Letter | Published:

Most genetic risk for autism resides with common variation

Nature Genetics 46, 881–885 (2014) | Download Citation

Abstract

A key component of genetic architecture is the allelic spectrum influencing trait variability. For autism spectrum disorder (herein termed autism), the nature of the allelic spectrum is uncertain. Individual risk-associated genes have been identified from rare variation, especially de novo mutations1,2,3,4,5,6,7,8. From this evidence, one might conclude that rare variation dominates the allelic spectrum in autism, yet recent studies show that common variation, individually of small effect, has substantial impact en masse9,10. At issue is how much of an impact relative to rare variation this common variation has. Using a unique epidemiological sample from Sweden, new methods that distinguish total narrow-sense heritability from that due to common variation and synthesis of results from other studies, we reach several conclusions about autism's genetic architecture: its narrow-sense heritability is ∼52.4%, with most due to common variation, and rare de novo mutations contribute substantially to individual liability, yet their contribution to variance in liability, 2.6%, is modest compared to that for heritable variation.

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Acknowledgements

This study was supported by National Institute of Mental Health (NIMH) grants MH057881 and MH097849 and also in part through the computational resources and staff expertise provided by the Scientific Computing Facility at the Icahn School of Medicine at Mount Sinai. We thank the Mount Sinai Genomics Core Facility for carrying out Illumina bead array genotyping. We thank D. Cutler, M. Daly and S. Purcell for comments on the manuscript and M. Daly and P. Sullivan for facilitating access to control samples, collected and genotyped by M. Daly, C.M.H., P.S. and P. Sullivan with support from NIMH grants MH095034 and MH077139. We also thank the nurses, A.-K. Sundberg and A.-B. Holmgren, for their hard work in collecting the samples. AGP: We used data from the Autism Genome Project (AGP) Consortium Whole-Genome Association and Copy Number Variation Study of over 2,600 parent-offspring trios (database of Genotypes and Phenotypes (dbGaP) study phs000267.v4.p2). Funding for AGP was provided from the US NIH (HD055751, HD055782, HD055784, HD35465, MH52708, MH55284, MH57881, MH061009, MH06359, MH066673, MH080647, MH081754, MH66766, NS026630, NS042165 and NS049261); the Canadian Institutes for Health Research (CIHR); Assistance Publique–Hôpitaux de Paris, France; Autism Speaks, UK; the Canada Foundation for Innovation/Ontario Innovation Trust; grant Po 255/17-4 from Deutsche Forschungsgemeinschaft, Germany; the European Community's Sixth Framework Programme AUTISM MOLGEN; Fundação Calouste Gulbenkian, Portugal; Fondation de France; Fondation FondaMental, France; Fondation Orange, France; Fondation pour la Recherche Médicale, France; Fundação para a Ciência e Tecnologia, Portugal; The Hospital for Sick Children Foundation and the University of Toronto, Canada; INSERM, France; Institut Pasteur, France; Convention 181 of 19.10.2001 from the Italian Ministry of Health; the John P. Hussman Foundation, USA; the McLaughlin Centre, Canada; Rubicon 825.06.031 from the Netherlands Organization for Scientific Research; TMF/DA/5801 from the Royal Netherlands Academy of Arts and Sciences; the Ontario Ministry of Research and Innovation, Canada; the Seaver Foundation, USA; the Swedish Science Council; the Centre for Applied Genomics, Canada; the Utah Autism Foundation, USA; and Core award 075491/Z/04 from the Wellcome Trust, UK. Genotype and phenotype data were obtained from dbGaP, as provided by AGP study investigators. HealthABC: These controls were obtained from dbGaP. Funding support for the CIDR Visceral Adiposity Study (dbGaP study phs000169.v1.p1) was provided through the Division of Aging Biology and the Division of Geriatrics and Clinical Gerontology, National Institute on Aging. The CIDR Visceral Adiposity Study includes a GWAS funded as part of the Division of Aging Biology and the Division of Geriatrics and Clinical Gerontology, National Institute on Aging. Assistance with phenotype harmonization and genotype cleaning, as well as with general study coordination, was provided by Health ABC study investigators. This manuscript reflects the views of the authors and does not necessarily reflect the opinions or views of the US NIH.

Author information

Affiliations

  1. Department of Statistics, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.

    • Trent Gaugler
    • , Corneliu A Bodea
    • , Ann B Lee
    •  & Kathryn Roeder

  2. Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.

    • Lambertus Klei
    •  & Bernie Devlin

  3. Department of Psychiatry, University of California, San Francisco, San Francisco, California, USA.

    • Stephan J Sanders

  4. Department of Genetics, Yale University School of Medicine, New Haven, Connecticut, USA.

    • Stephan J Sanders

  5. Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Arthur P Goldberg
    • , Jennifer Reichert
    • , Abraham Reichenberg
    •  & Joseph D Buxbaum

  6. Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Arthur P Goldberg
    • , Jennifer Reichert
    • , Pamela Sklar
    • , Abraham Reichenberg
    •  & Joseph D Buxbaum

  7. Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Arthur P Goldberg
    •  & Pamela Sklar

  8. Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Milind Mahajan
    • , Dina Manaa
    • , Pamela Sklar
    •  & Joseph D Buxbaum

  9. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

    • Yudi Pawitan
    • , Sven Sandin
    • , Oscar Svantesson
    •  & Christina M Hultman

  10. Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA.

    • Stephan Ripke

  11. Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Pamela Sklar
    •  & Joseph D Buxbaum

  12. Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Pamela Sklar

  13. Department of Preventive Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Abraham Reichenberg

  14. Ray and Stephanie Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.

    • Kathryn Roeder

  15. Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Joseph D Buxbaum

  16. The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Joseph D Buxbaum

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Contributions

A.R., C.M.H., B.D., K.R. and J.D.B. conceived the project and designed its components. A.R., C.M.H., B.D., K.R. and J.D.B. identified funding for the study. S.S., O.S. and C.M.H. were responsible for ascertaining case samples, and P.S. and C.M.H. were responsible for ascertaining control samples. J.R., D.M. and M.M. were responsible for genotyping the case samples. A.P.G. organized and managed the data files, and T.G. and A.P.G. carried out quality control for the SNP data. S.J.S. carried out simulations and additional analyses to assess the contribution of rare variation to variance in liability, and S.R. carried out imputation to 1000 Genomes Project data. T.G., C.A.B. and A.B.L. carried out statistical analyses under the guidance of B.D., L.K. and K.R., and Y.P., S.S., O.S., A.R. and C.M.H. carried out epidemiological analyses. B.D., K.R. and J.D.B. took the lead in writing the manuscript, and all authors reviewed and approved the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Kathryn Roeder or Joseph D Buxbaum.

Integrated supplementary information

Supplementary figures

  1. 1.

    Estimated prevalence of strict autism for the entire Swedish population as a function of individuals’ ages.

  2. 2.

    Distribution of relative pairs by degree of relatedness estimated using TCS.

Supplementary information

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    Supplementary Text and Figures

    Supplementary Note, Supplementary Tables 1–3 and Supplementary Figures 1 and 2.

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DOI

https://doi.org/10.1038/ng.3039

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