MicroRNAs expressed in depression and their associated pathways: A systematic review and a bioinformatics analysis

Ferrúa, Camila Perelló; Giorgi, Roberta; Rosa, Laísa Camerini da; Amaral, Cainá Corrêa do; Ghisleni, Gabriele; Pinheiro, Ricardo Tavares; Nedel, Fernanda

doi:10.1016/j.jchemneu.2019.101650

Cited by 41 publications

(35 citation statements)

References 70 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Screening by qRT-PCR revealed that mmu-mir-17-5p and mmu-mir-7b-5p were upregulated. Although there is no current evidence to prove their direct role in depression, the target gene Wfs1 of mmu-mir-17-5p is considered a candidate genetic marker related to the relief of depression (Ferrua et al, 2019). Therefore, Wfs1/UBTF/mmu-mir-17-5 may play an important role in the pathogenesis of depression caused by long-term stress.…”

Section: Discussionmentioning

confidence: 99%

Wfs1 and Related Molecules as Key Candidate Genes in the Hippocampus of Depression

et al. 2021

View full text Add to dashboard Cite

BackgroundDepression is a prevalent mental disorder, which is difficult to diagnose and treat due to its unclear pathogenic mechanisms. The discovery of novel and effective therapeutic targets for depression is urgently needed. The hippocampus is a crucial region involved in depression and has been a therapeutic target for many antidepressants. Thus, it is beneficial for comprehensive research to be carried out on the molecular mechanisms of the hippocampus involved in the pathogenesis of depression. This study aims to investigate the differentially expressed genes (DEG) in the hippocampus in a chronic unpredictable mild stress (CUMS) mouse model.MethodThe study obtained GSE84183 from the GEO database. The R language screened the differential expression genes (DEG) in the hippocampus tissue of depressed mice, and the enrichment pathways of DEGs were analyzed. A protein-protein interaction (PPI) network was constructed in the STRING database and visualized in Cytoscape software. MicroRNAs for these DEGs were obtained from TarBase and mortar base databases, and transcription factors (TF) related to DEG were predicted from the ENCODE database. Both networks used the visual analysis platform NetworkAnalyst. Finally, the microRNA-TF network was integrated based on the above two networks and imported into Cytoscape for further analysis.ResultsThis study screened 325 differentially expressed genes, containing 42 downregulated genes and 283 upregulated genes. Most of these genes are enriched in the cell cycle and the chemokine signaling pathway. Meanwhile, Wfs1, one of the top ten DEGs, was identified as the key regulator of the cell cycle and the participator in the highest number of modules screened out in PPI networks. Wfs1-related molecules, including UBTF, mmu-mir-17-5p, and mmu-mir-7b-5p, were therefore screened out. Furthermore, we confirmed the downregulation of Wfs1 and upregulation of UBTF/mmu-mir-17-5p/mmu-mir-7b-5p in the hippocampus of the CUMS mouse model. Our data indicate that Wfs1 and related molecules were predicted to be associated with the pathological process of depression. This research provided potential new molecular targets of stress-induced depression.

show abstract

Section: Discussionmentioning

confidence: 99%

Wfs1 and Related Molecules as Key Candidate Genes in the Hippocampus of Depression

et al. 2021

View full text Add to dashboard Cite

show abstract

“…There is evidence that a large number of miRNAs are specifically expressed or enriched in the brain or central nervous system, and the neurological disorders in depression patients are often accompanied by disorders in the expression of many miRNAs. 33 , 34 MiRNAs have been proven to be used for the diagnosis and treatment biomarkers of depression. 35 , 36 Here, we found that Berberine could regulate miR-34b-5p, miR-470-5p and BDNF expression, so we speculated that Berberine regulated the progression of depression disorder through miRNA/mRNA axis.…”

Section: Discussionmentioning

confidence: 99%

Berberine Suppresses Mice Depression Behaviors and Promotes Hippocampal Neurons Growth Through Regulating the miR-34b-5p/miR-470-5p/BDNF Axis

Zhan¹,

Xia²,

Wang³

2021

NDT

View full text Add to dashboard Cite

Background Berberine has been found to inhibit the progression of depression disorder, but its specific mechanism is still unclear. MicroRNA (miRNA) is considered to play an important role in the progression of depression. However, it is unclear whether Berberine is involved in the regulation of depression progression through miRNA. Methods The chronic unpredictable mild stress (CUMS) mice model was constructed. Mice depression behaviors were evaluated by sucrose preference test (SPT) and forced swim test (FST). Quantitative real-time PCR was employed to assess the expression of miR-34b-5p, miR-470-5p and brain-derived neurotrophic factor (BDNF). The protein expression of BDNF was examined using Western blot analysis. In addition, the viability and apoptosis of hippocampal neurons were determined using cell counting kit 8 assay, flow cytometry and TUNEL assay. The interaction between BDNF and miR-34b-5p or miR-470-5p was verified by dual-luciferase reporter assay and RNA immunoprecipitation assay. Results Our data indicated that Berberine could inhibit CUMS mice depression behaviors and enhance hippocampal neurons growth by targeting miR-34b-5p and miR-470-5p. In addition, we found that BDNF was a target of miR-34b-5p and miR-470-5p. Overexpressed BDNF could reverse the regulation of miR-34b-5p and miR-470-5p on CUMS mice depression behaviors and hippocampal neurons growth. Furthermore, Berberine could promote BDNF expression to regulate CUMS mice depression behaviors and hippocampal neurons growth. Conclusion Berberine might inhibit the progression of depression disorder by regulating the miR-34b-5p/miR-470-5p/BDNF axis.

show abstract

“…5 To date, the microarray technique has increasingly been used for life science research purposes, and bioinformatic data-mining of the gene has widely been used for differential expression analysis to identify novel diagnostic and therapeutic biomarkers of diseases. 6,7 Extensive research efforts investigating depression have been performed in past decades, and potential new therapeutic targets are being identified, including oxidative stress, immune system effects 8 and neuroinflammation 9 in the central nervous system (CNS), through cytokines, which regulate brain activities and emotions. In particular, a recognition that immune system actions profoundly impact mood regulation 10 has been particularly well established for inflammatory signals from the innate immune system linked to depression in human and rodent studies.…”

Section: Introductionmentioning

confidence: 99%

<p>Weighted Gene Coexpression Network Analysis Identifies Specific Modules and Hub Genes Related to Major Depression</p>

Zhang¹,

Xu²,

Yuan³

et al. 2020

NDT

View full text Add to dashboard Cite

Purpose: Despite advances in characterizing the neurobiology of emotional disorders, there is still a significant lack of scientific understanding of the pathophysiological mechanisms governing major depressive disorder (MDD). This study attempted to elucidate the molecular circuitry of MDD and to identify more potential genes associated with the pathogenesis of the disease. Patients and Methods: Microarray data from the GSE98793 dataset were downloaded from the NCBI Gene Expression Omnibus (GEO) database, including 128 patients with MDD and 64 healthy controls. Weighted gene coexpression network analysis (WGCNA) was performed to find modules of differentially expressed genes (DEGs) with high correlations followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to obtain further biological insight into the top three key modules. The protein-protein interaction (PPI) network, the modules from the PPI network, and the gene annotation enrichment of modules were analyzed, as well. Results: We filtered 3276 genes that were considered significant DEGs for further WGCNA analysis. By performing WGCNA, we found that the turquoise, blue and brown functional modules were all strongly correlated with MDD development, including immune response, neutrophil degranulation, ribosome biogenesis, T cell activation, glycosaminoglycan biosynthetic process, and protein serine/threonine kinase activator activity. Hub genes were identified in the key functional modules that might have a role in the progression of MDD. Functional annotation showed that these modules primarily enriched such KEGG pathways as the TNF signaling pathway, T cell receptor signaling pathway, primary immunodeficiency, Th1, Th2 and Th17 cell differentiation, autophagy and RNA degradation and oxidative phosphorylation. These results suggest that these genes are closely related to autophagy and cellular immune function. Conclusion: The results of this study may help to elucidate the pathophysiology of MDD development at the molecular level and explore the potential molecular mechanisms for new interventional strategies.

show abstract

MicroRNAs expressed in depression and their associated pathways: A systematic review and a bioinformatics analysis

Cited by 41 publications

References 70 publications

Wfs1 and Related Molecules as Key Candidate Genes in the Hippocampus of Depression

Wfs1 and Related Molecules as Key Candidate Genes in the Hippocampus of Depression

Berberine Suppresses Mice Depression Behaviors and Promotes Hippocampal Neurons Growth Through Regulating the miR-34b-5p/miR-470-5p/BDNF Axis

<p>Weighted Gene Coexpression Network Analysis Identifies Specific Modules and Hub Genes Related to Major Depression</p>

Contact Info

Product

Resources

About