The relevance of rich club regions for functional outcome post-stroke is enhanced in women

This study aimed to investigate the influence of stroke lesions in predefined highly interconnected (rich-club) brain regions on functional outcome post-stroke, determine their spatial specificity and explore the effects of biological sex on their relevance. We analyzed MRI data recorded at index stroke and similar to 3-months modified Rankin Scale (mRS) data from patients with acute ischemic stroke enrolled in the multisite MRI-GENIE study. Spatially normalized structural stroke lesions were parcellated into 108 atlas-defined bilateral (sub)cortical brain regions. Unfavorable outcome (mRS > 2) was modeled in a Bayesian logistic regression framework. Effects of individual brain regions were captured as two compound effects for (i) six bilateral rich club and (ii) all further non-rich club regions. In spatial specificity analyses, we randomized the split into "rich club" and "non-rich club" regions and compared the effect of the actual rich club regions to the distribution of effects from 1000 combinations of six random regions. In sex-specific analyses, we introduced an additional hierarchical level in our model structure to compare male and female-specific rich club effects. A total of 822 patients (age: 64.7[15.0], 39% women) were analyzed. Rich club regions had substantial relevance in explaining unfavorable functional outcome (mean of posterior distribution: 0.08, area under the curve: 0.8). In particular, the rich club-combination had a higher relevance than 98.4% of random constellations. Rich club regions were substantially more important in explaining long-term outcome in women than in men. All in all, lesions in rich dub regions were associated with increased odds of unfavorable outcome. These effects were spatially specific and more pronounced in women.Peer reviewe

Novel genetic loci associated with hippocampal volume

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg =-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness

Heterogeneity in age-related white matter changes

White matter changes occur endemically in routine magnetic resonance imaging (MRI) scans of elderly persons. MRI appearance and histopathological correlates of white matter changes are heterogeneous. Smooth periventricular hyperintensities, including caps around the ventricular horns, periventricular lining and halos are likely to be of non-vascular origin. They relate to a disruption of the ependymal lining with subependymal widening of the extracellular space and have to be differentiated from subcortical and deep white matter abnormalities. For the latter a distinction needs to be made between punctate, early confluent and confluent types. Although punctate white matter lesions often represent widened perivascular spaces without substantial ischemic tissue damage, early confluent and confluent lesions correspond to incomplete ischemic destruction. Punctate abnormalities on MRI show a low tendency for progression, while early confluent and confluent changes progress rapidly. The causative and modifying pathways involved in the occurrence of sporadic age-related white matter changes are still incompletely understood, but recent microarray and genome-wide association approaches increased the notion of pathways that might be considered as targets for therapeutic intervention. The majority of differentially regulated transcripts in white matter lesions encode genes associated with immune function, cell cycle, proteolysis, and ion transport. Genome-wide association studies identified six SNPs mapping to a locus on chromosome 17q25 to be related to white matter lesion load in the general population. We also report first and preliminary data that demonstrate apolipoprotein E (ApoE) immunoreactivity in white matter lesions and support epidemiological findings indicating that ApoE is another factor possibly related to white matter lesion occurrence. Further insights come from modern MRI techniques, such as diffusion tensor and magnetization transfer imaging, as they provide tools for the characterization of normal-appearing brain tissue beyond what can be expected from standard MRI scans. There is a need for additional pre- and postmortem studies in humans, including these new imaging techniques

Data from: Cerebral white matter lesions and affective episodes correlate in male individuals with bipolar disorder

Background: Cerebral white matter lesions (WML) have been found in normal aging, vascular disease and several neuropsychiatric conditions. Correlations of WML with clinical parameters in BD have been described, but not with the number of affective episodes, illness duration, age of onset and Body Mass Index in a well characterized group of euthymic bipolar adults. Herein, we aimed to evaluate the associations between bipolar course of illness parameters and WML measured with volumetric analysis. Methods: In a cross-sectional study 100 euthymic individuals with BD as well as 54 healthy controls (HC) were enrolled to undergo brain magnetic resonance imaging using 3T including a FLAIR sequence for volumetric assessment of WML-load using FSL-software. Additionally, clinical characteristics and psychometric measures including Structured Clinical Interview according to DSM-IV, Hamilton-Depression, Young Mania Rating Scale and Beck’s Depression Inventory were evaluated. Results: Individuals with BD had significantly more (F = 3.968, p < .05) WML (Mdn = 3710mm3; IQR = 2961mm3) than HC (Mdn = 2185mm3; IQR = 1665mm3). BD men (Mdn = 4095mm3; IQR = 3295mm3) and BD women (Mdn = 3032mm3; IQR = 2816mm3) did not significantly differ as to the WML-load or the number and type of risk factors for WML. However, in men only, the number of manic/hypomanic episodes (r = 0.72; p < .001) as well as depressive episodes (r = 0.51; p < .001) correlated positively with WML-load. Conclusions: WML-load strongly correlated with the number of manic episodes in male BD patients, suggesting that men might be more vulnerable to mania in the context of cerebral white matter changes

Cerebral White Matter Lesions and Affective Episodes Correlate in Male Individuals with Bipolar Disorder.

Cerebral white matter lesions (WML) have been found in normal aging, vascular disease and several neuropsychiatric conditions. Correlations of WML with clinical parameters in BD have been described, but not with the number of affective episodes, illness duration, age of onset and Body Mass Index in a well characterized group of euthymic bipolar adults. Herein, we aimed to evaluate the associations between bipolar course of illness parameters and WML measured with volumetric analysis.In a cross-sectional study 100 euthymic individuals with BD as well as 54 healthy controls (HC) were enrolled to undergo brain magnetic resonance imaging using 3T including a FLAIR sequence for volumetric assessment of WML-load using FSL-software. Additionally, clinical characteristics and psychometric measures including Structured Clinical Interview according to DSM-IV, Hamilton-Depression, Young Mania Rating Scale and Beck's Depression Inventory were evaluated.Individuals with BD had significantly more (F = 3.968, p < .05) WML (Mdn = 3710 mm3; IQR = 2961 mm3) than HC (Mdn = 2185 mm3; IQR = 1665 mm3). BD men (Mdn = 4095 mm3; IQR = 3295 mm3) and BD women (Mdn = 3032 mm3; IQR = 2816 mm3) did not significantly differ as to the WML-load or the number and type of risk factors for WML. However, in men only, the number of manic/hypomanic episodes (r = 0.72; p < .001) as well as depressive episodes (r = 0.51; p < .001) correlated positively with WML-load.WML-load strongly correlated with the number of manic episodes in male BD patients, suggesting that men might be more vulnerable to mania in the context of cerebral white matter changes

data on white matter lesions in bipolar disorder

The data sheet contains all volumetric and demographic variables and that were used for statistical analysis in our study. Data are either continuous or binary. A comprehensive description of variables is given in the file

Performance of five research-domain automated WM lesion segmentation methods in a multi-center MS study

Background and Purpose In vivoidentification of white matter lesions plays a key-role in evaluation of patients with multiple sclerosis (MS). Automated lesion segmentation methods have been developed to substitute manual outlining, but evidence of their performance in multi-center investigations is lacking. In this work, five research-domain automated segmentation methods were evaluated using a multi-center MS dataset. Methods 70 MS patients (median EDSS of 2.0 [range 0.0–6.5]) were included from a six-center dataset of the MAGNIMS Study Group (www.magnims.eu) which included 2D FLAIR and 3D T1 images with manual lesion segmentation as a reference. Automated lesion segmentations were produced using five algorithms: Cascade; Lesion Segmentation Toolbox (LST) with both the Lesion growth algorithm (LGA) and the Lesion prediction algorithm (LPA); Lesion-Topology preserving Anatomical Segmentation (Lesion-TOADS); and k-Nearest Neighbor with Tissue Type Priors (kNN-TTP). Main software parameters were optimized using a training set (N = 18), and formal testing was performed on the remaining patients (N = 52). To evaluate volumetric agreement with the reference segmentations, intraclass correlation coefficient (ICC) as well as mean difference in lesion volumes between the automated and reference segmentations were calculated. The Similarity Index (SI), False Positive (FP) volumes and False Negative (FN) volumes were used to examine spatial agreement. All analyses were repeated using a leave-one-center-out design to exclude the center of interest from the training phase to evaluate the performance of the method on ‘unseen’ center. Results Compared to the reference mean lesion volume (4.85 ± 7.29 mL), the methods displayed a mean difference of 1.60 ± 4.83 (Cascade), 2.31 ± 7.66 (LGA), 0.44 ± 4.68 (LPA), 1.76 ± 4.17 (Lesion-TOADS) and −1.39 ± 4.10 mL (kNN-TTP). The ICCs were 0.755, 0.713, 0.851, 0.806 and 0.723, respectively. Spatial agreement with reference segmentations was higher for LPA (SI = 0.37 ± 0.23), Lesion-TOADS (SI = 0.35 ± 0.18) and kNN-TTP (SI = 0.44 ± 0.14) than for Cascade (SI = 0.26 ± 0.17) or LGA (SI = 0.31 ± 0.23). All methods showed highly similar results when used on data from a center not used in software parameter optimization. Conclusion The performance of the methods in this multi-center MS dataset was moderate, but appeared to be robust even with new datasets from centers not included in training the automated methods

Demographic data.

<p>Note: Results from <i>t</i>-tests (<i>t</i>), Chi square tests (<i>χ2</i>), Mann-Whitney-U-tests (<i>U</i>) and ANCOVA (<i>F</i>)</p><p>(1) For ANCOVA, WML volumes were normalized by individual total intracranial volume and controlled for age, diabetes, smoking and BMI.</p><p>Statistically significant effects are marked bold.</p><p>Demographic data.</p