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The aims of the present study were: (i) to examine the association between schizophrenia (SCZ) and 47, XXY or 47, XXX in a large case-control sample; and (ii) to characterize the clinical features of patients with SCZ with these X chromosome aneuploidies.To identify 47, XXY and 47, XXX, array comparative genomic hybridization (aCGH) was performed in 3188 patients with SCZ and 3586 controls. We examined the association between 47, XXY and 47, XXX and SCZ in males and females separately using exact conditional tests to control for platform effects. Clinical data were retrospectively examined for patients with SCZ with X chromosome aneuploidies.Of the analyzed samples, 3117 patients (97.8%) and 3519 controls (98.1%) passed our quality control. X chromosome aneuploidies were exclusively identified in patients: 47, XXY in seven patients (0.56%), 47, XXX in six patients (0.42%). Statistical analysis revealed a significant association between SCZ and 47, XXY (P = 0.028) and 47, XXX (P = 0.011). Phenotypic data were available from 12 patients. Treatment-resistance to antipsychotics and manic symptoms were observed in six patients each (four with 47, XXY and two with 47, XXX for both), respectively. Statistical analysis revealed that treatment-resistance to antipsychotics, mood stabilizer use, and manic symptoms were significantly more common in patients with 47, XXY than in male patients without pathogenic copy number variations.These findings indicate that both 47, XXY and 47, XXX are significantly associated with risk for SCZ. Patients with SCZ with 47, XXY may be characterized by treatment-resistance and manic symptoms.

The overwhelming majority of participants in current genetic studies are of European ancestry. To elucidate disease biology in the East Asian population, we conducted a genome-wide association study (GWAS) with 212,453 Japanese individuals across 42 diseases. We detected 320 independent signals in 276 loci for 27 diseases, with 25 novel loci (P < 9.58 × 10-9). East Asian-specific missense variants were identified as candidate causal variants for three novel loci, and we successfully replicated two of them by analyzing independent Japanese cohorts; p.R220W of ATG16L2 (associated with coronary artery disease) and p.V326A of POT1 (associated with lung cancer). We further investigated enrichment of heritability within 2,868 annotations of genome-wide transcription factor occupancy, and identified 378 significant enrichments across nine diseases (false discovery rate < 0.05) (for example, NKX3-1 for prostate cancer). This large-scale GWAS in a Japanese population provides insights into the etiology of complex diseases and highlights the importance of performing GWAS in non-European populations.

ENIGMA-CNV Working Group: van der Meer, Dennis; Sonderby, Ida E; Kaufmann, Tobias; Walters, G Bragi; Abdellaoui, Abdel; Ames, David; Amunts, Katrin; Andersson, Micael; Armstrong, Nicola J; Bernard, Manon; Blackburn, Nicholas B; Blangero, John; Boomsma, Dorret I; Brodaty, Henry; Brouwer, Rachel M; Bulow, Robin; Cahn, Wiepke; Calhoun, Vince D; Caspers, Svenja; Cavalleri, Gianpiero L; Ching, Christopher R K; Cichon, Sven; Ciufolini, Simone; Corvin, Aiden; Crespo-Facorro, Benedicto; Curran, Joanne E; Dalvie, Shareefa; Dazzan, Paola; de Geus, Eco J C; de Zubicaray, Greig I; de Zwarte, Sonja M C; Delanty, Norman; den Braber, Anouk; Desrivieres, Sylvane; Di Forti, Marta; Doherty, Joanne L; Donohoe, Gary; Ehrlich, Stefan; Eising, Else; Espeseth, Thomas; Fisher, Simon E; Fladby, Tormod; Frei, Oleksandr; Frouin, Vincent; Fukunaga, Masaki; Gareau, Thomas; Glahn, David C; Grabe, Hans J; Groenewold, Nynke A; Gustafsson, Omar; Haavik, Jan; Haberg, Asta K; Hashimoto, Ryota; Hehir-Kwa, Jayne Y; Hibar, Derrek P; Hillegers, Manon H J; Hoffmann, Per; Holleran, Laurena; Hottenga, Jouke-Jan; Hulshoff Pol, Hilleke E; Ikeda, Masashi; Jacquemont, Sebastien; Jahanshad, Neda; Jockwitz, Christiane; Johansson, Stefan; Jonsson, Erik G; Kikuchi, Masataka; Knowles, Emma E M; Kwok, John B; Le Hellard, Stephanie; Linden, David E J; Liu, Jingyu; Lundervold, Arvid; Lundervold, Astri J; Martin, Nicholas G; Mather, Karen A; Mathias, Samuel R; McMahon, Katie L; McRae, Allan F; Medland, Sarah E; Moberget, Torgeir; Moreau, Clara; Morris, Derek W; Muhleisen, Thomas W; Murray, Robin M; Nordvik, Jan E; Nyberg, Lars; Olde Loohuis, Loes M; Ophoff, Roel A; Owen, Michael J; Paus, Tomas; Pausova, Zdenka; Peralta, Juan M; Pike, Bruce; Prieto, Carlos; Quinlan, Erin Burke; Reinbold, Celine S; Reis Marques, Tiago; Rucker, James J H; Sachdev, Perminder S; Sando, Sigrid B; Schofield, Peter R; Schork, Andrew J; Schumann, Gunter; Shin, Jean; Shumskaya, Elena; Silva, Ana I; Sisodiya, Sanjay M; Steen, Vidar M; Stein, Dan J; Strike, Lachlan T; Tamnes, Christian K; Teumer, Alexander; Thalamuthu, Anbupalam; Tordesillas-Gutierrez, Diana; Uhlmann, Anne; Ulfarsson, Magnus O; van 't Ent, Dennis; van den Bree, Marianne B M; Vassos, Evangelos; Wen, Wei; Wittfeld, Katharina; Wright, Margaret J; Zayats, Tetyana; Dale, Anders M; Djurovic, Srdjan; Agartz, Ingrid; Westlye, Lars T; Stefansson, Hreinn; Stefansson, Kari; Thompson, Paul M; Andreassen, Ole A., [Importance] Recurrent microdeletions and duplications in the genomic region 15q11.2 between breakpoints 1 (BP1) and 2 (BP2) are associated with neurodevelopmental disorders. These structural variants are present in 0.5% to 1.0% of the population, making 15q11.2 BP1-BP2 the site of the most prevalent known pathogenic copy number variation (CNV). It is unknown to what extent this CNV influences brain structure and affects cognitive abilities., [Objective] To determine the association of the 15q11.2 BP1-BP2 deletion and duplication CNVs with cortical and subcortical brain morphology and cognitive task performance., [Design, Setting, and Participants] In this genetic association study, T1-weighted brain magnetic resonance imaging were combined with genetic data from the ENIGMA-CNV consortium and the UK Biobank, with a replication cohort from Iceland. In total, 203 deletion carriers, 45 247 noncarriers, and 306 duplication carriers were included. Data were collected from August 2015 to April 2019, and data were analyzed from September 2018 to September 2019., [Main Outcomes and Measures] The associations of the CNV with global and regional measures of surface area and cortical thickness as well as subcortical volumes were investigated, correcting for age, age2, sex, scanner, and intracranial volume. Additionally, measures of cognitive ability were analyzed in the full UK Biobank cohort., [Results] Of 45 756 included individuals, the mean (SD) age was 55.8 (18.3) years, and 23 754 (51.9%) were female. Compared with noncarriers, deletion carriers had a lower surface area (Cohen d = −0.41; SE, 0.08; P = 4.9 × 10−8), thicker cortex (Cohen d = 0.36; SE, 0.07; P = 1.3 × 10−7), and a smaller nucleus accumbens (Cohen d = −0.27; SE, 0.07; P = 7.3 × 10−5). There was also a significant negative dose response on cortical thickness (β = −0.24; SE, 0.05; P = 6.8 × 10−7). Regional cortical analyses showed a localization of the effects to the frontal, cingulate, and parietal lobes. Further, cognitive ability was lower for deletion carriers compared with noncarriers on 5 of 7 tasks., [Conclusions and Relevance] These findings, from the largest CNV neuroimaging study to date, provide evidence that 15q11.2 BP1-BP2 structural variation is associated with brain morphology and cognition, with deletion carriers being particularly affected. The pattern of results fits with known molecular functions of genes in the 15q11.2 BP1-BP2 region and suggests involvement of these genes in neuronal plasticity. These neurobiological effects likely contribute to the association of this CNV with neurodevelopmental disorders., This study is supported in part by grants U54 EB20403, R01MH116147, and R56AG058854 from the National Institutes of Health, grant 609020 from the European Union Seventh Framework Programme, and grants 223273 and 276082 from the Research Council Norway. Part of this work was performed using the Service for Sensitive Data (TSD), which is developed and operated by the TSD Service Groupand owned by the University of Oslo.

Contains fulltext : 248656.pdf (Publisher’s version ) (Closed access) BACKGROUND: Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk. METHODS: We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH. RESULTS: Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10(-8)), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10(-6)) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10(-7); rs73033497, p = 8.8 × 10(-7); rs7914279, p = 6.4 × 10(-7)), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10(-7)) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10(-7)), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10(-7)) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05). CONCLUSIONS: In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.

Publisher's version (útgefin grein), Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = −0.71 to −1.37; P < 0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (β = −0.95, P = 0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P = 0.0032, 8.9 × 10−6, 1.7 × 10− 9, 3.5 × 10−12 and 1.0 × 10−4, respectively). Full scale IQ was lower in both deletion and duplication carriers compared to non-carriers. This is the first brain MRI study of the impact of the 16p11.2 distal CNV, and we demonstrate a specific effect on subcortical brain structures, suggesting a neuropathological pattern underlying the neurodevelopmental syndromes., 1000BRAINS: 1000BRAINS is a population-based cohort based on the Heinz-Nixdorf Recall Study and is supported in part by the German National Cohort. We thank the Heinz Nixdorf Foundation (Germany) for their generous support in terms of the Heinz Nixdorf Study. The HNR study is also supported by the German Ministry of Education and Science (FKZ 01EG940), and the German Research Council (DFG, ER 155/6-1). The authors are supported by the Initiative and Networking Fund of the Helmholtz Association (Svenja Caspers) and the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement 7202070 (Human Brain Project SGA1; Katrin Amunts, Sven Cichon). This work was further supported by the German Federal Ministry of Education and Research (BMBF) through the Integrated Network IntegraMent (Integrated Understanding of Causes and Mechanisms in Mental Disorders) under the auspices of the e:Med Program (grant 01ZX1314A to M.M.N. and S.C.), and by the Swiss National Science Foundation (SNSF, grant 156791 to S.C.). 16p.11.2 European Consortium: B.D. is supported by the Swiss National Science Foundation (NCCR Synapsy, project grant Nr 32003B_159780) and Foundation Synapsis. LREN is very grateful to the Roger De Spoelberch and Partridge Foundations for their generous financial support. This work was supported by grants from the Simons Foundation (SFARI274424) and the Swiss National Science Foundation (31003A_160203) to A.R. and S.J. Betula: The relevant Betula data collection and analyses were supported by a grant from the Knut & Alice Wallenberg (KAW) to L. Nyberg. Brainscale: the Brainscale study was supported by the Netherlands Organization for Scientific Research MagW 480-04-004 (Dorret Boomsma), 51.02.060 (Hilleke Hulshoff Pol), 668.772 (Dorret Boomsma & Hilleke Hulshoff Pol); NWO/SPI 56-464-14192 (Dorret Boomsma), the European Research Council (ERC-230374) (Dorret Boomsma), High Potential Grant Utrecht University (Hilleke Hulshoff Pol), NWO Brain and Cognition 433-09-220 (Hilleke Hulshoff Pol). Brain Imaging Genetics (BIG): This work makes use of the BIG database, first established in Nijmegen, The Netherlands, in 2007. This resource is now part of Cognomics (www.cognomics.nl), a joint initiative by researchers of the Donders Centre for Cognitive Neuroimaging, the Human Genetics and Cognitive Neuroscience departments of the Radboud university medical centre and the Max Planck Institute for Psycholinguistics in Nijmegen. The Cognomics Initiative has received supported from the participating departments and centres and from external grants, i.e., the Biobanking and Biomolecular Resources Research Infrastructure (the Netherlands) (BBMRI-NL), the Hersenstichting Nederland, and the Netherlands Organisation for Scientific Research (NWO). The research leading to these results also receives funding from the NWO Gravitation grant ‘Language in Interaction’, the European Community’s Seventh Framework Programme (FP7/2007–2013) under grant agreements n° 602450 (IMAGEMEND), n°278948 (TACTICS), and n°602805 (Aggressotype) as well as from the European Community’s Horizon 2020 programme under grant agreement n° 643051 (MiND) and from ERC-2010-AdG 268800-NEUROSCHEMA. In addition, the work was supported by a grant for the ENIGMA Consortium (grant number U54 EB020403) from the BD2K Initiative of a cross-NIH partnership. COBRE: This work was supported by a NIH COBRE Phase I grant (1P20RR021938, Lauriello, PI and 2P20GM103472, Calhoun, PI) awarded to the Mind Research Network. We wish to express our gratitude to numerous investigators who were either external consultants to the Cores and projects, mentors on the projects, members of the external advisory committee and members of the internal advisory committee. Decode: The research leading to these results has received financial contribution from the European Union’s Seventh Framework Programme (EU-FP7/2007–2013), EU-FP7 funded grant no. 602450 (IMAGEMEND) as well as support from the Innovative Medicines Initiative Joint Undertaking under grant agreement no.115300 (EUAIMS). DemGene: Norwegian Health Association and Research Council of Norway. Dublin: Work was supported by Science Foundation Ireland (SFI grant 12/IP/1359 to Gary Donohoe and SFI08/IN.1/B1916-Corvin to Aidan C Corvin) and the European Research Council (ERC-StG-2015-677467). EPIGEN-UK (SMS, CL): The work was partly undertaken at UCLH/UCL, which received a proportion of funding from the UK Department of Health’s NIHR Biomedical Research Centres funding scheme. We are grateful to the Wolfson Trust and the Epilepsy Society for supporting the Epilepsy Society MRI scanner, and the Epilepsy Society for supporting CL. Haavik: The work at the K.G.Jebsen center for neuropsychiatric disorders at the University of Bergen, Norway, was supported by Stiftelsen K.G. Jebsen, European Community’s Seventh Framework Program under grant agreement no 602805 and the H2020 Research and Innovation Program under grant agreement numbers 643051 and 667302. HUNT: The HUNT Study is a collaboration between HUNT Research Centre (Faculty of Medicine, 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. IMAGEN: The work received support from the European Union-funded FP6Integrated Project IMAGEN (Reinforcement-related behaviour in normal brain function and psychopathology) (LSHM-CT- 2007-037286), the Horizon 2020 funded ERC Advanced Grant ‘STRATIFY’ (Brain network based stratification of reinforcement-related disorders) (695313), ERANID (Understanding the Interplay between Cultural, Biological and Subjective Factors in Drug Use Pathways) (PR-ST-0416-10004), BRIDGET (JPND: BRain Imaging, cognition Dementia and next generation GEnomics) (MR/N027558/1), the FP7 projects IMAGEMEND (602450; IMAging GEnetics for MENtal Disorders) and MATRICS (603016), the Innovative Medicine Initiative Project EU-AIMS (115300), the Medical Research Council Grant ‘c-VEDA’ (Consortium on Vulnerability to Externalizing Disorders and Addictions) (MR/N000390/1), the Swedish Research Council FORMAS, the Medical Research Council, the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, the Bundesministeriumfür Bildung und Forschung (BMBF grants 01GS08152; 01EV0711; eMED SysAlc01ZX1311A; Forschungsnetz AERIAL), the Deutsche Forschungsgemeinschaft (DFG grants SM 80/7-1, SM 80/7-2, SFB 940/1). Further support was provided by grants from: ANR (project AF12-NEUR0008-01—WM2NA, and ANR-12-SAMA-0004), the Fondation de France, the Fondation pour la Recherche Médicale, the Mission Interministérielle de Lutte-contre-les-Drogues-et-les-Conduites-Addictives (MILDECA), the Assistance-Publique-Hôpitaux-de-Paris and INSERM (interface grant), Paris Sud University IDEX 2012; the National Institutes of Health, Science Foundation Ireland (16/ERCD/3797), USA (Axon, Testosterone and Mental Health during Adolescence; RO1 MH085772-01A1), and by NIH Consortium grant U54 EB020403, supported by a cross-NIH alliance that funds Big Data to Knowledge Centres of Excellence. MCIC: This work was supported primarily by the Department of Energy DE-FG02-99ER62764 through its support of the Mind Research Network and the consortium as well as by the National Association for Research in Schizophrenia and Affective Disorders (NARSAD) Young Investigator Award (to SE) as well as through the Blowitz-Ridgeway and Essel Foundations, and through NWO ZonMw TOP 91211021, the DFG research fellowship (to SE), the Mind Research Network, National Institutes of Health through NCRR 5 month-RR001066 (MGH General Clinical Research Center), NIMH K08 MH068540, the Biomedical Informatics Research Network with NCRR Supplements to P41 RR14075 (MGH), M01 RR 01066 (MGH), NIBIB R01EB006841 (MRN), R01EB005846 (MRN), 2R01 EB000840 (MRN), 1RC1MH089257 (MRN), as well as grant U24 RR021992. NCNG: this sample collection was supported by grants from the Bergen Research Foundation and the University of Bergen, the Dr Einar Martens Fund, the K.G. Jebsen Foundation, the Research Council of Norway, to SLH, VMS and TE. The Bergen group was supported by grants from the Western Norway Regional Health Authority (Grant 911593 to AL, Grant 911397 and 911687 to AJL). NESDA: Funding for NESDA was obtained from the Netherlands Organization for Scientific Research (Geestkracht program grant 10-000-1002); the Center for Medical Systems Biology (CSMB, NWO Genomics), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL), VU University’s Institutes for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam, University Medical Center Groningen, Leiden University Medical Center, National Institutes of Health (NIH, R01D0042157-01A, MH081802, Grand Opportunity grants 1RC2 MH089951 and 1RC2 MH089995). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health.Computing was supported by BiG Grid, the Dutch e-Science Grid, which is financially supported by NWO. NTR: The NTR study was supported by the Netherlands Organization for Scientific Research (NWO), MW904-61-193 (Eco de Geus & Dorret Boomsma), MaGW-nr: 400-07- 080 (Dennis van ‘t Ent), MagW 480-04-004 (Dorret Boomsma), NWO/SPI 56-464-14192 (Dorret Boomsma), the European Research Council, ERC-230374 (Dorret Boomsma), and Amsterdam Neuroscience. OATS: OATS (Older Australian Twins Study) was facilitated by access to Twins Research Australia, which is funded by a National Health and Medical Research Council (NHMRC) Enabling Grant 310667. OATS is also supported via a NHMRC/Australian Research Council Strategic Award (401162) and a NHMRC Project Grant (1045325). DNA extraction was performed by Genetic Repositories Australia, which was funded by a NHMRC Enabling Grant (401184). OATS genotyping was partly funded by a Commonwealth Scientific and Industrial Research Organisation Flagship Collaboration Fund Grant. PAFIP: PAFIP data were collected at the Hospital Universitario Marqués de Valdecilla, University of Cantabria, Santander, Spain, under the following grant support: Carlos III Health Institute PIE14/00031 and SAF2013-46292-R and SAF2015-71526-REDT. We wish to acknowledge IDIVAL Neuroimaging Unit for imaging acquirement and analysis.We want to particularly acknowledge the patients and the BioBankValdecilla (PT13/0010/0024) integrated in the Spanish National Biobanks Network for its collaboration. QTIM: The QTIM study was supported by grants from the US National Institute of Child Health and Human Development (R01 HD050735) and the Australian National Health and Medical Research Council (NHMRC) (486682, 1009064). Genotyping was supported by NHMRC (389875). Lachlan Strike is supported by an Australian Postgraduate Award (APA). AFM is supported by NHMRC CDF 1083656. We thank the twins and siblings for their participation, the many research assistants, as well as the radiographers, for their contribution to data collection and processing of the samples. SHIP: 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, 01ZZ0403 and 01ZZ0701), the Ministry of Cultural Affairs as well as the Social Ministry of the Federal State of Mecklenburg-West Pomerania, and the network ‘Greifswald Approach to Individualized Medicine (GANI_MED)’ funded by the Federal Ministry of Education and Research (grant 03IS2061A). Genome-wide data have been supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg- West Pomerania. Whole-body MR imaging was supported by a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg West Pomerania. The University of Greifswald is a member of the Caché Campus program of the InterSystems GmbH. StrokeMRI: StrokeMRI has been supported by the Research Council of Norway (249795), the South-Eastern Norway Regional Health Authority (2014097, 2015044, 2015073) and the Norwegian ExtraFoundation for Health and Rehabilitation. TOP: TOP is supported by the Research Council of Norway (223273, 213837, 249711), the South East Norway Health Authority (2017-112), the Kristian Gerhard Jebsen Stiftelsen (SKGJ‐MED‐008) and the European Community’s Seventh Framework Programme (FP7/2007–2013), grant agreement no. 602450 (IMAGEMEND). We acknowledge the technical support and service from the Genomics Core Facility at the Department of Clinical Science, the University of Bergen

Bipolar disorder is a severe mental illness characterized by recurrent manic and depressive episodes. To better understand its genetic architecture, we analyze ultra-rare de novo mutations in 354 trios with bipolar disorder. For germline de novo mutations, we find significant enrichment of loss-of-function mutations in constrained genes (corrected-P = 0.0410) and deleterious mutations in presynaptic active zone genes (FDR = 0.0415). An analysis integrating single-cell RNA-sequencing data identifies a subset of excitatory neurons preferentially expressing the genes hit by deleterious mutations, which are also characterized by high expression of developmental disorder genes. In the analysis of postzygotic mutations, we observe significant enrichment of deleterious ones in developmental disorder genes (P = 0.00135), including the SRCAP gene mutated in two unrelated probands. These data collectively indicate the contributions of both germline and postzygotic mutations to the risk of bipolar disorder, supporting the hypothesis that postzygotic mutations of developmental disorder genes may contribute to bipolar disorder., The significance of rare and de novo variants in bipolar disorder is not well understood. Here, the authors have analyzed whole exome/genome data from trios to identify deleterious de novo variants associated with bipolar disorder.

ENIGMA-CNV working group., Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers—the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function., 1000BRAINS: The 1000BRAINS study was funded by the Institute of Neuroscience and Medicine, Research Center Juelich, Germany. We thank the Heinz Nixdorf Foundation (Germany) for the generous support of the Heinz Nixdorf Recall Study on which 1000BRAINS is based. We also thank the scientists and the study staff of the Heinz Nixdorf Recall Study and 1000BRAINS. Funding was also granted by the Initiative and Networking Fund of the Helmholtz Association (Caspers) and the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement 945539 (Human Brain Project SGA3; Amunts, Caspers, Cichon). Brainscale: The Brainscale study was supported by the Netherlands Organization for Scientific Research MagW 480-04-004 (Dorret I. Boomsma), 51.02.060 (Hilleke E. Hulshoff Pol), 668.772 (Dorret I. Boomsma and Hilleke E. Hulshoff Pol); NWO/SPI 56-464-14192 (Dorret I. Boomsma), the European Research Council (ERC-230374) (Dorret I. Boomsma), High Potential Grant Utrecht University (Hilleke E.Hulshoff Pol) and NWO Brain and Cognition 433-09-220 (Hilleke E.Hulshoff Pol). Betula: The Betula study was funded by the Knut and Alice Wallenberg (KAW) foundation (Nyberg). The Freesurfer segmentations on the Betula sample were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at HPC2N (in Umeå, Sweden), partially funded by the Swedish Research Council through grant agreement no. 2018-05973. Brain Imaging Genetics (BIG): This work makes use of the BIG database, first established in Nijmegen, The Netherlands, in 2007. This resource is now part of Cognomics (www.cognomics.nl), a joint initiative by researchers from the Donders Centre for Cognitive Neuroimaging, the Human Genetics and Cognitive Neuroscience departments of the Radboud University Medical Centre and the Max Planck Institute for Psycholinguistics in Nijmegen. The Cognomics Initiative has received support from the participating departments and centres and from external grants, that is, the Biobanking and Biomolecular Resources Research Infrastructure (Netherlands) (BBMRI-NL), the Hersenstichting Nederland and the Netherlands Organization for Scientific Research (NWO). The research leading to these results also receives funding from the NWO Gravitation grant ‘Language in Interaction’, the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement nos. 602450 (IMAGEMEND), 278948 (TACTICS) and 602805 (Aggressotype), as well as from the European Community’s Horizon 2020 programme under grant agreement no. 643051 (MiND) and from ERC-2010-AdG 268800-NEUROSCHEMA. In addition, the work was supported by a grant for the ENIGMA Consortium (grant number U54 EB020403) from the BD2K Initiative of a cross-NIH partnership. deCODE genetics: deCODE genetics acknowledges support from the Innovative Medicines Initiative Joint Undertaking under grant agreement nos. 115008 (NEWMEDS) and 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), EU-FP7-funded grant agreement no. 602450 (IMAGEMEND) and EU-funded FP7-People-2011-IAPP grant agreement no. 286213 (PsychDPC). Dublin: This work was supported by Science Foundation Ireland (SFI grant 12/IP/1359 to Gary Donohoe and grant SFI08/IN.1/B1916-Corvin to Aidan C. Corvin). ECHO-DEFINE: The ECHO study acknowledges funding from a Medical Research Council (MRC) Centre Grant to Michael J. Owen (G0801418), the Wellcome Trust (Institutional Strategic Support Fund (ISSF) to van den Bree and Clinical Research Training Fellowship to Joanne L. Doherty), the Waterloo Foundation (WF 918-1234 to van den Bree), the Baily Thomas Charitable Fund (2315/1 to van den Bree), National Institute of Mental Health (NIMH 5UO1MH101724 to van den Bree and Michael J. Owen), the IMAGINE-2 study (funded by the MRC (MR/T033045/1) to van den Bree, Jeremy Hall and Michael J. Owen), the IMAGINE-ID study (funded by MRC (MR/N022572/1) to Jeremy Hall, van den Bree and Owen). The DEFINE study was supported by a Wellcome Trust Strategic Award (100202/Z/12/Z) to Michael J. Owen. ENIGMA: ENIGMA is supported in part by NIH grants U54 EB20403, R01MH116147 and R56AG058854. NIA T32AG058507; NIH/NIMH 5T32MH073526. EPIGEN-Dublin: The EPIGEN-Dublin cohort was supported by a Science Foundation Ireland Research Frontiers Programme award (08/RFP/GEN1538). EPIGEN-UK (Sisodiya): The work was partly undertaken at UCLH/UCL, which received a proportion of funding from the UK Department of Health’s NIHR Biomedical Research Centres funding scheme. We are grateful to the Wolfson Trust and the Epilepsy Society for supporting the Epilepsy Society MRI scanner. GAP: This work was supported by the National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and the Institute of Psychiatry, Psychology and Neuroscience, King’s College London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. GOBS: 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 C06 RR020547. GSP: Data were in part provided by the Brain Genomics Superstruct Project (GSP) of Harvard University and Massachusetts General Hospital (MGH) (Principal Investigators: Randy Buckner, Jordan Smoller and Joshua Roffman), with support from the Center for Brain Science Neuroinformatics Research Group, Athinoula A. Martinos Center for Biomedical Imaging, Center for Genomic Medicine and Stanley Center for Psychiatric Research. Twenty individual investigators at Harvard and MGH generously contributed data to the overall project. We would like to thank Randy Buckner for insightful comments and feedback on this work. HUBIN: The HUBIN study was financed by the Swedish Research Council (K2010-62X-15078-07-2, K2012-61X-15078-09-3, 521-2014-3487 K2015-62X-15077-12-3, 2017-00949), the regional agreement on medical training and clinical research between Stockholm County Council and the Karolinska Institutet. HUNT: The HUNT study is a collaboration between HUNT Research Centre (Faculty of Medicine and Movement 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. IMAGEN: This work received support from the following sources: the European Union-funded FP6 Integrated Project IMAGEN (reinforcement-related behaviour in normal brain function and psychopathology) (LSHM-CT- 2007-037286), the Horizon 2020 funded ERC Advanced Grant ‘STRATIFY’ (Brain network based stratification of reinforcement-related disorders) (695313), ERANID (Understanding the Interplay between Cultural, Biological and Subjective Factors in Drug Use Pathways) (PR-ST-0416-10004), BRIDGET (JPND: BRain Imaging, cognition Dementia and next generation GEnomics) (MR/N027558/1), Human Brain Project (HBP SGA 2, 785907),the FP7 projects IMAGEMEND(602450; IMAging GEnetics for MENtal Disorders) and MATRICS (603016), the Innovative Medicine Initiative Project EUAIMS (115300-2), the Medical Research Council Grant ‘c-VEDA’ (Consortium on Vulnerability to Externalizing Disorders and Addictions) (MR/N000390/1), the Swedish Research Council FORMAS, the Medical Research Council, the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, the Bundesministeriumfür Bildung und Forschung (BMBF grants 01GS08152, 01EV0711; eMED SysAlc01ZX1311A; Forschungsnetz AERIAL 01EE1406A, 01EE1406B), the Deutsche Forschungsgemeinschaft (DFG grants, SM 80/7-2, SFB 940/2), the Medical Research Foundation and Medical Research Council (grants MR/R00465X/1 and MR/S020306/1). Further support was provided by grants from: ANR (project AF12-NEUR0008-01—WM2NA, ANR-12-SAMA-0004), the Eranet Neuron (ANR-18-NEUR00002-01), the Fondation de France (00081242), the Fondation pour la Recherche Médicale (DPA20140629802), the Mission Interministérielle de Lutte-contre-les-Drogues-et-les-Conduites-Addictives (MILDECA), the Assistance-Publique-Hôpitaux-de-Paris and INSERM (interface grant), Paris Sud University IDEX 2012, the Fondation de l’Avenir (grant AP-RM-17-013), the Fédération pour la Recherche sur le Cerveau; the National Institutes of Health, Science Foundation Ireland (16/ERCD/3797), USA (Axon, Testosterone and Mental Health during Adolescence; RO1 MH085772-01A1) and by NIH Consortium grant U54 EB020403, supported by a cross-NIH alliance that funds Big Data to Knowledge Centres of Excellence. Lifespan: The study is funded by the Research Council of Norway (230345, 288083 and 223273). NCNG: NCNG sample collection was supported by grants from the Bergen Research Foundation and the University of Bergen, the Dr Einar Martens Fund, the Research Council of Norway, to le Hellard, Steen and Espeseth. The Bergen group was supported by grants from the Western Norway Regional Health Authority (Grant 911593 to Arvid Lundervold, Grant 911397 and 911687 to Astri Johansen Lundervold). NTR: The NTR cohort was supported by the Netherlands Organization for Scientific Research (NWO) and The Netherlands Organisation for Health Research and Development (ZonMW) grants 904-61-090, 985-10-002, 912-10-020, 904-61-193, 480-04-004,463-06-001, 451-04-034, 400-05-717, Addiction-31160008, 016-115-035, 481-08-011, 056-32-010, Middelgroot-911-09-032, OCW_NWO Gravity programme—024.001.003, NWO-Groot 480-15-001/674, Center for Medical Systems Biology (CSMB, NWO Genomics), NBIC/BioAssist/RK(2008.024), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL, 184.021.007 and 184.033.111); Spinozapremie (NWO-56-464-14192), KNAW Academy Professor Award (PAH/6635) and University Research Fellow grant (URF) to Dorret I. Boomsma; Amsterdam Public Health research institute (former EMGO+), Neuroscience Amsterdam research institute (former NCA); the European Science Foundation (ESF, EU/QLRT-2001-01254), the European Community’s Seventh Framework Programme (FP7- HEALTH-F4-2007-2013, grant 01413: ENGAGE and grant 602768: ACTION); the European Research Council (ERC Starting 284167, ERC Consolidator 771057, ERC Advanced 230374), Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06), the National Institutes of Health (NIH, R01D0042157-01A1, R01MH58799-03, MH081802, DA018673, R01 DK092127-04, 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. Computing was supported by NWO through grant 2018/EW/00408559, BiG Grid, the Dutch e-Science Grid and SURFSARA. OATS: The OATS study has been funded by a National Health & Medical Research Council (NHMRC) and Australian Research Council (ARC) Strategic Award Grant of the Ageing Well, Ageing Productively Programme (ID No. 401162) and NHMRC Project Grants (ID Nos. 1045325 and 1085606). This research was facilitated through Twins Research Australia, a national resource in part supported by an NHMRC Centre for Research Excellence Grant (ID No.: 1079102). We thank the participants for their time and generosity in contributing to this research. We acknowledge the contribution of the OATS research team (https://cheba.unsw.edu.au/project/older-australian-twins-study) to this study. OATS genotyping was partly funded by a Commonwealth Scientific and Industrial Research Organization Flagship Collaboration Fund Grant. Osaka: Osaka study was supported by the Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS: Grant Number JP18dm0207006), Brain/MINDS& beyond studies (Grant Number JP20dm0307002) and Health and Labour Sciences Research Grants for Comprehensive Research on Persons with Disabilities (Grant Number JP20dk0307081) from the Japan Agency for Medical Research and Development (AMED), Grants-in-Aid for Scientific Research (KAKENHI; Grant Numbers JP25293250 and JP16H05375). Some computations were performed at the Research Center for Computational Science, Okazaki, Japan. PAFIP: The PAFIP study was supported by Instituto de Salud Carlos III, FIS 00/3095, 01/3129, PI020499, PI060507, PI10/00183, the SENY Fundació Research Grant CI2005-0308007 and the FundaciónMarqués de Valdecilla API07/011. Biological samples from our cohort were stored at the Valdecilla Biobank and genotyping services were conducted at the Spanish ‘Centro Nacional de Genotipado’ (CEGEN-ISCIII). MCIC/COBRE: The study is funded by the National Institutes of Health studies R01EB006841, P20GM103472 and P30GM122734 and Department of Energy DE-FG02-99ER62764. PING: Data collection and sharing for the Paediatric Imaging, Neurocognition and Genetics (PING) Study (National Institutes of Health Grant RC2DA029475) were funded by the National Institute on Drug Abuse and the Eunice Kennedy Shriver National Institute of Child Health & Human Development. A full list of PING investigators is at http://pingstudy.ucsd.edu/investigators.html. QTIM: The QTIM study was supported by the National Institute of Child Health and Human Development (R01 HD050735) and the National Health and Medical Research Council (NHMRC 486682, 1009064), Australia. Genotyping was supported by NHMRC (389875). Medland is supported in part by an NHMRC fellowship (APP1103623). SHIP: 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 (grant nos. 01ZZ9603, 01ZZ0103 and 01ZZ0403), the Ministry of Cultural Affairs and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. Genome-wide single-nucleotide polymorphism typing in SHIP and MRI scans in SHIP and SHIP-TREND have been supported by a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. StrokeMRI: StrokeMRI was supported by the Norwegian ExtraFoundation for Health and Rehabilitation(2015/FO5146), the Research Council of Norway (249795, 262372), the South-Eastern Norway Regional Health Authority (2014097, 2015044, 2015073) and the Department of Psychology, University of Oslo. Sydney MAS: The Sydney Memory and Aging Study (Sydney MAS) is funded by National and HealthMedical Research Council (NHMRC) Programme and Project Grants (ID350833, ID568969 and ID109308). We also thank the Sydney MAS participants and the Research Team. SYS: The SYS Study is supported by Canadian Institutes of Health Research. TOP: Centre of Excellence: RCN #23273 and RCN #226971. Part of this work was performed on the TSD (Tjeneste for Sensitive Data) facilities, owned by the University of Oslo, operated and developed by the TSD service group at the University of Oslo, IT-Department (USIT) (tsd-drift@usit.uio.no). The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7-PEOPLE-2013-COFUND) under grant agreement no. 609020—Scientia Fellows; the Research Council of Norway (RCN) #276082—A lifespan perspective on mental illness: toward precision medicine using multimodal brain imaging and genetics. Ida E. Sønderby and Rune Bøen are supported by South-Eastern Norway Regional Health Authority (#2020060). Ida E. Sønderby and Ole A. Andreassen have received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant agreement no. 847776 (CoMorMent project) and the KG Jebsen Foundation (SKGJ-MED-021). UCLA_UMCU: The UCLA_UMCU cohort comprises of six studies which were supported by National Alliance for Research in Schizophrenia and Affective Disorders (NARSAD) (20244 to Prof. Hillegers), The Netherlands Organisation for Health Research and Development (ZonMw) (908-02-123 to Prof. Hulshoff Pol), and Netherlands Organisation for Scientific Research (NWO 9120818 and NWO-VIDI 917-46-370 to Prof. Hulshoff Pol). The GROUP study was funded through the Geestkracht programme of the Dutch Health Research Council (ZonMw, grant number 10-000-1001), and matching funds from participating pharmaceutical companies (Lundbeck, AstraZeneca, Eli Lilly and Janssen Cilag) and universities and mental health care organizations (Amsterdam: Academic Psychiatric Centre of the Academic Medical Center and the mental health institutions: GGZ inGeest, Arkin, Dijk en Duin, GGZ Rivierduinen, Erasmus Medical Centre, GGZ Noord-Holland-Noord. Groningen: University Medical Center Groningen and the mental health institutions: Lentis, GGZ Friesland, GGZ Drenthe, Dimence, Mediant, GGNet Warnsveld, Yulius Dordrecht and Parnassia Psycho-medical Center, The Hague. Maastricht: Maastricht University Medical Centre and the mental health institutions: GGzE, GGZ Breburg, GGZ Oost-Brabant, Vincent van Gogh, voor Geestelijke Gezondheid, Mondriaan, Virenzeriagg, Zuyderland GGZ, MET ggz, Universitair Centrum Sint-JozefKortenberg, CAPRI University of Antwerp, PC Ziekeren Sint-Truiden, PZ Sancta Maria Sint-Truiden, GGZ Overpelt, OPZ Rekem. Utrecht: University Medical Center Utrecht and the mental health institutions: Altrecht, GGZ Centraal and Delta.). UK Biobank: This work made use of data sharing from UK Biobank (under project code 27412). Others: Work by Pierre Vanderhaeghen was funded by Grants of the European Research Council (ERC Adv Grant GENDEVOCORTEX), the EOS Programme, the Belgian FWO, the AXA Research Fund and the Belgian Queen Elizabeth Foundation. Ikuo K. Suzuki was supported by a postdoctoral fellowship of the FRS/FNRS.

Associations between altered DNA methylation of the serotonin transporter (5-HTT)-encoding gene SLC6A4 and early life adversity, mood and anxiety disorders, and amygdala reactivity have been reported. However, few studies have examined epigenetic alterations of SLC6A4 in schizophrenia (SZ). We examined CpG sites of SLC6A4, whose DNA methylation levels have been reported to be altered in bipolar disorder, using three independent cohorts of patients with SZ and age-matched controls. We found significant hypermethylation of a CpG site in SLC6A4 in male patients with SZ in all three cohorts. We showed that chronic administration of risperidone did not affect the DNA methylation status at this CpG site using common marmosets, and that in vitro DNA methylation at this CpG site diminished the promoter activity of SLC6A4. We then genotyped the 5-HTT-linked polymorphic region (5-HTTLPR) and investigated the relationship among 5-HTTLPR, DNA methylation, and amygdala volume using brain imaging data. We found that patients harboring low-activity 5-HTTLPR alleles showed hypermethylation and they showed a negative correlation between DNA methylation levels and left amygdala volumes. These results suggest that hypermethylation of the CpG site in SLC6A4 is involved in the pathophysiology of SZ, especially in male patients harboring low-activity 5-HTTLPR alleles.

Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = -0.71 to -1.37; P 0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (β = -0.95, P = 0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P = 0.0032, 8.9 × 10

Genome-wide association studies (GWASs) have identified >100 susceptibility loci for schizophrenia (SCZ) and demonstrated that SCZ is a polygenic disorder determined by numerous genetic variants but with small effect size. We conducted a GWAS in the Japanese (JPN) population (a) to detect novel SCZ-susceptibility genes and (b) to examine the shared genetic risk of SCZ across (East Asian [EAS] and European [EUR]) populations and/or that of trans-diseases (SCZ, bipolar disorder [BD], and major depressive disorder [MDD]) within EAS and between EAS and EUR (trans-diseases/populations). Among the discovery GWAS subjects (JPN-SCZ GWAS: 1940 SCZ cases and 7408 controls) and replication dataset (4071 SCZ cases and 54479 controls), both comprising JPN populations, 3 novel susceptibility loci for SCZ were identified: SPHKAP (P(best) = 4.1 × 10(−10)), SLC38A3 (P(best) = 5.7 × 10(−10)), and CABP1-ACADS (P(best) = 9.8 × 10(−9)). Subsequent meta-analysis between our samples and those of the Psychiatric GWAS Consortium (PGC; EUR samples) and another study detected 12 additional susceptibility loci. Polygenic risk score (PRS) prediction revealed a shared genetic risk of SCZ across populations (P(best) = 4.0 × 10(−11)) and between SCZ and BD in the JPN population (P ~ 10(−40)); however, a lower variance-explained was noted between JPN-SCZ GWAS and PGC-BD or MDD within/across populations. Genetic correlation analysis supported the PRS results; the genetic correlation between JPN-SCZ and PGC-SCZ was ρ = 0.58, whereas a similar/lower correlation was observed between the trans-diseases (JPN-SCZ vs JPN-BD/EAS-MDD, r(g) = 0.56/0.29) or trans-diseases/populations (JPN-SCZ vs PGC-BD/MDD, ρ = 0.38/0.12). In conclusion, (a) Fifteen novel loci are possible susceptibility genes for SCZ and (b) SCZ “risk” effect is shared with other psychiatric disorders even across populations.

Summary: Compelling evidence in Caucasian populations suggests a role for copy-number variations (CNVs) in autism spectrum disorder (ASD) and schizophrenia (SCZ). We analyzed 1,108 ASD cases, 2,458 SCZ cases, and 2,095 controls in a Japanese population and confirmed an increased burden of rare exonic CNVs in both disorders. Clinically significant (or pathogenic) CNVs, including those at 29 loci common to both disorders, were found in about 8% of ASD and SCZ cases, which was significantly higher than in controls. Phenotypic analysis revealed an association between clinically significant CNVs and intellectual disability. Gene set analysis showed significant overlap of biological pathways in both disorders including oxidative stress response, lipid metabolism/modification, and genomic integrity. Finally, based on bioinformatics analysis, we identified multiple disease-relevant genes in eight well-known ASD/SCZ-associated CNV loci (e.g., 22q11.2, 3q29). Our findings suggest an etiological overlap of ASD and SCZ and provide biological insights into these disorders. : Kushima et al. perform comparative analyses of CNVs in ASD and SCZ in a Japanese population. They identify pathogenic CNVs and biological pathways in each disorder with significant overlap. Patients with pathogenic CNVs have a higher prevalence of intellectual disability. Disease-relevant genes are detected in eight well-known ASD/SCZ-associated CNV loci. Keywords: autism spectrum disorder, schizophrenia, copy-number variation, array comparative genomic hybridization, genetic overlap, Japanese population, oxidative stress response, genome integrity, lipid metabolism, gene ontology

Eye movements are considered endophenotypes of schizophrenia. However, the genetic factors underlying eye movement are largely unknown. In this study, we explored the susceptibility loci for four eye movement scores: the scanpath length during the free viewing test (SPL), the horizontal position gain during the fast Lissajous paradigm of the smooth pursuit test (HPG), the duration of fixations during the far distractor paradigm of the fixation stability test (DF) and the integrated eye movement score of those three scores (EMS). We found 16 SNPs relevant to the HPG that were located in 3 genomic regions (1q21.3, 7p12.1 and 20q13.12) in the patient group; however, these SNPs were intronic or intergenic SNPs. To determine whether these SNPs occur in functional non-coding regions (i.e., enhancer or promoter regions), we examined the chromatin status on the basis of publicly available epigenomic data from 127 tissues or cell lines. This analysis suggested that the SNPs on 1q21.3 and 20q13.12 are in enhancer or promoter regions. Moreover, we performed an analysis of expression quantitative trait loci (eQTL) in human brain tissues using a public database. Finally, we identified significant eQTL effects for all of the SNPs at 1q21.3 and 20q13.12 in particular brain regions.

In schizophrenia (SCZ) and autism spectrum disorder (ASD), the dysregulation of glutamate transmission through N-methyl-d-aspartate receptors (NMDARs) has been implicated as a potential etiological mechanism. Previous studies have accumulated evidence supporting NMDAR-encoding genes' role in etiology of SCZ and ASD. We performed a screening study for exonic regions of GRIN1, GRIN2A, GRIN2C, GRIN2D, GRIN3A, and GRIN3B, which encode NMDAR subunits, in 562 participates (370 SCZ and 192 ASD). Forty rare variants were identified including 38 missense, 1 frameshift mutation in GRIN2C and 1 splice site mutation in GRIN2D. We conducted in silico analysis for all variants and detected seven missense variants with deleterious prediction. De novo analysis was conducted if pedigree samples were available. The splice site mutation in GRIN2D is predicted to result in intron retention by minigene assay. Furthermore, the frameshift mutation in GRIN2C and splice site mutation in GRIN2D were genotyped in an independent sample set comprising 1877 SCZ cases, 382 ASD cases, and 2040 controls. Both of them were revealed to be singleton. Our study gives evidence in support of the view that ultra-rare variants with loss of function (frameshift, nonsense or splice site) in NMDARs genes may contribute to possible risk of SCZ.

Depressive symptoms are a serious problem in workplaces. Hospital staff members, such as newly licensed registered nurses (NLRNs), are at particularly increased risk of these symptoms owing to their limited experience. Previous studies have shown that a brief program-based cognitive behavioral therapy program (CBP) can offer effective treatment. Here, we conducted a longitudinal observational study of 683 NLRNs (CBP group, n = 522; no-CBP group, n = 181) over a period of 1 year (six times surveys were done during this period). Outcomes were assessed on the basis of surveys that covered the Beck Depression Inventory-I (BDI). The independent variables were CBP attendance (CBP was conducted 3 months after starting work), personality traits, personal stressful life events, workplace adversity, and pre-CBP change in BDI in the 3 months before CBP (ΔBDIpre-CBP). All factors were included in Cox proportional hazards models with time-dependent covariates for depressive symptoms (BDI ≥10), and we reported hazard ratios (HRs). Based on this analysis, we detected that CBP was significantly associated with benefit for depressive symptoms in all NLRNs (Puncorrected = 0.0137, HR = 0.902). To identify who benefitted most from CBP, we conducted a subgroup analysis based on the change in BDI before CBP (ΔBDIpre-CBP). The strongest association was when BDI scores were low after starting work and increased before CBP (Puncorrected = 0.00627, HR = 0.616). These results are consistent with previous findings, and indicate that CBP may benefit the mental health of NLRNs. Furthermore, selective prevention based on the pattern of BDI change over time may be important in identifying who should be offered CBP first. Although CBP is generally effective for all nurses, such a selective approach may be most appropriate where cost-effectiveness is a prominent concern.

Genome‐wide association studies (GWASs) are highly effective at identifying common risk variants for schizophrenia. Rare risk variants are also important contributors to schizophrenia etiology but, with the exception of large copy number variants, are difficult to detect with GWAS. Exome and genome sequencing, which have accelerated the study of rare variants, are expensive so alternative methods are needed to aid detection of rare variants. Here we re‐analyze an Irish schizophrenia GWAS dataset (n = 3,473) by performing identity‐by‐descent (IBD) mapping followed by exome sequencing of individuals identified as sharing risk haplotypes to search for rare risk variants in coding regions. We identified 45 rare haplotypes (>1 cM) that were significantly more common in cases than controls. By exome sequencing 105 haplotype carriers, we investigated these haplotypes for functional coding variants that could be tested for association in independent GWAS samples. We identified one rare missense variant in PCNT but did not find statistical support for an association with schizophrenia in a replication analysis. However, IBD mapping can prioritize both individual samples and genomic regions for follow‐up analysis but genome rather than exome sequencing may be more effective at detecting risk variants on rare haplotypes. National Institutes of Health, Grant/Award Numbers: R01‐MH041953, R01‐MH083094; Science Foundation Ireland, Grant/Award Numbers: 08/IN.1/B1916, 12/IP/1359, 12/IP/1670; Wellcome Trust, Grant/Award Number: 085475/B/08/Z peer-reviewed

Genome-wide association studies (GWASs) have identified several susceptibility loci for bipolar disorder (BD) and shown that the genetic architecture of BD can be explained by polygenicity, with numerous variants contributing to BD. In the present GWAS (Phase I/II), which included 2964 BD and 61 887 control subjects from the Japanese population, we detected a novel susceptibility locus at 11q12.2 (rs28456, P=6.4 × 10−9), a region known to contain regulatory genes for plasma lipid levels (FADS1/2/3). A subsequent meta-analysis of Phase I/II and the Psychiatric GWAS Consortium for BD (PGC-BD) identified another novel BD gene, NFIX (P best=5.8 × 10−10), and supported three regions previously implicated in BD susceptibility: MAD1L1 (P best=1.9 × 10−9), TRANK1 (P best=2.1 × 10−9) and ODZ4 (P best=3.3 × 10−9). Polygenicity of BD within Japanese and trans-European-Japanese populations was assessed with risk profile score analysis. We detected higher scores in BD cases both within (Phase I/II) and across populations (Phase I/II and PGC-BD). These were defined by (1) Phase II as discovery and Phase I as target, or vice versa (for ‘within Japanese comparisons’, Pbest~10−29, R2~2%), and (2) European PGC-BD as discovery and Japanese BD (Phase I/II) as target (for ‘trans-European-Japanese comparison,’ Pbest~10−13, R2~0.27%). This ‘trans population’ effect was supported by estimation of the genetic correlation using the effect size based on each population (liability estimates~0.7). These results indicate that (1) two novel and three previously implicated loci are significantly associated with BD and that (2) BD ‘risk’ effect are shared between Japanese and European populations.

Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (odds ratio (OR) = 1.11, P = 5.7 x 10(-15)), which persisted after excluding loci implicated in previous studies (OR = 1.07, P = 1.7 x 10(-6)). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 x 10(-11)) and neurobehavioral phenotypes in mouse (OR = 1.18, P = 7.3 x 10(-5)). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by nonallelic homologous recombination. Refereed/Peer-reviewed

Recent schizophrenia (SCZ) studies have reported an increased burden of de novo copy number variants (CNVs) and identified specific high-risk CNVs, although with variable phenotype expressivity. However, the pathogenesis of SCZ has not been fully elucidated. Using array comparative genomic hybridization, we performed a high-resolution genome-wide CNV analysis on a mainly (92%) Japanese population (1699 SCZ cases and 824 controls) and identified 7066 rare CNVs, 70.0% of which were small (

There is insufficient serotonergic neuronal function in the pathophysiology of major depressive disorder (MDD). Serotonin transporter (SERT) plays a critical role in terminating the function of serotoninergic neurons. SERT is linked to vulnerability to MDD and is an important target for antidepressants. The expression of SERT in lymphocytes and platelets is associated with their expression in central nervous system. Most of the clinical studies that have analyzed the role of SERT in depression have focused on absolute expression of SERT in the brain or peripheral tissue. Our study has shown that the SERT protein is ubiquitinated, which has been implicated through the SERT stability and depressive behaviors in mice. In our study, we have used lymphoblasts derived from the peripheral blood lymphocytes to quantitatively examine SERT protein expression and ubiquitination in fluvoxamine-responsive and fluvoxamine-resistant MDD patients. We found that the protein levels of SERT were higher in the fluvoxamine-resistant MDD patients. Ubiquitinated protein levels of SERT were lower in the fluvoxamine-resistant MDD patients. The proteasome inhibitor failed to increase the protein levels of SERT in both fluvoxamine-responsive and fluvoxamine-resistant MDD patients. In sum, these findings suggest that the downregulation of the ubiquitination of SERT protein induces insufficient degradation of SERT by proteasome, which resulted in the upregulation of SERT protein in fluvoxamine-resistant MDD patients. Although further studies with various populations will be required to generalize results, SERT protein expression, ubiquitination, and the responsiveness of SERT expression to proteasome inhibitor are potential biomarkers for the diagnosis of MDD and antidepressant efficacy.

Major depressive disorder (MDD) is a common and disabling psychiatric disorder. A recent mega analysis of genome-wide association studies (GWASs) identified 44 loci associated with MDD, though most of the genetic etiologies of the MDD/psychological distress remain unclear. To further understand the genetic basis of MDD/psychological distress, we conducted a GWAS in East Asia with more than 10,000 participants of Japanese ancestry who had enrolled in a direct-to-consumer genetic test. After quality control on the genotype data, 10,330 subjects with a total of 8,567,708 imputed SNPs were eligible for the analysis. The participants completed a self-administered questionnaire on their past medical history and health conditions that included the 6-item Kessler screening scale (K6 scale) for psychological distress (cut-off point of 5) and past medical history of MDD, resulting in 3981 subjects assigned to “psychologically distressed group” [cases], and the remaining 6349 subjects were assigned to the “non-psychologically distressed group” [controls]. In this GWAS, we found an association with genome-wide significance at rs6073833 (P = 7.60 × 10−9) in 20q13.12. This is, to the best of our knowledge, the first large-scale GWAS for psychological distress using data from direct-to-consumer (DTC) genetic tests in a population of non-European-ancestry, and the present study thus detected a novel locus significantly associated with psychological distress in the Japanese population.

Accumulating evidence suggests that aberrant epigenetic regulation is involved in the pathophysiology of major psychiatric disorders such as schizophrenia (SZ) and bipolar disorder (BD). We previously showed that the plasma level of betaine (N,N,N-trimethylglycine), a methyl-group donor, was significantly decreased in patients with first episode schizophrenia (FESZ). In this study, we identified decrease of global DNA methylation level in FESZ (N = 24 patients vs N = 42 controls), and found that global DNA methylation level was inversely correlated with scores on the global assessment of functioning (GAF) scale, and positively correlated with plasma betaine level. Notably, correlations between levels of betaine and its metabolites (N,N-dimethylglycine and sarcosine, N-methylglycine) were lower or lost in FESZ plasma, but remained high in controls. We further examined global DNA methylation levels in patients with chronic SZ (N = 388) and BD (N = 414) as well as controls (N = 430), and confirmed significant hypomethylation and decreased betaine level in SZ. We also found that patients with BD type I, but not those with BD type II, showed significant global hypomethylation. These results suggest that global hypomethylation associated with decreased betaine level in blood cells is common to SZ and BD, and may reflect common pathophysiology such as psychotic symptoms.

Enhanced carbonyl stress has been observed in a subgroup of patients with schizophrenia. Glyoxalase I, which is encoded by GLO1, is an enzyme that protects against carbonyl stress. In this study, we focused on the association between rare genetic variants of GLO1 and schizophrenia. First, we identified one heterozygous frameshift variant, p.P122fs, in 370 Japanese schizophrenia cases with allele frequencies of up to 1% by exon-targeted mutation screening of GLO1. We then performed an association analysis on 1282 cases and 1764 controls with this variant. The variant was found in three cases and eight controls. There was no statistically significant association between p.P122fs in GLO1 and schizophrenia (P=0.25). This frameshift variant in GLO1 might occur at near-polymorphic frequencies in the Japanese population, although further investigations using larger samples and biological analyses are needed to exclude the possibility of a low-penetrance genetic risk associated with this variant.

Cigarette smoking is a risk factor for a wide range of human diseases1. To investigate the genetic components associated with smoking behaviours in the Japanese population, we conducted a genome-wide association study of four smoking-related traits using up to 165,436 individuals. In total, we identified seven new loci, including three loci associated with the number of cigarettes per day (EPHX2–CLU, RET and CUX2–ALDH2), three loci associated with smoking initiation (DLC1, CXCL12–TMEM72-AS1 and GALR1–SALL3) and LINC01793–MIR4432HG, associated with the age of smoking initiation. Of these, three loci (LINC01793–MIR4432HG, CXCL12–TMEM72-AS1 and GALR1–SALL3) were found by conducting an additional sex-stratified genome-wide association study. This additional analysis showed heterogeneity of effects between sexes. The cross-sex linkage disequilibrium score regression2,3 analysis also indicated that the genetic component of smoking initiation was significantly different between the sexes. Cross-trait linkage disequilibrium score regression analysis and trait-relevant tissue analysis showed that the number of cigarettes per day has a specific genetic background distinct from those of the other three smoking behaviours. We also report 11 diseases that share genetic basis with smoking behaviours. Although the current study should be carefully considered owing to the lack of replication samples, our findings characterized the genetic architecture of smoking behaviours. Further studies in East Asian populations are warranted to confirm our findings. Matoba et al. examine genetic components of smoking behaviours in the Japanese population, identifying seven novel loci and 11 diseases that share genetic bases with smoking behaviours.

To understand the genetics of type 2 diabetes in people of Japanese ancestry, we conducted A meta-analysis of four genome-wide association studies (GWAS; 36,614 cases and 155,150 controls of Japanese ancestry). We identified 88 type 2 diabetes-associated loci (P 5.0 × 10

Background: Alterations in one-carbon metabolism have been associated with schizophrenia, and vitamin B6 is one of the key components in this pathway. Methods: We first conducted a case–control study of serum pyridoxal levels and schizophrenia in a large Japanese cohort (n = 1276). Subsequently, we conducted a meta-analysis of association studies (n = 2125). Second, we investigated whether rs4654748, which was identified in a genome-wide association study as a vitamin B6-related single nucleotide polymorphism, was genetically implicated in patients with schizophrenia in the Japanese population (n = 10 689). Finally, we assessed the effect of serum pyridoxal levels on schizophrenia risk using a Mendelian randomization (MR) approach. Results: Serum pyridoxal levels were significantly lower in patients with schizophrenia than in controls, not only in our cohort, but also in the pooled data set of the meta-analysis of association studies (standardized mean difference –0.48, 95% confidence interval [CI] –0.57 to –0.39, p = 9.8 × 10–24). We failed to find a significant association between rs4654748 and schizophrenia. Furthermore, an MR analysis failed to find a causal relationship between pyridoxal levels and schizophrenia risk (odds ratio 0.99, 95% CI 0.65–1.51, p = 0.96). Limitations: Food consumption and medications may have affected serum pyridoxal levels in our cross-sectional study. Sample size, number of instrumental variables and substantial heterogeneity among patients with schizophrenia are limitations of an MR analysis. Conclusion: We found decreased serum pyridoxal levels in patients with schizophrenia in this observational study. However, we failed to obtain data supporting a causal relationship between pyridoxal levels and schizophrenia risk using the MR approach.

Many patients with schizophrenia have poor clinical and social outcomes. Some risk alleles closely related to the onset of schizophrenia have been reported to be associated with their clinical phenotypes, but the direct relationship between genetic vulnerability to schizophrenia and clinical/social outcomes of schizophrenia, as evaluated by both practical clinical scales and 'real-world' function, has not been investigated. We evaluated the clinical and social outcomes of 455 Japanese patients with schizophrenia by severity of illness according to the Clinical Global Impression-Severity Scale (CGI-S) and social outcomes by social adjustment/maladjustment at 5 years after the first visit. We examined whether 46 single nucleotide polymorphisms (SNPs) selected from a Japanese genome-wide association study of susceptibility to schizophrenia were associated with clinical and social outcomes. We also investigated the polygenic risk scores of 46 SNPs. Allele-wise association analysis detected three SNPs, including rs2623659 in the CUB and Sushi multiple domains-1 (CSMD1) gene, associated with severity of illness at end point. The severity of illness at end point was associated with treatment response, but not with the severity of illness at baseline. Three SNPs, including rs2294424 in the C6orf105 gene, were associated with social outcomes. Point estimates of odds ratios showed positive relationships between polygenic risk scores and clinical/social outcomes; however, the results were not statistically significant. Because these results are exploratory, we need to replicate them with a larger sample in a future study.

Although a number of genome-wide association studies (GWASs) of late-onset Alzheimer's disease (LOAD) have been carried out, there have been little GWAS data on East Asian populations.To discover the novel susceptibility loci of LOAD, we carried out a GWAS using 816 LOAD cases and 7992 controls with a replication analysis using an independent panel of 1011 LOAD cases and 7212 controls in a Japanese population. In addition, we carried out a stratified analysis by APOE-ε4 status to eliminate the established effect of APOE region.Our data indicated that 18p11.32 (rs1992269, P = 9.77 × 10(-7)), CNTNAP2 (rs802571, P = 1.26 × 10(-6)), and 12q24.23 (rs11613092, P = 6.85 × 10(-6)) were suggestive loci for susceptibility to LOAD.We identified three suggestive loci for susceptibility to LOAD in a Japanese population. Among these, rs802571, located at intron 1 of CNTNAP2, was considered to be a plausible candidate locus from a functional perspective.

Many observational studies have shown elevated blood CRP levels in schizophrenia compared with controls, and one population-based prospective study has reported that elevated plasma CRP levels were associated with late- and very-late-onset schizophrenia. Furthermore, several clinical studies have reported the efficacy of anti-inflammatory drugs on the symptoms in patients with schizophrenia. However, whether elevated CRP levels are causally related to schizophrenia is not still established because of confounding factors and reverse causality. In the present study, we demonstrated that serum CRP levels were significantly higher in patients with schizophrenia than in the controls by conducting a case-control study and a meta-analysis of case-control studies between schizophrenia and serum CRP levels. Furthermore, we provided evidence for a causal association between elevated CRP levels and increased schizophrenia risk by conducting a Mendelian randomization analysis. Our findings suggest that elevated CRP itself may be a causal risk factor for schizophrenia.

Schizophrenia (SZ) and bipolar disorder (BD) have been known to share genetic and environmental risk factors, and complex gene-environmental interactions may contribute to their pathophysiology. In contrast to high genetic overlap between SZ and BD, as revealed by genome-wide association studies, the extent of epigenetic overlap remains largely unknown. In the present study, we explored whether SZ and BD share epigenetic risk factors in the same manner as they share genetic components.We performed DNA methylation analyses of the CpG sites in the top five candidate regions (FAM63B, ARHGAP26, CTAGE11P, TBC1D22A, and intergenic region [IR] on chromosome 16) reported in a previous methylome-wide association study (MWAS) of SZ, using whole blood samples from subjects with BD and controls.Among the five candidate regions, the CpG sites in FAM63B and IR on chromosome 16 were significantly hypomethylated in the samples from subjects with BD as well as those from subjects with SZ. On the other hand, the CpG sites in TBC1D22A were hypermethylated in the samples from subjects with BD, in contrast to hypomethylation in the samples from subjects with SZ.Hypomethylation of FAM63B and IR on chromosome 16 could be common epigenetic risk factors for SZ and BD. Further comprehensive epigenetic studies for BD, such as MWAS, will uncover the extent of similarity and uniqueness of epigenetic alterations.

Clinical measurements can be viewed as useful intermediate phenotypes to promote understanding of complex human diseases. To acquire comprehensive insights into the underlying genetics, here we conducted a genome-wide association study (GWAS) of 58 quantitative traits in 162,255 Japanese individuals. Overall, we identified 1,407 trait-associated loci (P 5.0 × 10

Cognitive impairments are a core feature in patients with schizophrenia. These deficits could serve as effective tools for understanding the genetic architecture of schizophrenia. This study investigated whether genetic variants associated with cognitive impairments aggregate in functional gene networks related to the pathogenesis of schizophrenia. Here, genome-wide association studies (GWAS) of a range of cognitive phenotypes relevant to schizophrenia were performed in 411 healthy subjects. We attempted to replicate the GWAS data using 257 patients with schizophrenia and performed a meta-analysis of the GWAS findings and the replicated results. Because gene networks, rather than a single gene or genetic variant, may be strongly associated with the susceptibility to schizophrenia and cognitive impairments, gene-network analysis for genes in close proximity to the replicated variants was performed. We observed nominal associations between 3054 variants and cognitive phenotypes at a threshold of P1.0 × 10(-) (4). Of the 3054 variants, the associations of 191 variants were replicated in the replication samples (P.05). However, no variants achieved genome-wide significance in a meta-analysis (P5.0 × 10(-) (8)). Additionally, 115 of 191 replicated single nucleotide polymorphisms (SNPs) have genes located within 10 kb of the SNPs (60.2%). These variants were moderately associated with cognitive phenotypes that ranged from P = 2.50 × 10(-) (5) to P = 9.40 × 10(-) (8). The genes located within 10 kb from the replicated SNPs were significantly grouped in terms of glutamate receptor activity (false discovery rate (FDR) q = 4.49 × 10(-) (17)) and the immune system related to major histocompatibility complex class I (FDR q = 8.76 × 10(-) (11)) networks. Our findings demonstrate that genetic variants related to cognitive trait impairment in schizophrenia are involved in the N-methyl-d-aspartate glutamate network.

An altered sulcogyral pattern in the orbitofrontal cortex (OFC) has been implicated in schizophrenia as a possible marker of abnormal neurodevelopment, while its genetic mechanism remains unknown. This magnetic resonance imaging study investigated the relationship between the polymorphism of YWHAE (rs28365859), a gene encoding 14-3-3epsilon that is a Disrupted-in-Schizophrenia 1 (DISC1)-interacting molecule associated with neuronal development, and the OFC subtypes of the ‘H-shaped’ sulcus (Types I, II, and III) in a Japanese sample of 72 schizophrenia patients and 86 healthy controls. The schizophrenia patients had significantly increased Type III (p = 0.004) and decreased Type I (p = 0.013) expression on the right hemisphere compared to the controls. The subjects carrying the protective C allele showed a decrease in Type III (p = 0.005) and an increase in Type I (p = 0.017) compared to the G allele homozygotes, especially for the healthy subjects in the left hemisphere. These results suggest a possible role for the YWHAE genotype in the early development of the OFC sulcogyral pattern, but its effect alone is not likely to explain the altered sulcogyral pattern in schizophrenia.

Recent genome-wide association studies (GWASs) of schizophrenia (SCZ) identified several susceptibility genes and suggested shared genetic components between SCZ and bipolar disorder (BD). We conducted a genetic association study of single nucleotide polymorphisms (SNPs) selected according to previous SCZ GWAS targeting psychotic disorders (SCZ and BD) in the Japanese population. Fifty-one SNPs were analyzed in a two-stage design using first-set screening samples (all SNPs: 1,032 SCZ, 1,012 BD, and 993 controls) and second-set replication samples (“significant” SNPs in the first-set screening analysis: 1,808 SCZ, 821 BD, and 2,321 controls). We assessed allelic associations between the selected SNPs and the three phenotypes (SCZ, BD, and “psychosis” [SCZ + BD]). Nine SNPs revealed nominal association signals for all comparisons (Puncorrected

Atypical psychosis with a periodic course of exacerbation and features of major psychiatric disorders [schizophrenia (SZ) and bipolar disorder (BD)] has a long history in clinical psychiatry in Japan. Based upon the new criteria of atypical psychosis, a Genome-Wide Association Study (GWAS) was conducted to identify the risk gene or variants. The relationships between atypical psychosis, SZ and BD were then assessed using independent GWAS data. Forty-seven patients with solid criteria of atypical psychosis and 882 normal controls (NCs) were scanned using an Affymetrics 6.0 chip. GWAS SZ data (560 SZ cases and 548 NCs) and GWAS BD (107 cases with BD type 1 and 107 NCs) were compared using gene-based analysis. The most significant SNPs were detected around the CHN2/CPVL genes (rs245914, P = 1.6 × 10−7), COL21A1 gene (rs12196860, P = 2.45 × 10−7), and PYGL/TRIM9 genes (rs1959536, P = 7.73 × 10−7), although none of the single-nucleotide polymorphisms exhibited genome-wide significance (P = 5 × 10−8). One of the highest peaks was detected on the major histocompatibility complex region, where large SZ GWASs have previously disclosed an association. The gene-based analysis suggested significant enrichment between SZ and atypical psychosis (P = 0.01), but not BD. This study provides clues about the types of patient whose diagnosis lies between SZ and BD. Studies with larger samples are required to determine the causal variant. © 2013 Wiley Periodicals, Inc.

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg=-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness., published version, peerReviewed

Bipolar disorder (BPD) and major depressive disorder (MDD) are primary major mood disorders. Recent studies suggest that they share certain psychopathological features and common risk genes, but unraveling the full genetic architecture underlying the risk of major mood disorders remains an important scientific task. The public genome-wide association study (GWAS) data sets offer the opportunity to examine this topic by utilizing large amounts of combined genetic data, which should ultimately allow a better understanding of the onset and development of these illnesses. Genome-wide meta-analysis was performed by combining two GWAS data sets on BPD and MDD (19,637 cases and 18,083 controls), followed by replication analyses for the loci of interest in independent 12,364 cases and 76,633 controls from additional samples that were not included in the two GWAS data sets. The single-nucleotide polymorphism (SNP) rs10791889 at 11q13.2 was significant in both discovery and replication samples. When combining all samples, this SNP and multiple other SNPs at 2q11.2 (rs717454), 8q21.3 (rs10103191), and 11q13.2 (rs2167457) exhibited genome-wide significant association with major mood disorders. The SNPs in 2q11.2 and 8q21.3 were novel risk SNPs that were not previously reported, and SNPs at 11q13.2 were in high LD with potential BPD risk SNPs implicated in a previous GWAS. The genome-wide significant loci at 2q11.2 and 11q13.2 exhibited strong effects on the mRNA expression of certain nearby genes in cerebellum. In conclusion, we have identified several novel loci associated with major mood disorders, adding further support for shared genetic risk between BPD and MDD. Our study highlights the necessity and importance of mining public data sets to explore risk genes for complex diseases such as mood disorders.

Reticulon 4 receptor (RTN4R) plays an essential role in regulating axonal regeneration and plasticity in the central nervous system through the activation of rho kinase, and is located within chromosome 22q11.2, a region that is known to be a hotspot for schizophrenia (SCZ) and autism spectrum disorder (ASD). Recently, rare variants such as copy-number variants and single-nucleotide variants have been a focus of research because of their large effect size associated with increased susceptibility to SCZ and ASD and the possibility of elucidating the pathophysiology of mental disorder through functional analysis of the discovered rare variants. To discover rare variants with large effect size and to evaluate their role in the etiopathophysiology of SCZ and ASD, we sequenced the RTN4R coding exons with a sample comprising 370 SCZ and 192 ASD patients, and association analysis using a large number of unrelated individuals (1716 SCZ, 382 ASD and 4009 controls). Through this mutation screening, we discovered four rare (minor allele frequency

N-methyl-d-aspartate receptors (NMDARs) play a critical role in excitatory synaptic transmission and plasticity in the central nervous systems. Recent genetics studies in schizophrenia (SCZ) show that SCZ is susceptible to NMDARs and the NMDAR signaling complex. In autism spectrum disorder (ASD), several studies report dysregulation of NMDARs as a risk factor for ASD. To further examine the association between NMDARs and SCZ/ASD development, we conducted a mutation screening study of GRIN2B which encodes NR2B subunit of NMDARs, to identify rare mutations that potentially cause diseases, in SCZ and ASD patients (n = 574 and 152, respectively). This was followed by an association study in a large sample set of SCZ, ASD, and normal healthy controls (n = 4145, 381, and 4432, respectively). We identified five rare missense mutations through the mutation screening of GRIN2B. Although no statistically significant association between any single mutation and SCZ or ASD was found, one of its variant, K1292R, is found only in the patient group. To further examine the association between mutations in GRIN2B and SCZ/ASD development, a larger sample size and functional experiments are needed.

Oxytocin appears beneficial for autism spectrum disorder (ASD), and more than 20 single-nucleotide polymorphisms (SNPs) in oxytocin receptor (OXTR) are relevant to ASD. However, neither biological functions of OXTR SNPs in ASD nor critical OXTR SNPs that determine oxytocin's effects on ASD remains known. Here, using a machine-learning algorithm that was designed to evaluate collective effects of multiple SNPs and automatically identify most informative SNPs, we examined relationships between 27 representative OXTR SNPs and six types of behavioral/neural response to oxytocin in ASD individuals. The oxytocin effects were extracted from our previous placebo-controlled within-participant clinical trial administering single-dose intranasal oxytocin to 38 high-functioning adult Japanese ASD males. Consequently, we identified six different SNP sets that could accurately predict the six different oxytocin efficacies, and confirmed the robustness of these SNP selections against variations of the datasets and analysis parameters. Moreover, major alleles of several prominent OXTR SNPs-including rs53576 and rs2254298-were found to have dissociable effects on the oxytocin efficacies. These findings suggest biological functions of the OXTR SNP variants on autistic oxytocin responses, and implied that clinical oxytocin efficacy may be genetically predicted before its actual administration, which would contribute to establishment of future precision medicines for ASD.

Genome-wide association and follow-up studies have reported an association between schizophrenia and rs12807809 of the NRGN gene on chromosome 11q24.2. We investigated the association of five linkage disequilibrium-tagging SNPs and haplotypes that cover the NRGN gene with schizophrenia in a Japanese sample of 2,019 schizophrenia patients and 2,574 controls to determine whether rs12807809 is the most strongly associated variant for schizophrenia in the vicinity of the NRGN gene. We found that the rs12807809–rs12278912 haplotype of the NRGN gene was associated with schizophrenia (global P = 0.0042). The frequencies of the TG and TA haplotypes of rs12807809–rs12278912 in patients were higher (OR = 1.14, P = 0.0019) and lower (OR = 0.85, P = 0.0053), respectively, than in the controls. We did not detect any evidence of association of schizophrenia with any SNPs; however, two nominal associations of rs12278912 (OR = 1.10, P = 0.057) and rs2075713 (OR = 1.10, P = 0.057) were observed. Furthermore, we detected an association between the rs12807809–rs12278912 haplotype and NRGN expression in immortalized lymphoblasts derived from 45 HapMap JPT subjects (z = 2.69, P = 0.007) and confirmed the association in immortalized lymphoblasts derived from 42 patients with schizophrenia and 44 healthy controls (z = 3.09, P = 0.002). The expression of the high-risk TG haplotype was significantly lower than the protective TA haplotype. The expression was lower in patients with schizophrenia than in controls; however, this difference was not statistically significant. This study provides further evidence of the association of the NRGN gene with schizophrenia, and our results suggest that there is a link between the TG haplotype of rs12807809–rs12278912, decreased expression of NRGN and risk of developing schizophrenia. © 2012 Wiley Periodicals, Inc.

Pro-brain natriuretic peptide (proBNP)-108 and N-terminal proBNP-76 (NT-BNP) contain seven sites for O-linked oligosaccharide attachment. Currently, levels of glycosylated NT-BNP are probably underestimated because it is not recognised by one antibody in the sandwich assay system. The pathophysiological significance of cardiac and plasma levels of non-glycosylated (nonglyNT-BNP) and glycosylated NT-BNP (glyNT-BNP) in heart failure (HF) and chronic renal failure (CRF) was investigated.Plasma samples from 186 patients with HF and 76 patients with CRF on haemodialysis were studied, together with 11 atrial tissue samples. To measure nonglyNT-BNP and glyNT-BNP, samples were incubated with or without deglycosylating enzymes and NT-BNP was measured using Roche Elecsys proBNP I. The percentage glyNT-BNP was calculated as glyNT-BNP/(glyNT-BNP + nonglyNT-BNP).In HF, plasma BNP, nonglyNT-BNP and glyNT-BNP levels all increased with increasing disease severity (New York Heart Association class; p0.0001), though the molar ratio remained constant (molar ratio, BNP:nonglyNT-BNP:glyNT-BNP = 1:2.4:9.6). Before haemodialysis for CRF, plasma BNP and nonglyNT-BNP were somewhat elevated, and glyNT-BNP was markedly increased (molar ratio, BNP:nonglyNT-BNP:glyNT-BNP = 1:8.5:82). After haemodialysis, plasma BNP, nonglyNT-BNP, atrial natriuretic protein and cGMP all declined (p0.0001), but glyNT-BNP was unchanged. Notably, the percentage of glyNT-BNP was elevated before haemodialysis, and was further increased after haemodialysis (p0.0001). Atrial tissue levels of BNP, nonglyNT-BNP and glyNT-BNP were similar.THE findings suggest that most endogenous plasma NT-BNP is glycosylated and therefore undetectable with the current assay system, and that the relative glycosylation level is increased by haemodialysis.

BACKGROUND: Genome-wide association studies have detected a small number of weak but strongly supported schizophrenia risk alleles. Moreover, a substantial polygenic component to the disorder consisting of a large number of such alleles has been reported by the International Schizophrenia Consortium. METHOD: We report a Japanese genome-wide association study of schizophrenia comprising 575 cases and 564 controls. We attempted to replicate 97 markers, representing a nonredundant panel of markers derived mainly from the top 150 findings, in up to three data sets totaling 1990 cases and 5389 controls. We then attempted to replicate the observation of a polygenic component to the disorder in the Japanese and to determine whether this overlaps that seen in UK populations. RESULTS: Single-locus analysis did not reveal genome-wide support for any locus in the genome-wide association study sample (best p = 6.2 × 10(-6)) or in the complete data set in which the best supported locus was SULT6B1 (rs11895771: p = 3.7 × 10(-5) in the meta-analysis). Of loci previously supported by genome-wide association studies, we obtained in the Japanese support for NOTCH4 (rs2071287: p(meta) = 5.1 × 10(-5)). Using the approach reported by the International Schizophrenia Consortium, we replicated the observation of a polygenic component to schizophrenia within the Japanese population (p = .005). Our trans Japan-UK analysis of schizophrenia also revealed a significant correlation (best p = 7.0 × 10(-5)) in the polygenic component across populations. CONCLUSIONS: These results indicate a shared polygenic risk of schizophrenia between Japanese and Caucasian samples, although we did not detect unequivocal evidence for a novel susceptibility gene for schizophrenia.

It is known that pica, the consumption of non-nutritive substances such as kaolin, can be induced by administration of toxins or emetic agents in rats. In the present study, we examined the effects of intraperitoneal (i.p.) administration of cyclophosphamide on pica behavior and on the concentration of 5-hydroxyindoleacetic acids (5HIAA) in cerebrospinal fluid (CSF) in the following five strains of adult male rats: Sprague Dawley (SD), Wistar, Fischer 344 (F344), Wistar-Imamichi (WI) and Long Evans (LE). Cyclophosphamide (25 mg or 50 mg/kg) was injected (i.p.) into the rats and kaolin and food intake were measured at 24 hr after injection. The animals were anesthetized with urethane (1 g/kg) at 3 hr after injection of cyclophosphamide, and CSF was collected from the cisterna magna. WI and LE rats clearly showed pica behavior as compared with the other strains. In LE rats, the concentration of 5HIAA in CSF also increased in a dose-dependent manner of cyclophosphamide. The pretreatment with ondansetron (5-HT(3) antagonist) restored both changes (kaolin consumption and 5HIAA levels) induced by cyclophosphamide. These results suggest that the LE rat is sensitive to cyclophosphamide, that pica induced by cyclophosphamide mimics many aspects of emesis including the serotonergic response in the central nervous system and that use of the pica model would be a practical method for evaluating the effects of antiemetic drugs in addition to the mechanism of emesis.

Our genome-wide association study of schizophrenia found association signals at the Kalirin gene (KALRN) and EPH receptor B1 gene (EPHB1) in a Japanese population. The importance of these synaptogenic pathway genes in schizophrenia is gaining independent supports. Although there has been growing interest in rare (1%) missense mutations as potential contributors to the unexplained heritability of schizophrenia, there are no population-based studies targeting rare (1%) coding mutations with a larger effect size (eg, OR1.5) in KALRN or EPHB1.The present study design consisted of 3 phases. At the discovery phase, we conducted resequencing analyses for all exon regions of KALRN and EPHB1 using a DNA microarray-based method. Seventeen rare (1%) missense mutations were discovered in the first sample set (320 schizophrenic patients). After the prioritization phase based on frequencies in the second sample set (729 cases and 562 controls), we performed association analyses for each selected mutation using the third sample set (1511 cases and 1517 controls), along with a combined association analysis across all selected mutations. In KALRN, we detected a significant association between schizophrenia and P2255T (OR = 2.09, corrected P = .048, 1 tailed); this was supported in the combined association analysis (OR = 2.07, corrected P = .006, 1 tailed). We found no evidence of association of EPHB1 with schizophrenia. In silico analysis indicated the functional relevance of these rare missense mutations.We provide evidence that multiple rare (1%) missense mutations in KALRN may be genetic risk factors for schizophrenia.

The chitinase 3-like 1 (CHI3L1) gene acts as a cellular survival factor in response to several environmental and psychosocial stresses. The expression level of CHI3L1 was increased in the hippocampus and prefrontal cortex regions of patients with schizophrenia. Genetic variants of the CHI3L1 gene have been significantly associated with schizophrenia in two distinct ethnic groups, the Chinese and Irish populations. The aims of this study are to confirm the association between the CHI3L1 gene and schizophrenia in a Japanese population using the largest sample size to date (1463 cases and 1795 controls) and perform a meta-analysis of the combined samples (3005 cases, 3825 controls and 601 trios). We found significant associations between single nucleotide polymorphism (SNP) 4/rs4950928 (p=0.009), which is located in the promoter region of the CHI3L1 gene, and haplotypes including this SNP and schizophrenia (the most significant global p0.001). As the meta-analysis of the combined samples showed significant heterogeneity among studies of SNP3/rs10399805 (p=0.026) and SNP4 (p0.001), we performed meta-analyses separately in the Japanese (2033 cases and 2365 controls) and Chinese populations (412 cases, 464 controls and 601 trios), the major groups analyzed in association studies of the CHI3L1 gene. The meta-analysis in Japanese populations showed stronger evidence for the association of schizophrenia with SNP4 (p=0.003), while the meta-analysis in Chinese populations showed an association with a different variant (SNP3) (p=0.003). We conclude that the genetic variants in the CHI3L1 gene have ethnic heterogeneity and confer a susceptibility to schizophrenia in Asian populations.

Several investigations have reported that the translin-associated factor X gene (TSNAX)/disrupted-in-schizophrenia-1 gene (DISC1) was associated with major psychiatric disorders including schizophrenia, bipolar disorder (BP), and major depressive disorder (MDD). TSNAX is located immediately upstream of DISC1, and has been shown to undergo intergenic splicing with DISC1. It thus may also be influenced by translocation. To our knowledge, there are no reported gene-based association analyses between TSNAX and mood disorders in the Japanese population. We conducted a case-control study of Japanese samples (158 bipolar patients, 314 major depressive disorder patients, and 811 controls) with three tagging SNPs in TSNAX, selected using HapMap database. In addition, we performed an association analysis between TSNAX and the efficacy of fluvoxamine treatment in 120 Japanese patients with MDD. The MDD patients in this study had scores of 12 or higher on the 17 items of the Structured Interview Guide for Hamilton Rating Scale for Depression (SIGH-D). We defined a clinical response as a decrease of more than 50% in baseline SIGH-D within 8 weeks, and clinical remission as an SIGH-D score of less than 7 at 8 weeks. We found an association between rs766288 in TSNAX and female MDD in the allele/genotype analysis. However, we did not find any association between TSNAX and BP or the fluvoxamine therapeutic response in MDD in the allele/genotype analysis or haplotype analysis. Our results suggest that rs766288 in TSNAX may play a role in the pathophysiology of female MDD in the Japanese population. A replication study using larger samples may be required for conclusive results, since our sample size was small.

Several genetic studies have shown an association between the 5-HT1A receptor gene (HTR1A) and major depressive disorder (MDD); however, results have been rather inconsistent. Moreover, to our knowledge, no association study on HTR1A and MDD in the Japanese population has been reported. Therefore, to evaluate the association between HTR1A and MDD, we conducted a case-control study of Japanese population samples with two single-nucleotide polymorphisms (SNPs), including rs6295 (C-1019G) in HTR1A. In addition, we conducted a meta-analysis of rs6295, which has been examined in other papers. Using one functional SNP (rs6295) and one tagging SNP (rs878567) selected with the HapMap database, we conducted a genetic association analysis of case-control samples (331 patients with MDD and 804 controls) in the Japanese population. Seven population-based association studies, including this study, met our criteria for the meta-analysis of rs6295. We found an association between rs878567 and Japanese MDD patients in the allele-wise analysis, but the significance of this association did not remain after Bonferroni's correction. We also did not detect any association between HTR1A and MDD in the allele/genotype-wise or haplotype-wise analysis. On the other hand, we detected an association between rs6295 and MDD in the meta-analysis (P(Z)=0.0327). In an explorative analysis, rs6295 was associated with Asian MDD patients after correction for multiple testing (P(Z)=0.0176), but not with Caucasian MDD patients (P(Z)=0.138). Our results suggest that HTR1A may not have a role in the pathophysiology of Japanese MDD patients. On the other hand, according to the meta-analysis, HTR1A was associated with MDD patients, especially in the Asian population.

Several investigations have suggested that disruption of circadian rhythms may provide the foundation for the development of mood disorders such as bipolar disorder (BP) and major depressive disorder (MDD). Recent animal studies reported that prokineticin 2 or prokineticin 2 receptor gene deficient mice showed disruptions in circadian and homeostatic regulation of sleep. This evidence indicates that prokineticin 2 gene (PROK2) and prokineticin 2 receptor gene (PROKR2) are good candidate genes for the pathogenesis of mood disorders. To evaluate the association between PROK2, PROKR2, and mood disorders, we conducted a case-control study of Japanese samples (151 bipolar patients, 319 major depressive disorder patients, and 340 controls) with four and five tagging SNPs in PROK2 or PROKR2, respectively, selected by HapMap database. We detected a significant association between PROKR2 and major depressive disorder and bipolar disorder in the Japanese population. In conclusion, our findings suggest that PROKR2 may play a role in the pathophysiology of mood disorders in the Japanese population. However, because our samples were small, it will be important to replicate and confirm these findings in other independent studies using larger samples.

The neuronal nitric oxide synthase gene (NOS1) is located on 12q24, in a susceptibility region for schizophrenia, and produces nitric oxide (NO) in the brain. NO plays a role in neurotransmitter release and is the second messenger of the N-methyl-D-aspartate (NMDA) receptor. Furthermore, it is connected to the dopaminergic and serotonergic neural transmission systems. Therefore, abnormalities in the NO pathway are thought to be involved in the pathophysiology of schizophrenia. Several genetic studies showed an association of NOS1 with schizophrenia. However, results of replication studies have been inconsistent. Therefore, we conducted a replication study of NOS1 with schizophrenia in a Japanese sample. We selected seven SNPs (rs41279104, rs3782221, rs3782219, rs561712, rs3782206, rs2682826, and rs6490121) in NOS1 that were positively associated with schizophrenia in previous studies. Two SNPs showed an association with Japanese schizophrenic patients (542 cases and 519 controls, rs3782219: P allele = 0.0291 and rs3782206: P allele = 0.0124, P genotype = 0.0490), and almost these significances remained with an increased sample size (1154 cases and 1260 controls, rs3782219: P allele = 0.0197 and rs3782206: P allele = 0.0480). However, these associations also might have resulted from type I error on account of multiple testing (rs3782219: P allele = 0.133 and rs3782206: P allele = 0.168). In conclusion, we could not replicate the association between seven SNPs in NOS1 and schizophrenia found in several earlier studies, using larger Japanese schizophrenia and control samples.

G72 is one of the most widely tested genes for association with schizophrenia. As G72 activates the D-amino acid oxidase (DAO), G72 is termed D-amino acid oxidase activator (DAOA). The aim of this study is to investigate the association between G72 and schizophrenia in a Japanese population, using the largest sample size to date (1774 patients with schizophrenia and 2092 healthy controls). We examined eight single nucleotide polymorphisms (SNPs), which had been associated with schizophrenia in previous studies. We found nominal evidence for association of alleles, M22/rs778293, M23/rs3918342 and M24/rs1421292, and the genotype of M22/rs778293 with schizophrenia, although there was no association of allele or genotype in the other five SNPs. We also found nominal haplotypic association, including M15/rs2391191 and M19/rs778294 with schizophrenia. However, these associations were no longer positive after correction for multiple testing. We conclude that G72 might not play a major role in the risk for schizophrenia in the Japanese population.