Modern Psychiatry: from Theory to Practice
https://doi.org/10.52667/2712-9179-2024-4-4-11-25
Abstract
In this review scientific papers published on eLibrary, PubMed, Google Scholar were searched and analyzed for all time till 2024 year on the problem of neuropsychiatry, translational neuro-science, biomarkers. The issues of precision psychiatry and targeted therapy of mental disorders are considered. The ways of bridging the gap between theoretical and practical (clinical) psychiatry are discussed.
About the Author
N. N. Petrova
St. Petersburg State University
Russian Federation
Russian Federation
Nataliia N. Petrova
Saint Petersburg
References
1. Whiteford, H.A.; Degenhardt, L.; Rehm, J.; et al. Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010. Lancet. 2013, 382(9904):1575-1586. https://doi.org/10.1016/S0140-6736(13)61611-6.
2. World Health Organization. Depression: Fact Sheet (updated Feb 2017). WHO, 2018. (http://www.who.int/mediacentre/factsheets/fs369/en/).
3. Chang, C.K.; Hayes, R.D.; Perera, G.; et al. Life expectancy at birth for people with serious mental illness and other major disorders from a secondary mental health care case register in London. PLoS One. 2011, 6(5):e19590. https://doi.org/10.1371/journal.pone.0019590.
4. Teng, A.; Taylor, Z.; Pfeffer, J.; Williams, L.M. Using longitudinal prescription data to examine the incidence of other chronic diseases following antidepressant use. J Psychiatric Research. 2020, 125:7-12. https://doi.org/10.1016/j.jpsychires.2020.02.030.
5. Huhn, M.; Tardy, M.; Spineli, L.M.; et al. Efficacy of pharmacotherapy and psychotherapy for adult psychiatric disorders: a systematic overview of meta-analyses. JAMA Psychiatry. 2014, 71(6):706-15. https://doi.org/10.1001/jamapsychiatry.2014.112.
6. Kahn, R.S.; Sommer, I.E.; Murray, R.M.; Meyer-Lindenberg, A.; Weinberger, D.R.; Cannon, T.D.; O'Donovan, M.; Correll, C.U.; Kane, J.M.; van, Os. J.; Insel, T.R. Schizophrenia. Nat Rev Dis Primers. 2015, 1:15067. doi: 10.1038/nrdp.2015.67.
7. Berton, O.; Nestler, E.J. New approaches to antidepressant drug discovery: beyond monoamines. Nat Rev Neurosci. 2006, 7(2):137-51. https://doi.org/10.1038/nrn1846.
8. Agid, Y.; Buzsáki, G.; Diamond, D.M.; et al. How can drug discovery for psychiatric disorders be improved? Nat Rev Drug Discov. 2007, 6(3):189-201. https://doi.org/10.1038/nrd2217.
9. Stephan, K.E.; Bach, D.R.; Fletcher, P.C.; et al. Charting the landscape of priority problems in psychiatry, part 1: classification and diagnosis. Lancet Psychiatry. 2016, 3(1):77-83. https://doi.org/10.1016/S2215-0366(15)00361-2.
10. Stephan, K.E.; Binder, E.B.; Breakspear, M.; et al. Charting the landscape of priority problems in psychiatry, part 2: pathogenesis and aetiology. Lancet Psychiatry. 2016, 3(1):84-90. https://doi.org/10.1016/S2215-0366(15)00360-0.
11. Marazziti, D. Biomarkers and Emerging Drug Targets in Neuropsychiatry (Part I). Curr Med Chem. 2022, 29(35):5583. https://doi.org/10.2174/092986732935220907150412.
12. Shulman, R.G. Neuroscience: A multidisciplinary, multilevel field. In: Shulman RG editor. Brain Imaging: What it Can (and Cannot) Tell Us About Consciousness. New York: Oxford University Press. 2013, 59-74.
13. Ogawa, H.; Oka, K. Methods in Neuroethological Research. Tokyo: Springer. 2013.
14. Tanner, K.D. Issues in Neuroscience Education: Making Connections. CBE Life Sci Educ. 2006, 5(2):85. https://doi.org/10.1187/cbe.06-04-0156.
15. Kandel, E.; Koester, J.D.; Mack, S.H.; Siegelbaum, S. Principles of Neural Science. 6th ed. New York: McGraw-Hill Education, 2021.
16. Samancı, B.M.; Yıldızhan, E.; Tüzün, E. Neuropsychiatry in the Century of Neuroscience. Noro Psikiyatr Ars. 2022, 59(1):S1-S2. https://doi.org/10.29399/npa.28375.
17. Sullivan, P.F.; Geschwind, D.H. Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders. Cell. 2019, 177(1):162-183. https://doi.org/10.1016/j.cell.2019.01.015.
18. Gutiérrez-Rodríguez, A.; Cruz-Fuentes, C.S.; Genis-Mendoza, A.D.; Nicolini, H. CRISPR/Cas9 Genome Editing Approaches for Psychiatric Research. Braz J Psychiatry. 2023, 45(2):137-145. https://doi.org/10.47626/1516-4446-2022-2913.
19. Buckholtz, J.W.; Meyer-Lindenberg, A. Psychopathology and the human connectome: toward a transdiagnostic model of risk for mental illness. Neuron. 2012, 74(6):990-1004. https://doi.org/10.1016/j.neuron.2012.06.002.
20. Nestler, E.J.; Peña, C.J.; Kundakovic, M.; Mitchell, A.; Akbarian, S. Epigenetic basis of mental illness. Neuroscientist. 2016, 22(5):447-63. https://doi.org/10.1177/1073858415608147.
21. Orrù, G.; Pettersson-Yeo, W.; Marquand, A.F.; et al. Using Support Vector Machine to identify imaging biomarkers of neurological and psychiatric disease: a critical review. Neurosci Biobehav Rev. 2012, 36(4):1140-52. https://doi.org/10.1016/j.neubiorev.2012.01.004.
22. Grezenko, H.; Ekhator, C.; Nwabugwu, N.U.; et al. Epigenetics in neurological and psychiatric disorders: a comprehensive review of current understanding and future perspectives. Cureus. 2023, 15(8):e43960. https://doi.org/10.7759/cureus.43960.
23. Insel, T.R.; Cuthbert, B.N. Medicine. Brain disorders? Precisely. Science. 2015, 348(6234):499-500. https://doi.org/10.1126/science.aab2358.
24. Taslim, S.; Shadmani, S.; Saleem, A.R.; et al. Neuropsychiatric disorders: bridging the gap between neurology and psychiatry. Cureus. 2024, 16(1):e51655. https://doi.org/10.7759/cureus.51655.
25. Koliatsos, V.E.; Wisner-Carlson, R.; Watkins, C. Neuropsychiatry: definitions, concepts, and patient types. Psychiatr Clin North Am. 2020, 43:213-27. https://doi.org/10.1016/j.psc.2020.02.007.
26. Medina-Rodríguez, J.C. Exploring neuropsychiatry: contemporary challenges, breakthroughs, and philosophical perspectives. Cureus. 2023, 15(11):e49404. https://doi.org/10.7759/cureus.49404.
27. Yatham, L.N.; Thibaut, F. Translational chasm and dialogues in clinical neuroscience. Dialogues Clin Neurosci. 2022, 23(1):1-2. https://doi.org/10.1080/19585969.2022.2073566.
28. Torres, E.B.; Isenhower, R.W.; Nguyen, J.; et al. Toward Precision Psychiatry: statistical platform for the personalized characterization of natural behaviors. Front. Neurol. 2016, 7, 8. https://doi.org/10.3389/fneur.2016.00008.
29. Gandal, M.J.; Leppa, V.; Won, H.; et al. The road to precision psychiatry: translating genetics into disease mechanisms. Nat Neurosci. 2016, 19(11):1397-1407. https://doi.org/10.1038/nn.4409.
30. Lin, E.; Tsai, S.J. Genome-wide microarray analysis of gene expression profiling in major depression and antidepressant therapy. Prog. Neuropsychopharmacol. Biol. Psychiatry 2016, 64:334–340. https://doi.org/10.3389/fneur.2016.00008.
31. Lin, E.; Lane, H.Y. Machine learning and systems genomics approaches for multi-omics data. Biomark Res. 2017, 5, 2. https://doi.org/10.1186/s40364-017-0082-y.
32. Bzdok, D.; Meyer-Lindenberg, A. Machine learning for precision psychiatry: opportunities and challenges. Biol. Psychiatry Cogn. Neurosci. Neuroimaging 2018, 3:223–230. https://doi.org/10.1016/j.bpsc.2017.11.007.
33. Davatzikos, C. Machine learning in neuroimaging: Progress and challenges. Neuroimage. 2019, 197:652-656. https://doi.org/10.1016/j.neuroimage.2018.10.003.
34. Sullivan, P.F.; Agrawal, A.; Bulik, C.M.; et al. Psychiatric Genomics Consortium. Psychiatric Genomics: an update and an agenda. Am J Psychiatry. 2018, 175(1):15-27. https://doi.org/10.1176/appi.ajp.2017.17030283.
35. Singh, A.B.; Bousman, C.A.; Ng, C.H.; Berk, M. Antidepressant pharmacogenetics. The Australian and New Zealand Journal of Psychiatry. 2017, 51(8):776-87. https://doi.org/10.1097/YCO.0000000000000023.
36. Woo, C.W.; Wager, T.D. Neuroimaging-based biomarker discovery and validation. PAIN. 2015, 156(8): 1379-1381. https://doi.org/10.1097/j.pain.0000000000000223.
37. Miller BJ, Buckley P. Precision medicine in psychiatry. Journal of Clinical Psychopharmacology. 2017, 37(6):703-707.
38. Dwyer, D.B.; Falkai, P.; Koutsouleris, N. Machine learning approaches for clinical psychology and psychiatry. Annu Rev Clin Psychol. 2018, 14:91-118. https://doi.org/10.1146/annurev-clinpsy-032816-045037.
39. Lin, E.; Kuo, P.-H.; Liu, Y.-L.; et al. Polymorphisms of the DNA repair gene EXO1 modulate cognitive aging in old adults in a Taiwanese population. DNA Repair (Amst). 2019, 78:1-6. https://doi.org/10.1016/j.dnarep.2019.03.013.
40. Stein, M.B.; Smoller, J.W. Precision psychiatry-will genomic medicine lead the way? JAMA Psychiatry. 2018, 75(7):663-664. https://doi.org/10.1001/jamapsychiatry.2018.0375.
41. Lin, C.H.; Lin, E.; Lane, H.Y. Genetic biomarkers on age-related cognitive decline. Front Psychiatry. 2017, 8:247. https://doi.org/10.3389/fpsyt.2017.00247.
42. Iniesta, R.; Stahl, D.; McGuffin, P. Machine learning, statistical learning and the future of biological research in psychiatry. Psychol. Med. 2016, 46:2455–2465.
43. Mukherjee, S.; Asnani, H.; Lin, E.; Kannan, S. ClusterGAN: Latent space clustering in generative adversarial networks. Proc. AAAI Conf. Artif. Intell. 2019, 33. https://doi.org/10.1609/aaai.v33i01.33014610
44. Hu, Y.; Hase, T.; Li, H.P.; et al. A machine learning approach for the identification of key markers involved in brain development from single-cell transcriptomic data. BMC Genom. 2016, 17(13):1025. https://doi.org/10.1186/s12864-016-3317-7
45. Lin, E.; Tsai, S.-J. Diagnostic prediction based on gene expression profiles and artificial neural networks. soft computing for biological systems. Springer: Berlin, Germany, 2018, 13–22.
46. Williams, L.M. Special report: precision psychiatry—Are we getting closer? Psychiatric News. 2022, 57(9). https://doi.org/ 10.1176/appi.pn.2022.09.9.23
47. Dalvie, S.; Koen, N.; McGregor, N.; et al. Toward a global roadmap for precision medicine in psychiatry: challenges and opportunities. OMICS. 2016, 20(10):557-564. https://doi.org/10.1089/omi.2016.0110.
48. Williams, L.M. Precision psychiatry: A neural circuit taxonomy for depression and anxiety. Lancet Psychiatry 2016, 3, 472–480. https://doi.org/10.1016/S2215-0366(15)00579-9.
49. Lin, E.; Lin, C.H.; Lane, H.Y. Precision psychiatry applications with pharmacogenomics: artificial intelligence and machine learning approaches. Int J Mol Sci. 2020, 21(3):969. https://doi.org/10.3390/ijms21030969.
50. Lin, E.; Tsai, S.-J. Multi-omics and machine learning applications in precision medicine. Curr. Pharm. Pers. Med. (Former. Curr. Pharm.) 2017, 15, 97–104. https://doi.org/10.2174/1875692115666170616093844.
51. Serretti, A. The present and future of precision medicine in psychiatry: focus on clinical psychopharmacology of antidepressants. Clin Psychopharmacol Neurosci. 2018, 16(1):1-6. https://doi.org/10.9758/cpn.2018.16.1.1.
52. Scala, J.J.; Ganz, A.B.; Snyder, M.P. Precision medicine approaches to mental health care. Physiology (Bethesda). 2023, 38(2):0. https://doi.org/10.1152/physiol.00013.2022.
53. Hutson, P.H.; Clark, J.A.; Cross, A.J. CNS target identification and validation: avoiding the valley of death or naive optimism? Annu Rev Pharmacol Toxicol. 2017, 57:171-187. https://doi.org/10.1146/annurev-pharmtox-010716-104624.
54. Blokland, A. Drug Discovery in CNS: Finding a target for what? In: Schreiber, R. (eds) Modern CNS Drug Discovery. Springer, Cham. https://doi.org/10.1007/978-3-030-62351-7_2
55. Halene, T.B.; Vahdat, L.T. Molecular mechanisms of psychiatric disease. Wiley Interdisciplinary Reviews: Systems Biology and Medicine. 2018, 10(3):e1424.
56. Sanacora, G.; Frye, M.A.; McDonald, W.; et al. American Psychiatric Association (APA) Council of Research Task Force on Novel Biomarkers and Treatments. A Consensus Statement on the Use of Ketamine in the Treatment of Mood Disorders. JAMA Psychiatry. 2017, 74(4):399-405. https://doi.org/10.1001/jamapsychiatry.2017.0080.
57. Popik, P.; Kozela, E.; Krawczyk, M. Gliptins: a novel therapeutic approach in the treatment of depression? CNS & Neurological Disorders Drug Targets. 2014, 13(10):1630-41. 27.
58. Jurek, B.; Neumann, I.D.; Theodorsson, E. How to study sex differences in addiction using animal models. Addiction Biology. 2015, 20(5):911-937.
59. Goldsmith, D.R.; Haroon, E.; Miller, AH. Major depressive disorder in youths: clinical and treatment implications. Pediatric drugs. 2017, 19(4):329-42.
60. Javitt. D.C.; Zukin, S.R. Recent advances in the phencyclidine model of schizophrenia. Am J Psychiatry. 1991, 148(10):1301-8. https://doi.org/10.1176/ajp.148.10.1301.
61. Mueller, L.G.; Slusher, B.S.; Tsukamoto, T. Empirical analysis of drug targets for nervous system disorders. ACS Chem Neurosci. 2024, 15(3):394-399. https://doi.org/10.1021/acschemneuro.3c00676.
62. van der Doef, T.F.; Zaragoza, D.S.; Jacobs, G.E.; et al. New approaches in psychiatric drug development. Eur Neuropsychopharmacol. 2018, 28(9):983-993. https://doi.org/10.1016/j.euroneuro.2018.06.006.
63. Littman, B.H.; Di Mario, L.; Plebani, M.; Marincola, F.M. What's next in translational medicine? Clin Sci (Lond). 2007, 112(4):217-227. https://doi.org/10.1042/CS20060108.
64. Hurko, O. The uses of biomarkers in drug development. Ann N Y Acad Sci. 2009, 1180:1-10. https://doi.org/10.1111/j.1749-6632.2009.04946.x.
65. Hurko, O. Future drug discovery and development. Mol Genet Metab. 2010, 100 (1):92-96. https://doi.org/10.1016/j.ymgme.2010.01.010.
66. Insel, T.R. Translating scientific opportunity into public health impact: a strategic plan for research on mental illness. Arch Gen Psychiatry. 2017, 68(1):14-20.
67. Machado-Vieira, R. Tracking the impact of translational research in psychiatry: state of the art and perspectives. J Transl Med. 2012, 10:175. https://doi.org/10.1186/1479-5876-10-175.
68. Hyman, S.E. Revolution stalled. Sci Transl Med. 2012, 4(155):155cm11. https://doi.org/10.1126/scitranslmed.3003142.
69. Nosek, B.A.; Alter, G.; Banks, G.C.; et al. Promoting an open research culture. Science. 2015, 348(6242):1422-5. https://doi.org/10.1126/science.aab2374.
70. Miller, G. Mental health funding: closing the gap between research and practice. Science. 2010, 327(5969):1193-4.
71. DeJong, C.; Aguilar, T.; Tseng, C.; et al. Pharmaceutical Industry–Sponsored Meals and Physician Prescribing Patterns for Medicare Beneficiaries. JAMA Intern Med. 2016, 176(8):1114–1122. https://doi.org/10.1001/jamainternmed.2016.2765
72. Tanaka, M.; Battaglia, S.; Giménez-Llort, L.; et al. Innovation at the intersection: emerging translational research in neurology and psychiatry. Cells. 2024, 13(10):790. https://doi.org/10.3390/cells13100790.
73. Meijboom, F.L.B.; Kostrzewa. E.; Leenaars, C.H.C. Joining forces: the need to combine science and ethics to address problems of validity and translation in neuropsychiatry research using animal models. Philos Ethics Humanit Med. 2020, 15(1):1. https://doi.org/10.1186/s13010-019-0085-4.
74. García-Gutiérrez, M.S.; Navarrete, F.; Sala, F.; et al. Biomarkers in psychiatry: concept, definition, types and relevance to the clinical reality. Front Psychiatry. 2020, 11:432. https://doi.org/10.3389/fpsyt.2020.00432.
75. Emerson, E.; Einfeld, S.L. Challenging Behavior. Cambridge University Press, Cambridge, UK, 2014. https://doi.org/10.1017/CBO9780511861178
76. Chumakov, E.; Dorofeikova, M.; Tsyrenova, K.; Petrova, N. A cross-sectional study on associations between BDNF, CRP, IL-6 and clinical symptoms, cognitive and personal performance in patients with paranoid schizophrenia. Front. Psychiatry 2022, 13:943869. https://doi.org/10.3389/fpsyt.2022.943869
77. Dorofeikova, M.; Neznanov, N.; Petrova, N. Cognitive deficit in patients with paranoid schizophrenia: Its clinical and laboratory correlates. Psychiatry Research 2018, 262:542-548. https://doi.org/10.1016/j.psychres.2017.09.041
78. Brady, L.S.; Lisanby, S.H.; Gordon, J.A. New directions in psychiatric drug development: promising therapeutics in the pipeline. Expert Opin Drug Discov. 2023, 18(8):835-850. https://doi.org/10.1080/17460441.2023.2224555.
79. Petrova, N .; Dorofeikova, M. Psychiatry as clinical neuroscience: present and future. Neurology bulletin named after V.M. Bekhterev. 2020, LII(4):12–19. https://doi.org/10.17816/nb52656
80. Arbuckle, M.R.; Travis, M.J.; Ross, D.A. Integrating a neuroscience perspective into clinical psychiatry today. JAMA Psychiatry. 2017, 74(4):313-314. doi: 10.1001/jamapsychiatry.2016.3849.
81. Cooper, J.J.; Korb, A.S.; Akil, M. Bringing neuroscience to the bedside. Focus (Am Psychiatr Publ). 2019, 17(1):2-7. https://doi.org/10.1176/appi.focus.20180033.
82. Strege, M.V.; Persons, J.B.; Ressler, K.J.; et al. Integrating neuroscience into clinical practice: current opinions and dialogue between drs. Jacqueline Persons and Kerry Ressler. Behav Ther (N Y N Y). 2021, 44(7):326-334.
83. Cooper, J.; Walke, A.E. Neuroscience education: making it relevant to psychiatric training. Psychiatr Clin North Am. 2021, 44(2):295-307. https://doi.org/10.1016/j.psc.2020.12.008
84. Gómez-Carrillo, A.; Kirmayer, L.J.; Aggarwal, N.K.; et al. Integrating neuroscience in psychiatry: a cultural-ecosocial systemic approach. Lancet Psychiatry. 2023, 10(4):296-304. https://doi.org/10.1016/S2215-0366(23)00006-8.
85. Griffiths, R.R.; Johnson, M.W.; Carducci, M.A.; et al. Psilocybin produces substantial and sustained decreases in depression and anxiety in patients with life-threatening cancer: A randomized double-blind trial. J Psychopharmacol. 2016, 30(12):1181-1197. https://doi.org/10.1177/0269881116675513.
Review
For citations:
Petrova N.N. Modern Psychiatry: from Theory to Practice. Personalized Psychiatry and Neurology. 2024;4(4):11-25. https://doi.org/10.52667/2712-9179-2024-4-4-11-25
Views:
127
Email this article 