Published August 8, 2019
| Supplemental Material
Journal Article
Open
Inherited and De Novo Genetic Risk for Autism Impacts Shared Networks
- Creators
- Ruzzo, Elizabeth K.
- Pérez-Cano, Laura
- Jung, Jae-Yoon
- Wang, Lee-kai
- Kashef-Haghighi, Dorna
- Hartl, Chris
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Singh, Chanpreet
- Xu, Jin
- Hoekstra, Jackson N.
- Leventhal, Olivia
- Leppä, Virpi M.
- Gandal, Michael J.
- Paskov, Kelley
- Stockham, Nate
- Polioudakis, Damon
- Lowe, Jennifer K.
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Prober, David A.
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Geschwind, Daniel H.
- Wall, Dennis P.
Abstract
We performed a comprehensive assessment of rare inherited variation in autism spectrum disorder (ASD) by analyzing whole-genome sequences of 2,308 individuals from families with multiple affected children. We implicate 69 genes in ASD risk, including 24 passing genome-wide Bonferroni correction and 16 new ASD risk genes, most supported by rare inherited variants, a substantial extension of previous findings. Biological pathways enriched for genes harboring inherited variants represent cytoskeletal organization and ion transport, which are distinct from pathways implicated in previous studies. Nevertheless, the de novo and inherited genes contribute to a common protein-protein interaction network. We also identified structural variants (SVs) affecting non-coding regions, implicating recurrent deletions in the promoters of DLG2 and NR3C2. Loss of nr3c2 function in zebrafish disrupts sleep and social function, overlapping with human ASD-related phenotypes. These data support the utility of studying multiplex families in ASD and are available through the Hartwell Autism Research and Technology portal.
Additional Information
© 2019 Elsevier. Received 15 November 2018, Revised 8 April 2019, Accepted 11 July 2019, Available online 8 August 2019. We thank Stephanie A. Arteaga, Stephanie N. Kravitz, Cheyenne L. Schloffman, Min Sun, Tor Solli-Nowlan, T. Chang, Hyejung Won, Sasha Sharma, Marlena Duda, Greg Madden McInnes, Ravina Jain, Valentí Moncunill, Josep M. Mercader, Montserrat Puiggròs, Hailey H. Choi, Anika Gupta, and David Torrents for technical support and Hannah Hurley and Amina Kinkhabwala for assistance with zebrafish experiments. We are grateful to The Hartwell Foundation for supporting the creation of the iHART database. We are grateful to the Simons Foundation for additional support for genome sequencing. We are grateful to the PRACE Research Infrastructure resource MareNostrum III based in Spain at the Barcelona Supercomputing Center. We thank the New York Genome Center for conducting sequencing and initial quality control. We thank A. Gordon, J. Huang, J. Sebat, and D. Antaki for help with resolving the DLG2 structural variant. We thank Amazon Web Services for their grant support for the computational infrastructure and storage for the iHART database. We thank J. Sul for helpful discussions and for suggesting a machine learning approach. This work has been supported by grants from The Hartwell Foundation and the NIH (U24MH081810, R01MH064547, NS101158, NS070911, NS101665, NS095824, S10OD011939, P30AG10161, R01AG17917, and U01AG61356) and from the Stanford Precision Health and Integrated Diagnostics Center and from the Stanford Bio-X Center. We are grateful to all of the families at the participating SSC sites as well as the principal investigators (A. Beaudet, R. Bernier, J. Constantino, E. Cook, E. Fombonne, D. Geschwind, R. Goin-Kochel, E. Hanson, D. Grice, A. Klin, D. Ledbetter, C. Lord, C. Martin, D. Martin, R. Maxim, J. Miles, O. Ousley, K. Pelphrey, B. Peterson, J. Piggot, C. Saulnier, M. State, W. Stone, J. Sutcliffe, C. Walsh, Z. Warren, and E. Wijsman). We appreciate obtaining access to genetic data on SFARI Base. Approved researchers can obtain the SSC population dataset described in this study (https://www.sfari.org/2015/12/11/whole-genome-analysis-of-the-simons-simplex-collection-ssc-2/#chapter-wgs-of-500-additional-ssc-families) by applying at https://base.sfari.org. Author Contributions: E.K.R. and L.P.C. contributed to the analytical plans, performed analyses, and interpreted results. J.K.L. selected and submitted samples for sequencing. E.K.R., J.Y.J., L.K.W., and J.K.L. performed quality control checks. L.K.W. wrote scripts for data processing and helped interpret results. L.P.C., D.K.H., J.Y.J., E.K.R., and D.P.W. developed ARC. C.H. interpreted results and ran TADA simulations. E.K.R. and C.H. ran high-risk inherited simulations. J.Y.J. and D.P.W. designed the access systems. J.Y.J. performed joint genotyping, VCF annotation, and data transfers. L.P.C. and D.K.H. processed SVs, and L.P.C. wrote the SV cross-algorithm comparison pipeline. D.P. performed single-cell analyses. M.J.G. analyzed phenotypes. V.M.L. helped with array-based CNV analyses. C.S., J.X., and D.A.P. performed and analyzed zebrafish experiments. D.P.W. identified and supplied funding. E.K.R. and D.H.G. took the lead in writing the manuscript, and all authors reviewed, edited, and approved the manuscript. D.H.G. and D.P.W. supervised the experimental design and analysis and interpreted results. Data and Code Availability: The whole-genome sequencing data generated during this study are available from the Hartwell Foundation's Autism Research and Technology Initiative (iHART) following request and approval of the data use agreement available at http://www.ihart.org. Access to the whole-genome sequencing data generated in this study will be subject to approval by Autism Speaks and AGRE. Details about the format of the data, access options, and access instructions are included at http://www.ihart.org. We also freely provide the code for ARC (Artifact Removal by Classifier), our random forest supervised model developed to distinguish true rare de novo variants from LCL-specific genetic aberrations or other types of artifacts such as sequencing and mapping errors, together with a full tutorial at https://github.com/walllab/iHART-ARC. Interactive genotype/phenotype search engine: To facilitate sharing of iHART data with the broader autism research community and patients, we implemented a set of online data access methods to preview and search genetic variants and phenotypic traits (http://www.ihart.org/home). Zebrafish data: The zebrafish datasets generated and analyzed in this study, and the code used to generate the data, are available upon request. The authors declare no competing interests.Attached Files
Supplemental Material - 1-s2.0-S0092867419307809-mmc1.xlsx
Supplemental Material - 1-s2.0-S0092867419307809-mmc2.xlsx
Supplemental Material - 1-s2.0-S0092867419307809-mmc3.xlsx
Supplemental Material - 1-s2.0-S0092867419307809-mmc4.xlsx
Supplemental Material - 1-s2.0-S0092867419307809-mmc5.xlsx
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Additional details
- PMCID
- PMC7102900
- Eprint ID
- 97709
- DOI
- 10.1016/j.cell.2019.07.015
- Resolver ID
- CaltechAUTHORS:20190808-135241284
- Hartwell Foundation
- U24 MH081810
- NIH
- R01MH064547
- NIH
- NS101158
- NIH
- NS070911
- NIH
- NS101665
- NIH
- NS095824
- NIH
- S10OD011939
- NIH
- P30AG10161
- NIH
- R01AG17917
- NIH
- U01AG61356
- NIH
- Stanford Precision Health and Integrated Diagnostics Center
- Stanford Bio-X Center
- Created
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2019-08-09Created from EPrint's datestamp field
- Updated
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2021-11-16Created from EPrint's last_modified field