397 research outputs found

    Previous hospital admissions and disease severity predict the use of antipsychotic combination treatment in patients with schizophrenia

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    <p>Abstract</p> <p>Background</p> <p>Although not recommended in treatment guidelines, previous studies have shown a frequent use of more than one antipsychotic agent among patients with schizophrenia. The main aims of the present study were to explore the antipsychotic treatment regimen among patients with schizophrenia in a catchment area-based sample and to investigate clinical characteristics associated with antipsychotic combination treatment.</p> <p>Methods</p> <p>The study included 329 patients diagnosed with schizophrenia using antipsychotic medication. Patients were recruited from all psychiatric hospitals in Oslo. Diagnoses were obtained by use of the Structured Clinical Interview for DSM-IV Axis I disorders (SCID-I). Additionally, Global Assessment of Functioning (GAF), Positive and Negative Syndrome Scale (PANSS) and number of hospitalisations and pharmacological treatment were assessed.</p> <p>Results</p> <p>Multiple hospital admissions, low GAF scores and high PANSS scores, were significantly associated with the prescription of combination treatment with two or more antipsychotics. The use of combination treatment increased significantly from the second hospital admission. Combination therapy was not significantly associated with age or gender. Regression models confirmed that an increasing number of hospital admission was the strongest predictor of the use of two or more antipsychotics.</p> <p>Conclusions</p> <p>Previous hospital admissions and disease severity measured by high PANSS scores and low GAF scores, predict the use of antipsychotic combination treatment in patients with schizophrenia. Future studies should further explore the use of antipsychotic drug treatment in clinical practice and partly based on such data establish more robust treatment guidelines for patients with persistently high symptom load.</p

    Cortical folding in Broca's area relates to obstetric complications in schizophrenia patients and healthy controls

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    Background The increased occurrence of obstetric complications (OCs) in patients with schizophrenia suggests that alterations in neurodevelopment may be of importance to the aetiology of the illness. Abnormal cortical folding may reflect subtle deviation from normal neurodevelopment during the foetal or neonatal period. In the present study, we hypothesized that OCs would be related to cortical folding abnormalities in schizophrenia patients corresponding to areas where patients with schizophrenia display altered cortical folding when compared with healthy controls. Method In total, 54 schizophrenia patients and 54 healthy control subjects underwent clinical examination and magnetic resonance image scanning on a 1.5 T scanner. Information on OCs was collected from original birth records. An automated algorithm was used to calculate a three-dimensional local gyrification index (lGI) at numerous points across the cortical mantle. Results In both schizophrenia patients and healthy controls, an increasing number of OCs was significantly related to lower lGI in the left pars triangularis (p<0.0005) in Broca's area. For five other anatomical cortical parcellations in the left hemisphere, a similar trend was demonstrated. No significant relationships between OCs and lGI were found in the right hemisphere and there were no significant case-control differences in lGI. Conclusions The reduced cortical folding in the left pars triangularis, associated with OCs in both patients and control subjects suggests that the cortical effect of OCs is caused by factors shared by schizophrenia patients and healthy controls rather than factors related to schizophrenia alon

    Obstetric complications and intelligence in patients on the schizophrenia-bipolar spectrum and healthy participants

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    Background Whether severe obstetric complications (OCs), which harm neural function in offspring, contribute to impaired cognition found in psychiatric disorders is currently unknown. Here, we sought to evaluate how a history of severe OCs is associated with cognitive functioning, indicated by Intelligence Quotient (IQ). Methods We evaluated the associations of a history of OCs and IQ in 622 healthy controls (HC) and 870 patients on the schizophrenia (SCZ) – bipolar disorder (BIP) spectrum from the ongoing Thematically Organized Psychosis study cohort, Oslo, Norway. Participants underwent assessments using the NART (premorbid IQ) and the WASI (current IQ). Information about OCs was obtained from the Medical Birth Registry of Norway. Multiple linear regression models were used for analysis. Results Severe OCs were equally common across groups. SCZ patients with OCs had lower performances on both premorbid and current IQ measures, compared to those without OCs. However, having experienced more than one co-occurring severe OC was associated with lower current IQ in all groups. Conclusions Severe OCs were associated with lower IQ in the SCZ group and in the BIP and HC groups, but only if they had experienced more than one severe OC. Low IQ might be a neurodevelopmental marker for SCZ; wherein, severe OCs influence cognitive abilities and increase the risk of developing SCZ. Considering OCs as a variable of neurodevelopmental risk for severe mental illness may promote the development of neuroprotective interventions, improve outcome in vulnerable newborns and advance our ability to make clinical prognoses

    Healthy Adolescent Performance With Standardized Scoring Tables for the MATRICS Consensus Cognitive Battery: A Multisite Study.

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    The aim of this study was to develop standardized scores and scoring tables for test performance in healthy adolescents for the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) for each year from 11 to 19 years of age, by sex, with T scores and percentile ranks.A total of 502 healthy participants (aged 11-19 years) from 7 cohorts from Ireland, Norway, Sweden, and United States, were included in this multisite study. Regression-predicted means for the MCCB tests, except the social cognition subtest, were calculated using the MCCB test scores as outcome variables and age, age2, sex, age × sex as predictors. The regression-predicted means for each combination of age and sex were added with the residuals from the entire cohort to yield the expected distribution of that group. Age effects were examined using regression models with age and age2 as predictors. Sex differences were examined using Student\u27s t-tests.Significant positive age effects were found for all tests, except for the Brief Visuospatial Memory Test, revised (BVMT-R; measure of visual learning). Females performed significantly better than males on BACS Symbol coding (measure of speed of processing) and BVMT-R, while males performed significantly better than females on NAB Mazes (measure of reasoning and problem solving). Based on the regression-predicted distributions of scores, 19 standardized scoring tables for each test and domain were created.With the results from this study, we have developed an accessible standardized data set of healthy adolescent test performance for the MCCB

    Impact of second-generation antipsychotics on white matter microstructure in adolescent-onset psychosis

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    White matter abnormalities are well-established in adult patients with psychosis. Yet less is known about changes in early onset psychosis (EOP) during adolescence, especially whether antipsychotic medication might impact white matter microstructure in this sensitive phase. Here, we utilized Magnetic Resonance Imaging (MRI) in unmedicated and medicated adolescent EOP patients in comparison to healthy controls to examine the impact of antipsychotic medication status on indices of white matter microstructure. Twenty-two EOP patients (11 unmedicated) and 33 healthy controls, aged between 12-18 years, underwent 3T diffusion-weighted MRI. Using Tract-based Spatial Statistics, we calculate case-control differences in scalar diffusion measures, e.g. fractional anisotropy (FA), and investigated their association with antipsychotic medication. We replicated previous results from studies in EOP patients showing significantly decreased mean FA including the left genu of the corpus callosum, the left anterior corona radiata and the right superior longitudinal fasciculus in patients relative to healthy controls. Mean FA in the left anterior corona radiata was significantly associated with antipsychotic medication status, showing higher FA values in medicated compared to unmedicated EOP patients. Increased regional FA values might be a first hint towards an early effect of antipsychotic medication on white matter microstructure in adolescent EOP patients

    Lower plasma total tau in adolescent psychosis: Involvement of the orbitofrontal cortex

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    Schizophrenia is thought to be a neurodevelopmental disorder with neuronal migration, differentiation and maturation disturbances. Tau is a microtubule-associated protein with a crucial role in these processes. Lower circulating tau levels have been reported in adults with schizophrenia, but this association has not been investigated in adolescent psychosis. We aimed to test the hypotheses that a) adolescents with early-onset psychosis (EOP; age of onset <18 years) display lower plasma tau concentrations compared to healthy controls, and b) among patients with psychosis, tau levels are linked to structural brain measures associated with the microtubule-associated tau (MAPT) gene and psychosis. We included 37 adolescent patients with EOP (mean age 16.4 years) and 59 adolescent healthy controls (mean age 16.2 years). We investigated putative patient-control differences in plasma total tau concentrations measured by a Single molecule array (Simoa) immunoassay. We explored the correlations between tau and selected structural brain measures based on T1-weighted MRI scans processed in FreeSurfer v6.0. We found significantly lower plasma tau concentrations in patients compared to healthy controls (p = 0.017, partial eta-squared = 0.061). Tau was not associated with antipsychotic use or the antipsychotic dosage. Among patients but not healthy controls, tau levels were positively correlated with the cortical orbitofrontal surface area (p = 0.013, R-squared = 0.24). The results are suggestive of a tau-related neurodevelopmental disturbance in adolescent psychosis

    Patterns of childhood adverse events are associated with clinical characteristics of bipolar disorder

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    Background Previous studies in bipolar disorder investigating childhood trauma and clinical presentations of the illness have mainly focused on physical and sexual abuse. Our aim was to explore further the relationship between childhood trauma and disease characteristics in bipolar disorder to determine which clinical characteristics were most strongly associated with childhood trauma total score, as well as subtypes of adverse childhood events, including physical, sexual, emotional abuse and neglect. Methods 141 Patients with bipolar disorder were consecutively recruited, and disease history and clinical characteristics were assessed. History of childhood abuse was obtained using the Childhood Trauma Questionnaire (CTQ). Statistical methods used were factor analysis, Poisson and linear regression, and generalized additive modeling (GAM). Results The factor analysis of CTQ identified three factors: emotional abuse/neglect, sexual abuse and physical abuse. There were significant associations between CTQ total score and earlier onset of illness, reduced level of psychosocial functioning (GAF; Global Assessment of Functioning) and decreased number of hospitalization, which mainly were due to the factor emotional abuse/neglect. Physical abuse was significantly associated with lower GAF scores, and increased number of mood episodes, as well as self-harm. Sexual abuse was significantly associated with increased number of mood episodes. For mood episodes and self-harm the associations were characterized by great variance and fluctuations. Conclusions Our results suggest that childhood trauma is associated with a more severe course of bipolar illness. Further, childhood abuse (physical and sexual), as well as emotional abuse and neglect were significantly associated with accelerating staging process of bipolar disorder. By using specific trauma factors (physical abuse, sexual abuse and emotional abuse/neglect) the associations become both more precise, and diverse

    Increased ventral striatal volume in college-aged binge drinkers

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    BACKGROUND Binge drinking is a serious public health issue associated with cognitive, physiological, and anatomical differences from healthy individuals. No studies, however, have reported subcortical grey matter differences in this population. To address this, we compared the grey matter volumes of college-age binge drinkers and healthy controls, focusing on the ventral striatum, hippocampus and amygdala. METHOD T1-weighted images of 19 binge drinkers and 19 healthy volunteers were analyzed using voxel-based morphometry. Structural data were also covaried with Alcohol Use Disorders Identification Test (AUDIT) scores. Cluster-extent threshold and small volume corrections were both used to analyze imaging data. RESULTS Binge drinkers had significantly larger ventral striatal grey matter volumes compared to controls. There were no between group differences in hippocampal or amygdalar volume. Ventral striatal, amygdalar, and hippocampal volumes were also negatively related to AUDIT scores across groups. CONCLUSIONS Our findings stand in contrast to the lower ventral striatal volume previously observed in more severe forms of alcohol use disorders, suggesting that college-age binge drinkers may represent a distinct population from those groups. These findings may instead represent early sequelae, compensatory effects of repeated binge and withdrawal, or an endophenotypic risk factor

    Morphological correlates to cognitive dysfunction in schizophrenia as studied with Bayesian regression

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    BACKGROUND: Relationships between cognitive deficits and brain morphological changes observed in schizophrenia are alternately explained by less gray matter in the brain cerebral cortex, by alterations in neural circuitry involving the basal ganglia, and by alteration in cerebellar structures and related neural circuitry. This work explored a model encompassing all of these possibilities to identify the strongest morphological relationships to cognitive skill in schizophrenia. METHODS: Seventy-one patients with schizophrenia and sixty-five healthy control subjects were characterized by neuropsychological tests covering six functional domains. Measures of sixteen brain morphological structures were taken using semi-automatic and fully manual tracing of MRI images, with the full set of measures completed on thirty of the patients and twenty controls. Group differences were calculated. A Bayesian decision-theoretic method identified those morphological features, which best explained neuropsychological test scores in the context of a multivariate response linear model with interactions. RESULTS: Patients performed significantly worse on all neuropsychological tests except some regarding executive function. The most prominent morphological observations were enlarged ventricles, reduced posterior superior vermis gray matter volumes, and increased putamen gray matter volumes in the patients. The Bayesian method associated putamen volumes with verbal learning, vigilance, and (to a lesser extent) executive function, while caudate volumes were associated with working memory. Vermis regions were associated with vigilance, executive function, and, less strongly, visuo-motor speed. Ventricular volume was strongly associated with visuo-motor speed, vocabulary, and executive function. Those neuropsychological tests, which were strongly associated to ventricular volume, showed only weak association to diagnosis, possibly because ventricular volume was regarded a proxy for diagnosis. Diagnosis was strongly associated with the other neuropsychological tests, implying that the morphological associations for these tasks reflected morphological effects and not merely group volumetric differences. Interaction effects were rarely associated, indicating that volumetric relationships to neuropsychological performance were similar for both patients and controls. CONCLUSION: The association of subcortical and cerebellar structures to verbal learning, vigilance, and working memory supports the importance of neural connectivity to these functions. The finding that a morphological indicator of diagnosis (ventricular volume) provided more explanatory power than diagnosis itself for visuo-motor speed, vocabulary, and executive function suggests that volumetric abnormalities in the disease are more important for cognition than non-morphological features

    Effects of copy number variations on brain structure and risk for psychiatric illness: large-scale studies from the ENIGMA working groups on CNVs

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    The Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q-ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest-ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi-site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene-dosage effects on distinct brain regions also emerged, providing further insight into genotype-phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This "genotype-first" approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior.Funding information: European Union's Horizon2020 Research and Innovation Programme, Grant/Award Number: CoMorMent project; Grant #847776; KG Jebsen Stiftelsen; National Institutes of Health, Grant/Award Number: U54 EB020403; Norges Forskningsråd, Grant/Award Number: #223273; South-Eastern Norway Regional Health Authority, Grant/Award Number: #2020060ACKNOWLEDGMENTS: The ENIGMA Consortium is supported by the NIH Big Data to Knowledge (BD2K) program under consortium grant number U54 EB020403 (PI: Thompson). OAA is supported by the Research Council of Norway, South East Norway Health Authority, KG Jebsen Stiftelsen, EU H2020. C. A. has been funded by the Spanish Ministry of Science and Innovation; Instituto de Salud Carlos III (SAM16PE07CP1, PI16/02012, PI19/ 024), co-financed by ERDF Funds from the European Commission, “A way of making Europe”, CIBERSAM; Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), European Union Structural Funds; European Union Seventh Framework Program under grant agreements FP7-4-HEALTH-2009-2.2.1-2-241,909 (Project EU-GEI), FP7- HEALTH-2013-2.2.1-2-603,196 (Project PSYSCAN) and FP7- HEALTH-2013- 2.2.1-2-602,478 (Project METSY); and European Union H2020 Program under the Innovative Medicines Initiative two Joint Undertaking (grant agreement No 115916, Project PRISM, and grant agreement No 777394, Project AIMS-2-TRIALS), Fundación Familia Alonso and Fundación Alicia Koplowitz. R. A-A is funded by a Miguel Servet contract from the Carlos III Health Institute (CP18/00003). G. B. is supported by the Dutch Organization for Health Research and Development ZonMw (grants 91112002 & 91712394). A. S. B. is supported by the Dalglish Family Chair in 22q11.2 Deletion Syndrome, Canadian Institutes of Health Research (CIHR) grants MOP-79518, MOP89066, MOP-97800 and MOP-111238, and NIMH grant number U01 MH101723–01(3/5). C. E. B. is also supported by the National Institute of Mental Health: RO1 MH085953, R01 MH100900 and 1U01MH119736. N. E. B. is granted the KNAW Academy Professor Award (PAH/6635). V. D. C. is supported by NIH R01 MH094524. S. C. is supported by the European Union's Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 945539 (Human Brain Project SGA3); Helmholtz Initiative and Networking Fund. C. R. K. C. is supported by NIA T32AG058507. E. W. C. C. is supported by the Canadian Institutes of Health Research, Ontario Mental Health Foundation grant MOP-74631 and NIMH grant U01MH101723–01(3/5). S. Ci. has received funding from the European Union's Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 945539 (Human Brain Project SGA3). M. C. C. is supported by the Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. N. A. C. is supported by Agencia Nacional de Investigación y Desarrollo (ANID Chile) PIA ACT192064. GId. Z. is supported by the NHMRC. J. L. D. and D. E. J. L. are supported by the Wellcome Trust. T. B. C. is supported by NICHD grant PO1-HD070454, NIH grant UO1-MH191719, and NIMH grant R01 MH087636-01A1. AMD is supported by U24DA041147. B. D. is supported by the Swiss National Science Foundation (NCCR Synapsy, project grant numbers 32003B_135679, 32003B_159780, 324730_192755 and CRSK3_190185), the Leenaards Foundation and the Roger De Spoelberch Foundation. SE is supported by the NARSAD-Young Investigator Grant “Epigenetic Regulation of Intermediate Phenotypes in Schizophrenia”. B. E. S. is supported by the NIH (NIMH). D. C. G. is supported by NIH grant numbers MH078143, MH083824, AG058464. W. R. K. is supported by NIH/MH R0106824. R. E. G. is supported by NIH/NIMH grant numbers MH087626, MH119737. DMMcD-McG is supported by National Institutes of Mental Health (NIMH), grant numbers MH119737-02; MH191719; and MH087636-01A1. S. E. M. is supported by NHMRC grants APP1103623; APP1158127; APP1172917. TM is supported by Research Council of Norway - grant number 273345. D. G. M. is supported by the National Institute for Health Research Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London and S (European Autism Interventions)/EU AIMS-2-TRIALS, a European Innovative Medicines Initiative Joint Undertaking under grant agreements 115300 and 777394. T. N. was supported by Stiftelsen KG Jebsen under grant number SKGJ-MED-021. R. A. O. is supported by NIMH R01 MH090553. S. Y. S. has been funded by the Canadain Institutes of Health Research. M. J. O. is supported by MRC Centre grant MR/L010305/1 and Wellcome Trust grant 100,202/Z/12/Z; Dr. Owen has received research support from Takeda. Z. P. is supported by CIHR, CFI, HSFC. B. G. P. is supported by CIHR FDN 143290 and CAIP Chair. G. M. R. is supported by Fondecyt-Chile #1171014 and ANID-Chile ACT192064. A. Re. was supported by a grant from the Swiss National Science Foundation (31003A_182632). DRR is supported by R01 MH120174 (PI: Roalf). This report represents independent research funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London (to J. J. R). PSS is supported by NHMRC (Australia) program grant 1093083. J. E. S. is supported by NIH K01-ES026840. S. M. S. is supported by the Epilepsy Society. T. J. S. is supported by NIH grants R01MH107108, R01HD042794, and HDU54079125. I. E. S. is supported by South-Eastern Norway Regional Health Authority (#2020060), European Union's Horizon2020 Research and Innovation Programme (CoMorMent project; grant #847776) and the KG Jebsen Foundation (SKGJ-MED-021). V. M. S. is supported by Research Council of Norway (CoE funding scheme, grant number 223273). D. J. S. is supported by the SA MRC. C. K. T. is supported by Research Council of Norway (#230345, #288083, #223273) and South-Eastern Norway Regional Health Authority (#2019069, #2021070, #500189). D. T.-G. was supported by the Instituto de Salud Carlos III (PI14/00639 and PI14/00918) and Fundación Instituto de Investigación Marqués de Valdecilla (NCT0235832 and NCT02534363). Dvd. M. is supported by Research Council of Norway #276082. F. V. R. is supported by the Michael Smith Foundation for Health Research Scholar Award. deCODE genetics has received support from the Innovative Medicines Initiative Joint Undertaking under grant agreements' no. 115008 (NEWMEDS) and no. 115300 (EUAIMS), of which resources are composed of EFPIA in-kind contribution and financial contribution from the European Union's Seventh Framework Programme (EU-FP7/ 2007–2013). L. T. W. is supported by Research Council of Norway, European Research Council. The IDIVAL neuroimage unit is supported by Instituto de Salud Carlos III PI020499, research funding SCIII-INT13/0014, MICINN research funding SAF2010-20840-C02- 02, SAF2013-46292-R. The TOP/NORMENT study are supported by the Research Council of Norway (#223273). The GOBS study data collection was supported in part by the National Institutes of Health (NIH) grants: R01 MH078143, R01 MH078111, and R01 MH083824 with work conducted in part in facilities constructed under the support of NIH grant number C06 RR020547. The Sydney Memory and Ageing Study has been funded by three National Health & Medical Research Council (NHMRC) Program Grants (ID No. ID350833, ID568969, and APP1093083). We thank the participants and their informants for their time and generosity in contributing to this research. We also acknowledge the MAS research team: https://cheba.unsw.edu.au/researchprojects/sydney-memory-and-ageing-study. We acknowledge the contribution of the OATS research team (https://cheba.unsw.edu.au/ project/older-australian-twins-study) to this study. The OATS study has been funded by a National Health & Medical Research Council (NHMRC) and Australian Research Council (ARC) Strategic Award Grant of the Aging Well, Aging Productively Program (ID No. 401162); NHMRC Project (seed) Grants (ID No. 1024224 and 1025243); NHMRC Project Grants (ID No. 1045325 and 1085606); and NHMRC Program Grants (ID No. 568969 and 1093083). We thank the participants for their time and generosity in contributing to this research. This research was facilitated through access to Twins Research Australia, a national resource supported by a Centre of Research Excellence Grant (ID No. 1079102) from the National Health and Medical Research Council. The NCNG sample collection was supported by grants from the Bergen Research Foundation and the University of Bergen, the Dr Einar Martens Fund, the KG Jebsen Foundation, the Research Council of Norway, to S. L. H., V. M. S., A. J. L., and T. E. The authors thank Dr. Eike Wehling for recruiting participants in Bergen, and Professor Jonn-Terje Geitung and Haraldplass Deaconess Hospital for access to the MRI facility. Additional support by RCN grants 177458/V50 and 231286/F20. The Betula study was supported by a Wallenberg Scholar Grant (KAW). The HUNT Study is a collaboration between HUNT Research Centre (Faculty of Medicine and Health Sciences, NTNU—Norwegian University of Science and Technology), Nord-Trøndelag County Council, Central Norway Health Authority, and the Norwegian Institute of Public Health. HUNT-MRI was funded by the Liaison Committee between the Central Norway Regional Health Authority and the Norwegian University of Science and Technology, and the Norwegian National Advisory Unit for functional MRI. Research for the GAP cohort was supported by the Department of Health via the National Institute for Health Research (NIHR) Specialist Biomedical Research Center for Mental Health award to South London and Maudsley NHS Foundation Trust (SLaM) and the Institute of Psychiatry at King's College London, London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. S.J. is supported by Calcul Quebec (http:// www.calculquebec.ca), Compute Canada (http://www.computecanada. ca), the Brain Canada Multi investigator research initiative (MIRI), the Institute of Data Valorization (Canada First Research Excellence Fund), CHIR, Canada Research Chairs and the Jeanne et Jean Louis Levesque Foundation. The NTR cohort was supported by the Netherlands Organization for Scientific Research (NWO), MW904-61-193 (de Geus & Boomsma), MaGWnr: 400-07-080 (van 't Ent), MagW 480-04-004 (Boomsma), NWO/SPI 56-464-14,192 (Boomsma), the European Research Council, ERC-230374 (Boomsma), and Amsterdam Neuroscience. Funding for genotyping was obtained from the National Institutes of Health (NIMH U24 MH068457-06; Grand Opportunity grants 1RC2 MH089951, and 1RC2 MH089995); the Avera Institute for Human Genetics, Sioux Falls, South Dakota (USA). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health. The Brainscale study was supported by the Netherlands Organization for Scientific Research MagW 480-04-004 (Boomsma), 51.02.060 (Hilleke Hulshoff Pol), 668.772 (Boomsma & Hulshoff Pol); NWO/SPI 56-464-14192 (Boomsma), the European Research Council (ERC230374) (Boomsma), High Potential Grant Utrecht University (Hulshoff Pol), NWO Brain and Cognition 433-09-220 (Hulshoff Pol). SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. Genome-wide SNP typing in SHIP and MRI scans in SHIP and SHIP-TREND have been supported by a joint grant from Siemens Healthcare, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. The ENIGMA-22q11.2 Deletion Syndrome Working Group wishes to acknowledge our dear colleague Dr. Clodagh Murphy, who sadly passed away in April 2020. Open access funding enabled and organized by Projekt DEAL
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