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Rates, distribution and implications of postzygotic mosaic mutations in autism spectrum disorder

A Publisher Correction to this article was published on 14 July 2020

This article has been updated

Abstract

We systematically analyzed postzygotic mutations (PZMs) in whole-exome sequences from the largest collection of trios (5,947) with autism spectrum disorder (ASD) available, including 282 unpublished trios, and performed resequencing using multiple independent technologies. We identified 7.5% of de novo mutations as PZMs, 83.3% of which were not described in previous studies. Damaging, nonsynonymous PZMs within critical exons of prenatally expressed genes were more common in ASD probands than controls (P < 1 × 10−6), and genes carrying these PZMs were enriched for expression in the amygdala (P = 5.4 × 10−3). Two genes (KLF16 and MSANTD2) were significantly enriched for PZMs genome-wide, and other PZMs involved genes (SCN2A, HNRNPU and SMARCA4) whose mutation is known to cause ASD or other neurodevelopmental disorders. PZMs constitute a significant proportion of de novo mutations and contribute importantly to ASD risk.

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Figure 1: De novo mutations in ASD show an excess of low AAFs, consistent with postzygotic mosaicism.
Figure 2: Postzygotic mutations in ASD show excess deleterious mutations in critical exons of genes expressed during early brain development.
Figure 3: Postzygotic mutations implicate the prenatal amygdala in ASD.
Figure 4: Recurrent nonsynonymous postzygotic mosaic mutations implicate previously uncharacterized genes with more mutations than expected false calls.

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Acknowledgements

We are grateful to all the families who participated in the research, including the Simons Foundation Autism Research Initiative (SFARI) Simplex Collection (SSC), the Autism Sequencing Consortium (ASC) and Autism Speaks. We acknowledge the clinicians and organizations that contributed to samples used in this study, including the ASC and SSC principal investigators; the coordinators and staff at the ASC and SSC sites for the recruitment and comprehensive assessment of simplex families; and the ASC, SFARI and NDAR staff for facilitating access to the data sets. This work was supported by a grant from the Simons Foundation (178093, C.A.W.); the National Institutes of Health (NIH) grants R01MH083565, RC2MH089952 and U01MH106883 to C.A.W.; grants R01MH097849, U01MH100233, U01MH100209, U01MH100229, U01MH100239, U01MH111661, U01MH111660, U01MH111658, U01MH111662 and R01MH097849 to the Autism Sequencing Consortium; grants from the Centre for Applied Genomics, the University of Toronto McLaughlin Centre, Genome Canada and Autism Speaks (S.W.S.); Simons Foundation grant (368485, G.M.C.); SRPBS and Brain/MINDS grants from AMED (I.K., B.A., N.O.); grants from the Spanish Ministry of Economy and Competitiveness (M.P.), Instituto de Salud Carlos III (M.P.), PI10/02989 (M.P.), CIBERSAM (M.P.) and ERA-NET NEURON (M.P., C.M.F.), Network of European Funding for Neuroscience Research (M.P.), and Fundación María José Jove and The Institute of Health Carlos III-Fondo de Investigaciones Sanitarias grant project PI13/01136 (A.C.) and the Seaver Foundation. We thank A. Hossain and N. Hatem for their help with sample preparation; F. Zhao and C. Stevens for their help with reprocessing the BAM files; and M. Daly, S. McCarroll, G. Genovese and J. Hirschhorn for comments and suggestions. Research reported in this paper was supported by the Office of Research Infrastructure of the National Institutes of Health under award number S10OD018522. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This work was supported in part through the computational resources and staff expertise provided by the Department of Scientific Computing at the Icahn School of Medicine at Mount Sinai. Additional computing support was provided by the Harvard Medical School's Orchestra High-Performance Computing Group, which is partially supported by NIH grant NCRR 1S10RR028832-01. The NHLBI GO Exome Sequencing Project and its ongoing studies produced and provided exome variant calls for comparison: the Lung GO Sequencing Project (HL-102923), the WHI Sequencing Project (HL-102924), the Broad GO Sequencing Project (HL-102925), the Seattle GO Sequencing Project (HL-102926) and the Heart GO Sequencing Project (HL-103010). C.A.W. is an Investigator of the Howard Hughes Medical Institute; S.W.S. is funded by the GlaxoSmithKline-Canadian Institutes of Heath Research Chair in Genome Sciences at the Hospital for Sick Children and University of Toronto; A.M.D. is supported by the NIGMS (T32GM007753) and NRSA (5T32 GM007226-39); S.D.R. is supported by the Seaver Foundation.

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Contributions

E.T.L. and C.A.W. conceived the project and wrote the manuscript. E.T.L. and M.U. performed the spatiotemporal analyses. E.T.L., S.D.R., Y.C., A.S.K., A.M.D. and S.N.K. performed the resequencing and Sanger sequencing experiments. E.T.L., S.D.R. and X.Z. performed the mutagenesis, overexpression and qPCR experiments. E.T.L. and Y.C. performed the permutations and modeling of background rates. R.S.H., A.P.G. and C.P. performed the data processing and annotation of the variant call files. N.J.M., I.K., B.A., N.O., M.P., C.A., M.J.P., A.C., A.K., C.M.H., L.A.W., A.G.C. and C.M.F. provided additional trio exome sequence data and blood samples for resequencing experiments. E.T.L. and M.F. performed the phasing of mutations. G.M.C., S.W.S., J.D.B. and C.A.W. supervised the project, provided critical comments and edited the manuscript. All authors critically reviewed the manuscript for content.

Corresponding authors

Correspondence to Elaine T Lim or Christopher A Walsh.

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Competing interests

S.W.S., M.U. and the Hospital for Sick Children hold intellectual property used in this analysis, which is also licensed by Lineagen, Inc. M.P. has received educational honoraria from Otsuka, research grants from Fundación Alicia Koplowitz and Mutua Madrileña and travel grants from Otsuka and Janssen. C.A. has been a consultant to or has received honoraria or grants from Abbot, Amgen, AstraZeneca, Bristol-Myers-Squibb, Caja Navarra, CIBERSAM, Fundación Alicia Koplowitz, Instituto de Salud Carlos III, Janssen Cilag, Lundbeck, Merck, Ministerio de Ciencia e Innovación, Ministerio de Sanidad, Ministerio de Economía y Competitividad, Mutua Madrileña, Otsuka, Pfizer, Roche, Servier, Shire, Takeda and Schering-Plough.

Additional information

A list of members and affiliations appears in the Supplementary Note.

Integrated supplementary information

Supplementary Figure 1 RVIS scores for genes with recurrent nonsynonymous PZMs in probands

(a) Graph showing the –log10(P-value) calculated from the genes with recurrent non-synonymous PZMs in probands versus RVIS scores of the genes, and (b) genes sorted by increasing order of p-values based on the recurrent non-synonymous PZMs in probands, with the RVIS score for each sorted gene shown on the y-axis.

Supplementary information

Supplementary Text and Figures

Supplementary Figure 1, Supplementary Tables 1, 6–12, 14, 15, and Supplementary Note (PDF 1026 kb)

Supplementary Methods Checklist (PDF 399 kb)

Supplementary Table 2

Rates of PZMs across ASC datasets, with the median depth and mode allele fraction of the de novos (Group A) in each dataset (XLSX 147 kb)

Supplementary Table 3

List of all de novo mutations found in the probands and unaffected siblings (XLSX 601 kb)

Supplementary Table 4

List of all de novo mutations that were validated using the different resequencing approaches (XLSX 145 kb)

Supplementary Table 5

Quantitative RT-PCR results for assaying copy number variants (XLSX 71 kb)

Supplementary Table 13

Gene-specific mutation rates for post-zygotic mutations estimated from the rare inherited variants (XLSX 660 kb)

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Lim, E., Uddin, M., De Rubeis, S. et al. Rates, distribution and implications of postzygotic mosaic mutations in autism spectrum disorder. Nat Neurosci 20, 1217–1224 (2017). https://doi.org/10.1038/nn.4598

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