Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity.

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.

Genetic and inflammatory effects on childhood trauma and cognitive functioning in patients with schizophrenia and healthy participants.

Recent studies have reported a negative association between exposure to childhood trauma, including physical neglect, and cognitive functioning in patients with schizophrenia. Childhood trauma has been found to influence immune functioning, which may contribute to the risk of schizophrenia and cognitive symptoms of the disorder. In this study, we aimed to test the hypothesis that physical neglect is associated with cognitive ability, and that this association is mediated by a combined latent measure of inflammatory response, and moderated by higher genetic risk for schizophrenia. The study included 279 Irish participants, comprising 102 patients and 177 healthy participants. Structural equation modelling was used to perform mediation and moderation analyses. Inflammatory response was measured via basal plasma levels of IL-6, TNF-α, and CRP, and cognitive performance was assessed across three domains: full-scale IQ, logical memory, and the emotion recognition task. Genetic variation for schizophrenia was estimated using a genome-wide polygenic score based on genome-wide association study summary statistics. The results showed that inflammatory response mediated the association between physical neglect and all measures of cognitive functioning, and explained considerably more variance than any of the inflammatory markers alone. Furthermore, genetic risk for schizophrenia was observed to moderate the direct pathway between physical neglect and measures of non-social cognitive functioning in both patient and healthy participants. However, genetic risk did not moderate the mediated pathway associated with inflammatory response. Therefore, we conclude that the mediating role of inflammatory response and the moderating role of higher genetic risk may independently influence the association between adverse early life experiences and cognitive function in patients and healthy participants.

Mega-analysis of association between obesity and cortical morphology in bipolar disorders: ENIGMA study in 2832 participants.

BACKGROUND: Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact. METHODS: We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations. RESULTS: BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI. CONCLUSIONS: We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.

Aberrant Subnetwork and Hub Dysconnectivity in Adult Bipolar Disorder: A Multicenter Graph Theory Analysis.

Neuroimaging evidence implicates structural network-level abnormalities in bipolar disorder (BD); however, there remain conflicting results in the current literature hampered by sample size limitations and clinical heterogeneity. Here, we set out to perform a multisite graph theory analysis to assess the extent of neuroanatomical dysconnectivity in a large representative study of individuals with BD. This cross-sectional multicenter international study assessed structural and diffusion-weighted magnetic resonance imaging data obtained from 109 subjects with BD type 1 and 103 psychiatrically healthy volunteers. Whole-brain metrics, permutation-based statistics, and connectivity of highly connected nodes were used to compare network-level connectivity patterns in individuals with BD compared with controls. The BD group displayed longer characteristic path length, a weakly connected left frontotemporal network, and increased rich-club dysconnectivity compared with healthy controls. Our multisite findings implicate emotion and reward networks dysconnectivity in bipolar illness and may guide larger scale global efforts in understanding how human brain architecture impacts mood regulation in BD.

What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar 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.

Association between body mass index and subcortical brain volumes in bipolar disorders-ENIGMA study in 2735 individuals.

Individuals with bipolar disorders (BD) frequently suffer from obesity, which is often associated with neurostructural alterations. Yet, the effects of obesity on brain structure in BD are under-researched. We obtained MRI-derived brain subcortical volumes and body mass index (BMI) from 1134 BD and 1601 control individuals from 17 independent research sites within the ENIGMA-BD Working Group. We jointly modeled the effects of BD and BMI on subcortical volumes using mixed-effects modeling and tested for mediation of group differences by obesity using nonparametric bootstrapping. All models controlled for age, sex, hemisphere, total intracranial volume, and data collection site. Relative to controls, individuals with BD had significantly higher BMI, larger lateral ventricular volume, and smaller volumes of amygdala, hippocampus, pallidum, caudate, and thalamus. BMI was positively associated with ventricular and amygdala and negatively with pallidal volumes. When analyzed jointly, both BD and BMI remained associated with volumes of lateral ventricles  and amygdala. Adjusting for BMI decreased the BD vs control differences in ventricular volume. Specifically, 18.41% of the association between BD and ventricular volume was mediated by BMI (Z = 2.73, p = 0.006). BMI was associated with similar regional brain volumes as BD, including lateral ventricles, amygdala, and pallidum. Higher BMI may in part account for larger ventricles, one of the most replicated findings in BD. Comorbidity with obesity could explain why neurostructural alterations are more pronounced in some individuals with BD. Future prospective brain imaging studies should investigate whether obesity could be a modifiable risk factor for neuroprogression.

Genetic copy number variants, cognition and psychosis: a meta-analysis and a family study.

The burden of large and rare copy number genetic variants (CNVs) as well as certain specific CNVs increase the risk of developing schizophrenia. Several cognitive measures are purported schizophrenia endophenotypes and may represent an intermediate point between genetics and the illness. This paper investigates the influence of CNVs on cognition. We conducted a systematic review and meta-analysis of the literature exploring the effect of CNV burden on general intelligence. We included ten primary studies with a total of 18,847 participants and found no evidence of association. In a new psychosis family study, we investigated the effects of CNVs on specific cognitive abilities. We examined the burden of large and rare CNVs (>200 kb, <1% MAF) as well as known schizophrenia-associated CNVs in patients with psychotic disorders, their unaffected relatives and controls (N = 3428) from the Psychosis Endophenotypes International Consortium (PEIC). The carriers of specific schizophrenia-associated CNVs showed poorer performance than non-carriers in immediate (P = 0.0036) and delayed (P = 0.0115) verbal recall. We found suggestive evidence that carriers of schizophrenia-associated CNVs had poorer block design performance (P = 0.0307). We do not find any association between CNV burden and cognition. Our findings show that the known high-risk CNVs are not only associated with schizophrenia and other neurodevelopmental disorders, but are also a contributing factor to impairment in cognitive domains such as memory and perceptual reasoning, and act as intermediate biomarkers of disease risk.

Diagnosis of bipolar disorders and body mass index predict clustering based on similarities in cortical thickness-ENIGMA study in 2436 individuals.

AIMS: Rates of obesity have reached epidemic proportions, especially among people with psychiatric disorders. While the effects of obesity on the brain are of major interest in medicine, they remain markedly under-researched in psychiatry. METHODS: We obtained body mass index (BMI) and magnetic resonance imaging-derived regional cortical thickness, surface area from 836 bipolar disorders (BD) and 1600 control individuals from 14 sites within the ENIGMA-BD Working Group. We identified regionally specific profiles of cortical thickness using K-means clustering and studied clinical characteristics associated with individual cortical profiles. RESULTS: We detected two clusters based on similarities among participants in cortical thickness. The lower thickness cluster (46.8% of the sample) showed thinner cortex, especially in the frontal and temporal lobes and was associated with diagnosis of BD, higher BMI, and older age. BD individuals in the low thickness cluster were more likely to have the diagnosis of bipolar disorder I and less likely to be treated with lithium. In contrast, clustering based on similarities in the cortical surface area was unrelated to BD or BMI and only tracked age and sex. CONCLUSIONS: We provide evidence that both BD and obesity are associated with similar alterations in cortical thickness, but not surface area. The fact that obesity increased the chance of having low cortical thickness could explain differences in cortical measures among people with BD. The thinner cortex in individuals with higher BMI, which was additive and similar to the BD-associated alterations, may suggest that treating obesity could lower the extent of cortical thinning in BD.

Lithium prevents grey matter atrophy in patients with bipolar disorder: an international multicenter study.

BACKGROUND: Lithium (Li) is the gold standard treatment for bipolar disorder (BD). However, its mechanisms of action remain unknown but include neurotrophic effects. We here investigated the influence of Li on cortical and local grey matter (GM) volumes in a large international sample of patients with BD and healthy controls (HC). METHODS: We analyzed high-resolution T1-weighted structural magnetic resonance imaging scans of 271 patients with BD type I (120 undergoing Li) and 316 HC. Cortical and local GM volumes were compared using voxel-wise approaches with voxel-based morphometry and SIENAX using FSL. We used multiple linear regression models to test the influence of Li on cortical and local GM volumes, taking into account potential confounding factors such as a history of alcohol misuse. RESULTS: Patients taking Li had greater cortical GM volume than patients without. Patients undergoing Li had greater regional GM volumes in the right middle frontal gyrus, the right anterior cingulate gyrus, and the left fusiform gyrus in comparison with patients not taking Li. CONCLUSIONS: Our results in a large multicentric sample support the hypothesis that Li could exert neurotrophic and neuroprotective effects limiting pathological GM atrophy in key brain regions associated with BD.

Early life Adversity, functional connectivity and cognitive performance in Schizophrenia: The mediating role of IL-6.

OBJECTIVE: Exposure to childhood trauma (CT) is associated with cognitive impairment in schizophrenia, and deficits in social cognition in particular. Here, we sought to test whether IL-6 mediated the association between CT and social cognition both directly, and sequentially via altered default mode network (DMN) connectivity. METHODS: Three-hundred-and-eleven participants (104 patients and 207 healthy participants) were included, with MRI data acquired in a subset of n = 147. CT was measured using the childhood trauma questionnaire (CTQ). IL-6 was measured in both plasma and in toll like receptor (TLR) stimulated whole blood. The CANTAB emotion recognition task (ERT) was administered to assess social cognition, and cortical connectivity was assessed based on resting DMN connectivity. RESULTS: Higher IL-6 levels, measured both in plasma and in toll-like receptor (TLR-2) stimulated blood, were significantly correlated with higher CTQ scores and lower cognitive and social cognitive function. Plasma IL-6 was further observed to partly mediate the association between higher CT scores and lower emotion recognition performance (CTQ total: ßindirect -0.0234, 95% CI: -0.0573 to -0.0074; CTQ physical neglect: ßindirect = -0.0316, 95% CI: -0.0741 to -0.0049). Finally, sequential mediation was observed between plasma IL-6 levels and DMN connectivity in mediating the effects of higher CTQ on lower social cognitive function (ßindirect = -0.0618, 95% CI: -0.1523 to -0.285). CONCLUSION: This work suggests that previous associations between CT and social cognition may be partly mediated via an increased inflammatory response. IL-6's association with changes in DMN activity further suggest at least one cortical network via which CT related effects on cognition may be transmitted.

Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group.

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47-67.00, ROC-AUC = 71.49%, 95% CI = 69.39-73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70-60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen's Kappa = 0.83, 95% CI = 0.829-0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data.

A 52-week prophylactic randomised control trial of omega-3 polyunsaturated fatty acids in bipolar disorder.

OBJECTIVES: Previous work suggests supplementation with omega-3 polyunsaturated fatty acids (PUFAs) may improve mood symptoms in bipolar disorder (BD) although findings remain unclear. In this study, we assess the efficacy of omega-3 PUFA administration for prophylaxis in BD using a clinical trial design over 52-weeks (ClinicalTrials.gov Identifier: NCT04210804). METHODS: Individuals with BD (n = 80) were randomised to receive placebo (n = 40) or 1 g eicosapentaenoic acid (EPA) plus 1 g docosahexaenoic acid (DHA; n = 40) adjunctively for 52-weeks. The primary outcome measure comprised the number of mood episode relapses including hospital admissions and medication changes experienced. Secondary outcome measures included time to first mood episode relapse and change in psychometric measures of depression and elation (Hamilton Depression Rating Scale and Young Mania Rating Scale). RESULTS: No significant differences in the number of mood episode relapses (U = 490.00, p = 0.14) or the number of individuals requiring admission to hospital (χ2  = 0.67, p = 0.41) or medication adjustment in the omega-3 PUFA compared to the placebo group were noted. Time to relapse was not significantly different between groups (Log Rank χ2  = 0.41, p = 0.52). Change in Young Manic Rating Scale (F(3.12, 152.86) = 2.71, p = 0.05) was significantly different between treatment groups over 12-months, with scores at 9-months and 12-months significantly lower than those at 3-months in the omega-3 group and not in the placebo group. Change in Hamilton Depression Rating Scale, Global Clinical Impression and Global Assessment of Functioning were not different between groups. CONCLUSIONS: Despite a minor reduction in hypomania scores in the omega-3 PUFA group compared to placebo, we find little evidence that the supplementation of omega-3-PUFAs exhibits prophylactic benefit in BD.

Childhood trauma, parental bonding, and social cognition in patients with schizophrenia and healthy adults.

OBJECTIVE: This study investigated associations between childhood trauma, parental bonding, and social cognition (i.e., Theory of Mind and emotion recognition) in patients with schizophrenia and healthy adults. METHODS: Using cross-sectional data, we examined the recollections of childhood trauma experiences and social cognitive abilities in 74 patients with schizophrenia and 116 healthy adults. RESULTS: Patients had significantly higher scores compared with healthy participants on childhood trauma, and lower scores on parental bonding and social cognitive measures. Physical neglect was found to be the strongest predictor of emotion recognition impairments in both groups. Optimal parental bonding attenuated the impact of childhood trauma on emotion recognition. CONCLUSION: The present study provides evidence of an association between physical neglect and emotion recognition in patients with schizophrenia and healthy individuals and shows that both childhood trauma and parental bonding may influence social cognitive development. Psychosocial interventions should be developed to prevent and mitigate the long-term effects of childhood adversities.

Computerised working memory-based cognitive remediation therapy does not affect Reading the Mind in The Eyes test performance or neural activity during a Facial Emotion Recognition test in psychosis.

Working memory-based cognitive remediation therapy (CT) for psychosis has recently been associated with broad improvements in performance on untrained tasks measuring working memory, episodic memory and IQ, and changes in associated brain regions. However, it is unclear whether these improvements transfer to the domain of social cognition and neural activity related to performance on social cognitive tasks. We examined performance on the Reading the Mind in the Eyes test (Eyes test) in a large sample of participants with psychosis who underwent working memory-based CT (N = 43) compared to a control group of participants with psychosis (N = 35). In a subset of this sample, we used functional magnetic resonance imaging (fMRI) to examine changes in neural activity during a facial emotion recognition task in participants who underwent CT (N = 15) compared to a control group (N = 15). No significant effects of CT were observed on Eyes test performance or on neural activity during facial emotion recognition, either at p < 0.05 family-wise error or at a p < 0.001 uncorrected threshold, within a priori social cognitive regions of interest. This study suggests that working memory-based CT does not significantly impact an aspect of social cognition which was measured behaviourally and neurally. It provides further evidence that deficits in the ability to decode mental state from facial expressions are dissociable from working memory deficits, and suggests that future CT programmes should target social cognition in addition to working memory for the purposes of further enhancing social function.

Use of schizophrenia and bipolar disorder polygenic risk scores to identify psychotic disorders.

BACKGROUND: There is increasing evidence for shared genetic susceptibility between schizophrenia and bipolar disorder. Although genetic variants only convey subtle increases in risk individually, their combination into a polygenic risk score constitutes a strong disease predictor.AimsTo investigate whether schizophrenia and bipolar disorder polygenic risk scores can distinguish people with broadly defined psychosis and their unaffected relatives from controls. METHOD: Using the latest Psychiatric Genomics Consortium data, we calculated schizophrenia and bipolar disorder polygenic risk scores for 1168 people with psychosis, 552 unaffected relatives and 1472 controls. RESULTS: Patients with broadly defined psychosis had dramatic increases in schizophrenia and bipolar polygenic risk scores, as did their relatives, albeit to a lesser degree. However, the accuracy of predictive models was modest. CONCLUSIONS: Although polygenic risk scores are not ready for clinical use, it is hoped that as they are refined they could help towards risk reduction advice and early interventions for psychosis.Declaration of interestR.M.M. has received honoraria for lectures from Janssen, Lundbeck, Lilly, Otsuka and Sunovian.

Neurodevelopmental subtypes of bipolar disorder are related to cortical folding patterns: An international multicenter study.

OBJECTIVES: Brain sulcation is an indirect marker of neurodevelopmental processes. Studies of the cortical sulcation in bipolar disorder have yielded mixed results, probably due to high variability in clinical phenotype. We investigated whole-brain cortical sulcation in a large sample of selected patients with high neurodevelopmental load. METHODS: A total of 263 patients with bipolar disorder I and 320 controls were included in a multicentric magnetic resonance imaging (MRI) study. All subjects underwent high-resolution T1-weighted brain MRI. Images were processed with an automatized pipeline to extract the global sulcal index (g-SI) and the local sulcal indices (l-SIs) from 12 a priori determined brain regions covering the whole brain. We compared l-SI and g-SI between patients with and without early-onset bipolar disorder and between patients with and without a positive history of psychosis, adjusting for age, gender and handedness. RESULTS: Patients with early-onset bipolar disorder had a higher l-SI in the right prefrontal dorsolateral region. Patients with psychotic bipolar disorder had a decreased l-SI in the left superior parietal cortex. No group differences in g-SI or l-SI were found between healthy subjects and the whole patient cohort. We could replicate the early-onset finding in an independent cohort. CONCLUSIONS: Our work suggests that bipolar disorder is not associated with generalized abnormalities of sulcation, but rather with localized changes of cortical folding restricted to patients with a heavy neurodevelopmental loading. These findings support the hypothesis that bipolar disorder is heterogeneous but may be disentangled using MRI, and suggest the need for investigations into neurodevelopmental deviations in the disorder.

A polygenic risk score analysis of psychosis endophenotypes across brain functional, structural, and cognitive domains.

This large multi-center study investigates the relationships between genetic risk for schizophrenia and bipolar disorder, and multi-modal endophenotypes for psychosis. The sample included 4,242 individuals; 1,087 patients with psychosis, 822 unaffected first-degree relatives of patients, and 2,333 controls. Endophenotypes included the P300 event-related potential (N = 515), lateral ventricular volume (N = 798), and the cognitive measures block design (N = 3,089), digit span (N = 1,437), and the Ray Auditory Verbal Learning Task (N = 2,406). Data were collected across 11 sites in Europe and Australia; all genotyping and genetic analyses were done at the same laboratory in the United Kingdom. We calculated polygenic risk scores for schizophrenia and bipolar disorder separately, and used linear regression to test whether polygenic scores influenced the endophenotypes. Results showed that higher polygenic scores for schizophrenia were associated with poorer performance on the block design task and explained 0.2% (p = 0.009) of the variance. Associations in the same direction were found for bipolar disorder scores, but this was not statistically significant at the 1% level (p = 0.02). The schizophrenia score explained 0.4% of variance in lateral ventricular volumes, the largest across all phenotypes examined, although this was not significant (p = 0.063). None of the remaining associations reached significance after correction for multiple testing (with alpha at 1%). These results indicate that common genetic variants associated with schizophrenia predict performance in spatial visualization, providing additional evidence that this measure is an endophenotype for the disorder with shared genetic risk variants. The use of endophenotypes such as this will help to characterize the effects of common genetic variation in psychosis.

ENIGMA and the individual: Predicting factors that affect the brain in 35 countries worldwide.

In this review, we discuss recent work by the ENIGMA Consortium (http://enigma.ini.usc.edu) - a global alliance of over 500 scientists spread across 200 institutions in 35 countries collectively analyzing brain imaging, clinical, and genetic data. Initially formed to detect genetic influences on brain measures, ENIGMA has grown to over 30 working groups studying 12 major brain diseases by pooling and comparing brain data. In some of the largest neuroimaging studies to date - of schizophrenia and major depression - ENIGMA has found replicable disease effects on the brain that are consistent worldwide, as well as factors that modulate disease effects. In partnership with other consortia including ADNI, CHARGE, IMAGEN and others1, ENIGMA's genomic screens - now numbering over 30,000 MRI scans - have revealed at least 8 genetic loci that affect brain volumes. Downstream of gene findings, ENIGMA has revealed how these individual variants - and genetic variants in general - may affect both the brain and risk for a range of diseases. The ENIGMA consortium is discovering factors that consistently affect brain structure and function that will serve as future predictors linking individual brain scans and genomic data. It is generating vast pools of normative data on brain measures - from tens of thousands of people - that may help detect deviations from normal development or aging in specific groups of subjects. We discuss challenges and opportunities in applying these predictors to individual subjects and new cohorts, as well as lessons we have learned in ENIGMA's efforts so far.

Neuropsychiatric syndromes of multiple sclerosis.

Neuropsychiatric signs and symptoms occur frequently in individuals with multiple sclerosis (MS), either as the initial presenting complaint prior to a definitive neurological diagnosis or more commonly with disease progression. However, the pathogenesis of these comorbid conditions remains unclear and it remains difficult to accurately elucidate if neuropsychiatric symptoms or conditions are indicators of MS illness severity. Furthermore, both the disease process and the treatments of MS can adversely impact an individual's mental health. In this review, we discuss the common neuropsychiatric syndromes that occur in MS and describe the clinical symptoms, aetiology, neuroimaging findings and management strategies for these conditions.

White matter deficits in schizophrenia are global and don't progress with age.

INTRODUCTION: Diffusion tensor imaging has revealed differences in all examined white matter tracts in schizophrenia, with a range of explanations for why this may be. The distribution and timing of differences may help explain their origin; however, results are usually dependent on the analytical method. We therefore sought to examine the extent of differences and their relationship with age using two different methods. METHODS: A combined voxel-based whole-brain study and a tract-based spatial-statistics study of 104 patients with schizophrenia and 200 matched healthy controls, aged between 17 and 63 years. RESULTS: Fractional anisotropy was reduced throughout the brain in both analyses. The relationship of fractional anisotropy with age differed between patients and controls, with controls showing the gentle fractional anisotropy decline widely noted but patients showing an essentially flat relationship: younger patients had lower fractional anisotropy than controls, but the difference disappeared with age. Mean diffusivity was widely increased in patients. CONCLUSION: Reduction in fractional anisotropy and increase in mean diffusivity would be consistent with global disruption in myelination; the relationship with age would suggest this is present already at the onset of their illness, but does not progress.