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Most genetic risk for autism resides with common variation

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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Figure 1: Results for PAGES (Population-Based Autism Genetics and Environment Study), the Swedish study of the heritability of autism.
Figure 2: Results regarding the genetic architecture of autism spectrum disorder.

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References

  1. Iossifov, I. et al. De novo gene disruptions in children on the autistic spectrum. Neuron 74, 285–299 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Neale, B.M. et al. Patterns and rates of exonic de novo mutations in autism spectrum disorders. Nature 485, 242–245 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. O'Roak, B.J. et al. Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations. Nature 485, 246–250 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Sanders, S.J. et al. De novo mutations revealed by whole-exome sequencing are strongly associated with autism. Nature 485, 237–241 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Sebat, J. et al. Strong association of de novo copy number mutations with autism. Science 316, 445–449 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Glessner, J.T. et al. Autism genome-wide copy number variation reveals ubiquitin and neuronal genes. Nature 459, 569–573 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Sanders, S.J. et al. Multiple recurrent de novo CNVs, including duplications of the 7q11.23 Williams syndrome region, are strongly associated with autism. Neuron 70, 863–885 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Pinto, D. et al. Convergence of genes and cellular pathways dysregulated in autism spectrum disorders. Am. J. Hum. Genet. 94, 677–694 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Klei, L. et al. Common genetic variants, acting additively, are a major source of risk for autism. Mol. Autism 3, 9 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Lee, S.H. et al. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nat. Genet. 45, 984–994 (2013).

    Article  CAS  PubMed  Google Scholar 

  11. State, M.W. & Levitt, P. The conundrums of understanding genetic risks for autism spectrum disorders. Nat. Neurosci. 14, 1499–1506 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Devlin, B. & Scherer, S.W. Genetic architecture in autism spectrum disorder. Curr. Opin. Genet. Dev. 22, 229–237 (2012).

    Article  CAS  PubMed  Google Scholar 

  13. Anney, R. et al. Individual common variants exert weak effects on the risk for autism spectrum disorderspi. Hum. Mol. Genet. 21, 4781–4792 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Wang, K. et al. Common genetic variants on 5p14.1 associate with autism spectrum disorders. Nature 459, 528–533 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Weiss, L.A. et al. A genome-wide linkage and association scan reveals novel loci for autism. Nature 461, 802–808 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. International Schizophrenia Consortium. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 460, 748–752 (2009).

  17. Cross-Disorder Group of the Psychiatric Genomics Consortium. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nat. Genet. 45, 984–994 (2013).

  18. Stefansson, H. et al. CNVs conferring risk of autism or schizophrenia affect cognition in controls. Nature 505, 361–366 (2014).

    Article  CAS  PubMed  Google Scholar 

  19. Talkowski, M.E. et al. Sequencing chromosomal abnormalities reveals neurodevelopmental loci that confer risk across diagnostic boundaries. Cell 149, 525–537 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Hallmayer, J. et al. Genetic heritability and shared environmental factors among twin pairs with autism. Arch. Gen. Psychiatry 68, 1095–1102 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Sandin, S. et al. The familial risk of autism. J. Am. Med. Assoc. (in the press) (2014).

  22. Yang, J., Lee, S.H., Goddard, M.E. & Visscher, P.M. GCTA: a tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76–82 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Dickson, S.P., Wang, K., Krantz, I., Hakonarson, H. & Goldstein, D.B. Rare variants create synthetic genome-wide associations. PLoS Biol. 8, e1000294 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Orozco, G., Barrett, J.C. & Zeggini, E. Synthetic associations in the context of genome-wide association scan signals. Hum. Mol. Genet. 19, R137–R144 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Wray, N.R., Purcell, S.M. & Visscher, P.M. Synthetic associations created by rare variants do not explain most GWAS results. PLoS Biol. 9, e1000579 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Crossett, A., Lee, A.B., Klei, L., Devlin, B. & Roeder, K. Refining genetically inferred relationships using treelet covariance smoothing. Ann. Appl. Stat. 7, 669–690 (2013).

    Article  PubMed  Google Scholar 

  27. Lim, E.T. et al. Rare complete knockouts in humans: population distribution and significant role in autism spectrum disorders. Neuron 77, 235–242 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Agarwala, V., Flannick, J., Sunyaev, S. & Altshuler, D. Evaluating empirical bounds on complex disease genetic architecture. Nat. Genet. 45, 1418–1427 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Zuk, O., Hechter, E., Sunyaev, S.R. & Lander, E.S. The mystery of missing heritability: genetic interactions create phantom heritability. Proc. Natl. Acad. Sci. USA 109, 1193–1198 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Lynch, M. & Walsh, B. Genetics and Analysis of Quantitative Traits (Sinauer Associates, Sunderland, MA, 1998).

  31. Devlin, B., Daniels, M. & Roeder, K. The heritability of IQ. Nature 388, 468–471 (1997).

    Article  CAS  PubMed  Google Scholar 

  32. Lichtenstein, P., Carlstrom, E., Rastam, M., Gillberg, C. & Anckarsater, H. The genetics of autism spectrum disorders and related neuropsychiatric disorders in childhood. Am. J. Psychiatry 167, 1357–1363 (2010).

    Article  PubMed  Google Scholar 

  33. Lundström, S. et al. Autism spectrum disorders and autistic like traits: similar etiology in the extreme end and the normal variation. Arch. Gen. Psychiatry 69, 46–52 (2012).

    Article  PubMed  Google Scholar 

  34. Levy, D. et al. Rare de novo and transmitted copy-number variation in autistic spectrum disorders. Neuron 70, 886–897 (2011).

    Article  CAS  PubMed  Google Scholar 

  35. Willsey, A.J. et al. Coexpression networks implicate human midfetal deep cortical projection neurons in the pathogenesis of autism. Cell 155, 997–1007 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

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.

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Authors and Affiliations

Authors

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.

Corresponding authors

Correspondence to Kathryn Roeder or Joseph D Buxbaum.

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Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Estimated prevalence of strict autism for the entire Swedish population as a function of individuals’ ages.

Prevalence was calculated by Kaplan-Meier function utilizing year of birth, age at autistic disorder diagnosis and censoring due to death, emigration or end of study period, whichever came first. (a) Prevalence pooled across cohorts and counties. (b) Prevalence by cohort.

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Supplementary Figure 2 Distribution of relative pairs by degree of relatedness estimated using TCS.

On the basis of 3,044 subjects, there are 4,631,446 subject pairs, and 63% of the pairs are estimated to be unrelated (degree > 10). Of these pairs, 1,346 were estimated to be degree 6 or closer, with 12, 37, 104 and 1,193 of the pairs falling into the intervals 2–3, 3–4, 4–5 and 5–6, respectively.

Source data

Supplementary information

Supplementary Text and Figures

Supplementary Note, Supplementary Tables 1–3 and Supplementary Figures 1 and 2. (PDF 40004 kb)

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Gaugler, T., Klei, L., Sanders, S. et al. Most genetic risk for autism resides with common variation. Nat Genet 46, 881–885 (2014). https://doi.org/10.1038/ng.3039

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