Циркулирующие микроРНК — перспективные биомаркеры для оценки риска развития антипсихотик-индуцированного метаболического синдрома (обзор): часть 2

ВВЕДЕНИЕ. В первой части статьи был рассмотрен антипсихотик-индуцированный метаболический синдром (АИМетС) как распространенная нежелательная реакция при фармакотерапии психических расстройств и болезней зависимости. Показаны подходы к спектру и оценке основных и дополнительных клинических и лабораторных маркеров метаболического синдрома (МетС) у пациентов с расстройствами шизофренического спектра в целом и АИМетС в частности. Изменение уровня экспрессии циркулирующих микроРНК в крови может рассматриваться как одна из перспективных методологий прогнозирования и диагностики АИМетС.

ЦЕЛЬ. Рассмотреть роль циркулирующих микроРНК как эпигенетических биомаркеров развития основных звеньев патогенеза АИМетС.

ОБСУЖДЕНИЕ. Проведен анализ и систематизация результатов фундаментальных и клинических исследований роли циркулирующих микроРНК, влияющих на основные звенья патогенеза и прогрессирования АИМетС, опубликованных в период 2012–2024 гг. Проанализированы результаты исследований, отражающих роль микроРНК в ключевых звеньях патогенеза МетС и АИМетС: окислительном стрессе, системном воспалении, регуляции адипогенеза и развитии центрального ожирения, липидного метаболизма, гомеостаза холестерина липопротеинов высокой/низкой плотности, атерогенеза, жировом гепатозе, а также регуляции чувствительности к инсулину, его экспрессии, метаболизма глюкозы, аппетита, экспрессии нейропептида Y, орексина тиреоидных гормонов, паратиреоидного гормона, чувствительности к лептину. Показано, что персонализированная оценка безопасности фармакотерапии может зависеть от паттерна циркулирующих микроРНК, которые индуцируют или ингибируют основные звенья патогенеза АИМетС. Различия в результатах проанализированных исследований микроРНК могут быть обусловлены тем, что фундаментальные (преимущественно) и клинические исследования имели вариабельный дизайн, а также тем, что в них не учитывались другие модифицируемые и немодифицируемые факторы риска АИМетС. Предложена градация микроРНК по степени риска развития АИМетС.

ВЫВОДЫ. Этот обзор демонстрирует, что чувствительность и специфичность эпигенетических биомаркеров АИМетС могут варьировать в широком диапазоне в зависимости от характера их влияния (предиктивного или протективного) на один или несколько основных звеньев патогенеза рассматриваемой распространенной нежелательной реакции психофармакотерапии. Наиболее изученными являются микроРНК — предиктивные биомаркеры окислительного стресса (miR-1, miR-21, miR-23b, miR-27a) и системного воспаления (miR-21, miR-23a, miR-27a) у пациентов с высоким риском развития МетС и АИМетС. Перспективными эпигенетическими биомаркерами АИМетС являются микроРНК, влияющие на уровень экспрессии нейропептидов и чувствительность к ним, включая нейропептид Y (miR-let7b, miR-29b, miR-33 и др.), лептин (miR-let7a, miR-9, miR-30e и др.) и орексин (miR-137, miR-637, miR-654 и др.).

1. Correll CU, Solmi M, Croatto G, et al. Mortality in people with schizophrenia: A systematic review and meta-analysis of relative risk and aggravating or attenuating factors. World Psychiatry. 2022;21(2):248–71. https://doi.org/10.1002/wps.20994

2. Peritogiannis V, Ninou A, Samakouri M. Mortality in schizophrenia-spectrum disorders: Recent advances in understanding and management. Healthcare (Basel). 2022;10(12):2366. https://doi.org/10.3390/healthcare10122366

3. De Hert M, Detraux J, van Winkel R, Yu W, Correll C. Metabolic and cardiovascular adverse effects associated with antipsychotic drugs. Nat Rev Endocrinol. 2012;8(2):114–26. https://doi.org/10.1038/nrendo.2011.156

4. De Hert M, Correll CU, Bobes J, Cetkovich-Bakmas M, Cohen D, Asai I, et al. Physical illness in patients with severe mental disorders. I. Prevalence, impact of medications and disparities in health care. World Psychiatry. 2011;10(1):52–77. https://doi.org/10.1002/j.2051-5545.2011.tb00014.x

5. Khasanova AK, Dobrodeeva VS, Shnayder NA, Petrova MM, Pronina EA, Bochanova EN, et al. Blood and urinary biomarkers of antipsychotic-induced metabolic syndrome. Metabolites. 2022;12(8):726. https://doi.org/10.3390/metabo12080726

6. Saha S. Role of microRNA in oxidative stress. Stresses. 2024;4(2):269–81. https://doi.org/10.3390/stresses4020016

7. Włodarski A, Strycharz J, Wróblewski A, Kasznicki J, Drzewoski J, Śliwińska A. The role of microRNAs in metabolic syndrome-related oxidative stress. Int J Mol Sci. 2020;21(18):6902. https://doi.org/10.3390/ijms21186902

8. Carvalho GB, Brandão-Lima PN, Payolla TB, Lucena SEF, Sarti FM, Fisberg RM, Rogero MM. Circulating miRNAs are associated with low-grade systemic inflammation and leptin levels in older adults. Inflammation. 2023;46(6):2132–46. https://doi.org/10.1007/s10753-023-01867-6

9. Das K, Rao LVM. The role of microRNAs in inflammation. Int J Mol Sci. 2022;23(24):15479. https://doi.org/10.3390/ijms232415479

10. Engin AB, Engin A. Adipogenesis-related microRNAs in obesity. ExRNA. 2022;4:16. https://doi.org/10.21037/exrna-22-4

11. Agbu P, Carthew RW. MicroRNA-mediated regulation of glucose and lipid metabolism. Nat Rev Mol Cell Biol. 2021;22(6):425–38. https://doi.org/10.1038/s41580-021-00354-w

12. Dong M, Ye Y, Chen Z, Xiao T, Liu W, Hu F. MicroRNA 182 is a novel negative regulator of adipogenesis by targeting CCAAT/enhan cerbinding protein α. Obesity (Silver Spring). 2020;28(8):1467–76. https://doi.org/10.1002/oby.22863

13. Wagschal A, Najafi-Shoushtari SH, Wang L, Goedeke L, Sinha S, deLemos AS, et al. Genome-wide identification of microRNAs regulating cholesterol and triglyceride homeostasis. Nat Med. 2015;21(11):1290–7. https://doi.org/10.1038/nm.3980

14. Cheng J, Cheng A, Clifford BL, Wu X, Hedin U, Maegdefessel L, et al. MicroRNA-144 silencing protects against atherosclerosis in male, but not female mice. Arterioscler Thromb Vasc Biol. 2020;40(2):412–25. https://doi.org/10.1161/ATVBAHA.119.313633

15. Irani S, Iqbal J, Antoni WJ, Ijaz L, Hussain MM. MicroRNA-30c reduces plasma cholesterol in homozygous familial hypercholesterole mic and type 2 diabetic mouse models. J Lipid Res. 2018;59(1):144–54. https://doi.org/10.1194/jlr.M081299

16. Trajkovski M, Hausser J, Soutschek J, Bhat B, Akin A, Zavolan M, et al. MicroRNAs 103 and 107 regulate insulin sensitivity. Nature. 2011;474(7353):649–53. https://doi.org/10.1038/nature10112

17. Liu W, Cao H, Ye C, Chang C, Lu M, Jing Y, et al. Hepatic miR-378 targets p110α and controls glucose and lipid homeostasis by modulating hepatic insulin signalling. Nat Commun. 2014;5:5684. https://doi.org/10.1038/ncomms6684

18. Kornfeld JW, Baitzel C, Könner AC, Nicholls HT, Vogt MC, Herrmanns K, et al. Obesity-induced overexpression of miR-802 impairs glucose metabolism through silencing of Hnf1b. Nature. 2013;494(7435):111–5. https://doi.org/10.1038/nature11793

19. Xu H, Du X, Xu J, Zhang Y, Tian Y, Liu G, et al. Pancreatic β cell microRNA-26a alleviates type 2 diabetes by improving peripheral insulin sensitivity and preserving β cell function. PLoS Biol. 2020;18(2):e3000603. https://doi.org/10.1371/journal.pbio.3000603

20. Ofori JK, Salunkhe VA, Bagge A, Vishnu N, Nagao M, Mulder H, et al. Elevated miR-130a/miR130b/miR-152 expression reduces intracellular ATP levels in the pancreatic beta cell. Sci Rep. 2017;7:44986. https://doi.org/10.1038/srep44986

21. Belgardt BF, Ahmed K, Spranger M, Latreille M, Denzler R, Kondratiuk N, et al. The microRNA-200 family regulates pancreatic beta cell survival in type 2 diabetes. Nat Med. 2015;21(6):619–27. https://doi.org/10.1038/nm.3862

22. Zhang F, Ma D, Zhao W, Wang D, Liu T, Liu Y, et al. Obesity-induced overexpression of miR-802 impairs insulin transcription and secretion. Nat Commun. 2020;11(1):1822. https://doi.org/10.1038/s41467-020-15529-w

23. Melkman-Zehavi T, Oren R, Kredo-Russo S, Shapira T, Mandelbaum AD, Rivkin N, et al. miRNAs control insulin content in pancreatic β-cells via downregulation of transcriptional repressors. EMBO J. 2011;30(5):835–45. https://doi.org/10.1038/emboj.2010.361

24. Price NL, Fernández-Tussy P, Varela L, Cardelo MP, Shanabrough M, Aryal B, et al. microRNA-33 controls hunger signaling in hypothalamic AgRP neurons. Nat Commun. 2024;15(1):2131. https://doi.org/10.1038/s41467-024-46427-0

25. Taouis M. MicroRNAs in the hypothalamus. Best Pract Res Clin Endocrinol Metab. 2016;30(5):641–51. https://doi.org/10.1016/j.beem.2016.11.006

26. Zhang D, Yamaguchi S, Zhang X, Yang B, Kurooka N, Sugawara R, et al. Upregulation of mir342 in diet-induced obesity mouse and the hypothalamic appetite control. Front Endocrinol (Lausanne). 2021;12:727915. https://doi.org/10.3389/fendo.2021.727915

27. Sangiao-Alvarellos S, Pena-Bello L, Manfredi-Lozano M, Tena-Sempere M, Cordido F. Perturbation of hypothalamic microRNA expression patterns in male rats after metabolic distress: Impact of obesity and conditions of negative energy balance. Endocrinology. 2014;155(5):1838–50. https://doi.org/10.1210/en.2013-1770

28. Derghal A, Djelloul M, Azzarelli M, Degonon S, Tourniaire F, Landrier JF, et al. MicroRNAs are involved in the hypothalamic leptin sensitivity. Epigenetics. 2018;13(10–11):1127–40. https://doi.org/10.1080/15592294.2018.1543507

29. Mak KWY, He W, Loganathan N, Belsham DD. Bisphenol A Alters the levels of miRNAs that directly and/or indirectly target neuropeptide Y in murine hypothalamic neurons. Genes (Basel). 2023;14(9):1773. https://doi.org/10.3390/genes14091773

30. Dobrodeeva VS, Abdyrahmanova AK, Nasyrova RF. Personalized approach to antipsychotic-induced weight gain prognosis. Personalized Psychiatry and Neurology. 2021;1(1):3–10. https://doi.org/10.52667/2712-9179-2021-1-1-3-10

31. Holm A, Possovre ML, Bandarabadi M, Moseholm KF, Justinussen JL, Bozic I, et al. The evolutionarily conserved miRNA-137 targets the neuropeptide hypocretin/orexin and modulates the wake to sleep ratio. Proc Natl Acad Sci USA. 2022;119(17):e2112225119. https://doi.org/10.1073/pnas.2112225119

32. Siegert S, Seo J, Kwon EJ, Rudenko A, Cho S, Wang W, et al. The schizophrenia risk gene product miR-137 alters presynaptic plasticity. Nat Neurosci. 2015;18(7):1008–16. https://doi.org/10.1038/nn.4023

33. Azhar S, Dong D, Shen WJ, Hu Z, Kraemer FB. The role of miRNAs in regulating adrenal and gonadal steroidogenesis. J Mol Endocrinol. 2020;64(1):R21–R43. https://doi.org/10.1530/JME-19-0105

34. Aranda A. MicroRNAs and thyroid hormone action. Mol Cell Endocrinol. 2021;525:111175. https://doi.org/10.1016/j.mce.2021.111175

35. Vaira V, Verdelli C, Forno I, Corbetta S. MicroRNAs in parathyroid physiopathology. Mol Cell Endocrinol. 2017;456:9–15. https://doi.org/10.1016/j.mce.2016.10.035

36. Шнайдер НА, Насырова РФ, Пекарец НА, Гречкина ВВ, Петрова ММ. Роль паттерна циркулирующих микроРНК в крови в оценке риска развития антипсихотик-индуцированного метаболического синдрома (обзор): часть 1. Безопасность и риск фармакотерапии. 2025. https://doi.org/10.30895/2312-7821-2025-478

37. Dietrich-Muszalska A, Kolodziejczyk-Czepas J, Nowak P. Comparative study of the effects of atypical antipsychotic drugs on plasma and urine biomarkers of oxidative stress in schizophrenic patients. Neuropsychiatr Dis Treat. 2021;17:555–65. https://doi.org/10.2147/NDT.S283395

38. Tsai MC, Liou CW, Lin TK, Lin IM, Huang TL. Changes in oxidative stress markers in patients with schizophrenia: The effect of antipsychotic drugs. Psychiatry Res. 2013;209(3):284–90. https://doi.org/10.1016/j.psychres.2013.01.023

39. Bhandari R, Kaur J, Kaur S, Kuhad A. The Nrf2 pathway in psychiatric disorders: Pathophysiological role and potential targeting. Expert Opin Ther Targets. 2021;25(2):115–39. https://doi.org/10.1080/14728222.2021.1887141

40. Fang X, Yu L, Wang D, Chen Y, Wang Y, Wu Z, et al. Association between SIRT1, cytokines, and metabolic syndrome in schizophrenia patients with olanzapine or clozapine monotherapy. Front Psychiatry. 2020;11:602121. https://doi.org/10.3389/fpsyt.2020.602121

41. Ткачев ВО, Меньшикова ЕБ, Зенков НК. Механизм работы сигнальной системы Nrf2/Keap1/ARE (обзор). Биохимия. 2011;76(4):407–22. https://doi.org/10.1134/s0006297911040031

42. Zhang H, Dai S, Yang Y, Wei J, Li X, Luo P, Jiang X. Role of sirtuin 3 in degenerative diseases of the central nervous system. Biomolecules. 2024;13(5):735. https://doi.org/10.3390/biom13050735

43. Yang W, Nagasawa K, Munch C, Xu Y, Satterstrom K, Jeong S, et al. Mitochondrial sirtuin network reveals dynamic Sirt3-dependent deacetylation in response to membrane depolarization. Cell. 2016;167(4):985–1000.e21. https://doi.org/10.1016/j.cell.2016.10.016

44. Lee BJ, Marchionni L, Andrews CE, Norris AL, Nucifora LG, Wu YC, et al. Analysis of differential gene expression mediated by clozapine in human postmortem brains. Schizophr Res. 2017;185:58–66. https://doi.org/10.1016/j.schres.2016.12.017

45. Sommerfeld-Klatta K, Jiers W, Rzepczyk S, Nowicki F, Łukasik-Głębocka M, Świderski P, et al. The effect of neuropsychiatric drugs on the oxidation-reduction balance in therapy. Int J Mol Sci. 2024;25(13):7304. https://doi.org/10.3390/ijms25137304

46. Nasyrova RF, Moskaleva PV, Vaiman EE, Shnayder NA, Blatt NL, Rizvanov AA. Genetic factors of nitric oxide’s system in psychoneurologic disorders. Int J Mol Sci. 2020;21(5):1604. https://doi.org/10.3390/ijms2105160

47. Patel S, Keating BA, Dale RC. Anti-inflammatory properties of commonly used psychiatric drugs. Front Neurosci. 2023;16:1039379. https://doi.org/10.3389/fnins.2022.1039379

48. Al-Amin MM, Nasir Uddin MM, Mahmud Reza H. Effects of antipsychotics on the inflammatory response system of patients with schizophrenia in peripheral blood mononuclear cell cultures. Clin Psychopharmacol Neurosci. 2013;11(3):144–51. https://doi.org/10.9758/cpn.2013.11.3.144

49. Marcinowicz P, Więdłocha M, Zborowska N, Dębowska W, Podwalski P, Misiak B, et al. A meta-analysis of the influence of antipsychotics on cytokines levels in first episode psychosis. J Clin Med. 2021;10(11):2488. https://doi.org/10.3390/jcm10112488

50. Patlola SR, Donohoe G, McKernan DP. Anti-inflammatory effects of 2nd generation antipsychotics in patients with schizophrenia: A systematic review and meta-analysis. J Psychiatr Res. 2023;160:126–36. https://doi.org/10.1016/j.jpsychires.2023.01.042

51. Cohen T, Sundaresh S, Levine F. Antipsychotics activate the TGFβ pathway effector SMAD3. Mol Psychiatry. 2013;18(3):347–57. https://doi.org/10.1038/mp.2011.186

52. Prestwood TR, Asgariroozbehani R, Wu S, Agarwal SM, Logan RW, Ballon JS, et al. Roles of inflammation in intrinsic pathophysiology and antipsychotic drug-induced metabolic disturbances of schizophrenia. Behav Brain Res. 2021;402:113101. https://doi.org/10.1016/j.bbr.2020.113101

53. Melbourne JK, Pang Y, Park MR, Sudhalkar N, Rosen C, Sharma RP. Treatment with the antipsychotic risperidone is associated with increased M1-like JAK-STAT1 signature gene expression in PBMCs from participants with psychosis and THP-1 monocytes and macrophages. Int Immunopharmacol. 2020;79:106093. https://doi.org/10.1016/j.intimp.2019.106093

54. Cheng L, Xia F, Li Z, Shen C, Yang Z, Hou H, et al. Structure, function and drug discovery of GPCR signaling. Mol Biomed. 2023;4(1):46. https://doi.org/10.1186/s43556-023-00156-w

55. Chen CY, Liu HY, Hsueh YP. TLR3 downregulates expression of schizophrenia gene Disc1 via MYD88 to control neuronal morpho logy. EMBO Rep. 2017;18(1):169–83. https://doi.org/10.15252/embr.201642586

56. Kositsyn YM, de Abreu MS, Kolesnikova TO, Lagunin AA, Poroikov VV, Harutyunyan HS, et al. Towards novel potential molecular targets for antidepressant and antipsychotic pharmacotherapies. Int J Mol Sci. 2023;24(11):9482. https://doi.org/10.3390/ijms24119482

57. Bahmad HF, Daouk R, Azar J, Sapudom J, Teo JCM, Abou-Kheir W, et al. Modeling adipogenesis: Current and future perspective. Cells. 2020;9(10):2326. https://doi.org/10.3390/cells9102326

58. Ghesmati Z, Rashid M, Fayezi S, Gieseler F, Alizadeh E, Darabi M. An update on the secretory functions of brown, white, and beige adipose tissue: Towards therapeutic applications. Rev Endocr Metab Disord. 2024;25(2):279–308. https://doi.org/10.1007/s11154-023-09850-0

59. Li Y, Zhao X, Feng X, Liu X, Deng C, Hu CH. Berberine alleviates olanzapine-induced adipogenesis via the AMPKα-SREBP pathway in 3T3-L1 Cells. Int J Mol Sci. 2016;17(11):1865. https://doi.org/10.3390/ijms17111865

60. Chen CC, Hsu LW, Huang KT, Goto S, Chen CL, Nakano T. Overexpression of Insig-2 inhibits atypical antipsychotic-induced adipogenic differentiation and lipid biosynthesis in adipose-derived stem cells. Sci Rep. 2017;7(1):10901. https://doi.org/10.1038/s41598-017-11323-9

61. Fehsel K, Bouvier ML. Sex-specific effects of long-term antipsychotic drug treatment on adipocyte tissue and the crosstalk to liver and brain in rats. Int J Mol Sci. 2024;25(4):2188. https://doi.org/10.3390/ijms25042188

62. Ma J, Zheng Y, Sun F, Fan Y, Fan Y, Su X, et al. Research progress in the correlation between SREBP/PCSK9 pathway and lipid metabolism disorders induced by antipsychotics. Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2023;48(10):1529–38. https://doi.org/10.11817/j.issn.1672-7347.2023.230029

63. Vantaggiato C, Panzeri E, Citterio A, Orso G, Pozzi M. Antipsychotics promote metabolic disorders disrupting cellular lipid metabolism and trafficking. Trends Endocrinol Metab. 2019;30(3):189–210. https://doi.org/doi:10.1016/j.tem.2019.01.003

64. Delacrétaz A, Vandenberghe F, Glatard A, Dubath C, Levier A, Gholam-Rezaee M, et al. Lipid disturbances in adolescents treated with second-generation antipsychotics: Clinical determinants of plasma lipid worsening and new-onset hypercholesterolemia. J Clin Psychiatry. 2019;80(3):18m12414. https://doi.org/10.4088/JCP.18m12414

65. O’Donnell C, Demler TL, Trigoboff E, Lee C. The impact of high-density lipoprotein cholesterol (HDL-C) levels and risk of movement disorders in patients taking antipsychotics. Innov Clin Neurosci. 2024;21(4–6):27–30. PMCID: PMC11208005

66. Richards-Belle A, Austin-Zimmerman I, Wang B, Zartaloudi E, Cotic M, Gracie C, et al. Associations of antidepressants and antipsychotics with lipid parameters: Do CYP2C19/CYP2D6 genes play a role? A UK population-based study. J Psychopharmacol. 2023;37(4):396–407. https://doi.org/10.1177/02698811231152748

67. Chen CH, Leu SJ, Hsu CP, Pan CC, Shyue SK, Lee TS. Atypical antipsychotic drugs deregulate the cholesterol metabolism of macrophage-foam cells by activating NOX-ROS-PPARγ-CD36 signaling pathway. Metabolism. 2021;123:154847. https://doi.org/10.1016/j.metabol.2021.154847

68. Gangopadhyay A, Ibrahim R, Theberge K, May M, Houseknecht KL. Non-alcoholic fatty liver disease (NAFLD) and mental illness: Mechanisms linking mood, metabolism and medicines. Front Neurosci. 2022;16:1042442. https://doi.org/10.3389/fnins.2022.1042442

69. Chen J, Huang XF, Shao R, Chen C, Deng C. Molecular mechanisms of antipsychotic drug-induced diabetes. Front Neurosci. 2017;11:643. https://doi.org/10.3389/fnins.2017.00643

70. Weeks KR, Dwyer DS, Aamodt EJ. Antipsychotic drugs activate the C. elegans Akt pathway via the DAF-2 insulin/IGF-1 receptor. ACS Chem Neurosci. 2010;1(6):463–73. https://doi.org/10.1021/cn100010p

71. Kowalchuk C, Kanagasundaram P, Belsham DD, Hahn MK. Antipsychotics differentially regulate insulin, energy sensing, and inflammation pathways in hypothalamic rat neurons. Psychoneuroendocrinology. 2019;104:42–8. https://doi.org/10.1016/j.psyneuen.2019.01.029

72. Li YZ, Di Cristofano A, Woo M. Metabolic role of PTEN in insulin signaling and resistance. Cold Spring Harb Perspect Med. 2020;10(8):a036137. https://doi.org/10.1101/cshperspect.a036137

73. Ramasubbu K, Devi Rajeswari V. Impairment of insulin signaling pathway PI3K/Akt/mTOR and insulin resistance induced AGEs on diabetes mellitus and neurodegenerative diseases: A perspective review. Mol Cell Biochem. 2023;478(6):1307–24. https://doi.org/10.1007/s11010-022-04587-x

74. Zhou W, Sun J, Huai C, Liu Y, Chen L, Yi Z, et al. Multi-omics analysis identifies rare variation in leptin/PPAR gene sets and hypermethylation of ABCG1 contribute to antipsychotics-induced metabolic syndromes. Mol Psychiatry. 2022;27(12):5195–205. https://doi.org/10.1038/s41380-022-01759-5

75. Nwosu BU, Meltzer B, Maranda L, Ciccarelli C, Reynolds D, Curtis L, et al. A potential role for adjunctive vitamin D therapy in the management of weight gain and metabolic side effects of second-generation antipsychotics. J Pediatr Endocrinol Metab. 2011;24(9–10):619–26. https://doi.org/10.1515/jpem.2011.300

76. Mukherjee S, Skrede S, Milbank E, Andriantsitohaina R, López M, Fernø J. Understanding the effects of antipsychotics on appetite control. Front Nutr. 2022;8:815456. https://doi.org/10.3389/fnut.2021.815456

77. Добродеева ВС, Шнайдер НА, Миронов КО, Насырова РФ. Фармакогенетические маркеры антипсихотик-индуцированного набора веса: система лептина и нейропептида Y. Обозрение психиатрии и медицинской психологии имени В.М. Бехтерева. 2021;55(1):3–10. https://doi.org/10.31363/2313-7053-2021-1-3-10

78. Klemettilä JP, Kampman O, Solismaa A, Lyytikäinen LP, Seppälä N, Viikki M, et al. Association study of arcuate nucleus neuropeptide Y neuron receptor gene variation and serum Npy levels in clozapine treated patients with schizophrenia. European Psychiatry. 2017;40:13–9. https://doi.org/10.1016/j.eurpsy.2016.07.004

79. Zhang Y, Li X, Yao X, Yang Y, Ning X, Zhao T, et al. Do leptin play a role in metabolism-related psychopathological symptoms? Front Psychiatry. 2021;12:710498. https://doi.org/10.3389/fpsyt.2021.710498

80. Chen PY, Chang CK, Chen CH, Fang SC, Mondelli V, Chiu CC, et al. Orexin-a elevation in antipsychotic-treated compared to drug-free patients with schizophrenia: A medication effect independent of metabolic syndrome. J Formos Med Assoc. 2022;121(11):2172–81. https://doi.org/10.1016/j.jfma.2022.03.008

81. Burghardt KJ, Mando W, Seyoum B, Yi Z, Burghardt PR. The effect of antipsychotic treatment on hormonal, inflammatory, and metabolic biomarkers in healthy volunteers: A systematic review and meta-analysis. Pharmacotherapy. 2022;42(6):504–13. https://doi.org/10.1002/phar.2689

82. Su X, Chen X, Peng H, Song J, Wang B, Wu X. Novel insights into the pathological development of dyslipidemia in patients with hypothyroidism. Bosn J Basic Med Sci. 2022;22(3):326–39. https://doi.org/10.17305/bjbms.2021.6606

83. Nwosu BU, Meltzer B, Maranda L, Ciccarelli C, Reynolds D, Curtis L, et al. A potential role for adjunctive vitamin D therapy in the management of weight gain and metabolic side effects of second-generation antipsychotics. J Pediatr Endocrinol Metab. 2011;24(9–10):619–26. https://doi.org/10.1515/jpem.2011.300

84. Neznanov NG. A paradigm shift to treat psychoneurological disorders. Personalized Psychiatry and Neurology. 2021;1(1):1–2.

85. Ashurov ZS. The evolution of personalized psychiatry. Personalized Psychiatry and Neurology. 2023;3(2):1–2.

86. Wei H, Yuan Y, Liu S, Wang C, Yang F, Lu Z, et al. Detection of circulating miRNA levels in schizophrenia. Am J Psychiatry. 2015;172(11):1141–7. https://doi.org/10.1176/appi.ajp.2015.14030273

87. Liu S, Zhang F, Shugart YY, Yang L, Li X, Liu Z, et al. MiR143-3p-mediated NRG-1-dependent mitochondrial dysfunction contributes to olanzapine resistance in refractory schizophrenia. Biol Psychiatry. 2022;92(5):419–33. https://doi.org/10.1016/j.biopsych.2022.03.012

88. Liu S, Zhang F, Shugart YY, Yang L, Li X, Liu Z, et al. The early growth response protein 1-miR-30a-5p-neurogenic differentiation factor 1 axis as a novel biomarker for schizophrenia diagnosis and treatment monitoring. Transl Psychiatry. 2017;7(1):e998. https://doi.org/10.1038/tp.2016.268

89. Chen SD, Sun XY, Niu W, Kong LM, He MJ, Fan HM, et al. A preliminary analysis of microRNA-21 expression alteration after antipsychotic treatment in patients with schizophrenia. Psychiatry Res. 2016;244:324–32. https://doi.org/10.1016/j.psychres.2016.04.087

90. Yu HC, Wu J, Zhang HX, Zhang GL, Sui J, Tong WW, et al. Alterations of miR-132 are novel diagnostic biomarkers in peripheral blood of schizophrenia patients. Prog Neuropsychopharmacol Biol Psychiatry. 2015;63:23–9. https://doi.org/10.1016/j.pnpbp.2015.05.007