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Mapping genomic loci implicates genes and synaptic biology in schizophrenia

Abstract

Schizophrenia has a heritability of 60–80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies.

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Fig. 1: Overview of GWAS and gene prioritization.
Fig. 2: Gene set enrichment tests at the genome-wide level and for protein-coding genes that contain FINEMAP credible SNPs.
Fig. 3: Mapping of all fine-mapped and SMR-associated genes, and prioritized genes, to synaptic locations using SynGO.
Fig. 4: Associations between schizophrenia and cell types from multiple brain regions in human and mouse.

Data availability

Summary statistics for the ‘extended’, ‘core’, ancestry-specific and sex-stratified analyses are available at https://www.med.unc.edu/pgc/download-results/scz/. Genotype data are available for a subset of cohorts, including dbGAP accession numbers and/or restrictions, as described in the ‘Case–control sample descriptions’ section of the Supplementary Information.

Code availability

Core analysis code for RICOPILI can be found at https://sites.google.com/a/broadinstitute.org/ricopili/. This wraps PLINK (https://www.cog-genomics.org/plink2/), EIGENSOFT (https://www.hsph.harvard.edu/alkes-price/software/), Eagle2 (https://alkesgroup.broadinstitute.org/Eagle/), Minimac3 (https://genome.sph.umich.edu/wiki/Minimac3), SHAPEIT3 (https://mathgen.stats.ox.ac.uk/genetics_software/shapeit/shapeit.html), METAL (https://genome.sph.umich.edu/wiki/METAL_Documentation) and LDSR (https://github.com/bulik/ldsc). For downstream analyses, FINEMAP can be found at http://christianbenner.com/, and our utility for meta-analysing cohort-specific LD matrices can be found at https://github.com/Pintaius/LDmergeFM. MAGMA can be found at https://ctg.cncr.nl/software/magma and the GO gene sets and automated curation pipeline are provided in https://github.com/janetcharwood/pgc3-scz_wg-genesets. SMR is available at https://cnsgenomics.com/software/smr/ and SbayesS at https://cnsgenomics.com/software/gctb/.

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Acknowledgements

The National Institute of Mental Health (USA) provides core funding for the PGC under award no. U01MH109514. The content is the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The work of the contributing groups was supported by numerous grants from governmental and charitable bodies as well as philanthropic donation (details in Supplementary Note). We acknowledge a substantial contribution from P. Sklar (deceased) as one of the PGC principal investigators, and E. Scolnick, whose support for this study was vital. We acknowledge the Wellcome Trust Case Control Consortium for the provision of control genotype information. Membership of the Psychosis Endophenotypes International Consortium, the SynGO consortium, the PsychENCODE Consortium, the eQTLGen consortium, the BIOS Consortium and the Indonesia Consortium are provided in the author list. We are grateful to C. Hopkins for illustrations. The work at Cardiff University was additionally supported by Medical Research Council Centre grant no. MR/L010305/1 and program grant no. G0800509. S. Xu also gratefully acknowledges the support of the National Natural Science Foundation of China (NSFC) grants (31525014, 91731303, 31771388, 31961130380 and 32041008), the UK Royal Society-Newton Advanced Fellowship (NAF\R1\191094), the Key Research Program of Frontier Sciences (QYZDJ-SSW-SYS009) and the Strategic Priority Research Program (XDB38000000) of the Chinese Academy of Sciences, and the Shanghai Municipal Science and Technology Major Project (2017SHZDZX01). O. A. Andreassen was supported by the Research Council of Norway (283798, 262656, 248980, 273291, 248828, 248778, 223273); KG Jebsen Stiftelsen, South-East Norway Health Authority, EU H2020 no. 847776. B. Melegh was supported in part by the National Scientific Research Program (NKFIH) K 138669. S. V. Faraone is supported by the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 602805, the European Union’s Horizon 2020 research and innovation programme under grant agreements 667302 and 728018 and NIMH grants 5R01MH101519 and U01 MH109536-01. S. I. Belangero was supported by FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo), grant numbers: 2010/08968-6; 2014/07280-1 2011/50740-5 (including R. A. Bressan). The Singapore team (J. Lee, J. Liu, K. Sim, S. A. Chong and M. Subramanian) acknowledges the National Medical Research Council Translational and Clinical Research Flagship Programme (grant no.: NMRC/TCR/003/2008). M. Macek was supported by LM2018132, CZ.02.1.01/0.0/0.0/18_046/0015515 and IP6003 –VZFNM00064203. C. Arango has been funded by the Spanish Ministry of Science and Innovation, Instituto de Salud Carlos III (SAM16PE07CP1, PI16/02012, PI19/024), co-financed by ERDF Funds from the European Commission, ‘A way of making Europe’, CIBERSAM, Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), European Union Structural Funds, European Union Seventh Framework Program and European Union H2020 Program under the Innovative Medicines Initiative 2 Joint Undertaking (grant agreement no 115916, project PRISM; and grant agreement no. 777394, project AIMS-2-TRIALS), Fundación Familia Alonso and Fundación Alicia Koplowitz. E. Bramon acknowledges support from the National Institute of Health Research UK (grant NIHR200756); Mental Health Research UK John Grace QC Scholarship 2018; an ESRC collaborative award 2020; BMA Margaret Temple Fellowship 2016; Medical Research Council New Investigator Award (G0901310); MRC Centenary Award (G1100583); MRC project grant G1100583; National Institute of Health Research UK post-doctoral fellowship (PDA/02/06/016); NARSAD Young Investigator awards 2005 and 2008; Wellcome Trust Research Training Fellowship; Wellcome Trust Case Control Consortium awards (085475/B/08/Z, 085475/Z/08/Z); European Commission Horizon 2020 (747429); NIHR Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust and King’s College London; and NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust and University College London (UCLH BRC - Mental Health Theme). D. Molto is funded by the European Regional Development Fund (ERDF)–Valencian Community 2014–2020, Spain. E. G. Atkinson was supported by the NIMH K01MH121659.

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