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miRNAs in treatment-resistant depression: a systematic review

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Abstract

Background

Treatment-resistant depression (TRD) is a condition in a subset of depressed patients characterized by resistance to antidepressant medications. The global prevalence of TRD has been steadily increasing, yet significant advancements in its diagnosis and treatment remain elusive despite extensive research efforts. The precise underlying pathogenic mechanisms are still not fully understood. Epigenetic mechanisms play a vital role in a wide range of diseases. In recent years, investigators have increasingly focused on the regulatory roles of miRNAs in the onset and progression of TRD. miRNAs are a class of noncoding RNA molecules that regulate the translation and degradation of their target mRNAs via interaction, making the exploration of their functions in TRD essential for elucidating their pathogenic mechanisms.

Methods and results

A systematic search was conducted in four databases, namely PubMed, Web of Science, Cochrane Library, and Embase, focusing on studies related to treatment-resistant depression and miRNAs. The search was performed using terms individually or in combination, such as “treatment-resistant depression,” “medication-resistant depression,” and “miRNAs.” The selected articles were reviewed and collated, covering the time period from the inception of each database to the end of February 2024. We found that miRNAs play a crucial role in the pathophysiology of TRD through three main aspects: 1) involvement in miRNA-mediated inflammatory responses (including miR-155, miR-345-5p, miR-146a, and miR-146a-5p); 2) influence on 5-HT transport processes (including miR-674,miR-708, and miR-133a); and 3) regulation of synaptic plasticity (including has-miR-335-5p,has-miR- 1292-3p, let-7b, and let-7c). Investigating the differential expression and interactions of these miRNAs could contribute to a deeper understanding of the molecular mechanisms underlying TRD.

Conclusions

miRNAs might play a pivotal role in the pathogenesis of TRD. Gaining a deeper understanding of the roles and interrelations of miRNAs in TRD will contribute to elucidating disease pathogenesis and potentially provide avenues for the development of novel diagnostic and therapeutic strategies.

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References

  1. Malhi GS, Mann JJ (2018) Depression. Lancet 392:2299–2312. https://doi.org/10.1016/S0140-6736(18)31948-2

    Article  PubMed  Google Scholar 

  2. World Health O (2017) Depression and other common mental disorders: global health estimates.

  3. Diseases GBD, Injuries C (2020) Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet 396:1204–1222. https://doi.org/10.1016/S0140-6736(20)30925-9

    Article  Google Scholar 

  4. Wyska E (2019) Pharmacokinetic considerations for current state-of-the-art antidepressants. Exp Opin Drug Metab Toxicol 15:831–847. https://doi.org/10.1080/17425255.2019.1669560

    Article  CAS  Google Scholar 

  5. Berlim MT, Turecki G (2007) Definition, assessment, and staging of treatment-resistant refractory major depression: a review of current concepts and methods. Canadian J Psychiatry 52:46–54

    Article  Google Scholar 

  6. Zhdanava M, Pilon D, Ghelerter I et al (2021) The prevalence and national burden of treatment-resistant depression and major depressive disorder in the United States. J Clin Psychiatry. https://doi.org/10.4088/JCP.20m13699

    Article  PubMed  Google Scholar 

  7. Lundberg J, Cars T, Lööv S-Å et al (2023) Association of treatment-resistant depression with patient outcomes and health care resource utilization in a population-wide study. JAMA Psychiatry 80:167–175. https://doi.org/10.1001/jamapsychiatry.2022.3860

    Article  PubMed  Google Scholar 

  8. Demyttenaere K, Van Duppen Z (2019) The impact of (the concept of) treatment-resistant depression: an opinion review. Int J Neuropsychopharmacol 22:85–92. https://doi.org/10.1093/ijnp/pyy052

    Article  PubMed  Google Scholar 

  9. Borbély É, Simon M, Fuchs E, Wiborg O, Czéh B, Helyes Z (2022) Novel drug developmental strategies for treatment-resistant depression. British J Pharmacol 179:1146–1186. https://doi.org/10.1111/bph.15753

    Article  CAS  Google Scholar 

  10. Nestler EJ (2014) Epigenetic mechanisms of depression. JAMA Psychiatry 71:454–456. https://doi.org/10.1001/jamapsychiatry.2013.4291

    Article  PubMed  PubMed Central  Google Scholar 

  11. Uchida S, Yamagata H, Seki T, Watanabe Y (2018) Epigenetic mechanisms of major depression: targeting neuronal plasticity. Psychiatry Clin Neurosci 72:212–227. https://doi.org/10.1111/pcn.12621

    Article  PubMed  Google Scholar 

  12. Page MJ, McKenzie JE, Bossuyt PM et al (2021) The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 372:n71. https://doi.org/10.1136/bmj.n71

    Article  PubMed  PubMed Central  Google Scholar 

  13. Valiuliene G, Valiulis V, Zentelyte A, Dapsys K, Germanavicius A, Navakauskiene R (2023) Anti-neuroinflammatory microRNA-146a-5p as a potential biomarker for neuronavigation-guided rTMS therapy success in medication resistant depression disorder. Biomed Pharmacother 166:115313. https://doi.org/10.1016/j.biopha.2023.115313

    Article  CAS  PubMed  Google Scholar 

  14. Maffioletti E, Bocchio-Chiavetto L, Perusi G et al (2021) Inflammation-related microRNAs are involved in stressful life events exposure and in trauma-focused psychotherapy in treatment-resistant depressed patients. Eur J Psychotraumatol 12:1987655. https://doi.org/10.1080/20008198.2021.1987655

    Article  PubMed  PubMed Central  Google Scholar 

  15. Kaurani L, Besse M, Methfessel I et al (2023) Baseline levels of miR-223–3p correlate with the effectiveness of electroconvulsive therapy in patients with major depression. Trans Psychiatry 13:294–294. https://doi.org/10.1038/s41398-023-02582-4

    Article  CAS  Google Scholar 

  16. Liu Y, Yu J, Wang X, Dong J (2020) MicroRNA-345–5p regulates depression by targeting suppressor of cytokine signaling 1. Brain Behav 10:e01653. https://doi.org/10.1002/brb3.1653

    Article  PubMed  PubMed Central  Google Scholar 

  17. Sun XH, Song MF, Song HD, Wang YW, Luo MJ, Yin LM (2019) miR155 mediates inflammatory injury of hippocampal neuronal cells via the activation of microglia. Mol Med Rep 19:2627–2635. https://doi.org/10.3892/mmr.2019.9917

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Korlatowicz A, Pabian P, Solich J et al (2023) Habenula as a possible target for treatment-resistant depression phenotype in Wistar Kyoto Rats. Mole Neurobiol 60:643–654. https://doi.org/10.1007/s12035-022-03103-y

    Article  CAS  Google Scholar 

  19. Li L-D, Naveed M, Du Z-W et al (2021) Abnormal expression profile of plasma-derived exosomal microRNAs in patients with treatment-resistant depression. Hum Genomics 15:55. https://doi.org/10.1186/s40246-021-00354-z

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Israel-Elgali I, Hertzberg L, Shapira G et al (2021) Blood transcriptional response to treatment-resistant depression during electroconvulsive therapy. J Psychiatry Res 141:92–103. https://doi.org/10.1016/j.jpsychires.2021.06.039

    Article  Google Scholar 

  21. Gururajan A, Naughton ME, Scott KA et al (2016) MicroRNAs as biomarkers for major depression: a role for let-7b and let-7c. Trans Psychiatry. https://doi.org/10.1038/tp.2016.131

    Article  Google Scholar 

  22. Zhou L, Zhu Y, Chen W, Tang Y (2021) Emerging role of microRNAs in major depressive disorder and its implication on diagnosis and therapeutic response. J Affec Disord 286:80–86. https://doi.org/10.1016/j.jad.2021.02.063

    Article  CAS  Google Scholar 

  23. Dwivedi Y (2014) Emerging role of microRNAs in major depressive disorder: diagnosis and therapeutic implications. Dialogues Clin Neurosci 16:43–61

    Article  PubMed  PubMed Central  Google Scholar 

  24. Wei N, Zhang H, Wang J et al (2020) The progress in diagnosis and treatment of exosomes and microRNAs on epileptic comorbidity depression. Front Psychiatry 11:405. https://doi.org/10.3389/fpsyt.2020.00405

    Article  PubMed  PubMed Central  Google Scholar 

  25. Strawbridge R, Hodsoll J, Powell TR et al (2019) Inflammatory profiles of severe treatment-resistant depression. J Affect Disord 246:42–51. https://doi.org/10.1016/j.jad.2018.12.037

    Article  CAS  PubMed  Google Scholar 

  26. Chen M-H, Li C-T, Lin W-C et al (2018) Rapid inflammation modulation and antidepressant efficacy of a low-dose ketamine infusion in treatment-resistant depression: a randomized, double-blind control study. Psychiatry Res 269:207–211. https://doi.org/10.1016/j.psychres.2018.08.078

    Article  CAS  PubMed  Google Scholar 

  27. Sukoff Rizzo SJ, Neal SJ, Hughes ZA et al (2012) Evidence for sustained elevation of IL-6 in the CNS as a key contributor of depressive-like phenotypes. Trans Psychiatry 2:e199. https://doi.org/10.1038/tp.2012.120

    Article  CAS  Google Scholar 

  28. Lv F, Huang Y, Lv W et al (2017) MicroRNA-146a ameliorates inflammation via TRAF6/NF-κB pathway in intervertebral disc cells. Med Sci Monitor 23:659–664

    Article  CAS  Google Scholar 

  29. Chen L, Dong R, Lu Y et al (2019) MicroRNA-146a protects against cognitive decline induced by surgical trauma by suppressing hippocampal neuroinflammation in mice. Brain Behav Immun 78:188–201. https://doi.org/10.1016/j.bbi.2019.01.020

    Article  CAS  PubMed  Google Scholar 

  30. Liu C-P, Zhong M, Sun J-X, He J, Gao Y, Qin F-X (2021) miR-146a reduces depressive behavior by inhibiting microglial activation. Mol Med Rep. https://doi.org/10.3892/mmr.2021.12102

    Article  PubMed  PubMed Central  Google Scholar 

  31. Dantzer R (2018) Neuroimmune interactions: from the brain to the immune system and vice versa. Physiol Rev 98:477–504. https://doi.org/10.1152/physrev.00039.2016

    Article  CAS  PubMed  Google Scholar 

  32. Jia X, Gao Z, Hu H (2021) Microglia in depression: current perspectives. Sci China Life Sci 64:911–925. https://doi.org/10.1007/s11427-020-1815-6

    Article  CAS  PubMed  Google Scholar 

  33. Brites D, Fernandes A (2015) Neuroinflammation and depression: microglia activation, extracellular microvesicles and microRNA dysregulation. Front Cell Neurosci 9:476. https://doi.org/10.3389/fncel.2015.00476

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Verdonk F, Petit A-C, Abdel-Ahad P et al (2019) Microglial production of quinolinic acid as a target and a biomarker of the antidepressant effect of ketamine. Brain Behav Immun 81:361–373. https://doi.org/10.1016/j.bbi.2019.06.033

    Article  CAS  PubMed  Google Scholar 

  35. Tang CZ, Zhang DF, Yang JT, Liu QH, Wang YR, Wang WS (2019) Overexpression of microRNA-301b accelerates hippocampal microglia activation and cognitive impairment in mice with depressive-like behavior through the NF-kappaB signaling pathway. Cell Death Dis 10:316. https://doi.org/10.1038/s41419-019-1522-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Kedzierski L, Tate MD, Hsu AC et al (2017) Suppressor of cytokine signaling (SOCS)5 ameliorates influenza infection via inhibition of EGFR signaling. Elife. https://doi.org/10.7554/eLife.20444

    Article  PubMed  PubMed Central  Google Scholar 

  37. Zhang S, Gao L, Liu X, Lu T, Xie C, Jia J (2017) Resveratrol Attenuates Microglial Activation via SIRT1-SOCS1 Pathway. Evid Based Complement Alternat Med 2017:8791832. https://doi.org/10.1155/2017/8791832

    Article  PubMed  PubMed Central  Google Scholar 

  38. Maciak K, Dziedzic A, Miller E, Saluk-Bijak J (2021) miR-155 as an important regulator of multiple sclerosis pathogenesis. A review. Int J Mol Sci. https://doi.org/10.3390/ijms22094332

    Article  PubMed  PubMed Central  Google Scholar 

  39. Salazar A, Gonzalez-Rivera BL, Redus L, Parrott JM, O’Connor JC (2012) Indoleamine 2,3-dioxygenase mediates anhedonia and anxiety-like behaviors caused by peripheral lipopolysaccharide immune challenge. Horm Behav 62:202–209. https://doi.org/10.1016/j.yhbeh.2012.03.010

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Zheng X, Huang H, Liu J, Li M, Liu M, Luo T (2018) propofol attenuates inflammatory response in LPS-activated microglia by regulating the miR-155/SOCS1 pathway. Inflammation 41:11–19. https://doi.org/10.1007/s10753-017-0658-6

    Article  CAS  PubMed  Google Scholar 

  41. Albert (2010) Modifying 5-HT1A receptor gene expression as a new target for antidepressant therapy. Front Neurosci. https://doi.org/10.3389/fnins.2010.00035

    Article  PubMed  PubMed Central  Google Scholar 

  42. Krishnan V, Nestler EJ (2008) The molecular neurobiology of depression. Nature 455:894–902. https://doi.org/10.1038/nature07455

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Coplan JD, Gopinath S, Abdallah CG, Berry BR (2014) A neurobiological hypothesis of treatment-resistant depression - mechanisms for selective serotonin reuptake inhibitor non-efficacy. Front Behav Neurosci 8:189. https://doi.org/10.3389/fnbeh.2014.00189

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Bonvicini C, Minelli A, Scassellati C et al (2010) Serotonin transporter gene polymorphisms and treatment-resistant depression. Prog Neuropsychopharmacol Biol Psychiatry 34:934–939. https://doi.org/10.1016/j.pnpbp.2010.04.020

    Article  CAS  PubMed  Google Scholar 

  45. David DJ, Gardier AM (2016) The pharmacological basis of the serotonin system: application to antidepressant response. L’Encephale 42:255–263. https://doi.org/10.1016/j.encep.2016.03.012

    Article  CAS  PubMed  Google Scholar 

  46. Akil H, Gordon J, Hen R et al (2018) Treatment resistant depression: a multi-scale, systems biology approach. Neurosci Biobehav Rev 84:272–288. https://doi.org/10.1016/j.neubiorev.2017.08.019

    Article  PubMed  Google Scholar 

  47. Kulikov AV, Gainetdinov RR, Ponimaskin E, Kalueff AV, Naumenko VS, Popova NK (2018) Interplay between the key proteins of serotonin system in SSRI antidepressants efficacy. Exp Opin Therapeutic Targets 22:319–330. https://doi.org/10.1080/14728222.2018.1452912

    Article  Google Scholar 

  48. Anttila S, Huuhka K, Huuhka M et al (2007) Interaction between 5-HT1A and BDNF genotypes increases the risk of treatment-resistant depression. J Neural Transm (Vienna) 114:1065–1068. https://doi.org/10.1007/s00702-007-0705-9

    Article  CAS  PubMed  Google Scholar 

  49. Kolshus E, Dalton VS, Ryan KM, McLoughlin DM (2014) When less is more–microRNAs and psychiatric disorders. Acta Psychiatry Scand 129:241–256. https://doi.org/10.1111/acps.12191

    Article  CAS  Google Scholar 

  50. Holtmaat A, Svoboda K (2009) Experience-dependent structural synaptic plasticity in the mammalian brain. Nat Rev Neurosci 10:647–658. https://doi.org/10.1038/nrn2699

    Article  CAS  PubMed  Google Scholar 

  51. Kessels HW, Malinow R (2009) Synaptic AMPA receptor plasticity and behavior. Neuron 61:340–350. https://doi.org/10.1016/j.neuron.2009.01.015

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Duman RS, Aghajanian GK, Sanacora G, Krystal JH (2016) Synaptic plasticity and depression: new insights from stress and rapid-acting antidepressants. Nat Med 22:238–249. https://doi.org/10.1038/nm.4050

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Rosso P, Iannitelli A, Pacitti F et al (2020) Vagus nerve stimulation and neurotrophins: a biological psychiatric perspective. Neurosci Biobehav Rev 113:338–353. https://doi.org/10.1016/j.neubiorev.2020.03.034

    Article  PubMed  Google Scholar 

  54. Miller OH, Moran JT, Hall BJ (2016) Two cellular hypotheses explaining the initiation of ketamine’s antidepressant actions: direct inhibition and disinhibition. Neuropharmacology 100:17–26. https://doi.org/10.1016/j.neuropharm.2015.07.028

    Article  CAS  PubMed  Google Scholar 

  55. Fiore R, Rajman M, Schwale C et al (2014) MiR-134-dependent regulation of Pumilio-2 is necessary for homeostatic synaptic depression. EMBO J 33:2231–2246. https://doi.org/10.15252/embj.201487921

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Cohen JE, Lee PR, Chen S, Li W, Fields RD (2011) MicroRNA regulation of homeostatic synaptic plasticity. Proc Natl Acad Sci USA 108:11650–11655. https://doi.org/10.1073/pnas.1017576108

    Article  PubMed  PubMed Central  Google Scholar 

  57. Wang Z, Xu Y, Sun Y, Wang S, Dong M (2022) Novel homozygous silent mutation of ITGB3 gene caused Glanzmann thrombasthenia. Front Pediatrics 10:1062900. https://doi.org/10.3389/fped.2022.1062900

    Article  Google Scholar 

  58. Cingolani LA, Thalhammer A, Yu LMY et al (2008) Activity-dependent regulation of synaptic AMPA receptor composition and abundance by beta3 integrins. Neuron 58:749–762. https://doi.org/10.1016/j.neuron.2008.04.011

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Parenti I, Rabaneda LG, Schoen H, Novarino G (2020) Neurodevelopmental disorders: from genetics to functional pathways. Trends Neurosci 43:608–621. https://doi.org/10.1016/j.tins.2020.05.004x

    Article  CAS  PubMed  Google Scholar 

  60. Leal G, Comprido D, Duarte CB (2014) BDNF-induced local protein synthesis and synaptic plasticity. Neuropharmacology 76:639–656. https://doi.org/10.1016/j.neuropharm.2013.04.005

    Article  CAS  PubMed  Google Scholar 

  61. Haile CN, Murrough JW, Iosifescu DV et al (2014) Plasma brain derived neurotrophic factor (BDNF) and response to ketamine in treatment-resistant depression. Int J Neuropsychopharmacol 17:331–336. https://doi.org/10.1017/S1461145713001119

    Article  CAS  PubMed  Google Scholar 

  62. Xin C, Xia J, Liu Y, Zhang Y (2020) MicroRNA-202–3p targets brain-derived neurotrophic factor and is involved in depression-like behaviors. Neuropsychiatr Dis Treat 16:1073–1083. https://doi.org/10.2147/NDT.S241136

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Radice PD, Mathieu P, Leal MC et al (2015) Fibulin-2 is a key mediator of the pro-neurogenic effect of TGF-beta1 on adult neural stem cells. Mol Cell Neurosci 67:75–83. https://doi.org/10.1016/j.mcn.2015.06.004

    Article  CAS  PubMed  Google Scholar 

  64. Caraci F, Copani A, Nicoletti F, Drago F (2010) Depression and Alzheimer’s disease: neurobiological links and common pharmacological targets. Eur J Pharmacol 626:64–71. https://doi.org/10.1016/j.ejphar.2009.10.022

    Article  CAS  PubMed  Google Scholar 

  65. Xu N, Meng H, Liu T et al (2017) Blueberry phenolics reduce gastrointestinal infection of patients with cerebral venous thrombosis by improving depressant-induced autoimmune disorder via miR-155-mediated brain-derived neurotrophic factor. Front Pharmacol 8:853. https://doi.org/10.3389/fphar.2017.00853

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. McIntyre RS, Alsuwaidan M, Baune BT et al (2023) Treatment-resistant depression: definition, prevalence, detection, management, and investigational interventions. World Psychiatry 22:394–412. https://doi.org/10.1002/wps.21120

    Article  PubMed  PubMed Central  Google Scholar 

  67. Belzeaux R, Bergon A, Jeanjean V et al (2012) Responder and nonresponder patients exhibit different peripheral transcriptional signatures during major depressive episode. Trans Psychiatry 2:e185. https://doi.org/10.1038/tp.2012.112

    Article  CAS  Google Scholar 

  68. Lopez JP, Fiori LM, Cruceanu C et al (2017) MicroRNAs 146a/b-5 and 425–3p and 24–3p are markers of antidepressant response and regulate MAPK/Wnt-system genes. Nat Commun 8:15497. https://doi.org/10.1038/ncomms15497

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Funding

This work was supported by the Guangxi Key Laboratory of Chinese Medicine Foundation Research (2020), the Training Plan for Thousands of Young and Middle-aged Key Teachers in Colleges and Universities of Guangxi (The third batch), the Guangxi Natural Science Foundation (2020GXNSFAA259020), and the National Natural Science Foundation of China (81960845).

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  1. Lun Cai, and Jingwen Xu and Jie Liu are co-first authors.

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  1. Department of Neurology, The First Affiliated Hospital of Guangxi University of Chinese Medicine, Guangxi University of Chinese Medicine, Nanning, 530023, People’s Republic of China

    Lun Cai, Jingwen Xu, Jie Liu, Huazheng Luo & Rongrong Yang

  2. Department of Surgery, The First Affiliated Hospital of Guangxi University of Chinese Medicine, Guangxi University of Chinese Medicine, No. 89-9 Dongge Road, Nanning, 530000, Guangxi, People’s Republic of China

    Xiongbin Gui & Liping Wei

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JX and JL wrote the manuscript and revised it. LC designed and supervised the study. HL, RY, XG, and LW collected the data and designed the figures. All the authors have read and approved the submitted manuscript.

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Cai, L., Xu, J., Liu, J. et al. miRNAs in treatment-resistant depression: a systematic review. Mol Biol Rep 51, 638 (2024). https://doi.org/10.1007/s11033-024-09554-x

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