Hostname: page-component-76fb5796d-skm99 Total loading time: 0 Render date: 2024-04-25T15:12:44.667Z Has data issue: false hasContentIssue false

Polymorphic Variation in the Epigenetic Gene DNMT3B Modulates the Environmental Impact on Cognitive Ability: A Twin Study

Published online by Cambridge University Press:  15 April 2020

A. Córdova-Palomera
Affiliation:
Unitat d’Antropologia, Departament de Biologia Animal, Facultat de Biologia and Institut de Biomedicina (IBUB), Universitat de Barcelona, avenue Diagonal, 643, 08028Barcelona, Spain Centro de Investigaciones Biomédicas en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
M. Fatjó-Vilas
Affiliation:
Unitat d’Antropologia, Departament de Biologia Animal, Facultat de Biologia and Institut de Biomedicina (IBUB), Universitat de Barcelona, avenue Diagonal, 643, 08028Barcelona, Spain Centro de Investigaciones Biomédicas en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
O. Kebir
Affiliation:
Inserm, UMR 894, laboratoire de physiopathologie des maladies psychiatriques, centre de psychiatrie et neurosciences, université Paris-Descartes, PRES Paris Sorbonne Cité, 75014ParisFrance Service hospitalo-universitaire, faculté de médecine Paris-Descartes, hôpital Sainte-Anne, 75014Paris, France GDR3557-institut de psychiatrie, 75014ParisFrance
C. Gastó
Affiliation:
Centro de Investigaciones Biomédicas en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain Instituto de Investigaciones Biomédicas August Pi i Sunyer (IDIBAPS), Barcelona, Spain Departamento de Psiquiatría, Instituto Clínico de Neurociencias (ICN), Hospital Clínico, Barcelona, Spain
M.O. Krebs
Affiliation:
Inserm, UMR 894, laboratoire de physiopathologie des maladies psychiatriques, centre de psychiatrie et neurosciences, université Paris-Descartes, PRES Paris Sorbonne Cité, 75014ParisFrance Service hospitalo-universitaire, faculté de médecine Paris-Descartes, hôpital Sainte-Anne, 75014Paris, France GDR3557-institut de psychiatrie, 75014ParisFrance
L. Fañanás*
Affiliation:
Unitat d’Antropologia, Departament de Biologia Animal, Facultat de Biologia and Institut de Biomedicina (IBUB), Universitat de Barcelona, avenue Diagonal, 643, 08028Barcelona, Spain Centro de Investigaciones Biomédicas en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
*
*Corresponding author. Unitat d'Antropologia, Departament de Biologia Animal, Facultat de Biologia and Institut de Biomedicina (IBUB), Universitat de Barcelona, avenue Diagonal, 643, 08028 Barcelona, Spain. Tel.: +34 93 402 1461; fax: +34 93 403 5740. E-mail address:lfananas@ub.edu(L. Fanñanás).
Get access

Abstract

Background:

Though cognitive abilities in adulthood are largely influenced by individual genetic background, they have also been shown to be importantly influenced by environmental factors. Some of these influences are mediated by epigenetic mechanisms. Accordingly, polymorphic variants in the epigenetic gene DNMT3B have been linked to neurocognitive performance. Since monozygotic (MZ) twins may show larger or smaller intrapair phenotypic differences depending on whether their genetic background is more or less sensitive to environmental factors, a twin design was implemented to determine if particular polymorphisms in the DNMT3B gene may be linked to a better (worse) response to enriched (deprived) environmental factors.

Methods:

Applying the variability gene methodology in a sample of 54 healthy MZ twin pairs (108 individuals) with no lifetime history of psychopathology, two DNMT3B polymorphisms were analyzed in relation to their intrapair differences for either intellectual quotient (IQ) or working memory performance.

Results:

MZ twin pairs with the CC genotype for rs406193 SNP showed statistically significant larger intrapair differences in IQ than CT pairs.

Conclusions:

Results suggest that DNMT3B polymorphisms may explain variability in the IQ response to either enriched or impoverished environmental conditions. Accordingly, the applied methodology is shown as a potentially valuable tool for determining genetic markers of cognitive plasticity. Further research is needed to confirm this specific result and to expand on other putative genetic markers of environmental sensitivity.

Type
Original article
Copyright
Copyright © Elsevier Masson SAS 2014

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

Alemany, S., Goldberg, X., van Winkel, R., Gasto, C., Peralta, V., Fananas, L.. Childhood adversity and psychosis: examining whether the association is due to genetic confounding using a monozygotic twin differences approach. Eur Psychiatry 2013;28 :207212.CrossRefGoogle ScholarPubMed
Allis, C.D., Jenuwein, T., Reinberg, D.Epigenetics. Cold Spring Harbor, N.Y: Cold Spring Harbor Laboratory Press; 2007.Google Scholar
Ando, J., Ono, Y., Wright, M.J.. Genetic structure of spatial and verbal working memory. Behav Genet 2001;31 :615624.CrossRefGoogle ScholarPubMed
Bavelier, D., Levi, D.M., Li, R.W., Dan, Y., Hensch, T.K.. Removing brakes on adult brain plasticity: from molecular to behavioral interventions. J Neurosci 2010;30 :1496414971.CrossRefGoogle ScholarPubMed
Bellander, M., Brehmer, Y., Westerberg, H., Karlsson, S., Furth, D., Bergman, O., et al.Preliminary evidence that allelic variation in the LMX1A gene influences training-related working memory improvement. Neuropsychologia 2011;49 :19381942.CrossRefGoogle ScholarPubMed
Belsky, J., Jonassaint, C., Pluess, M., Stanton, M., Brummett, B., Williams, R.. Vulnerability genes or plasticity genes?. Mol Psychiatry 2009;14 :746754.Google ScholarPubMed
Benjamini, Y., Hochberg, Y.Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B 1995 289300.Google Scholar
Berg, K.. Variability gene effect on cholesterol at the Kidd blood group locus. Clin Genet 1988;33 :102107.CrossRefGoogle ScholarPubMed
Berg, K.Gene-environment interaction: variability gene concept. Genetic factors in coronary heart disease. Springer 1994;373383.Google Scholar
Bohacek, J., Farinelli, M., Mirante, O., Steiner, G., Gapp, K., Coiret, G., et al.Pathological brain plasticity and cognition in the offspring of males subjected to postnatal traumatic stress. Mol Psychiatry 2014.Google ScholarPubMed
Brans, R.G., Kahn, R.S., Schnack, H.G., van Baal, G.C., Posthuma, D., van Haren, N.E., et al.Brain plasticity and intellectual ability are influenced by shared genes. J Neurosci 2010;30 :55195524.CrossRefGoogle ScholarPubMed
Champely, S. pwr: basic functions for power analysis; 2012 [computer program. Version 1.1.1; 2012. Available from: http://CRAN.R-project.org/package=pwr].Google Scholar
Cohen, J.Statistical power analysis for the behavioral sciences, 2nd ed.Hillsdale, N.J: L. Erlbaum Associates; 1988.Google Scholar
Cook, R.J., Farewell, V.T.Multiplicity considerations in the design and analysis of clinical trials. J R Stat Soc Ser A 1996;93110.CrossRefGoogle Scholar
Coppede, F., Zitarosa, M.T., Migheli, F., Lo Gerfo, A., Bagnoli, S., Dardano, A., et al.DNMT3B promoter polymorphisms and risk of late onset Alzheimer's disease. Curr Alzheimer Res 2012;9 :550554.CrossRefGoogle ScholarPubMed
Coppede, F., Bosco, P., Tannorella, P., Romano, C., Antonucci, I., Stuppia, L., et al.DNMT3B promoter polymorphisms and maternal risk of birth of a child with Down syndrome. Hum Reprod 2013;28 :545550.CrossRefGoogle ScholarPubMed
Coppede, F., Grossi, E., Buscema, M., Migliore, L.. Application of artificial neural networks to investigate one-carbon metabolism in Alzheimer's disease and healthy matched individuals. PLoS One 2013;8 :e74012.CrossRefGoogle ScholarPubMed
Cordova-Palomera, A., Alemany, S., Fatjo-Vilas, M., Goldberg, X., Leza, J.C., Gonzalez-Pinto, A., et al.Birth weight, working memory and epigenetic signatures in IGF2 and related genes: a MZ Twin Study. PLoS One 2014;9 :e103639.CrossRefGoogle ScholarPubMed
Davies, G., Tenesa, A., Payton, A., Yang, J., Harris, S.E., Liewald, D., et al.Genome-wide association studies establish that human intelligence is highly heritable and polygenic. Mol Psychiatry 2011;16 :9961005.CrossRefGoogle ScholarPubMed
Deary, I.J., Spinath, F.M., Bates, T.C.. Genetics of intelligence. Eur J Hum Genet 2006;14 :690700.Google ScholarPubMed
Deary, I.J., Penke, L., Johnson, W.. The neuroscience of human intelligence differences. Nat Rev Neurosci 2010;11 :201211.CrossRefGoogle ScholarPubMed
Dukas, R.Evolutionary biology of animal cognition. Annu Rev Ecol Evol Syst 2004 347374.CrossRefGoogle Scholar
Feinberg, A.P.. Phenotypic plasticity and the epigenetics of human disease. Nature 2007;447 :433440.CrossRefGoogle ScholarPubMed
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 2005;79 :734746.CrossRefGoogle ScholarPubMed
First M.B.. In: Clinician SCID-I: structured clinical interview for DSM-IV axis I disorders. New York: American Psychiatric Press; 1997.Google Scholar
Genomes Project, C., Abecasis, G.R., Auton, A., Brooks, L.D., DePristo, M.A., Durbin, R.M., et al.An integrated map of genetic variation from 1092 human genomes. Nature 2012;491 :5665.Google Scholar
Glickman, M.E., Rao, S.R., Schultz, M.R.. False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies. J Clin Epidemiol 2014;67 :850857.CrossRefGoogle ScholarPubMed
Goldberg, X., Alemany, S., Rosa, A., Picchioni, M., Nenadic, I., Owens, S.F., et al.Substantial genetic link between iq and working memory: Implications for molecular genetic studies on schizophrenia. the european twin study of schizophrenia (EUTwinsS). Am J Med Genet B Neuropsychiatr Genet 2013;162 :413418.CrossRefGoogle Scholar
Goldberg, X., Fatjo-Vilas, M., Alemany, S., Nenadic, I., Gasto, C., Fananas, L.. Gene-environment interaction on cognition: a twin study of childhood maltreatment and COMT variability. J Psychiatr Res 2013;47 :989994.CrossRefGoogle ScholarPubMed
Graff, J., Mansuy, I.M.. Epigenetic codes in cognition and behaviour. Behav Brain Res 2008;192 :7087.CrossRefGoogle ScholarPubMed
Greenwood, P.M., Parasuraman, R.. Neuronal and cognitive plasticity: a neurocognitive framework for ameliorating cognitive aging. Front Aging Neurosci 2010;2 :150.CrossRefGoogle ScholarPubMed
Greenwood, T.A., Braff, D.L., Light, G.A., Cadenhead, K.S., Calkins, M.E., Dobie, D.J., et al.Initial heritability analyses of endophenotypic measures for schizophrenia: the consortium on the genetics of schizophrenia. Arch Gen Psychiatry 2007;64 :12421250.CrossRefGoogle Scholar
Guilherme, R., Drunat, S., Delezoide, A.L., Oury, J.F., Luton, D.. Zygosity and chorionicity in triplet pregnancies: new data. Hum Reprod 2009;24 :100105.CrossRefGoogle ScholarPubMed
Haggarty, P., Hoad, G., Harris, S.E., Starr, J.M., Fox, H.C., Deary, I.J., et al.Human intelligence and polymorphisms in the DNA methyltransferase genes involved in epigenetic marking. PLoS One 2010;5 :e11329.CrossRefGoogle ScholarPubMed
Haggarty, P., Hoad, G., Horgan, G.W., Campbell, D.M.. DNA methyltransferase candidate polymorphisms, imprinting methylation, and birth outcome. PLoS One 2013;8 :e68896.CrossRefGoogle ScholarPubMed
Hansen, R.S., Wijmenga, C., Luo, P., Stanek, A.M., Canfield, T.K., Weemaes, C.M., et al.The DNMT3B DNA methyltransferase gene is mutated in the ICF immunodeficiency syndrome. Proc Natl Acad Sci U S A 1999;96 :1441214417.CrossRefGoogle ScholarPubMed
Harrel, F. rms: regression modeling strategies; 2013 [computer program. Version 4.2-1; 2013. Available from: http://CRAN.R-project.org/package=rms].Google Scholar
Haworth, C.M., Wright, M.J., Luciano, M., Martin, N.G., de Geus, E.J., van Beijsterveldt, C.E., et al.The heritability of general cognitive ability increases linearly from childhood to young adulthood. Mol Psychiatry 2010;15 :11121120.CrossRefGoogle ScholarPubMed
Hong, E.J., West, A.E., Greenberg, M.E.. Transcriptional control of cognitive development. Curr Opin Neurobiol 2005;15 :2128.CrossRefGoogle ScholarPubMed
Jurkowska, R.Z., Jurkowski, T.P., Jeltsch, A.. Structure and function of mammalian DNA methyltransferases. Chembiochem 2011;12 :206222.CrossRefGoogle ScholarPubMed
Kaminsky, Z.A., Tang, T., Wang, S.C., Ptak, C., Oh, G.H., Wong, A.H., et al.DNA methylation profiles in monozygotic and dizygotic twins. Nat Genet 2009;41 :240245.Google ScholarPubMed
Kaprio, J.. Twins and the mystery of missing heritability: the contribution of gene-environment interactions. J Intern Med 2012;272 :440448.CrossRefGoogle ScholarPubMed
Klingberg, T.. Training and plasticity of working memory. Trends Cogn Sci 2010;14 :317324.CrossRefGoogle ScholarPubMed
Kramer, A.F., Willis, S.L.Cognitive plasticity and aging. Ross, B.H., editors. The psychology of learning and motivation San Diego, CA: Academic Press; 2003.Google Scholar
Kumar, S., Cheng, X., Klimasauskas, S., Mi, S., Posfai, J., Roberts, R.J., et al.The DNA (cytosine-5) methyltransferases. Nucleic Acids Res 1994;22 :110.CrossRefGoogle ScholarPubMed
Lamb, Y.N., Thompson, J.M., Murphy, R., Wall, C., Kirk, I.J., Morgan, A.R., et al.Perceived stress during pregnancy and the catechol-O-methyltransferase (COMT) rs165599 polymorphism impacts on childhood IQ. Cognition 2014;132 :461470.CrossRefGoogle ScholarPubMed
Lehto, K., Akkermann, K., Parik, J., Veidebaum, T., Harro, J.. Effect of COMT Val158Met polymorphism on personality traits and educational attainment in a longitudinal population representative study. Eur Psychiatry 2013;28 :492498.CrossRefGoogle Scholar
Lillard, A.S., Erisir, A.. Old dogs learning new tricks: neuroplasticity beyond the juvenile period. Dev Rev 2011;31 :207239.CrossRefGoogle ScholarPubMed
Liu, W., Jamshidian, M., Zhang, Y.. Multiple comparison of several linear regression models. J Am Statist Assoc 2004;99 :395403.CrossRefGoogle Scholar
Lovden, M., Backman, L., Lindenberger, U., Schaefer, S., Schmiedek, F.. A theoretical framework for the study of adult cognitive plasticity. Psychol Bull 2010;136 :659676.CrossRefGoogle Scholar
Luciano, M., Wright, M., Smith, G.A., Geffen, G.M., Geffen, L.B., Martin, N.G.. Genetic covariance among measures of information processing speed, working memory, and IQ. Behav Genet 2001;31 :581592.CrossRefGoogle ScholarPubMed
Lynn, R., Meisenberg, G.. National IQs calculated and validated for 108 nations. Intelligence 2010;38 :353360.CrossRefGoogle Scholar
MacDonald, J.L., Roskams, A.J.. Epigenetic regulation of nervous system development by DNA methylation and histone deacetylation. Prog Neurobiol 2009;88 :170183.CrossRefGoogle ScholarPubMed
Melby-Lervåg, M., Hulme, C.. Is working memory training effective? A meta-analytic review. Dev Psychol 2013;49 :270.CrossRefGoogle ScholarPubMed
Mercado, E.3rd.Neural and cognitive plasticity: from maps to minds. Psychol Bull 2008;134 :109137.CrossRefGoogle ScholarPubMed
Miller, C.A., Sweatt, J.D.. Covalent modification of DNA regulates memory formation. Neuron 2007;53 :857869.CrossRefGoogle ScholarPubMed
Murgatroyd, C., Spengler, D.. Genetic variation in the epigenetic machinery and mental health. Curr Psychiatry Rep 2012;14 :138149.CrossRefGoogle ScholarPubMed
Murphy, T.M., Mullins, N., Ryan, M., Foster, T., Kelly, C., McClelland, R., et al.Genetic variation in DNMT3B and increased global DNA methylation is associated with suicide attempts in psychiatric patients. Genes Brain Behav 2013;12 :125132.CrossRefGoogle ScholarPubMed
Nakagawa, S.. A farewell to Bonferroni: the problems of low statistical power and publication bias. Behav Ecol 2004;15 :10441045.CrossRefGoogle Scholar
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 1999;99 :247257.Google Scholar
Panizzutti, R., Hamilton, S.P., Vinogradov, S.. Genetic correlate of cognitive training response in schizophrenia. Neuropharmacol 2013;64 :264267.CrossRefGoogle Scholar
Perneczky, R., Alexopoulos, P., Wagenpfeil, S., Bickel, H., Kurz, A.. Head circumference, apolipoprotein E genotype and cognition in the Bavarian School Sisters Study. Eur Psychiatry 2012;27 :219222.CrossRefGoogle ScholarPubMed
Perneger, T.V.. What's wrong with Bonferroni adjustments. BMJ 1998;316 :12361238.CrossRefGoogle ScholarPubMed
Potter, C., McKay, J., Groom, A., Ford, D., Coneyworth, L., Mathers, J.C., et al.Influence of DNMT genotype on global and site specific DNA methylation patterns in neonates and pregnant women. PLoS One 8 2 2013 e76506.CrossRefGoogle ScholarPubMed
R Development Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2011.Google Scholar
Rahu, K., Rahu, M., Pullmann, H., Allik, J.. Effect of birth weight, maternal education and prenatal smoking on offspring intelligence at school age. Early Hum Dev 2010;86 :493497.CrossRefGoogle ScholarPubMed
Raznahan, A., Greenstein, D., Lee, N.R., Clasen, L.S., Giedd, J.N.. Prenatal growth in humans and postnatal brain maturation into late adolescence. Proc Natl Acad Sci U S A 2012;109 :1136611371.CrossRefGoogle ScholarPubMed
Redick, T.S., Shipstead, Z., Harrison, T.L., Hicks, K.L., Fried, D.E., Hambrick, D.Z., et al.No evidence of intelligence improvement after working memory training: a randomized, placebo-controlled study. J Exp Psychol Gen 2013;142 :359.CrossRefGoogle ScholarPubMed
Saffery, R., Morley, R., Foley, D.L.The utility of twins for epigenetic analysis. In: Michels, K.B., editors. Epigenet Epidemiol Dordrecht, Netherlands: Springer; 2012. p. 161183.CrossRefGoogle Scholar
Sattler, J.M.Assessment of children: cognitive applications, 4th ed.San Diego: J.M. Sattler; 2001.Google Scholar
Schlichting, C.D.. Origins of differentiation via phenotypic plasticity. Evol Dev 2003;5 :98105.CrossRefGoogle ScholarPubMed
Shipstead, Z., Redick, T.S., Engle, R.W.. Is working memory training effective?. Psychol Bull 2012;138 :628.CrossRefGoogle ScholarPubMed
Simons, C.J., van Winkel, R., Group. Intermediate phenotype analysis of patients, unaffected siblings, and healthy controls identifies VMAT2 as a candidate gene for psychotic disorder and neurocognition. Schizophr Bull 2013;39 :848856.CrossRefGoogle ScholarPubMed
Slagter, H.A.. Conventional working memory training may not improve intelligence. Trends Cogn Sci 2012;16 :582583.CrossRefGoogle Scholar
Soderqvist, S., Bergman Nutley, S., Peyrard-Janvid, M., Matsson, H., Humphreys, K., Kere, J., et al.Dopamine, working memory, and training induced plasticity: implications for developmental research. Dev Psychol 2012;48 :836843.CrossRefGoogle ScholarPubMed
Soderqvist, S., Matsson, H., Peyrard-Janvid, M., Kere, J., Klingberg, T.. Polymorphisms in the dopamine receptor 2 gene region influence improvements during working memory training in children and adolescents. J Cogn Neurosci 2014;26 :5462.CrossRefGoogle ScholarPubMed
Stromswold, K.. Why aren’t identical twins linguistically identical? Genetic, prenatal and postnatal factors. Cognition 2006;101 :333384.CrossRefGoogle ScholarPubMed
Sweatt, J.D.. Experience-dependent epigenetic modifications in the central nervous system. Biol Psychiatry 2009;65 :191197.CrossRefGoogle ScholarPubMed
Tan, Q.. Epigenetic epidemiology of complex diseases using twins. Med Epigenet 2013;1 :4651.CrossRefGoogle Scholar
Tan, Q., Christiansen, L., Thomassen, M., Kruse, T.A., Christensen, K.. Twins for epigenetic studies of human aging and development. Ageing Res Rev 2013;12 :182187.CrossRefGoogle ScholarPubMed
Warnes, G. Genetics: population genetics; 2013 [computer program. Version 1.3.8.1; 2013. Available from: http://CRAN.R-project.org/package=genetics].Google Scholar
Wechsler, D., Cordero Pando, A., Yela Granizo, M., Zimmerman, I.L., Woo-Sam, J.M., Glasser, A.J.WAIS escala de inteligencia de Wechsler para adultos, 12th ed.Barcelona: TEA Ediciones; 1997.Google Scholar
Werner, H., Leroith, D.Insulin and insulin-like growth factor receptors in the brain: physiological and pathological aspects. Eur Neuropsychopharmacol 2014.CrossRefGoogle ScholarPubMed
West-Eberhard, M.J.. Phenotypic plasticity and the origins of diversity. Annu Rev Ecol Evol Syst 249–78 1989.CrossRefGoogle Scholar
Wheeler, B. lmPerm: permutation tests for linear models; 2010 [computer program. Version 1.1-2; 2010. Available from: http://CRAN.R-project.org/package=lmPerm].Google Scholar
Zhang, C., Fang, Y., Xie, B., Cheng, W., Du, Y., Wang, D., et al.DNA methyltransferase 3B gene increases risk of early onset schizophrenia. Neurosci Lett 2009;462 :308311.CrossRefGoogle ScholarPubMed
Submit a response

Comments

No Comments have been published for this article.