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Rare coding variants in ten genes confer substantial risk for schizophrenia

Abstract

Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3–50, P < 2.14 × 10−6) and 32 genes at a false discovery rate of <5%. These genes have the greatest expression in central nervous system neurons and have diverse molecular functions that include the formation, structure and function of the synapse. The associations of the NMDA (N-methyl-d-aspartate) receptor subunit GRIN2A and AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptor subunit GRIA3 provide support for dysfunction of the glutamatergic system as a mechanistic hypothesis in the pathogenesis of schizophrenia. We observe an overlap of rare variant risk among schizophrenia, autism spectrum disorders1, epilepsy and severe neurodevelopmental disorders2, although different mutation types are implicated in some shared genes. Most genes described here, however, are not implicated in neurodevelopment. We demonstrate that genes prioritized from common variant analyses of schizophrenia are enriched in rare variant risk3, suggesting that common and rare genetic risk factors converge at least partially on the same underlying pathogenic biological processes. Even after excluding significantly associated genes, schizophrenia cases still carry a substantial excess of URVs, which indicates that more risk genes await discovery using this approach.

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Fig. 1: Study design and analytic approach.
Fig. 2: Results from meta-analysis of URVs in 3,402 trios, 24,248 cases and 97,322 controls.
Fig. 3: Biological insights from exome sequence data.
Fig. 4: Shared genetic signal with schizophrenia GWAS.
Fig. 5: Shared genetic signal between schizophrenia and other neurodevelopmental disorders.
Fig. 6: Contributions of ultra-rare PTVs to schizophrenia risk.

Data availability

We describe all datasets in the manuscript or its Supplementary Information. We provide summary-level data at the variant and gene level in an online browser for viewing and download (https://schema.broadinstitute.org). There are no restrictions on the aggregated data released on the browser. For contributing datasets that are permitted to be distributed at the individual level, we have deposited or are currently depositing the data in a public repository (the database of Genotypes and Phenotypes (dbGaP) and/or the European Genome–Phenome Archive (EGA)), and we provide the accessions in Supplementary Table 1. Whole-exome sequence data generated under this study are currently hosted on and shared with the collaborating study groupsvia the controlled-access Terra platform (https://app.terra.bio/). The Terra environment, created by the Broad Institute, contains a rich system of workspace functionalities centred on data sharing and analysis. Requests for access to the controlled datasets are managed by data custodians of the SCHEMA consortium and the Broad Institute and are sent to sample contributing investigators for approval.

Code availability

The software and code used are described throughout the Supplementary Methods. In brief, for sequence data generation, we used GATK versions 3.4 and 3.6, Picard version 1.1431 and VerifyBamID version 1.0.0. Sample and variant quality control and analyses were performed using Hail 0.1 and 0.2 (https://hail.is/), with functions and arguments referred to in the Supplementary Methods. Wrappers and methods using Hail code can be found at https://github.com/TarjinderSingh/hailutils. Additional (basic) processing and visualization were performed using base R (version 3.6) with tidyverse libraries (https://www.tidyverse.org/packages/).

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Acknowledgements

We would like to thank the patients and families who participated in our studies during the past two decades, without whom our research and findings would not be possible. The research reported in this publication was supported by the National Institute of Mental Health (NIMH) and the National Human Genome Research Institute of the National Institutes of Health under award numbers U01 MH105641, U01 MH105578, U01 MH105666, U01 MH109539, R01 MH085548, R01 MH085521, R01 MH124851 and U54 HG003067. We would also like to acknowledge support from K. Dauten and E. Dauten, the Stanley Family Foundation and the Dalio Foundation, which has enabled us to rapidly expand our data generation collections with the goal of moving towards better treatments for schizophrenia and other psychiatric disorders. Further, we wish to acknowledge all of the research participants in the BRIDGES cohort, which wassupported by NIMH under award numbers R01 MH094145 (M.B. and R.M.M., PIs) and U01 MH105653 (M.B., PI). The collection and storage of cases and controls from the Centre for Addiction and Mental Health (CAMH) in Toronto and from the Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, in London was supported by funding from GlaxoSmithKline. CAMH was supported by the Canadian Institutes of Health Research (MOP-172013, J. B. Vincent, PI, CAMH). IoPPN was supported by funding from the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and the Maudsley NHS Foundation Trust and by King’s College London. The views expressed are those of the author(s) and not necessarily those of the UK NHS, the NIHR or the UK Department of Health. Case and control collection was supported by the Heinz C. Prechter Bipolar Research Fund at the University of Michigan Depression Center to M.G. McInnis. Data and biomaterials were collected for the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD), a multi-centre, longitudinal project selected from responses to RFP NIMH-98-DS-0001, ‘Treatment for Bipolar Disorder’, which was led by G. Sachs and coordinated by Massachusetts General Hospital in Boston, with support from 2N01 MH080001-001. The Genomic Psychiatric Cohort (GPC) was supported by NIMH (U01 MH105641 (C.N.P., PI), R01 MH085548 (C.N.P. and M.T.P., PIs) and R01 MH104964 (C.N.P. and M.T.P., PIs). The MCTFR study was supported through grants from the National Institutes of Health under numbers DA037904, DA024417, DA036216, DA05147, AA09367, DA024417, HG007022 and HL117626. The work at Cardiff University was supported by Medical Research Council Centre grant no. MR/L010305/1 and programme grant mo. G0800509. We would like to acknowledge the Pritzker Neuropsychiatric Disorders Research Consortium for funding sample collection efforts. The iPSYCH team was supported by grants from the Lundbeck Foundation (R102-A9118, R155-2014-1724, and R248-2017-2003) and the Universities and University Hospitals of Aarhus and Copenhagen. The Danish National Biobank resource was supported by the Novo Nordisk Foundation. A.P. was supported by Academy of Finland Centre of Excellence in Complex Disease Genetics (grant no. 312074, 336824).S.V.F. is supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 667302 and 965381; NIMH grants U01MH109536-01, U01AR076092-01A1, R0MH116037 and 5R01AG06495502; Oregon Health and Science University, Otsuka Pharmaceuticals and Supernus Pharmaceutical Company.  T.S. was supported by a NARSAD Young Investigator Award from the Brain and Behavior Research Foundation.

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Contributions

, .T.S., E.S., L.J.S., P.S., A.P.C., M.B., M.C.O., B.M.N. and M.J.D. conceived and designed the experiments. T.S., T. Poterba, S.A.G.T., A.G., G.G., H.O.H., D.P.H., H.H., H.M.K., B.R., F.K.S., G.T., J.T.W., R.A.O., M.J.O., M.B., M.C.O., B.M.N. and M.J.D. designed and executed the analysis. H.A., J.D.B., W.E.B., S.B.C., C.C., C.M.C., S.D., S.B.G., D.G., F.S.L., P.B.M., R.M.M., A.M.O., A.S., E.A.S., C.R.S., N.A.W., J.T.W., M.J.O., M.C.O. and B.M.N contributed to project management/sequencing. D.C., M. A. Eissa, N.B., G.B., W.F.B., W.J.C., N.C., L.D., M. A. Escamilla, S.E., A.H.F., S.V.F., A.F., D.C.G., M.H., M.H., H.H., R.S.K., G.K., J.A.K., D.S.L., F.L., S.R.M., S.A.M., A.M.M., H.M., C.P.M., P.B.M., M.N., N.L.O., D.O., W.H.O., T. Paunio, D.Q., M.H.R., E.R., S.I.S., J.W.S., J.L.S., J.S., S.J.W., D.H.B., A.D.B., B.M.C., A.P.C., T.E., N.B.F., S.J.G., C.M.H., A.M., A.P., C.N.P., M.T.P., A.E.P., D.S.C., M.T.T., M.P.V., J.T.W., T.M.W., R.A.O., P.F.S., M.J.O. and M.C.O. recruited, assessed and/or contributed patient samples. T.S., T.B.B., E.J.B., P.F.B., J.B., L.F., J.G., E.H., D.M.H., K.J.K., D.M., A.M.M., L.M., C.P.M., D.S.P., J.W.S., M.S., A.P. and T.M.W. contributed reagents/materials/analysis tools. T.S., D.C., A.M.M., L.J.S., M.P.V., J.T.W., M.J.O., M.C.O., B.M.N. and M.J.D. wrote and/or edited the paper. 

Corresponding authors

Correspondence to Tarjinder Singh, Benjamin M. Neale or Mark J. Daly.

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Competing interests

M.J.D. is a founder of Maze Therapeutics and Neumora Therapeutics. B.M.N. is a member of the scientific advisory board at Deep Genomics and Neumora Therapeutics, a member of the scientific advisory committee at Milken and a consultant for Camp4 Therapeutics, Merck and Biogen. A.P. is a member of the genomics advisory board at AstraZeneca. M.C.O., M.J.O. and J.T.W. are supported by a collaborative research grant from Takeda Pharmaceuticals. E.A.S. is currently an employee of the Regeneron Genetics Center. D.S.P. was an employee of Genomics plc; all analyses reported in this paper were performed as part of his employment at Massachusetts General Hospital and the Broad Institute. The remaining authors declare no competing interests. In the past year, S.V.F. received income, potential income, travel expenses continuing education support and/or research support from Aardvark, Akili, Genomind, Ironshore, KemPharm/Corium, Noven, Ondosis, Otsuka, Rhodes, Supernus, Takeda, Tris and Vallon. In previous years, S.V.F. received support from: Alcobra, Arbor, Aveksham, CogCubed, Eli Lilly, Enzymotec, Impact, Janssen, Lundbeck/Takeda, McNeil, NeuroLifeSciences, Neurovance, Novartis, Pfizer, Shire, and Sunovion. With his institution, S.V.F. has US patent US20130217707 A1 for the use of sodium-hydrogen exchange inhibitors in the treatment of ADHD. S.V.F. receives royalties from books published by Guilford Press: Straight Talk about Your Child’s Mental Health; Oxford University Press: Schizophrenia: The Facts; and Elsevier: ADHD: Non-Pharmacologic Interventions, and is Program Director of www.adhdinadults.com.

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Extended data figures and tables

Extended Data Fig. 1 Schizophrenia case-control enrichment in constrained genes (pLI > 0.9) in different SCHEMA cohorts (n = 22,444 cases and n = 39,837 controls).

The odds ratio and standard error of PTVs and synonymous variants are provided for each cohort. The meta-analyzed odds ratio and standard error is calculated using inverse-variance. PTVs show consistent signals across the different cohorts, and synonymous variants do not deviate from expectation. Bars represent the 95% CIs of the point estimates.

Extended Data Fig. 2 Schizophrenia case-control enrichment in constrained genes (pLI > 0.9) stratified by different variant annotations and inferred consequences (n = 22,444 cases and n = 39,837 controls).

LoF: all loss-of-function or PTVs; LoFHC: high-confidence LOFTEE PTVs; LoFLC: low-confidence based on LOFTEE; MPC > 3: missense variants with MPC > 3; MPC 2 - 3: missense variants with MPC 2 - 3; Other missense: missense variants with MPC < 2; Syn: synonymous variants. The dot represents the odds ratio, and the bars represent the 95% CIs of the point estimates.

Extended Data Fig. 3 Enrichment of URVs in n = 4,403 ASD and n = 3,292 ADHD cases compared to n = 5,220 controls stratified by variant annotation and consequences in constrained genes (pLI > 0.9).

Two-sided P values from logistic regression displayed are from comparing the burden of variants of the labeled consequence in cases compared to controls. The dot represents the odds ratio, and the bars represent the 95% CIs of the point estimates.

Extended Data Fig. 4 Schizophrenia case-control gene set enrichment in brain and non-brain GTEx tissues.

We test for the burden of rare PTVs in genes with the strongest specific expression in that tissue type relative to other tissues as defined in30. Gene set burden statistics are calculated using a logistic regression model of rare variants from n = 22,444 cases and n = 39,837 controls. We report two-sided P values. Each bar is a different tissue in GTEx, grouped by whether it is part of the central nervous system and sorted by P value (Supplementary Table 8).

Extended Data Table 1 Case-control and de novo counts of the ten Bonferroni significant genes in the main analysis

Supplementary information

Supplementary Information

This file contains Supplementary Methods, Supplementary Figs. 1–23, Supplementary Tables 2 and 3, full descriptions for Supplementary Tables 1–13, Supplementary Note and Supplementary References. See contents page for details.

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Supplementary Tables 1 and 4–13; see Supplementary Information document for full descriptions.

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Singh, T., Poterba, T., Curtis, D. et al. Rare coding variants in ten genes confer substantial risk for schizophrenia. Nature 604, 509–516 (2022). https://doi.org/10.1038/s41586-022-04556-w

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