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Genotype to phenotype relationships in autism spectrum disorders

Nature Neuroscience volume 18, pages 191198 (2015) | Download Citation

Abstract

Autism spectrum disorders (ASDs) are characterized by phenotypic and genetic heterogeneity. Our analysis of functional networks perturbed in ASD suggests that both truncating and nontruncating de novo mutations contribute to autism, with a bias against truncating mutations in early embryonic development. We find that functional mutations are preferentially observed in genes likely to be haploinsufficient. Multiple cell types and brain areas are affected, but the impact of ASD mutations appears to be strongest in cortical interneurons, pyramidal neurons and the medium spiny neurons of the striatum, implicating cortical and corticostriatal brain circuits. In females, truncating ASD mutations on average affect genes with 50–100% higher brain expression than in males. Our results also suggest that truncating de novo mutations play a smaller role in the etiology of high-functioning ASD cases. Overall, we find that stronger functional insults usually lead to more severe intellectual, social and behavioral ASD phenotypes.

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Acknowledgements

We would like to sincerely thank M. Wigler, M. State, D. Geschwind, A. Packer, G. Fischbach and all of the members of the Vitkup laboratory for helpful discussions. This work was supported by a grant from the Simons Foundation SFARI# 308962 to D.V. and US National Centers for Biomedical Computing (MAGNet) grant U54CA121852 to Columbia University. S.R.G. was supported in part by US NIGMS training grant T32 GM082797. S.J.S. was supported by a Howard Hughes Medical Institute International Student Research Fellowship.

Author information

Author notes

    • Jonathan Chang
    •  & Sarah R Gilman

    These authors contributed equally to this work.

Affiliations

  1. Department of Biomedical Informatics, Columbia University, New York, New York, USA.

    • Jonathan Chang
    • , Sarah R Gilman
    • , Andrew H Chiang
    •  & Dennis Vitkup
  2. Department of Systems Biology, Center for Computational Biology and Bioinformatics, Columbia University, New York, New York, USA.

    • Jonathan Chang
    • , Sarah R Gilman
    • , Andrew H Chiang
    •  & Dennis Vitkup
  3. Department of Psychiatry, University of California, San Francisco, California, USA.

    • Stephan J Sanders
  4. Department of Psychiatry, Department of Genetics, Yale University, New Haven, Connecticut, USA.

    • Stephan J Sanders

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Contributions

J.C., S.R.G. and A.H.C. performed computational analysis and interpreted the results. S.J.S. contributed data, interpreted the results and contributed to the functional analysis. D.V. designed the study, supervised the project and interpreted the results. J.C., S.R.G., A.H.C. and D.V. wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Dennis Vitkup.

Integrated supplementary information

Supplementary information

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    Supplementary Text and Figures

    Supplementary Figures 1–3 and Supplementary Tables 3–9

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    Supplementary Methods Checklist

Excel files

  1. 1.

    Supplementary Table 1

    Genetic SNV and CNV events from the Simons Simplex Collection used as input for NETBAG.

  2. 2.

    Supplementary Table 2

    Implicated ASD network genes and associated prioritization annotations (average log2 brain expression and truncating SNV status).

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DOI

https://doi.org/10.1038/nn.3907