Restraint Stress in Mice Alters Set of 25 miRNAs Which Regulate Stress- and Depression-Related mRNAs
Open accessAbstract
In the present study, we aim to identify the effect of restrain stress (RS) on the expression of miRNAs in mouse serum. We used three genotypes of animals (mice with knock-out of the gene-encoding norepinephrine transporter, NET-KO; C57BL/6J, and SWR/J) which had previously been shown to display different sensitivity to RS, and focused on miRNAs which were altered by RS in the serum of all three genotypes. An analysis of miRNAs expression allowed for the identification of a set of 25 differentially expressed miRNAs; 10 were down-regulated compared to an appropriate control group of animals, while 15 were up-regulated. The application of DIANA-miRPath v. 3.0 allowed for the identification of selected pathways (KEGG) and Gene Ontology (GO) categories that were significantly controlled by these miRNAs, while miRWalk v. 3.0—the platform that used the machine learning based algorithm, TaRPmiR—was used to find their targets. The results indicate that 25 miRNAs, identified as altered upon RS in three genotypes of mice, are responsible for regulation of mRNA-encoding proteins that are key for the main hypotheses of depression; therefore, they may help to understand the link between stress and depression at the molecular level.
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The link between miRNAs and the pathophysiology of depression may be implicated by the fact that miRNAs regulate neuronal regulation, neurotransmitter regulation, and microglia activation.
“The link between miRNAs and the pathophysiology of depression248–252 may be implicated by the fact that miRNAs regulate neuronal regulation, neurotransmitter regulation, and microglia activation.253,254”
From Epigenetic regulation in major depression and other stress-related disorders: molecular mechanisms, clinical relevance and therapeutic potential (2023) · cites this paper as [251]
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Vandesompele, J., De Preter, K., Pattyn, F., Poppe, B., Van Roy, N., De Paepe, A., & Speleman, F. (2002) · Genome Biology · doi:10.1186/gb-2002-3-7-research0034 · Cited by 20,038 · see citing works
Lewis, B. P., Burge, C. B., & Bartel, D. P. (2005) · Cell · doi:10.1016/j.cell.2004.12.035 · Cited by 11,855 · see citing works
Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene
Caspi, A., Sugden, K., Moffitt, T. E., Taylor, A., Craig, I. W., Harrington, H., McClay, J., Mill, J., Martin, J., Braithwaite, A., et al. (2003) · Science · doi:10.1126/science.1083968 · Cited by 8,120 · see citing works
miRDB: an online database for prediction of functional microRNA targets
Chen, Y., & Wang, X. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkz757 · Cited by 3,277 · see citing works
miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions
Chou, C., Shrestha, S., Yang, C.-D., Chang, N.-W., Lin, Y., Liao, K., Huang, W.-C., Sun, T.-H., Tu, S.-J., Lee, W.-H., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx1067 · Cited by 1,813 · see citing works
miRWalk: An online resource for prediction of microRNA binding sites
Sticht, C., Torre, C. D. L., Parveen, A., & Gretz, N. (2018) · PLoS ONE · doi:10.1371/journal.pone.0206239 · Cited by 1,807 · see citing works
DIANA-miRPath v3.0: deciphering microRNA function with experimental support
Vlachos, I. S., Zagganas, K., Paraskevopoulou, M. D., Georgakilas, G. K., Karagkouni, D., Vergoulis, T., Dalamagas, T., & Hatzigeorgiou, A. G. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv403 · Cited by 1,682 · see citing works
Mechanisms of stress in the brain
McEwen, B. S., Bowles, N. P., Gray, J. D., Hill, M. N., Hunter, R. G., Karatsoreos, I. N., & Nasca, C. (2015) · Nature Neuroscience · doi:10.1038/nn.4086 · Cited by 1,386 · see citing works
Implication of sperm RNAs in transgenerational inheritance of the effects of early trauma in mice
Gapp, K., Jawaid, A., Sarkies, P., Bohacek, J., Pelczar, P., Prados, J., Farinelli, L., Miska, E., & Mansuy, I. M. (2014) · Nature Neuroscience · doi:10.1038/nn.3695 · Cited by 1,306 · see citing works
Rodgers, A. B., Morgan, C. P., Bronson, S. L., Revello, S., & Bale, T. L. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.0914-13.2013 · Cited by 814 · see citing works
Transgenerational epigenetic programming via sperm microRNA recapitulates effects of paternal stress
Rodgers, A. B., Morgan, C. P., Leu, N. A., & Bale, T. L. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1508347112 · Cited by 751 · see citing works
Duman, R. S., & Voleti, B. (2012) · Trends in Neurosciences · doi:10.1016/j.tins.2011.11.004 · Cited by 714 · see citing works
MiR-16 Targets the Serotonin Transporter: A New Facet for Adaptive Responses to Antidepressants
Baudry, A., Mouillet-Richard, S., Schneider, B., Launay, J.-M., & Kellermann, O. (2010) · Science · doi:10.1126/science.1193692 · Cited by 480 · see citing works
Mice lacking the norepinephrine transporter are supersensitive to psychostimulants
Xu, F., Gainetdinov, R. R., Wetsel, W. C., Jones, S. R., Bohn, L., Miller, G. W., Wang, Y.-M., & Caron, M. G. (2000) · Nature Neuroscience · doi:10.1038/74839 · Cited by 464 · see citing works
Wray, N. R., Pergadia, M. L., Blackwood, D. H. R., Penninx, B. W. J. H., Gordon, S. D., Nyholt, D. R., Ripke, S., MacIntyre, D. J., McGhee, K. A., Maclean, A. W., et al. (2012) · Molecular Psychiatry · doi:10.1038/mp.2010.109 · Cited by 444 · see citing works
Resilience to social stress coincides with functional DNA methylation of the Crf gene in adult mice
Elliott, E., Ezra-Nevo, G., Regev, L., Neufeld-Cohen, A., & Chen, A. (2010) · Nature Neuroscience · doi:10.1038/nn.2642 · Cited by 436 · see citing works
The mTOR signaling pathway in the prefrontal cortex is compromised in major depressive disorder
Jernigan, C. S., Goswami, D. B., Austin, M. C., Iyo, A. H., Chandran, A., Stockmeier, C. A., & Karolewicz, B. (2011) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2011.05.010 · Cited by 386 · see citing works
Chronic stress: Implications for neuronal morphology, function and neurogenesis
Joëls, M., Karst, H., Krugers, H. J., & Lucassen, P. J. (2007) · Frontiers in Neuroendocrinology · doi:10.1016/j.yfrne.2007.04.001 · Cited by 381 · see citing works
Issler, O., Haramati, S., Paul, E. D., Maeno, H., Navon, I., Zwang, R., Gil, S., Mayberg, H. S., Dunlop, B. W., Menke, A., et al. (2014) · Neuron · doi:10.1016/j.neuron.2014.05.042 · Cited by 318 · see citing works
Determining the role of microRNAs in psychiatric disorders
Issler, O., & Chen, A. (2015) · Nature Reviews Neuroscience · doi:10.1038/nrn3879 · Cited by 309 · see citing works
A systems approach to stress, stressors and resilience in humans
Oken, B., Chamine, I., & Wakeland, W. W. (2014) · Behavioural Brain Research · doi:10.1016/j.bbr.2014.12.047 · Cited by 288 · see citing works
Normalization of circulating microRNA expression data obtained by quantitative real-time RT-PCR
Marabita, F., de Candia, P., Torri, A., Tegner, J. N., Abrignani, S., & Rossi, R. L. (2015) · Briefings in Bioinformatics · doi:10.1093/bib/bbv056 · Cited by 270 · see citing works
microRNA as Repressors of Stress-Induced Anxiety: The Case of Amygdalar miR-34
Haramati, S., Navon, I., Issler, O., Ezra-Nevo, G., Gil, S., Zwang, R., Hornstein, E., & Chen, A. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.1673-11.2011 · Cited by 252 · see citing works
Blood microRNA changes in depressed patients during antidepressant treatment
Bocchio-Chiavetto, L., Maffioletti, E., Bettinsoli, P., Giovannini, C., Bignotti, S., Tardito, D., Corrada, D., Milanesi, L., & Gennarelli, M. (2013) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2012.06.013 · Cited by 238 · see citing works
Shah, J. S., Soon, P. S., & Marsh, D. J. (2016) · PLOS ONE · doi:10.1371/journal.pone.0153200 · Cited by 216 · see citing works
Identification of MicroRNA-124-3p as a Putative Epigenetic Signature of Major Depressive Disorder
Roy, B., Dunbar, M., Shelton, R. C., & Dwivedi, Y. (2017) · Neuropsychopharmacology · doi:10.1038/npp.2016.175 · Cited by 199 · see citing works
TarPmiR: a new approach for microRNA target site prediction
Ding, J., Li, X., & Hu, H. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw318 · Cited by 189 · see citing works
Peripheral whole blood microRNA alterations in major depression and bipolar disorder
Maffioletti, E., Cattaneo, A., Rosso, G., Maina, G., Maj, C., Gennarelli, M., Tardito, D., & Bocchio-Chiavetto, L. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.04.021 · Cited by 181 · see citing works
MicroRNAs as biomarkers for major depression: a role for let-7b and let-7c
Gururajan, A., Naughton, M., Scott, K. A., O’Connor, R. M., Moloney, G. M., Clarke, G. A., Dowling, J. L., Walsh, A. E. L., Ismail, M. F., Shorten, G., et al. (2016) · Translational Psychiatry · doi:10.1038/tp.2016.131 · Cited by 144 · see citing works
Chandran, A., Iyo, A. H., Jernigan, C. S., Legutko, B., Austin, M. C., & Karolewicz, B. (2012) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2012.08.001 · Cited by 137 · see citing works
Fan, H., Sun, X., Guo, W., Zhong, A., Niu, W., Zhao, L., Dai, Y.-H., Guo, Z.-M., Zhang, L.-Y., & Lu, J. Z. (2014) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2014.08.007 · Cited by 129 · see citing works
Lopez, J. P., Fiori, L. M., Gross, J. A., Labonte, B., Yerko, V., Mechawar, N., & Turecki, G. (2014) · The International Journal of Neuropsychopharmacology · doi:10.1017/s1461145713000941 · Cited by 103 · see citing works
MicroRNAs as biomarkers of resilience or vulnerability to stress
Chen, R. J., Kelly, G., Sengupta, A., Heydendael, W., Nicholas, B., Beltrami, S., Luz, S., Peixoto, L., Abel, T. G., & Bhatnagar, S. (2015) · Neuroscience · doi:10.1016/j.neuroscience.2015.07.045 · Cited by 100 · see citing works
MicroRNA dysregulation in neuropsychiatric disorders and cognitive dysfunction
Xu, B., Hsu, P.-K., Karayiorgou, M., & Gogos, J. A. (2012) · Neurobiology of Disease · doi:10.1016/j.nbd.2012.02.016 · Cited by 82 · see citing works
MiR-335 is involved in major depression disorder and antidepressant treatment through targeting GRM4
Li, J., Meng, H., Cao, W., & Qiu, T. (2015) · Neuroscience Letters · doi:10.1016/j.neulet.2015.08.038 · Cited by 73 · see citing works
Jaffee, S. R. (2007) · Development and Psychopathology · doi:10.1017/s0954579407000326 · Cited by 66 · see citing works
Marzi, M. J., Montani, F., Carletti, R. M., Dezi, F., Dama, E., Bonizzi, G., Sandri, M. T., Rampinelli, C., Bellomi, M., Maisonneuve, P., et al. (2016) · Clinical Chemistry · doi:10.1373/clinchem.2015.251942 · Cited by 63 · see citing works
Role of non-coding RNA in the pathogenesis of depression
Liu, N., Wang, Z., Zhao, M., Zhang, Y., & Chen, N. (2019) · Gene · doi:10.1016/j.gene.2019.144276 · Cited by 61 · see citing works
Żurawek, D., Kuśmider, M., Faron‐Górecka, A., Gruca, P., Pabian, P., Solich, J., Kolasa, M., Papp, M., & Dziedzicka‐Wasylewska, M. (2016) · Molecular Neurobiology · doi:10.1007/s12035-016-0107-9 · Cited by 46 · see citing works
Self-citationŻurawek, D., Kuśmider, M., Faron‐Górecka, A., Gruca, P., Pabian, P., Kolasa, M., Solich, J., Szafran‐Pilch, K., Papp, M., & Dziedzicka‐Wasylewska, M. (2015) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2015.11.013 · Cited by 38 · see citing works
Self-citationXie, L., Chen, J., Yong-min, D., Gui, X., Wu, L., Tian, S., & Wu, W. (2019) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2019.02.078 · Cited by 38 · see citing works
Bahí, A., & Dreyer, J. (2018) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2018.09.004 · Cited by 31 · see citing works
Increased risk of chronic liver disease in patients with bipolar disorder: A population-based study
Hsu, J., Chien, I., & Lin, C. (2016) · General Hospital Psychiatry · doi:10.1016/j.genhosppsych.2016.07.006 · Cited by 27 · see citing works
Andolina, D., Segni, M. D., Accoto, A., Iacono, L. L., Borreca, A., Ielpo, D., Berretta, N., Perlas, E., Puglisi‐Allegra, S., & Ventura, R. (2018) · Molecular Neurobiology · doi:10.1007/s12035-018-0925-z · Cited by 27 · see citing works
Potential Roles of microRNAs in the Regulation of Monoamine Oxidase A in the Brain
Higuchi, Y., Soga, T., & Parhar, I. S. (2018) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2018.00339 · Cited by 22 · see citing works
Solich, J., Kuśmider, M., Faron‐Górecka, A., Pabian, P., Kolasa, M., Zemła, B., & Dziedzicka‐Wasylewska, M. (2020) · Cells · doi:10.3390/cells9040917 · Cited by 14 · see citing works
Self-citationStress-induced regulation of glucocorticoid receptor gene expression in the rat.
Ln, S., Yl, Y., & Rb, X. (1991) · PubMed · Cited by 10 · see citing works
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Li, Y., Fan, C., Wang, L., Lan, T., Gao, R., Wang, W., & Yu, S. Y. (2021) · Journal of Clinical Investigation · doi:10.1172/jci148853 · Cited by 90 · see citing works
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- Authors
- Solich, J., Kuśmider, M., Faron-Górecka, A., Pabian, P., & Dziedzicka-Wasylewska, M.
- Affiliations
- Maj Institute of Pharmacology (PL)
- Maj Institute of Pharmacology Polish Academy of Sciences, Smętna Street 12, 31-343 Kraków, Poland
- Corresponding author
- Solich, Joanna
- Venue
- International Journal of Molecular Sciences
- Publisher
- MDPI AG
- Published
- 2020-12-12
- Volume
- 21
- Issue
- 24
- Pages
- 9469
- ISSN
- 1422-0067 (ISSN-L)
- PMC
- PMC7763317
- OpenAlex
- W3111489577
- Cited by
- 13
- References
- 47
- Citations by year
- 2025: 2 · 2024: 4 · 2023: 2 · 2021: 5
- FWCI
- 0.60
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- International Journal of Molecular Sciences (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Science Centre Poland (2016/23/B/NZ4/01086)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › MicroRNA in disease regulation
- Life Sciences › Neuroscience › Behavioral Neuroscience › Stress Responses and Cortisol
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Keywords
- restraint stress, microRNA, serum microRNA expression, depression, stress-related genes, stress sensitivity, miRNA target prediction, mouse genotypes
- MeSH terms
- Machine Learning, Algorithms, Animals, Depression, Gene Expression Regulation, Mice, Inbred C57BL, Restraint, Physical, Stress, Physiological, Signal Transduction, Down-Regulation, Up-Regulation, Mice, Knockout, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, MicroRNAs, Norepinephrine Plasma Membrane Transport Proteins, Mice, Gene Regulatory Networks, Real-Time Polymerase Chain Reaction, Gene Ontology
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