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Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenia's alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia., (© 2024. The Author(s).)

Converging evidence suggests that schizophrenia (SZ) with primary, enduring negative symptoms (i.e., Deficit SZ (DSZ)) represents a distinct entity within the SZ spectrum while the neurobiological underpinnings remain undetermined. In the largest dataset of DSZ and Non-Deficit (NDSZ), we conducted a meta-analysis of data from 1560 individuals (168 DSZ, 373 NDSZ, 1019 Healthy Controls (HC)) and a mega-analysis of a subsampled data from 944 individuals (115 DSZ, 254 NDSZ, 575 HC) collected across 9 worldwide research centers of the ENIGMA SZ Working Group (8 in the mega-analysis), to clarify whether they differ in terms of cortical morphology. In the meta-analysis, sites computed effect sizes for differences in cortical thickness and surface area between SZ and control groups using a harmonized pipeline. In the mega-analysis, cortical values of individuals with schizophrenia and control participants were analyzed across sites using mixed-model ANCOVAs. The meta-analysis of cortical thickness showed a converging pattern of widespread thinner cortex in fronto-parietal regions of the left hemisphere in both DSZ and NDSZ, when compared to HC. However, DSZ have more pronounced thickness abnormalities than NDSZ, mostly involving the right fronto-parietal cortices. As for surface area, NDSZ showed differences in fronto-parietal-temporo-occipital cortices as compared to HC, and in temporo-occipital cortices as compared to DSZ. Although DSZ and NDSZ show widespread overlapping regions of thinner cortex as compared to HC, cortical thinning seems to better typify DSZ, being more extensive and bilateral, while surface area alterations are more evident in NDSZ. Our findings demonstrate for the first time that DSZ and NDSZ are characterized by different neuroimaging phenotypes, supporting a nosological distinction between DSZ and NDSZ and point toward the separate disease hypothesis., (© 2023. The Author(s).)

Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.

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.

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., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta-Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1-weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed-effects models and mega-analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = -0.20), cornu ammonis (CA)1 (d = -0.18), CA2/3 (d = -0.11), CA4 (d = -0.19), molecular layer (d = -0.21), granule cell layer of dentate gyrus (d = -0.21), hippocampal tail (d = -0.10), subiculum (d = -0.15), presubiculum (d = -0.18), and hippocampal amygdala transition area (d = -0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non-users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

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., (© 2021. The Author(s).)

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates., (© 2020. The Author(s).)

Importance: Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood., Objective: To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia., Design, Setting, and Participants: Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244., Main Outcomes and Measures: Interregional profiles of group difference in cortical thickness between cases and controls., Results: A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders., Conclusions and Relevance: In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.

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.

Background: Substance use disorders (SUDs) occur frequently in patients with psychotic disorders and have been associated with various demographic and clinical correlates. There is an absence of research on the prevalence and clinical correlates of SUDs in psychotic disorders in low-and-middle-income countries (LMICs)., Aim: We aimed to determine the prevalence and correlates of SUDs in psychotic disorders., Setting: Patients attending a large secondary-level psychiatric hospital in Cape Town South Africa., Methods: We used the Structured Clinical Interview for DSM-IV (SCID-I) to determine psychiatric and substance use diagnoses, depressive, anxiety, obsessive-compulsive and post-traumatic symptoms. We used logistic regression models to determine significant predictors of SUDs., Results: In total sample ( N = 248), 55.6% of participants had any SUD, 34.3% had cannabis use disorders, 30.6% alcohol use disorders, 27.4% methamphetamine use disorders, 10.4% methaqualone use disorders and 4.8% had other SUDs. There were significant associations with male sex for most SUDs, with younger age and Coloured ethnicity for methamphetamine use disorders, and with lower educational attainment for cannabis use disorders. Anxiety symptoms and suicide attempts were significantly associated with alcohol use disorders; a diagnosis of a substance induced psychosis with cannabis and methamphetamine use disorders. Across most SUDs legal problems and criminal involvement were significantly increased., Conclusion: This study found a high prevalence and wide distribution of SUDs in patients with psychotic disorders, consistent with previous work from high income countries. Given clinical correlates, in individuals with psychotic disorders and SUDs it is important to assess anxiety symptoms, suicidality and criminal involvement., Competing Interests: The authors declare that no competing interests exist., (© 2020. The Authors.)

Objective: Extrapyramidal side-effects (EPSE) are frequent in patients treated with antipsychotics and comorbid substance use disorders (SUDs). Methamphetamine has been shown to act as a dopaminergic neurotoxin. We aimed to determine whether EPSE occur more often in patients with psychotic disorders and co-occurring methamphetamine (MA) use disorders, and we examined the relationship between MA use, antipsychotic type, dose and EPSE. Methods: This study was a secondary analysis of data from three separate primary studies. Across all studies, psychiatric and SUD diagnoses were determined using the SCID-I for DSM-IV. EPSE were determined using the Simpson-Angus Scale (SAS) for Parkinsonism, the Barnes Akathisia Rating scale (BARS), and the Abnormal Involuntary Movement Scale (AIMS) for tardive dyskinesia. Participants were classified as having any EPSE if they scored above the cutoff on any of the EPSE scales (SAS, BARS, AIMS). We analyzed data using multivariable logistic regression analysis. Results: The sample included 102 patients with non-affective or affective psychotic disorders. Of the total sample, 65.7% were male, 54.9% had schizophrenia spectrum disorders, 20.5% bipolar type I disorder with psychotic features, 11.7% schizoaffective disorder and 12.7% had substance-induced psychosis. A diagnosis of a methamphetamine use disorder (abuse or dependence) was present in 25.5% of participants. EPSE occurred in 38.2% of patients and were significantly associated with MA use in the unadjusted and adjusted analysis, OR adj  = 4.01, 95% CI [1.07, 14.98], p  = .039. Patients with MA dependence and MA use >3 years were significantly more likely to have EPSE. We found a significant interaction effect between MA use disorders and standardized antipsychotic dose on the occurrence of EPSE, OR adj  = 1.01, 95% CI [1.00, 1.01], p  = .042, with MA users having a disproportionally higher likelihood of having EPSE compared to MA non-users as antipsychotic dosage increased. There were no significant associations of EPSE with comorbid alcohol, cannabis, or methaqualone use disorders. Conclusions: Patients with a MA use disorder were significantly more likely to have EPSE with evidence for a dose-response effect. Clinicians should carefully titrate antipsychotic dosage from lower to higher doses to avoid EPSE in patients with MA use disorders.

Fronto-limbic white matter (WM) abnormalities are assumed to lie at the heart of the pathophysiology of bipolar disorder (BD); however, diffusion tensor imaging (DTI) studies have reported heterogeneous results and it is not clear how the clinical heterogeneity is related to the observed differences. This study aimed to identify WM abnormalities that differentiate patients with BD from healthy controls (HC) in the largest DTI dataset of patients with BD to date, collected via the ENIGMA network. We gathered individual tensor-derived regional metrics from 26 cohorts leading to a sample size of N = 3033 (1482 BD and 1551 HC). Mean fractional anisotropy (FA) from 43 regions of interest (ROI) and average whole-brain FA were entered into univariate mega- and meta-analyses to differentiate patients with BD from HC. Mega-analysis revealed significantly lower FA in patients with BD compared with HC in 29 regions, with the highest effect sizes observed within the corpus callosum (R 2  = 0.041, P corr  < 0.001) and cingulum (right: R 2  = 0.041, left: R 2  = 0.040, P corr  < 0.001). Lithium medication, later onset and short disease duration were related to higher FA along multiple ROIs. Results of the meta-analysis showed similar effects. We demonstrated widespread WM abnormalities in BD and highlighted that altered WM connectivity within the corpus callosum and the cingulum are strongly associated with BD. These brain abnormalities could represent a biomarker for use in the diagnosis of BD. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.

Background: The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group., Methods: The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide., Results: Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset., Conclusions: The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia., (Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

The regional distribution of white matter (WM) abnormalities in schizophrenia remains poorly understood, and reported disease effects on the brain vary widely between studies. In an effort to identify commonalities across studies, we perform what we believe is the first ever large-scale coordinated study of WM microstructural differences in schizophrenia. Our analysis consisted of 2359 healthy controls and 1963 schizophrenia patients from 29 independent international studies; we harmonized the processing and statistical analyses of diffusion tensor imaging (DTI) data across sites and meta-analyzed effects across studies. Significant reductions in fractional anisotropy (FA) in schizophrenia patients were widespread, and detected in 20 of 25 regions of interest within a WM skeleton representing all major WM fasciculi. Effect sizes varied by region, peaking at (d=0.42) for the entire WM skeleton, driven more by peripheral areas as opposed to the core WM where regions of interest were defined. The anterior corona radiata (d=0.40) and corpus callosum (d=0.39), specifically its body (d=0.39) and genu (d=0.37), showed greatest effects. Significant decreases, to lesser degrees, were observed in almost all regions analyzed. Larger effect sizes were observed for FA than diffusivity measures; significantly higher mean and radial diffusivity was observed for schizophrenia patients compared with controls. No significant effects of age at onset of schizophrenia or medication dosage were detected. As the largest coordinated analysis of WM differences in a psychiatric disorder to date, the present study provides a robust profile of widespread WM abnormalities in schizophrenia patients worldwide. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.

Electroencephalography (EEG) has been proposed as a neurophysiological biomarker to delineate psychotic disorders. It is known that increased delta and decreased alpha, which are apparent in psychosis, are indicative of inappropriate arousal state, which leads to reduced ability to attend to relevant information. On this premise, we investigated delta/alpha frequency activity, as this ratio of frequency activity may serve as an effective neurophysiological biomarker. The current study investigated differences in delta/alpha frequency activity, in schizophrenia (SCZ), bipolar I disorder with psychotic features and methamphetamine-induced psychosis. One hundred and nine participants, including individuals with SCZ (n = 28), bipolar I disorder with psychotic features (n = 28), methamphetamine-induced psychotic disorder (MPD) (n = 24) and healthy controls (CON, n = 29). Diagnosis was ascertained with the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, 4th Edition disorders and current medication was recorded. EEG was undertaken in three testing conditions: resting eyes open, resting eyes closed and during completion of a simple cognitive task (visual continuous performance task). EEG delta/alpha frequency activity was investigated across these conditions. First, delta/alpha frequency activity during resting eyes closed was higher in SCZ and MPD globally, when compared to CON, then lower for bipolar disorder (BPD) than MPD for right hemisphere. Second, delta/alpha frequency activity during resting eyes open was higher in SCZ, BPD and MPD for all electrodes, except left frontal, when compared to CON. Third, delta/alpha frequency activity during the cognitive task was higher in BPD and MPD for all electrodes, except left frontal, when compared to CON. Assessment of EEG delta/alpha frequency activity supports the delineation of underlying neurophysiological mechanisms present in psychotic disorders, which are likely related to dysfunctional thalamo-cortical connectivity. Delta/alpha frequency activity may provide a useful neurophysiological biomarker to delineate psychotic disorders.

Background: Up to 75% of people with serious mental illness (SMI) such as schizophrenia and bipolar disorder have co-occurring substance use disorders (dual diagnosis). Dual diagnosis can have an adverse effect on treatment and prognosis of SMI., Objectives: To evaluate the effects of risperidone compared to treatment with other antipsychotics (first-generation and other second-generation antipsychotics) used in people with serious mental illness and co-occurring substance misuse., Search Methods: On 6 January 2016 and 9 October 2017, we searched the Cochrane Schizophrenia Group's Study-Based Register of Trials (including trial registers)., Selection Criteria: We selected randomised trials of risperidone versus any other antipsychotic in people with SMI and substance abuse (dual diagnosis). We included trials meeting our inclusion criteria and reporting useable data. We excluded trials that either did not meet our inclusion criteria or met our inclusion criteria but did not report any useable data., Data Collection and Analysis: We independently inspected citations and selected studies. For included studies, we independently extracted data and appraised study quality. For binary outcomes we calculated the risk ratios (RRs) and their 95% confidence intervals. For continuous outcomes we calculated the mean differences (MDs) and their 95% confidence intervals. We pooled data using random-effects meta-analyses and assessed the quality of evidence, creating a 'Summary of findings' table using the GRADE approach., Main Results: We identified eight randomised trials containing a total of 1073 participants with SMI and co-occurring substance misuse. Seven of these contributed useable data to the review. There was heterogeneity in trial design and measurement. Risperidone was compared to clozapine, olanzapine, perphenazine, quetiapine and ziprasidone. Few trials compared risperidone with first-generation agents. Few trials examined participants with a dual diagnosis from the outset and most trials only contained separate analyses of subgroups with a dual diagnosis or were secondary data analyses of subgroups of people with a dual diagnosis from existing larger trials.For risperidone versus clozapine we found no clear differences between these two antipsychotics in the reduction of positive psychotic symptoms (1 randomised controlled trial (RCT), n = 36, mean difference (MD) 0.90, 95% CI -2.21 to 4.01, very low quality evidence), or reduction in cannabis use (1 RCT, n = 14, risk ratio (RR) 1.00, 95% CI 0.30 to 3.35, very low quality evidence), improvement in subjective well-being (1 RCT, n = 36, MD -6.00, 95% CI -14.82 to 2.82, very low quality evidence), numbers discontinuing medication (1 RCT, n = 36, RR 4.05, 95% CI 0.21 to 78.76, very low quality evidence), extrapyramidal side-effects (2 RCTs, n = 50, RR 2.71, 95% CI 0.30 to 24.08; I² = 0%, very low quality evidence), or leaving the study early (2 RCTs, n = 45, RR 0.49, 95% CI 0.10 to 2.51; I² = 34%, very low quality evidence). Clozapine was associated with lower levels of craving for cannabis (1 RCT, n = 28, MD 7.00, 95% CI 2.37 to 11.63, very low quality evidence).For risperidone versus olanzapine we found no clear differences in the reduction of positive psychotic symptoms (1 RCT, n = 37, MD -1.50, 95% CI -3.82 to 0.82, very low quality evidence), reduction in cannabis use (1 RCT, n = 41, MD 0.40, 95% CI -4.72 to 5.52, very low quality evidence), craving for cannabis (1 RCT, n = 41, MD 5.00, 95% CI -4.86 to 14.86, very low quality evidence), parkinsonism (1 RCT, n = 16, MD -0.08, 95% CI -1.21 to 1.05, very low quality evidence), or leaving the study early (2 RCT, n = 77, RR 0.68, 95% CI 0.34 to 1.35; I² = 0%, very low quality evidence).For risperidone versus perphenazine, we found no clear differences in the number of participants leaving the study early (1 RCT, n = 281, RR 1.05, 95% CI 0.92 to 1.20, low-quality evidence).For risperidone versus quetiapine, we found no clear differences in the number of participants leaving the study early (1 RCT, n = 294, RR 0.96, 95% CI 0.86 to 1.07, low-quality evidence).For risperidone versus ziprasidone, we found no clear differences in the number of participants leaving the study early (1 RCT, n = 240, RR 0.96, 95% CI 0.85 to 1.10, low-quality evidence).For many comparisons, important outcomes were missing; and no data were reported in any study for metabolic disturbances, global impression of illness severity, quality of life or mortality., Authors' Conclusions: There is not sufficient good-quality evidence available to determine the effects of risperidone compared with other antipsychotics in people with a dual diagnosis. Few trials compared risperidone with first-generation agents, leading to limited applicability to settings where access to second-generation agents is limited, such as in low- and middle-income countries. Moreover, heterogeneity in trial design and measurement of outcomes precluded the use of many trials in our analyses. Future trials in this area need to be sufficiently powered but also need to conform to consistent methods in study population selection, use of measurement scales, definition of outcomes, and measures to counter risk of bias. Investigators should adhere to CONSORT guidelines in the reporting of results.

Background: In contrast to findings from the developed world where general practitioners and mental health professionals are central in first episode psychosis pathways, studies from Africa have found GPs to play a less prominent role with other help providers such as traditional healers being more important., Methods: We compared pathways to care, treatment delays and gender differences in patients with first versus multi episode psychosis., Results: Private sector GPs were first contacts in first episode patients in as many as 38% of patients and were significantly more likely to be the first contact (odds ratio = 4.5, 95% CI = 1.38-14.67) and final referring agent (odds ratio = 6.8, 95% CI = 1.56-25.12) in first episode patients. Female multi episode patients were significantly more likely to make first contact with primary care practitioners whereas male multi episode patients were more likely to first come into contact with the police (P = 0.003) and be admitted compulsorily (P = 0.009). Only 5.6% (n = 4) of patients contacted traditional healers at some point in their pathway to care. Treatment delays and DUP in first episode patients were longer and reached a median of 4.5 versus 2.5 months in multi episode patients. Treatment discontinuation of antipsychotics occurred in 82% of multi episode patients. Despite significantly longer overall treatment delays in first episode patients the distribution of treatment delays in multi episode patients followed a similar pattern to DUP in first episode patients with a subgroup having very long delays., Conclusions: Pathways to care in this treatment setting correspond more to findings from first world and newly industrialized countries. A subgroup of multi episode patients had very long periods of untreated illness. Limitations include small sample size and the retrospective nature of data collection.