Identification of target genes and pathways regulated by miRNA-132, miRNA-182, and miRNA-124 in depression: a bioinformatics analysis

Main Article Content

Shamaila Wadud
Sadia Fatima
Roshan Ali
Rubina Nazli
Zahid Khan
Muhammad Irfan

Abstract

OBJECTIVE: To investigate the associations of miRNA-132, miRNA-182, and miRNA-124 with long-term depression and elucidate their target genes and translational implications utilizing miRabel, a bioinformatics tool.


METHODS: This study is a part of a randomized controlled trial conducted in Psychiatry OPD of a teaching hospital, Peshawar, Pakistan from February-2021 till December-2021. It’s a computational study using miRabel which is a miRNA target prediction instrument. This software improves bioinformatic analysis by anticipation of microRNAs targets by grading and grouping.


RESULTS: By utilizing the miRabel software, our research reveals that miRNA-132, miRNA-182, and miRNA-124 target a total of 123 genes involved in long-term depression. Out of these genes, twelve (PRKCB, PLA2G4A, PRKCG, GNAZ, GNAO1, GUCY1B3, GNAI2, PLCB3, PPP2R1A, PLCB2, GNA11, and GUCY1A2) display significant potential impact, with scores close to 1.0 (0.9). These particular genes exhibit a stronger influence compared to other target genes of miRNA-132, miRNA-182, and miRNA-124 concerning long-term depression. Our investigation also revealed that these genes target several pathways, including Beta-catenin independent WNT signaling, Corticotropin-releasing hormone relating pathway, ErbB communicating path, G protein signaling, Glutamic acid  attachment, triggering  of AMPA receptors, GnRH communication , Ras signaling, Serotonin and anxiety-related events, communication by WNT, Signaling by GPCR, MAPK pathway, NO/cGMP/PKG neural-preservation, Phosphodiesterases neuronal tasks, Neuroinflammation and glutamatergic signing, along with several other pathways.


CONCLUSION: miRNAs such as miRNA-132, miRNA-182, and miRNA-124, identified via comprehensive bioinformatic analysis, show potential as depression biomarkers and treatment targets. Insight into their roles and target genes within depression pathways could inspire innovative treatment strategies.

Article Details

How to Cite
Wadud, S., S. Fatima, R. Ali, R. Nazli, Z. Khan, and M. Irfan. “Identification of Target Genes and Pathways Regulated by MiRNA-132, MiRNA-182, and MiRNA-124 in Depression: A Bioinformatics Analysis”. KHYBER MEDICAL UNIVERSITY JOURNAL, vol. 16, no. 1, Mar. 2024, pp. 30-7, doi:10.35845/kmuj.2024.23517.
Section
Original Articles

References

Ferrúa CP, Giorgi R, da Rosa LC, do Amaral CC, Ghisleni GC, Pinheiro RT, et al. MicroRNAs expressed in depression and their associated pathways: A systematic review and a bioinformatics analysis. J Chem Neuroanat 2019;100:101650. https://doi.org/10.1016/j.jchemneu.2019.101650

Alvarez-Mon MA, Ortega MA, García-Montero C, Fraile-Martinez O, Monserrat J, Lahera G, et al. Exploring the role of nutraceuticals in major depressive disorder (MDD): Rationale, state of the art and future prospects. Pharmaceuticals 2021;14(8):821. https://doi.org/10.3390/ph14080821

James SL, Abate D, Abate KH, Abay SM, Abbafati C, Abbasi N, et al. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. The Lancet 2018;392(10159):1789-858. https://doi.org/10.1016/S0140-6736(18)32279-7

Wan Y, Liu Y, Wang X, Wu J, Liu K, Zhou J, et al. Identification of differential microRNAs in cerebrospinal fluid and serum of patients with major depressive disorder. PLoS One 2015;10(3):e0121975. https://doi.org/10.1371/journal.pone.0121975

Lopez JP, Kos A, Turecki G. Major depression and its treatment: microRNAs as peripheral biomarkers of diagnosis and treatment response. Curr Opin Psychiatry 2018;31(1):7-16. https://doi.org/10.1097/YCO.0000000000000384

Hassan M, Amir A, Shahzadi S, Kloczkowski A. Therapeutic implications of microRNAs in depressive disorders: a review. Int J Mol Sci 2022;23(21):13530. https://doi.org/10.3390/ijms232113530

Xu YY, Xia QH, Xia QR, Zhang XL, Liang J. MicroRNA-based biomarkers in the diagnosis and monitoring of therapeutic response in patients with depression. Neuropsychiatr Dis Treat 2019;15:3583-97. https://doi.org/10.2147/NDT.S235186

Wani MY, Ganie NA, Rani S, Mehraj S, Mir MR, Baqual MF, et al. Advances and applications of Bioinformatics in various fields of life. Int J Fauna Biol Stud 2018;5(2):03-10.

Quillet A, Saad C, Ferry G, Anouar Y, Vergne N, Lecroq T, et al. Improving bioinformatics prediction of microRNA targets by ranks aggregation. Front genet 2020;10:1330. https://doi.org/10.3389/fgene.2019.01330

LITIS lab, University of Rouen Normandy, France. Accessed on: June 20, 2023. Available from URL: http://bioinfo.univ-rouen.fr/mirabel/

Lesk, Arthur M. "bioinformatics". Encyclopedia Britannica. 2023. Accessed on: June 20, 2023. Available from URL https://www.britannica.com/science/bioinformatics

National library of Medicine. PRKCB protein kinase C beta [Homo sapiens (human)] Gene ID: 5579. 2022. Accessed on: June 20, 2023. Available from URL: https://www.ncbi.nlm.nih.gov/gene/5579

National library of Medicine. PLA2G4A phospholipase A2 group IVA [ Homo sapiens (human)] Gene ID: 5321, updated on 21-Jun-2023. Accessed on: July 15, 2023. Available from URL: https://www.ncbi.nlm.nih.gov/gene/5321

National library of Medicine. PRKCG protein kinase C gamma [Homo sapiens (human)] Gene ID: 5582. 2023. Accessed on: July 25, 2023. Available from URL: https://www.ncbi.nlm.nih.gov/gene/5582

National library of Medicine. GNAZ G protein subunit alpha z [Homo sapiens (human)] Gene ID: 2781. 2023. Accessed on: July 21, 2023. Available from URL: https://www.ncbi.nlm.nih.gov/gene/2781

National library of Medicine. GNAO1 G protein subunit alpha o1 [Homo sapiens (human)] Gene ID: 2775. 2023. Accessed on: July 21, 2023. Available from URL https://www.ncbi.nlm.nih.gov/gene/2775

National library of Medicine. GNAI2 G protein subunit alpha i2 [Homo sapiens (human)] Gene ID: 2771.2023. Accessed on: July 20, 2023. Available from URL: https://www.ncbi.nlm.nih.gov/gene/2771

National library of Medicine. GUCY1B1 guanylate cyclase 1 soluble subunit beta 1 [Homo sapiens (human)] Gene ID: 2983. 2023. Accessed on: July 20, 2023. Available from URL: https://www.ncbi.nlm.nih.gov/gene/2983

National library of Medicine. PLCB2 phospholipase C beta 2 [Homo sapiens (human)] Gene ID: 5330. 2023. Accessed on: July 20, 2023. Available from URL: https://www.ncbi.nlm.nih.gov/gene/5330

National library of Medicine. PLCB3 phospholipase C beta 3 [Homo sapiens (human)] Gene ID: 5331. 2023. Accessed on: July 20, 2023. Available from URL: https://www.ncbi.nlm.nih.gov/gene/5331

National library of Medicine. PPP2R1A protein phosphatase 2 scaffold subunit Alpha [Homo sapiens (human)] Gene ID: 5518. 2023. Accessed on: July 20, 2023. Available from URL https://www.ncbi.nlm.nih.gov/gene/5518

National library of Medicine. GNA11 G protein subunit alpha 11 [Homo sapiens (human)] Gene ID: 2767. 2023. Accessed on: July 20, 2023. Available from URL: https://www.ncbi.nlm.nih.gov/gene/2767

National library of Medicine. GUCY1A2 guanylate cyclase 1 soluble subunit alpha 2 [Homo sapiens (human)] Gene ID: 2977. 2023. Accessed on: July 20, 2023. Available from URL: https://www.ncbi.nlm.nih.gov/gene/2977

Qian Y, Song J, Ouyang Y, Han Q, Chen W, Zhao X, et al. Advances in roles of miR-132 in the nervous system. Front Pharmacol 2017;8:770. https://doi.org/10.3389/fphar.2017.00770

Guo X, Li Z, Zhang C, Yi Z, Li H, Cao L, et al. Down-regulation of PRKCB1 expression in Han Chinese patients with subsyndromal symptomatic depression. J Psychiatr Res 2015;69:1-6. https://doi.org/10.1016/j.jpsychires.2015.07.011

Su KP, Huang SY, Peng CY, Lai HC, Huang CL, Chen YC, et al. Phospholipase A2 and cyclooxygenase 2 genes influence the risk of interferon-alpha-induced depression by regulating polyunsaturated fatty acids levels. Biol Psychiatry 2010;67(6):550-7. https://doi.org/10.1016/j.biopsych.2009.11.005

Pandey GN, Sharma A, Rizavi HS, Ren X. Dysregulation of Protein Kinase C in Adult Depression and Suicide: Evidence from Postmortem Brain Studies. Int J Neuropsychopharmacol 2021;24(5):400-408. https://doi.org/10.1093/ijnp/pyab003

Tsolakidou A, Czibere L, Pütz B, Trümbach D, Panhuysen M, Deussing JM et al. Gene expression profiling in the stress control brain region hypothalamic paraventricular nucleus reveals a novel gene network including amyloid beta precursor protein. BMC Genomics 2010;11:546. https://doi.org/10.1186/1471-2164-11-546

Alexander JM, Pirone A, Jacob MH. Excessive β-catenin in excitatory neurons results in reduced social and increased repetitive behaviors and altered expression of multiple genes linked to human autism. Front. Synap Neurosci 2020;12:14. https://doi.org/10.3389/fnsyn.2020.00014

He JG, Zhou HY, Wang F, Chen JG. Dysfunction of Glutamatergic Synaptic Transmission in Depression: Focus on AMPA Receptor Trafficking. BP GOS 2023;3(2):187-96. https://doi.org/10.1016/j.bpsgos.2022.02.007

Dwivedi Y. MicroRNAs in depression and suicide: recent insights and future perspectives. J Affect Disord 2018;240:146-54. https://doi.org/10.1016/j.jad.2018.07.075

Zhao C, Cai H, Wang H, Ge Z. Correlation between serum renin-angiotensin system (RAS) level and depression and anxiety symptoms in patients with Parkinson's disease. Saudi J Biol Sci 2021;28(4):2146-54. https://doi.org/10.1016/j.sjbs.2021.02.029

Philips GT, Ye X, Kopec AM, Carew TJ. MAPK establishes a molecular context that defines effective training patterns for long-term memory formation. J Neurosci 2013;33(17):7565-73. https://doi.org/10.1523/JNEUROSCI.5561-12.2013

Jernigan CS, Goswami DB, Austin MC, Iyo AH, Chandran A, Stockmeier CA, et al. The mTOR signaling pathway in the prefrontal cortex is compromised in major depressive disorder. Progress in Prog Neuro-Psychopharmacol Biol Psychiatry 2011;35(7):1774-9. https://doi.org/10.1016/j.pnpbp.2011.05.010

Haroon E, Miller AH, Sanacora G. Inflammation, Glutamate, and Glia: A Trio of Trouble in Mood Disorders. Neuropsychopharmacol 2017;42(1):193-215. https://doi.org/10.1038/npp.2016.199

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