5 research outputs found
Recommended from our members
Association between Psychotic Symptoms and Cortical Thickness Reduction across the Schizophrenia Spectrum
The current study provides a complete MRI analysis of thickness throughout the cerebral cortical mantle in patients with schizophrenia (SZ) and rigorously screened and matched unaffected relatives and controls and an assessment of its relation to psychopathology and subjective cognitive function. We analyzed 3D-anatomical magnetic resonance imaging data sets, obtained at 3 Tesla, from three different subject groups: 25 SZ patients, 29 first-degree relatives and 37 healthy control subjects. We computed whole-brain cortical thickness using the Freesurfer software and assessed group differences. We also acquired clinical and psychometric data. The results showed markedly reduced cortical thickness in SZ patients compared with controls, most notably in the frontal and temporal lobes, in the superior parietal lobe and several limbic areas, with intermediate levels of cortical thickness in relatives. In both patients and relatives, we found an association between subjective cognitive dysfunction and reduced thickness of frontal cortex, and predisposition towards hallucinations and reduced thickness of the superior temporal gyrus. Our findings suggest that changes in specific cortical areas may predispose to specific symptoms, as exemplified by the association between temporal cortex thinning and hallucinations
What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from theENIGMABipolar Disorder Working Group
MRI‐derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta‐Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis‐driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large‐scale meta‐ and mega‐analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large‐scale, collaborative studies of mental illness
Anatomical brain connectivity and positive symptoms of schizophrenia: a diffusion tensor imaging study
Structural brain changes in schizophrenia are well documented in the neuroimaging literature. The classical morphometric analyses of magnetic resonance imaging (MRI) data have recently been supplemented by diffusion tensor imaging (DTI), which mainly assesses changes in white matter (WM). DTI increasingly provides evidence for abnormal anatomical connectivity in schizophrenia, most often using fractional anisotropy (FA) as an indicator of the integrity of WM tracts. To better understand the clinical significance of such anatomical changes, we studied FA values in a whole-brain analysis comparing paranoid schizophrenic patients with a history of auditory hallucinations and matched healthy controls. The relationship of WM changes to psychopathology was assessed by correlating FA values with PANSS scores (positive symptoms and severity of auditory hallucinations) and with illness duration. Schizophrenic patients showed FA reductions indicating WM integrity disturbance in the prefrontal regions, external capsule, pyramidal tract, occipitofrontal fasciculus, superior and inferior longitudinal fasciculi, and corpus callosum. The arcuate fasciculus was the only tract which showed increased FA values in patients. Increased FA values in this region correlated with increased severity of auditory hallucinations and length of illness. Our results suggest that local changes in anatomical integrity of WM tracts in schizophrenia may be related to patients' clinical presentation
Increased power by harmonizing structural MRI site differences with the ComBat batch method in ENIGMA
A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega-analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related heterogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega-analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random-effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning)