Skip to main content
SpringerLink
Log in

Genetic Mechanisms of Cognitive Development

  • REVIEWS AND THEORETICAL ARTICLES
  • Published:
Russian Journal of Genetics Aims and scope Submit manuscript

Abstract

The results of large-scale meta-analyses of GWAS and genetic association studies demonstrated the role of allelic variants of a large number of genes in the development of cognitive abilities. Many of the identified genes are expressed in the brain and are involved in the pathogenesis of nervous system diseases. It has been shown that the summarized genetic effect for various cognitive abilities is no more than 50%. For certain genes, such as BDNF, DRD2, FNBP1L, PDE1C, PDE4B, and PDE4D, related to the regulation of neurogenesis and synaptic plasticity, associations with specific cognitive abilities were revealed. We assume the prospect of using the obtained results for the targeted effect in order to improve human cognitive abilities. This review describes DNA methylation, histone acetylation, expression of specific noncoding RNAs during brain functioning, and the development of individual differences in cognitive abilities. The revealed epigenetic mechanisms suggest the methods of reversible correction of cognitive functioning both in nonclinical forms and pathological states.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

REFERENCES

  1. Medaglia, J.D., Lynall, M.E., and Bassett, D.S., Cognitive network neuroscience, J. Cognit. Neurosci., 2015, vol. 27, pp. 1471—1491. https://doi.org/10.1162/jocn_a_00810

    Article  Google Scholar 

  2. Zabaneh, D., Krapohl, E., Gaspar, H.A., et al., A genome-wide association study for extremely high intelligence, Mol. Psychiatry, 2018, vol. 23, pp. 1226—1232. https://doi.org/10.1038/mp.2017.121

    Article  CAS  PubMed  Google Scholar 

  3. Benyamin, B., Pourcain, B., Davis, O.S., et al., Childhood intelligence is heritable, highly polygenic and associated with FNBP1L, Mol. Psychiatry, 2014, vol. 19, pp. 253—258.

    Article  CAS  PubMed  Google Scholar 

  4. Junkiert-Czarnecka, A. and Haus, O., Genetical background of intelligence, Postepy Hig. Med. Dosw., 2016, vol. 70, pp. 590—598.

    Article  Google Scholar 

  5. Tucker-Drob, E.M. and Briley, D.A., Continuity of genetic and environmental influences on cognition across the life span: a meta-analysis of longitudinal twin and adoption studies, Psychol. Bull., 2014, vol. 140, pp. 949—979. https://doi.org/10.1037/a0035893

    Article  PubMed  PubMed Central  Google Scholar 

  6. Davis, O.S., Band, G., Pirinen, M., et al., The correlation between reading and mathematics ability at age twelve has a substantial genetic component, Nat. Commun., 2014, vol. 5, p. 4204. https://doi.org/10.1038/ncomms5204

    Article  CAS  PubMed  Google Scholar 

  7. Tosto, M.G., Garon-Carrier, G., Gross, S., et al., The nature of the association between number line and mathematical performance: an international twin study, Br. J. Educ. Psychol., 2018, vol. 11. https://doi.org/10.11111/bjep.12259

  8. Goldberg, T.E. and Weinberger, D.R., Genes and the parsing of cognitive processes, Trends Cognit. Sci., 2004, vol. 8, no. 7, pp. 325—335.

    Article  Google Scholar 

  9. Davies, G., Marioni, R.E., Liewald, D.C., et al., Genome-wide association study of cognitive functions and educational attainment in UK Biobank (N = 112 151), Mol. Psychiatry, 2016, vol. 21, pp. 758—767.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Kleefstra, T., Schenck, A., Kramer, J.M., and van Bokhoven, H., The genetics of cognitive epigenetics, Neuropharmacology, 2014, vol. 80, pp. 83—94. https://doi.org/10.1016/j.neuropharm.2013.12.025

    Article  CAS  PubMed  Google Scholar 

  11. Plomin, R. and Kovas, Y., Generalist genes and learning disabilities, Psychol. Bull., 2005, vol. 131, pp. 592—617.

    Article  PubMed  Google Scholar 

  12. Chow, B.W., Ho, C.S., Wong, S.W., et al., Generalist genes and cognitive abilities in Chinese twins, Dev. Sci., 2013, vol. 16, pp. 260—268. https://doi.org/10.1111/desc.12022

    Article  PubMed  PubMed Central  Google Scholar 

  13. Gurney, M.E., Genetic association of phosphodiesterases with human cognitive performance, Front. Mol. Neurosci., 2019, vol. 12, p. 22. https://doi.org/10.3389/fnmol.2019.00022

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Lee, J.J., Wedow, R., Okbay, A., et al., Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals, Nat. Genet., 2018, vol. 50, pp. 1112—1121.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Owens, M., Goodyer, I.M., and Wilkinson, P., 5-HTTLPR and early childhood adversities moderate cognitive and emotional processing in adolescence, PLoS One, 2012, vol. 7, no. 11. e48482. https://doi.org/10.1371/journal.pone.0048482

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Ibrahim-Verbaas, C.A., Bressler, J., Debette, S., et al., GWAS for executive function and processing speed suggests involvement of the CADM2 gene, Mol. Psychiatry, 2016, vol. 21, pp. 189—197. https://doi.org/10.1038/mp.2015.37

    Article  CAS  PubMed  Google Scholar 

  17. Davies, G., Tenesa, A., Payton, A., et al., Genome-wide association studies establish that human intelligence is highly heritable and polygenic, Mol. Psychiatry, 2011, vol. 16, pp. 996—1005. https://doi.org/10.1038/mp.2011.85

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Debette, S., Ibrahim Verbaas, C.A., Bressler, J., et al., Genome-wide studies of verbal declarative memory in nondemented older people: the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, Biol. Psychiatry, 2015, vol. 77, pp. 749—763. https://doi.org/10.1016/j.biopsych.2014.08.027

    Article  PubMed  Google Scholar 

  19. Sasayama, D., Hori, H., Teraishi, T., et al., Association of cognitive performance with interleukin-6 receptor Asp358Ala polymorphism in healthy adults, J. Neural Transm. (Vienna), 2012, vol. 119, pp. 313—318. https://doi.org/10.1007/s00702-011-0709-3

    Article  CAS  PubMed  Google Scholar 

  20. Crabtree, G.R., Our fragile intellect. Part I, Trends Genet., 2013, vol. 29, no. 1, pp. 1—3. https://doi.org/10.1016/j.tig.2012.10.002

    Article  CAS  PubMed  Google Scholar 

  21. Okbay, A., Beauchamp, J.P., Fontana, M.A., et al., Genome-wide association study identifies 74 loci associated with educational attainment, Nature, 2016, vol. 533, pp. 539—542. https://doi.org/10.1038/nature17671

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Sniekers, S., Stringer, S., and Watanabe, K., Genome-wide association meta-analysis of 78 308 individuals identifies new loci and genes influencing human intelligence, Nat. Genet., 2017, vol. 49, pp. 1107—1112. https://doi.org/10.1038/ng.3869

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Lam, M., Trampush, J.W., Yu, J., et al., Large-scale cognitive GWAS meta-analysis reveals tissue-specific neural expression and potential nootropic drug targets, Cell Rep., 2017, vol. 21, pp. 2597—2613. https://doi.org/10.1016/j.celrep.2017.11.028

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Davies, G., Armstrong, N., Bis, J.C., et al., Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N = 53 949), Mol. Psychiatry, 2015, vol. 20, pp. 183—192. https://doi.org/10.1038/mp.2014.188

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Davies, G., Lam, M., Harris, S.E., et al., Study of 300 486 individuals identifies 148 independent genetic loci influencing general cognitive function, Nat. Commun., 2018, vol. 9, p. 2098. https://doi.org/10.1038/s41467-018-04362-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. De Sanctis, C., Bellenchi, G.C., and Viggiano, D., A meta-analytic approach to genes that are associated with impaired and elevated spatial memory performance, Psychiatry Res., 2018, vol. 261, pp. 508—516. https://doi.org/10.1016/j.psychres.2018.01.036

    Article  PubMed  Google Scholar 

  27. Rietveld, C.A., Esko, T., Davies, G., et al., Common genetic variants associated with cognitive performance identified using the proxy-phenotype method, Proc. Natl. Acad. Sci. U.S.A., 2014, vol. 111, pp. 13790—13794. https://doi.org/10.1073/pnas.1404623111

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Trampush, J.W., Lencz, T., Knowles, E., et al., Independent evidence for an association between general cognitive ability and a genetic locus for educational attainment, Am. J. Med. Genet.,Part B, 2015, vol. 168B, pp. 363—373. https://doi.org/10.1002/ajmg.b.32319

    Article  Google Scholar 

  29. Trampush, J.W., Yang, M.L., Yu, J., et al., GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium, Mol. Psychiatry, 2017, vol. 22, pp. 336—345. https://doi.org/10.1038/mp.2016.244

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Enders, C.K., Analyzing longitudinal data with missing values, Rehabil. Psychol., 2011, vol. 56, no. 4, pp. 267—288. https://doi.org/10.1037/a0025579

    Article  PubMed  Google Scholar 

  31. Yang, Y., Wang, L., Sun, X., et al., The longitude study on the mental development of congenital hearing-impaired infants and toddlers, Zhonghua Er. Bi. Yan Hou Tou Jing Wai Ke Za Zhi., 2015, vol. 50, no. 10, pp. 799—804.

    PubMed  Google Scholar 

  32. Bergen, S.E., Gardner, C.O., and Kendler, K.S., Age-related changes in heritability of behavioral phenotypes over adolescence and young adulthood: a meta-analysis, Twin Res. Hum. Genet., 2007, vol. 10, no. 3, pp. 423—433.

    Article  PubMed  Google Scholar 

  33. Haworth, C.M., Wright, M.J., Luciano, M., et al., The heritability of general cognitive ability increases linearly from childhood to young adulthood, Mol. Psychiatry, 2010, vol. 15, pp. 1112—1120. https://doi.org/10.1038/mp.2009.55

    Article  CAS  PubMed  Google Scholar 

  34. Briley, D.A. and Tucker-Drob, E.M., Explaining the increasing heritability of cognitive ability across development: a meta-analysis of longitudinal twin and adoption studies, Psychol. Sci., 2013, vol. 24, pp. 1704—1713. https://doi.org/10.1177/0956797613478618

    Article  PubMed  Google Scholar 

  35. Ho, V., Zainal, N.H., Lim, L., et al., Voluntary cognitive screening: characteristics of participants in an Asian setting, Clin. Interventions Aging, 2015, vol. 10, pp. 771—780. https://doi.org/10.2147/CIA.S73563

    Article  Google Scholar 

  36. Virta, J.J., Heikkila, K., Perola, M., et al., Midlife sleep characteristics associated with late life cognitive function, Sleep, 2013, vol. 36, no. 10, pp. 1533—1541. https://doi.org/10.5665/sleep.3052

    Article  PubMed  PubMed Central  Google Scholar 

  37. Perna, L., Mons, U., Kliegel, M., and Brenner, H., Serum 25-hydroxyvitamin D and cognitive decline: a longitudinal study among non-demented older adults, Dementia Geriatr. Cognit. Disord., 2014, vol. 38, pp. 254—263. https://doi.org/10.1159/000362870

    Article  CAS  Google Scholar 

  38. Crichton, G.E., Elias, M.F., Davey, A., and Alkerwi, A., Cardiovascular health and cognitive function: the Maine-Syracuse Longitudinal Study, PLoS One, 2014, vol. 9, no. 3. e89317. https://doi.org/10.1371/journal.pone.0089317

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Arfanakis, K., Wilson, R.S., Barth, C.M., et al., Cognitive activity, cognitive function, and brain diffusion characteristics in old age, Brain Imaging Behav., 2016, vol. 10, no. 2, pp. 455—463. https://doi.org/10.1007/s11682-015-9405-5

    Article  PubMed  PubMed Central  Google Scholar 

  40. Chu, D.C., Fox, K.R., Chen, L.J., and Ku, P.W., Components of late-life exercise and cognitive function: an 8-year longitudinal study, Prev. Sci., 2015, vol. 16, no. 4, pp. 568—577. https://doi.org/10.1007/s11121-014-0509-8

    Article  PubMed  Google Scholar 

  41. Fu, C., Li, Z., and Mao, Z., Association between social activities and cognitive function among the elderly in China: a cross-sectional study, Int. J. Environ. Res. Publ. Health, 2018, vol. 15, no. 2. pii: E231. https://doi.org/10.3390/ijerph15020231

    Article  Google Scholar 

  42. Gow, A., Avlund, K., and Mortensen, E.L., Occupational characteristics and cognitive aging in the Glostrup 1914 Cohort, J. Gerontol.,Ser. B, 2014, vol. 69, no. 2, pp. 228—236. https://doi.org/10.1093/geronb/gbs115

    Article  Google Scholar 

  43. Das, D., Tan, X., Bielak, A.A., et al., Cognitive ability, intraindividual variability, and common genetic variants of catechol-O-methyltransferase and brain-derived neurotorophic factor: a longitudinal study in a population-based sample of older adults, Psychol. Aging, 2014, vol. 29, no. 2, pp. 393—403. https://doi.org/10.1037/a0035702

    Article  PubMed  Google Scholar 

  44. Trompet, S., de Craen, A.J., Jukema, J.W., et al., Variation in the CBP gene involved in epigenetic control associated with cognitive function, Neurobiol. Aging, 2011, vol. 32, no. 3, p. 549. e1—8. https://doi.org/10.1016/j.neurobiolaging.2009.12.019

  45. Porter, T., Burnham, S.C., Dore, V., et al., KIBRA is associated with accelerated cognitive decline and hippocampal atrophy in APOE ε4-positive cognitively normal adults with high Aβ-amyloid burden, Sci. Rep., 2018, vol. 8, no. 1, p. 2034. https://doi.org/10.1038/s41598-018-20513-y

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Beydoun, M.A., Ding, E.L., Beydoun, H.A., et al., Vitamin D receptor and megalin gene polymorphisms and their associations with longitudinal cognitive change in US adults, Am. J. Clin. Nutr., 2012, vol. 95, no. 1, pp. 163—178. https://doi.org/10.3945/ajcn.111.017137

    Article  CAS  PubMed  Google Scholar 

  47. Bradburn, S., Sarginson, J., and Murgaroyd, C.A., Association of peripheral interleukin-6 with global cognitive decline in non-demented adults: a meta-analysis of prospective studies, Front. Aging Neurosci., 2018, vol. 9, p. 438. https://doi.org/10.3389/fnagi.2017.00438

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Wentz, L.M., Eldred, J.D., Henry, M.D., and Berry-Caban, C.S., Clinical relevance of optimizing vitamin D status in soldiers to enhance physical and cognitive performance, J. Spec. Oper. Med., 2014, vol. 14, pp. 58—66.

    PubMed  Google Scholar 

  49. Nygaard, E., Moe, V., Slinning, K., and Walhovd, K.B., Longitudinal cognitive development of children born to mothers with opioid and polysubstance use, Pediatr. Res., 2015, vol. 78, pp. 330—335. https://doi.org/10.1038/pr.2015.95

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Davis, E.P. and Sandman, C.A., The timing of prenatal exposure to maternal cortisol and psychosocial stress is associated with human infant cognitive development, Child. Dev., 2010, vol. 81, pp. 131—148. https://doi.org/10.1111/j.1467-8624.2009.01385.x

    Article  PubMed  PubMed Central  Google Scholar 

  51. Cao-Lei, L., Elgbeili, G., Massart, R., et al., Pregnant women’s cognitive appraisal of a natural disaster affects DNA methylation in their children 13 years later: Project Ice Storm, Transl. Psychiatry, 2015, vol. 5. e515. https://doi.org/10.1038/tp.2015.13

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Wong, C.C., Caspi, A., Williams, B., et al., A longitudinal study of epigenetic variation in twins, Epigenetics, 2010, vol. 5, pp. 516—526.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Harada, C.N., Natelson Love, M.C., and Triebel, K.L., Normal cognitive aging, Clin. Geriatr. Med., 2013, vol. 29, no. 4, pp. 737—752. https://doi.org/10.1016/j.cger.2013.07.002

    Article  PubMed  PubMed Central  Google Scholar 

  54. Xu, X., DNA methylation and cognitive aging, Oncotarget, 2015, vol. 6, no. 16, pp. 13922—13932.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Dauncey, M.J., Nutrition, the brain and cognitive decline: insights from epigenetics, Eur. J. Clin. Nutr., 2014, vol. 68, pp. 1179—1185. https://doi.org/10.1038/ejcn.2014.173

    Article  CAS  PubMed  Google Scholar 

  56. Lupu, D.S., Tint, D., and Niculescu, M.D., Perinatal epigenetic determinants of cognitive and metabolic disorders, Aging Dis., 2012, vol. 3, pp. 444—453.

    PubMed  PubMed Central  Google Scholar 

  57. Butler, A.A., Webb, W.M., and Lubin, F.D., Regulatory RNAs and control of epigenetic mechanisms: expectations for cognition and cognitive dysfunction, Epigenomics, 2016, vol. 8, pp. 135—151. https://doi.org/10.2217/epi.15.79

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Adler, S.M. and Schmauss, C., Cognitive deficits triggered by early life stress: the role of histone deacetylase 1, Neurobiol. Dis., 2016, vol. 94, pp. 1—9. https://doi.org/10.1016/j.nbd.2016.05.018

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Rudenko, A. and Tsai, L.H., Epigenetic modifications in the nervous system and their impact upon cognitive impairments, Neuropharmacology, 2014, vol. 80, pp. 70—82. https://doi.org/10.1016/j.neuropharm.2014.01.043

    Article  CAS  PubMed  Google Scholar 

  60. Lewis, C.R., Henderson-Smith, A., Breitenstein, R.S., et al., Dopaminergic gene methylation is associated with cognitive performance in childhood monozygotic twin study, Epigenetics, 2019, vol. 14, pp. 310—323. https://doi.org/10.1080/15592294.2019.1583032

    Article  PubMed  PubMed Central  Google Scholar 

  61. Mather, K.A., Kwok, J.B., Armstrong, N., and Sachdev, P.S., The role of epigenetics in cognitive ageing, Int. J. Geriatr. Psychiatry, 2014, vol. 29, pp. 1162—1171. https://doi.org/10.1002/gps.4183

  62. Hernandez, D.G., Nalls, M.A., Gibbs, J.R., et al., Distinct DNA methylation changes highly correlated with chronological age in the human brain, Hum. Mol. Genet., 2011, vol. 20, pp. 1164—1172. https://doi.org/10.1093/hmg/ddq561

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Djebali, S., Davis, C.A., Merkel, A., et al., Landscape of transcription in human cells, Nature, 2012, vol. 489, no. 7414, p. 101. https://doi.org/10.1038/nature11233

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Woldemichael, B.T. and Mansuy, I.M., Micro-RNAs in cognition and cognitive disorders: potential for novel biomarkers and therapeutics, Biochem. Pharmacol., 2016, vol. 104, pp. 1—7. https://doi.org/10.1016/j.bcp.2015.11.021

    Article  CAS  PubMed  Google Scholar 

  65. Briggs, J.A., Wolvetang, E.J., Mattick, J.S., et al., Mechanisms of long non-coding RNAs in mammalian nervous system development, plasticity, disease, and evolution, Neuron, 2015, vol. 88, pp. 861—877. https://doi.org/10.1016/j.neuron.2015.09.045

    Article  CAS  PubMed  Google Scholar 

  66. Pereira Fernandes, D., Bitar, M., Jacobs, F.M.J., and Barry, G., Long non-coding RNAs in neuronal aging, Noncoding RNA, 2018, vol. 4. pii: E12. https://doi.org/10.3390/ncrna4020012

    Article  CAS  PubMed  Google Scholar 

  67. Yi, J., Chen, B., Yao, X., et al., Upregulation of the lncRNA MEG3 improves cognitive impairment, alleviates neuronal damage, and inhibits activation of astrocytes in hippocampus tissues in Alzheimer’s disease through inactivating the PI3K/Akt signaling pathway, J. Cell. Biochem., 2019. https://doi.org/10.1002/jcb.29108

  68. Mercer, T.R., Dinger, M.E., Sunkin, S.M., et al., Specific expression of long noncoding RNAs in the mouse brain, Proc. Natl. Acad. Sci. U.S.A., 2008, vol. 105, no. 2, pp. 716—721. https://doi.org/10.1073/pnas.0706729105

    Article  PubMed  PubMed Central  Google Scholar 

  69. Aprea, J., Prenninger, S., Dori, M., et al., Transcriptome sequencing during mouse brain development identifies long non-coding RNAs functionally involved in neurogenic commitment, EMBO J., 2013, vol. 32, no. 24, pp. 3145—3160. https://doi.org/10.1038/emboj.2013.245

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Barry, G., Integrating the roles of long and small non-coding RNA in brain function and disease, Mol. Psychiatry, 2014, vol. 19, pp. 410—416. https://doi.org/10.1038/mp.2013.196

    Article  CAS  PubMed  Google Scholar 

  71. Stappert, L., Roese-Koerner, B., and Brustle, O., The role of microRNAs in human neural stem cells, neuronal differentiation and subtype specification, Cell Tissue Res., 2015, vol. 359, pp. 47—64. https://doi.org/10.1007/s00441-014-1981-y

    Article  CAS  PubMed  Google Scholar 

  72. Smirnova, L., Grafe, A., Seiler, A., et al., Regulation of miRNA expression during neural cell specification, Eur. J. Neurosci., 2005, vol. 21, pp. 1499—1477.

    Article  Google Scholar 

  73. Lugli, G., Torvik, V.L., Larson, J., and Smalheiser, N.R., Expression of microRNAs and their precursors in synaptic fractions of adult mouse forebrain, J. Neurochem., 2008, vol. 106, pp. 650—661. https://doi.org/10.1111/j.1471-4159.2008.05413.x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Fiorenza, A. and Barco, A., Role of Dicer and the miRNA system in neuronal plasticity and brain function, Neurobiol. Learn. Mem., 2016, vol. 135, pp. 3—12. https://doi.org/10.1016/j.nlm.2016.05.001

    Article  CAS  PubMed  Google Scholar 

  75. Gao, J., Wang, W.Y., Mao, Y.W., et al., A novel pathway regulates memory and plasticity via SIRT1 and miR-134, Nature, 2010, vol. 466, pp. 1105—1109. https://doi.org/10.1038/nature09271

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Lin, Q., Wei, W., Coelho, C.M., et al., The brain-specific microRNA miR-128b regulates the formation of fear-extinction memory, Nat. Neurosci., 2011, vol. 14, pp. 1115—1117. https://doi.org/10.1038/nn.2891

    Article  CAS  PubMed  Google Scholar 

  77. Griggs, E.M., Young, E.J., Rumbaugh, G., and Miller, C.A., MicroRNA-182 regulates amygdale-dependent memory formation, J. Neurosci., 2013, vol. 33, pp. 1734—1740. https://doi.org/10.1523/JNEUROSCI.2873-12.2013

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Shaltiel, G., Hanan, M., Wolf, Y., et al., Hippocampal microRNA-132 mediates stress-inducible cognitive deficits through its acetylcholinesterase target, Brain Struct. Funct., 2013, vol. 218, pp. 59—72. https://doi.org/10.1007/s00429-011-0376-z

    Article  CAS  PubMed  Google Scholar 

  79. Wang, R.Y., Phang, R.Z., Hsu, P.H., et al., In vivo knockdown of hippocampal miR-132 expression impairs memory acquisition of trace fear conditioning, Hippocampus, 2013, vol. 23, pp. 625—633. https://doi.org/10.1002/hipo.22123

    Article  CAS  PubMed  Google Scholar 

  80. Hansen, K.F., Karelina, K., Sakamoto, K., et al., miRNA-132: a dynamic regulator of cognitive capacity, Brain Struct. Funct., 2013, vol. 218, pp. 817—831. https://doi.org/10.1007/s00429-012-0431-4

    Article  PubMed  Google Scholar 

  81. Luikart, B.W., Bensen, A.L., Washburn, E.K., et al., miR-132 mediates the integration of newborn neurons into the adult dentate gyrus, PLoS One, 2011, vol. 6. e19077. https://doi.org/10.1371/journal.pone.0019077

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Yang, L., Zhang, R., Li, M., et al., A functional MiR-124 binding-site polymorophism in IQGAP1 affects human cognitive performance, PLoS One, 2014, vol. 9. e107065. https://doi.org/10.1371/journal.pone.0107065

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Malmevik, J., Petri, R., Knauff, P., et al., Distinct cognitive effects and underlying transcriptome changes upon inhibition of individual miRNAs in hippocampal neurons, Sci. Rep., 2016, vol. 6, p. 19879. https://doi.org/10.1038/srep19879

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Sun, L., Liu, A., Zhang, J., et al., miR-23b improves cognitive impairments in traumatic brain injury by targeting ATG12-mediated neuronal autophagy, Behav. Brain Res., 2018, vol. 340, pp. 126—136. https://doi.org/10.1016/j.bbr.2016.09.020

    Article  CAS  PubMed  Google Scholar 

  85. Andrews, S.J., Das, D., Anstey, K.J., and Easteal, S., Association of AKAP6 and MIR2113 with cognitive performance in population-based sample of older adults, Genet. Brain Behav., 2017, vol. 16, pp. 472—478. https://doi.org/10.1111/gbb.12368

    Article  CAS  Google Scholar 

  86. Mengel-From, J., Feddersen, S., Halekoh, U., et al., Circulating microRNA disclose biology of normal cognitive function in healthy elderly people—a discovery twin study, Eur. J. Hum. Genet., 2018, vol. 26, pp. 378—1387.

    Article  Google Scholar 

  87. Nair, P.S., Kuusi, T., Ahvenainen, M., et al., Music-performance regulates microRNAs in professional musicians, Peer J., 2019, vol. 7. e6660. https://doi.org/10.7717/peerj.6660

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Mustafin, R.N., Enikeeva, R.F., Davydova, Y.D., et al., The role of epigenetic factors in the development of depressive disorders, Russ. J. Genet., 2018, vol. 54, no. 12, pp. 1397—1409. https://doi.org/10.1134/S1022795418120104

    Article  CAS  Google Scholar 

  89. Mustafin, R.N., Kazantseva, A.V., Enikeeva, R.F., et al., Epigenetics of aggressive behavior, Russ. J. Genet., 2019, vol. 55, no. 9, pp. 1051—1060. https://doi.org/10.1134/S1022795419090096

    Article  CAS  Google Scholar 

  90. Mustafin, R.N. and Khusnutdinova, E.K., Epigenetic hypothesis of the role of peptides in aging, Adv. Gerontol., 2018, vol. 8, no. 1, pp. 200—209. https://doi.org/10.1134/S2079057018030128

    Article  Google Scholar 

Download references

Funding

This study was supported by the Russian Science Foundation (project no. 17-78-30028).

Author information

Authors and Affiliations

  1. Bashkir State Medical University, 450008, Ufa, Russia

    R. N. Mustafin

  2. Institute of Biochemistry and Genetics, Ufa Federal Research Centre, Russian Academy of Sciences, 450054, Ufa, Russia

    A. V. Kazantseva & E. K. Khusnutdinova

  3. Moscow State University, 119991, Moscow, Russia

    S. B. Malykh & E. K. Khusnutdinova

Authors
  1. R. N. Mustafin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. V. Kazantseva
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S. B. Malykh
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. E. K. Khusnutdinova
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to R. N. Mustafin.

Ethics declarations

The authors declare that they have no conflict of interest. This article does not contain any studies involving animals or human participants performed by any of the authors.

Additional information

Translated by A. Kazantseva

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mustafin, R.N., Kazantseva, A.V., Malykh, S.B. et al. Genetic Mechanisms of Cognitive Development. Russ J Genet 56, 891–902 (2020). https://doi.org/10.1134/S102279542007011X

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S102279542007011X

Keywords:

Search

Navigation