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.

  • Review Article
  • Published:

The landscape of DNA methylation amid a perfect storm of autism aetiologies

Key Points

  • The aetiology of autism spectrum disorder is complex: hundreds of genetic variants and various environmental factors have been implicated as risk factors.

  • Epigenetic mechanisms such as DNA methylation and chromatin structure are optimally poised at the intersection of genes and environment in autism aetiologies.

  • DNA methylation includes multiple modification types, some of which are specifically enriched in the nervous system.

  • The association of DNA methylation with gene expression and the dynamics of modification changes during brain development depend on genomic context.

  • DNA-methylation patterns are highly dynamic across the lifespan, with the biggest changes occurring around implantation and in the transition between fetal to early postnatal life.

  • Alterations in DNA methylation have been observed by both candidate gene and genomic studies of the post-mortem brain in autism. Future investigations of the autistic brain and surrogate tissues using larger sample sizes and whole-genome sequencing approaches hold promise for improved understanding and potential molecular diagnosis of autism risk.

Abstract

Increasing evidence points to a complex interplay between genes and the environment in autism spectrum disorder (ASD), including rare de novo mutations in chromatin genes such as methyl-CpG binding protein 2 (MECP2) in Rett syndrome. Epigenetic mechanisms such as DNA methylation act at this interface, reflecting the plasticity in metabolic and neurodevelopmentally regulated gene pathways. Genome-wide studies of gene sequences, gene pathways and DNA methylation are providing valuable mechanistic insights into ASD. The dynamic developmental landscape of DNA methylation is vulnerable to numerous genetic and environmental insults: therefore, understanding pathways that are central to this 'perfect storm' will be crucial to improving the diagnosis and treatment of ASD.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Types of DNA methylation in the mammalian brain.
Figure 2: The landscape of DNA methylation in relation to gene expression.
Figure 3: DNA methylation landscape across development.

Similar content being viewed by others

References

  1. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (Arlington, 2013).

  2. Doshi-Velez, F., Ge, Y. & Kohane, I. Comorbidity clusters in autism spectrum disorders: an electronic health record time-series analysis. Pediatrics 133, e54–e63 (2013).

    Article  PubMed  Google Scholar 

  3. Developmental Disabilities Monitoring Network Surveillance Year 2010 Principal Investigators & Centers for Disease Control and Prevention (CDC). Prevalence of autism spectrum disorder among children aged 8 years — autism and developmental disabilities monitoring network, 11 sites, United States, 2010. MMWR Surveill. Summ. 63, 1–21 (2014).

  4. 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 

  5. Kalkbrenner, A. E., Schmidt, R. J. & Penlesky, A. C. Environmental chemical exposures and autism spectrum disorders: a review of the epidemiological evidence. Curr. Probl. Pediatr. Adolesc. Health Care 44, 277–318 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Krumm, N., O'Roak, B. J., Shendure, J. & Eichler, E. E. A de novo convergence of autism genetics and molecular neuroscience. Trends Neurosci. 37, 95–105 (2014).

    Article  CAS  PubMed  Google Scholar 

  7. Bourgeron, T. From the genetic architecture to synaptic plasticity in autism spectrum disorder. Nat. Rev. Neurosci. 16, 551–563 (2015).

    Article  PubMed  CAS  Google Scholar 

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

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Sandin, S. et al. The familial risk of autism. JAMA 311, 1770–1777 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Schmidt, R. J. et al. Maternal periconceptional folic acid intake and risk for developmental delay and autism spectrum disorder: a case-control study. Am. J. Epidemiol. 175, S126 (2012).

    Google Scholar 

  11. Schmidt, R. J. Maternal folic acid supplements associated with reduced autism risk in the child. Evid. Based. Med. 18, e53 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Suren, P. et al. Association between maternal use of folic acid supplements and risk of autism spectrum disorders in children. J. Am. Med. Assoc. 309, 570–577 (2013).

    Article  CAS  Google Scholar 

  13. Lee, B. K. et al. Maternal hospitalization with infection during pregnancy and risk of autism spectrum disorders. Brain Behav. Immun. 44, 100–105 (2015).

    Article  PubMed  Google Scholar 

  14. Fang, S. Y., Wang, S., Huang, N., Yeh, H. H. & Chen, C. Y. Prenatal infection and autism spectrum disorders in childhood: a population-based case-control study in Taiwan. Paediatr. Perinat. Epidemiol. 29, 307–316 (2015).

    Article  PubMed  Google Scholar 

  15. Keil, A. P., Daniels, J. L. & Hertz-Picciotto, I. Autism spectrum disorder, flea and tick medication, and adjustments for exposure misclassification: the CHARGE (CHildhood Autism Risks from Genetics and Environment) case-control study. Environ. Health 13, 3 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. Shelton, J. F. et al. Neurodevelopmental disorders and prenatal residential proximity to agricultural pesticides: the CHARGE study. Environ. Health Perspect. 122, 1103–1109 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Lasalle, J. Epigenetic layers and players underlying neurodevelopment. Trends Neurosci. 36, 460–470 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. Lister, R. et al. Human DNA methylomes at base resolution show widespread epigenomic differences. Nature 462, 315–322 (2009). This study was the first whole-genome bisulfite sequencingexamination of DNA methylation in human cells to reveal mCHmethylation.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Lister, R. et al. Global epigenomic reconfiguration during mammalian brain development. Science. 341, 629–643 (2013). This was the first whole-genome bisulfite sequencingexamination of DNA methylation dynamics in brain development in humans and mice.

    Article  CAS  Google Scholar 

  20. Ziller, M. J. et al. Charting a dynamic DNA methylation landscape of the human genome. Nature 500, 477–481 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  21. Schultz, M. D. et al. Human body epigenome maps reveal noncanonical DNA methylation variation. Nature 523, 212–216 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Hon, G. C. et al. Epigenetic memory at embryonic enhancers identified in DNA methylation maps from adult mouse tissues. Nat. Genet. 45, 1198–1206 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Mo, A. et al. Epigenomic signatures of neuronal diversity in the mammalian brain. Neuron 86, 1369–1384 (2015). This study was the first to show DNA-methylation maps in specific neuronal subtypes from the mouse cortex, and it reveals cell-type-specific methylation signatures.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Goto, K. et al. Expression of DNA methyltransferase gene in mature and immature neurons as well as proliferating cells in mice. Differentiation 56, 39–44 (1994).

    Article  CAS  PubMed  Google Scholar 

  25. Li, E., Bestor, T. H. & Jaenisch, R. Targeted mutation of the DNA methyltransferase gene results in embryonic lethality. Cell 69, 915–926 (1992).

    Article  CAS  PubMed  Google Scholar 

  26. Watanabe, D., Suetake, I., Tada, T. & Tajima, S. Stage- and cell-specific expression of Dnmt3a and Dnmt3b during embryogenesis. Mech. Dev. 118, 187–190 (2002).

    Article  PubMed  CAS  Google Scholar 

  27. Feng, J., Chang, H., Li, E. & Fan, G. Dynamic expression of de novo DNA methyltransferases Dnmt3a and Dnmt3b in the central nervous system. J. Neurosci. Res. 79, 734–746 (2005).

    Article  CAS  PubMed  Google Scholar 

  28. Okano, M., Bell, D. W., Haber, D. A. & Li, E. DNA methyltransferases Dnmt3a and Dnmt3b are essential for de novo methylation and mammalian development. Cell 99, 247–257 (1999).

    Article  CAS  PubMed  Google Scholar 

  29. Tahiliani, M. et al. Conversion of 5-methylcytosine to 5-hydroxymethylcytosine in mammalian DNA by MLL partner TET1. Science 324, 930–935 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  30. He, Y.-F. et al. Tet-mediated formation of 5-carboxylcytosine and its excision by TDG in mammalian DNA. Science 333, 1303–1307 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  31. Ito, S. et al. Tet proteins can convert 5-methylcytosine to 5-formylcytosine and 5-carboxylcytosine. Science 333, 1300–1303 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Guo, J. U., Su, Y., Zhong, C., Ming, G. L. & Song, H. Hydroxylation of 5-methylcytosine by TET1 promotes active DNA demethylation in the adult brain. Cell 145, 423–434 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. Szwagierczak, A., Bultmann, S., Schmidt, C. S., Spada, F. & Leonhardt, H. Sensitive enzymatic quantification of 5-hydroxymethylcytosine in genomic DNA. Nucleic Acids Res. 38, e181 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. Gu, T.-P. et al. The role of Tet3 DNA dioxygenase in epigenetic reprogramming by oocytes. Nature 477, 606–610 (2011).

    Article  PubMed  CAS  Google Scholar 

  35. Dawlaty, M. M. et al. Tet1 is dispensable for maintaining pluripotency and its loss is compatible with embryonic and postnatal development. Cell Stem Cell 9, 166–175 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Li, Z. et al. Deletion of Tet2 in mice leads to dysregulated hematopoietic stem cells and subsequent development of myeloid malignancies. Blood 118, 4509–4518 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. Dawlaty, M. M. et al. Combined deficiency of Tet1 and Tet2 causes epigenetic abnormalities but is compatible with postnatal development. Dev. Cell 24, 310–323 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  38. Szulwach, K. E. et al. 5-hmC-mediated epigenetic dynamics during postnatal neurodevelopment and aging. Nat. Neurosci. 14, 1607–1616 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Wen, L. et al. Whole-genome analysis of 5-hydroxymethylcytosine and 5-methylcytosine at base resolution in the human brain. Genome Biol. 15, R49 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Song, C.-X. et al. Genome-wide profiling of 5-formylcytosine reveals its roles in epigenetic priming. Cell 153, 678–691 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Schanen, N. C. Epigenetics of autism spectrum disorders. Hum. Mol. Genet. 15 (Suppl. 2), R138–R150 (2006).

    Article  PubMed  CAS  Google Scholar 

  42. Lasalle, J. M. Epigenomic strategies at the interface of genetic and environmental risk factors for autism. 58, 396–401 (2013).

  43. Tatton-Brown, K. et al. Mutations in the DNA methyltransferase gene DNMT3A cause an overgrowth syndrome with intellectual disability. Nat. Genet. 46, 385–388 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  44. Sanders, S. J. et al. Insights into autism spectrum disorder genomic architecture and biology from 71 risk loci. Neuron 87, 1215–1233 (2015). This is the most recent and comprehensive examination of de novo mutations in ASD.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  45. Leung, K. N., Chamberlain, S. J., Lalande, M. & Lasalle, J. M. Neuronal chromatin dynamics of imprinting in development and disease. J. Cell. Biochem. 112, 365–373 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  46. LaSalle, J. M., Reiter, L. T. & Chamberlain, S. J. Epigenetic regulation of UBE3A and roles in human neurodevelopmental disorders. Epigenomics 7, 1213–1228 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  47. LaSalle, J. M. & Yasui, D. H. Evolving role of MeCP2 in Rett syndrome and autism. Epigenomics 1, 119–130 (2009).

    Article  PubMed  CAS  Google Scholar 

  48. Cukier, H. N. et al. Novel variants identified in methyl-CpG-binding domain genes in autistic individuals. Neurogenetics 11, 291–303 (2010).

    Article  PubMed  CAS  Google Scholar 

  49. Spruijt, C. G. et al. Dynamic readers for 5-(hydroxy)methylcytosine and its oxidized derivatives. Cell 152, 1146–1159 (2013).

    Article  PubMed  CAS  Google Scholar 

  50. Lyst, M. J. & Bird, A. Rett syndrome: a complex disorder with simple roots. Nat. Rev. Genet. 16, 261–275 (2015).

    Article  PubMed  CAS  Google Scholar 

  51. Woods, R. et al. Long-lived epigenetic interactions between perinatal PBDE exposure and Mecp2308 mutation. Hum. Mol. Genet. 21, 2399–2411 (2012). This paper presents an example of an in utero environmental exposure (to polybrominated diphenyl ether) and a genetic mutation (MECP2 truncation) interacting to alter DNA methylation in, and behaviour of, the offspring.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Jones, P. A. Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nat. Rev. Genet. 13, 484–492 (2012).

    Article  CAS  PubMed  Google Scholar 

  53. Numata, S. et al. DNA methylation signatures in development and aging of the human prefrontal cortex. Am. J. Hum. Genet. 90, 260–272 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  54. Maunakea, A. K. et al. Conserved role of intragenic DNA methylation in regulating alternative promoters. Nature 466, 253–257 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  55. Kim, M. et al. Dynamic changes in DNA methylation and hydroxymethylation when hES cells undergo differentiation toward a neuronal lineage. Hum. Mol. Genet. 23, 657–667 (2014).

    Article  PubMed  CAS  Google Scholar 

  56. Smith, E. Y., Futtner, C. R., Chamberlain, S. J., Johnstone, K. a. & Resnick, J. L. Transcription is required to establish maternal imprinting at the Prader–Willi syndrome and Angelman syndrome locus. PLoS Genet. 7, e1002422 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  57. Christensen, B. C. et al. Aging and environmental exposures alter tissue-specific DNA methylation dependent upon CPG island context. PLoS Genet. 5, e1000602 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. Schroeder, D. I., Lott, P., Korf, I. & LaSalle, J. M. Large-scale methylation domains mark a functional subset of neuronally expressed genes. Genome Res. 21, 1583–1591 (2011). PMDs mark distinct subsets of developmentally important genes in the neuronal cell line SH-SY5Y. These findings suggest that PMDs may be regions of DNA methylation that are relevant to the epigenetic regulation of ASD candidate genes acting at synapses.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  59. Schroeder, D. et al. The human placenta methylome. Proc. Natl Acad. Sci. USA 110, 6037–6042 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  60. Hansen, K. D. et al. Increased methylation variation in epigenetic domains across cancer types. Nat. Genet. 43, 768–775 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  61. Schroeder, D. I. et al. Early developmental and evolutionary origins of gene body DNA methylation patterns in mammalian placentas. PLOS Genet. 11, e1005442 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  62. Novakovic, B. & Saffery, R. The ever growing complexity of placental epigenetics — role in adverse pregnancy outcomes and fetal programming. Placenta 33, 959–970 (2012).

    Article  PubMed  CAS  Google Scholar 

  63. Stadler, M. B. et al. DNA-binding factors shape the mouse methylome at distal regulatory regions. Nature 484, 550–550 (2012).

    Article  CAS  Google Scholar 

  64. Guo, H. et al. The DNA methylation landscape of human early embryos. Nature 511, 606–610 (2014).

    Article  PubMed  CAS  Google Scholar 

  65. Smith, Z. D. et al. DNA methylation dynamics of the human preimplantation embryo. Nature 511, 611–615 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  66. Gkountela, S. et al. DNA demethylation dynamics in the human prenatal germline. Cell 161, 1425–1436 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  67. Tang, W. W. C. et al. A unique gene regulatory network resets the human germline epigenome for development. Cell 161, 1453–1467 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  68. Guo, F. et al. The transcriptome and DNA methylome landscapes of human primordial germ cells. Cell 161, 1437–1452 (2015).

    Article  PubMed  CAS  Google Scholar 

  69. Hernandez, D. G. et al. Distinct DNA methylation changes highly correlated with chronological age in the human brain. Hum. Mol. Genet. 20, 1164–1172 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  70. Jaffe, A. E. et al. Mapping DNA methylation across development, genotype and schizophrenia in the human frontal cortex. Nat. Neurosci. 19, 4–7 (2015). This is a large 450k array study examining DNA methylation in human brain across fetal and postnatal development. The authors identify regions of differential methylation between fetal and postnatal ages that are enriched for schizophrenia GWAS risk loci, indicating a disruption of the fetal epigenome in this disorder.

    Google Scholar 

  71. Wang, T. et al. Genome-wide DNA hydroxymethylation changes are associated with neurodevelopmental genes in the developing human cerebellum. Hum. Mol. Genet. 21, 5500–5510 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  72. Tognini, P. et al. Experience-dependent DNA methylation regulates plasticity in the developing visual cortex. Nat. Neurosci. 18, 956–958 (2015).

    Article  PubMed  CAS  Google Scholar 

  73. Nord, A. S., Pattabiraman, K., Visel, A. & Rubenstein, J. L. R. Review genomic perspectives of transcriptional regulation in forebrain development. Neuron 85, 27–47 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  74. Gregory, S. G. et al. Genomic and epigenetic evidence for oxytocin receptor deficiency in autism. BMC Med. 7, 62 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  75. Zhu, L. et al. Epigenetic dysregulation of SHANK3 in brain tissues from individuals with autism spectrum disorders. Hum. Mol. Genet. 23, 1563–1578 (2014).

    Article  PubMed  CAS  Google Scholar 

  76. Zhubi, a et al. Increased binding of MeCP2 to the GAD1 and RELN promoters may be mediated by an enrichment of 5-hmC in autism spectrum disorder (ASD) cerebellum. Transl Psychiatry 4, e349 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  77. Jiang, Y. H. et al. A mixed epigenetic/genetic model for oligogenic inheritance of autism with a limited role for UBE3A. Am. J. Med. Genet. 131, 1–10 (2004).

    Article  PubMed  Google Scholar 

  78. Nagarajan, R. P., Hogard, A. R., Gwye, Y., Martin, M. R. & Lasalle, J. M. Reduced MeCP2 expression is frequent in autism frontal cortex and correlates with aberrant MECP2 promoter methylation. Epigenetics 1, 1–11 (2006).

    Article  Google Scholar 

  79. Nardone, S. et al. DNA methylation analysis of the autistic brain reveals multiple dysregulated biological pathways. Transl Psychiatry 4, e433 (2014). This is one of the two 450k array studies to examine DNA methylation in ASD brain samples. In BA10, 5,000 differentially methylationed CpGs and in BA24 more than 10,000 differentially methylationed CpGs were identified between controls and ASD samples. In ASD brain samples, genes with lower levels of methylation in BA10 show an overlap with genes showing lower expression levels in BA9.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  80. Ladd-Acosta, C. et al. Common DNA methylation alterations in multiple brain regions in autism. Mol. Psychiatry 19, 862–871 (2014). This is one of the two 450k array studies to examine DNA methylation in ASD brain samples from the prefrontal cortex, temporal cortex and cerebellum. Four significant ASD-associated DMRs were identified.

    Article  PubMed  CAS  Google Scholar 

  81. Schwenk, J. et al. High-resolution proteomics unravel architecture and molecular diversity of native AMPA receptor complexes. Neuron 74, 621–633 (2012).

    Article  PubMed  CAS  Google Scholar 

  82. Nicholson, R. H. et al. Phemx, a novel mouse gene expressed in hematopoietic cells maps to the imprinted cluster on distal chromosome 7. Genomics 68, 13–21 (2000).

    Article  PubMed  CAS  Google Scholar 

  83. Zhu, X. et al. C11orf21 a novel gene within the Beckwith–Wiedemann syndrome region in human chromosome 11p15.5. Gene 256, 311–317 (2000).

    Article  PubMed  CAS  Google Scholar 

  84. Gartlan, K. H. et al. A complementary role for the tetraspanins CD37 and Tssc6 in cellular immunity. J. Immunol. 185, 3158–3166 (2010).

    Article  PubMed  CAS  Google Scholar 

  85. Hemler, M. E. Tetraspanin proteins mediate cellular penetration, invasion, and fusion events and define a novel type of membrane microdomain. Annu. Rev. Cell Dev. Biol. 19, 397–422 (2003).

    Article  PubMed  CAS  Google Scholar 

  86. Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011). This is the first transcriptome-wide analysis of gene expression in ASD compared with control brain samples. This study suggests that differences in gene expression between brain regions may be disrupted in ASD samples.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  87. Estes, M. L. & Mcallister, A. K. Immune mediators in the brain and peripheral tissues in autism spectrum disorder. Nat. Rev. Neurosci. 16, 469–486 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  88. Takano, T. Role of microglia in autism: recent advances. Dev. Neurosci. 37, 195–202 (2015).

    Article  PubMed  CAS  Google Scholar 

  89. Xin, Y. et al. Genome-wide divergence of DNA methylation marks in cerebral and cerebellar cortices. PLoS ONE 5, e11357 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  90. Ziats, M. N. & Rennert, O. M. Aberrant expression of long noncoding RNAs in autistic brain. J. Mol. Neurosci. 49, 589–593 (2013). This large-scale transcriptome analysis of gene expression in ASD and control brain samples further supports a lack of regional expression differences in ASD for both coding and non-coding transcripts.

    Article  PubMed  CAS  Google Scholar 

  91. Ginsberg, M. R., Rubin, R. a & Natowicz, M. R. Patterning of regional gene expression in autism: new complexity. Sci. Rep. 3, 1831 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  92. Rhein, M. et al. DNA methylation results depend on DNA integrity — role of post mortem interval. Front. Genet. 6, 1–7 (2015).

    Article  CAS  Google Scholar 

  93. Lim, A. S. P. et al. 24-hour rhythms of DNA methylation and their relation with rhythms of RNA expression in the human dorsolateral prefrontal cortex. PLoS Genet. 10, e1004792 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  94. Vaiserman, A. Epidemiologic evidence for association between adverse environmental exposures in early life and epigenetic variation: a potential link to disease susceptibility? Clin. Epigenetics 7, 96 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  95. Schmidt, R. et al. Prenatal vitamins, one-carbon metabolism gene variants, and risk for autism. Epidemiology 22, 476–485 (2011). In this large, population-based case–control study, periconception and early prentatal vitamin intake are associated with lower risk for ASD. ASD risk was higher for children whose mothers failed to take prenatal vitamins and had specific genetic variants detrimental to one-carbon metabolism pathways.

    Article  PubMed  PubMed Central  Google Scholar 

  96. Julvez, J. et al. Maternal use of folic acid supplements during pregnancy and four-year-old neurodevelopment in a population-based birth cohort. Paediatr. Perinat. Epidemiol. 23, 199–206 (2009).

    Article  PubMed  Google Scholar 

  97. Tamura, T. et al. Folate status of mothers during pregnancy and mental and psychomotor development of their children at five years of age. Pediatrics 116, 703–708 (2005).

    Article  PubMed  Google Scholar 

  98. Steegers-Theunissen, R. P. et al. Periconceptional maternal folic acid use of 400 μg per day is related to increased methylation of the IGF2 gene in the very young child. PLoS ONE 4, 1–5 (2009).

    Article  CAS  Google Scholar 

  99. Dominguez-Salas, P. et al. Maternal nutrition at conception modulates DNA methylation of human metastable epialleles. Nat. Commun. 5, 1–7 (2014).

    Article  CAS  Google Scholar 

  100. Barua, S. et al. Single-base resolution of mouse offspring brain methylome reveals epigenome modifications caused by gestational folic acid. Epigenetics Chromatin 7, 3 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  101. Hustad, S. et al. The methylenetetrahydrofolate reductase 677→T polymorphism as a modulator of a B vitamin network with major effects on homocysteine metabolism. Am. J. Hum. Genet. 80, 846–855 (2007).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  102. James, S. J. et al. Metabolic endophenotype and related genotypes are associated with oxidative stress in children with autism. Am. J. Med. Genet. B Neuropsychiatr. Genet. 141B, 947–956 (2006).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  103. James, S. J. et al. A functional polymorphism in the reduced folate carrier gene and DNA hypomethylation in mothers of children with autism. Am. J. Med. Genet. B Neuropsychiatr. Genet. 153, 1209–1220 (2010).

    Google Scholar 

  104. Hannon, E. et al. Methylation QTLs in the developing brain and their enrichment in schizophrenia risk loci. Nat. Neurosci. 19, 48–54 (2016).

    Article  CAS  PubMed  Google Scholar 

  105. Ronald, A. & Hoekstra, R. A. Autism spectrum disorders and autistic traits: a decade of new twin studies. Am. J. Med. Genet. B Neuropsychiatr. Genet. 156, 255–274 (2011).

    Article  Google Scholar 

  106. Ozonoff, S. et al. Recurrence risk for autism spectrum disorders: a baby siblings research consortium study. Pediatrics 128, e488–e495 (2011).

    PubMed  PubMed Central  Google Scholar 

  107. Robinson, E. B., Lichtenstein, P., Anckarsater, H., Happe, F. & Ronald, A. Examining and interpreting the female protective effect against autistic behavior. Proc. Natl Acad. Sci. USA 110, 5258–5262 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

  109. Pinto, D. et al. Functional impact of global rare copy number variation in autism spectrum disorders. Nature 466, 368–372 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  110. Girirajan, S. et al. Global increases in both common and rare copy number load associated with autism. Hum. Mol. Genet. 22, 2870–2880 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  113. Hormozdiari, F., Penn, O., Borenstein, E. & Eichler, E. E. The discovery of integrated gene networks for autism and related disorders. Genome Res. 25, 142–154 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  114. Gupta, S. et al. Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism. Nat. Commun. 5, 5748 (2014).

    Article  PubMed  CAS  Google Scholar 

  115. Miller, C. a & Sweatt, J. D. Covalent modification of DNA regulates memory formation. Neuron 53, 857–869 (2007).

    Article  PubMed  CAS  Google Scholar 

  116. Levenson, J., Roth, T. & Lubin, F. Evidence that DNA (cytosine-5) methyltransferase regulates synaptic plasticity in the hippocampus. J. Biol. Chem. 281, 15763–15773 (2006).

    Article  PubMed  CAS  Google Scholar 

  117. Guo, J. U. et al. Neuronal activity modifies the DNA methylation landscape in the adult brain. Nat. Neurosci. 14, 1345–1351 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  118. Feng, J. et al. Dnmt1 and Dnmt3a maintain DNA methylation and regulate synaptic function in adult forebrain neurons. Nat. Neurosci. 13, 423–430 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  119. Kaas, G. a et al. Hydroxylation, active DNA demethylation, gene transcription, and memory formation. Neuron 79, 1086–1093 (2013).

    Article  PubMed  CAS  Google Scholar 

  120. Rudenko, A. et al. Tet1 is critical for neuronal activity-regulated gene expression and memory extinction. Neuron 79, 1109–1122 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  121. Li, X. et al. Neocortical Tet3-mediated accumulation of 5-hydroxymethylcytosine promotes rapid behavioral adaptation. Proc. Natl Acad. Sci. USA 111, 7120–7125 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  122. Day, J. J. et al. DNA methylation regulates associative reward learning. Nat. Neurosci. 16, 1445–1452 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  123. Bali, P., Im, H. I. & Kenny, P. J. Methylation, memory and addiction. Epigenetics 6, 671–674 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  124. Zannas, A. S. & West, A. E. Epigenetics and the regulation of stress vulnerability and resilience. Neuroscience 264, 157–170 (2014).

    Article  PubMed  CAS  Google Scholar 

  125. Yu, M. et al. Tet-assisted bisulfite sequencing of 5-hydroxymethylcytosine. Nat. Protoc. 7, 2159–2170 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  126. Reinius, L. E. et al. Differential DNA methylation in purified human blood cells: implications for cell lineage and studies on disease susceptibility. PLoS ONE 7, e41361 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  127. Ashwood, P. et al. In search of cellular immunophenotypes in the blood of children with autism. PLoS ONE 6, e19299 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  128. Smith, A. K. et al. DNA extracted from saliva for methylation studies of psychiatric traits: evidence tissue specificity and relatedness to brain. Am. J. Med. Genet. B Neuropsychiatr. Genet. 168, 36–44 (2015).

    Article  CAS  Google Scholar 

  129. Feinberg, J. I. et al. Paternal sperm DNA methylation associated with early signs of autism risk in an autism-enriched cohort. Int. J. Epidemiol. 1–12 (2015).

  130. Lister, R. et al. Hotspots of aberrant epigenomic reprogramming in human induced pluripotent stem cells. Nature 470, 68–73 (2011).

    Article  CAS  Google Scholar 

  131. Ohi, Y. et al. Incomplete DNA methylation underlies a transcriptional memory of somatic cells in human iPS cells. Nat. Cell Biol. 13, 541–549 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  132. Gore, A. et al. Somatic coding mutations in human induced pluripotent stem cells. Nature 470, 63–67 (2011).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The authors thank D. Yasui, K. Dunaway and A. Nord for critical reading of the manuscript. Ongoing support for this research is supported by the US National Institute of Neurological Disorders and Stroke (grants R01NS081913 and R01NS076263), the US National Institute of Environmental Health Sciences (grant R01ES021707), the US Department of Defense (grant W81XWH-12-1-0491) and the US National Institute of Mental Health (grant T32MH073124-06).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Janine LaSalle.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

PowerPoint slides

Glossary

CpG

Cytosine 5′ of guanine, where the 'p' stands for the phosphate.

5-methylcytosine

(5mC). A cytosine base with a methyl group (CH3) in the 5′ position.

CpG islands

Short (< 1 kb) regions in mammalian genomes with the highest density of CpG sites.

5-hydroxymethylcytosine

(5hmC). A cytosine base with a hydroxymethyl (-CH2-OH) group in the 5′ position.

CpH

A cytosine followed by either adenine (CpA), cytosine (CpC) or thymine (CpT), where the 'p' stands for the phosphate

Ten-eleven translocase

(TET). The three TET enzymes, TET1, TET2 and TET3, are methylcytosine dioxygenases that convert 5-methylcytosine to 5-hydroxymethylcytosine.

Gene body

The genomic region extending from the transcription start site to the transcription end site.

Methyl-binding domain

(MBD). A protein domain structure with a higher affinity to methylated DNA than to unmethylated DNA. The MBD family of proteins includes methyl-CpG binding protein 2.

Differentially methylated regions

(DMRs). Short clusters of CpG sites in regions showing significant differences in methylation between stages or samples, defined bioinformatically.

Partially methylated domains

(PMDs). Large genomic regions in the mammalian genome that are characterized by lower than 70% 5-methylcytosine-guanine (5mCG). PMDs are found in 30–50% of the genome in preimplantation embryos, the placenta and most solid tumours. They are characterized by lower or more-variable transcript levels, repressive histone marks and nuclear lamina localization.

Inner cell mass

(ICM). The cells in the blastocyst of the preimplantation embryo that become fetal tissues.

Primordial germ cells

(PGCs). The embryonic lineage of cells that migrate to the genital ridge as precursors of the germline cells of the next generation (spermatagonia and oocytes).

Methylenetetrahydrofolate reductase

(MTHFR). An enzyme in the one-carbon metabolism cycle that supplies methyl groups for DNA-methylation reactions. A common polymorphism in the MTHFR gene encodes a less-efficient enzyme and is a risk factor for neural tube defects and autism.

DNA methylation valleys

(DMVs). Regions of low methylation that are >5 kb in length and are found in most cell types. They can show differences in developmental methylation between fetal and adult tissues.

Induced pluripotent stem cells

(iPSCs). Adult somatic cells that are genetically reprogrammed in vitro to produce an embryonic stem cell-like state of pluripotency. iPSCs can then be differentiated into a number of different cell types.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ciernia, A., LaSalle, J. The landscape of DNA methylation amid a perfect storm of autism aetiologies. Nat Rev Neurosci 17, 411–423 (2016). https://doi.org/10.1038/nrn.2016.41

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrn.2016.41

This article is cited by

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