Identification of Crucial Genes and Diagnostic Value Analysis in Major Depressive Disorder Using Bioinformatics Analysis.

AIM AND OBJECTIVE: Despite the prevalence and burden of major depressive disorder (MDD), our current understanding of the pathophysiology is still incomplete. Therefore, this paper aims to explore genes and evaluate their diagnostic ability in the pathogenesis of MDD. METHODS: Firstly, the expression profiles of mRNA and microRNA were downloaded from the gene expression database and analyzed by the GEO2R online tool to identify differentially expressed genes (DEGs) and differentially expressed microRNAs (DEMs). Then, the DAVID tool was used for functional enrichment analysis. Secondly, the comprehensive protein-protein interaction (PPI) network was analyzed using Cytoscape, and the network MCODE was applied to explore hub genes. Thirdly, the receiver operating characteristic (ROC) curve of the core gene was drawn to evaluate clinical diagnostic ability. Finally, mirecords was used to predict the target genes of DEMs. RESULTS: A total of 154 genes were identified as DEGs, and 14 microRNAs were identified as DEMs. Pathway enrichment analysis showed that DEGs were mainly involved in hematopoietic cell lineage, PI3K-Akt signaling pathway, cytokine-cytokine receptor interaction, chemokine signaling pathway, and JAK-STAT signaling pathway. Three important modules are identified and selected by the MCODE clustering algorithm. The top 12 hub genes, including CXCL16, CXCL1, GNB5, GNB4, OPRL1, SSTR2, IL7R, MYB, CSF1R, GSTM1, GSTM2, and GSTP1, were identified as important genes for subsequent analysis. Among these important hub genes, GSTM2, GNB4, GSTP1 and CXCL1 have the good diagnostic ability. Finally, by combining these four genes, the diagnostic ability of MDD can be improved to 0.905, which is of great significance for the clinical diagnosis of MDD. CONCLUSION: Our results indicate that GSTM2, GNB4, GSTP1 and CXCL1 have potential diagnostic markers and are of great significance in clinical research and diagnostic application of MDD. This result needs a large sample study to further confirm the pathogenesis of MDD.

Impact of Pricing and Product Information on Consumer Buying Behavior With Customer Satisfaction in a Mediating Role.

The relationship between product pricing and product packaging plays an important role in the buying behavior of consumers, whereas customer satisfaction plays a mediating role. To test these hypotheses, research was conducted on university students in China. Questionnaire-based convenience sampling was conducted on 500 students for data collection using online and offline sources. A total of 367 (73%) students responded, and 17 questionnaires were rejected due to missing information. SPSS and AMOS software were used for the data analysis. Product pricing and product information were independent variables in this study, whereas consumer buying behavior was a dependent variable. Customer satisfaction is mediated by one dependent and two independent variables. Confirmatory factor analysis, path analysis, and discriminant validity in structural equation modeling revealed that product pricing and packaging had a statistically significant relationship with the buyer decision process. The introduction of satisfaction as a mediating variable led to the observation of full mediation in the case of product pricing and partial mediation in product packaging. Given the results of this research, product managers should adopt pricing tactics along with product packaging to influence the buying intentions of consumers.

Branched-Chain Amino Acids Catabolism Pathway Regulation Plays a Critical Role in the Improvement of Leukopenia Induced by Cyclophosphamide in 4T1 Tumor-Bearing Mice Treated With Lvjiaobuxue Granule.

Background: Cyclophosphamide is a common tumor chemotherapy drug used to treat various cancers. However, the resulting immunosuppression leads to leukopenia, which is a serious limiting factor in clinical application. Therefore, the introduction of immunomodulators as adjuvant therapy may help to reduce the hematological side effects of cyclophosphamide. Lvjiaobuxue granule has been widely used in the clinical treatment of gynecological diseases such as anemia and irregular menstruation. Recently, it has been found to increase the function of white blood cells, but its mechanism of action is still unclear. We aimed to reveal the mechanisms of Lvjiaobuxue granule against acute leukopenia by an integrated strategy combining metabolomics with network pharmacology. Methods: Subcutaneously inoculated 4T1 breast cancer cells to prepare tumor-bearing mice, intraperitoneal injection of cyclophosphamide to establish a 4T1 tumor-bearing mice leukopenia animal model, using pharmacodynamic indicators, metabolomics, network pharmacology and molecular biology and other technical methods. To comprehensively and systematically elucidate the effect and mechanism of Lvjiaobuxue granule in improving cyclophosphamide-induced leukopenia in 4T1 tumor-bearing mice. Results: Lvjiaobuxue granule can improve the blood routine parameters and organ index levels of the leukopenia model of 4T1 tumor-bearing mice. Metabolomics studies revealed that 15 endogenous metabolites in the spleen of mice were considered as potential biomarkers of Lvjiaobuxue granule for their protective effect. Metabonomics and network pharmacology integrated analysis indicated that Lvjiaobuxue granule exerted the leukocyte elevation activity by inhibiting the branched-chain amino acids (BCAAs) degradation pathway and increasing the levels of valine, leucine and isoleucine. The results of molecular biology also showed that Lvjiaobuxue granule can significantly regulate the key enzymes in the catabolism of BCAAs, which further illustrates the importance of BCAAs in improving leukopenia. Conclusion: Lvjiaobuxue granule exerts obvious pharmacological effects on the leukopenia model of 4T1 tumor-bearing mice induced by cyclophosphamide, which could be mediated by regulating the branched-chain amino acid degradation pathway and the levels of valine, leucine and isoleucine.

Comprehensive Analysis Strategy of Nervous-Endocrine-Immune-Related Metabolites to Evaluate Arachidonic Acid as a Novel Diagnostic Biomarker in Depression.

Depression is one of the most complex multifactorial diseases affected by genetic and environmental factors. The molecular mechanism underlying depression remains largely unclear. To address this issue, a novel nervous-endocrine-immune (NEI) network module was used to find the metabolites and evaluate the diagnostic ability of patients with depression. During this process, metabolites were acquired from a professional depression metabolism database. Over-representation analysis was performed using IMPaLA. Then, the metabolite-metabolite interaction (MMI) network of the NEI system was used to select key metabolites. Finally, the receiver operating characteristic curve analysis was evaluated for the diagnostic ability of arachidonic acid. The results show that the numbers of the nervous system, endocrine system, and immune system pathways are 10, 19, and 12 and the numbers of metabolites are 38, 52, and 13, respectively. The selected shared metabolite-enriched pathways can be 97.56% of the NEI-related pathways. Arachidonic acid was extracted from the NEI system network by using an optimization formula and validated by in vivo experiments. It was indicated that the proposed model was good at screening arachidonic acid for the diagnosis of depression. This method provides reliable evidences and references for the diagnosis and mechanism research of other related diseases.

Metabolomic analysis of the hippocampus in a rat model of chronic mild unpredictable stress-induced depression based on a pathway crosstalk and network module approach.

BACKGROUND: The molecular alterations underlying the pathogenesis of depression have not been systematically defined. Increasing evidence suggests that hippocampus metabolism is strongly involved in the pathogenesis of chronic mild unpredictable stress (CUMS)-induced depression. The principal objective of this study was to reveal important information concerning the pathogenesis of depression through a comprehensive analysis of metabolites in the hippocampus in a CUMS rat model. METHODS: Metabolites related to metabolic changes in the hippocampus in the CUMS model were collected from a depression-specific database and published literature. Potential metabolite pathways were identified by the Omicsolution tool. Then, crosstalk analysis was carried out to investigate the relationship between different important pathways. In addition, MetaboAnalyst was used to analyze potential metabolites for drug-related metabolite enrichment analysis, which was used to study hippocampus metabolite-related drug pathways in a CUMS model. Then, a metabolite-protein interaction (MPI) network was constructed and analyzed to identify important metabolites and proteins. The functional modules were extracted using the CNM network decomposition algorithm. Finally, neurotransmitters in the hippocampus of rats with CUMS depression were detected to verify the important pathways. RESULTS: In the current study, 53 significantly enriched pathways related to the 107 identified metabolites were selected, and the top ranked enriched pathways included arginine and proline metabolism, neuroactive ligand-receptor interaction, phenylalanine metabolism, bile secretion, and glutathione metabolism. Pathway crosstalk analysis showed that the significantly enriched pathways were divided into two interrelated modules, which were mainly involved in metabolism, signal transduction, neurotransmitters, and the endocrine system. Enrichment analysis of drug-related metabolic KEGG pathways identified the antibiotic pathways as the most important pathways. In the MPI network, the hub metabolites were phosphate, arachidonic acid, oxoglutaric acid, l-glutamic acid, and glutathione, and the hub proteins were Got1, Got2, Tat, Ccbl1, Ccbl2, Il4i1. A total of 16 functional modules were extracted from the MPI network by using the CNM algorithm. Finally, metabolites related to serotonergic synapses, dopaminergic synapses, and glutamatergic synapses were found to be involved in the pathology of depression. CONCLUSION: We found that neurotransmitter pathways (serotonergic synapses, dopaminergic synapses and glutamatergic synapses) in the hippocampus play a crucial role in the underlying molecular mechanism of depression, which provides useful clues for identifying the detailed depression-associated metabolic profiles.

MicroRNA-H4-5p encoded by HSV-1 latency-associated transcript promotes cell proliferation, invasion and cell cycle progression via p16-mediated PI3K-Akt signaling pathway in SHSY5Y cells.

Herpes simplex virus 1 (HSV-1) microRNAs (miRNAs) mostly located in transcription-associated transcript (LAT) region have been identified that play critical roles in the intricate host-pathogen interaction networks. Increasing evidences throw new insight into the role of miRNA-mediated miRNA-mRNA cross-talk in HSV-1 latent or acute infection. In the present study, we found that hsv-1 miR-H4-5p (here termed as miR-H4b) can down-regulate the expression of cyclin-dependent kinase inhibitor 2A (CDKN2A, p16) in neuroblastoma (SHSY5Y) cell lines. Decreased expression of miR-H4b was directly related to attenuated cell proliferation and invasion as well as malfunction of cell cycle in recombinant SHSY5Y cells that stably expressing miR-H4b. Bioinformatics analysis and luciferase assays demonstrated miR-H4b can directly target p16 mRNA. MiR-H4b exerts its pro-proliferation function through inhibition of the p16-related PI3K-Akt pathways. Our findings provide, for the first time, significant clues regarding the role of herpesvirus-encoded miRNAs as a viral modulator to host cells.

Mesothelin regulates growth and apoptosis in pancreatic cancer cells through p53-dependent and -independent signal pathway.

Mesothelin, a secreted protein, is overexpressed in some cancers, including pancreatic cancer. Rescent studies have shown that overexpression of mesothelin significantly increased tumor cell proliferation, and downregulation of mesothelin inhibited cell proliferation in pancreatic cancer cells, but its exact function and mechanism remains unclear. The aim of the present study was to evaluate the effects of mesothelin on proliferation and apoptosis in pancreatic cancer cells with different p53 status and to explore its signal pathway. Mesothelin levels were detected by western blot and RT-PCR assay in human pancreatic cancer AsPC-1, HPAC and Capan-2, Capan-1 and MIA PaCa-2 cell lines. Mesothelin was slienced by shRNA in AsPC-1, Capan-2 and Capan-1 cells with rich mesothelin level, and mesothelin was overexpressed in the HPAC and Capan-2 cells with less mesothelin level. We observed that in the AsPC-1 and Capan-1cells with mt-p53, and Capan-2 cells with wt-p53, shRNA mediated sliencing of the mesothelin significantly increased PUMA and Bax expression and caspase-3 activity, and decreased bcl-2 expression, followed by the reduced proliferation and colony forming capability and increased cell apoptosis. When PUMA was slienced by siRNA in the stable mesothelin shRNA transfected cells, proliferative capability was significantly increased, and apoptosis was decreased. However, in the Capan-2 cells with wt-p53, suppression of the mesothelin significantly increased wt-p53 levels. When p53 was blocked by siRNA in the stable mesothelin shRNA transfected Capan-2 cells, PUMA was inhibited, followed by increased proliferative capability and decreased cell apoptosis. In the HPAC and Capan-2 cells with wt-p53 and in the MIA PaCa-2 cells with mt-p53, overexpression of the mesothelin significantly decreased bax levels and increased bcl-2 levels, followed by increased proliferative and colony forming capability. Furthermore, mesothelin-shRNA-transfected cells exhibited a reduced rate of tumor growth under in vivo conditions. However, mesothelin-transfected cells exhibited a increased rate of tumor growth under in vivo conditions. Our data demonstrated that mesothelin promotes proliferation and inhibited apoptosis through p53-dependent pathway in pancreatic cancer cells with wt-p53, and p53-independent pathway in pancreatic cancer cells with mt-p53. Targeting mesothelin by shRNA is the important method for pancreatic cancer therapy.