Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-76fb5796d-skm99 Total loading time: 0 Render date: 2024-04-25T21:15:26.395Z Has data issue: false hasContentIssue false

9 - Epigenome-wide association studies in neurodevelopmental disorders

from Part II - Genome-wide studies in disease biology

Published online by Cambridge University Press:  18 December 2015

By
Takeo Kubota ,
Kunio Miyake  and
Takae Hirasawa
Edited by
Krishnarao Appasani
Foreword by
Stephen W. Scherer  and
Peter M. Visscher
Takeo Kubota
Affiliation:
University of Yamanashi
Kunio Miyake
Affiliation:
University of Yamanashi
Takae Hirasawa
Affiliation:
University of Yamanashi
Krishnarao Appasani
Affiliation:
GeneExpression Systems, Inc., Massachusetts
Stephen W. Scherer
Affiliation:
University of Toronto
Peter M. Visscher
Affiliation:
University of Queensland
Get access

Summary

Introduction

The brain is a gene-dosage sensitive organ in which either under- or overexpression of genes encoding proteins associated with brain function results in a range of congenital neurodevelopmental disorders, suggesting that the brain is extremely sensitive to perturbations in gene regulation, and further indicating the importance of a proper gene expression control in the brain.

Intrinsic epigenetic mechanisms are involved in the controls of gene expression, and are essential for normal development during embryogenesis and for differentiation of neural cells (Takizawa et al., 2001). It has been reported that abnormalities in epigenetic mechanisms can result in a number of congenital neurodevelopmental disorders.

Advances in methodologies for epigenetic analysis, such as Beadchip microarrays and next-generation sequencing, now enable the investigation of the epigenetic status at individual loci, multiple loci, or the whole genome. These new approaches also enable epigenome-wide association studies (EWAS).

Several lines of evidence suggest that epigenetic abnormalities can be induced by environmental factors. Thus, clinical epigenetic research not only needs to target congenital disorders, but must also investigate acquired chronic diseases including common mental and neurodevelopmental disorders, in which epigenomic abnormalities may reside at multiple genomic loci.

We are now in the process of identifying environmentally induced epigenomic changes that can be used as “epigenomic disease signature,” that is, predictive markers for chronic diseases. Realization of this goal will ensure the start of “personalized medicine” or “preemptive medicine.”

In this chapter, we describe epigenetic and epigenomic (genome-wide epigenetic) abnormalities associated with congenital neurodevelopmental disorders. Additionally, we describe environment-induced epigenetic abnormalities, and discuss EWAS on various diseases including neurodevelopmental disorders. We also discuss personalized medicine as a goal of EWAS.

Congenital neurodevelopmental disorders with epigenetic abnormalities

Genomic imprinting disorders

Genomic imprinting is an epigenetic phenomenon that was initially discovered in mammals, and results in the monoallelic, parent-of-origin expression of some genes. These inherited maternal and paternal imprints are erased in the germ line and a new imprinting pattern is established according to the sex of the individual.

Type
Chapter
Information
Genome-Wide Association Studies
From Polymorphism to Personalized Medicine
 , pp. 123 - 136
Publisher: Cambridge University Press
Print publication year: 2016

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Adkins, R.M., Thomas, F., Tylavsky, F.A. and Krushkal, J. (2011). Parental ages and levels of DNA methylation in the newborn are correlated. BMC Med. Genet., 12, 47.CrossRefGoogle ScholarPubMed
Amir, R.E., Van den Veyver, I.B., Wan, M., et al. (1999). Rett syndrome is caused by mutations in X-linked MECP2 encoding methyl-CpG-binding protein 2. Nature Genet., 23, 185–188.CrossRefGoogle ScholarPubMed
Breitling, L.P., Yang, R., Korn, B., Burwinkel, B. and Brenner, H. (2011). Tobacco-smoking-related differential DNA methylation: 27K discovery and replication. Am. J. Hum. Genet., 88, 450–457.CrossRefGoogle Scholar
Champagne, F.A., Weaver, I.C., Diorio, J., et al.(2006). Maternal care associated with methylation of the estrogen receptor-alpha1b promoter and estrogen receptor-alpha expression in the medial preoptic area of female offspring. Endocrinology, 147, 2909–2915.CrossRefGoogle ScholarPubMed
Choi, S.W., Claycombe, K.J., Martinez, J.A., Friso, S. and Schalinske, K.L. (2013). Nutritional epigenomics: a portal to disease prevention. Adv. Nutr., 4, 530–532.CrossRefGoogle ScholarPubMed
Chong, S., Youngson, N.A. and Whitelow, E. (2007). Heritable germline epimutation is not the same as transgenerational epigenetic inheritance. Nature Genet., 39, 574–575.CrossRefGoogle Scholar
Cruickshank, M.N., Pitt, J. and Craig, J.M. (2012). Going back to the future with Guthrie-powered epigenome-wide association studies. Genome Med., 4, 83.CrossRefGoogle ScholarPubMed
Daxinger, L. and Whitelaw, E. (2010). Transgenerational epigenetic inheritance: more questions than answers. Genome Res., 20, 1623–1628.CrossRefGoogle ScholarPubMed
Florath, I., Butterbach, K., Müller, H., Bewerunge-Hudler, M. and Brenner, H. (2014). Cross-sectional and longitudinal changes in DNA methylation with age: an epigenome-wide analysis revealing over 60 novel age-associated CpG sites. Hum. Molec. Genet., 23, 1186–1201.CrossRefGoogle ScholarPubMed
Fraga, M.F., Ballestar, E., Paz, M.F., et al. (2005). Epigenetic differences arise during the lifetime of monozygotic twins. Proc. Natl Acad. Sci. USA, 102, 10604–10609.CrossRefGoogle ScholarPubMed
Franklin, T.B., Russig, H., Weiss, I.C., et al. (2010). Epigenetic transmission of the impact of early stress across generations. Biol. Psych., 68, 408–415.Google Scholar
Fromer, M., Pocklington, A.J., Kavanagh, D.H., et al. (2014). De novo mutations in schizophrenia implicate synaptic networks. Nature, 506, 179–184.CrossRefGoogle ScholarPubMed
Gertz, J., Varley, K.E., Reddy, T.E, et al. (2011). Analysis of DNA methylation in a three-generation family reveals widespread genetic influence on epigenetic regulation. PLoS Genet., 7, e1002228.CrossRefGoogle Scholar
Gluckman, P.D., Seng, C.Y., Fukuoka, H., Beedle, A.S. and Hanson, M.A. (2007). Low birthweight and subsequent obesity in Japan. Lancet, 369, 1081–1082.CrossRefGoogle ScholarPubMed
Hackett, J.A., Sengupta, R., Zylicz, J.J., et al. (2013). Germline DNA demethylation dynamics and imprint erasure through 5-hydroxymethylcytosine. Science, 339, 448–452.CrossRefGoogle ScholarPubMed
Hidalgo, B., Irvin, M.R., Sha, J., et al. (2014). Epigenome-wide association study of fasting measures of glucose, insulin, and HOMA-IR in the genetics of lipid lowering drugs and diet network study. Diabetes, 63, 801–807.CrossRefGoogle ScholarPubMed
Horsthemke, B. (2007). Heritable germline epimutations in humans. Nature Genet., 39, 573–574.CrossRefGoogle ScholarPubMed
Kaminsky, Z., Tochigi, M., Jia, P., et al. (2012). A multi-tissue analysis identifies HLA complex group 9 gene methylation differences in bipolar disorder. Molec. Psych., 17, 728–740.CrossRefGoogle ScholarPubMed
Kerkel, K., Spadola, A., Yuan, E., et al. (2008). Genomic surveys by methylation-sensitive SNP analysis identify sequence-dependent allele-specific DNA methylation. Nature Genet., 40, 904–908.CrossRefGoogle ScholarPubMed
Kim, Y.S., Leventhal, B.L., Koh, Y.J., et al. (2011). Prevalence of autism spectrum disorders in a total population sample. Am. J. Psych., 168, 904–912.CrossRefGoogle Scholar
Kubota, T., Das, S., Christian, S.L., et al. (1997). Methylation-specific PCR simplifies imprinting analysis. Nature Genet., 16, 16–17.CrossRefGoogle ScholarPubMed
Kubota, T., Wakui, K., Nakamura, T., et al. (2002). Proportion of the cells with functional X disomy is associated with the severity of mental retardation in mosaic ring X Turner syndrome females. Cytogenet. Genome Res., 99, 276–284.CrossRefGoogle ScholarPubMed
Kubota, T., Furuumi, H., Kamoda, T., et al. (2004). ICF syndrome in a girl with DNA hypomethylation but without detectable DNMT3B mutation. Am. J. Med. Genet. A, 129A, 290–293.CrossRefGoogle Scholar
Lahiri, D.K. and Maloney, B. (2012). Gene × environment interaction by a longitudinal epigenome-wide association study (LEWAS) overcomes limitations of genome-wide association study (GWAS). Epigenomics, 4, 685–699.CrossRefGoogle Scholar
Lambrot, R., Xu, C., Saint-Phar, S., et al. (2013). Low paternal dietary folate alters the mouse sperm epigenome and is associated with negative pregnancy outcomes. Nature Commun., 4, 2889.CrossRefGoogle ScholarPubMed
Langevin, S.M., Koestler, D.C., Christensen, B.C., et al. (2012). Peripheral blood DNA methylation profiles are indicative of head and neck squamous cell carcinoma: an epigenome-wide association study. Epigenetics, 7, 291–299.CrossRefGoogle ScholarPubMed
Lillycrop, K.A., Phillips, E.S., Torrens, C., et al. (2008). Feeding pregnant rats a protein-restricted diet persistently alters the methylation of specific cytosines in the hepatic PPAR alpha promoter of the offspring. Br. J. Nutr., 100, 278–282.CrossRefGoogle ScholarPubMed
Lim, D., Bowdin, S.C. and Tee, L. (2009). Clinical and molecular genetic features of Beckwith–Wiedemann syndrome associated with assisted reproductive technologies. Hum. Reprod., 24, 741–747.Google ScholarPubMed
Liu, Y., Aryee, M.J., Padyukov, L., et al. (2013). Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis. Nature Biotechnol., 31, 142–147.CrossRefGoogle ScholarPubMed
McGowan, P.O., Sasaki, A., D'Alessio, A.C., et al. (2009). Epigenetic regulation of the glucocorticoid receptor in human brain associates with childhood abuse. Nature Neurosci., 12, 342–348.CrossRefGoogle ScholarPubMed
Miyake, K., Hirasawa, T., Soutome, M., et al. (2011). The protocadherins, PCDHB1 and PCDH7, are regulated by MeCP2 in neuronal cells and brain tissues: implication for pathogenesis of Rett syndrome. BMC Neurosci., 12, 81.CrossRefGoogle ScholarPubMed
Miyake, K., Yang, C., Minakuchi, Y., et al. (2013). Comparison of genomic and epigenomic expression in monozygotic twins discordant for Rett syndrome. PLoS ONE, 8, e66729.Google ScholarPubMed
Murgatroyd, C., Patchev, A.V., Wu, Y., et al. (2009). Dynamic DNA methylation programs persistent adverse effects of early-life stress. Nature Neurosci., 12, 1559–1566.CrossRefGoogle ScholarPubMed
Nguyen, H.N., Fujiyoshi, A., Abbott, R.D. and Miura, K. (2013). Epidemiology of cardiovascular risk factors in Asian countries. Circul. J., 77, 2851–2859.CrossRefGoogle ScholarPubMed
Nolen, L.D., Gao, S., Han, Z., et al. (2005). X chromosome reactivation and regulation in cloned embryos. Develop. Biol., 279, 525–540.CrossRefGoogle ScholarPubMed
Painter, R.C., de Rooij, S.R., Bossuyt, P.M., et al. (2006). Early onset of coronary artery disease after prenatal exposure to the Dutch famine. Am. J. Clin. Nutr., 84, 322–327.Google ScholarPubMed
Petersen, A.K., Zeilinger, S., Kastenmüller, G., et al. (2014). Epigenetics meets metabolomics: an epigenome-wide association study with blood serum metabolic traits. Hum. Molec. Genet., 23, 534–545.CrossRefGoogle ScholarPubMed
Rakyan, V.K., Down, T.A., Balding, D.J. and Beck, S. (2011). Epigenome-wide association studies for common human diseases. Nature Rev. Genet., 12, 529–541.CrossRefGoogle ScholarPubMed
Sakazume, S., Ohashi, H., Sasaki, Y., et al. (2012) Spread of X-chromosome inactivation into chromosome 15 is associated with Prader–Willi syndrome phenotype in a boy with a t(X;15)(p21.1;q11.2) translocation. Hum. Genet., 131, 121–130.CrossRefGoogle Scholar
Sato, S., Yoshimizu, T., Sato, E. and Matsui, Y. (2003). Erasure of methylation imprinting of Igf2r during mouse primordial germ-cell development. Molec. Reprod. Devel., 65, 41–50.CrossRefGoogle ScholarPubMed
Shenker, N.S., Polidoro, S., van Veldhoven, K., et al. (2013). Epigenome-wide association study in the European Prospective Investigation into Cancer and Nutrition (EPIC-Turin) identifies novel genetic loci associated with smoking. Hum. Molec. Genet., 22, 843–851.CrossRefGoogle ScholarPubMed
St Clair, D., Xu, M., Wang, P., et al. (2005). Rates of adult schizophrenia following prenatal exposure to the Chinese famine of 1959–1961. J. Am. Med. Ass., 294, 557–562.CrossRefGoogle ScholarPubMed
Takizawa, T., Nakashima, K., Namihira, M., et al. (2001). DNA methylation is a critical cell-intrinsic determinant of astrocyte differentiation in the fetal brainDevelop. Cell, 1, 749–758.CrossRefGoogle ScholarPubMed
Tobi, E.W., Lumey, L.H., Talens, R.P., et al. (2009). DNA methylation differences after exposure to prenatal famine are common and timing- and sex-specific. Hum. Molec. Genet., 18, 4046–4053.CrossRefGoogle ScholarPubMed
Tsai, P.C., Spector, T.D. and Bell, J.T. (2012). Using epigenome-wide association scans of DNA methylation in age-related complex human traits. Epigenomics, 4, 511–526.CrossRefGoogle ScholarPubMed
Verkerk, A.J., Pieretti, M., Sutcliffe, J.S., et al. (1991). Identification of a gene (FMR-1) containing a CGG repeat coincident with a breakpoint cluster region exhibiting length variation in fragile X syndrome. Cell, 65, 905–914.CrossRefGoogle ScholarPubMed
Verma, M. (2012). Epigenome-Wide Association Studies (EWAS) in cancer. Curr. Genom., 13, 308–313.CrossRefGoogle Scholar
Wang, Y., Zhang, Y.L., Hennig, K., et al. (2013). Class I HDAC imaging using [(3)H]CI-994 autoradiography. Epigenetics, 8, 756–764.CrossRefGoogle Scholar
Weaver, I.C., Cervoni, N., Champagne, F.A., et al. (2004). Epigenetic programming by maternal behavior. Nature Neurosci., 7, 847–854.CrossRefGoogle ScholarPubMed
Xu, Z., Bolick, S.C., DeRoo, L.A., et al. (2013). Epigenome-wide association study of breast cancer using prospectively collected sister study samples. J. Natl Cancer Inst., 105, 694–700.CrossRefGoogle ScholarPubMed
Yamaguchi, S., Shen, L., Liu, Y., Sendler, D. and Zhang, Y. (2013). Role of Tet1 in erasure of genomic imprinting. Nature, 504, 460–464.CrossRefGoogle ScholarPubMed

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×