop a Convolution Neural Network (CNN) to classify probable AD, FTD, DLB, PD and healthy elderly control (CN) subjects starting from Diffusion Tensor Imaging (DTI).MethodThe cohort used in this study came from six different initiatives: ADNI1, NIFD2, NACC3, PDBP4, PPMI5 and Newcastle University6,7,8,9. We analysed a total of 108 CN, 110 AD, 135 FTD, 150 DLB, 132 PD. Demographic and neuropsychological characterization is shown in Table 1. The DTI scans were pre‐processed using the FMRIB software library (FSL) with eddy current correction, skull‐stripping and diffusion tensor calculation. We post‐processed the Fractional Anisotropy (FA) map using 3D CNN. The proposed CNN structure consisted of an image input layer, convolutional filters, several batch normalization with max‐pooling layers and, finally, the classification layer. A data augmentation approach was adopted that ultimately resulted in a dataset of 26’450 brain scans. A hold‐out validation (70% training set 30% test set) was performed.ResultWe found excellent performance of the 3D CNN in discriminating the different neurodegenerative diseases. Figure 1 shows the confusion matrix with the following values for the area under the ROC curve in each class: 0.92 for CN, 0.90 for AD, 0.97 for DLB, 0.96 for FTD, 0.99 for PD.ConclusionThese results prove that Deep Learning and the 3D CCN method are suitable for clinical practice and provide additional clues that can help clinicians in diagnosis making.

Temporal Irreversibility of Large-Scale Brain Dynamics in Alzheimer's Disease.

Healthy brain dynamics can be understood as the emergence of a complex system far from thermodynamic equilibrium. Brain dynamics are temporally irreversible and thus establish a preferred direction in time (i.e., arrow of time). However, little is known about how the time-reversal symmetry of spontaneous brain activity is affected by Alzheimer's disease (AD). We hypothesized that the level of irreversibility would be compromised in AD, signaling a fundamental shift in the collective properties of brain activity toward equilibrium dynamics. We investigated the irreversibility from resting-state fMRI and EEG data in male and female human patients with AD and elderly healthy control subjects (HCs). We quantified the level of irreversibility and, thus, proximity to nonequilibrium dynamics by comparing forward and backward time series through time-shifted correlations. AD was associated with a breakdown of temporal irreversibility at the global, local, and network levels, and at multiple oscillatory frequency bands. At the local level, temporoparietal and frontal regions were affected by AD. The limbic, frontoparietal, default mode, and salience networks were the most compromised at the network level. The temporal reversibility was associated with cognitive decline in AD and gray matter volume in HCs. The irreversibility of brain dynamics provided higher accuracy and more distinctive information than classical neurocognitive measures when differentiating AD from control subjects. Findings were validated using an out-of-sample cohort. Present results offer new evidence regarding pathophysiological links between the entropy generation rate of brain dynamics and the clinical presentation of AD, opening new avenues for dementia characterization at different levels.SIGNIFICANCE STATEMENT By assessing the irreversibility of large-scale dynamics across multiple brain signals, we provide a precise signature capable of distinguishing Alzheimer's disease (AD) at the global, local, and network levels and different oscillatory regimes. Irreversibility of limbic, frontoparietal, default-mode, and salience networks was the most compromised by AD compared with more sensory-motor networks. Moreover, the time-irreversibility properties associated with cognitive decline and atrophy outperformed and complemented classical neurocognitive markers of AD in predictive classification performance. Findings were generalized and replicated with an out-of-sample validation procedure. We provide novel multilevel evidence of reduced irreversibility in AD brain dynamics that has the potential to open new avenues for understating neurodegeneration in terms of the temporal asymmetry of brain dynamics.

Alteration of the Individual Metabolic Network of the Brain Based on Jensen-Shannon Divergence Similarity Estimation in Elderly Patients With Type 2 Diabetes Mellitus.

The aim of this study was to investigate the interactive effect between aging and type 2 diabetes mellitus (T2DM) on brain glucose metabolism, individual metabolic connectivity, and network properties. Using a 2 × 2 factorial design, 83 patients with T2DM (40 elderly and 43 middle-aged) and 69 sex-matched healthy control subjects (HCs) (34 elderly and 35 middle-aged) underwent 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance scanning. Jensen-Shannon divergence was applied to construct individual metabolic connectivity and networks. The topological properties of the networks were quantified using graph theoretical analysis. The general linear model was used to mainly estimate the interaction effect between aging and T2DM on glucose metabolism, metabolic connectivity, and network. There was an interaction effect between aging and T2DM on glucose metabolism, metabolic connectivity, and regional metabolic network properties (all P < 0.05). The post hoc analyses showed that compared with elderly HCs and middle-aged patients with T2DM, elderly patients with T2DM had decreased glucose metabolism, increased metabolic connectivity, and regional metabolic network properties in cognition-related brain regions (all P < 0.05). Age and fasting plasma glucose had negative correlations with glucose metabolism and positive correlations with metabolic connectivity. Elderly patients with T2DM had glucose hypometabolism, strengthened functional integration, and increased efficiency of information communication mainly located in cognition-related brain regions. Metabolic connectivity pattern changes might be compensatory changes for glucose hypometabolism.

In vivo microstructural heterogeneity of white matter lesions in healthy elderly and Alzheimer's disease participants using tissue compositional analysis of diffusion MRI data

White matter hyperintensities (WMH) are regions of high signal intensity typically identified on fluid attenuated inversion recovery (FLAIR). Although commonly observed in elderly individuals, they are more prevalent in Alzheimer’s disease (AD) patients. Given that WMH appear relatively homogeneous on FLAIR, they are commonly partitioned into location- or distance-based classes when investigating their relevance to disease. Since pathology indicates that such lesions are often heterogeneous, probing their microstructure in vivo may provide greater insight than relying on such arbitrary classification schemes. In this study, we investigated WMH in vivo using an advanced diffusion MRI method known as single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD), which models white matter microstructure while accounting for grey matter and CSF compartments. Diffusion MRI data and FLAIR images were obtained from AD (n = 48) and healthy elderly control (n = 94) subjects. WMH were automatically segmented, and classified: (1) as either periventricular or deep; or (2) into three distance-based contours from the ventricles. The 3-tissue profile of WMH enabled their characterisation in terms of white matter-, grey matter-, and fluid-like characteristics of the diffusion signal. Our SS3T-CSD findings revealed substantial heterogeneity in the 3-tissue profile of WMH, both within lesions and across the various classes. Moreover, this heterogeneity information indicated that the use of different commonly used WMH classification schemes can result in different disease-based conclusions. We conclude that future studies of WMH in AD would benefit from inclusion of microstructural information when characterising lesions, which we demonstrate can be performed in vivo using SS3T-CSD.

The applause sign in frontotemporal lobar degeneration and related conditions

The applause sign, i.e., the inability to execute the same amount of claps as performed by the examiner, was originally reported as a sign specific for progressive supranuclear palsy (PSP). Recent research, however, has provided evidence for the occurrence of the applause sign in various conditions. The aim of this study was to determine the prevalence of the applause sign and correlate its presence with neuropsychological and MRI volumetry findings in frontotemporal lobar degeneration and related conditions. The applause sign was elicited with the three clap test (TCT), with a higher score indicating poorer performance. Data were recorded from 272 patients from the cohort of the German consortium for frontotemporal lobar degeneration (FTLDc): 111 with behavioral variant frontotemporal dementia (bvFTD), 98 with primary progressive aphasia (PPA), 30 with progressive supranuclear palsy Richardson's syndrome, 17 with corticobasal syndrome (CBS) and 16 with amyotrophic lateral sclerosis with frontotemporal dementia (ALS/FTD). For comparison, 29 healthy elderly control subjects (HC) were enrolled in the study. All subjects underwent detailed language and neuropsychological assessment. In a subset of 156 subjects, atlas-based volumetry was performed. The applause sign occurred in all patient groups (40% in PSP, 29.5% in CBS, 25% in ALS/FTD, 13.3% in PPA and 9.0% in bvFTD) but not in healthy controls. The prevalence was highest in PSP patients. It was significantly more common in PSP as compared to bvFTD, PPA and HC. The comparison between the other groups failed to show a significant difference regarding the occurrence of the applause sign. The applause sign was highly correlated to a number of neuropsychological findings, especially to measures of executive, visuospatial, and language function as well as measures of disease severity. TCT scores showed an inverse correlation with the volume of the ventral diencephalon and the pallidum. Furthermore the volume of the ventral diencephalon and pallidum were significantly smaller in patients displaying the applause sign. Our study confirms the occurrence of the applause sign in bvFTD, PSP and CBS and adds PPA and ALS/FTD to these conditions. Although still suggestive of PSP, clinically it must be interpreted with caution. From the correlation with various cognitive measures we suggest the applause sign to be indicative of disease severity. Furthermore we suggest that the applause sign represents dysfunction of the pallidum and the subthalamic nucleus, structures which are known to play important roles in response inhibition.

Functional Disconnectivity during Inter-Task Resting State in Dementia with Lewy Bodies

Aims: Limited research has been done on the functional connectivity in visuoperceptual regions in dementia with Lewy bodies (DLB) patients. This study aimed to investigate the functional connectivity differences between a task condition and an inter-task resting state condition within a visuoperceptual paradigm, in DLB patients compared with Alzheimer disease (AD) patients and healthy elderly control subjects. Methods: Twenty-six DLB, 29 AD, and 22 healthy subjects underwent a detailed clinical and neuropsychological examination along with a functional MRI during the different conditions of a visuoperceptual paradigm. Functional images were analyzed using group-level spatial independent component analysis and seed-based connectivity analyses. Results: While the DLB patients scored well and did not differ from the control and AD groups in terms of functional activity and connectivity during the task conditions, they showed decreased functional connectivity in visuoperceptual regions during the resting state condition, along with a temporal impairment of the default-mode network activity. Functional connectivity disturbances were also found within two attentional-executive networks and between these networks and visuoperceptual regions. Conclusion: We found a specific functional profile in the switching between task and resting state conditions in DLB patients. This result could help better characterize functional impairments in DLB and their contribution to several core symptoms of this pathology such as visual hallucinations and cognitive fluctuations.

Abstract 21: Motor Tract Impairment is an Independent Predictor of Lower Limb Motor Recovery

Introduction: Initial motor impairment assessed in the acute stroke phase (as measured by the Fugl-Meyer (FM) Assessment) is a strong predictor of lower extremity (LE) motor impairment at 3 months (Smith et al., 2017). The predictive value of measures of motor tract integrity, lesion size and location is not known. For our analysis we combined two motor tracts that might be particularly important in the control of proximal leg muscles to create a canonical tract of the corticospinal tract proper (CST) and the corticorubrospinal tract (CRST)(Lindenberg et al., 2010; Rueber et al., 2012). In previous work (Feng et al., 2015) we have shown that weighted CST-Lesion Load (a combined variable of lesion size and location) is a significant predictor of 3 months outcome for the UE. Hypothesis: Weighted CST-CRST Lesion-Load (wCST/CRST-LL) can improve the FM-based predictions of lower limb motor recovery. Methods: Ischemic stroke patients with a upper limb paresis (UE-FM&lt;66) and lower limb paresis (LE-FM&lt;34) were assessed between 48-72h and 3 months poststroke with the FM scale. Lesion maps drawn on diffusion-weighted images were used to calculate lesion loads of a combined CST-CRST probabilistic tract derived from matched elderly healthy control subjects. Then, several variables that have been shown to predict outcome (e.g., FM, lesion load, age, hemisphere) were subjected to individual regression analyses. Significant variables (at p&lt;0.05) were entered into a multiple regression model to assess predictors of lower limb motor recovery (i.e., actual difference in LE-FM between 3 months and initial stroke phase assessment). Results: Both baseline and 3-months follow-up were available for 134 patients. Initial motor impairment (FM-LE) and wCST/CRST-LL were independent strong predictors of lower limb motor recovery (respectively p&lt;0.0001 and p=0.0005). Combining initial motor impairment and wCST/CRST lesion load was a much better model than FM-LE by itself (respectively R2=0.43 and R2=0.46, p=0.003) which was confirmed by the Akaike Information Criterion (AIC). Conclusion: wCST/CRST-LL, a combined measure of lesion size/location, adds significant power to a combined model with FM, but is also a strong predictor of lower limb motor recovery by itself.

Abstract WP146: Predictors of Recovery From Acute Aphasia

Introduction: Making accurate predictions about a stroke patient’s language/speech-motor outcome and recovery potential is a challenge. We previously showed that a combined variable of lesion site and size pertinent to relevant white matter language structures, the Arcuate Fasciculus lesion load (AF-LL), correlated highly with measures of speech fluency in chronic aphasic patients (Marchina et al., 2011; Wang et al., 2013). However, studies in motor recovery and other domains have shown that behavioral measures in the acute stroke phase might be equal or better predictors of recovery compared to lesion measures. Whether or not any of these measures follow a proportional recovery rule, has not been established. Hypothesis: To evaluate whether acute aphasia measures (overall WAB score) and/or acute lesion measures (e.g., AF-Lesion Load) predict recovery from aphasia. Methods: Over a period of several years, patients presenting with acute aphasia were evaluated using a bedside version of the Western Aphasia Battery complemented by picture naming tests, automatic speech measures, and custom-made word/phrase spoken and sung test. A total of 100 acute patients were assessed of which 56 followed up at 3 months. Lesion maps drawn on diffusion-weighted images were used to calculate lesion loads of a probabilistic Arcuate Fasciculus (AF) tract derived from matched elderly healthy control subjects. Analyses included correlations between recovery potential and actual recovery and other predictors of 3 months outcome. AF-LL was regressed with the overall WAB score, measures of speech fluency and naming ability (using the Boston Naming Test). Results: The overall bedside WAB score in the acute stroke period was the best predictor of the overall WAB score at 3 months (R2=0.60). This predictor was slightly improved when a measure of speaking-singing dissociation was added to the model. Lesion-load of the AF was also a good predictor of WAB score at 3 months (R2=0.48), but did not improve outcome predictions of the WAB score by itself. Overall acute aphasic patients followed a proportional recovery rule, but only recovered about 56% of what was theoretically possible. Conclusion: Language and Speech-Motor Outcome after stroke can be predicted best by a bedside WAB score.

Fibre-specific white matter reductions in Alzheimer's disease and mild cognitive impairment.

Alzheimer's disease is increasingly considered a large-scale network disconnection syndrome, associated with progressive aggregation of pathological proteins, cortical atrophy, and functional disconnections between brain regions. These pathological changes are posited to arise in a stereotypical spatiotemporal manner, targeting intrinsic networks in the brain, most notably the default mode network. While this network-specific disruption has been thoroughly studied with functional neuroimaging, changes to specific white matter fibre pathways within the brain's structural networks have not been closely investigated, largely due to the challenges of modelling complex white matter structure. Here, we applied a novel technique known as 'fixel-based analysis' to comprehensively investigate fibre tract-specific differences at a within-voxel level (called 'fixels') to assess potential axonal loss in subjects with Alzheimer's disease and mild cognitive impairment. We hypothesized that patients with Alzheimer's disease would exhibit extensive degeneration across key fibre pathways connecting default network nodes, while patients with mild cognitive impairment would exhibit selective degeneration within fibre pathways connecting regions previously identified as functionally implicated early in Alzheimer's disease. Diffusion MRI data from Alzheimer's disease (n = 49), mild cognitive impairment (n = 33), and healthy elderly control subjects (n = 95) were obtained from the Australian Imaging, Biomarkers and Lifestyle study of ageing. We assessed microstructural differences in fibre density, and macrostructural differences in fibre bundle morphology using fixel-based analysis. Whole-brain analysis was performed to compare groups across all white matter fixels. Subsequently, we performed a tract of interest analysis comparing fibre density and cross-section across 11 selected white matter tracts, to investigate potentially subtle degeneration within fibre pathways in mild cognitive impairment, initially by clinical diagnosis alone, and then by including amyloid status (i.e. a positive or negative amyloid PET scan). Our whole-brain analysis revealed significant white matter loss manifesting both microstructurally and macrostructurally in Alzheimer's disease patients, evident in specific fibre pathways associated with default mode network nodes. Reductions in fibre density and cross-section in mild cognitive impairment patients were only exhibited within the posterior cingulum when statistical analyses were limited to tracts of interest. Interestingly, these degenerative changes did not appear to be associated with high amyloid accumulation, given that amyloid-negative, but not positive, mild cognitive impairment subjects exhibited subtle focal left posterior cingulum deficits. The findings of this study demonstrated a stereotypical distribution of white matter degeneration in patients with Alzheimer's disease, which was in line with canonical findings from other imaging modalities, and with a network-based conceptualization of the disease.awx355media15726254535001.

Early Prediction of Alzheimer's Disease Using Null Longitudinal Model-Based Classifiers.

Incipient Alzheimer’s Disease (AD) is characterized by a slow onset of clinical symptoms, with pathological brain changes starting several years earlier. Consequently, it is necessary to first understand and differentiate age-related changes in brain regions in the absence of disease, and then to support early and accurate AD diagnosis. However, there is poor understanding of the initial stage of AD; seemingly healthy elderly brains lose matter in regions related to AD, but similar changes can also be found in non-demented subjects having mild cognitive impairment (MCI). By using a Linear Mixed Effects approach, we modelled the change of 166 Magnetic Resonance Imaging (MRI)-based biomarkers available at a 5-year follow up on healthy elderly control (HC, n = 46) subjects. We hypothesized that, by identifying their significant variant (vr) and quasi-variant (qvr) brain regions over time, it would be possible to obtain an age-based null model, which would characterize their normal atrophy and growth patterns as well as the correlation between these two regions. By using the null model on those subjects who had been clinically diagnosed as HC (n = 161), MCI (n = 209) and AD (n = 331), normal age-related changes were estimated and deviation scores (residuals) from the observed MRI-based biomarkers were computed. Subject classification, as well as the early prediction of conversion to MCI and AD, were addressed through residual-based Support Vector Machines (SVM) modelling. We found reductions in most cortical volumes and thicknesses (with evident gender differences) as well as in sub-cortical regions, including greater atrophy in the hippocampus. The average accuracies (ACC) recorded for men and women were: AD-HC: 94.11%, MCI-HC: 83.77% and MCI converted to AD (cAD)-MCI non-converter (sMCI): 76.72%. Likewise, as compared to standard clinical diagnosis methods, SVM classifiers predicted the conversion of cAD to be 1.9 years earlier for females (ACC:72.5%) and 1.4 years earlier for males (ACC:69.0%).

A multinational study distinguishing Alzheimer's and healthy patients using cerebrospinal fluid tau/Aβ42 cutoff with concordance to amyloid positron emission tomography imaging

IntroductionChanges in cerebrospinal fluid (CSF) tau and amyloid β (Aβ)42 accompany development of Alzheimer's brain pathology. Robust tau and Aβ42 immunoassays were developed to establish a tau/Aβ42 cutoff distinguishing mild-to-moderate Alzheimer's disease (AD) subjects from healthy elderly control (HC) subjects. MethodsA CSF tau/Aβ42 cutoff criteria was chosen, which distinguished the groups and maximized concordance with amyloid PET. Performance was assessed using an independent validation cohort. ResultsA tau/Aβ42 = 0.215 cutoff provided 94.8% sensitivity and 77.7% specificity. Concordance with PET visual reads was estimated at 86.9% in a ∼50% PET positive population. In the validation cohort, the cutoff demonstrated 78.4% sensitivity and 84.9% specificity to distinguish the AD and HC populations. DiscussionA tau/Aβ42 cutoff with acceptable sensitivity and specificity distinguished HC from mild-to-moderate AD subjects and maximized concordance to brain amyloidosis. The defined cutoff demonstrated that CSF analysis may be useful as a surrogate to imaging assessment of AD pathology.

Positron emission tomography measurement of brain MAO-B inhibition in patients with Alzheimer\u2019s disease and elderly controls after oral administration of sembragiline

PurposeIn Alzheimer’s disease (AD), increased metabolism of monoamines by monoamine oxidase type B (MAO-B) leads to the production of toxic reactive oxygen species (ROS), which are thought to contribute to disease pathogenesis. Inhibition of the MAO-B enzyme may restore brain levels of monoaminergic neurotransmitters, reduce the formation of toxic ROS and reduce neuroinflammation (reactive astrocytosis), potentially leading to neuroprotection. Sembragiline (also referred as RO4602522, RG1577 and EVT 302 in previous communications) is a potent, selective and reversible inhibitor of MAO-B developed as a potential treatment for AD.MethodsThis study assessed the relationship between plasma concentration of sembragiline and brain MAO-B inhibition in patients with AD and in healthy elderly control (EC) subjects. Positron emission tomography (PET) scans using [11C]-L-deprenyl-D2 radiotracer were performed in ten patients with AD and six EC subjects, who received sembragiline each day for 6–15 days.ResultsAt steady state, the relationship between sembragiline plasma concentration and MAO-B inhibition resulted in an Emax of ∼80–90 % across brain regions of interest and in an EC50 of 1–2 ng/mL. Data in patients with AD and EC subjects showed that near-maximal inhibition of brain MAO-B was achieved with 1 mg sembragiline daily, regardless of the population, whereas lower doses resulted in lower and variable brain MAO-B inhibition.ConclusionsThis PET study confirmed that daily treatment of at least 1 mg sembragiline resulted in near-maximal inhibition of brain MAO-B enzyme in patients with AD.

Cognitive and affective theory of mind in dementia with Lewy bodies and Alzheimer's disease.

BackgroundTheory of mind (ToM) refers to the ability to attribute mental states, thoughts (cognitive component) or feelings (affective component) to others. This function has been studied in many neurodegenerative diseases; however, to our knowledge, no studies investigating ToM in dementia with Lewy bodies (DLB) have been published. The aim of our study was to assess ToM in patients with DLB and to search for neural correlates of potential deficits.MethodsThirty-three patients with DLB (DLB group) and 15 patients with Alzheimer’s disease (AD group), all in the early stage of the disease, as well as 16 healthy elderly control subjects (HC group), were included in the study. After a global cognitive assessment, we used the Faux Pas Recognition (FPR) test, the Reading the Mind in the Eyes (RME) test and Ekman’s Facial Emotion Recognition test to assess cognitive and affective components of ToM. Patients underwent cerebral 3-T magnetic resonance imaging, and atrophy of grey matter was analysed using voxel-based morphometry. We performed a one-sample t test to investigate the correlation between each ToM score and grey matter volume and a two-sample t test to compare patients with DLB impaired with those non-impaired for each test.ResultsThe DLB group performed significantly worse than the HC group on the FPR test (P = 0.033) and the RME test (P = 0.015). There was no significant difference between the AD group and the HC group or between the DLB group and the AD group. Some brain regions were associated with ToM impairments. The prefrontal cortex, with the inferior frontal cortex and the orbitofrontal cortex, was the main region, but we also found correlations with the temporoparietal junction, the precuneus, the fusiform gyrus and the insula.ConclusionsThis study is the first one to show early impairments of ToM in DLB. The two cognitive and affective components both appear to be affected in this disease. Among patients with ToM difficulties, we found atrophy in brain regions classically involved in ToM, which reinforces the neuronal network of ToM. Further studies are now needed to better understand the neural basis of such impairment.Electronic supplementary materialThe online version of this article (doi:10.1186/s13195-016-0179-9) contains supplementary material, which is available to authorized users.

A new method to quantify tau pathologies with (11)C-PBB3 PET using reference tissue voxels extracted from brain cortical gray matter.

BackgroundQuantitative in vivo imaging of tau pathologies potentially improves diagnostic accuracy of neurodegenerative tauopathies and would facilitate evaluation of disease-modifying drugs targeting tau lesions in these diseases. Tau pathology can be quantified by reference tissue models without arterial blood sampling when reference tissue devoid of target binding sites is available. The cerebellar cortex has been used as a reference region in analyses of tau positron emission tomography (PET) data in Alzheimer’s disease (AD). However, in a significant subset of tauopathies such as progressive supranuclear palsy and corticobasal degeneration, tau accumulation may occur in diverse brain regions including the cerebellar cortex. This hampers selection of a distinctive reference region lacking binding sites for a tau PET ligand. The purpose of this study was to develop a new method to quantify specific binding of a PET radioligand, 11C-PBB3, to tau deposits using reference voxels extracted from cortical gray matter, which have a low likelihood of containing tau accumulations.MethodsWe reanalyzed 11C-PBB3 PET data of seven mild AD patients (ADs) and seven elderly healthy control subjects (HCs) acquired in a previous study. As a standard method, parametric images of binding potential ( {BP}_{mathsf{ND}}^{ast } ) were initially generated using reference tissue manually defined on the cerebellar cortex. We then constructed a frequency histogram of {BP}_{mathsf{ND}}^{ast } values in these parametric images and selected cortical gray matter voxels contained in a certain range of the histogram with a low likelihood of having 11C-PBB3 binding sites. Finally, these reference voxels were used for generating new {BP}_{mathsf{ND}}^{ast } parametric images.ResultsReference tissue voxels defined by the histogram analysis spread throughout the cortical gray matter of AD and HC brains. The {BP}_{mathsf{ND}}^{ast } values determined by our new method correlated very well with those estimated by the standard method (r2 = 0.94), although the binding estimates by the current method were slightly higher by ~0.14 than those by the standard method.ConclusionsWe developed and validated a new method enabling quantification of tau lesions that can accumulate in the cerebellum and other extensive brain areas. This method may be applicable to all tauopathy subtypes and various tau PET ligands besides 11C-PBB3.Trial registrationThe number is UMIN000009052

Comprehensive circular RNA profiling reveals that circular RNA100783 is involved in chronic CD28-associated CD8(+)T cell ageing.

BackgroundAgeing brings about the gradual deterioration of the immune system, also known as immunosenescence. The role of non-coding circular RNA in immunosenescence is under studied. Using circular RNA microarray data, we assembled Comparison groups (C1, C2, C3 and C4) that allowed us to compare the circular RNA expression profiles between CD28(+)CD8(+) T cells and CD28(-)CD8(+) T cells isolated from healthy elderly or adult control subjects. Using a step-wise biomathematical strategy, the differentially-expressed circRNAs were identified in C1 (CD28(+)CD8(+) vs CD28(-)CD8(+)T cells in the elderly) and C4 (CD28(-)CD8(+)T cells in the elderly vs in the adult), and the commonly-expressed circRNA species from these profiles were optimized as immunosenescence biomarkers.ResultsFour overlapping upregulated circular RNAs (100550, 100783, 101328 and 102592) expressed in cross-comparison between C1 and C4 were validated using quantitative polymerase chain reaction. Of these, only circular RNA100783 exhibited significant validation. None of the down-regulated circular RNAs were expressed in the C1 and the C4 cross-comparisons. Therefore, we further predicted circular RNA100783-targeted miRNA-gene interactions using online DAVID annotation. The analysis revealed that a circular RNA100783-targeted miRNA-mRNA network may be involved in alternative splicing, the production of splice variants, and in the regulation of phosphoprotein expression. Considering the hypothesis of splicing-related biogenesis of circRNAs, we propose that circular RNA100783 may play a role in phosphoprotein-associated functions duringCD28-related CD8(+) T cell ageing.ConclusionsThis study is the first to employ circular RNA profiling to investigate circular RNA-micro RNA interactions in ageing human CD8(+)T cell populations and the accompanying loss of CD28 expression. The overlapping expression of circular RNA100783 may represent a novel biomarker for the longitudinal tracking ofCD28-related CD8(+) T cell ageing and global immunosenescence.Electronic supplementary materialThe online version of this article (doi:10.1186/s12979-015-0042-z) contains supplementary material, which is available to authorized users.

Increased genetic risk for obesity in premature coronary artery disease.

There is ongoing controversy as to whether obesity confers risk for CAD independently of associated risk factors including diabetes mellitus. We have carried out a Mendelian randomization study using a genetic risk score (GRS) for body mass index (BMI) based on 35 risk alleles to investigate this question in a population of 5831 early onset CAD cases without diabetes mellitus and 3832 elderly healthy control subjects, all of strictly European ancestry, with adjustment for traditional risk factors (TRFs). We then estimated the genetic correlation between these BMI and CAD (rg) by relating the pairwise genetic similarity matrix to a phenotypic covariance matrix between these two traits. GRSBMI significantly (P=2.12 × 10−12) associated with CAD status in a multivariate model adjusted for TRFs, with a per allele odds ratio (OR) of 1.06 (95% CI 1.042–1.076). The addition of GRSBMI to TRFs explained 0.75% of CAD variance and yielded a continuous net recombination index of 16.54% (95% CI=11.82–21.26%, P<0.0001). To test whether GRSBMI explained CAD status when adjusted for measured BMI, separate models were constructed in which the score and BMI were either included as covariates or not. The addition of BMI explained ~1.9% of CAD variance and GRSBMI plus BMI explained 2.65% of CAD variance. Finally, using bivariate restricted maximum likelihood analysis, we provide strong evidence of genome-wide pleiotropy between obesity and CAD. This analysis supports the hypothesis that obesity is a causal risk factor for CAD.

Regional cerebral blood flow estimated by early PiB uptake is reduced in mild cognitive impairment and associated with age in an amyloid-dependent manner

Early uptake of [11C]-Pittsburgh Compound B (ePiB, 0–6 minutes) estimates cerebral blood flow. We studied ePiB in 13 PiB-negative and 10 PiB-positive subjects with mild cognitive impairment (MCI, n = 23) and 11 PiB-positive and 74 PiB-negative cognitively healthy elderly control subjects (HCS, n = 85) in 6 bilateral volumes of interest: posterior cingulate cortex (PCC), hippocampus (hipp), temporoparietal region, superior parietal gyrus, parahippocampal gyrus (parahipp), and inferior frontal gyrus (IFG) for the associations with cognitive status, age, amyloid deposition, and apolipoprotein E ε4-allele. We observed no difference in ePiB between PiB-positive and -negative subjects and carriers and noncarriers. EPiB decreased with age in PiB-positive subjects in bilateral superior parietal gyrus, bilateral temporoparietal region, right IFG, right PCC, and left parahippocampal gyrus but not in PiB-negative subjects. MCI had lower ePiB than HCS (left PCC, left IFG, and left and right hipp). Lowest ePiB values were found in MCI of 70 years and older, who also displayed high cortical PiB binding. This suggests that lowered regional cerebral blood flow indicated by ePiB is associated with age in the presence but not in the absence of amyloid pathology.

カテゴリー流暢性課題と近赤外光を用いた認知症診断の可能性

Near-Infrared Spectroscopy has become one of the most important measurement tools of the brain's function. In this study we used a Near-Infrared Spectroscopy while performing a category fluency task to diagnose dementia. 50 dementia patients (age 83.3±6.7, 12 male, 38 female, Mini Mental State Examination: 0-22) and 16 health elderly controls (age 80.5±4.6, 2 male, 14 female, Mini Mental State Examination: 24-30) were instructed to produce a noun belonging to the category of vegetables while being scanned by the Near-Infrared Spectroscopy. Our results showed better test results and also a significant larger prefrontal blood volume among the healthy elderly control subjects compared to those subjects previously diagnosed with dementia. This leads us to conclude that the measurement of the prefrontal blood volume using a Near-Infrared Spectroscopy, usually used to diagnose other psychiatric disorders, could also be used as another tool to diagnose dementia.

Alzheimer's disease is associated with altered expression of genes involved in immune response and mitochondrial processes in astrocytes

Alzheimer's disease (AD) is characterized by deficits in cerebral metabolic rates of glucose in the posterior cingulate (PC) and precuneus in AD subjects, and in APOEε4 carriers, decades before the onset of measureable cognitive deficits. However, the cellular and molecular basis of this phenotype remains to be clarified. Given the roles of astrocytes in energy storage and brain immunity, we sought to characterize the transcriptome of AD PC astrocytes. Cells were laser capture microdissected from AD (n = 10) and healthy elderly control (n = 10) subjects for RNA sequencing. We generated >5.22 billion reads and compared sequencing data between controls and AD patients. We identified differentially expressed mitochondria-related genes including TRMT61B, FASTKD2, and NDUFA4L2, and using pathway and weighted gene coexpression analyses, we identified differentially expressed immune response genes. A number of these genes, including CLU, C3, and CD74, have been implicated in beta amyloid generation or clearance. These data provide key insights into astrocyte-specific contributions to AD, and we present this data set as a publicly available resource.

Interest of active posturography to detect age-related and early Parkinson's disease-related impairments in mediolateral postural control.

Patients with Parkinson's disease display impairments of postural control most particularly in active, challenging conditions. The objective of the present study was to analyze early signs of disease-related and also age-related impairments in mediolateral body extension and postural control. Fifty-five participants (18 Hoehn and Yahr stage 2 patients in the off-drug condition, 18 healthy elderly control subjects, and 19 young adults) were included in the study. The participants performed a quiet stance task and two active tasks that analyzed the performance in mediolateral body motion: a limit of stability and a rhythmic weight shift task. As expected, the patients displayed significantly lower and slower body displacement (head, neck, lower back, center of pressure) than elderly control subjects when performing the two body excursion tasks. However, the behavioral variability in both tasks was similar between the groups. Under these active conditions, the patients showed significantly lower contribution of the hip postural control mechanisms compared with the elderly control subjects. Overall, the patients seemed to lower their performance in order to prevent a mediolateral postural instability. However, these patients, at an early stage of their disease, were not unstable in quiet stance. Complementarily, elderly control subjects displayed slower body performance than young adults, which therefore showed an additional age-related impairment in mediolateral postural control. Overall, the study illustrated markers of age-related and Parkinson's disease impairments in mediolateral postural control that may constrain everyday activities in elderly adults and even more in patients with Parkinson's disease.