Genome-Wide miRNA Expression Profiling of Human Lymphoblastoid Cell Lines Identifies Tentative SSRI Antidepressant Response Biomarkers
Abstract
Aim Over 30% of patients with major depression do not respond well to first-line treatment with selective serotonin reuptake inhibitors (SSRIs). Using genome-wide expression profiling of human lymphoblastoid cell lines (LCLs) CHL1 was identified as a tentative SSRI sensitivity biomarker. This study reports on miRNAs implicated in SSRI sensitivity of LCLs. Methods Eighty LCLs were screened from healthy adult female individuals for growth inhibition by paroxetine. Eight LCLs exhibiting high or low sensitivities to paroxetine were chosen for genome-wide expression profiling with miRNA microarrays. Results The miRNA miR-151-3p had 6.7-fold higher basal expression in paroxetine-sensitive LCLs. This corresponds with lower expression of CHL1, a target of miR-151-3p. The additional miRNAs miR-212, miR-132, miR-30b*, let-7b and let-7c also differed by >1.5-fold (p Conclusion The potential value of these miRNAs as tentative SSRI response biomarkers awaits validation with lymphocyte samples of major depression patients.
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Some evidence suggests that SSRIs, SNRIs, or ketamine may exert their influence by affecting miRNAs.
“Some evidence suggests that SSRIs, SNRIs, or ketamine may exert their influence by affecting miRNAs.249,325–328”
From Epigenetic regulation in major depression and other stress-related disorders: molecular mechanisms, clinical relevance and therapeutic potential (2023) · cites this paper as [327]
Cites
Role of neurotrophic factors in depression
CASTREN, E., VOIKAR, V, & RANTAMAKI, T. (2007) · Current Opinion in Pharmacology · doi:10.1016/j.coph.2006.08.009 · Cited by 667 · see citing works
Souery, D., Oswald, P., Massat, I., Bailer, U., Bollen, J., Demyttenaere, K., Kasper, S., Lecrubier, Y., Montgomery, S., Serretti, A., et al. (2007) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.v68n0713 · Cited by 521 · see citing works
A Review of Current Guidelines for Depression Treatment
Gelenberg, A. J. (2010) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.9078tx1c · Cited by 137 · see citing works
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Yuan, M., Yang, B., Rothschild, G., Mann, J. J., Sanford, L. D., Tang, X., Huang, C., Wang, C., & Zhang, W. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01519-z · Cited by 246 · see citing works
Emerging role of microRNAs in major depressive disorder: diagnosis and therapeutic implications
Dwivedi, Y. (2014) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2014.16.1/ydwivedi · Cited by 169 · see citing works
MicroRNAs as critical biomarkers of major depressive disorder: a comprehensive perspective
Ortega, M. A., Alvarez-Mon, M. A., García-Montero, C., Fraile-Martinez, O., Lahera, G., Monserrat, J., Muñoz-Merida, L., Mora, F., Rodríguez-Jiménez, R., Fernandez-Rojo, S., et al. (2021) · Biomedicines · doi:10.3390/biomedicines9111659 · Cited by 57 · see citing works
Role of Monocyte-Derived MicroRNA106b∼25 in Resilience to Social Stress
Pfau, M. L., Menard, C., Cathomas, F., Desland, F., Kana, V., Chan, K. L., Shimo, Y., LeClair, K., Flanigan, M. E., Aleyasin, H., et al. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2019.02.023 · Cited by 46 · see citing works
The importance of epigenetics in diagnostics and treatment of major depressive disorder
Czarny, P., Białek, K., Ziółkowska, S., Strycharz, J., Barszczewska, G., & Sliwinski, T. (2021) · Journal of Personalized Medicine · doi:10.3390/jpm11030167 · Cited by 37 · see citing works
miRNAs in depression vulnerability and resilience: novel targets for preventive strategies
Lopizzo, N., Zonca, V., Cattane, N., Pariante, C. M., & Cattaneo, A. (2019) · Journal of Neural Transmission · doi:10.1007/s00702-019-02048-2 · Cited by 37 · see citing works
Liu, S., Zhou, B., Wang, L., Hu, H., Yao, C., Cai, Z., & Cui, X. (2018) · Medical Science Monitor · doi:10.12659/msm.908543 · Cited by 18 · see citing works
- Authors
- Oved, K., Morag, A., Pasmanik-Chor, M., Oron-Karni, V., Shomron, N., Rehavi, M., Stingl, J. C., & Gurwitz, D.
- Affiliations
- Tel Aviv University (IL)
- Bioinformatics Unit, George Wise Faculty of Life Sciences, Tel-Aviv University, Tel-Aviv, Israel
- Federal Institute for Drugs and Medical Devices (DE)
- Venue
- Pharmacogenomics
- Publisher
- Informa UK Limited
- Published
- 2012-07
- Volume
- 13
- Issue
- 10
- Pages
- 1129-1139
- ISSN
- 1462-2416 (ISSN-L)
- 1744-8042
- OpenAlex
- W2124680844
- Cited by
- 66
- References
- 3
- Citations by year
- 2025: 1 · 2024: 2 · 2023: 1 · 2022: 2 · 2021: 4 · 2020: 5 · 2019: 6 · 2018: 8 · 2017: 6 · 2016: 8 · 2015: 7 · 2014: 7 · 2013: 8 · 2012: 1
- FWCI
- 5.40
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Pharmacogenomics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Chief Scientist office
- Ministry of Health
- ERA-Net Neuron
- National Institution of Health (R01DC011835)
- The Israel Science Foundation, Israel (41/11)
- Topics
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › MicroRNA in disease regulation
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Keywords
- miRNA expression profiling, lymphoblastoid cell lines, CHL1, paroxetine, major depressive disorder, treatment-resistant depression, miR-151-3p, miR-212, miR-132, miR-30b, let-7b, let-7c, antidepressant sensitivity
- MeSH terms
- Cell Line, Transformed, Major Depressive Disorder, Female, Gene Expression Regulation, Humans, Cell Adhesion Molecules, Genome, Human, Selective Serotonin Reuptake Inhibitors, Paroxetine, Gene Expression Profiling, MicroRNAs, Biomarkers, Pharmacological
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