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An interactome perturbation framework prioritizes damaging missense mutations for developmental disorders

Nature Genetics (2018) | Download Citation


Identifying disease-associated missense mutations remains a challenge, especially in large-scale sequencing studies. Here we establish an experimentally and computationally integrated approach to investigate the functional impact of missense mutations in the context of the human interactome network and test our approach by analyzing ~2,000 de novo missense mutations found in autism subjects and their unaffected siblings. Interaction-disrupting de novo missense mutations are more common in autism probands, principally affect hub proteins, and disrupt a significantly higher fraction of hub interactions than in unaffected siblings. Moreover, they tend to disrupt interactions involving genes previously implicated in autism, providing complementary evidence that strengthens previously identified associations and enhances the discovery of new ones. Importantly, by analyzing de novo missense mutation data from six disorders, we demonstrate that our interactome perturbation approach offers a generalizable framework for identifying and prioritizing missense mutations that contribute to the risk of human disease.

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We would like to thank J. F. Beltrán, J. Liang, S. D. Wierbowski and other Yu laboratory members for constructive discussions. This work was supported by National Institute of General Medical Sciences grants (R01 GM104424, R01 GM124559, R01 GM125639); a National Cancer Institute grant (R01 CA167824); a Eunice Kennedy Shriver National Institute of Child Health and Human Development grant (R01 HD082568); a National Human Genome Research Institute grant (UM1 HG009393); a National Science Foundation grant (DBI-1661380) to H.Y.; a National Institute of Mental Health grant (R37MH057881) to B.D. and K.R.; and Simons Foundation Autism Research Initiative grants (SF367561 to H.Y., B.D. and K.R. and SF402281 to B.D. and K.R.). We would like to thank the SSC principal investigators (A. L. Beaudet, R. Bernier, J. Constantino, E. H. Cook, Jr, E. Fombonne, D. Geschwind, D. E. Grice, A. Klin, D. H. Ledbetter, C. Lord, C. L. Martin, D. M. Martin, R. Maxim, J. Miles, O. Ousley, B. Peterson, J. Piggot, C. Saulnier, M. W. State, W. Stone, J. S. Sutcliffe, C. A. Walsh and E. Wijsman) and the coordinators and staff at the SSC clinical sites; the SFARI staff, in particular N. Volfovsky; D. B. Goldstein for contributing to the experimental design; and the Rutgers University Cell and DNA repository for accessing biomaterials.

Author information

Author notes

  1. These authors contributed equally: Siwei Chen, Robert Fragoza.


  1. Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY, USA

    • Siwei Chen
    • , Robert Fragoza
    • , Yuan Liu
    •  & Haiyuan Yu
  2. Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY, USA

    • Siwei Chen
    • , Robert Fragoza
    • , Yuan Liu
    •  & Haiyuan Yu
  3. Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA

    • Siwei Chen
    •  & Robert Fragoza
  4. Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA

    • Lambertus Klei
    •  & Bernie Devlin
  5. Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, PA, USA

    • Jiebiao Wang
    •  & Kathryn Roeder
  6. Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA

    • Kathryn Roeder


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S.C., R.F., K.R., B.D. and H.Y. conceived the study. H.Y. oversaw all aspects of the study. S.C. and L.K. performed computational analyses with extensive input from K.R., B.D., and H.Y. R.F. and Y.L. performed laboratory experiments. S.C. and R.F. wrote the manuscript with input from J.W., K.R., B.D. and H.Y. All authors edited and approved of the final manuscript.

Competing interests

The authors declare no competing interests.

Corresponding authors

Correspondence to Kathryn Roeder or Bernie Devlin or Haiyuan Yu.

Supplementary information

  1. Supplementary Text and Figures

    Supplementary Figures 1–10 and Supplementary Note

  2. Reporting Summary

  3. Supplementary Table 1

    All dnMis mutations in the SSC database

  4. Supplementary Table 2

    Interaction disruption results tested in Y2H experiments

  5. Supplementary Table 3

    Genes with interaction-disrupting (Dis) or non-disrupting (NonDis) dnMis mutations

  6. Supplementary Table 4

    Lists of genes in seven ASD-associated functional classes

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