Exploring the influence of the DRD2 gene on mathematical ability: perspectives of gene association and gene-environment interaction.
DRD2 gene
Gene-environment interaction
Haplotype
Mathematical ability
Journal
BMC psychology
ISSN: 2050-7283
Titre abrégé: BMC Psychol
Pays: England
ID NLM: 101627676
Informations de publication
Date de publication:
18 Oct 2024
18 Oct 2024
Historique:
received:
28
04
2024
accepted:
11
09
2024
medline:
19
10
2024
pubmed:
19
10
2024
entrez:
18
10
2024
Statut:
epublish
Résumé
Mathematical ability is influenced by genes and environment. This study focused on the effect of DRD2, a candidate gene for working memory, on mathematical ability. The results in child participants revealed associations between the DRD2 gene and mathematical ability. It was found that individual's mathematical ability was influenced by Single Nucleotide Polymorphisms (SNPs) in DRD2, both in the form of haplotypes and in the way of interaction with parental education. These findings suggest that dopaminergic genes are linked to mathematical ability. This study provides evidence for the genetic basis of mathematical ability and offers guidance for personalized intervention in mathematical education.
Identifiants
pubmed: 39425204
doi: 10.1186/s40359-024-01997-y
pii: 10.1186/s40359-024-01997-y
doi:
Substances chimiques
Receptors, Dopamine D2
0
DRD2 protein, human
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
572Subventions
Organisme : Fund for Humanities and Social Sciences Research of the Ministry of Education of China
ID : 23XJC740010
Organisme : Fund for Natural Science Basic Research Program of Shaanxi Province
ID : 2023-JC-YB-703
Informations de copyright
© 2024. The Author(s).
Références
Docherty SJ, Davis OSP, Kovas Y, Meaburn EL, Dale PS, Petrill SA, Schalkwyk LC, Plomin R. A genome-wide association study identifies multiple loci associated with mathematics ability and disability. Genes Brain Behav. 2010;9(2):234–47.
pubmed: 20039944
doi: 10.1111/j.1601-183X.2009.00553.x
Zhang L, Wang Z, Zhu Z, Yang Q, Cheng C, Zhao S, Liu C, Zhao J. A genome-wide association study identified new variants associated with mathematical abilities in Chinese children. Genes Brain Behav. 2023;22(2):e12843.
pubmed: 36811322
pmcid: 10067424
doi: 10.1111/gbb.12843
Mascheretti S, Riva V, Giorda R, Beri S, Lanzoni LFE, Cellino MR, Marino C. KIAA0319 and ROBO1: evidence on association with reading and pleiotropic effects on language and mathematics abilities in developmental dyslexia. J Hum Genet. 2014;59(4):189–97.
pubmed: 24430574
doi: 10.1038/jhg.2013.141
D’Esposito M, Postle BR. The cognitive neuroscience of working memory. Ann Rev Psychol. 2015;66(1):115–42.
doi: 10.1146/annurev-psych-010814-015031
Raghubar KP, Barnes MA, Hecht SA. Working memory and mathematics: a review of developmental, individual difference, and cognitive approaches. Learn Individual Differences. 2010;20(2):110–22.
doi: 10.1016/j.lindif.2009.10.005
Judd N, Klingberg T. Training spatial cognition enhances mathematical learning in a randomized study of 17,000 children. Nat Hum Behav. 2021;5(11):1548–54.
pubmed: 34017098
doi: 10.1038/s41562-021-01118-4
Fuchs LS, Schumacher RF, Sterba SK, Long J, Namkung J, Malone A, Hamlett CL, Jordan NC, Gersten R, Siegler RS, et al. Does working memory moderate the effects of fraction intervention? An aptitude–treatment interaction. J Educ Psychol. 2014;106(2):499–514.
doi: 10.1037/a0034341
Peng P, Namkung J, Barnes M, Sun C. A meta-analysis of mathematics and working memory: moderating effects of working memory domain, type of mathematics skill, and sample characteristics. J Educ Psychol. 2016;108(4):455–73.
doi: 10.1037/edu0000079
Störmer VS, Passow S, Biesenack J, Li S-C. Dopaminergic and cholinergic modulations of visual-spatial attention and working memory: insights from molecular genetic research and implications for adult cognitive development. Dev Psychol. 2012;48(3):875–89.
pubmed: 22103306
doi: 10.1037/a0026198
Quintana C, Beaulieu J-M. A fresh look at cortical dopamine D2 receptor expressing neurons. Pharmacol Res. 2019;139:440–5.
pubmed: 30528973
doi: 10.1016/j.phrs.2018.12.001
Reuter M, Peters K, Schroeter K, Koebke W, Lenardon D, Bloch B, Hennig J. The influence of the dopaminergic system on cognitive functioning: a molecular genetic approach. Behav Brain Res. 2005;164(1):93–9.
pubmed: 16026865
doi: 10.1016/j.bbr.2005.06.002
Xu H, Kellendonk CB, Simpson EH, Keilp JG, Bruder GE, Polan HJ, Kandel ER, Gilliam TC. DRD2 C957T polymorphism interacts with the COMT Val158Met polymorphism in human working memory ability. Schizophr Res. 2007;90(1):104–7.
pubmed: 17113268
doi: 10.1016/j.schres.2006.10.001
Colzato LS, Steenbergen L, Sellaro R, Stock A-K, Arning L, Beste C. Effects of l-Tyrosine on working memory and inhibitory control are determined by DRD2 genotypes: a randomized controlled trial. Cortex. 2016;82:217–24.
pubmed: 27403851
doi: 10.1016/j.cortex.2016.06.010
Kellendonk C, Simpson EH, Polan HJ, Malleret G, Vronskaya S, Winiger V, Moore H, Kandel ER. Transient and selective overexpression of dopamine D2 receptors in the striatum causes persistent abnormalities in prefrontal cortex functioning. Neuron. 2006;49(4):603–15.
pubmed: 16476668
doi: 10.1016/j.neuron.2006.01.023
Zhang Y, Bertolino A, Fazio L, Blasi G, Rampino A, Romano R, Lee M-LT, Xiao T, Papp A, Wang D, et al. Polymorphisms in human dopamine D2 receptor gene affect gene expression, splicing, and neuronal activity during working memory. Proc Natl Acad Sci. 2007;104(51):20552–7.
pubmed: 18077373
pmcid: 2154469
doi: 10.1073/pnas.0707106104
Beaver KM, DeLisi M, Vaughn MG, Wright JP. Association between the A1 allele of the DRD2 gene and reduced verbal abilities in adolescence and early adulthood. J Neural Transm. 2010;117(7):827–30.
pubmed: 20532925
doi: 10.1007/s00702-010-0421-8
Eicher JD, Powers NR, Cho K, Miller LL, Mueller KL, Ring SM, Tomblin JB, Gruen JR. Associations of prenatal nicotine exposure and the dopamine related genes ANKK1 and DRD2 to verbal language. PLoS ONE. 2013;8(5):e63762.
pubmed: 23691092
pmcid: 3655151
doi: 10.1371/journal.pone.0063762
Ramsay H, Barnett JH, Miettunen J, Mukkala S, Mäki P, Liuhanen J, Murray GK, Jarvelin M-R, Ollila H, Paunio T, et al. Association between dopamine receptor D2 (DRD2) variations rs6277 and rs1800497 and cognitive performance according to risk type for psychosis: a nested case control study in a Finnish population sample. PLoS ONE. 2015;10(6):e0127602.
pubmed: 26114663
pmcid: 4482687
doi: 10.1371/journal.pone.0127602
Docherty SJ, Kovas Y, Plomin R. Gene-environment interaction in the etiology of mathematical ability using SNP sets. Behav Genet. 2011;41(1):141–54.
pubmed: 20978832
doi: 10.1007/s10519-010-9405-6
Petrill SA, Kovas Y, Hart SA, Thompson LA, Plomin R. The genetic and environmental etiology of high math performance in 10-year-old twins. Behav Genet. 2009;39(4):371–9.
pubmed: 19247827
pmcid: 2913421
doi: 10.1007/s10519-009-9258-z
Pani L, Porcella A, Gessa GL. The role of stress in the pathophysiology of the dopaminergic system. Mol Psychiatry. 2000;5(1):14–21.
pubmed: 10673764
doi: 10.1038/sj.mp.4000589
Aumann TD, Tomas D, Horne MK. Environmental and behavioral modulation of the number of substantia nigra dopamine neurons in adult mice. Brain Behav. 2013;3(6):617–25.
pubmed: 24363965
pmcid: 3868167
doi: 10.1002/brb3.163
Andrews Espy K, Clark CAC, Volk A, Vrantsidis DM, Wakschlag LS, Wiebe SA. Exploring the interplay of dopaminergic genotype and parental behavior in relation to executive function in early childhood. Dev Psychopathol. 2023;35(3):1147–58.
pubmed: 34779374
doi: 10.1017/S0954579421001061
Vrantsidis DM, Wuest V, Wiebe SA. Differential relations of parental behavior to children’s early executive function as a function of child genotype: a systematic review. Clin Child Fam Psychol Rev. 2022;25(3):435–70.
pubmed: 35195834
doi: 10.1007/s10567-022-00387-3
Kallitsoglou A. Inattention, hyperactivity and low parental education in children with conduct problems and poor reading skills. J Res Special Educational Needs. 2014;14(4):239–47.
doi: 10.1111/1471-3802.12006
Rindermann H, Michou CD, Thompson J. Children’s writing ability: effects of parent’s education, mental speed and intelligence. Learn Individual Differences. 2011;21(5):562–8.
doi: 10.1016/j.lindif.2011.07.010
Davis-Kean PE. The influence of parent education and family income on child achievement: the indirect role of parental expectations and the home environment. 2005;19:294–304.
Tooley UA, Bassett DS, Mackey AP. Environmental influences on the pace of brain development. Nat Rev Neurosci. 2021;22(6):372–84.
pubmed: 33911229
pmcid: 8081006
doi: 10.1038/s41583-021-00457-5
Friend A, DeFries JC, Olson RK. Parental education moderates genetic influences on reading disability. Psychol Sci. 2008;19(11):1124–30.
pubmed: 19076484
doi: 10.1111/j.1467-9280.2008.02213.x
Keltikangas-Järvinen L, Jokela M, Hintsanen M, Salo J, Hintsa T, Alatupa S, Lehtimäki T. Does genetic background moderate the association between parental education and school achievement? Genes Brain Behav. 2010;9(3):318–24.
pubmed: 20039947
doi: 10.1111/j.1601-183X.2009.00561.x
Zhao J, Yang Q, Cheng C, Wang Z. Cumulative genetic score of KIAA0319 affects reading ability in Chinese children: moderation by parental education and mediation by rapid automatized naming. Behav Brain Funct. 2023;19(1):10.
pubmed: 37259151
pmcid: 10234066
doi: 10.1186/s12993-023-00212-z
Yang Q, Cheng C, Wang Z, Zhang X, Zhao J. Interaction between risk single-nucleotide polymorphisms of developmental dyslexia and parental education on reading ability: evidence for differential susceptibility theory. In: Behavioral Sciences. vol. 14; 2024.
Docherty SJ, Kovas Y, Petrill SA, Plomin R. Generalist genes analysis of DNA markers associated with mathematical ability and disability reveals shared influence across ages and abilities. BMC Genet. 2010;11(1):61.
pubmed: 20602751
pmcid: 2909150
doi: 10.1186/1471-2156-11-61
Manuck SB, McCaffery JM. Gene-environment interaction. Annu Rev Psychol. 2014;65:41–70.
Dick DM, Latendresse SJ, Lansford JE, Budde JP, Goate A, Dodge KA, Pettit GS, Bates JE. Role of GABRA2 in trajectories of externalizing behavior across development and evidence of moderation by parental monitoring. Arch Gen Psychiatry. 2009;66(6):649–57.
pubmed: 19487630
pmcid: 2750080
doi: 10.1001/archgenpsychiatry.2009.48
Latendresse SJ, Bates JE, Goodnight JA, Lansford JE, Budde JP, Goate A, Dodge KA, Pettit GS, Dick DM. Differential susceptibility to adolescent externalizing trajectories: examining the interplay between CHRM2 and peer group antisocial behavior. Child Dev. 2011;82(6):1797–814.
pubmed: 21883161
pmcid: 3218245
doi: 10.1111/j.1467-8624.2011.01640.x
Mascheretti S, Trezzi V, Giorda R, Boivin M, Plourde V, Vitaro F, Brendgen M, Dionne G, Marino C. Complex effects of dyslexia risk factors account for ADHD traits: evidence from two independent samples. J Child Psychol Psychiatry. 2017;58(1):75–82.
pubmed: 27501527
doi: 10.1111/jcpp.12612
Su M, Wang J, Maurer U, Zhang Y, Li J, McBride C, Tardif T, Liu Y, Shu H. Gene–environment interaction on neural mechanisms of orthographic processing in Chinese children. J Neurolinguistics. 2015;33:172–86.
pubmed: 26294811
doi: 10.1016/j.jneuroling.2014.09.007
Widaman KF, Helm JL, Castro-Schilo L, Pluess M, Stallings MC, Belsky J. Distinguishing ordinal and disordinal interactions. In., vol. 17. US: American Psychological Association; 2012: 615–622.
Ross CE, Mirowsky J. The interaction of personal and parental education on health. Soc Sci Med. 2011;72(4):591–9.
pubmed: 21227556
doi: 10.1016/j.socscimed.2010.11.028
Noble KG, Houston SM, Brito NH, Bartsch H, Kan E, Kuperman JM, Akshoomoff N, Amaral DG, Bloss CS, Libiger O, et al. Family income, parental education and brain structure in children and adolescents. Nat Neurosci. 2015;18(5):773–8.
pubmed: 25821911
pmcid: 4414816
doi: 10.1038/nn.3983
Li L. Study on the developmental level of pupil’s basic mathematical ability [D]. Huazhong University of Science and Technology; 2005.
Haffner J. HRT 1–4: Heidelberger Rechentest; Erfassung mathematischer Basiskompetenzen Im Grundschulalter. Hogrefe; 2005.
Gabriel SB, Schaffner SF, Nguyen H, Moore JM, Roy J, Blumenstiel B, Higgins J, DeFelice M, Lochner A, Faggart M, et al. The structure of haplotype blocks in the human genome. Science. 2002;296(5576):2225–9.
pubmed: 12029063
doi: 10.1126/science.1069424
Botstein D, Risch N. Discovering genotypes underlying human phenotypes: past successes for Mendelian disease, future approaches for complex disease. Nat Genet. 2003;33(3):228–37.
pubmed: 12610532
doi: 10.1038/ng1090
Stranger BE, Stahl EA, Raj T. Progress and promise of genome-wide association studies for human complex trait genetics. Genetics. 2011;187(2):367–83.
pubmed: 21115973
pmcid: 3030483
doi: 10.1534/genetics.110.120907
Lewis CR, Henderson-Smith A, Breitenstein RS, Sowards HA, Piras IS, Huentelman MJ, Doane LD, Lemery-Chalfant K. Dopaminergic gene methylation is associated with cognitive performance in a childhood monozygotic twin study. Epigenetics. 2019;14(3):310–23.
pubmed: 30806146
pmcid: 6557595
doi: 10.1080/15592294.2019.1583032
Xu H, Zhang Z, Zhao Z. Parental socioeconomic status and children’s cognitive ability in China. J Asian Econ. 2023;84:101579.
doi: 10.1016/j.asieco.2022.101579
Qi D, Wu Y. Family’s social economic status and child educational outcomes in China: the mediating effects of parenting practices and children’s learning attitudes. Child Youth Serv Rev. 2020;118:105387.
doi: 10.1016/j.childyouth.2020.105387
Bernardi F. Compensatory advantage as a mechanism of educational inequality:a regression discontinuity based on month of birth. Sociol Educ. 2014;87(2):74–88.
doi: 10.1177/0038040714524258
Stienstra K, Knigge A, Maas I. Gene-environment interaction analysis of school quality and educational inequality. npj Sci Learn. 2024;9(1):14.
pubmed: 38429323
pmcid: 10907386
doi: 10.1038/s41539-024-00225-x
Cheesman R, Borgen NT, Lyngstad TH, Eilertsen EM, Ayorech Z, Torvik FA, Andreassen OA, Zachrisson HD, Ystrom E. A population-wide gene-environment interaction study on how genes, schools, and residential areas shape achievement. npj Sci Learn. 2022;7(1):29.
pubmed: 36302785
pmcid: 9613652
doi: 10.1038/s41539-022-00145-8
Haworth CMA, Meaburn EL, Harlaar N, Plomin R. Reading and generalist genes. Mind Brain Educ. 2007;1(4):173–80.
pubmed: 20383260
pmcid: 2847194
doi: 10.1111/j.1751-228X.2007.00018.x