Bioinformatics analysis of a TF-miRNA-lncRNA regulatory network in major depressive disorder

Bian, Qinglai; Chen, Jianbei; Wu, Jiajia; Ding, Fengmin; Li, Xiaojuan; Ma, Qingyu; Zhang, Liqing; Zou, Xiaojuan; Chen, Jiaxu

doi:10.1016/j.psychres.2021.113842

Cited by 15 publications

(7 citation statements)

References 56 publications

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“…However, considering that the microarrays of GSE45642 and GSE92538 only detected a limited number of genes, covering only 11875 and 10241 probes, respectively, we only conducted subsequent analyses on the DEGs of GSE53987. Genes with a log-fold change greater than 0.1 ( | logFC | > 0.1) and P value less than 0.05 (P < 0.05) were identified as DEGs [41].…”

Section: Analysis Of Bulk Transcriptomic Data From Postmortem Human B...mentioning

confidence: 99%

Does decreased autophagy and dysregulation of LC3A in astrocytes play a role in major depressive disorder?

He,

Shi,

et al. 2023

Transl Psychiatry

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Astrocytic dysfunction contributes to the molecular pathogenesis of major depressive disorder (MDD). However, the astrocytic subtype that mainly contributes to MDD etiology and whether dysregulated autophagy in astrocytes is associated with MDD remain unknown. Using a single-nucleus RNA sequencing (snRNA-seq) atlas, three astrocyte subtypes were identified in MDD, while C2 State-1Q astrocytes showed aberrant changes in both cell proportion and most differentially expressed genes compared with other subtypes. Moreover, autophagy pathways were commonly inhibited in astrocytes in the prefrontal cortices (PFCs) of patients with MDD, especially in C2 State-1Q astrocytes. Furthermore, by integrating snRNA-seq and bulk transcriptomic data, we found significant reductions in LC3A expression levels in the PFC region of CUMS-induced depressed mice, as well as in postmortem PFC tissues and peripheral blood samples from patients with MDD. These results were further validated by qPCR using whole-blood samples from patients with MDD and healthy controls. Finally, LC3A expression in the whole blood of patients with MDD was negatively associated with the severity of depressive symptoms. Overall, our results underscore autophagy inhibition in PFC astrocytes as a common molecular characteristic in MDD and might reveal a novel potential diagnostic marker LC3A.

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Section: Analysis Of Bulk Transcriptomic Data From Postmortem Human B...mentioning

confidence: 99%

Does decreased autophagy and dysregulation of LC3A in astrocytes play a role in major depressive disorder?

He,

Shi,

et al. 2023

Transl Psychiatry

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“…LncRNAs and mRNAs can act as miRNA sponges and compete with each other binding to mutual miRNAs, known as competitive endogenous RNAs (ceRNAs) (18). CeRNA networks formed by lncRNAs, miRNAs, and mRNAs mediating brain development, stress responses, and neural plasticity (19), and may serve as potential diagnostic or therapeutic markers for psychiatric disorders such as MDD and schizophrenia (19)(20)(21).…”

Section: Introductionmentioning

confidence: 99%

Aberrant plasma exosomal derived ceRNA networks as diagnosis biomarkers for adolescent major depressive disorder and its potential prediction for antidepressant

Liu

et al. 2023

Preprint

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Background: Major depressive disorder (MDD) in adolescence seriously endangers their mental and physical health and is associated with poor social and scholastic function. However, the diagnosis biomarkers for adolescent with MDD remain unclear. Methods：A total of 114 adolescent subjects were enrolled in this study, the comprehensive clinical and cognitive assessments were performed. Differential expressions of lncRNAs and mRNAs of plasma exosomes were screened by microarray assay. Two sets of ceRNA (lncRNAs-miRNAs-mRNAs) networks had been generated and candidate genes had been screened by bioinformatic analysis, and candidate genes were validated in cohort using qRT-PCR. Results：A total of 3752 differentially expressed lncRNAs and 1789 differentially expressed mRNAs were identified. AC156455.1, miR-126-5p, AAK1 and CCDC18AS1, miR-6835-5p, CCND2 were picked from each network as candidate genes. We found that the six candidate genes were differential expression between MDD patients and healthy controls, or before and after antidepressant treatment of MDD group. The expression levels of AAK1, CCDC18AS1 and miR6835 varied in efficacy after 8-week sertraline treatment. We also found that the expression of CCDC18AS1, miR-6835-5p, CCND2 (in the same network) at baseline could predicted antidepressant efficacy, which may be mediated through reducing suicidal ideation and improving cognitive function. Conclusion:Our study identified and validated the plasma exosome-derived ceRNA networks altered in adolescent with MDD, our findings provided potential diagnosis and therapeutic biomarkers for adolescent with MDD.

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“…The recent rapid development of bioinformatics with high-throughput gene expression detection and hub gene screening methods, as well as weighted gene co-expression network analysis (WGCNA), has been advantageous in identifying the genes or specific molecular cascades involved in complex diseases, providing strategies for elucidating the molecular mechanisms of depression. Some molecular characterization and gene signatures have been shown to have pathophysiological significance in the mechanism of depression ( Iwamoto et al, 2004 ; Bian et al, 2021 ; see also Liu et al, 2020 ). However, their biological functions need to be clarified, and integrated bioinformatic analyses of the transcription factors (TFs) and immune and methyladenosine gene characteristics in depression are still lacking.…”

Section: Introductionmentioning

confidence: 99%

General Transcription Factor IIF Polypeptide 2: A Novel Therapeutic Target for Depression Identified Using an Integrated Bioinformatic Analysis

Zhang

Cheng

Dong

et al. 2022

Front. Aging Neurosci.

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Depression currently affects 4% of the world’s population; it is associated with disability in 11% of the global population. Moreover, there are limited resources to treat depression effectively. Therefore, we aimed to identify a promising novel therapeutic target for depression using bioinformatic analysis. The GSE54568, GSE54570, GSE87610, and GSE92538 gene expression data profiles were retrieved from the Gene Expression Omnibus (GEO) database. We prepared the four GEO profiles for differential analysis, protein–protein interaction (PPI) network construction, and weighted gene co-expression network analysis (WGCNA). Gene Ontology functional enrichment and Kyoto Encyclopedia of Genes and Genomes metabolic pathway analyses were conducted to determine the key functions of the corresponding genes. Additionally, we performed correlation analyses of the hub genes with transcription factors, immune genes, and N6-methyladenosine (m6A) genes to reveal the functional landscape of the core genes associated with depression. Compared with the control samples, the depression samples contained 110 differentially expressed genes (DEGs), which comprised 56 downregulated and 54 upregulated DEGs. Moreover, using the WGCNA and PPI clustering analysis, the blue module and cluster 1 were found to be significantly correlated with depression. GTF2F2 was the only common gene identified using the differential analysis and WGCNA; thus, it was used as the hub gene. According to the enrichment analyses, GTF2F2 was predominantly involved in the cell cycle and JAK-STAT, PI3K-Akt, and p53 signaling pathways. Furthermore, differential and correlation analyses revealed that 9 transcription factors, 12 immune genes, and 2 m6A genes were associated with GTF2F2 in depression samples. GTF2F2 may serve as a promising diagnostic biomarker and treatment target of depression, and this study provides a novel perspective and valuable information to explore the molecular mechanism of depression.

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Bioinformatics analysis of a TF-miRNA-lncRNA regulatory network in major depressive disorder

Cited by 15 publications

References 56 publications

Does decreased autophagy and dysregulation of LC3A in astrocytes play a role in major depressive disorder?

Does decreased autophagy and dysregulation of LC3A in astrocytes play a role in major depressive disorder?

Aberrant plasma exosomal derived ceRNA networks as diagnosis biomarkers for adolescent major depressive disorder and its potential prediction for antidepressant

General Transcription Factor IIF Polypeptide 2: A Novel Therapeutic Target for Depression Identified Using an Integrated Bioinformatic Analysis

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