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Russian Journal of Genetics

, Volume 54, Issue 12, pp 1397–1409 | Cite as

The Role of Epigenetic Factors in the Development of Depressive Disorders

  • R. N. MustafinEmail author
  • R. F. Enikeeva
  • Y. D. Davydova
  • E. K. KhusnutdinovaEmail author
REVIEWS AND THEORETICAL ARTICLES
  • 10 Downloads

Abstract

To determine the molecular mechanisms of the development of depressive disorders, numerous analyses of associations and gene linkage were carried out using the whole-genomic methods of searching for candidate genes. The role of neurotransmitter systems and metabolic pathways in the pathogenesis of depressive disorders as a result of these studies was revealed. A promising direction is the search for epigenetic markers because of the possibility of standardizing diagnostic methods for the effective pharmacological correction of depression. MicroRNAs and long noncoding RNAs regulate neurogenesis and fine tuning of the differentiation of brain regions during their development. Numerous studies have shown that changes in the levels of microRNAs and long noncoding RNAs play an important role in the development of depressive disorders. Stress appears to be the cause of depressive disorders. It is known that stress causes the activation of transposons, which may result in pathological epigenetic regulation of neurotransmitter systems. In this regard, we can suggest the role of transposons in the pathogenesis of depressive disorders. The role of transposons in the development of depression can be confirmed on the basis of association of depression with telomere shortening, since telomerase originated from transposons. Transposons are also important sources of noncoding RNAs, which are associated with depressive disorders. Noncoding RNAs can specifically alter DNA methylation and histone modifications, the epigenetic labels of which also affect the development of depression. Drug therapy directed to only one neurotransmitter system is not effective in all patients, which may be due to the differences in the mechanisms of development of depression in different patients. In order to determine the main molecular pathways of the pathogenesis of depression with an individual approach, the most convenient diagnostic systems are noncoding RNAs. Moreover, noncoding RNAs can be used for targeted therapy of depressive disorders.

Keywords:

brain depression methylation microRNA long noncoding RNA 

Notes

REFERENCES

  1. 1.
    Cui, X., Niu, W., Kong, L., et al., Long noncoding RNA expression in peripheral blood mononuclear cells and suicide risk in Chinese patients with major depressive disorder, Brain Behav., 2017, vol. 7, no. 6. e00711CrossRefGoogle Scholar
  2. 2.
    Dempster, E.L., Wong, C.C., Lester, K.J., et al., Genome-wide methylomic analysis of monozygotic twins discordant for adolescent depression, Biol. Psychiatry, 2014, vol. 76, pp. 977—983.CrossRefGoogle Scholar
  3. 3.
    Saavedra, K., Molina-Marguez, A.M., Saavedra, N., et al., Epigenetic modifications of major depressive disorder, Int. J. Mol. Sci., 2016, vol. 17, no. 8. E1279. doi 10.3390/ijms17081279CrossRefGoogle Scholar
  4. 4.
    Vein, A.M., Voznesenskaya, T.G., Golubev, V.L., et al., Depressiya v nevrologicheskoi praktike (Depression in Neurological Practice), Moscow: Med. Inf. Agentstvo, 2007, 3rd ed.Google Scholar
  5. 5.
    Archer, T. and Garcia, D., Epigenetic influences on anxious and depressive behavior: BDNF links, JSM Anxiety Depress., 2016, vol. 1, no. 3, p. 1015.Google Scholar
  6. 6.
    Huang, X., Luo, Y.L., Mao, Y.S., and Ji, J.L., The link between long noncoding RNAs and depression, Prog. Neuropsychopharmacol. Biol. Psychiatry, 2017, vol. 73, pp. 73—78.CrossRefGoogle Scholar
  7. 7.
    Miller, G.E. and Cole, S.W., Clustering of depression and inflammation in adolescents previously exposed to childhood adversity, Biol. Psychiatry, 2012, vol. 72, no. 1, pp. 34—40.CrossRefGoogle Scholar
  8. 8.
    Serafini, G., Pompili, M., Hansen, K.F., et al., The involvement of microRNAs in major depression, suicidal behavior, and related disorders: a focus on miR-185 and miR-491-3p, Cell. Mol. Neurobiol., 2014, vol. 34, no. 1, pp. 17—30.CrossRefGoogle Scholar
  9. 9.
    Dwivedi, Y., Roy, B., Lugli, G., et al., Chronic corticosterone-mediated dysregulation of microRNA network in prefrontal cortex of rats: relevance to depression pathophysiology, Transl. Psychiatry, 2015, vol. 5. e:682Google Scholar
  10. 10.
    Feng, G., Leem, Y.E., and Levin, H.L., Transposon integration enhances expression of stress response genes, Nucleic Acids Res., 2013, vol. 41, no. 2, pp. 775—789.CrossRefGoogle Scholar
  11. 11.
    Ito, H., Kim, J.M., Matsunaga, W., et al., A stress-activated transposon in Arabidopsis induces transgenerational abscisic acid insensitivity, Sci. Rep., 2016, vol. 6, p. 23181.CrossRefGoogle Scholar
  12. 12.
    Masuta, Y., Nozawa, K., Takagi, H., et al., Inducible transposition of a heat-activated retrotransposon in tissue culture, Plant Cell Physiol., 2017, vol. 58, no. 2, pp. 375—384.Google Scholar
  13. 13.
    Borchert, G.M., Holton, N.W., Williams, J.D., et al., Comprehensive analysis of microRNA genomic loci identifies pervasive repetitive-element origins, Mobile Genet. Elem., 2011, vol. 1, pp. 8—17.CrossRefGoogle Scholar
  14. 14.
    Gim, J., Ha, H., Ahn, K., et al., Genome-wide identification and classification of microRNAs derived from repetitive elements, Genomic Inf., 2014, vol. 12, no. 4, pp. 261—267.CrossRefGoogle Scholar
  15. 15.
    Kapusta, A. and Feschotte, C., Volatile evolution of long noncoding RNA repertoires: mechanisms and biological implications, Trends Genet., 2014, vol. 30, no. 10, pp. 439—452.CrossRefGoogle Scholar
  16. 16.
    Morita, S., Horii, T., Kimura, M., et al., MiR-29 represses the activities of DNA methyltransferases and DNA demethylases, Int. J. Mol. Sci., 2013, vol. 14, pp. 14 647—14 658.CrossRefGoogle Scholar
  17. 17.
    Samantarrai, D., Dash, S., Chhetri, B., et al., Genomic and epigenomic cross-talks in the regulatory landscape of miRNAs in breast cancer, Mol. Cancer Res., 2013, vol. 11, pp. 315—328.CrossRefGoogle Scholar
  18. 18.
    Zhang, G., Esteve, P., Chin, H.G., et al., Small RNA-mediated DNA (cytosine-5) methyltransferase 1 inhibition leads to aberrant DNA methylation, Nucleic Acids Res., 2015, vol. 43, pp. 6112—6124.CrossRefGoogle Scholar
  19. 19.
    Sibille, E., Molecular aging of the brain, neuroplasticity, and vulnerability to depression and other brain-related disorders, Dialogues Clin. Neurosci., 2013, vol. 15, no. 1, pp. 53—65.Google Scholar
  20. 20.
    Lin, P.Y., Huang, Y.C., and Hung, C.F., Shortened telomere length in patients with depression: a metaanalytic study, J. Psychiatr. Res., 2016, vol. 76, pp. 84—93.CrossRefGoogle Scholar
  21. 21.
    Pavlov, K.I., Mukhin, V.N., Klimenko, V.M., and Anisimov, V.N., The telomere—telomerase system and mental processes in aging under normal and pathological conditions, Usp. Gerontol., 2017, no. 1, pp. 17—26.Google Scholar
  22. 22.
    Ledwing, K.H., Brockhaus, A.C., Baumert, J., et al., Posttraumatic stress disorder and not depression is associated with shorter leukocyte telomere length: findings from 3000 participants in the population-based KORA F4 study, PLoS One, 2013, vol. 8. e6462Google Scholar
  23. 23.
    Needham, B.L., Mezuk, B., Bareis, N., et al., Depression, anxiety and telomere length in young adults: evidence from the National Health and Nutrition Examination Survey, Mol. Psychiatry, 2015, vol. 20, pp. 520—528.CrossRefGoogle Scholar
  24. 24.
    Ridout, K.K., Ridout, S.J., Price, L.H., et al., Depression and telomere length: a meta-analysis, J. Affect. Disord., 2016, vol. 191, pp. 237—247.CrossRefGoogle Scholar
  25. 25.
    Mustafin, R.N. and Khusnutdinova, E.K., Interrelation of epigenetic factors in the mechanisms of aging and malignancy, Usp. Fiziol. Nauk, 2017, vol. 48, no. 2, pp. 72—99.Google Scholar
  26. 26.
    Casacuberta, E., Drosophila: retrotransposons making up telomeres, Viruses, 2017, vol. 9. E192. doi 10.3390/v9070192CrossRefGoogle Scholar
  27. 27.
    Lopez, J.P., Kos, A., and Turecki, G., Major depression and its treatment: microRNAs as peripheral biomarkers of diagnosis and treatment response, Curr. Opin. Psychiatry, 2018, vol. 31, no. 1, pp. 7—16.CrossRefGoogle Scholar
  28. 28.
    Menke, A. and Binder, E.B., Epigenetic alterations in depression and antidepressant treatment, Dialogues Clin. Neurosci., 2014, vol. 16, no. 3, pp. 395—404.Google Scholar
  29. 29.
    Kiselev, O.I., Endogenous retroviruses: structure and functions in the human genome, Vopr. Virusol., 2013, no. 1, pp. 102—115.Google Scholar
  30. 30.
    Lu, Y., Feng, F., Yang, Y., et al., LINE-1 ORF-1p functions as a novel androgen receptor co-activator and promotes the growth of human prostatic carcinoma cells, Cell. Signal., 2013, vol. 25, no. 2, pp. 479—489.CrossRefGoogle Scholar
  31. 31.
    de Souza, F.S., Franchini, L.F., and Rubinstein, M., Exaptation of transposable elements into novel cis-regulatory elements: is the evidence always strong, Mol. Biol. Evol., 2013, vol. 30, no. 6, pp. 1239—1251. doi 10.1093/molbev/mst045CrossRefGoogle Scholar
  32. 32.
    Chadha, S. and Sharma, M., Transposable elements as stress adaptive capacitors induce genome instability in fungal pathogen Magnaporthe oryzae, PLoS One, 2014, vol. 9, no. 4. e94415CrossRefGoogle Scholar
  33. 33.
    Grandbastien, M.A., LTR retrotransposons, handy hitchhikers of plant regulation and stress response, Biochim. Biophys. Acta, 2015, vol. 1849, no. 4, pp. 403—416.CrossRefGoogle Scholar
  34. 34.
    Reilly, M.T., Faulkner, G.J., Dubnau, J., et al., The role of transposable elements in health and diseases of the central nervous system, J. Neurosci., 2013, vol. 33, no. 45, pp. 17577—17586. doi 10.1523/JNEUROSCI.3369-13.2013CrossRefGoogle Scholar
  35. 35.
    Deng, B., Cheng, X., Li, H., et al., Microarray expression profiling in the denervated hippocampus identifies long noncoding RNAs functionally involved in neurogenesis, BMC Mol. Biol., 2017, vol. 18, no. 1, p. 15.CrossRefGoogle Scholar
  36. 36.
    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.CrossRefGoogle Scholar
  37. 37.
    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.CrossRefGoogle Scholar
  38. 38.
    Notwell, J.H., Chung, T., Heavner, W., and Bejerano, G., A family of transposable elements co-opted into developmental enhancers in the mouse neocortex, Nat. Commun., 2015, vol. 6, p. 6644.CrossRefGoogle Scholar
  39. 39.
    Johnson, R. and Guigo, R., The RIDL hypothesis: transposable elements as functional domains of long noncoding RNAs, RNA, 2014, vol. 20, no. 7, pp. 959—976.CrossRefGoogle Scholar
  40. 40.
    Lu, X., Sachs, F., Ramsay, L., et al., The retrovirus HERVH is a long noncoding RNA required for human embryonic stem cell identity, Nat. Struct. Mol. Biol., 2014, vol. 21, no. 4, pp. 423—425.CrossRefGoogle Scholar
  41. 41.
    Dwivedi, Y., Emerging role of microRNAs in major depressive disorder: diagnosis and therapeutic implications, Dialogues Clin. Neurosci., 2014, vol. 16, no. 1, pp. 43—61.Google Scholar
  42. 42.
    Mustafin, R.N. and Khusnutdinova, E.K., Non-coding parts of genomes as the basis of epigenetic heredity, Vavilovskii Zh. Genet. Sel., 2017, vol. 21, no. 6, pp. 742—749.Google Scholar
  43. 43.
    Shelton, R.C., The molecular neurobiology of depression, Psychiatr. Clin. North Am., 2007, vol. 30, no. 1, pp. 1—11.CrossRefGoogle Scholar
  44. 44.
    Kurnosov, A.A., Ustyugova, S.V., Nazarov, V., et al., The evidence for increased L1 activity in the site of human adult brain neurogenesis, PLoS One, 2015, vol. 10, no. 2. e0117854CrossRefGoogle Scholar
  45. 45.
    Muotri, A.R., Chu, V.T., Marchetto, M.C., et al., Somatic mosaicism in neuronal precursor cells mediated by L1 retrotransposition, Nature, 2005, vol. 435, pp. 903—910.CrossRefGoogle Scholar
  46. 46.
    Coufal, N.G., Garcia-Perez, J.L., Peng, G.E., et al., L1 retrotransposition in human neural progenitor cells, Nature, 2009, vol. 460, no. 7259, pp. 1127—1131.CrossRefGoogle Scholar
  47. 47.
    Faulkner, G.J., Retrotransposons: mobile and mutagenic from conception to death, FEBS Lett., 2011, vol. 585, no. 11, pp. 1589—1594.CrossRefGoogle Scholar
  48. 48.
    Upton, K.R., Gerhardt, D.J., Jesuadian, J.S., et al., Ubiquitous L1 mosaicism in hippocampal neurons, Cell, 2015, vol. 161, no. 2, pp. 22—39.CrossRefGoogle Scholar
  49. 49.
    Evrony, G.D., Cai, X., Lee, E., et al., Single-neuron sequencing analysis of L1 retrotransposition and somatic mutation in the human brain, Cell, 2012, vol. 151, no. 3, pp. 483—496.CrossRefGoogle Scholar
  50. 50.
    Van Meter, M., Kashyap, M., Rezazadeh, S., et al., SIRT6 represses LINE1 retrotransposons by ribosylating KAP1 but this repression fails with stress and age, Nat. Commun., 2014, vol. 5, p. 5011.CrossRefGoogle Scholar
  51. 51.
    Zalsman, G., Huang, Y.Y., Oquendo, M.A., et al., Association of a triallelic serotonin transporter gene promoter region (5-HTTLPR) polymorphism with stressful life events and severity of depression, Am. J. Psychiatry, 2006, vol. 163, pp. 1588—1593.CrossRefGoogle Scholar
  52. 52.
    Schulze, T.G., Muller, D.J., Krauss, H., et al., Association between a functional polymorphism in the monoamine oxidase A gene promoter and major depressive disorder, Am. J. Med. Genet., 2000, vol. 96, pp. 801—803.CrossRefGoogle Scholar
  53. 53.
    Jurka, J. and Gentles, A.J., Origin and diversification of minisatellites derived from human Alu sequences, Gene, 2006, vol. 365, pp. 21—26.CrossRefGoogle Scholar
  54. 54.
    Yirmiya, R. and Goshen, I., Immune modulation of learning, memory, neural plasticity and neurogenesis, Brain Behav. Immun., 2011, vol. 25, pp. 181—213.CrossRefGoogle Scholar
  55. 55.
    Dantzer, R. and Kelley, K.W., Twenty years of research on cytokine-induced sickness behavior, Brain Behav. Immun., 2007, vol. 21, pp. 153—160.CrossRefGoogle Scholar
  56. 56.
    Martinez, J.M., Garakani, A., Yehuda, R., and Gorman, J.M., Proinflammatory and “resiliency” proteins in the CSF of patients with major depression, Depress. Anxiety, 2012, vol. 29, pp. 2—38.CrossRefGoogle Scholar
  57. 57.
    Bull, S.J., Huezo-Diaz, P., Binder, E.B., et al., Functional polymorphisms in the interleukin-6 and serotonin transporter genes, and depression and fatigue induced by interferon-alpha and ribavirin treatment, Mol. Psychiatry, 2009, vol. 14, pp. 1095—1104.CrossRefGoogle Scholar
  58. 58.
    Jansen, R., Penninx, B.W., Madar, V., et al., Gene expression in major depressive disorder, Mol. Psychiatry, 2016, vol. 21, pp. 339—347.CrossRefGoogle Scholar
  59. 59.
    Murphy, T.M., O’Donovan, A., Mullins, N., et al., Anxiety is associated with higher levels of global DNA methylation and altered expression of epigenetic and interleukin-6 genes, Psychiatr. Genet., 2015, vol. 25, no. 2, pp. 71—78.CrossRefGoogle Scholar
  60. 60.
    Ryan, J., Pilkington, L., Neuhaus, K., et al., Investigationg the epigenetic profile of the inflammatory gene IL-6 in late-life depression, BMC Psychiatry, 2017, vol. 17, p. 354.CrossRefGoogle Scholar
  61. 61.
    Cordova-Palomera, A., Fatjo-Vilas, M., Gasto, C., et al., Genome-wide methylation study on depression: differential methylation and variable methylation in monozygotic twins, Transl. Psychiatry, 2015, vol. 5. e557CrossRefGoogle Scholar
  62. 62.
    Byrne, E.M., Carrillo-Roa, T., Henders, A.K., et al., Monozygotic twins affected with major depressive disorder have greater variance in methylation than their unaffected co-twin, Transl. Psychiatry, 2013, vol. 3. e269CrossRefGoogle Scholar
  63. 63.
    Vanyushin, B.F., Epigenetics today and tomorrow, Russ. J. Genet.: Appl. Res., 2014, vol. 4, no. 3, pp. 168—188.CrossRefGoogle Scholar
  64. 64.
    Feschotte, C., Transposable elements and the evolution of regulatory networks, Nat. Rev. Genet., 2008, vol. 9, no. 5, pp. 397—405.CrossRefGoogle Scholar
  65. 65.
    Gerdes, P., Richardson, S.R., Mager, D.L., and Faulkner, G.J., Transposable elements in the mammalian embryo: pioneers surviving through stealth and service, Genome Biol., 2016, vol. 17, p. 100.CrossRefGoogle Scholar
  66. 66.
    Ito, J., Suqimoto, R., Nakaoka, H., et al., Systematic identification and characterization of regulatory elements derived from human endogenous retroviruses, PLoS Genet., 2017, vol. 13, no. 7. e1006883CrossRefGoogle Scholar
  67. 67.
    Jacques, P.E., Jeyakani, J., and Bourgue, G., The majority of primate-specific regulatory sequences are derived from transposable elements, PLoS Genet., 2013, vol. 9, no. 5. e1003504CrossRefGoogle Scholar
  68. 68.
    Cruceanu, C., Alda, M., Nagy, C., et al., H3K4 tri-methylation in synapsin genes leads to different expression patterns in bipolar disorder and major depression, Int. J. Neuropsychopharmacol., 2013, vol. 16, no. 2, pp. 289—299.CrossRefGoogle Scholar
  69. 69.
    Iga, J., Ueno, S., Yamauchi, K., et al., Altered HDAC5 and CREB mRNA expressions in the peripheral leukocytes of major depression, Prog. Neuropsychopharmacol. Biol. Psychiatry, 2007, vol. 31, no. 3, pp. 628—632.CrossRefGoogle Scholar
  70. 70.
    Renthal, W., Maze, I., Krishnan, V., et al., Histone deacetylase 5 epigenetically controls behavioral adaptations to chronic emotional stimuli, Neuron, 2007, vol. 56, pp. 517—529.CrossRefGoogle Scholar
  71. 71.
    Covington, H.E., Maze, I., LaPlant, Q., et al., Antidepressant actions of HDAC inhibitors, J. Neurosci., 2009, vol. 29, pp. 11451—11460. doi 10.1523/JNEUROSCI.1758-09.2009CrossRefGoogle Scholar
  72. 72.
    Hobara, T., Uchida, S., Otsuki, K., et al., Altered gene expression of histone deacetylases in mood disorder patients, J. Psychiatr. Res., 2010, vol. 44, no. 5, pp. 263—270.CrossRefGoogle Scholar
  73. 73.
    Liu, D., Qiu, H.M., Fei, H.Z., et al., Histone acetylation and expression of mono-aminergic transmitters synthetases involved in CUS-induced depressive rats, Exp. Biol. Med. (Maywood), 2014, vol. 239, no. 3, pp. 330—336. doi 10.1177/1535370213513987CrossRefGoogle Scholar
  74. 74.
    Wan, Q., Gao, K., Rong, H., et al., Histone modifications of the Crhr1 gene in a rat model of depression following chronic stress, Behav. Brain Res., 2014, vol. 271, pp. 1—6.CrossRefGoogle Scholar
  75. 75.
    Titov, I.I. and Vorozheikin, P.S., Transposons containing human miRNAs, Vavilovskii Zh. Genet. Sel., 2011, vol. 15, no. 2, pp. 323—326.Google Scholar
  76. 76.
    Wang, Q., Zhao, G., Yang, Z., et al., Downregulation of microRNA-124-3p suppresses the mTOR signaling pathway by targeting DDIT4 in males with major depressive disorder, Int. J. Mol. Med., 2018, vol. 41, no. 1, pp. 493—500.Google Scholar
  77. 77.
    Mouillet-Richard, S., Baudry, A., Launay, J.M., and Kellermann, O., MicroRNAs and depression, Neurobiol. Dis., 2012, vol. 46, no. 2, pp. 272—278.CrossRefGoogle Scholar
  78. 78.
    Song, M.F., Dong, J.Z., Wang, Y.W., et al., CSF miR-16 is decreased in major depression patients and its neutralization in rats induces depression-like behaviors via a serotonin transmitter system, J. Affect. Disord., 2015, vol. 178, pp. 25—31.CrossRefGoogle Scholar
  79. 79.
    Wan, Y., Liu, Y., Wang, X., et al., Identification of differential microRNAs in cerebrospinal fluid and serum of patients with major depressive disorder, PLoS One, 2015, vol. 10, no. 3. e0121975CrossRefGoogle Scholar
  80. 80.
    Maffioletti, E., Salvi, A., Conde, I., et al., Study of the in vitro modulation exerted by the antidepressant drug escitalopram on the expression of candidate microRNAs and their target genes, Mol. Cell. Neurosci., 2017, vol. 85, pp. 220—225.CrossRefGoogle Scholar
  81. 81.
    Wu, P., Zuo, X., Deng, H., et al., Roles of long noncoding RNAs in brain development, functional diversification and neurodegenerative diseases, Brain Res. Bull., 2013, vol. 97, pp. 69—80.CrossRefGoogle Scholar
  82. 82.
    Ye, N., Rao, S., Du, T., et al., Intergenic variant may predispose to major depression disorder through regulation of long non-coding RNA expression, Gene, 2017, vol. 601, pp. 21—26.CrossRefGoogle Scholar
  83. 83.
    Liu, Z., Li, X., Sun, N., et al., Microarray profiling and co-expression network analysis of circulating lncRNAs and mRNAs associated with major depressive disorder, PLoS One, 2014, vol. 27, no. 9. e93388CrossRefGoogle Scholar
  84. 84.
    Lisitsyn, N.A., Chernyi, A.A., and Karpov, V.L., A role of long noncoding RNAs in carcinogenesis, Mol. Biol. (Moscow), 2015, vol. 49, pp. 561—570.CrossRefGoogle Scholar
  85. 85.
    Ni, X., Liao, Y., Li, L., et al., Therapeutic role of long non-coding RNA TCONS_00019174 in depressive disorders is dependent on Wnt/β-catenin signaling pathway, J. Integr. Neurosci., 2017. doi 10.3233/JIN-170052Google Scholar
  86. 86.
    Darrow, S.M., Verhoeven, J.E., Revesz, D., et al., The association between psychiatric disorders and telomere length: a meta-analysis involving 14827 persons, Psychosom. Med., 2016, vol. 78, pp. 776—787.CrossRefGoogle Scholar
  87. 87.
    Bortolozzi, A., Celada, P., and Artigas, F., Novel therapeutic strategies in major depression: focus on RNAi and ketamine, Curr. Pharm. Des., 2014, vol. 20, pp. 3848—3860.CrossRefGoogle Scholar
  88. 88.
    Pan, B. and Liu, Y., Effects of duoxetine on microRNA expression profile in frontal lobe and hippocampus in mouse model of depression, Int. J. Clin. Exp. Pathol., 2015, vol. 8, pp. 15454—15461.Google Scholar
  89. 89.
    Issler, O., Haramati, S., and Paul, E.D., MicroRNA135 is essential for chronic stress resiliency, antidepressant efficacy, and intact serotonergic activity, Neuron, 2014, vol. 83, pp. 344—360. doi 10.1016/j.neuron.2014.05.042CrossRefGoogle Scholar
  90. 90.
    Lopez, J.P., Lim, R., Cruceanu, C., et al., MiR-1202 is a primate-specific and brain-enriched microRNA involved in major depression and antidepressant treatment, Nat. Med., 2014, vol. 20, no. 7, pp. 764—768. doi 10.1038/nm.3582CrossRefGoogle Scholar
  91. 91.
    Anreiter, I., Kramer, J.M., and Sokolowski, M.B., Epigenetic mechanisms modulate differences in Drosophila foraging behavior, Proc. Natl. Acad. Sci. U.S.A., 2017, vol. 114, pp. 12518—12523. doi 10.1073/pnas.1710770114CrossRefGoogle Scholar

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© Pleiades Publishing, Inc. 2018

Authors and Affiliations

  1. 1.Department of Genetics and Fundamental Medicine, Bashkir State UniversityUfaRussia
  2. 2.Institute of Biochemistry and Genetics, Ufa Federal Research Centre, Russian Academy of SciencesUfaRussia

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