De novo mutations in schizophrenia implicate synaptic networks (original) (raw)

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Data included in this manuscript have been deposited at dbGaP under accession number phs000687.v1.p1 and is available for download at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000687.v1.p1.

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Acknowledgements

Work in Cardiff was supported by Medical Research Council (MRC) Centre (G0800509) and Program Grants (G0801418), the European Community’s Seventh Framework Programme (HEALTH-F2-2010-241909 (Project EU-GEI)), and NIMH (2 P50 MH066392-05A1). Work at the Icahn School of Medicine at Mount Sinai was supported by the Friedman Brain Institute, the Institute for Genomics and Multiscale Biology (including computational resources and staff expertise provided by the Department of Scientific Computing), and National Institutes of Health grants R01HG005827 (S.M.P.), R01MH099126 (S.M.P.), and R01MH071681 (P.S.). Work at the Broad Institute was funded by Fidelity Foundations, the Sylvan Herman Foundation, philanthropic gifts from K. and E. Dauten, and the Stanley Medical Research Institute. Work at the Wellcome Trust Sanger Institute was supported by The Wellcome Trust (grant numbers WT089062 and WT098051) and also by the European Commission FP7 project gEUVADIS no. 261123 (P.P.). We would like to thank M. Daly, B. Neale and K. Samocha for discussions and providing unpublished autism data. We would also like to acknowledge M. DePristo, S. Gabriel, T. J. Fennel, K. Shakir, C. Tolonen and H. Shah for their help in generating and processing the various data sets.

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Authors and Affiliations

  1. Division of Psychiatric Genomics in the Department of Psychiatry, and Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, 10029, New York, USA
    Menachem Fromer, Douglas M. Ruderfer, Jessica S. Johnson, Panos Roussos, Milind Mahajan, Pamela Sklar & Shaun M. Purcell
  2. Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, 02142, Massachusetts, USA
    Menachem Fromer, Douglas D. Barker, Samuel A. Rose, Kimberly Chambert, Edward M. Scolnick, Jennifer L. Moran, Steven A. McCarroll & Shaun M. Purcell
  3. Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff CF24 4HQ, UK ,
    Andrew J. Pocklington, David H. Kavanagh, Hywel J. Williams, Sarah Dwyer, Lyudmila Georgieva, Elliott Rees, Douglas M. Ruderfer, Noa Carrera, Isla Humphreys, Eilis Hannon, George Kirov, Peter Holmans, Michael J. Owen & Michael C. O’Donovan
  4. Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK ,
    Padhraig Gormley, Priit Palta & Aarno Palotie
  5. Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, 02142, Massachusetts, USA
    Padhraig Gormley, Eric Banks, Aarno Palotie & Steven A. McCarroll
  6. Department of Bioinformatics, Institute of Molecular and Cell Biology, University of Tartu, 51010 Tartu, Estonia,
    Priit Palta
  7. Institute for Molecular Medicine Finland (FIMM), University of Helsinki, 00290 Helsinki, Finland ,
    Priit Palta & Aarno Palotie
  8. Department of Psychiatry, Medical University, Sofia 1431, Bulgaria,
    Vihra Milanova
  9. Centre for Neuroregeneration, University of Edinburgh, Edinburgh EH16 4SB, UK ,
    Seth G. Grant
  10. Department of Genetics, Harvard Medical School, Boston, 02115, Massachusetts, USA
    Steven A. McCarroll
  11. Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, 10029, New York, USA
    Pamela Sklar
  12. Analytic and Translational Genetics Unit, Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, 02114, Massachusetts, USA
    Shaun M. Purcell

Authors

  1. Menachem Fromer
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  2. Andrew J. Pocklington
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  3. David H. Kavanagh
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  4. Hywel J. Williams
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  5. Sarah Dwyer
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  6. Padhraig Gormley
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  7. Lyudmila Georgieva
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  8. Elliott Rees
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  9. Priit Palta
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  10. Douglas M. Ruderfer
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  11. Noa Carrera
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  12. Isla Humphreys
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  13. Jessica S. Johnson
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  14. Panos Roussos
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  15. Douglas D. Barker
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  16. Eric Banks
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  17. Vihra Milanova
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  18. Seth G. Grant
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  19. Eilis Hannon
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  20. Samuel A. Rose
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  21. Kimberly Chambert
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  22. Milind Mahajan
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  23. Edward M. Scolnick
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  24. Jennifer L. Moran
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  25. George Kirov
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  26. Aarno Palotie
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  27. Steven A. McCarroll
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  28. Peter Holmans
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  29. Pamela Sklar
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  30. Michael J. Owen
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  31. Shaun M. Purcell
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  32. Michael C. O’Donovan
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Contributions

The project was led in Cardiff by M.C.O.D. and M.J.O., in Mount Sinai by S.M.P. and P.S., at the Broad by S.A.M. and J.L.M., and at the Sanger by A.P.; H.J.W., J.L.M., K.C., J.S.J., D.D.B., M.M. and S.A.R. were responsible for sample processing and data management. M.F., H.J.W., P.G., D.M.R., D.H.K., G.K., E.R. and S.D. processed NGS data, annotated and validated mutations. L.G., N.C., I.H., S.D., H.J.W. and S.A.R. undertook validation of mutations and additional lab work. A.J.P., M.F., D.H.K., S.M.P. and P.H. co-ordinated/undertook the main bioinformatics/statistical analyses. E.R., D.M.R., E.B., P.P., E.H. and P.R. performed additional analyses. S.G.G. contributed additional insights into synaptic biology. Sample recruitment was led by G.K. and V.M.; The main findings were interpreted by M.C.O.D., M.F., M.J.O., P.H., G.K., E.M.S., S.A.M., D.H.K., A.J.P., A.P., S.M.P. and P.S. who drafted the manuscript.

Corresponding author

Correspondence toMichael J. Owen.

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Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Comparison of sequencing metrics for putative de novo calls and parental singletons.

a–e, Putative de novo calls (child heterozygous, both parents homozygous reference; N parent-proband trios = 623) were compared with variants observed in only a single parent (“singletons”), in terms of depth of all reads at the variant site (a), fraction of reads with the alternate allele (AB = allele balance) (b), mapping quality of the reads at the site (MQ) (c), the likelihood of the heterozygous genotype (PL = Phred-scaled likelihood) (d), and the number of other samples in the present study with a non-reference allele at that site (AAC = alternate allele count) (e). Distributions were calculated for putative de novo variants (red), or grouped by sites of putatively recurrent de novo mutations (orange) when relevant, transmitted singletons (green), and non-transmitted singletons (blue).

Extended Data Figure 2 Metrics for de novo variants across cohorts and trios.

a, Rates of recurrence of validated de novo mutations for tri-nucleotide sequences. For each of 96 possible tri-nucleotide base contexts of single-base mutations (accounting for strand symmetry by reverse complementarity), the number of observed de novo SNV is plotted (sorted by this count). Mutation counts are sub-divided into those not found in external data (red), those found in dbSNP (build 137, green), those found in controls (N = 2543) in the parallel exome sequencing study[15](/articles/nature12929#ref-CR15 "Purcell, S. M. et al. A polygenic burden of rare disruptive mutations in schizophrenia. Nature http://dx.doi.org/10.1038/nature12975

             (22 January 2014)") (cyan), and those found both in dbSNP and that study (purple). **b**, Comparison of on-target heterozygous SNV and indel call rate with putative _de novo_ mutation calls. For each proband (_N_ \= 623), the number of heterozygous SNV and indel calls is compared with the number of putative _de novo_ mutations (child heterozygous, both parents homozygous reference). Probands are coloured by sequencing centre (see [Supplementary Information](/articles/nature12929#MOESM38) for differences in exome capture), and six trios are noticeable outliers from all others (marked by ‘×’) in terms of number of putative _de novo_ mutations. **c**, Variation in sequencing coverage between and across trios and sequencing centres. For each trio (_N_ \= 623), the number of bases covered by 10 reads or more for each member (marked by ‘×’) and the joint coverage[9](/articles/nature12929#ref-CR9 "Iossifov, I. et al. De novo gene disruptions in children on the autistic spectrum. Neuron 74, 285–299 (2012)") in all three members (marked by points) are plotted at corresponding horizontal points; trios are sorted in increasing order of joint coverage and coloured by sequencing centre (see [Supplementary Information](/articles/nature12929#MOESM38)). The intersection of each exome capture with the RefSeq coding sequence is marked by respective dotted lines.

Extended Data Figure 3 De novo mutation counts and rates.

a, The observed distribution of number of validated RefSeq-coding (see Supplementary Information) de novo mutations found for each trio (N = 617) is compared with that expected from a Poisson distribution with a rate equal to the observed mean number of de novo mutations (λ = 1.032). b, Deleterious mutation rate inversely correlates with academic performance. Individuals were grouped according to their final school grade (3–6, corresponding to D, C, B, A in the US system, http://www.fulbright.bg/en/p-Educational-System-of-Bulgaria-18/), and the proportion of individuals with one or more de novo loss-of-function mutations is plotted. N, number of individuals in each group. See Supplementary Information for details on linear regression performed to evaluate association; note that 19 samples were removed from this analysis for missing parental age or school grade information, leaving a total of 598 trios.

Extended Data Figure 4 Enrichment of de novo SNVs, indels and CNVs in genes encoding postsynaptic complexes at glutamatergic synapses.

a, Number of de novo mutations (N cases = 617) in postsynaptic complexes in current study (and genes affected) are shown alongside the most conservative estimate of de novo CNV enrichment from ref. 20 (N cases studied = 662). NS, nonsynonymous, LoF, loss-of-function, PSD, postsynaptic density. The NMDAR complex gene set was derived a priori from a published proteomics data set42. To avoid investigator bias, we did not add additional members post hoc, thus omitting genes with de novo mutations and important NMDAR functions; these include GRIN2A, which encodes a subunit of the NMDA receptor itself, and AKAP9, which directly anchors protein complexes involved in signalling at NMDA receptors43. P < 0.05 are marked in bold as are genes hit by mutations in the current study and by de novo CNVs in ref. 20. b–g, 95% credible intervals (CI) for fold-enrichment statistics of de novo mutations in postsynaptic gene sets (corresponding to enrichments in a, above, and as marked) were calculated from the posterior distributions of fold-enrichment (O/E, observed to expected) statistic values for individuals in this study. Point estimates of O/E are given in Table 3, and correspond to the distribution modes here. The 95% CI is marked by red vertical lines, and a null effect size (value of 1) is marked by a grey line. Note that loss-of-function mutations in the large postsynaptic density set are not significantly enriched, and thus the corresponding CI includes an effect size of 1. All posterior distributions were calculated using dnenrich, as described in the Supplementary Information.

Extended Data Table 1 Stratification of de novo mutations based on polygenic burden, presence of a ‘pathogenic’ CNV, or poor scholastic achievement

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Extended Data Table 2 Genes overlapped by two nonsynonymous de novo mutations in schizophrenia probands

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Extended Data Table 3 Enrichment of de novo mutations in genes targeted by FMRP and conditional analysis of enrichment in postsynaptic density complexes

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Extended Data Table 4 Brain expression biases of genes affected by de novo mutations

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Extended Data Table 5 Comparison of genes hit by de novo mutations between this study and other disease studies and control individuals

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Extended Data Table 6 Mammalian conservation at de novo mutation sites and of genes hit by de novo mutations

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Supplementary information

Supplementary Information

This file contains Supplementary Text and additional references. (PDF 761 kb)

Supplementary Table 1

This file contains a list of validated coding de novo mutations discovered in subjects with schizophrenia. For each de novo mutation (single-nucleotide or insertion/deletion variant) discovered in a proband with schizophrenia in this study, listed are basic details, including genomic coordinates (hg19), reference and de novo alleles, functional impact in genes overlapped (see Supplementary Text), number of total alternate alleles called at that locus in this sample (N=623 trios, including parental genotypes), sequencing metrics for the genotypes (in the proband, father, and mother), the phased parent-of-origin when known, and family history (first-degree relatives). (XLSX 170 kb)

Supplementary Table 2

The file contains a compiled list of published de novo mutations in unaffected controls and individuals with neuropsychiatric illness. Sheet 1 shows de novo mutations analyzed alongside the schizophrenia mutations in this study, counts of individuals and RefSeq-coding mutations from published study sources, neuropsychiatric phenotype, and first author of study source are given. ASD = autism spectrum disorders, CONTROL = individual from unaffected family, ID = intellectual disability, SZ = schizophrenia, SIB = unaffected sibling of proband (from families with sequenced “quads” = father, mother, child with ASD or SZ, unaffected sibling). Sheet 2 shows that for the studies and sample sizes listed in the sheet 1, all published de novo mutations were collated and uniformly annotated. Note that only those annotated as RefSeq-coding by Plink/Seq (see Supplementary Text) are listed here. Columns are as described in Table S1. (XLSX 259 kb)

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Fromer, M., Pocklington, A., Kavanagh, D. et al. De novo mutations in schizophrenia implicate synaptic networks.Nature 506, 179–184 (2014). https://doi.org/10.1038/nature12929

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