Associations of cortical thickness and cognition in patients with schizophrenia and healthy controls

Previous studies have found varying relationships between cognitive functioning and brain volumes in patients with schizophrenia. However, cortical thickness may more closely reflect cytoarchitectural characteristics than gray matter density or volume estimates. Here, we aimed to compare associations between regional variation in cortical thickness and executive functions, memory, as well as verbal and spatial processing in patients with schizophrenia and healthy controls (HCs). We obtained magnetic resonance imaging and neuropsychological data for 131 patients and 138 matched controls. Automated cortical pattern matching methods allowed testing for associations with cortical thickness estimated as the shortest distance between the gray/white matter border and the pial surface at thousands of points across the entire cortical surface. Two independent measures of working memory showed robust associations with cortical thickness in lateral prefrontal cortex in HCs, whereas patients exhibited associations between working memory and cortical thickness in the right middle and superior temporal lobe. This study provides additional evidence for a disrupted structure-function relationship in schizophrenia. In line with the prefrontal inefficiency hypothesis, schizophrenia patients may engage a larger compensatory network of brain regions other than frontal cortex to recall and manipulate verbal material in working memory.     

Spatial source phase: A new feature for identifying spatial differences based on complex‐valued resting‐state fMRI data

Spatial source phase, the phase information of spatial maps extracted from functional magnetic resonance imaging (fMRI) data by data‐driven methods such as independent component analysis (ICA), has rarely been studied. While the observed phase has been shown to convey unique brain information, the role of spatial source phase in representing the intrinsic activity of the brain is yet not clear. This study explores the spatial source phase for identifying spatial differences between patients with schizophrenia (SZs) and healthy controls (HCs) using complex‐valued resting‐state fMRI data from 82 individuals. ICA is first applied to preprocess fMRI data, and post‐ICA phase de‐ambiguity and denoising are then performed. The ability of spatial source phase to characterize spatial differences is examined by the homogeneity of variance test (voxel‐wise F‐test) with false discovery rate correction. Resampling techniques are performed to ensure that the observations are significant and reliable. We focus on two components of interest widely used in analyzing SZs, including the default mode network (DMN) and auditory cortex. Results show that the spatial source phase exhibits more significant variance changes and higher sensitivity to the spatial differences between SZs and HCs in the anterior areas of DMN and the left auditory cortex, compared to the magnitude of spatial activations. Our findings show that the spatial source phase can potentially serve as a new brain imaging biomarker and provide a novel perspective on differences in SZs compared to HCs, consistent with but extending previous work showing increased variability in patient data.     

Specific default mode subnetworks support mentalizing as revealed through opposing network recruitment by social and semantic FMRI tasks

The ability to attribute mental states to others, or “mentalizing,” is posited to involve specific subnetworks within the overall default mode network (DMN), but this question needs clarification. To determine which default mode (DM) subnetworks are engaged by mentalizing processes, we assessed task‐related recruitment of DM subnetworks. Spatial independent component analysis (sICA) applied to fMRI data using relatively high‐order model (75 components). Healthy participants (n = 53, ages 17–60) performed two fMRI tasks: an interactive game involving mentalizing (Domino), a semantic memory task (SORT), and a resting state fMRI scan. sICA of the two tasks split the DMN into 10 subnetworks located in three core regions: medial prefrontal cortex (mPFC; five subnetworks), posterior cingulate/precuneus (PCC/PrC; three subnetworks), and bilateral temporoparietal junction (TPJ). Mentalizing events increased recruitment in five of 10 DM subnetworks, located in all three core DMN regions. In addition, three of these five DM subnetworks, one dmPFC subnetwork, one PCC/PrC subnetwork, and the right TPJ subnetwork, showed reduced recruitment by semantic memory task events. The opposing modulation by the two tasks suggests that these three DM subnetworks are specifically engaged in mentalizing. Our findings, therefore, suggest the unique involvement of mentalizing processes in only three of 10 DM subnetworks, and support the importance of the dmPFC, PCC/PrC, and right TPJ in mentalizing as described in prior studies. Hum Brain Mapp 36:3047–3063, 2015. © 2015 Wiley Periodicals, Inc.     

Artifact removal in the context of group ICA: A comparison of single‐subject and group approaches

Independent component analysis (ICA) has been widely applied to identify intrinsic brain networks from fMRI data. Group ICA computes group‐level components from all data and subsequently estimates individual‐level components to recapture intersubject variability. However, the best approach to handle artifacts, which may vary widely among subjects, is not yet clear. In this work, we study and compare two ICA approaches for artifacts removal. One approach, recommended in recent work by the Human Connectome Project, first performs ICA on individual subject data to remove artifacts, and then applies a group ICA on the cleaned data from all subjects. We refer to this approach as Individual ICA based artifacts Removal Plus Group ICA (IRPG). A second proposed approach, called Group Information Guided ICA (GIG‐ICA), performs ICA on group data, then removes the group‐level artifact components, and finally performs subject‐specific ICAs using the group‐level non‐artifact components as spatial references. We used simulations to evaluate the two approaches with respect to the effects of data quality, data quantity, variable number of sources among subjects, and spatially unique artifacts. Resting‐state test–retest datasets were also employed to investigate the reliability of functional networks. Results from simulations demonstrate GIG‐ICA has greater performance compared with IRPG, even in the case when single‐subject artifacts removal is perfect and when individual subjects have spatially unique artifacts. Experiments using test–retest data suggest that GIG‐ICA provides more reliable functional networks. Based on high estimation accuracy, ease of implementation, and high reliability of functional networks, we find GIG‐ICA to be a promising approach. Hum Brain Mapp 37:1005–1025, 2016. © 2015 Wiley Periodicals, Inc .     

Correlation of P-glycoprotein expression and function in childhood acute leukemia: a children's cancer group study

Clinical drug resistance may be attributed to the simultaneous selection and expression of genes modulating the uptake and metabolism of chemotherapeutic agents. P-glycoprotein (P-gp) functions as a membrane-associated drug efflux pump whose increased expression results in resistance to anthracyclines, epipodophyllotoxins, vinca alkaloids, and some alkylating agents. This type of resistance occurs as both de novo and acquired resistance to therapy for leukemia. We have studied P- gp expression and function in childhood acute leukemias by developing a series of doxorubicin- and vincristine-selected CEM, T-cell lymphoblastoid cell lines that recapitulate the low levels of expression and resistance seen clinically. These cell lines have been used to develop flow cytometric assays for the semiquantitative measurements of P-gp expression with the MRK16 monoclonal antibody and P-gp function using the enhanced retention of rhodamine 123 in the presence of verapamil, a resistance modulator. Kolmogorov-Smirnov statistics, represented by the D measurement, are used to determine the difference in level of P-gp expression by comparing MRK16 staining to an IgG2a isotype control. When D is > 0.09, there is an excellent correlation (R = 0.82) between P-gp expression and function. The evaluation of 107 bone marrow specimens from 84 children with lymphoblastic or myelogenous leukemia showed a statistically significant (P = .004) increase in P-gp function at relapse. P-gp expression at relapse, however, approached but did not reach a significant level (P = .097). Using this methodology, we can identify patients with levels of P-gp expression and function that we can define clinically, as well as children with discordant multidrug resistance phenotypes. This study supports the role of P-gp-mediated drug resistance in childhood leukemia and confirms that P-gp expression and function are measurable in their leukemic blasts. These assays provide the means for the in vitro testing of resistance modulators and the monitoring of in vivo response to treatment with these agents.     

Anti-stigma training and positive changes in mental illness stigma outcomes in medical students in ten countries: a mediation analysis on pathways via empathy development and anxiety reduction

Purpose

Studies of mental illness stigma reduction interventions have been criticised for failing to evaluate behavioural outcomes and mechanisms of action. This project evaluates training for medical students entitled ‘Responding to Experienced and Anticipated Discrimination’ (READ), developed to focus on skills in addition to attitudes and knowledge. We aimed to (i) evaluate the effectiveness of READ with respect to knowledge, attitudes, and clinical communication skills in responding to mental illness-related discrimination, and (ii) investigate whether its potential effectiveness was mediated via empathy or/and intergroup anxiety.

Methods

This is an international multisite non-randomised pre- vs post-controlled study. Eligible medical students were currently undertaking their rotational training in psychiatry. Thirteen sites across ten countries (n = 570) were included in the final analysis.

Results

READ was associated with positive changes in knowledge (mean difference 1.35; 95% CI 0.87 to 1.82), attitudes (mean difference − 2.50; 95% CI − 3.54 to − 1.46), skills (odds ratio 2.98; 95% CI 1.90 to 4.67), and simulated patient perceived empathy (mean difference 3.05; 95% CI 1.90 to 4.21). The associations of READ with knowledge, attitudes, and communication skills but not with simulated patient perceived empathy were partly mediated through student reported empathy and intergroup anxiety.

Conclusion

This is the first study to identify mediating effects of reduced intergroup anxiety and increased empathy in an evaluation of anti-stigma training that includes behavioural measures in the form of communication skills and perceived empathy. It shows the importance of both mediators for all of knowledge, skills, and attitudes, and hence of targeting both in future interventions.

     

Nonlinear functional network connectivity in resting functional magnetic resonance imaging data

In this work, we focus on explicitly nonlinear relationships in functional networks. We introduce a technique using normalized mutual information (NMI) that calculates the nonlinear relationship between different brain regions. We demonstrate our proposed approach using simulated data and then apply it to a dataset previously studied by Damaraju et al. This resting‐state fMRI data included 151 schizophrenia patients and 163 age‐ and gender‐matched healthy controls. We first decomposed these data using group independent component analysis (ICA) and yielded 47 functionally relevant intrinsic connectivity networks. Our analysis showed a modularized nonlinear relationship among brain functional networks that was particularly noticeable in the sensory and visual cortex. Interestingly, the modularity appears both meaningful and distinct from that revealed by the linear approach. Group analysis identified significant differences in explicitly nonlinear functional network connectivity (FNC) between schizophrenia patients and healthy controls, particularly in the visual cortex, with controls showing more nonlinearity (i.e., higher normalized mutual information between time courses with linear relationships removed) in most cases. Certain domains, including subcortical and auditory, showed relatively less nonlinear FNC (i.e., lower normalized mutual information), whereas links between the visual and other domains showed evidence of substantial nonlinear and modular properties. Overall, these results suggest that quantifying nonlinear dependencies of functional connectivity may provide a complementary and potentially important tool for studying brain function by exposing relevant variation that is typically ignored. Beyond this, we propose a method that captures both linear and nonlinear effects in a “boosted” approach. This method increases the sensitivity to group differences compared to the standard linear approach, at the cost of being unable to separate linear and nonlinear effects.     

Excel97在药物分析中的应用

目的：在药物分析中,电子表格软件ＭｉｃｒｏｓｏｆｔＥｘｃｅ１９７ｆｏｒ Ｗｉｎｄｏｗｓ。方法：利用Ｅｘｃｅｌ的数据处理功能,进行药物的图表绘制、数据计算和统计处理,回归分析,特别是计算分析,并可建立分析数据库。结果和结论：Ｅｘｃｅｌ操作简单,功能强大,数据分析工作直观。     

Correspondence of DNA Methylation Between Blood and Brain Tissue and Its Application to Schizophrenia Research

Given the difficulty of procuring human brain tissue, a key question in molecular psychiatry concerns the extent to which epigenetic signatures measured in more accessible tissues such as blood can serve as a surrogate marker for the brain. Here, we aimed (1) to investigate the blood-brain correspondence of DNA methylation using a within-subject design and (2) to identify changes in DNA methylation of brain-related biological pathways in schizophrenia.We obtained paired blood and temporal lobe biopsy samples simultaneously from 12 epilepsy patients during neurosurgical treatment. Using the Infinium 450K methylation array we calculated similarity of blood and brain DNA methylation for each individual separately. We applied our findings by performing gene set enrichment analyses (GSEA) of peripheral blood DNA methylation data (Infinium 27K) of 111 schizophrenia patients and 122 healthy controls and included only Cytosine-phosphate-Guanine (CpG) sites that were significantly correlated across tissues.Only 7.9% of CpG sites showed a statistically significant, large correlation between blood and brain tissue, a proportion that although small was significantly greater than predicted by chance. GSEA analysis of schizophrenia data revealed altered methylation profiles in pathways related to precursor metabolites and signaling peptides.Our findings indicate that most DNA methylation markers in peripheral blood do not reliably predict brain DNA methylation status. However, a subset of peripheral data may proxy methylation status of brain tissue. Restricting the analysis to these markers can identify meaningful epigenetic differences in schizophrenia and potentially other brain disorders.Key words: DNA methylation, cross-tissue, blood, brain, correlation, schizophrenia