Quantitative assessment of energy and resource recovery in wastewater treatment plants based on plant-wide simulations.

The growing development of technologies and processes for resource treatment and recovery is offering endless possibilities for creating new plant-wide configurations or modifying existing ones. However, the configurations’ complexity, the interrelation between technologies and the influent characteristics turn decision-making into a complex or unobvious process. In this frame, the Plant-Wide Modelling (PWM) library presented in this paper allows a thorough, comprehensive and refined analysis of different plant configurations that are basic aspects in decision-making from an energy and resource recovery perspective. In order to demonstrate the potential of the library and the need to run simulation analyses, this paper carries out a comparative analysis of WWTPs, from a techno-economic point of view. The selected layouts were (1) a conventional WWTP based on a modified version of the Benchmark Simulation Model No. 2, (2) an upgraded or retrofitted WWTP, and (3) a new Wastewater Resource Recovery Facilities (WRRF) concept denominated as C/N/P decoupling WWTP. The study was based on a preliminary analysis of the organic matter and nutrient energy use and recovery options, a comprehensive mass and energy flux distribution analysis in each configuration in order to compare and identify areas for improvement, and a cost analysis of each plant for different influent COD/TN/TP ratios. Analysing the plants from a standpoint of resources and energy utilization, a low utilization of the energy content of the components could be observed in all configurations. In the conventional plant, the COD used to produce biogas was around 29%, the upgraded plant was around 36%, and 34% in the C/N/P decoupling WWTP. With regard to the self-sufficiency of plants, achieving self-sufficiency was not possible in the conventional plant, in the upgraded plant it depended on the influent C/N ratio, and in the C/N/P decoupling WWTP layout self-sufficiency was feasible for almost all influents, especially at high COD concentrations. The plant layouts proposed in this paper are just a sample of the possibilities offered by current technologies. Even so, the library presented here is generic and can be used to construct any other plant layout, provided that a model is available

Structural brain alterations associated with suicidal thoughts and behaviors in young people: results from 21 international studies from the ENIGMA Suicidal Thoughts and Behaviours consortium

Identifying brain alterations associated with suicidal thoughts and behaviors (STBs) in young people is critical to understanding their development and improving early intervention and prevention. The ENIGMA Suicidal Thoughts and Behaviours (ENIGMA-STB) consortium analyzed neuroimaging data harmonized across sites to examine brain morphology associated with STBs in youth. We performed analyses in three separate stages, in samples ranging from most to least homogeneous in terms of suicide assessment instrument and mental disorder. First, in a sample of 577 young people with mood disorders, in which STBs were assessed with the Columbia Suicide Severity Rating Scale (C-SSRS). Second, in a sample of young people with mood disorders, in which STB were assessed using different instruments, MRI metrics were compared among healthy controls without STBs (HC; N = 519), clinical controls with a mood disorder but without STBs (CC; N = 246) and young people with current suicidal ideation (N = 223). In separate analyses, MRI metrics were compared among HCs (N = 253), CCs (N = 217), and suicide attempters (N = 64). Third, in a larger transdiagnostic sample with various assessment instruments (HC = 606; CC = 419; Ideation = 289; HC = 253; CC = 432; Attempt=91). In the homogeneous C-SSRS sample, surface area of the frontal pole was lower in young people with mood disorders and a history of actual suicide attempts (N = 163) than those without a lifetime suicide attempt (N = 323; FDR-p = 0.035, Cohen's d = 0.34). No associations with suicidal ideation were found. When examining more heterogeneous samples, we did not observe significant associations. Lower frontal pole surface area may represent a vulnerability for a (non-interrupted and non-aborted) suicide attempt; however, more research is needed to understand the nature of its relationship to suicide risk.This work was supported by the MQ Brighter Futures Award MQBFC/2 (LS, LC, LV, MRD, LvV, ALvH, HB) and the U.S. National Institute of Mental Health under Award Number R01MH117601 (LS, LvV, NJ). LvV received funding through the National Suicide Prevention Research Fund, managed by Suicide Prevention Australia. LS is supported by an NHMRC Career Development Fellowship (1140764). ALvH is funded through the Social Safety and Resilience program of Leiden University. SA, NB, FP, and GS acknowledge that data collected in IRCCS Santa Lucia Foundation, Rome, Italy was funded by a study funded by the Italian Ministry of Health grant RC17-18-19-20-21/A. ZB, KC, B K-D acknowledge data collected at the University of Minnesota was funded by the National Institute of Mental Health (K23MH090421), the National Alliance for Research on Schizophrenia and Depression, the University of Minnesota Graduate School, the Minnesota Medical Foundation, and the Biotechnology Research Center (P41 RR008079 to the Center for Magnetic Resonance Research), University of Minnesota, and the Deborah E. Powell Center for Women’s Health Seed Grant, University of Minnesota. HB acknowledges data collected at the Yale School of Medicine, New Haven, CT, USA, was funded by: MQ Brighter Futures, R61MH111929RC1MH088366, R01MH070902, R01MH069747, American Foundation for Suicide Prevention, International Bipolar Foundation, Brain and Behavior Research Foundation, For the Love of Travis Foundation and Women’s Health Research at Yale. LC is supported by Interdisziplinäres Zentrum für Klinische Forschung, UKJ. BCD was funded by a CJ Martin Fellowship (NHMRC app 1161356). BCD research leading to these results has received funding from the program “Investissements d’avenir” ANR-10-IAIHU-06. CGD and BJH acknowledge that data collected in Melbourne, Australia, was supported by Australian National Health and Medical Research Council of Australia (NHMRC) Project Grants 1064643 (principal investigator, BJH) and 1024570 (principal investigator, CGD). BJH and CGD were supported by NHMRC Career Development Fellowships (1124472 and 1061757, respectively). UD and TH acknowledge data collected at the FOR2107-Münster was funded by the German Research Foundation (DFG, grant FOR2107-DA1151/5-1 and DA1151/5-2 to UD, and DFG grants HA7070/2-2, HA7070/3, HA7070/4 to TH). AJ and TK acknowledges data collected at the FOR2107-Marburg was funded by the German Research Foundation (DFG, grant FOR2107-JA 1890/7-1 and JA 1890/7-2 to AJ, and DFG, grant FOR2107-KI588/14-1 and FOR2107-KI588/14-2 to TK). KD acknowledges data collected for the Münster Neuroimaging Cohort was funded by the Medical Faculty Münster, Innovative Medizinische Forschung (Grant IMF KO 1218 06 to KD). JMF, PBM, BJO, and GR acknowledge that the “Kids and Sibs” Study was supported by the Australian National Medical and Health Research Council (Program Grant 1037196 and Investigator Grant 1177991 to PBM, Project Grant 1066177 to JMF), the Lansdowne Foundation, Good Talk and the Keith Pettigrew Family Bequest (PM). JMF gratefully acknowledges the Janette Mary O’Neil Research Fellowship. IHG is supported in part by R37MH101495. Support for TAD comes from the National Institute of Mental Health (K01MH106805). TH acknowledges support for TIGER includes the Klingenstein Third Generation Foundation, the National Institute of Mental Health (K01MH117442), the Stanford Maternal Child Health Research Institute, and the Stanford Center for Cognitive and Neurobiological Imaging. TCH receives partial support from the Ray and Dagmar Dolby Family Fund. KAM, ABM, MAS acknowledge data collected at Harvard University was funded by the National Institute of Mental Health (R01-MH103291). IN is supported by grants of the Deutsche Forschungsgemeinschaft (DFG grants NE2254/1-2, NE2254/3-1, NE2254/4-1).This study was supported by the NationalCenter for Complementary and Integrative Health (NCCIH) R21AT009173 and R61AT009864 to TTY; by the National Center for Advancing Translational Sciences(CTSI), National Institutes of Health, through UCSF-CTSI UL1TR001872 to TTY; bythe American Foundation for Suicide Prevention (AFSP) SRG-1-141-18 to TTY; byUCSF Research Evaluation and Allocation Committee (REAC) and J. Jacobson Fundto TTY; by the National Institute of Mental Health (NIMH) R01MH085734 and the Brain and Behavior Research Foundation (formerly NARSAD) to TTY. YC acknowledges the Medical Leader Foundation of Yunnan Province (L2019011) and FamousDoctors Project of Yunnan Province Plan (YNWR-MY-2018-041). DTG, BCF and RAAwish to thank all PAFIP patients and family members who participated in the studyas well as PAFIP´s research team and Instituto de Investigación Marqués deValdecilla. Work by the PAFIP group has been funded by Instituto de Salud Carlos III through the projects PI14/00639, PI14/00918 and PI17/01056 (Co-funded byEuropean Regional Development Fund/European Social Fund “Investing in yourfuture”) and Fundación Instituto de Investigación Marqués de Valdecilla(NCT0235832 and NCT02534363). MER received support from the AustralianNational Health and Medical Research Council (NHMRC) Centre for ResearchExcellence on Suicide Prevention (CRESP) [GNT1042580]. ETCL is supported bygrants from NIAAA (K01AA027573, R21AA027884) and the American Foundationfor Suicide Prevention. All authors thank the participants for volunteering theirtime and supporting our research. Open Access funding enabled and organized by CAUL and its Member Institutions

Implementation of a multidisciplinary psychoeducational intervention for Parkinson's disease patients and carers in the community: study protocol

Background: Parkinson’s disease progressively limits patients at different levels and as a result family members play a key role in their care. However, studies show lack of an integrative approach in Primary Care to respond to the difficulties and psychosocial changes experienced by them. The aim of this study is to evaluate the effects of a multidisciplinary psychoeducational intervention focusing on improving coping skills, the psychosocial adjustment to Parkinson’s disease and the quality of life in patients and family carers in a Primary Care setting. Methods: This quasi-experimental study with control group and mixed methods was designed to evaluate a multidisciplinary psychoeducational intervention. Based on the study power calculations, 100 people with Parkinson’s disease and 100 family carers will be recruited and assigned to two groups. The intervention group will receive the ReNACE psychoeducational intervention. The control group will be given a general educational programme. The study will be carried out in six community-based health centres. The results obtained from the two groups will be collected for evaluation at three time points: at baseline, immediately after the intervention and at 6 months post-intervention. The results will be measured with these instruments: the Quality of Life Scale PDQ39 for patients and the Scale of Quality of Life of Care-givers SQLC for family carers, and for all participants the Psychosocial Adjustment to Illness scale and the Brief COPE Inventory. Focus groups will be organised with some patients and family carers who will have received the ReNACE psychoeducational intervention and also with the healthcare professionals involved in its development. Discussion: An important gap exists in the knowledge and application of interventions with a psychosocial approach for people with PD and family carers as a whole. This study will promote this comprehensive approach in Primary Care, which will clearly contribute in the existing knowledge and could reduce the burden of PD for patients and family carers, and also in other long-term conditions

Elementos clave en el proceso de convivencia con la enfermedad de Parkinson de pacientes y familiares cuidadores

Fundamento. La enfermedad de Parkinson produce un impacto considerable en la vida de las personas. Es necesario identificar los elementos clave que influyen en el proceso de convivencia con la enfermedad de Parkinson para que los profesionales de la salud puedan ayudar a los pacientes y sus familias a convivir lo mejor posible con los cambios y limitaciones producidos por la enfermedad. Material y método. Se llevó a cabo un estudio cualitativo descriptivo. Este estudio se corresponde con la primera fase de un diseño exploratorio secuencial (Mixed-methods) que incluye a su vez una fase cuantitativa. Se realizó un proyecto multicéntrico. Para la recogida de datos se aplicó un muestreo de conveniencia y se utilizó una entrevista semi-estructurada realizada individualmente a pacientes y familiares cuidadores y dos cuestionarios para pacientes: la Escala de Hoehn & Yahr y el Cuestionario PDNMS. Se realizó un análisis de contenido de las entrevistas y estadístico descriptivo de los cuestionarios. Resultados. La muestra la constituyeron 46 participantes. Se identificaron tres elementos clave en el proceso de convivencia con la enfermedad de Parkinson: aceptación, adaptación y automanejo. Estos elementos condicionaron dos modos de convivencia con la enfermedad de Parkinson: una convivencia positiva, caracterizada por sentimientos de armonía, equilibrio, y naturalidad; y una convivencia negativa caracterizada por sentimientos de frustración, pérdida de control y autoestima. Conclusiones. Es esencial que los profesionales de la salud conozcan a fondo estos elementos, así como los factores que los favorecen o dificultan. En la medida que se propicie la investigación en este ámbito y se identifiquen intervenciones efectivas se mejorará la atención integral de la personas en consonancia con las nuevas directrices para la cronicidad.Background. Parkinson’s disease has a considerable impact on people’s lives. It is necessary to identify the key elements that influence the process of living with Parkinson’s disease so that health professionals can help patients and their relatives to live as well as possible with the changes and limitations produced by the disease. Material and methods. A qualitative descriptive study was realized. This study corresponded to the first phase of a sequential, exploratory design (mixed method) that in turn included a quantitative phase. A multicentre project was carried out. Convenience sampling was applied to collect data, a semi-structured interview was realized individually with patients and carer-relatives and two questionnaires with patients: the Hoehn & Yahr scale and the PDNMS questionnaire. Content analysis of the interviews and a statistical description of the questionnaires were used. Results. The sample was made up of 46 participants. Three key elements were identified in the process of living with Parkinson’s disease: acceptance, adaptation and self-management. These elements conditioned the modes of living with Parkinson’s disease: positive living, characterized by feelings of harmony, balance and naturalness; negative living characterized be feelings of frustration, loss of control and self-esteem. Conclusions. It is essential for health professionals to have a deep understanding of these elements, as well as of the factors that favor or hinder them. To the extent that research in this field progresses and effective interventions are identified, comprehensive patient care will be improved in consonance with the new directives for chronicity

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

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

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

Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation

The value of normative models in research and clinical practice relies on their robustness and a systematic comparison of different modelling algorithms and parameters; however, this has not been done to date. We aimed to identify the optimal approach for normative modelling of brain morphometric data through systematic empirical benchmarking, by quantifying the accuracy of different algorithms and identifying parameters that optimised model performance. We developed this framework with regional morphometric data from 37 407 healthy individuals (53% female and 47% male; aged 3–90 years) from 87 datasets from Europe, Australia, the USA, South Africa, and east Asia following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The multivariate fractional polynomial regression (MFPR) emerged as the preferred algorithm, optimised with non-linear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3000 study participants. This model can inform about the biological and behavioural implications of deviations from typical age-related neuroanatomical changes and support future study designs. The model and scripts described here are freely available through CentileBrain

Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium

BACKGROUND 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 (N = 11,095), using a single image analysis protocol. METHODS We included T1-weighted data from 46 datasets (5,080 affected individuals and 6,015 controls) from the ENIGMA Consortium. 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. Analyses were also performed with respect to the use of antipsychotic medication and other clinical variables, as well as age and sex. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029). RESULTS Small average differences between cases and controls were observed for asymmetries in cortical thickness, specifically of the rostral anterior cingulate (d = −0.08, pFDR = 0.047) and the middle temporal gyrus (d = −0.07, pFDR = 0.048), both driven primarily by thinner cortices in the left hemisphere in schizophrenia. These asymmetries were not significantly associated with the use of antipsychotic medication or other clinical variables. Older individuals with schizophrenia showed a stronger average leftward asymmetry of pallidum volume than older controls (d = 0.08, pFDR = 9.0 × 10−3). The multivariate analysis revealed that 7% of the variance across all structural asymmetries was explained by case-control status (F = 1.87, p = 1.25 × 10−5). CONCLUSIONS Altered trajectories of asymmetrical brain development and/or lifespan asymmetry may contribute to schizophrenia pathophysiology. Small case-control differences of brain macro-structural asymmetry may manifest due to more substantial differences at the molecular, cytoarchitectonic or circuit levels, with functional relevance for lateralized cognitive processes