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Impaired decision making, a key characteristic of alcohol dependence (AD), manifests in continuous alcohol consumption despite severe negative consequences. The neural basis of this impairment in individuals with AD and differences with known neural decision mechanisms among healthy subjects are not fully understood. In particular, it is unclear whether the choice behavior among individuals with AD is based on a general impairment of decision mechanisms or is mainly explained by altered value attribution, with an overly high subjective value attributed to alcohol-related stimuli.Here, we use a functional magnetic resonance imaging (fMRI) monetary reward task to compare the neural processes of model-based decision making and value computation between AD individuals (n = 32) and healthy controls (n = 32). During fMRI, participants evaluated monetary offers with respect to dynamically changing constraints and different levels of uncertainty.Individuals with AD showed lower activation associated with model-based decision processes in the caudate nucleus than controls, but there were no group differences in value-related neural activity or task performance.Our findings highlight the role of the caudate nucleus in impaired model-based decisions of alcohol-dependent individuals.

To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance imaging, it may be useful to develop classification models that are explicitly generalizable to unseen sites and populations. This problem was explored in a mega‐analysis of previously published datasets from 2,034 AD and comparison participants spanning 27 sites curated by the ENIGMA Addiction Working Group. Data were grouped into a training set used for internal validation including 1,652 participants (692 AD, 24 sites), and a test set used for external validation with 382 participants (146 AD, 3 sites). An exploratory data analysis was first conducted, followed by an evolutionary search based feature selection to site generalizable and high performing subsets of brain measurements. Exploratory data analysis revealed that inclusion of case‐ and control‐only sites led to the inadvertent learning of site‐effects. Cross validation methods that do not properly account for site can drastically overestimate results. Evolutionary‐based feature selection leveraging leave‐one‐site‐out cross‐validation, to combat unintentional learning, identified cortical thickness in the left superior frontal gyrus and right lateral orbitofrontal cortex, cortical surface area in the right transverse temporal gyrus, and left putamen volume as final features. Ridge regression restricted to these features yielded a test‐set area under the receiver operating characteristic curve of 0.768. These findings evaluate strategies for handling multi‐site data with varied underlying class distributions and identify potential biomarkers for individuals with current AD., To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance imaging, we developed classifiers on data collected from multiple sites. Exploratory data analysis revealed that inclusion of case‐ and control‐only sites led to the inadvertent learning of site‐effects. Evolutionary‐based feature selection leveraging leave‐one‐site‐out cross‐validation, to combat unintentional learning, yielded a test‐set area under the receiver operating characteristic curve of 0.768.

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., This review discusses the major challenges facing neuroimaging research of bipolar disorder and highlights the major accomplishments, ongoing challenges and future goals of the ENIGMA Bipolar Disorder Working Group.

Recent large-scale, genome-wide association studies (GWAS) have identified hundreds of genetic loci associated with general intelligence. The cumulative influence of these loci on brain structure is unknown. We examined if cortical morphology mediates the relationship between GWAS-derived polygenic scores for intelligence (PSi) and g-factor. Using the effect sizes from one of the largest GWAS meta-analysis on general intelligence to date, PSi were calculated among 10 P value thresholds. PSi were assessed for the association with g-factor performance, cortical thickness (CT), and surface area (SA) in two large imaging-genetics samples (IMAGEN N = 1651; IntegraMooDS N = 742). PSi explained up to 5.1% of the variance of g-factor in IMAGEN (F1,1640 = 12.2–94.3; P

BackgroundLimbic-cortical imbalance is an established model for the neurobiology of major depressive disorder (MDD), but imaging genetics studies have been contradicting regarding potential risk and resilience mechanisms. Here, we re-assessed previously reported limbic-cortical alterations between MDD relatives and controls in combination with a newly acquired sample of MDD patients and controls, to disentangle pathology, risk, and resilience.MethodsWe analyzed functional magnetic resonance imaging data and negative affectivity (NA) of MDD patients (n = 48), unaffected first-degree relatives of MDD patients (n = 49) and controls (n = 109) who performed a faces matching task. Brain response and task-dependent amygdala functional connectivity (FC) were compared between groups and assessed for associations with NA.ResultsGroups did not differ in task-related brain activation but activation in the superior frontal gyrus (SFG) was inversely correlated with NA in patients and controls. Pathology was associated with task-independent decreases of amygdala FC with regions of the default mode network (DMN) and decreased amygdala FC with the medial frontal gyrus during faces matching, potentially reflecting a task-independent DMN predominance and a limbic-cortical disintegration during faces processing in MDD. Risk was associated with task-independent decreases of amygdala-FC with fronto-parietal regions and reduced faces-associated amygdala-fusiform gyrus FC. Resilience corresponded to task-independent increases in amygdala FC with the perigenual anterior cingulate cortex (pgACC) and increased FC between amygdala, pgACC, and SFG during faces matching.ConclusionOur results encourage a refinement of the limbic-cortical imbalance model of depression. The validity of proposed risk and resilience markers needs to be tested in prospective studies. Further limitations are discussed.

Extensive research has demonstrated that rs1360780, a common single nucleotide polymorphism within the FKBP5 gene, interacts with early-life stress in predicting psychopathology. Previous results suggest that carriers of the TT genotype of rs1360780 who were exposed to child abuse show differences in structure and functional activation of emotion-processing brain areas belonging to the salience network. Extending these findings on intermediate phenotypes of psychopathology, we examined if the interaction between rs1360780 and child abuse predicts resting-state functional connectivity (rsFC) between the amygdala and other areas of the salience network. We analyzed data of young European adults from the general population (N = 774; mean age = 18.76 years) who took part in the IMAGEN study. In the absence of main effects of genotype and abuse, a significant interaction effect was observed for rsFC between the right centromedial amygdala and right posterior insula (p < .025, FWE-corrected), which was driven by stronger rsFC in TT allele carriers with a history of abuse. Our results suggest that the TT genotype of rs1360780 may render individuals with a history of abuse more vulnerable to functional changes in communication between brain areas processing emotions and bodily sensations, which could underlie or increase risk for psychopathology.

While the knowledge in neuroscience and the possibilities in clinical neurology have improved for many years, neurogenerative diseases and associated dementia remain a growing problem. Alzheimer’s Disease (AD) is the most common cause of dementia and also represents the most prevalent type of neurodegenerative diseases. For AD, disease-modifying treatments are presently lacking and the understanding of disease mechanisms remain incomplete. In the present review, we consider candidate contributing factors leading to AD and we evaluate novel computational brain simulation methods to further disentangle their potential roles. We first discuss existing computational models of AD that aim to provide a mechanistic understanding of the disease. Next, we outline the potential to link molecular aspects of neurodegeneration in AD with large-scale brain network modeling using The Virtual Brain (TVB, www.thevirtualbrain.org), an open-source, multi- scale, whole-brain simulation neuroinformatics platform. Finally, we discuss how this methodological approach may contribute to the understanding, improved diagnostics and treatment of AD.

The specific impact of weather factors on psychiatric disorders has been investigated only in few studies with inconsistent results. We hypothesized that meteorological conditions influence the number of cases presenting in a psychiatric emergency room as a measure of mental health conditions. We analyzed the number of patients consulting the emergency room (ER) of a psychiatric hospital in Berlin, Germany, between January 1, 2008, and December 31, 2014. A total of N = 22,672 cases were treated in the ER over the study period. Meteorological data were obtained from a publicly available data base. Due to collinearity among the meteorological variables, we performed a principal component (PC) analysis. Association of PCs with the daily number of patients was analyzed with autoregressive integrated moving average model. Delayed effects were investigated using Granger causal modeling. Daily number of patients in the ER was significantly higher in spring and summer compared to fall and winter (p

Threshold-free cluster enhancement (TFCE) is a sensitive means to incorporate spatial neighborhood information in neuroimaging studies without using arbitrary thresholds. The majority of methods have applied TFCE to voxelwise data. The need to understand the relationship among multiple variables and imaging modalities has become critical. We propose a new method of applying TFCE to vertexwise statistical images as well as cortexwise (either voxel- or vertexwise) mediation analysis. Here we present TFCE_mediation, a toolbox that can be used for cortexwise multiple regression analysis with TFCE, and additionally cortexwise mediation using TFCE. The toolbox is open source and publicly available (https://github.com/trislett/TFCE_mediation). We validated TFCE_mediation in healthy controls from two independent multimodal neuroimaging samples (N = 199 and N = 183). We found a consistent structure-function relationship between surface area and the first independent component (IC1) of the N-back task, that white matter fractional anisotropy is strongly associated with IC1 N-back, and that our voxel-based results are essentially identical to FSL randomise using TFCE (all PFWE

Altres ajuts: The ENIGMA-Major Depressive Disorder working group gratefully acknowledges support from the NIH Big Data to Knowledge (BD2K) award (U54 EB020403 to PMT) and NIH grant R01 MH116147 (PMT). LS is supported by an NHMRC MRFF Career Development Fellowship (APP1140764). We wish to acknowledge the patients and control subjects that have particiaped int the study. We thank Rosa Schirmer, Elke Schreiter, Reinhold Borschke and Ines Eidner for image acquisition and data preparation, and Anna Oliynyk for quality checks. We thank Dorothee P. Auer and F. Holsboer for initiation of the RUD study. We wish to acknowledge the patients and control subjects that have particiaped int the study. We thank Rosa Schirmer, Elke Schreiter, Reinhold Borschke and Ines Eidner for image acquisition and data preparation, and Anna Oliynyk for quality checks. We thank Dorothee P. Auer and F. Holsboer for initiation of the RUD study. NESDA: The infrastructure for the NESDA study (www.nesda.nl) is funded through the Geestkracht program of the Netherlands Organisation for Health Research and Development (Zon-Mw, grant number 10-000-1002) and is supported by participating universities (VU University Medical Center, GGZ inGeest, Arkin, Leiden University Medical Center, GGZ Rivierduinen, University Medical Center Groningen) and mental health care organizations, see www.nesda.nl. M-JvT was supported by a VENI grant (NWO grant number 016.156.077). UCSF: This work was supported by the Brain and Behavior Research Foundation (formerly NARSAD) to TTY; the National Institute of Mental Health (R01MH085734 to TTY; K01MH117442 to TCH) and by the American Foundation for Suicide Prevention (PDF-1-064-13) to TCH. Stanford: This work was supported by NIMH Grants R01MH59259 and R37101495 to IHG. MS is partially supported by an award funded by the Phyllis and Jerome Lyle Rappaport Foundation. Muenster: This work was funded by the German Research Foundation (SFB-TRR58, Projects C09 and Z02 to UD) and the Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Münster (grant Dan3/012/17 to UD). Marburg: This work was funded by the German Research Foundation (DFG, grant FOR2107 DA1151/5-1 and DA1151/5-2 to UD; KI 588/ 14-1, KI 588/14-2 to TK; KR 3822/7-1, KR 3822/7-2 to AK; JA 1890/ 7-1, JA 1890/7-2 to AJ). IMH-MDD: This work was supported by the National Healthcare Group Research Grant (SIG/15012) awarded to KS. Barcelona: This study was funded by two grants of the Fondo de Investigación Sanitaria from the Instituto de Salud Carlos III, by the Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM). The author is funded through 'Miguel Servet' research contract (CP16-0020), co-financed by the European Regional Development Fund (ERDF) (2016-2019). QTIM: We thank the twins and singleton siblings who gave generously of their time to participate in the QTIM study. We also thank the many research assistants, radiographers, and IT support staff for data acquisition and DNA sample preparation. This study was funded by White matter disturbances in major depressive disorder: a coordinated analysis across 20 international. . . 1521 the National Institute of Child Health & Human Development (RO1 HD050735); National Institute of Biomedical Imaging and Bioengineering (Award 1U54EB020403-01, Subaward 56929223); National Health and Medical Research Council, Australia (Project Grants 496682, 1009064). NIH ENIGMA-BD2K U54 EB020403 (Thompson); R01 MH117601 (Jahanshad/Schmaal). Magdeburg: M.L. and M.W. are funded by SFB 779. Bipolar Family Study: This study has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013). This paper reflects only the author's views and the European Union is not liable for any use that may be made of the information contained therein. This work was also supported by a Wellcome Trust Strategic Award (104036/Z/14/Z). Minnesota Adolescent Depression Study: The study was funded by the National Institute of Mental Health (K23MH090421), the National Alliance for Research on Schizophrenia and Depression, the University of Minnesota Graduate School, the Minnesota Medical Foundation, and the Biotechnology Research Center (P41 RR008079 to the Center for Magnetic Resonance Research), University of Minnesota, and the Deborah E. Powell Center for Women's Health Seed Grant, University of Minnesota. Dublin: This study was supported by Science Foundation Ireland through a Stokes Professorhip grant to TF. MPIP: The MPIP Sample comprises patients included in the Recurrent Unipolar Depression (RUD) Case-Control study at the clinic of the Max Planck Institute of Psychiatry, Munich, German. The RUD study was supported by GlaxoSmithKline. Alterations in white matter (WM) microstructure have been implicated in the pathophysiology of major depressive disorder (MDD). However, previous findings have been inconsistent, partially due to low statistical power and the heterogeneity of depression. In the largest multi-site study to date, we examined WM anisotropy and diffusivity in 1305 MDD patients and 1602 healthy controls (age range 12-88 years) from 20 samples worldwide, which included both adults and adolescents, within the MDD Working Group of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium. Processing of diffusion tensor imaging (DTI) data and statistical analyses were harmonized across sites and effects were meta-analyzed across studies. We observed subtle, but widespread, lower fractional anisotropy (FA) in adult MDD patients compared with controls in 16 out of 25 WM tracts of interest (Cohen's d between 0.12 and 0.26). The largest differences were observed in the corpus callosum and corona radiata. Widespread higher radial diffusivity (RD) was also observed (all Cohen's d between 0.12 and 0.18). Findings appeared to be driven by patients with recurrent MDD and an adult age of onset of depression. White matter microstructural differences in a smaller sample of adolescent MDD patients and controls did not survive correction for multiple testing. In this coordinated and harmonized multisite DTI study, we showed subtle, but widespread differences in WM microstructure in adult MDD, which may suggest structural disconnectivity in MDD.

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.

Genetic variation underlies both the response to antidepressant treatment and the occurrence of side effects. Over the past two decades, a number of pharmacogenetic variants, among these the SCL6A4, BDNF, FKBP5, GNB3, GRIK4, and ABCB1 genes, have come to the forefront in this regard. However, small effects sizes, mixed results in independent samples, and conflicting meta-analyses results led to inherent difficulties in the field of pharmacogenetics translating these findings into clinical practice. Nearly all antidepressant pharmacogenetic variants have potentially pleiotropic effects in which they are associated with major depressive disorder, intermediate phenotypes involved in emotional processes, and brain areas affected by antidepressant treatment. The purpose of this article is to provide a comprehensive review of the advances made in the field of pharmacogenetics of antidepressant efficacy and side effects, imaging findings of antidepressant response, and the latest results in the expanding field of imaging-pharmacogenetics studies. We suggest there is mounting evidence that genetic factors exert their impact on treatment response by influencing brain structural and functional changes during antidepressant treatment, and combining neuroimaging and genetic methods may be a more powerful way to detect biological mechanisms of response than either method alone. The most promising imaging-pharmacogenetics findings exist for the SCL6A4 gene, with converging associations with antidepressant response, frontolimbic predictors of affective symptoms, and normalization of frontolimbic activity following antidepressant treatment. More research is required before imaging-pharmacogenetics informed personalized medicine can be applied to antidepressant treatment; nevertheless, inroads have been made towards assessing genetic and neuroanatomical liability and potential clinical application.

The XXIIIrd World Congress of Psychiatric Genetics (WCPG) meeting, sponsored by the International Society of Psychiatric Genetics (ISPG), was held in Toronto, ON, Canada, on October 16-20, 2015. Approximately 700 participants attended to discuss the latest state-of-the-art findings in this rapidly advancing and evolving field. The following report was written by trainee travel awardees. Each was assigned one session as a rapporteur. This manuscript represents the highlights and topics that were covered in the plenary sessions, symposia, and oral sessions during the conference, and contains major notable and new findings.

Objectives Behavioral deficits in the Theory of Mind (ToM) have been robustly demonstrated in bipolar disorder. These deficits may represent an intermediate phenotype of the disease. The aim of this study was: (i) to investigate alterations in neural ToM processing in euthymic patients with bipolar disorder, and (ii) to examine whether similar effects are present in unaffected relatives of patients with bipolar disorder suggesting that ToM functional activation may be, in part, due to genetic risk for the disease. Methods A total of 24 euthymic patients with bipolar disorder, 21 unaffected first-degree relatives, and 81 healthy controls completed a ToM task while undergoing functional magnetic resonance imaging. Results We observed reduced bilateral activation of the temporoparietal junction (TPJ) and diminished functional fronto-temporoparietal connectivity in patients compared to controls. Relatives tended towards intermediate temporoparietal activity and functional coupling with medial prefrontal areas. There was also evidence for a potentially compensatory enhanced recruitment of the right middle temporal gyrus and stronger connectivity between this region and the medial prefrontal cortex in relatives. Conclusions These findings provide further evidence of altered neural ToM processing in euthymic patients with bipolar disorder. Further, our findings in relatives lend support to the idea that altered ToM processing may act as an intermediate phenotype of the disorder.

Major depressive disorder (MDD) is characterized by low mood for at least two weeks. Impaired emotion regulation has been suggested to be the consequence of dysfunctional serotonergic regulation of limbic and prefrontal regions, especially the amygdala, the anterior cingulate cortex (ACC) and the prefrontal cortex (PFC). The impact of genetic variation on brain function can be investigated with intermediate phenotypes. A suggested intermediate phenotype of MDD is emotion recognition: The 5-HTTLPR polymorphism of SLC6A4 as well as other serotonergic genes have been associated with amygdala and prefrontal function during emotion recognition. Previously, it has been suggested that habituation is a more reliable index of emotion recognition than functional activation. We examined the relationship of genes involved in serotonergic signaling with amygdala as well as prefrontal functional activation and habituation during an emotion recognition task in 171 healthy subjects. While effects of 5-HTTLPR and of a serotonergic multi-marker score (5-HTTLPR, TPH1(rs1800532), TPH2(rs4570625), HTR1A(rs6295) and HTR2A(rs6311)) on amygdala activation did not withstand correction for multiple regions of interest, we observed a strong correlation of the multi-marker score and habituation in the amygdala, DLPFC, and ACC. We replicated a well-studied intermediate phenotype for association with 5-HTTLPR and provided additional evidence for polygenic involvement. Furthermore, we showed that task habituation may be influenced by genetic variation in serotonergic signaling, particularly by a serotonergic multi-marker score. We provided preliminary evidence that PFC activation is an important intermediate phenotype of MDD. Future studies are needed to corroborate the results in larger samples.

The rs1625579 variant near the microRNA-137 (MIR137) gene is one of the best-supported schizophrenia variants in genome-wide association studies (GWAS), and microRNA-137 functionally regulates other GWAS identified schizophrenia risk variants. Schizophrenia patients with the MIR137 rs1625579 risk genotype (homozygous for the schizophrenia risk variant) also have aberrant brain structure. It is unclear if the effect of MIR137 among schizophrenia patients is due to potential epistasis with genetic risk for schizophrenia or other factors of the disorder. Here, we investigated the effect of MIR137 genotype on white matter fractional anisotropy (FA), cortical thickness (CT), and surface area (SA) in a sample comprising healthy control subjects, and individuals with familial risk for psychosis (first-degree relatives of patients with schizophrenia or bipolar disorder; N=426). In voxel-wise analyses of FA, we observed a significant genotype-by-group interaction (PFWE

Recently, 125 loci with genome-wide support for association with schizophrenia were identified. We investigated the impact of these variants and their accumulated genetic risk on brain activation in five neurocognitive domains of the Research Domain Criteria (working memory, reward processing, episodic memory, social cognition and emotion processing). In 578 healthy subjects we tested for association (i) of a polygenic risk profile score (RPS) including all single-nucleotide polymorphisms (SNPs) reaching genome-wide significance in the recent genome-wide association studies (GWAS) meta-analysis and (ii) of all independent genome-wide significant loci separately that showed sufficient distribution of all allelic groups in our sample (105 SNPs). The RPS was nominally associated with perigenual anterior cingulate and posterior cingulate/precuneus activation during episodic memory (PFWE(ROI)=0.047) and social cognition (PFWE(ROI)=0.025), respectively. Single SNP analyses revealed that rs9607782, located near EP300, was significantly associated with amygdala recruitment during emotion processing (PFWE(ROI)=1.63 × 10−4, surpassing Bonferroni correction for the number of SNPs). Importantly, this association was replicable in an independent sample (N=150; PFWE(ROI)

Introduction Advances in image segmentation of magnetic resonance images (MRI) have demonstrated that multi-atlas approaches improve segmentation over regular atlas-based approaches. These approaches often rely on a large number of manually segmented atlases (e.g. 30–80) that take significant time and expertise to produce. We present an algorithm, MAGeT-Brain (Multiple Automatically Generated Templates), for the automatic segmentation of the hippocampus that minimises the number of atlases needed whilst still achieving similar agreement to multi-atlas approaches. Thus, our method acts as a reliable multi-atlas approach when using special or hard-to-define atlases that are laborious to construct. Method MAGeT-Brain works by propagating atlas segmentations to a template library, formed from a subset of target images, via transformations estimated by nonlinear image registration. The resulting segmentations are then propagated to each target image and fused using a label fusion method. We conduct two separate Monte Carlo cross-validation experiments comparing MAGeT-Brain and basic multi-atlas whole hippocampal segmentation using differing atlas and template library sizes, and registration and label fusion methods. The first experiment is a 10-fold validation (per parameter setting) over 60 subjects taken from the Alzheimer's Disease Neuroimaging Database (ADNI), and the second is a five-fold validation over 81 subjects having had a first episode of psychosis. In both cases, automated segmentations are compared with manual segmentations following the Pruessner-protocol. Using the best settings found from these experiments, we segment 246 images of the ADNI1:Complete 1Yr 1.5T dataset and compare these with segmentations from existing automated and semi-automated methods: FSL FIRST, FreeSurfer, MAPER, and SNT. Finally, we conduct a leave-one-out cross-validation of hippocampal subfield segmentation in standard 3T T1-weighted images, using five high-resolution manually segmented atlases (Winterburn et al., 2013). Results In the ADNI cross-validation, using 9 atlases MAGeT-Brain achieves a mean Dice's Similarity Coefficient (DSC) score of 0.869 with respect to manual whole hippocampus segmentations, and also exhibits significantly lower variability in DSC scores than multi-atlas segmentation. In the younger, psychosis dataset, MAGeT-Brain achieves a mean DSC score of 0.892 and produces volumes which agree with manual segmentation volumes better than those produced by the FreeSurfer and FSL FIRST methods (mean difference in volume: 80 mm3, 1600 mm3, and 800 mm3, respectively). Similarly, in the ADNI1:Complete 1Yr 1.5T dataset, MAGeT-Brain produces hippocampal segmentations well correlated (r > 0.85) with SNT semi-automated reference volumes within disease categories, and shows a conservative bias and a mean difference in volume of 250 mm3 across the entire dataset, compared with FreeSurfer and FSL FIRST which both overestimate volume differences by 2600 mm3 and 2800 mm3 on average, respectively. Finally, MAGeT-Brain segments the CA1, CA4/DG and subiculum subfields on standard 3T T1-weighted resolution images with DSC overlap scores of 0.56, 0.65, and 0.58, respectively, relative to manual segmentations. Conclusion We demonstrate that MAGeT-Brain produces consistent whole hippocampal segmentations using only 9 atlases, or fewer, with various hippocampal definitions, disease populations, and image acquisition types. Additionally, we show that MAGeT-Brain identifies hippocampal subfields in standard 3T T1-weighted images with overlap scores comparable to competing methods.

Threshold‐free cluster enhancement (TFCE) is a sensitive means to incorporate spatial neighborhood information in neuroimaging studies without using arbitrary thresholds. The majority of methods have applied TFCE to voxelwise data. The need to understand the relationship among multiple variables and imaging modalities has become critical. We propose a new method of applying TFCE to vertexwise statistical images as well as cortexwise (either voxel‐ or vertexwise) mediation analysis. Here we present TFCE_mediation, a toolbox that can be used for cortexwise multiple regression analysis with TFCE, and additionally cortexwise mediation using TFCE. The toolbox is open source and publicly available (https://github.com/trislett/TFCE_mediation). We validated TFCE_mediation in healthy controls from two independent multimodal neuroimaging samples (N = 199 and N = 183). We found a consistent structure–function relationship between surface area and the first independent component (IC1) of the N‐back task, that white matter fractional anisotropy is strongly associated with IC1 N‐back, and that our voxel‐based results are essentially identical to FSL randomise using TFCE (all P (FWE)

Background Previous studies have shown that antipsychotics with high propensity for antipsychotic-induced weight gain (AIWG) influence glucose transporter type 4 (GLUT4) mediated glucose intake. Variation in the gene encoding TBC1 domain family member 1 (TBC1D1), a Rab-GTPase activating protein regulating GLUT4 trafficking, has been associated with obesity. Therefore, we investigated the impact of TBC1D1 polymorphisms on AIWG. Methods We analyzed rs9852 and rs35859249 in TBC1D1 in 195 schizophrenia subjects treated mostly with clozapine or olanzapine for up to 14 weeks. Association was tested using analysis of variance and analysis of covariance with change (%) from baseline weight as the dependent variable. Results Analysis of covariance showed a non-significant trend for lower weight gain in carriers of the T-allele of rs9852 than in C-allele homozygotes (p = 0.063). This effect was more pronounced in the subgroup of patients treated with clozapine or olanzapine (p = 0.024). For rs35859249, no significant association with AIWG could be detected. Conclusions This is the first study examining the association between TBC1D1 and AIWG. The moderate association of rs9852, located in the 3′UTR near a miRNA binding site, indicates an influence of TBC1D1 on AIWG. Further investigations remain necessary to elucidate the role of this gene in AIWG. Copyright © 2013 John Wiley & Sons, Ltd.

Introduction There is mounting evidence that schizophrenia risk variants influence response to antipsychotic medication. Common single nucleotide polymorphisms (SNPs) in or near the inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3) gene have been repeatedly associated with schizophrenia and related psychiatric disorders in genome-wide association studies. Here, we provide the first study to assess the relevance of the ITIH3 rs2535629 SNP in response to antipsychotic medication. Methods The rs2535629 SNP was genotyped in N = 256 patients receiving various antipsychotics for up to 26 weeks. Treatment response was assessed using the Brief Psychiatric Rating Scale (BPRS) including its positive and negative subscales. Follow-up analyses were performed after stratifying for ethnicity and medication. Results We found significant association of rs2535629 with improvement of negative symptoms in patients of European ancestry after six months of clozapine treatment (F1,87 = 8.8, pcorr = 0.032). Patients homozygous for the minor A-allele showed the best improvement of negative BPRS scores. However, we observed no association between rs2535629 and changes in total BPRS score in the entire sample or the clozapine-treated subgroup. Discussion Although there was no association of genotype with overall changes in BPRS scores, the greater improvement of negative symptoms in minor allele carriers indicates that rs2535629 may help to identify a subset of schizophrenia patients with better treatment response to clozapine. Therefore, our findings provide the first suggestive evidence that rs2535629 is relevant in antipsychotic response.

The glutamic acid decarboxylase 1 (GAD1) gene is a major determinant of γ-aminobutyric acid (GABA), the most abundant inhibitory neurotransmitter modulating local neuronal circuitry. GABAergic dysfunction and expression of GAD1 have been implicated in the pathophysiology of schizophrenia, and in working memory impairment. We examined the influence of the functional GAD1 rs3749034 variant on white matter fractional anisotropy (FA), cortical thickness, and working memory performance in schizophrenia patients and healthy controls (N=197). Using transcranial magnetic stimulation with electroencephalography (TMS-EEG), we subsequently examined the effect of rs3749034 on long-interval cortical inhibition (LICI) in the dorsolateral prefrontal cortex (DLPFC) in schizophrenia patients and healthy controls (N=66). We found that the rs3749034 T-allele carrier risk group had lower voxel-wise FA in the prefrontal cortex region (PFWE-corrected

Background Antipsychotic-induced weight gain (AIWG) is a serious side-effect of antipsychotic medication leading to metabolic syndrome and increased cardiovascular morbidity. Unfortunately, there are still no valid predictors to assess an individual's risk to gain weight. Previous studies have indicated an impact of genetic variation in the genes encoding leptin, LEP, and leptin receptor, LEPR, on AIWG, but results have not been conclusive. Thus, we investigated polymorphisms in both genes for an association with AIWG. Methods A total of 181 schizophrenic and schizoaffective patients treated with various antipsychotics were included. In a small subset of patients, leptin plasma levels were additionally obtained. Five polymorphisms in LEP and LEPR (LEP: rs7799039 (-2548G/A polymorphism), rs10954173, rs3828942; LEPR: rs1327120, rs1137101 (Q223R polymorphism) were genotyped using TaqMan assays. Statistical association with % weight change from baseline weight was performed using ANCOVA with baseline weight as covariate. Results ANCOVA showed a non-significant trend for genotype association of the rs7799039 marker (p = .068). No significant association of the other LEP and LEPR SNPs with AIWG was detected. However, we found a significant association between a haplotype of LEP rs7799039G–rs10954173G–rs3828942G (p = .035) and AIWG. The rs7799039 G-allele (p = .042) and G-allele of rs3828942 (p = .032) were associated with higher weight gain. Conclusion Our study supports the hypothesis of an impact of LEP gene variation on AIWG. Limitations of our study include heterogeneous samples, short treatment duration and multiple comparisons. Our findings were compared to previous studies in detail in order to provide the readers with a more conclusive picture. However, further studies are warranted including more gene variants and interaction analyses with other genes of the leptin–melanocortin pathway.

Neurexin-1 (NRXN1) modulates recruitment of NMDA receptors. Furthermore, clozapine reduces hyperactivity of NMDA receptors. Thus, regulation of the NRXN1 gene may mediate the efficacy of clozapine at reducing cortical hyperactivity. We examined the putative functional SNP, rs1045881, for association with schizophrenia, and the potential role of this SNP in clozapine response. The rs1045881 variant was not significantly associated with schizophrenia (N = 302 case–control pairs), but with clozapine response (N = 163; p = 0.030). Baseline and BPRS scores after six months revealed a trend for rs1045881 genotype by treatment interaction (p = 0.079). In the post hoc analysis, a significant association between BPRS negative symptoms score and genotype was observed (p = 0.033). These results suggest that the rs1045881 NRXN1 polymorphism may influence clozapine response.

OBJECTIVE Tardive dyskinesia (TD) is a motor side effect that may develop after long-term antipsychotic treatment. Schizophrenia has recently been associated with the Neurexin-1 (NRXN1) gene that codes for a cell adhesion molecule in synaptic communication. METHODS This study examined five NRXN1 single-nucleotide polymorphisms (SNPs) for possible association with the occurrence and severity of TD in 178 schizophrenia patients of European ancestry. RESULTS We did not find these SNPs to be significantly associated with TD. CONCLUSIONS More research is needed with additional SNPs and in bigger samples before we can completely rule out the role of NRXN1 in TD.

Genetic variation in cytochrome enzymes is known to affect drug metabolism and influence treatment response. Recently, the rs472660 variant in CYP3A43 has been associated with olanzapine response and clearance. In this study, we investigated the impact of rs472660 and the putatively functional marker rs680055 on antipsychotic response. We genotyped the rs472660 and rs680055 single nucleotide polymorphisms (SNPs) in N = 152 schizophrenia patients of European descent collected at two sample sites who were predominately treated with second generation antipsychotics for up to 6 months. Treatment response was assessed prospectively using Brief Psychiatric Rating Scale (BPRS) scores. Statistical analysis was performed using Chi square and analysis of covariance. The rs680055 SNP was significantly associated with treatment response. Carriers of the minor allele had significantly lower BPRS scores at study end (p = 5.9 × 10(-4)) with 8 % of the variance being explained by rs680055 genotype. Post hoc analyses revealed that this effect was present in both samples and in both genders. The rs472660 SNP was also associated with response (p = 0.027); however, this finding was not significant after multiple test correction. This is the first evidence that the rs680055 missense mutation influences antipsychotic response. Although our finding for rs472660 was only a non-significant trend after correction, our results still support the notion that this SNP may play a role in antipsychotic response. Despite the fact that the functional role of CYP3A43 in antipsychotic metabolism is not fully understood yet, our study provides an important contribution to understanding genetic factors of antipsychotic response.

We examined the influence of the genome-wide significant schizophrenia risk variant rs1625579 near the microRNA (miRNA)-137 (MIR137) gene on well-established sources of phenotypic variability in schizophrenia: age-at-onset of psychosis and brain structure. We found that the MIR137 risk genotype strongly predicts an earlier age-at-onset of psychosis across four independently collected samples of patients with schizophrenia (n=510; F1,506=17.7, P=3.1 × 10(-5)). In an imaging-genetics subsample that included additional matched controls (n=213), patients with schizophrenia who had the MIR137 risk genotype had reduced white matter integrity (F3,209=13.6, P=3.88 × 10(-8)) throughout the brain as well as smaller hippocampi and larger lateral ventricles; the brain structure of patients who were carriers of the protective allele was no different from healthy control subjects on these neuroimaging measures. Our findings suggest that MIR137 substantially influences variation in phenotypes that are thought to have an important role in clinical outcome and treatment response. Finally, the possible consequences of genetic risk factors may be distinct in patients with schizophrenia compared with healthy controls.

Cognitive deficits are a core feature of schizophrenia. Among these deficits, working memory impairment is considered a central cognitive impairment in schizophrenia. The prefrontal cortex, a region critical for working memory performance, has been demonstrated as a critical liability region in schizophrenia. As yet, there are no standardized treatment options for working memory deficits in schizophrenia. In this review, we summarize the neuronal basis for working memory impairment in schizophrenia, including dysfunction in prefrontal signaling pathways (e.g., γ-aminobutyric acid transmission) and neural network synchrony (e.g., gamma/theta oscillations). We discuss therapeutic strategies for working memory dysfunction such as pharmacological agents, cognitive remediation therapy, and repetitive transcranial magnetic stimulation. Despite the drawbacks of current approaches, the advances in neurobiological and translational treatment strategies suggest that clinical application of these methods will occur in the near future.

The XVIII World Congress of Psychiatric Genetics (WCPG), sponsored by The International Society of Psychiatric Genetics (ISPG) took place in Washington, DC on September 10–14, 2011. Approximately 540 participants gathered to discuss the latest findings in this rapidly advancing field. The topics covered can be subdivided into the following categories: the latest results from Genome-Wide Association Studies (GWAS) examining the effects of common allele variation, the new focus on sequencing studies, other genomic mechanisms that include epigenetic gene modification and rare copy number variations, biologic and other endophenotypes, the genetics of post-traumatic stress disorder, substance abuse, gene functioning, pharmacogenomics, and other miscellaneous topics of genetic interest. Some notable reported findings introduced at this congress included: several new or replicated associations for common alleles in GWAS for schizophrenia (a SNP located near the hyaluronan binding protein 2 gene (HABP2) on chromosome 10, an SNP in the Transmembrane protein 45B gene (TMEM45B) on chromosome 11, some popular schizophrenia candidate genes, TCF4, NOTCH4, ZNF804A, and the MHC region replicated, and several novel genes reported, POM121L2, AS3MT, CNNM2, NT5C2; for major depression, the neuronal transporter gene SLC6A15; for bipolar disorder, TRANK1 gene, as well as LMAN2L, PTGFR and the SYNE1 gene encoding Nesprin. Some initial exome sequencing results were reported, but very preliminary, although promising. Endophenotypes that specifically were discussed included amygdala volume and prefrontal cortex activation, suicidal behavior, and impulsivity. There was a large emphasis on nicotine dependence in the substance abuse sessions and an association between smoking quantity and genetic loci on the chromosome 15q25 region was clearly demonstrated. The GABRA2 association to alcohol dependence was confirmed. There were several presentations of candidate gene polymorphisms associated with antidepressant and mood stabilizer response from large pharmacological treatment trials, but no one finding was confirmed and to be definitive yet to be able to be used commercially in the clinic. The complete report summarizing the findings reported at this meeting was written by junior travel awardees, as well as other individuals in training who were volunteers from meeting attendees. Each was assigned sessions as rapporteurs. The entire manuscript represents topics covered in oral presentations during the conference and can be found on line as a journal supplement. It is clear from this 2011 congress that multi-international collaborative efforts to solve the genetic tendency for all major psychiatric disorders are necessary and underway. It is impressive to find that the field has come together in such a collegial fashion in order to make progress toward alleviating the suffering of people with mental illnesses. It is now important to be able to decipher which if any of the accumulating findings are ready for communication to clinicians and implementation clinically. Ethical considerations to their use in treatment of patients will be a continuing ongoing discussion.

Second-generation antipsychotics (SGAs), such as risperidone, clozapine and olanzapine, are the most common drug treatments for schizophrenia. SGAs presented an advantage over first-generation antipsychotics (FGAs), particularly regarding avoidance of extrapyramidal symptoms. However, most SGAs, and to a lesser degree FGAs, are linked to substantial weight gain. This substantial weight gain is a leading factor in patient non-compliance and poses significant risk of diabetes, lipid abnormalities (that is, metabolic syndrome) and cardiovascular events including sudden death. The purpose of this article is to review the advances made in the field of pharmacogenetics of antipsychotic-induced weight gain (AIWG). We included all published association studies in AIWG from December 2006 to date using the Medline and ISI web of knowledge databases. There has been considerable progress reaffirming previous findings and discovery of novel genetic factors. The HTR2C and leptin genes are among the most promising, and new evidence suggests that the DRD2, TNF, SNAP-25 and MC4R genes are also prominent risk factors. Further promising findings have been reported in novel susceptibility genes, such as CNR1, MDR1, ADRA1A and INSIG2. More research is required before genetically informed, personalized medicine can be applied to antipsychotic treatment; nevertheless, inroads have been made towards assessing genetic liability and plausible clinical application.

OBJECTIVES. The ANK3, CACNA1C and ZNF804A genes have been implicated in both bipolar disorders (BPD) and schizophrenia (SCZ). It has been suggested that BPD with psychosis may be a clinical manifestation of genes overlapping between BPD and SCZ. We therefore tested the association of these genes with BPD in a large family-based sample, and then dissected the phenotype into psychosis present or absent subgroups. METHODS. We genotyped four high interest single nucleotide polymorphisms from ANK3 (rs10994336, rs9804190), CACNA1C (rs1006737), and ZNF804A (rs1344706). Family based association testing (FBAT) was performed on 312 families, and within psychotic (N = 158) and non-psychotic BPD (N = 119) subgroups. RESULTS. In the whole sample, we found a nominal association in ZNF804A (rs1344706, P = 0.046), and a trend in CACNA1C (rs1006737, P = 0.077). In the psychotic BPD subgroup, as hypothesized, stronger signals were observed in ZNF804A (P = 0.019) and CACNA1C (P = 0.017). We found no association in the ANK3 markers, but the rs10994336 variant was nominally associated with non-psychotic BPD (P = 0.046). Exploratory analysis revealed the rs1344706 variant was also implicated in suicide-attempt behaviour (P = 0.038). CONCLUSIONS. These tentative results are consistent with the hypothesis that the subphenotype of BPD with psychosis may represent a clinical manifestation of shared genetic liability between BPD and SCZ.

Background Structural variation in the neurexin-1 (NRXN1) gene increases risk for both autism spectrum disorders (ASD) and schizophrenia. However, the manner in which NRXN1 gene variation may be related to brain morphology to confer risk for ASD or schizophrenia is unknown. Method/Principal Findings 53 healthy individuals between 18–59 years of age were genotyped at 11 single nucleotide polymorphisms of the NRXN1 gene. All subjects received structural MRI scans, which were processed to determine cortical gray and white matter lobar volumes, and volumes of striatal and thalamic structures. Each subject's sensorimotor function was also assessed. The general linear model was used to calculate the influence of genetic variation on neural and cognitive phenotypes. Finally, in silico analysis was conducted to assess potential functional relevance of any polymorphisms associated with brain measures. A polymorphism located in the 3′ untranslated region of NRXN1 significantly influenced white matter volumes in whole brain and frontal lobes after correcting for total brain volume, age and multiple comparisons. Follow-up in silico analysis revealed that this SNP is a putative microRNA binding site that may be of functional significance in regulating NRXN1 expression. This variant also influenced sensorimotor performance, a neurocognitive function impaired in both ASD and schizophrenia. Conclusions Our findings demonstrate that the NRXN1 gene, a vulnerability gene for SCZ and ASD, influences brain structure and cognitive function susceptible in both disorders. In conjunction with our in silico results, our findings provide evidence for a neural and cognitive susceptibility mechanism by which the NRXN1 gene confers risk for both schizophrenia and ASD.