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De novo gene mutations highlight patterns of genetic and neural complexity in schizophrenia

Abstract

To evaluate evidence for de novo etiologies in schizophrenia, we sequenced at high coverage the exomes of families recruited from two populations with distinct demographic structures and history. We sequenced a total of 795 exomes from 231 parent-proband trios enriched for sporadic schizophrenia cases, as well as 34 unaffected trios. We observed in cases an excess of de novo nonsynonymous single-nucleotide variants as well as a higher prevalence of gene-disruptive de novo mutations relative to controls. We found four genes (LAMA2, DPYD, TRRAP and VPS39) affected by recurrent de novo events within or across the two populations, which is unlikely to have occurred by chance. We show that de novo mutations affect genes with diverse functions and developmental profiles, but we also find a substantial contribution of mutations in genes with higher expression in early fetal life. Our results help define the genomic and neural architecture of schizophrenia.

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Figure 1: Enrichment of nonsynonymous or functional de novo variants according to temporal expression profiles of genes mutated in schizophrenia.

References

  1. Rodriguez-Murillo, L., Gogos, J.A. & Karayiorgou, M. The genetic architecture of schizophrenia: new mutations and emerging paradigms. Annu. Rev. Med. 63, 63–80 (2012).

    Article  CAS  PubMed  Google Scholar 

  2. Karayiorgou, M. et al. Schizophrenia susceptibility associated with interstitial deletions of chromosome 22q11. Proc. Natl. Acad. Sci. USA 92, 7612–7616 (1995).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Xu, B. et al. Strong association of de novo copy number mutations with sporadic schizophrenia. Nat. Genet. 40, 880–885 (2008).

    Article  CAS  PubMed  Google Scholar 

  4. Malhotra, D. et al. High frequencies of de novo CNVs in bipolar disorder and schizophrenia. Neuron 72, 951–963 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Kirov, G. et al. De novo CNV analysis implicates specific abnormalities of postsynaptic signalling complexes in the pathogenesis of schizophrenia. Mol. Psychiatry 17, 142–153 (2012).

    Article  CAS  PubMed  Google Scholar 

  6. Girard, S.L. et al. Increased exonic de novo mutation rate in individuals with schizophrenia. Nat. Genet. 43, 860–863 (2011).

    Article  CAS  PubMed  Google Scholar 

  7. Xu, B. et al. Exome sequencing supports a de novo mutational paradigm for schizophrenia. Nat. Genet. 43, 864–868 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Xu, B. et al. Elucidating the genetic architecture of familial schizophrenia using rare copy number variant and linkage scans. Proc. Natl. Acad. Sci. USA 106, 16746–16751 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Kryukov, G.V., Pennacchio, L.A. & Sunyaev, S.R. Most rare missense alleles are deleterious in humans: implications for complex disease and association studies. Am. J. Hum. Genet. 80, 727–739 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Neale, B.M. et al. Patterns and rates of exonic de novo mutations in autism spectrum disorders. Nature 485, 242–245 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Sanders, S.J. et al. De novo mutations revealed by whole-exome sequencing are strongly associated with autism. Nature 485, 237–241 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. O'Roak, B.J. et al. Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations. Nature 485, 246–250 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Iossifov, I. et al. De novo gene disruptions in children on the autistic spectrum. Neuron 74, 285–299 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Kang, H.J. et al. Spatio-temporal transcriptome of the human brain. Nature 478, 483–489 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Colantuoni, C. et al. Temporal dynamics and genetic control of transcription in the human prefrontal cortex. Nature 478, 519–523 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Barch, D.M. & Ceaser, A. Cognition in schizophrenia: core psychological and neural mechanisms. Trends Cogn. Sci. 16, 27–34 (2012).

    Article  PubMed  Google Scholar 

  17. Sobin, C., Roos, J.L., Pretorius, H., Lundy, L.S. & Karayiorgou, M. A comparison study of early non-psychotic deviant behavior in Afrikaner and US patients with schizophrenia or schizoaffective disorder. Psychiatry Res. 117, 113–125 (2003).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Christopherson, K.S. et al. Thrombospondins are astrocyte-secreted proteins that promote CNS synaptogenesis. Cell 120, 421–433 (2005).

    Article  CAS  PubMed  Google Scholar 

  19. Georges-Labouesse, E., Mark, M., Messaddeq, N. & Gansmuller, A. Essential role of a6 integrins in cortical and retinal lamination. Curr. Biol. 8, 983–986 (1998).

    Article  CAS  PubMed  Google Scholar 

  20. Jones, K.J. et al. The expanding phenotype of laminin a2 chain (merosin) abnormalities: case series and review. J. Med. Genet. 38, 649–657 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Van Kuilenburg, A.B. et al. Genotype and phenotype in patients with dihydropyrimidine dehydrogenase deficiency. Hum. Genet. 104, 1–9 (1999).

    Article  CAS  PubMed  Google Scholar 

  22. Tiedje, K.E., Stevens, K., Barnes, S. & Weaver, D.F. b-alanine as a small molecule neurotransmitter. Neurochem. Int. 57, 177–188 (2010).

    Article  CAS  PubMed  Google Scholar 

  23. Ben-David, E. et al. Identification of a functional rare variant in autism using genome-wide screen for monoallelic expression. Hum. Mol. Genet. 20, 3632–3641 (2011).

    Article  CAS  PubMed  Google Scholar 

  24. Carter, M.T. et al. Hemizygous deletions on chromosome 1p21.3 involving the DPYD gene in individuals with autism spectrum disorder. Clin. Genet. 80, 435–443 (2011).

    Article  CAS  PubMed  Google Scholar 

  25. Willemsen, M.H. et al. Chromosome 1p21.3 microdeletions comprising DPYD and MIR137 are associated with intellectual disability. J. Med. Genet. 48, 810–818 (2011).

    Article  CAS  PubMed  Google Scholar 

  26. Ripke, S. et al. Genome-wide association study identifies five new schizophrenia loci. Nat. Genet. 43, 969–976 (2011).

    Article  CAS  Google Scholar 

  27. Arguello, P.A. & Gogos, J.A. Genetic and cognitive windows into circuit mechanisms of psychiatric disease. Trends Neurosci. 35, 3–13 (2012).

    Article  CAS  PubMed  Google Scholar 

  28. McGrath, J.J. & Susser, E.S. New directions in the epidemiology of schizophrenia. Med. J. Aust. 190, S7–S9 (2009).

    Article  PubMed  Google Scholar 

  29. Gilman, S.R. et al. Diverse types of genetic variation converge on functional gene networks involved in schizophrenia. Nat. Neurosci. (in the press).

  30. Stark, K.L. et al. Altered brain microRNA biogenesis contributes to phenotypic deficits in a 22q11-deletion mouse model. Nat. Genet. 40, 751–760 (2008).

    Article  CAS  PubMed  Google Scholar 

  31. Karayiorgou, M., Flint, J., Gogos, J.A. & Malenka, R.C. The best of times, the worst of times for psychiatric disease. Nat. Neurosci. 15, 811–812 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Adzhubei, I.A. et al. A method and server for predicting damaging missense mutations. Nat. Methods 7, 248–249 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Grantham, R. Amino acid difference formula to help explain protein evolution. Science 185, 862–864 (1974).

    Article  CAS  PubMed  Google Scholar 

  34. Desmet, F.O. et al. Human Splicing Finder: an online bioinformatics tool to predict splicing signals. Nucleic Acids Res. 37, e67 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Huang, D.W., Sherman, B.T. & Lempicki, R.A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44–57 (2009).

    Article  CAS  Google Scholar 

  36. Rossin, E.J. et al. Proteins encoded in genomic regions associated with immune-mediated disease physically interact and suggest underlying biology. PLoS Genet. 7, e1001273 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We are enormously grateful to all the families who participated in this research. We thank H. Pretorius and nursing sisters R. van Wyk, C. Botha and H. van den Berg for their assistance with subject recruitment, family history assessments and diagnostic evaluations. We thank S.L. Lundy for valuable assistance with clinical database maintenance and L. Rodriguez-Murillo for help with Supplementary Figure 9. We also thank B. Plummer and M. Robinson and the HudsonAlpha Genomics Services Laboratory for experimental support. Finally, we thank L.J. Mienie for the thymine loading test. This work was partially supported by National Institute of Mental Health (NIMH) grants MH061399 (to M.K.) and MH077235 (to J.A.G.) and the Lieber Center for Schizophrenia Research at Columbia University. B.X. was partially supported by a National Alliance for Research in Schizophrenia and Depression (NARSAD) Young Investigator Award.

Author information

Authors and Affiliations

Authors

Contributions

B.X., J.A.G. and M.K. designed the study, interpreted the data and prepared the manuscript. B.X. developed the analysis pipeline and had the primary role in the analysis and validation of sequence data. I.I.-L. performed statistical analysis of the sequence data. J.L.R. contributed to sample collection and clinical characterization. S.W. and Y.S. contributed to sample preparation and de novo mutation validation. B.B. performed exome library construction, capture and sequencing and initial analysis of SNV genotyping and indel variant calls. S.L. supervised the sequencing project at the HudsonAlpha Institute.

Corresponding authors

Correspondence to Joseph A Gogos or Maria Karayiorgou.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Note, Supplementary Figures 1–9 and Supplementary Tables 1, 3–5, 7–9 and 11 (PDF 1422 kb)

Supplementary Table 2

De novo mutations identified in all three cohorts examined (XLS 63 kb)

Supplementary Table 6

List of prenatally-biased genes (XLS 33 kb)

Supplementary Table 10

Functional enrichment analysis of hsa-mir-367 and hsa-mir-1244 targets (XLS 32 kb)

Supplementary Table 12

HSF prediction results for splice site mutations in three genes with recurrent de novo mutations (XLS 25 kb)

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Xu, B., Ionita-Laza, I., Roos, J. et al. De novo gene mutations highlight patterns of genetic and neural complexity in schizophrenia. Nat Genet 44, 1365–1369 (2012). https://doi.org/10.1038/ng.2446

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