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Emerging role of microRNAs in major depressive disorder: diagnosis and therapeutic implications
Open accessAbstract
Major depressive disorder (MDD) is a major public health concern. Despite tremendous advances, the pathogenic mechanisms associated with MDD are still unclear. Moreover, a significant number of MDD subjects do not respond to the currently available medication. MicroRNAs (miRNAs) are a class of small noncoding RNAs that control gene expression by modulating translation, messenger RNA (mRNA) degradation, or stability of mRNA targets. The role of miRNAs in disease pathophysiology is emerging rapidly. Recent studies demonstrating the involvement of miRNAs in several aspects of neural plasticity, neurogenesis, and stress response, and more direct studies in human postmortem brain provide strong evidence that miRNAs can not only play a critical role in MDD pathogenesis, but can also open up new avenues for the development of therapeutic targets. Circulating miRNAs are now being considered as possible biomarkers in disease pathogenesis and in monitoring therapeutic responses because of the presence and/or release of miRNAs in blood cells as well as in other peripheral tissues. In this review, these aspects are discussed in a comprehensive and critical manner.
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![Figure 1. miRNA biogenesis. microRNAs (miRNAs) are encoded in the genome (inter or intragenis) and transcribed by RNA polymerase II (RNA pol II) to generate primary microRNA (pri-miRNA). These pri-miRNAs are taken up by the RNA II enzyme Drosha/DiGeorge syndrome critical region 8 (DGCR8) protein, which catalyzes the formation of precursor miRNA (pre-miRNA). Pre-miRNA is then exported to cytoplasm by ExportinB in conjunction with Ras-related nuclear protein, RanGTR In the cytoplasm, pre-miRNA is cleaved into miRNA:miRNA* duplex by the Rnase III enzyme Dicer/Tar RNA-binding protein (TRBP) or PKR activating protein (PACT). One of these miRNA/miRNA* duplexes is discarded and the other one is loaded onto an Argonaute (Ago) homologue protein (isoforms of eukaryotic translation initiation factor [eIF] 2c) to generate the effector complex, known as RNA-induced silencing complex (RISC). The RISC complex directs miRNA to specific “short-seed” sequences located predominantly within the 3' UTR region of the target messenger RNA (mRNA). This leads to degradation or translational inhibition. nt, nucleotides](/paper-figures/5fadb9242e35452c8c67b69c1f9083ab/emerging-role-of-micrornas-in-major-depressive-disorder-diagnosis-and-figure-1.jpg)
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“A common post-transcriptional process mediated at least in part by miRNA alters the structure of dendrites and neurogenesis.”
From Epigenetic mechanisms of major depression: Targeting neuronal plasticity (2018) · cites this paper as [140]
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Cites
Bartel (2004) · doi:10.1016/s0092-8674(04)00045-5 · Cited by 34,714
Kessler, R. C. (1994) · Archives of General Psychiatry · doi:10.1001/archpsyc.1994.03950010008002 · Cited by 12,370
The functions of animal microRNAs
Ambros, V. (2004) · Nature · doi:10.1038/nature02871 · Cited by 10,728
Chen, X., Ba, Y., Ma, L., Cai, X., Yin, Y., Wang, K., Guo, J., Zhang, Y., Chen, J., Guo, X., et al. (2008) · Cell Research · doi:10.1038/cr.2008.282 · Cited by 4,560
A Mammalian microRNA Expression Atlas Based on Small RNA Library Sequencing
Landgraf, P., Rusu, M., Sheridan, R., Sewer, A., Iovino, N., Aravin, A., Pfeffer, S., Rice, A., Kamphorst, A. O., Landthaler, M., et al. (2007) · Cell · doi:10.1016/j.cell.2007.04.040 · Cited by 3,626
Identification of tissue-specific microRNAs from mouse
Lagos-Quintana, M., Rauhut, R., Yalcin, A., Meyer, J., Lendeckel, W., & Tuschl, T. (2002) · Current Biology · doi:10.1016/s0960-9822(02)00809-6 · Cited by 3,355
Arroyo, J. D., Chevillet, J. R., Kroh, E. M., Ruf, I. K., Pritchard, C. C., Gibson, D. F., Mitchell, P. S., Bennett, C. F., Pogosova-Agadjanyan, E. L., Stirewalt, D. L., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1019055108 · Cited by 3,294
Switching from Repression to Activation: MicroRNAs Can Up-Regulate Translation
Vasudevan, S., Tong, Y., & STEITZ, J. A. (2007) · Science · doi:10.1126/science.1149460 · Cited by 2,911
MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins
Vickers, K. C., Palmisano, B. T., Shoucri, B. M., Shamburek, R. D., & Remaley, A. T. (2011) · Nature Cell Biology · doi:10.1038/ncb2210 · Cited by 2,741
The MicroRNA Spectrum in 12 Body Fluids
Weber, J. A., Baxter, D. H., Zhang, S., Huang, D. Y., How Huang, K., Jen Lee, M., Galas, D. J., & Wang, K. (2010) · Clinical Chemistry · doi:10.1373/clinchem.2010.147405 · Cited by 2,477
Research works printed but not linked: 11
- Honer WG., 1999, J Neurosci., 24, 116
- Michalak P., 2006, J EvolBiol., 19, 1768
- Kapsimali M., 2007, Biol., 8, R173
- Lee MM., 2013, Curr Top Behav Neurosci., 14, 153
- Lang MF., 2012, Front Neurosci., 6, 71
- Dorval V., 2013, Front Mol Neurosci., 6, 24
- Cao MQ., 2013, Zhongguo Zhong Yao Za Zhi., 38, 1585
- Saito Y., 2012, Front Genet., 3, 194
- Chan AW., 2012, Front Genet., 17, 3
- Dwivedi Y., 2011, Am Coll Neuropsychophramacol., 36, S75
- Kalani A., Mol Neurobiol 2013. [Epub ahead of print] PMID:23999871.
Cited by
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Perroud, N. A. (2016) · Springer eBooks · doi:10.1007/978-3-319-26282-6_29 · Cited by 13
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Lin, E., & Tsai, S. (2018) · Springer eBooks · doi:10.1007/978-981-10-7455-4_2 · Cited by 5
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Liu, W., Zhang, L., Zheng, D.-L., & Zhang, Y. (2019) · Medicine · doi:10.1097/md.0000000000016373 · Cited by 5
RetractedMendez‐David, I., David, D. J. P., Deloménie, C., Beaulieu, J., Gardier, A. M., & Hen, R. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.05.26.115873 · Cited by 5
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Nedel, F., Ferrúa, C. P., Amaral, C. C. D., Corrêa, G. P., Silveira, R. G., Trettim, J. P., da Cunha, G. K., Klug, A. B., Ardais, A. P., Fogaça, T. B., et al. (2022) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2022.12.021 · Cited by 2
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Wang, Y., Huang, Y., Luo, X., Lai, X., Yu, L., Zhao, Z., Zhang, A., Li, H., Huang, G., Li, Y., et al. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e39026 · Cited by 4
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Mustafin, R. N., & Хуснутдинова, Э. К. (2018) · Vavilov Journal of Genetics and Breeding · doi:10.18699/vj18.377 · Cited by 4
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Lin, P., & Li, Q. (2017) · Frontiers in Laboratory Medicine · doi:10.1016/j.flm.2017.08.002 · Cited by 3
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Roy, B., & Dwivedi, Y. (2017) · Springer eBooks · doi:10.1007/978-981-10-6580-4_4 · Cited by 2
Self-citationSen, S., & Maulik, U. (2018) · Briefings in Functional Genomics · doi:10.1093/bfgp/ely021 · Cited by 2
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Manoharan, A., & Paul, A. (2021) · Asian Journal of Psychiatry · doi:10.1016/j.ajp.2021.102906 · Cited by 2
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Shahini, A., Khaksar, Z., & Negah, S. S. (2018) · The Neuroscience Journal of Shefaye Khatam · doi:10.29252/shefa.6.1.49 · Cited by 1
Sharma, H., Noman, A. A., Ahmad, I., Tonni, S. D., Mim, T. J., Afrose, F., Sharma, P., Parvez, A., Tamanna, S., Azad, M. A., et al. (2025) · Current Gene Therapy · doi:10.2174/0115665232361169250617192348 · Cited by 3
Xue, Y.-H., Li, Y., Chu, C., Lan-Tian, X., Zhao, K., Luo, Y.-Q., Zi, D., Hong, Z.-B., Zhou, Y., & Zhao, X.-M. (2026) · Ecotoxicology and Environmental Safety · doi:10.1016/j.ecoenv.2026.120302 · Cited by 1
Korkmaz, N. D., Elibol, B., Durmus, Z. B., Ozdemir, A., Akbaş, F., Gülöksüz, S., & Şahbaz, Ç. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5135082 · Cited by 1
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Jawaid, A., Kremer, E. A., & Mansuy, I. M. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-805388-1.00036-5
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Baldwin, D. A. (2015) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2015.00044
O’Neill, E. A., & Black, D. R. (2017) · Social Work in Mental Health · doi:10.1080/15332985.2017.1306823 · Cited by 1
Chen, X., Liu, X., Zuo, X., Cheng, C., Huang, W. C., & Xie, P. (2020) · PubMed Central
RetractedBustamante, F. A., Méndez-Ruette, M., Wyneken, Ú., Bátiz, L. F., & Henzi, R. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-813156-5.00017-0
Vitali, E., Maffioletti, E., Minelli, A., Bonvicini, C., Bortolomasi, M., Gainelli, G., Bocchio‐Chiavetto, L., & Gennarelli, M. (2020) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2020.09.198
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Kálmán, S. (2016) · SZTE Repository of Dissertations (University of Szeged) · doi:10.14232/phd.2988
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Jawaid, A., Kremer, E. A., Carullo, N. V. N., & Mansuy, I. M. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-91909-8.00025-6
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Blanco‐Vázquez, M. (2023) · doi:10.35376/10324/61070
Nguyen, H. D., Vu, G. H., & Kim, W. (2024) · Personalized Medicine in Psychiatry · doi:10.1016/j.pmip.2024.100128
Wang, Y., Huang, Y., Luo, X., Lai, X., Yu, L., Zhao, Z., Zhang, A., Li, H., Huang, G., Li, Y., et al. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4879423
Kowalczyk, M., Kowalczyk, E., Talarowska, M. E., Majsterek, I., Skrzypek, M., Popławski, T., Sienkiewicz, M., Wiktorowska‐Owczarek, A., Sokołowska, P., & Jóźwiak-Bębenista, M. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms252212204
The, J. T., & Ansermet, F. (2025) · The Psychoanalytic Quarterly · doi:10.1080/00332828.2025.2569599
McKibben, L. A., & Dwivedi, Y. (2021) · Figshare · doi:10.6084/m9.figshare.16696656
Self-citationLi, L.-D., Naveed, M., Du, Z.-W., Ding, H., Gu, K., Wei, L.-L., Zhou, Y.-P., Meng, F., Wang, C., Han, F., et al. (2021) · Figshare · doi:10.6084/m9.figshare.16305469
Li, L.-D., Naveed, M., Du, Z.-W., Ding, H., Gu, K., Wei, L.-L., Zhou, Y.-P., Meng, F., Wang, C., Han, F., et al. (2021) · Figshare · doi:10.6084/m9.figshare.16305472
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Selvaraj, D., & Chandra, H. M. (2026) · Network Modeling Analysis in Health Informatics and Bioinformatics · doi:10.1007/s13721-025-00707-x
Yuxin, X. U., You, Y., Wei, D., Liang, R., Liang, W., Bingzheng, F., Chen, J., Liang, J., & Li, F. (2026) · Research Square · doi:10.21203/rs.3.rs-10130523/v1
Kaadt, E., Søkilde, R., Hansen, H. D., Raval, N. R., Donovan, L. L., Just, J., Knudsen, G. M., & Elfving, B. (2026) · European Journal of Pharmacology · doi:10.1016/j.ejphar.2026.179222
Xu, Y., 游艳秋, Wei, D., Liang, R., Liang, W., Feng, B., Chen, J., Liang, J., & Li, F. (2026) · Frontiers in Pharmacology · doi:10.3389/fphar.2026.1924891
Boström, A. E. D., Chatzittofis, A., Andersson, P. S. G., Savard, J., Öberg, K. G., Arver, S., Flanagan, J. N., & Jokinen, J. (2026) · Frontiers in Neuroscience · doi:10.3389/fnins.2026.1946302
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Pal, A., & Rathored, J. (2026) · Royal Society of Chemistry eBooks · doi:10.1039/9781837071395-00203
Metadata
- Authors
- Dwivedi, Y.
- Affiliations
- University of Alabama at Birmingham (US)
- Corresponding author
- Dwivedi, Yogesh
- ORCID
- Dwivedi, Yogesh
- Venue
- Dialogues in Clinical Neuroscience
- Publisher
- Informa UK Limited
- Published
- 2014-03-31
- Volume
- 16
- Issue
- 1
- Pages
- 43-61
- ISSN
- 1294-8322 (ISSN-L)
- 1958-5969
- PMC
- PMC3984890
- OpenAlex
- W2166817991
- Cited by
- 169
- References
- 196
- Citations by year
- 2026: 8 · 2025: 8 · 2024: 12 · 2023: 9 · 2022: 13 · 2021: 23 · 2020: 20 · 2019: 15 · 2018: 15 · 2017: 21 · 2016: 10 · 2015: 12 · 2014: 3
- FWCI
- 4.91
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Dialogues in Clinical Neuroscience (publishedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (UL1TR000050)
- National Institute of Mental Health (1R01MH0100616, R21MH081099, R01MH101890, R01MH082802, R01MH100616, R21MH091509)
- National Center for Advancing Translational Sciences
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › MicroRNA in disease regulation
- Health Sciences › Medicine › Pharmacology (medical) › Treatment of Major Depression
- Life Sciences › Neuroscience › Biological Psychiatry › Tryptophan and brain disorders
- Keywords
- major depressive disorder, microRNA, circulating microRNAs, biomarkers, depression diagnosis, depression treatment response, postmortem brain, neuroplasticity, neurogenesis, stress response, therapeutic target, non-coding RNA
- MeSH terms
- Animals, Major Depressive Disorder, Humans, Neuronal Plasticity, Biomarkers, MicroRNAs, Neurogenesis
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