Grey matter volume and cortical structure in Prader-Willi syndrome compared to typically developing young adults.

Prader-Willi syndrome (PWS) is a neurodevelopmental disorder of genomic imprinting, presenting with a characteristic overeating disorder, mild to moderate intellectual disability, and a variable range of social and behavioral difficulties. Consequently, widespread alterations in neural structure and developmental and maturational trajectory would be expected. To date, there have been few quantitative and systematic studies of brain morphology in PWS, although alterations of volume and of cortical organisation have been reported. This study aimed to investigate, in detail, the structure of grey matter and cortex in the brain in a sample of young adults with PWS in a well-matched case-controlled analysis. 20 young adults with PWS, aged 19-27 years, underwent multiparameter mapping magnetic resonance imaging sequences, from which measures of grey matter volume, cortical thickness and magnetisation transfer saturation, as a proxy measure of myelination, were examined. These variables were investigated in comparison to a control group of 40 typically developing young adults, matched for age and sex. A voxel-based morphometry analysis identified large and widespread bilateral clusters of both increased and decreased grey matter volume in the brain in PWS. In particular, widespread areas of increased volume encompassed parts of the prefrontal cortex, especially medially, the majority of the cingulate cortices, from anterior to posterior aspects, insula cortices, and areas of the parietal and temporal cortices. Increased volume was also reported in the caudate, putamen and thalamus. The most ventromedial prefrontal areas, in contrast, showed reduced volume, as did the parts of the medial temporal lobe, bilateral temporal poles, and a small cluster in the right lateral prefrontal cortex. Analysis of cortical structure revealed that areas of increased volume in the PWS group were largely driven by greater cortical thickness. Conversely, analysis of myelin content using magnetisation transfer saturation indicated that myelination of the cortex was broadly similar in the PWS and control groups, with the exception of highly localised areas, including the insula. The bilateral nature of these abnormalities suggests a systemic biological cause, with possible developmental and maturational mechanisms discussed, and may offer insight into the contribution of imprinted genes to neural development

Intensity-based image registration using multiple distributed agents

Image registration is the process of geometrically aligning images taken from different sensors, viewpoints or instances in time. It plays a key role in the detection of defects or anomalies for automated visual inspection. A multiagent distributed blackboard system has been developed for intensity-based image registration. The images are divided into segments and allocated to agents on separate processors, allowing parallel computation of a similarity metric that measures the degree of likeness between reference and sensed images after the application of a transform. The need for a dedicated control module is removed by coordination of agents via the blackboard. Tests show that additional agents increase speed, provided the communication capacity of the blackboard is not saturated. The success of the approach in achieving registration, despite significant misalignment of the original images, is demonstrated in the detection of manufacturing defects on screen-printed plastic bottles and printed circuit boards

Brain structural signatures of negative symptoms in depression and schizophrenia.

Negative symptoms occur in several major mental health disorders with undetermined mechanisms and unsatisfactory treatments; identification of their neural correlates might unveil the underlying pathophysiological basis and pinpoint the therapeutic targets. In this study, participants with major depressive disorder (n = 24), schizophrenia (n = 22), and healthy controls (n = 20) were assessed with 10 frequently used negative symptom scales followed by principal component analysis (PCA) of the scores. A linear model with the prominent components identified by PCA was then regressed on gray and white-matter volumes estimated from T1-weighted magnetic resonance imaging. In depressed patients, negative symptoms such as blunted affect, alogia, withdrawal, and cognitive impairment, assessed mostly via clinician-rated scales were inversely associated with gray matter volume in the bilateral cerebellum. In patients with schizophrenia, anhedonia, and avolition evaluated via self-rated scales inversely related to white-matter volume in the left anterior limb of internal capsule/anterior thalamic radiation and positively in the left superior longitudinal fasiculus. The pathophysiological mechanisms underlying negative symptoms might differ between depression and schizophrenia. These results also point to future negative symptom scale development primarily focused on detecting and monitoring the corresponding changes to brain structure or function.This work was supported by Brain and Behavior Research Foundation (NARSAD) and Medical Research Council (MRC) awards to GKM, and by the Wellcome Trust/MRC Behavioural and Clinical Neuroscience Institute, University of Cambridge. We thank Dr. Zheng Ye for her help with image analysis and technical support, Niels Reinders and staff at the Wolfson Brain Imaging Centre for help with data collection, and staff at IAPT, CAMEO and the Rehabilitation and Recovery Service in the Cambridgeshire and Peterborough NHS Foundation Trust for help with recruitment. The study was supported by infrastructure provided by the Wellcome Trust/MRC Behavioural and Clinical Neuroscience Institute at the University of Cambridge.This is the final version published by Frontiers here: http://journal.frontiersin.org/Journal/10.3389/fpsyt.2014.00116/abstract

Reduced cardiovascular morbidity in patients with hemophilia:results of a 5-year multinational prospective study

Hemophilia is a congenital bleeding disorder caused by low levels of clotting factor VIII or IX. The life expectancy of people with hemophilia (PWH) has increased with the availability of clotting factor concentrates. At the same time, the incidence of cardiovascular disease (CVD) has increased; in retrospective studies, there are conflicting data regarding if, despite this increase, the incidence is still lower than in the general population. We prospectively compared the incidence of CVD in PWH vs the predicted incidence. This prospective, multicenter, observational study included adult PWH (aged &gt;30 years) from The Netherlands and United Kingdom. They were followed up for a 5-year period, and CVD incidence was compared with a predicted event rate based on the QRISK2-2011 CVD risk model. The primary end point was the observed fatal and nonfatal CVD incidence after 5 years compared with the estimated events and in relation to severity of hemophilia. The study included 709 patients, of whom 687 (96.9%) completed 5 years' follow-up or reached an end point. For 108 patients, the QRISK score could not be calculated at inclusion. For the remaining 579, fewer CVD events were observed than predicted: 9 vs 24 (relative risk, 0.38; 95% confidence interval, 0.18-0.80; P 5 .01), corresponding with an absolute risk reduction of 2.4%. Severe hemophilia treated on demand had the highest risk reduction. There was no statistically significant relation between severity of hemophilia and incidence of CVD. In hemophilia, a lower-than-predicted CVD incidence was found, supporting the theory that hemophilia protects against CVD. The study is registered at www.clinicaltrials.gov as #NCT01303900.</p

Semi-Metric Topology of the Human Connectome: Sensitivity and Specificity to Autism and Major Depressive Disorder.

INTRODUCTION: The human functional connectome is a graphical representation, consisting of nodes connected by edges, of the inter-relationships of blood oxygenation-level dependent (BOLD) time-series measured by MRI from regions encompassing the cerebral cortices and, often, the cerebellum. Semi-metric analysis of the weighted, undirected connectome distinguishes an edge as either direct (metric), such that there is no alternative path that is accumulatively stronger, or indirect (semi-metric), where one or more alternative paths exist that have greater strength than the direct edge. The sensitivity and specificity of this method of analysis is illustrated by two case-control analyses with independent, matched groups of adolescents with autism spectrum conditions (ASC) and major depressive disorder (MDD). RESULTS: Significance differences in the global percentage of semi-metric edges was observed in both groups, with increases in ASC and decreases in MDD relative to controls. Furthermore, MDD was associated with regional differences in left frontal and temporal lobes, the right limbic system and cerebellum. In contrast, ASC had a broadly increased percentage of semi-metric edges with a more generalised distribution of effects and some areas of reduction. In summary, MDD was characterised by localised, large reductions in the percentage of semi-metric edges, whilst ASC is characterised by more generalised, subtle increases. These differences were corroborated in greater detail by inspection of the semi-metric backbone for each group; that is, the sub-graph of semi-metric edges present in >90% of participants, and by nodal degree differences in the semi-metric connectome. CONCLUSION: These encouraging results, in what we believe is the first application of semi-metric analysis to neuroimaging data, raise confidence in the methodology as potentially capable of detection and characterisation of a range of neurodevelopmental and psychiatric disorders.This study was funded by the UK Medial Research Council (grants: G0802226 and G0701919), the National Institute for Health Research (NIHR) (grant: 06/05/01) and the Behavioural and Clinical Neuroscience Institute (BCNI), University of Cambridge. The BCNI is jointly funded by the Medical Research Council and the Wellcome Trust. Additional support was received from the NIHR Cambridge Biomedical Research Centre. CCH is supported by a Parke Davis Fellowship from the University of Cambridge and resides at Columbia University.This is the final version of the article. It first appeared from PLOS via http://dx.doi.org/10.1371/journal.pone.013638

Adolescents with current major depressive disorder show dissimilar patterns of age-related differences in ACC and thalamus.

OBJECTIVE: There is little understanding of the neural system abnormalities subserving adolescent major depressive disorder (MDD). In a cross-sectional study we compare currently unipolar depressed with healthy adolescents to determine if group differences in grey matter volume (GMV) were influenced by age and illness severity. METHOD: Structural neuroimaging was performed on 109 adolescents with current MDD and 36 healthy controls, matched for age, gender, and handedness. GMV differences were examined within the anterior cingulate cortex (ACC) and across the whole-brain. The effects of age and self-reported depressive symptoms were also examined in regions showing significant main or interaction effects. RESULTS: Whole-brain voxel based morphometry revealed no significant group differences. At the whole-brain level, both groups showed a main effect of age on GMV, although this effect was more pronounced in controls. Significant group-by-age interactions were noted: A significant regional group-by-age interaction was observed in the ACC. GMV in the ACC showed patterns of age-related differences that were dissimilar between adolescents with MDD and healthy controls. GMV in the thalamus showed an opposite pattern of age-related differences in adolescent patients compared to healthy controls. In patients, GMV in the thalamus, but not the ACC, was inversely related with self-reported depressive symptoms. CONCLUSIONS: The depressed adolescent brain shows dissimilar age-related and symptom-sensitive patterns of GMV differences compared with controls. The thalamus and ACC may comprise neural markers for detecting these effects in youth. Further investigations therefore need to take both age and level of current symptoms into account when disaggregating antecedent neural vulnerabilities for MDD from the effects of MDD on the developing brain.This study was funded by the UK Medial Research Council (grant: G0802226), theNational Institute for Health Research (NIHR) (grant: 06/05/01) and the Behavioural and Clinical Neuroscience Institute (BCNI), University of Cambridge. The BCNI is jointly funded by the Medical Research Council and the Wellcome Trust. Additional support was received from the Cambridge Biomedical Research Centre. CCH is supported by a Parke Davis Fellowship from the University of Cambridge and resides at Columbia University.This is the final published version. It first appeared at: http://www.sciencedirect.com/science/article/pii/S2213158214002046#

Functional network dysconnectivity as a biomarker of treatment resistance in schizophrenia.

Schizophrenia may develop from disruptions in functional connectivity regulated by neurotransmitters such as dopamine and acetylcholine. The modulatory effects of these neurotransmitters might explain how antipsychotics attenuate symptoms of schizophrenia and account for the variable response to antipsychotics observed in clinical practice. Based on the putative mechanisms of antipsychotics and evidence of disrupted connectivity in schizophrenia, we hypothesised that functional network connectivity, as assessed using network-based statistics, would exhibit differences between treatment response subtypes of schizophrenia and healthy controls. Resting-state functional MRI data were obtained from 17 healthy controls as well as individuals with schizophrenia who responded well to first-line atypical antipsychotics (first-line responders; FLR, n=18), had failed at least two trials of antipsychotics but responded to clozapine (treatment-resistant schizophrenia; TRS, n=18), or failed at least two trials of antipsychotics and a trial of clozapine (ultra-treatment-resistant schizophrenia; UTRS, n=16). Data were pre-processed using the Advanced Normalization Toolkit and BrainWavelet Toolbox. Network connectivity was assessed using the Network-Based Statistics toolbox in Matlab. ANOVA revealed a significant difference in functional connectivity between groups that extended between cerebellar and parietal regions to the frontal cortex (p<0.05). Post-hoc t-tests revealed weaker network connectivity in individuals with UTRS compared with healthy controls but no other differences between groups. Results demonstrated distinct differences in functional connectivity between individuals with UTRS and healthy controls. Future work must determine whether these changes occur prior to the onset of treatment and if they can be used to predict resistance to antipsychotics during first-episode psychosis