A meta-analysis of deep brain structural shape and asymmetry abnormalities in 2,833 individuals with schizophrenia compared with 3,929 healthy volunteers via the ENIGMA Consortium

Schizophrenia is associated with widespread alterations in subcortical brain structure.While analytic methods have enabled more detailed morphometric characterization,findings are often equivocal. In this meta-analysis, we employed the harmonizedENIGMA shape analysis protocols to collaboratively investigate subcortical brainstructure shape differences between individuals with schizophrenia and healthy con-trol participants. The study analyzed data from 2,833 individuals with schizophreniaand 3,929 healthy control participants contributed by 21 worldwide research groupsparticipating in the ENIGMA Schizophrenia Working Group. Harmonized shape analy-sis protocols were applied to each site's data independently for bilateral hippocam-pus, amygdala, caudate, accumbens, putamen, pallidum, and thalamus obtained fromT1-weighted structural MRI scans. Mass univariate meta-analyses revealed more-concave-than-convex shape differences in the hippocampus, amygdala, accumbens,and thalamus in individuals with schizophrenia compared with control participants,more-convex-than-concave shape differences in the putamen and pallidum, and bothconcave and convex shape differences in the caudate. Patterns of exaggerated asym-metry were observed across the hippocampus, amygdala, and thalamus in individualswith schizophrenia compared to control participants, while diminished asymmetryencompassed ventral striatum and ventral and dorsal thalamus. Our analyses also rev-ealed that higher chlorpromazine dose equivalents and increased positive symptomlevels were associated with patterns of contiguous convex shape differences acrossmultiple subcortical structures. Findings from our shape meta-analysis suggest thatcommon neurobiological mechanisms may contribute to gray matter reduction acrossmultiple subcortical regions, thus enhancing our understanding of the nature of net-work disorganization in schizophrenia

A Disrupted-in-Schizophrenia 1 Gene Variant is Associated with Clinical Symptomatology in Patients with First-Episode Psychosis

OBJECTIVE: DISC1 gene is one of the main candidate genes for schizophrenia since it has been associated to the illness in several populations. Moreover, variations in several DISC1 polymorphisms, and in particular Ser704Cys SNP, have been associated in schizophrenic patients to structural and functional modifications in two brain areas (pre-frontal cortex and hippocampus) that play a central role in the genesis of psychotic symptoms. This study tested the association between Ser704Cys DISC1 polymorphism and the clinical onset of psychosis. METHODS: Two hundred and thirteen Caucasian drug-naive patients experiencing a first episode of non-affective psychosis were genotyped for rs821616 (Ser704Cys) SNP of the DISC1 gene. The clinical severity of the illness was assessed using SAPS and SANS scales. Other clinical and socio-demographic variables were recorded to rule out possible confounding effects. RESULTS: Patients homozygous for the Ser allele of the Ser704Cys DISC1 SNP had significantly (p<0.05) higher rates at the positive symptoms dimension (SAPS-SANS scales) and hallucinations item, compared to Cys carriers. CONCLUSION: DISC1 gene variations may modulate the clinical severity of the psychosis at the onset of the disorde

Pattern of long-Term weight and metabolic changes after a first-episode of psychosis: Results from a 10-years prospective follow-up of the PAFIP cohort

Background: People with psychosis are at higher risk of cardiovascular events, partly explained by a higher predisposition to gain weight. This has been observed in studies on individuals with a first-episode psychosis (FEP) at short and long term (mainly up to 1 year) and transversally at longer term in people with chronic schizophrenia. However, there is scarcity of data regarding longer-term (above 3-year follow-up) weight progression in FEP from longitudinal studies. The aim of this study is to evaluate the longer-term (10 years) progression of weight changes and related metabolic disturbances in people with FEP. Methods: Two hundred and nine people with FEP and 57 healthy participants (controls) were evaluated at study entry and prospectively at 10-year follow-up. Anthropometric, clinical, and sociodemographic data were collected. Results: People with FEP presented a significant and rapid increase in mean body weight during the first year of treatment, followed by less pronounced but sustained weight gain over the study period (?15.2 kg; SD 12.3 kg). This early increment in weight predicted longer-term changes, which were significantly greater than in healthy controls (?2.9 kg; SD 7.3 kg). Weight gain correlated with alterations in lipid and glycemic variables, leading to clinical repercussion such as increments in the rates of obesity and metabolic disturbances. Sex differences were observed, with women presenting higher increments in body mass index than men. Conclusions: This study confirms that the first year after initiating antipsychotic treatment is the critical one for weight gain in psychosis. Besides, it provides evidence that weight gain keep progressing even in the longer term (10 years), causing relevant metabolic disturbances

Understanding sex differences in long-term outcomes after a first episode of psychosis

While sex differences in schizophrenia have long been reported and discussed, long-term sex differences in outcomes among first episode of psychosis (FEP) patients in terms of the efficacy of Early Intervention Services (EIS) has been an under-explored area. A total of 209 FEP patients (95 females and 114 males) were reassessed after a time window ranging from 8 to 16 years after their first contact with an EIS program (PAFIP) that we will call the 10-year PAFIP cohort. Multiple clinical, cognitive, functioning, premorbid, and sociodemographic variables were explored at 1-year, 3-year and 10-year follow-ups. At first contact, females were older at illness onset, had higher premorbid adjustment and IQ, and were more frequently employed, living independently, and accompanied by a partner and/or children. Existence of a schizophrenia diagnosis, and cannabis and alcohol consumption were more probable among men. During the first 3 years, women showed a significantly better response to minimal antipsychotic dosages and higher rates of recovery than men (50% vs. 30.8%). Ten years later, more females continued living independently and had partners, while schizophrenia diagnoses and cannabis consumption continued to be more frequent among men. Females also presented a lower severity of negative symptoms; however, functionality and recovery differences did not show significant differences (46.7% vs. 34.4%). Between the 3- and 10-year follow-up sessions, an increase in dosage of antipsychotics was observed. These results suggest that the better outcomes seen among women during the first 3 years (while they were treated in an EIS) were in the presence of more favourable premorbid and baseline characteristics. After an average period of 10 years, with the only difference being in negative symptoms course, outcomes for women approximated those of men, drawing particular attention to the increase in dosage of antipsychotic medication once FEP patients were discharged from the EIS program towards community-based services. These findings help to pose the question of whether it is advisable to target sexes and lengthen EIS interventions

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

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

Treatment discontinuation impact on long-term (10-years) weight gain and lipid metabolism in first-episode psychosis: results from the PAFIP-10 cohort

Background: patients with a first episode of psychosis (FEP) are at higher risk of gaining weight and presenting metabolic disturbances, partly related to antipsychotic exposure. Previous studies suggest that treatment discontinuation might have a positive impact on weight in schizophrenia. The aim of this study was to evaluate the effect of treatment discontinuation on weight and metabolic changes in a FEP cohort. Methods: a total of 209 FEP patients and 57 healthy controls were evaluated at study entry and prospectively at 10-year follow-up. Anthropometric measures and, clinical, metabolic, and sociodemographic data were collected. Results: patients discontinuing antipsychotic treatment presented a significantly lower increase in weight and better metabolic parameter results than those still on antipsychotic treatment at 10-year follow-up. Conclusions: treatment discontinuation had a positive effect on the weight and metabolic changes observed in FEP patients; however, this effect was not sufficient to reaching a complete reversal to normal levels

Reply to: New Meta- and Mega-analyses of Magnetic Resonance Imaging Findings in Schizophrenia: Do They Really Increase Our Knowledge About the Nature of the Disease Process?

This work was supported by National Institute of Biomedical Imaging and Bioengineering Grant No. U54EB020403 (to the ENIGMA consortium)

Obesity and brain structure in schizophrenia - ENIGMA study in 3021 individuals

Schizophrenia is frequently associated with obesity, which is linked with neurostructural alterations. Yet, we do not understand how the brain correlates of obesity map onto the brain changes in schizophrenia. We obtained MRI-derived brain cortical and subcortical measures and body mass index (BMI) from 1260 individuals with schizophrenia and 1761 controls from 12 independent research sites within the ENIGMA-Schizophrenia Working Group. We jointly modeled the statistical effects of schizophrenia and BMI using mixed effects. BMI was additively associated with structure of many of the same brain regions as schizophrenia, but the cortical and subcortical alterations in schizophrenia were more widespread and pronounced. Both BMI and schizophrenia were primarily associated with changes in cortical thickness, with fewer correlates in surface area. While, BMI was negatively associated with cortical thickness, the significant associations between BMI and surface area or subcortical volumes were positive. Lastly, the brain correlates of obesity were replicated among large studies and closely resembled neurostructural changes in major depressive disorders. We confirmed widespread associations between BMI and brain structure in individuals with schizophrenia. People with both obesity and schizophrenia showed more pronounced brain alterations than people with only one of these conditions. Obesity appears to be a relevant factor which could account for heterogeneity of brain imaging findings and for differences in brain imaging outcomes among people with schizophrenia

Epigenome-wide meta-analysis of blood DNA methylation and its association with subcortical volumes:findings from the ENIGMA Epigenetics Working Group

DNA methylation, which is modulated by both genetic factors and environmental exposures, may offer a unique opportunity to discover novel biomarkers of disease-related brain phenotypes, even when measured in other tissues than brain, such as blood. A few studies of small sample sizes have revealed associations between blood DNA methylation and neuropsychopathology, however, large-scale epigenome-wide association studies (EWAS) are needed to investigate the utility of DNA methylation profiling as a peripheral marker for the brain. Here, in an analysis of eleven international cohorts, totalling 3337 individuals, we report epigenome-wide meta-analyses of blood DNA methylation with volumes of the hippocampus, thalamus and nucleus accumbens (NAcc)-three subcortical regions selected for their associations with disease and heritability and volumetric variability. Analyses of individual CpGs revealed genome-wide significant associations with hippocampal volume at two loci. No significant associations were found for analyses of thalamus and nucleus accumbens volumes. Cluster-based analyses revealed additional differentially methylated regions (DMRs) associated with hippocampal volume. DNA methylation at these loci affected expression of proximal genes involved in learning and memory, stem cell maintenance and differentiation, fatty acid metabolism and type-2 diabetes. These DNA methylation marks, their interaction with genetic variants and their impact on gene expression offer new insights into the relationship between epigenetic variation and brain structure and may provide the basis for biomarker discovery in neurodegeneration and neuropsychiatric conditions

Brain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium

Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18-72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18-73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I2 = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen's d = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions