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

BioTrust. Ein interdisziplinaeres Projekt zur Foerderung biometrischer Identifizierungsverfahren Abschlussberichte Bd. 1 und 2

Published in two volumesAvailable from TIB Hannover: F03B182: F03B183 / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEBundesministerium fuer Bildung und Forschung, Berlin (Germany); DLR Deutsches Zentrum fuer Luft- und Raumfahrt e.V., Koeln (Germany)DEGerman

In vivo imaging of CT26 mouse tumours by using cmHsp70.1 monoclonal antibody.

The major stress-inducible heat shock protein 70 (Hsp70) is frequently present on the cell surface of human tumors, but not on normal cells. Herein, the binding characteristics of the cmHsp70.1 mouse monoclonal antibody (mAb) were evaluated in vitro and in a syngeneic tumor mouse model. More than 50% of the CT26 mouse colon carcinoma cells express Hsp70 on their cell surface at 4 degrees C. After a temperature shift to 37 degrees C, the cmHsp70.1-FITC mAb translocates into early endosomes and lysosomes Intraoperative and near-infrared fluorescence (NIRF) imaging revealed an enrichment of Cy5.5-conjugated mAb cmHsp70.1, but not an identically labelled IgG1 isotype-matched control, in i.p. and s.c. located CT26 tumors, as soon as 30min after i.v. injection into the tail vein. Due to the rapid turnover rate of membrane-bound Hsp70, the fluorescence-labelled cmHsp70.1 mAb became endocytosed and accumulated in the tumor, reaching a maximum after 24h and remained detectable at least up to 96h after a single i.v. injection. The tumor-selective internalization of mAb cmHsp70.1 at the physiological temperature of 37 degrees C might enable a targeted uptake of toxins or radionuclides into Hsp70 membrane-positive tumors. The anti-tumoral activity of the cmHsp70.1 mAb is further supported by its capacity to mediate antibody dependent cytotoxicity (ADCC)

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 het-erogeneity 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).</p