Skip to main content
SpringerLink
Log in

Molecular Biological Aspects of Depressive Disorders: A Modern View

  • REVIEWS
  • Published:
Molecular Biology Aims and scope Submit manuscript

Abstract

Depression is a serious mental disorder that affects more than 300 million people worldwide. Due to the lack of effective treatment methods, the pathogenesis of depression is necessary to study in order to understand its development and find new therapies. The review describes the main mechanisms of depression, including the monoamine hypothesis, impairment of the hipotalamic–pituitary–adrenal axis, decreased production of neurotropic factors, and neuroinflammation. Genetic correlations, gene polymorphisms, and epigenetic mechanisms are also considered. Common and different features of the etiology are analyzed for depression and depressive conditions associated with other pathologies (schizophrenia, Parkinson disease, and Alzheimer’s disease). Modern experimental methods used to investigate the molecular mechanisms of depressive conditions are described with a focus on gene knockouts in laboratory animals and the CRISPR/Cas technology. Consideration is given to optogenetic and chemogenetic methods and analyses of genetic polymorphisms and their combinations. The data may provide for a better integral understanding of the modern ideas about the pathogenesis of depression as an isolated or comorbid disorder and the prospects in studying the mechanisms of depressive conditions.

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

Fig. 1.
Fig. 2.

Similar content being viewed by others

REFERENCES

  1. Wang Q., Timberlake M.A., Prall K., Dwivedi Y. 2017. The recent progress in animal models of depression. Prog. Neuropsychopharmacol. Biol. Psychiatry.77, 99–109.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Felmet K., Zisook S., Kasckow J. 2010. Elderly patients with schizophrenia and depression: Diagnosis and treatment. Clin. Schizophr. Relat. Psychoses. 4, 239–250.

    Article  Google Scholar 

  3. Upthegrove R., Marwaha S., Birchwood M. 2017. Depression and schizophrenia: Cause, consequence, or trans-diagnostic issue? Schizophr. Bull.43, 240—244.

    PubMed  Google Scholar 

  4. Galts C., Bettio L., Jewett D.C., Yang C.C., Brocardo P.S., Rodrigues A., Thacker J.S., Gil-Mohapel J. 2019. Depression in neurodegenerative diseases: Common mechanisms and current treatment options. Neurosci. Biobehav. Rev. 102, 56–84.

    Article  PubMed  Google Scholar 

  5. Treadway M.T., Zald D.H. 2011. Reconsidering anhedonia in depression: Lessons from translational neuroscience. Neurosci. Biobehav. Rev. 35, 537–555.

    Article  PubMed  Google Scholar 

  6. Otte C., Gold S.M., Penninx B.W., Pariante C.M., Etkin A., Fava M., Mohr D.C., Schatzberg A.F. 2016. Major depressive disorder. Nat. Rev. Dis. Primers. 2, 160–165.

    Article  Google Scholar 

  7. Jesulola E., Micalos P., Baguley I.J. 2018. Understanding the pathophysiology of depression: From monoamines to the neurogenesis hypothesis model— are we there yet? Behav. Brain Res.341, 79–90.

    Article  CAS  PubMed  Google Scholar 

  8. Saavedra K., Molina-Márquez A.M., Saavedra N., Zambrano T., Salazar L.A. 2016. Epigenetic modifications of major depressive disorder. Int. J. Mol. Sci. 17, 1279. https://doi.org/10.3390/ijms17081279

    Article  CAS  PubMed Central  Google Scholar 

  9. Lee S., Jeong J., Kwak Y., Park S.K. 2010. Depression research: Where are we now? Mol. Brain. 3, 8. https://doi.org/10.1186/1756-6606-3-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Smulevich A.B. 1997. Depressii i komorbidnye rasstroistva (Depressions and Comorbid Disorders). Moscow: RAMN–NtsPZ.

  11. Koolschijn P.C., van Haren N.E., Lensvelt-Mulders G.J., Hulshoff Pol H.E., Kahn R.S. 2009. Brain volume abnormalities in major depressive disorder: A meta-analysis of magnetic resonance imaging studies. Hum. Brain Mapp. 30, 3719–3735.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Bora E., Fornito A., Pantelis C., Yucel M. 2012. Gray matter abnormalities in major depressive disorder: A meta-analysis of voxel based morphometry studies. J. Affect. Disord. 138, 9–18.

    Article  PubMed  Google Scholar 

  13. Du X., Pang T.Y. 2015. Is dysregulation of the HPA-axis a core pathophysiology mediating comorbid depression in neurodegenerative diseases? Front. Psychiatry. 6, 32. https://doi.org/10.3389/fpsyt.2015.00032

    Article  PubMed  PubMed Central  Google Scholar 

  14. Nikkheslat N., Pariante C.M., Zunszain P.A. 2018. Neuroendocrine abnormalities in major depression: An insight into glucocorticoids, cytokines, and the kynurenine pathway. In Inflammation and Immunity in Depression: Basic Science and Clinical Application. Academic Press, pp. 45–60.

    Google Scholar 

  15. Villas Boas G.R., Boerngen de Lacerda R., Paes M.M., Gubert P., Almeida W., Rescia V.C., de Carvalho P., de Carvalho A., Oesterreich S.A. 2019. Molecular aspects of depression: A review from neurobiology to treatment. Eur. J. Pharmacol.851, 99–121.

    Article  CAS  PubMed  Google Scholar 

  16. de Kloet E.R., Meijer O.C., de Nicola A.F., de Rijk R.H., Joëls M. 2018. Importance of the brain corticosteroid receptor balance in metaplasticity, cognitive performance and neuroinflammation. Front. Neuroendocrinol. 49, 124–145.

    Article  CAS  PubMed  Google Scholar 

  17. Binder E.B. 2009. The role of FKBP5, a co-chaperone of the glucocorticoid receptor in the pathogenesis and therapy of affective and anxiety disorders. Psychoneuroendocrinology. 34, 186–195.

    Article  CAS  Google Scholar 

  18. Xu J., Wang R., Liu Y., Wang W., Liu D., Jiang H., Pan, F. 2019. Short- and long-term alterations of FKBP5-GR and specific microRNAs in the prefrontal cortex and hippocampus of male rats induced by adolescent stress contribute to depression susceptibility. Psychoneuroendocrinology. 101, 204–215.

    Article  CAS  PubMed  Google Scholar 

  19. Bouwknecht J.A. 2015. Behavioral studies on anxiety and depression in a drug discovery environment: Keys to a successful future. Eur. J. Pharmacol. 753, 158–176.

    Article  CAS  PubMed  Google Scholar 

  20. Landgraf R. 2006. The involvement of the vasopressin system in stress-related disorders. CNS Neurol. Disord. Drug Targets. 5, 167–179.

    Article  CAS  PubMed  Google Scholar 

  21. Li J., Chen J., Ma N., Yan D., Wang Y., Zhao X., Zhang Y., Zhang C. 2019. Effects of corticosterone on the expression of mature brain-derived neurotrophic factor (mBDNF) and proBDNF in the hippocampal dentate gyrus. Behav. Brain Res. 365, 150–156.

    Article  CAS  PubMed  Google Scholar 

  22. Simon N.G., Guillon C., Fabio K., Heindel N.D., Lu S.F., Miller M., Ferris C.F., Brownstein M.J., Garripa C., Koppel G.A. 2008. Vasopressin antagonists as anxiolytics and antidepressants: Recent developments. Recent Pat. CNS Drug Discov. 3, 77–93.

    Article  CAS  PubMed  Google Scholar 

  23. Lang U.E., Borgwardt S. 2013. Molecular mechanisms of depression: Perspectives on new treatment strategies. Cell. Physiol. Biochem. 31, 761–777.

    Article  CAS  PubMed  Google Scholar 

  24. Bazyan A.S., Grigoryan G.A. 2006. Molecular-chemical basis of emotional states and reinforcement. Usp. Fiziol. Nauk.37, 68–83.

    CAS  Google Scholar 

  25. Goddard A.W., Ball S.G., Martinez J., Robinson M.J., Yang C.R., Russell J.M., Shekhar A. 2010. Current perspectives of the roles of the central norepinephrine system in anxiety and depression. Depress. Anxiety. 27, 339–350.

    Article  CAS  PubMed  Google Scholar 

  26. Shen L.H., Liao M.H., Tseng Y.C. 2012. Recent advances in imaging of dopaminergic neurons for evaluation of neuropsychiatric disorders. J. Biomed. Biotechnol. 2012, 259349.https://doi.org/10.1155/2012/259349

  27. Hannon J., Hoyer D. 2008. Molecular biology of 5-HT receptors. Behav. Brain Res. 195, 198–213.

    Article  CAS  PubMed  Google Scholar 

  28. Nautiyal K.M., Hen R. 2017. Serotonin receptors in depression: From A to B. F1000Res. 6, 123. https://doi.org/10.12688/f1000research.9736.1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Yohn C.N., Gergues M.M., Samuels B.A. 2017. The role of 5-HT receptors in depression. Mol. Brain. 10, 28. https://doi.org/10.1186/s13041-017-0306-y

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Anttila S., Huuhka K., Huuhka M., Rontu R., Hurme M., Leinonen E. 2007. Interaction between 5jHT1A and BDNF genotypes increases the risk of treatment-resistant depression. J. Neural Transm. (Vienna). 114, 1065–1068.

    Article  CAS  PubMed  Google Scholar 

  31. Ohtsuki T., Ishiguro H., Detera-Wadleigh S.D., Toyota T., Shimizu H., Yamada K., Yoshitsugu K., Hattori E., Yoshikawa T., Arinami T. 2002. Association between serotonin 4 receptor gene polymorphisms and bipolar disorder in Japanese case-control samples and the NIMH Genetics Initiative Bipolar Pedigrees. Mol. Psychiatry. 7, 954–961.

    Article  CAS  PubMed  Google Scholar 

  32. Lucas G., Rymar V.V., Du J., Mnie-Filali O., Bisgaard C., Manta S., Lambas-Senas L., Wiborg O., Haddjeri N., Piñeyro G., Sadikot A.F., Debonnel G. 2007. Serotonin(4) (5-HT(4)) receptor agonists are putative antidepressants with a rapid onset of action. Neuron. 55, 712–725.

    Article  CAS  PubMed  Google Scholar 

  33. Popova N.K., Ilchibaeva T.V., Naumenko V.S. 2017. Neurotrophic factors (BDNF and GDNF) and the serotonegic system of the brain. Biochemistry (Moscow). 82 (3), 308–317.

    CAS  PubMed  Google Scholar 

  34. Caspi A., Sugden K., Moffitt T.E., Taylor A., Craig I. W., Harrington H., McClay J., Mill J., Martin J., Braithwaite A., Poulton R. 2003. Influence of life stress on depression: Moderation by a polymorphism in the 5-HTT gene. Science. 301, 386–389.

    Article  CAS  PubMed  Google Scholar 

  35. Vinkers C.H., Joels M., Milaneschi Y., Kahn R.S., Penninx B.W., Boks M.P. 2014. Stress exposure across the life span cumulatively increases depression risk and is moderated by neuroticism. Depress. Anxiety.31, 737–745.

    Article  PubMed  Google Scholar 

  36. Landau A.M., Phan J.A., Iversen P., Lillethorup T.P., Simonsen M., Wegener G., Jakobsen S., Doudet D.J. 2015. Decreased in vivo α2 adrenoceptor binding in the Flinders Sensitive Line rat model of depression. Neuropharmacology.91, 97–102.

    Article  CAS  PubMed  Google Scholar 

  37. Seki K., Yoshida S., Jaiswal M.K. 2018. Molecular mechanism of noradrenaline during the stress-induced major depressive disorder. Neural Regen. Res. 13, 1159–1169.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Pitsillou E., Bresnehan S.M., Kagarakis E.A., Wijoyo S.J., Liang J., Hung A., Karagiannis T.C. 2020. The cellular and molecular basis of major depressive disorder: Towards a unified model for understanding clinical depression. Mol. Biol. Rep. 47, 753–770.

    Article  CAS  PubMed  Google Scholar 

  39. Belujon P., Grace A.A. 2017. Dopamine system dysregulation in major depressive disorders. Int. J. Neuropsychopharmacol. 20, 1036–1046.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Sarchiapone M., Carli V., Camardese G., Cuomo C., Di Giuda D., Calcagni M.L., Focacci C., De Risio S. 2006. Dopamine transporter binding in depressed patients with anhedonia. Psychiatry Res. 147, 243–248.

    Article  CAS  PubMed  Google Scholar 

  41. Beaulieu J.M. 2012. A role for Akt and glycogen synthase kinase-3 as integrators of dopamine and serotonin neurotransmission in mental health. J. Psychiatry Neurosci.37, 7–16.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Weng Y.T., Chien T., Kuan I.I., Chern Y. 2018. The TRAX, DISC1, and GSK3 complex in mental disorders and therapeutic interventions. J. Biomed. Sci. 25, 71. https://doi.org/10.1186/s12929-018-0473-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Costemale-Lacoste J.F., Guilloux J.P., Gaillard R. 2016. The role of GSK-3 in treatment-resistant depression and links with the pharmacological effects of lithium and ketamine: A review of the literature. Encephale. 42, 156–164.

    Article  CAS  PubMed  Google Scholar 

  44. Kram M.L., Kramer G.L., Ronan P.J., Steciuk M., Petty F. 2002. Dopamine receptors and learned helplessness in the rat: An autoradiographic study. Prog. Neuropsychopharmacol. Biol. Psychiatry. 26, 639–645.

    Article  CAS  PubMed  Google Scholar 

  45. Furuyashiki T. 2012. Roles of dopamine and inflammation-related molecules in behavioral alterations caused by repeated stress. J. Pharmacol. Sci. 120, 63–69.

    Article  CAS  PubMed  Google Scholar 

  46. Drago A., Crisafulli C., Sidoti A., Serretti A. 2011. The molecular interaction between the glutamatergic, noradrenergic, dopaminergic and serotoninergic systems informs a detailed genetic perspective on depressive phenotypes. Prog. Neurobiol.94, 418–460.

    Article  CAS  PubMed  Google Scholar 

  47. Duman R.S., Sanacora G., Krystal J.H. 2019. Altered connectivity in depression: GABA and glutamate neurotransmitter deficits and reversal by novel treatments. Neuron. 102, 75–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Kang H.J., Voleti B., Hajszan T., Rajkowska G., Stockmeier C.A., Licznerski P., Lepack A., Majik M.S., Jeong L.S., Banasr M. 2012. Decreased expression of synapse-related genes and loss of synapses in major depressive disorder. Nat. Med. 18, 1413–1417.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Li N., Liu R.J., Dwyer J.M., Banasr M., Lee B., Son H., Li X.Y., Aghajanian G., Duman R.S. 2011. Glutamate N-methyl-D-aspartate receptor antagonists rapidly reverse behavioral and synaptic deficits caused by chronic stress exposure. Biol. Psychiatry. 69, 754–761.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Banasr M., Lepack A., Fee C., Duric V., Maldonado-Aviles J., DiLeone R., Sibille E., Duman R.S., Sanacora G. 2017. Characterization of GABAergic marker expression in the chronic unpredictable stress model of depression. Chronic Stress (Thousand Oaks). 1, 10. https://doi.org/10.1177/2470547017720459

    Article  Google Scholar 

  51. Luscher B., Fuchs T. 2015. GABAergic control of depression-related brain states. Adv. Pharmacol. 73, 97–144.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Glue P., Medlicott N.J., Harland S., Neehoff S., Anderson-Fahey B., Le Nedelec M., Gra A., McNaughton N. 2017. Ketamine’s dose-related effects on anxiety symptoms in patients with treatment refractory anxiety disorders. J. Psychopharmacol. (Oxford). 31, 1302–1305.

    Article  CAS  PubMed  Google Scholar 

  53. Lesch K.P., Bengel D., Heils A., Sabol S.Z., Greenberg B.D., Petri S., Benjamin J., Muller C.R., Hamer D.H., Murphy D.L. 1996. Association of anxiety-related traits with a polymorphism in the serotonin transporter gene regulatory region. Science. 274, 1527–1531.

    Article  CAS  PubMed  Google Scholar 

  54. Xia L., Yao S. 2015. The involvement of genes in adolescent depression: A systematic review. Front. Behav. Neurosci. 9, 329. https://doi.org/10.3389/fnbeh.2015.00329

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Tsang R.S., Mather K.A., Sachdev P.S., Reppermund S. 2017. Systematic review and meta-analysis of genetic studies of late-life depression. Neurosci. Biobehav. Rev. 75, 129–139

    Article  PubMed  Google Scholar 

  56. Northoff G. 2013. Gene, brains, and environment-genetic neuroimaging of depression. Curr. Opin. Neurobiol. 23, 133–142.

    Article  CAS  PubMed  Google Scholar 

  57. Liu Y., Yu J.-T., Wang H.-F., Han P.-R., Tan C.-C., Wang C., Meng X.-F., Risacher S.L., Saykin A.J., Tan L. 2015. APOE genotype and neuroimaging markers of Alzheimer’s disease: Systematic review and meta-analysis. J. Neurol. Neurosurg. Psychiatry. 86, 127–134.

    Article  PubMed  Google Scholar 

  58. Liu R-J., Lee F.S., Li X-Y., Bambico F., Duman R.S., Aghajanian G.K. 2012. Brain-derived neurotrophic factor Val66Met allele impairs basal and ketamine-stimulated synaptogenesis in prefrontal cortex. Biol. Psychiatry. 71, 996–1005.

    Article  CAS  PubMed  Google Scholar 

  59. Piechaczek C.E., Greimel E., Feldmann L., Pehl V., Allgaier A.K., Frey M., Freisleder F.J., Halldorsdottir T., Binder E.B., Ising M., Schulte-Körne G. 2019. Interactions between FKBP5 variation and environmental stressors in adolescent major depression. Psychoneuroendocrinology. 106, 28–37.

    Article  CAS  PubMed  Google Scholar 

  60. Dalton V.S., Kolshus E., McLoughlin D.M. 2014. Epigenetics and depression: Return of the repressed. J. Affec. Disord. 155, 1–12.

    Article  Google Scholar 

  61. Chistiakov D.A., Bobryshev Y.V., Chekhonin V.P. 2017. Epigenetic alterations in DNA and histone modifications caused by depression and antidepressant drugs: Lessons from the rodent models. Curr. Pharm. Des. 23, 6828–6840.

    Article  CAS  PubMed  Google Scholar 

  62. Park C., Rosenblat J.D., Brietzke E., Pan Z., Lee Y., Cao B., Zuckerman H., Kalantarova A., McIntyre R.S. 2019. Stress, epigenetics and depression: A systematic review. Neurosci. Biobehav. Rev. 102, 139–152.

    Article  CAS  PubMed  Google Scholar 

  63. Chen D., Meng L., Pei F., Zheng Y., Leng J. 2017. A review of DNA methylation in depression. J. Clin. Neurosci. 43, 39–46.

    Article  PubMed  CAS  Google Scholar 

  64. Kim G.H., Ryan J.J., Marsboom G., Archer S.L. 2011. Epigenetic mechanisms of pulmonary hypertension. Pulm. Circ. 1, 347–356.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Gruzdev S.K., Yakovlev A.A., Druzhkova T.A., Guekht A.B., Gulyaeva N.V (2019. The missing link: How exosomes and miRNAs can help in bridging psychiatry and molecular biology in the context of depression, bipolar disorder and schizophrenia. Cell Mol. Neurobiol. 39, 729–750.

    Article  CAS  PubMed  Google Scholar 

  66. Pruunsild P., Kazantseva A., Aid T., Palm K., Timmusk T. 2007. Dissecting the human BDNF locus: Bidirectional transcription, complex splicing, and multiple promoters. Genomics. 90, 397–406.

    Article  CAS  PubMed  Google Scholar 

  67. Kang H.J., Kim J.M., Stewart R., Kim S.Y., Bae K.Y., Kim S.W., Yoon J.S. 2013). Association of SLC6A4 methylation with early adversity, characteristics and outcomes in depression. Prog. Neuropsychopharmacol. Biol. Psychiatry. 44, 23–28.

    Article  CAS  PubMed  Google Scholar 

  68. Murgatroyd C., Quinn J.P., Sharp H.M., Pickles A., Hill J. 2015. Effects of prenatal and postnatal depression, and maternal stroking, at the glucocorticoid receptor gene. Transl. Psychiatry. 5, e560. https://doi.org/10.1038/tp.2014.140

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Covington H.E. 3rd, Maze I., LaPlant Q.C., Vialou V.F., Ohnishi Y.N., Berton O., Fass D.M., Renthal W., Rush A.J. 3rd, Wu E.Y., Ghose S., Krishnan V., Russo S.J., Tamminga C., Haggarty S.J., Nestler E.J. 2009. Antidepressant actions of histone deacetylase inhibitors. J. Neurosci.29, 11451–11460.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Hobara T., Uchida S., Otsuki K., Matsubara T., Funato H., Matsuo K., Suetsugi M., Watanabe Y. 2010. Altered gene expression of histone deacetylases in mood disorder patients. J. Psychiatr. Res. 44, 263–270.

    Article  PubMed  Google Scholar 

  71. Tavakolizadeh J., Roshanaei K., Salmaninejad A., Yari R., Nahand J.S., Sarkarizi H.K., Mousavi S.M., Salarinia R., Rahmati M., Mousavi S.F., Mokhtari R., Mirzaei H. 2018. MicroRNAs and exosomes in depression: Potential diagnostic biomarkers. J. Cell. Biochem. 119, 3783–3797.

    Article  CAS  PubMed  Google Scholar 

  72. Gururajan A., Naughton M., Scott K., O’Connor R., Moloney G., Clarke G., Dowling J., Walsh A., Ismail F., Shorten G., Scott L., McLoughlin D., Cryan J., Dinan T. 2016. MicroRNAs as biomarkers for major depression: A role for Let-7b and Let-7c. Transl. Psychiatry. 6, e862. https://doi.org/10.1038/tp.2016.131

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. O’Connor R.M., Grenham S., Dinan T.G., Cryan J.F. 2013. MicroRNAs as novel antidepressant targets: Converging effects of ketamine and electroconvulsive shock therapy in the rat hippocampus. Int. J. Neuropsychopharmacol.16, 1885–1892.

    Article  PubMed  CAS  Google Scholar 

  74. Liu W., Ge T., Leng Y., Pan Z., Fan J., Yang W., Cui R. 2017. The role of neural plasticity in depression: From hippocampus to prefrontal cortex. Neural Plast. 2017, https://doi.org/10.1155/2017/6871089

  75. Levy M.J.F., Boulle F., Steinbusch H.W., van den Hove D.L.A., Kenis G., Lanfumey L. 2018. Neurotrophic factors and neuroplasticity pathways in the pathophysiology and treatment of depression. Psychopharmacology (Berl.). 235, 2195–2220.

    Article  CAS  Google Scholar 

  76. Bazovkina D.V., Kondaurova E.M., Tsybko A.S., Kovetskaya A.I., Il’chibaeva T.V., Naumenko V.S. 2017. The effects of chronic alcoholization on the expression of brain-derived neurotrophic factor and its receptors in the brains of mice genetically predisposed to depressive-like behavior. Mol. Biol. (Moscow). 51 (4), 571–578.

    Article  CAS  Google Scholar 

  77. Notaras M., van den Buuse M. 2020. Neurobiology of BDNF in fear memory, sensitivity to stress, and stress-related disorders. Mol. Psychiatry.https://doi.org/10.1038/s41380-019-0639-2

  78. Leal G., Bramham C.R., Duarte C.B. 2017. BDNF and hippocampal synaptic plasticity. Vitam. Horm. 104, 153–195.

    Article  CAS  PubMed  Google Scholar 

  79. Huang E.J., Reichardt L.F. 2003. Trk receptors: Roles in neuronal signal transduction. Annu. Rev. Biochem. 72, 609–642.

    Article  CAS  PubMed  Google Scholar 

  80. Garraway S.M., Huie J.R. 2016. Spinal plasticity and behavior: BDNF-induced neuromodulation in uninjured and injured spinal cord. Neur. Plast. 2016, https://doi.org/10.1155/2016/9857201

  81. Jin W. 2020. Regulation of BDNF-TrkB signaling and potential therapeutic strategies for Parkinson’s disease. J. Clin. Med.9 (1), 257.https://doi.org/10.3390/jcm9010257

    Article  CAS  PubMed Central  Google Scholar 

  82. Wang J.Q., Mao L. 2019. The ERK pathway: molecular mechanisms and treatment of depression. Mol. Neurobiol. 56, 6197–6205.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Lynch M.A. 2004. Long-term potentiation and memory. Physiol. Rev. 84, 87–136.

    Article  CAS  PubMed  Google Scholar 

  84. Eisch A.J., Petrik D. 2012. Depression and hippocampal neurogenesis: A road to remission? Science. 338, 72–75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Losenkov I.S., Mulder N., Levchuk L.A., Vyalova N.M., Loonen A., Bosker, F.J., Simutkin G.G., Boiko A.S., Bokhan N.A., Wilffert B., Hak E., Schmidt A.F., Ivanova S.A. 2020. Association between BDNF gene variant Rs6265 and the severity of depression in antidepressant treatment-free depressed patients. Front. Psychiatry. 11, 38. https://doi.org/10.3389/fpsyt.2020.00038

    Article  PubMed  PubMed Central  Google Scholar 

  86. Ivanova S.A., Losenkov I.N., Levchuk L.A., Boiko A.N., Vyalova N.M., Simutkin G.G., Bokhan N.A. 2018. Depressivnye rasstroistva: gipotezy patogeneza i potentsial’nye biologicheskie markery (Depressive Disorders: Hypotheses of Pathogenesis and Poyential Biological Markers). Moscow: Ross. Akad. Nauk.

  87. Chourbaji S., Brandwein C., Gass P. 2011. Altering BDNF expression by genetics and/or environment: impact for emotional and depression-like behaviour in laboratory mice. Neurosci. Biobehav. Rev. 35, 599–611.

    Article  CAS  PubMed  Google Scholar 

  88. Evans S.J., Choudary P.V., Neal C.R., Li J.Z., Vawter M.P., Tomita H. 2004. Dysregulation of the fibroblast growth factor system in major depression, Proc. Natl. Acad. Sci. U. S. A.101, 15506–15511.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Elsayed M., Banasr M., Duric V., Fournier N.M., Licznerski P., Duman R.S. 2012. Antidepressant effects of fibroblast growth factor-2 in behavioral and cellular models of depression. Biol. Psychiatry. 72, 258–265.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Angelucci F., Aloe L., Jimenez-Vasquez P., Mathe A.A. 2003). Electroconvulsive stimuli alter nerve growth factor but not brainderived neurotrophic factor concentrations in brains of a rat model of depression. Neuropeptides.37, 51–56.

    Article  CAS  PubMed  Google Scholar 

  91. Jeon S.W., Kim Y.K. 2017. Inflammation-induced depression: Its pathophysiology and therapeutic implications. J. Neuroimmunol. 313, 92–98.

    Article  CAS  PubMed  Google Scholar 

  92. Wohleb E.S., Franklin T., Iwata M., Duman R.S. 2016. Integrating neuroimmune systems in the neurobiology of depression. Nat. Rev. Neurosci. 17, 497–511.

    Article  CAS  PubMed  Google Scholar 

  93. Zhan Y., Paolicelli R.C., Sforazzini F., Weinhard L., Bolasco G., Pagani F., Vyssotski A.L., Bifone A., Gozzi A., Ragozzino D., Gross C.T. 2014. Deficient neuron–microglia signaling results in impaired functional brain connectivity and social behavior. Nat. Neurosci.17, 400–406.

    Article  CAS  PubMed  Google Scholar 

  94. Musselman D.L., Lawson D.H., Gumnick J.F., Manatunga A.K., Penna S., Goodkin R.S., Greiner K., Nemeroff C.B., Miller A.H. 2001. Paroxetine for the prevention of depression induced by high-dose interferon alfa. N. Engl. J. Med. 344, 961–966.

    Article  CAS  PubMed  Google Scholar 

  95. Franklin T.C., Xu C., Duman R.S. 2018. Depression and sterile inflammation: Essential role of danger associated molecular patterns. Brain Behav. Immun. 72, 2–13.

    Article  CAS  PubMed  Google Scholar 

  96. Trottier M.D., Newsted M.M., King L.E., Fraker, P.J. 2008. Natural glucocorticoids induce expansion of all developmental stages of murine bone marrow granulocytes without inhibiting function. Proc. Natl. Acad. Sci. U. S. A.105, 2028–2033.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Milenkovic V.M., Stanton E.H., Nothdurfter C., Rupprecht R., Wetzel C.H. 2013. The role of chemokines in the pathophysiology of major depressive disorder. Int. J. Mol. Sci. 20, 2283.https://doi.org/10.3390/ijms20092283

    Article  CAS  Google Scholar 

  98. Kierdorf K., Prinz M. 2013. Factors regulating microglia activation. Front. Cell. Neurosci.7, 44. https://doi.org/10.3389/fncel.2013.00044

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Guo H., Callaway J.B., Ting J.P. 2015. Inflammasomes: Mechanism of action, role in disease, and therapeutics. Nat. Med.21, 677–687.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  100. Kulmatycki K.M., Jamali F. 2005. Drug disease interactions: Role of inflammatory mediators in disease and variability in drug response. J. Pharm. Pharm. Sci. 8, 602–625.

    CAS  PubMed  Google Scholar 

  101. Black C.N., Bot M., Scheffer P.G., Cuijpers P., Penninx B.W. 2015. Is depression associated with increased oxidative stress? A systematic review and meta-analysis. Psychoneuroendocrinology. 51, 164–175.

    Article  CAS  PubMed  Google Scholar 

  102. Gorlova A.V., Zorkina Ya.A., Zubkov E.A., Morozova A.Yu., Inozemtsev A.N., Chekhonin V.P. 2019. Alteration of oxidative stress markers and behavior of rats in a novel model of depression. Acta Neurobiol. Exp. (Wars.). 79, 232–237

    Google Scholar 

  103. Moylan S., Berk M., Dean O.M., Samuni Y., Williams L.J., O’Neil A., Hayley A.C., Pasco J. A., Anderson G., Jacka F.N., Maes M. 2014. Oxidative and nitrosative stress in depression: Why so much stress? Neurosci. Biobehav. Rev. 45, 46–62.

    Article  CAS  PubMed  Google Scholar 

  104. Yager S., Forlenza M.J., Miller G.E. 2010. Depression and oxidative damage to lipids. Psychoneuroendocrinology. 35, 1356–1362.

    Article  CAS  PubMed  Google Scholar 

  105. Maes M., Galecki P., Chang Y.S., Berk M. 2011. A review on the oxidative andnitrosative stress (O&NS) pathways in major depression and their possible contribution to the neurodegenerative processes in that illness. Prog. Neuropsychopharmacol. Biol. Psychiatry. 35, 676–692.

    Article  CAS  PubMed  Google Scholar 

  106. Wigner P., Czarny P., Galecki P., Su K.P., Sliwinski T. 2018. The molecular aspects of oxidative and nitrosative stress and the tryptophan catabolites pathway (TRYCATs) as potential causes of depression. Psychiatry Res. 262, 566–574.

    Article  CAS  PubMed  Google Scholar 

  107. Schubert D., Piasecki D. 2001. Oxidative glutamate toxicity can be a component ofthe excitotoxicity cascade. J. Neurosci. 21, 7455–7462.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Howard D.M., Adams M.J., Clarke T.K., Hafferty J.D., Gibson J., Shirali M., Coleman J.R.I., Hagenaars S.P., Ward J., Wigmore E.M., Alloza C., Shen X., Barbu M.C., Xu E.Y., Whalley H.C., et al. 2019. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat. Neurosci. 22, 343–352.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Grace A.A. 2016. Dysregulation of the dopamine system in the pathophysiology of schizophrenia and depression. Nat. Rev. Neurosci. 17, 524–532.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Buzsaki G., Draguhn A. 2004. Neuronal oscillations in cortical networks. Science.304, 1926–1929.

    Article  CAS  PubMed  Google Scholar 

  111. Bora E., Fornito A., Pantelis C., Yucel M. 2012. Gray matter abnormalities in major depressive disorder: A meta-analysis of voxel based morphometry studies. J. Affect. Disord. 138, 9–18.

    Article  PubMed  Google Scholar 

  112. Herman J.P., Mueller N.K. 2016. Role of the ventral subiculum in stress integration. Behav. Brain Res.174, 215–224.

    Article  CAS  Google Scholar 

  113. Marchand W.R., Lee J.N., Thatcher G.W., Jensen C., Stewart D., Dilda V., Thatcher J., Creem-Regehr S.H. 2007. A functional MRI study of a paced motor activation task to evaluate frontalsubcortical circuit function in bipolar depression. Psychiatry Res.1553, 221–230.

    Article  Google Scholar 

  114. Hibar D.P., Westlye L.T., van Erp T.G., Rasmussen J, Leonardo C.D., Faskowitz J., Haukvik U.K., Hartberg C.B., Doan N.T., Agartz I., Dale A.M., Gruber O., Krämer B., Trost S., Liberg B., et al. 2016. Subcortical volumetric abnormalities in bipolar disorder. Mol. Psychiatry. 21, 1710–1716.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Sacuiu S., Eckerström M., Johansson L., Kern S., Sigström R., Xinxin G., Östling S., Skoog I. 2018. Increased risk of dementia in subjective cognitive decline if CT crain changes are present. J. Alzheimers Dis. 66, 483–495.

    Article  PubMed  PubMed Central  Google Scholar 

  116. Wen C., Chan L.L., Tan L.C., Tan E.K. 2016. Depression, anxiety, and apathy in Parkinson’s disease: Insights from neuroimaging studies. Eur. J. Neurol.23, 1001–1019.

    Article  PubMed  Google Scholar 

  117. Girshkin L., Matheson S.L., Shepherd A., Green M.J. 2017. Morning cortisol levels in schizophrenia and bipolar disorder: A meta-analysis. Psychoneuroendocrinology.49, 187–206.

    Article  CAS  Google Scholar 

  118. Karanikas E., Garyfallos G. 2015. Role of cortisol in patients at risk for psychosis mental state and psychopathological correlates: A systematic review. Psychiatry Clin. Neurosci. 69, 268–282.

    Article  PubMed  Google Scholar 

  119. Ouanes S., Popp J. 2019. High cortisol and the risk of dementia and Alzheimer’s disease: A review of the literature. Front. Aging Neurosci. 11, 43. https://doi.org/10.3389/fnagi.2019.00043

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Bao A.M., Meynen G., Swaab D.F. 2008. The stress system in depression and neurodegeneration: Focus on the human hypothalamus. Brain Res. Rev. 57, 531–553.

    Article  CAS  PubMed  Google Scholar 

  121. Soares N., Pereira G.M., Altmann V., de Almeida R.M., Rieder C.R. 2019. Cortisol levels, motor, cognitive and behavioral symptoms in Parkinson’s disease: A systematic review. J. Neural. Transm. (Vienna). 126, 219–232.

    Article  Google Scholar 

  122. Santos L.E., Beckman D., Ferreira S.T. 2016. Micro-glial dysfunction connects depression and Alzheimer’s disease. Brain Behav. Immun. 55, 151–165.

    Article  CAS  PubMed  Google Scholar 

  123. Fillman S., Cloonan N., Catts V., Miller L.C., Wong J., McCrossin T., Cairns M., Weickert C.S. 2013. Increased inflammatory markers identified in the dorsolateral prefrontal cortex of individuals with schizophrenia. Mol. Psychiatry. 18, 206–214.

    Article  CAS  PubMed  Google Scholar 

  124. Miller B.J., Buckley P., Seabolt W., Mellor A., Kirkpatrick B. 2011. Meta-analysis of cytokine alterations in schizophrenia: Clinical status and antipsychotic effects. Biol. Psychiatry.70, 663–671.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Benedetti F., Aggio V., Pratesi M.L., Greco G., Furlan R. 2020. Neuroinflammation in bipolar depression. Front. Psychiatry. 11, 71. https://doi.org/10.3389/fpsyt.2020.00071

    Article  PubMed  PubMed Central  Google Scholar 

  126. Kunz M., Cereser K.M., Goi P.D. 2011. Serum levels of IL-6, IL-10 and TNF-alpha in patients with bipolar disorder and schizophrenia: Differences in pro- and anti-inflammatory balance. Rev. Bras. Psiquiatr. 333, 268–274.

    Google Scholar 

  127. Calsolaro V., Edison P. 2016. Neuroinflammation in Alzheimer’s disease: Current evidence and future directions. Alzheimers Dement. 12, 719–732.

    Article  PubMed  Google Scholar 

  128. De Virgilio A., Greco A., Fabbrini G., Inghilleri M., Rizzo M.I., Gallo A., Conte M., Rosato C., Ciniglio Appiani M., de Vincentiis M. 2016. Parkinson’s disease: Autoimmunity and neuroinflammation. Autoimmun. Rev. 15, 1005–1011.

    Article  PubMed  CAS  Google Scholar 

  129. Peng S., Li W., Lv L., Zhang Z., Zhan X. 2018. BDNF as a biomarker in diagnosis and evaluation of treatment for schizophrenia and depression. Discov. Med. 26, 127–136.

    PubMed  Google Scholar 

  130. Barbosa I.G., Huguet R.B., Sousa L.P. 2011. Circulating levels of GDNF in bipolar disorder. Neurosci Lett. 5022, 103–106.

    Article  CAS  Google Scholar 

  131. Barbosa I.G., Rocha N.P., Miranda A.S., Huguet R.B., Bauer M.E., Reis H.J., Teixeira, A.L. 2013. Increased BDNF levels in long-term bipolar disorder patients. Rev. Bras. Psiquiatr. 351, 67–69.

    Article  Google Scholar 

  132. Kraft A.D., McPherson C.A., Harry G.J. 2009. Heterogeneity of microglia and TNF signaling as determinants for neuronal death or survival. Neurotoxicology. 305, 785–793.

    Article  CAS  Google Scholar 

  133. Sampaio T.B., Savall A.S., Gutierrez M.E.Z., Pinton S. 2017. Neurotrophic factors in Alzheimer’s and Parkinson’s diseases: Implications for pathogenesis and therapy. Neural Regen. Res. 12, 549–557.

    Article  PubMed  PubMed Central  Google Scholar 

  134. Valero J., Bernardino L., Cardoso F.L., Silva A.P., Fontes-Ribeiro C., Ambrósio A.F., Malva J.O. 2017. Impact of neuroinflammation on hippocampal neurogenesis: Relevance to aging and Alzheimer’s disease. J. Alzheimers Dis.60, 161–168.

    Article  CAS  Google Scholar 

  135. Lim J., Bang Y., Choi H.J. 2018. Abnormal hippocampal neurogenesis in Parkinson’s disease: Relevance to a new therapeutic target for depression with Parkinson’s disease. Arch. Pharm. Res. 41, 943–954.

    Article  CAS  PubMed  Google Scholar 

  136. Zorkina Ya.A., Morozova A.Yu., Andreyuk D.S. 2019. Prospects for using molecular genetic methods in studies on the pathophysiology of schizophrenia. Psikhich.Zdorov’e. 12, 26–33.

    Google Scholar 

  137. Ikeda M., Saito T., Kondo K., Iwata N. 2018. Genome-wide association studies of bipolar disorder: A systematic review of recent findings and their clinical implications. Psychiatry Clin. Neurosci. 72, 52–63.

    Article  PubMed  Google Scholar 

  138. Marioni R.E., Harris S.E., Zhang Q, McRae A.F., Hagenaars S.P., Hill W.D., Davies G., Ritchie C.W., Gale C.R., Starr J.M., Goate A.M., Porteous D.J., Yang J., Evans K.L., Deary I.J., et al. 2019. GWAS on family history of Alzheimer’s disease. Transl. Psychiatry. 9, 161.https://doi.org/10.1038/s41398-018-0150-6

    Article  PubMed  PubMed Central  Google Scholar 

  139. Chang D., Nalls M.A., Hallgrímsdóttir I.B., Hunkapiller J., van der Brug M., Cai F.; International Parkinson’s Disease Genomics Consortium; 23andMe Research Team, Kerchner G.A., Ayalon G., Bingol B., Sheng M., Hinds D., Behrens T.W., Singleton A.B., Bhangale T.R., Graham R.R. 2017. A meta-analysis of genome-wide association studies identifies 17 new Parkinson’s disease risk loci. Nat. Genet. 49, 1511–1516.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  140. Amare A.T., Vaez A., Hsu Y.H., Direk N., Kamali Z., Howard D.M., McIntosh A.M., Tiemeier H., Bültmann U., Snieder H., Hartman C.A. 2019. Bivariate genome-wide association analyses of the broad depression phenotype combined with major depressive disorder, bipolar disorder or schizophrenia reveal eight novel genetic loci for depression. Mol. Psychiatry. 1, 18–33.

    Google Scholar 

  141. Wray N.R., Ripke S., Mattheisen M., Trzaskowski M., Byrne E.M., Abdellaoui A. Adams M.J., Agerbo E., Air T.M., Andlauer T.M.F., Bacanu S.A., Bækvad-Hansen M., Beekman A.F.T., Bigdeli T.B., Binder E.B., et al. 2018. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat. Genet.50, 668–681.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  142. Hyde C.L., Nagle M.W., Tian C., Chen X., Paciga S.A., Wendland J.R., Tung J.Y., Hinds D.A., Perlis R.H., Winslow A.R. 2016. Identification of 15 genetic loci associated with risk of major depression in individuals of European descent. Nat. Genet. 48, 1031–1036.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  143. Frey B.N., Fonseca M., Machado-Vieira R., Soares J.C., Kapczinski F. 2004. Neuropathological and neurochemical abnormalities in bipolar disorder. Rev. Bras. Psiquiatr. 26, 180–188.

    Article  PubMed  Google Scholar 

  144. Goldstein B.I., Kemp D.E., Soczynska J.K., McIntyre R.S. 2009. Inflammation and the phenomenology, pathophysiology, comorbidity, and treatment of bipolar disorder: A systematic review of the literature. J. Clin. Psychiatry. 708, 1078–1090.

    Article  Google Scholar 

  145. Petersen J.D., Waldorff F.B., Siersma V.D., Phung T.K.T., Bebe A.C.K.M., Waldemar, G. 2017. Major depressive symptoms increase 3-year mortality rate in patients with mild dementia. Int. J. Alzheimers. Dis. 21, 45–58.

    Google Scholar 

  146. Trillo L., Das D., Hsieh W., Medina B., Moghadam S., Lin B., Dang V., Sanchez M.M., De Miguel Z., Ashford J.W., Salehi A. 2013. Ascending monoaminergic systems alterations in Alzheimer’s disease: Translating basic science into clinical care. Neurosci. Biobehav. Rev. 37, 1369–1379.

    Article  CAS  Google Scholar 

  147. Dong H., Murphy K.M., Meng L., Montalvo-Ortiz J., Zeng Z., Kolber B.J., Zhang S., Muglia L.J., Csernansky J.G. 2012. Corticotrophin releasing factor accelerates neuropathology and cognitive decline in a mouse model of Alzheimer’s disease. J. Alzheimers. Dis.28, 579–592.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  148. Glass C.K., Saijo K., Winner B., Marchetto M.C., Gage F.H. 2010. Mechanisms underlying inflammation in neurodegeneration. Cell.140, 918–934.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  149. Wuwongse S., Chang R.C.C., Law A.C.K. 2010. The putative neurodegenerative links between depression and Alzheimer’s disease. Prog. Neurobiol.12, 32–57.

    Google Scholar 

  150. Chhibber A., Zhao L. 2017. ER β and ApoE isoforms interact to regulate BDNF–5-HT 2A signaling and synaptic function in the female brain. Alzheimers. Res. Ther.21, 9–49.

    Google Scholar 

  151. Leentjens A.F. 2015. Parkinson disease: Depression— risk factor or early symptom in Parkinson disease? Nat. Rev. Neurol.18, 432–433.

    Article  Google Scholar 

  152. Olivola E., Pierantozzi M., Imbriani P., Liguori C., Stampanoni Bassi M., Conti M., D’Angelo V., Mercuri N.B., Stefani A. 2014. Serotonin impairment in CSF of PD patients, without an apparent clinical counterpart. PLoS One. 9. https://doi.org/10.1371/journal.pone.0101763

  153. Borgonovo J., Allende-Castro C., Laliena A., Guerrero N., Silva, H., Concha M.L., Guerrero E., An Silva H., Concha M.L. 2017. Changes in neural circuitry associated with depression at pre-clinical, pre-motor and early motor phases of Parkinson’s disease. Parkinsonism Relat. Disord.35, 17–24.

    Article  PubMed  Google Scholar 

  154. Remy P., Doder M., Lees A., Turjanski N., Brooks D. 2005). Depression in Parkinson’s disease: Loss of dopamine and noradrenaline innervation in the limbic system. Brain.128, 1314–1322.

    Article  PubMed  Google Scholar 

  155. Wang Y., Liu H., Du X.D., Zhang Y., Yin G., Zhang B.S., Soares J.C., Zhang X.Y. 2017. Association of low serum BDNF with depression in patients with Parkinson’s disease. Parkinsonism Relat. Disord. 41, 73–78.

    Article  PubMed  Google Scholar 

  156. Foltynie T., Sawcer S., Brayne C., Barker R.A. 2002. The genetic basis of Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry.73, 363–370.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  157. Burn D.J., Tiangyou W., Allcock L.M., Davison J., Chinnery P.F. 2006. Allelic variation of a functional polymorphism in the serotonin transporter gene and depression in Parkinson’s disease. Parkinsonism Relat. Disord. 12, 139–141.

    Article  PubMed  Google Scholar 

  158. Gören J.L. 2016. Brain-derived neurotrophic factor and schizophrenia. Ment. Health Clin. 6, 285–288.

    Article  PubMed  PubMed Central  Google Scholar 

  159. Toll A., Mane A. 2015. Brain-derived neurotrophic factor levels in first episode psychosis: A systematic review. World J. Psychiatry.5, 154–159.

    Article  PubMed  PubMed Central  Google Scholar 

  160. Zhang X.Y., Chen D.C., Xiu M.H., Haile C.N., Luo X., Xu K. 2012. Cognitive and serum BDNF correlates of BDNF Val66Met gene polymorphism in patients with schizophrenia and normal controls. Hum. Genet. 131, 1187–1195.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  161. Miranda M., Morici J.F., Zanoni M.B., Bekinschtein P. 2019. Brain-derived neurotrophic factor: A key molecule for memory in the healthy and the pathological brain. Front. Cell Neurosci. 13, 363. https://doi.org/10.3389/fncel.2019.00363

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  162. Slattery D.A., Cryan J.F. 2014. The ups and downs of modelling mood disorders in rodents. ILAR. J. 55, 297–309.

    Article  CAS  PubMed  Google Scholar 

  163. Jacobsen J.P., Medvedev I.O., Caron M.G. 2012. The 5-HT deficiency theory of depression: Perspectives from a naturalistic 5-HT deficiency model, the tryptophan hydroxylase 2Arg439His knockin mouse. Philos. Trans. R. Soc. Lond. B.367, 2444–2459.

    Article  CAS  Google Scholar 

  164. Morozova A., Zubkov E., Strekalova T., Kekelidze Z., Storozeva Z., Schroeter C., Bazhenova N., Lesch K., Cline B., Chekhonin V. 2016. Ultrasound of alternating frequencies and variable emotional impact evokes depressive syndrome in mice and rats. Prog. Neuropsychopharmacol. Biol. Psychiatry. 68, 52–63.

    Article  PubMed  Google Scholar 

  165. Zorkina Y.A., Zubkov E.A., Morozova A.Y., Ushakova V.M., Chekhonin V.P. 2019. The comparison of a new ultrasound-induced depression model to the chronic mild stress paradigm. Front. Behav. Neurosci. 13, 146. https://doi.org/10.3389/fnbeh.2019.00146

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  166. Ushakova V.M., Gorlova A.V., Zubkov E.A., Morozova A.Yu., Zorkina Ya.A., Pavlov D.A., Inozemtsev A.N., Chekhonin V.P. 2019. Experimental models of depressive state. Zh. Vyssh. Nerv. Deyat.im.I.P. Pavlova.69, 230–247.

    Google Scholar 

  167. Jarosik J., Legutko B., Unsicker K., von Bohlen und Halbach O. 2007. Antidepressant-mediated reversal of abnormal behavior and neurodegeneration in mice following olfactory bulbectomy. Exp. Neurol. 204, 20–28.

    Article  CAS  PubMed  Google Scholar 

  168. Sarkisova K.Yu., Kulikov M.A., Kudrin V.S., Narke-vich V.B, Midzyanovskaya I.S., Biryukova L.M., Folomkina A.A., Bazyan A.S. 2013. Neurochemical mechanisms of depressive-like behavior in WAG/RIJ rats. Zh. Vyssh. Nerv. Deyat.im.I.P. Pavlova. 63, 303–315.

    Google Scholar 

  169. Navabpour S., Kwapis J.L., Jarome T.J. 2020. A neuroscientist’s guide to transgenic mice and other genetic tools. Neurosci. Biobehav. Rev. 108, 732–748.

    Article  PubMed  Google Scholar 

  170. Evans M.J., Kaufman M.H. 1981. Establishment in culture of pluripotential cells from mouse embryos. Nature. 292, 154–156.

    Article  CAS  PubMed  Google Scholar 

  171. Mortensen R. 2011. Production of a heterozygous mutant cell line by homologous recombination (single knockout). Curr. Protoc. Neurosci. Ch.4. https://doi.org/10.1002/0471142301.ns0430s55

  172. Babinet C., Morello D., Renard J.P. 1989. Transgenic mice. Genome. 31, 938–949.

    Article  CAS  PubMed  Google Scholar 

  173. Achterberg K.G., Buitendijk G.H., Kool M.J., Goorden S.M., Post L., Slump D.E., Silva A.J., van Woerden G.M., Kushner S.A., Elgersma Y. 2014. Temporal and region-specific requirements of alpha CaMKII in spatial and contextual learning. J. Neurosci.34, 11180–11187.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  174. Orban P.C., Chui D., Marth J.D. 1992. Tissue- and site-specific DNA recombination in transgenic mice. Proc. Natl. Acad. Sci. U. S. A.89, 6861–6865.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  175. Kim H., Kim M., Im S.K., Fang S. 2018. Mouse Cre-LoxP system: General principles to determine tissue-specific roles of target genes. Lab. Anim. Res. 34, 147–159.

    Article  PubMed  PubMed Central  Google Scholar 

  176. Canavello P.R., Egan R.J., Bergner C.L., Hart P.C., Cachat J.M., Kalueff A.V. 2009. Genetic animal models of depression. Neurometh. 44, 191–200.

    Article  CAS  Google Scholar 

  177. Chourbaji S., Gass P. 2008. Glucocorticoid receptor transgenic mice as models for depression. Brain Res. Rev. 57, 554–560.

    Article  CAS  PubMed  Google Scholar 

  178. Knott G.J., Doudna J.A. 2018. CRISPR-Cas guides the future of genetic engineering. Science. 361, 866–869.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  179. Hussain W., Mahmood T., Hussain J., Ali N., Shah T., Qayyum S., Khan I. 2019. CRISPR/Cas system: A game changing genome editing technology, to treat human genetic diseases. Gene. 685, 70–75.

    Article  CAS  PubMed  Google Scholar 

  180. Zhang F., Wen Y., Guo X. 2014. CRISPR/Cas9 for genome editing: Progress, implications and challenges. Hum. Mol. Genet. 23, 40–46.

    Article  PubMed  CAS  Google Scholar 

  181. Adli M. 2018. The CRISPR tool kit for genome editing and beyond. Nat. Commun. 9, 1911. https://doi.org/10.1038/s41467-018-04252-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  182. Rost B.R., Schneider-Warme F., Schmitz D., Hegemann P. 2017. Optogenetic tools for subcellular applications in neuroscience. Neuron. 96, 572–603.

    Article  CAS  PubMed  Google Scholar 

  183. Leopold A.V., Chernov K.G., Verkhusha V.V. 2018. Optogenetically controlled protein kinases for regulation of cellular signaling. Chem. Soc. Rev. 47, 2454–2484.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  184. Biselli T., Lange S.S., Sablottny L., Steffen J., Walther A. 2019. Optogenetic and chemogenetic insights into the neurocircuitry of depression-like behaviour: A systematic review. Eur. J. Neurosci. https://doi.org/10.1111/ejn.14603

  185. Boyden E.S., Zhang F., Bamberg E., Nagel G., Deisseroth K. 2005. Millisecond-timescale, genetically 719 targeted optical control of neural activity. Nat. Neurosci. 8, 1263–1268.

    Article  CAS  PubMed  Google Scholar 

  186. Muir J., Lopez J., Bagot R.C. 2019. Wiring the depressed brain: Optogenetic and chemogenetic circuit interrogation in animal models of depression. Neuropsychopharmacology. 44, 1013–1026.

    Article  PubMed  Google Scholar 

  187. Roth B.L. 2016. DREADDs for neuroscientists. Neuron.89, 683–694.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  188. Teissier A., Magueresse C.L., Olusakin J., Costa B.L.S.A. da, Stasi A.M.D., Bacci A., Kawasawa Y.I., Vaidya V.A., Gaspar P. 2019. Early-life stress impairs postnatal oligodendrogenesis and adult emotional behaviour through activity-dependent mechanisms. Mol. Psychiatry. 25, 1159–1174. https://doi.org/10.1038/s41380-019-0493-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  189. Cheng J., Umschweif G., Leung J., Sagi Y., Greengard P. 2019. HCN2 channels in cholinergic interneurons of nucleus accumbens shell regulate depressive behaviors. Neuron. 101, 662–672.

    Article  CAS  PubMed  Google Scholar 

  190. Leopold A.V., Chernov K.G., Shemetov A.A., Verkhusha V.V. 2019. Neurotrophin receptor tyrosine kinases regulated with near-infrared light. Nat. Commun. 10, 1129. https://doi.org/10.1038/s41467-019-08988-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  191. McIntosh A.M., Sullivan P.F., Lewis C.M. 2019. Uncovering the genetic architecture of major depression. Neuron. 102, 91–103.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  192. Mullins N., Lewis C.M. 2017. Genetics of depression: Progress at last. Curr. Psychiatry Rep. 19, 43. https://doi.org/10.1007/s11920-017-0803-9

    Article  PubMed  PubMed Central  Google Scholar 

  193. Maul S., Giegling I., Fabbri C., Corponi F., Serretti A., Rujescu D. 2020. Genetics of resilience: Implications from genome-wide association studies and candidate genes of the stress response system in posttraumatic stress disorder and depression. Am. J. Med. Genet. B. Neuropsychiatr. Genet. 183, 77–94.

    Article  CAS  PubMed  Google Scholar 

  194. Ripke S., Wray N.R., Lewis C.M., Hamilton S.P., Weissman M.M., Breen G., Byrne E.M., Blackwood D.H., Boomsma D.I., Cichon S., Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium, Heath A.C., Holsboer F., Lucae S., et al. 2013. A mega-analysis of genome-wide association studies for major depressive disorder. Mol. Psychiatry.18, 497–511.

    Article  CAS  PubMed  Google Scholar 

Download references

Funding

This work was supported by the Russian Foundation for Basic Research (project no. 19-115-50458).

Author information

Authors and Affiliations

  1. Serbsky National Medical Research Center of Psychiatry and Narcology, 119034, Moscow, Russia

    V. M. Ushakova, A. Yu. Morozova & V. P. Chekhonin

  2. Moscow State University, 119234, Moscow, Russia

    V. M. Ushakova

  3. Moscow State University of Food Production, 125080, Moscow, Russia

    A. M. Reznik

  4. Alekseev Psychiatric Clinical Hospital no. 1, 117152, Moscow, Russia

    A. Yu. Morozova & G. P. Kostyuk

  5. Pirogov Russian National Research Medical University, 117997, Moscow, Russia

    V. P. Chekhonin

Authors
  1. V. M. Ushakova
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Yu. Morozova
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. A. M. Reznik
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. G. P. Kostyuk
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. V. P. Chekhonin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to V. M. Ushakova.

Ethics declarations

Conflict of interests. The authors declare that they have no conflict of interest.

This work does not contain any studies involving animals or human subjects performed by any of the authors.

Additional information

Translated by T. Tkacheva

Abbreviations: Akt, RAC-α serine/threonine-protein kinase; APOE, apolipoprotein E; BDNF, brain-derived neurotrophic factor; CaMKII, Ca2+/calmodulin-dependent protein kinase 2; CREB, cAMP response element binding protein; CSF1, colony-stimulating factor 1; CX3CL1, C-X3-C motif chemokine ligand 1 (fractalkine); DAMP, damage-associated molecular pattern; ERK, extracellular signal-regulated kinase; FKBP51, FK506 binding protein 51; GDNF, glial cell-derived growth factor; GR, glucocorticoid receptor; HAT, histone acetyltransferase; HDAC, histone deacetylase; HES5, Hes family transcription factor 5; LC, locus coereleus; LTD, long-term depression; LTP, long-term potentiation; MAPK, mitogen-activated protein kinase; MEK, MAPK/ERK kinase; mTOR, mammalian target of rapamycin; NGF, nerve growth factor; NUDR/DEAF-1, deformed epidermal autoregulatory factor 1 homolog; PAMP, pathogen-associated molecular pattern; PDK1, phosphoinositide-dependent kinase 1; PKA, protein kinase A; PKC, protein kinase C; PLCγ, phospholipase Cγ; SERT, serotonin transporter; SNP, single-nucleotide polymorphism; TGF-β, transforming growth factor β; TNF-α, tumor necrosis factor α; VEGF, vascular endothelial growth factor; AD, Alzheimer’s disease; BAD, bipolar affective disorder; PD, Parkinson disease; HPA, hypothalamic–pituitary–adrenal (axis); MAOA, monoamine oxidase A; MRI, magnetic resonance imaging; PET, positron emission tomography; CUMS, chronic unpredictable mild stress; CNS, central nervous system.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ushakova, V.M., Morozova, A.Y., Reznik, A.M. et al. Molecular Biological Aspects of Depressive Disorders: A Modern View. Mol Biol 54, 639–660 (2020). https://doi.org/10.1134/S0026893320050118

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0026893320050118

Keywords:

Search

Navigation