Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population

Abstract

Almost all genetic risk factors for autism spectrum disorders (ASDs) can be found in the general population, but the effects of this risk are unclear in people not ascertained for neuropsychiatric symptoms. Using several large ASD consortium and population-based resources (total n > 38,000), we find genome-wide genetic links between ASDs and typical variation in social behavior and adaptive functioning. This finding is evidenced through both LD score correlation and de novo variant analysis, indicating that multiple types of genetic risk for ASDs influence a continuum of behavioral and developmental traits, the severe tail of which can result in diagnosis with an ASD or other neuropsychiatric disorder. A continuum model should inform the design and interpretation of studies of neuropsychiatric disease biology.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: The genetic correlation between ASDs and pediatric social and communication difficulties in the general population.
Figure 2: The distribution of Vineland score overlaps between SSC cases and controls.
Figure 3: De novo variation influences a continuum of functional outcomes in ASD cases and controls.

References

  1. 1

    Gaugler, T. et al. Most genetic risk for autism resides with common variation. Nat. Genet. 46, 881–885 (2014).

    CAS  Article  Google Scholar 

  2. 2

    Krumm, N. et al. Excess of rare, inherited truncating mutations in autism. Nat. Genet. 47, 582–588 (2015).

    CAS  Article  Google Scholar 

  3. 3

    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).

  4. 4

    Bulik-Sullivan, B.K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).

    CAS  Article  Google Scholar 

  5. 5

    De Rubeis, S. et al. Synaptic, transcriptional and chromatin genes disrupted in autism. Nature 515, 209–215 (2014).

    CAS  Article  Google Scholar 

  6. 6

    Iossifov, I. et al. The contribution of de novo coding mutations to autism spectrum disorder. Nature 515, 216–221 (2014).

    CAS  Article  Google Scholar 

  7. 7

    Hanson, E. et al. The cognitive and behavioral phenotype of the 16p11.2 deletion in a clinically ascertained population. Biol. Psychiatry 77, 785–793 (2015).

    CAS  Article  Google Scholar 

  8. 8

    Plomin, R., Haworth, C.M. & Davis, O.S. Common disorders are quantitative traits. Nat. Rev. Genet. 10, 872–878 (2009).

    CAS  Article  Google Scholar 

  9. 9

    Kanner, L. Autistic disturbances of affective contact. Nervous Child 2, 217–250 (1943).

    Google Scholar 

  10. 10

    Constantino, J.N., Zhang, Y., Frazier, T., Abbacchi, A.M. & Law, P. Sibling recurrence and the genetic epidemiology of autism. Am. J. Psychiatry 167, 1349–1356 (2010).

    Article  Google Scholar 

  11. 11

    Robinson, E.B. et al. Evidence that autistic traits show the same etiology in the general population and at the quantitative extremes (5%, 2.5%, and 1%). Arch. Gen. Psychiatry 68, 1113–1121 (2011).

    Article  Google Scholar 

  12. 12

    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  Google Scholar 

  13. 13

    Ronald, A. et al. Genetic heterogeneity between the three components of the autism spectrum: a twin study. J. Am. Acad. Child Adolesc. Psychiatry 45, 691–699 (2006).

    Article  Google Scholar 

  14. 14

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

    CAS  Article  Google Scholar 

  15. 15

    Männik, K. et al. Copy number variations and cognitive phenotypes in unselected populations. J. Am. Med. Assoc. 313, 2044–2054 (2015).

    Article  Google Scholar 

  16. 16

    Moreno-De-Luca, A. et al. The role of parental cognitive, behavioral, and motor profiles in clinical variability in individuals with chromosome 16p11.2 deletions. JAMA Psychiatry 72, 119–126 (2015).

    Article  Google Scholar 

  17. 17

    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).

    CAS  Article  Google Scholar 

  18. 18

    Bulik-Sullivan, B. et al. An atlas of genetic correlations across human diseases and traits. Nat. Genet. 47, 1236–1241 (2015).

    CAS  Article  Google Scholar 

  19. 19

    Boyd, A. et al. Cohort Profile: the 'children of the 90s'—the index offspring of the Avon Longitudinal Study of Parents and Children. Int. J. Epidemiol. 42, 111–127 (2013).

    Article  Google Scholar 

  20. 20

    Fraser, A. et al. Cohort Profile: the Avon Longitudinal Study of Parents and Children: ALSPAC mothers cohort. Int. J. Epidemiol. 42, 97–110 (2013).

    Article  Google Scholar 

  21. 21

    Skuse, D.H., Mandy, W.P. & Scourfield, J. Measuring autistic traits: heritability, reliability and validity of the Social and Communication Disorders Checklist. Br. J. Psychiatry 187, 568–572 (2005).

    Article  Google Scholar 

  22. 22

    Robinson, E.B. et al. Stability of autistic traits in the general population: further evidence for a continuum of impairment. J. Am. Acad. Child Adolesc. Psychiatry 50, 376–384 (2011).

    Article  Google Scholar 

  23. 23

    St Pourcain, B. et al. Variability in the common genetic architecture of social-communication spectrum phenotypes during childhood and adolescence. Mol. Autism 5, 18 (2014).

    Article  Google Scholar 

  24. 24

    Fischbach, G.D. & Lord, C. The Simons Simplex Collection: a resource for identification of autism genetic risk factors. Neuron 68, 192–195 (2010).

    CAS  Article  Google Scholar 

  25. 25

    Sparrow, S.S., Cicchetti, D.V. & Balla, D.A. Vineland Adaptive Behavior Scales (Pearson, 2005).

  26. 26

    Robinson, E.B. et al. Autism spectrum disorder severity reflects the average contribution of de novo and familial influences. Proc. Natl. Acad. Sci. USA 111, 15161–15165 (2014).

    CAS  Article  Google Scholar 

  27. 27

    Samocha, K.E. et al. A framework for the interpretation of de novo mutation in human disease. Nat. Genet. 46, 944–950 (2014).

    CAS  Article  Google Scholar 

  28. 28

    Adzhubei, I.A. et al. A method and server for predicting damaging missense mutations. Nat. Methods 7, 248–249 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. 29

    Loh, P.R. et al. Contrasting regional architectures of schizophrenia and other complex diseases using fast variance components analysis. Nat. Genet. 47, 1385–1392 (2015).

    CAS  Article  Google Scholar 

  30. 30

    Bulik-Sullivan, B. Relationship between LD score and Haseman-Elston regression. bioRxiv 10.1101/018283 (20 April 2015).

  31. 31

    Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421–427 (2014).

  32. 32

    Børglum, A.D. et al. Genome-wide study of association and interaction with maternal cytomegalovirus infection suggests new schizophrenia loci. Mol. Psychiatry 19, 325–333 (2014).

    Article  Google Scholar 

  33. 33

    Hollegaard, M.V. et al. Robustness of genome-wide scanning using archived dried blood spot samples as a DNA source. BMC Genet. 12, 58 (2011).

    Article  Google Scholar 

  34. 34

    Benyamin, B. et al. Childhood intelligence is heritable, highly polygenic, and associated with FNBP1L. Mol. Psychiatry 19, 253–258 (2014).

    CAS  Article  Google Scholar 

Download references

Acknowledgements

We thank S. Hyman, T. Lehner and N. Kanwisher for comments on the manuscript. We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. The UK Medical Research Council, the Wellcome Trust (grant 102215/2/13/2) and the University of Bristol provide core support for ALSPAC. Autism Speaks (7132) provided support for the analysis of autistic trait–related data in ALSPAC (to B.S.P.). This work was also supported by the Medical Research Council Integrative Epidemiology Unit (MC_UU_12013/1-9). This publication is the work of the authors, and E.B.R. and M.J.D. will serve as guarantors for the contents of this paper. The ALSPAC GWAS data were generated by the Sample Logistics and Genotyping Facilities at the Wellcome Trust Sanger Institute and LabCorp (Laboratory Corporation of America) using support from 23andMe. E.B.R. was funded by National Institute of Mental Health grant 1K01MH099286-01A1 and Brain Behavior Research Foundation (NARSAD) Young Investigator grant 22379. We thank the families who took part in the Simons Simplex Collection study and the clinicians who collected data at each of the study sites. The iPSYCH project is funded by the Lundbeck Foundation and the universities and university hospitals of Aarhus and Copenhagen. Genotyping of iPSYCH and PGC samples was supported by grants from the Stanley Foundation, the Simons Foundation (SFARI 311789 to M.J.D.) and the National Institute of Mental Health (5U01MH094432-02 to M.J.D.). The authors would like to thank the Exome Aggregation Consortium and the groups that provided exome variant data for comparison. A full list of contributing groups can be found on the ExAC website (see URLs). This work was also supported by a grant from the Simons Foundation (SFARI 307705; to S.J.S.).

Author information

Affiliations

Authors

Consortia

Contributions

E.B.R., B.S.P., V.A., J.A.K., B.B.-S., J.G., J. Maller, K.E.S., S.J.S., D.M.E., S.R., J. Martin, M.V.H., T.W., D.M.H., P.B.M. and A.D.B. generated data and/or conducted analyses. E.B.R., B.S.P., B.B.-S., B.M.N., J. Martin, D.S. and M.J.D. designed the experiment and tools. P.B.M., A.D.B., A.R., G.D.S. and M.J.D. supervised the research. E.B.R., B.S.P. and M.J.D. wrote the manuscript.

Corresponding authors

Correspondence to Elise B Robinson or Mark J Daly.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 De novo variant continuum without the ExAC filter.

P values were derived from Poisson regression. LoF, loss of function; DCM, probably damaging constrained missense; ExAC, Exome Aggregation Consortium.

Supplementary information

Supplementary Text and Figures

Supplementary Figure 1 and Supplementary Tables 1–3. (PDF 328 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Robinson, E., St Pourcain, B., Anttila, V. et al. Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population. Nat Genet 48, 552–555 (2016). https://doi.org/10.1038/ng.3529

Download citation

Further reading

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing