Role of statins in regulating molecular pathways following traumatic brain injury: A system pharmacology study

Exploration of the Key Genes Involved in Non-alcoholic Fatty Liver Disease and Possible MicroRNA Therapeutic Targets

Background

MicroRNAs (miRNAs) are promising therapeutic agents for non-alcoholic fatty liver disease (NAFLD). This study aimed to identify key genes/proteins involved in NAFLD pathogenesis and progression and to evaluate miRNAs influencing their expression.

Methods

Gene expression profiles from datasets GSE151158, GSE163211, GSE135251, GSE167523, GSE46300, and online databases were analyzed to identify significant NAFLD-related genes. Then, protein-protein interaction networks and module analysis identified hub genes/proteins, which were validated using real-time PCR in oleic acid-treated HepG2 cells. Functional enrichment analysis evaluated signaling pathways and biological processes. Gene-miRNA interaction networks identified miRNAs targeting critical NAFLD genes.

Results

The most critical overexpressed hub genes/proteins included: TNF, VEGFA, TLR4, CYP2E1, ACE, SCD, FASN, SREBF2, and TGFB1 based on PPI network analysis, of which TNF, TLR4, SCD, FASN, SREBF2, and TGFB1 were up-regulated in oleic acid-treated HepG2 cells. Functional enrichment analysis for biological processes highlighted programmed necrotic cell death, lipid metabolic process response to reactive oxygen species, and inflammation. In the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, the highest adjusted P-value signaling pathways encompassed AGE-RAGE in diabetic complications, TNF, and HIF-1 signaling pathways. In gene-miRNA network analysis, miR-16 and miR-124 were highlighted as the miRNAs exerting the most influence on important NAFLD-related genes.

Conclusion

In silico analyses identified NAFLD therapeutic targets and miRNA candidates to guide further experimental investigation.

Effect of Calebin-A on Critical Genes Related to NAFLD: A Protein-Protein Interaction Network and Molecular Docking Study

Background

Calebin-A is a minor phytoconstituent of turmeric known for its activity against inflammation, oxidative stress, cancerous, and metabolic disorders like Non-alcoholic fatty liver disease(NAFLD). Based on bioinformatic tools. Subsequently, the details of the interaction of critical proteins with Calebin-A were investigated using the molecular docking technique.

Methods

We first probed the intersection of genes/ proteins between NAFLD and Calebin-A through online databases. Besides, we performed an enrichment analysis using the ClueGO plugin to investigate signaling pathways and gene ontology. Next, we evaluate the possible interaction of Calebin-A with significant hub proteins involved in NAFLD through a molecular docking study.

Results

We identified 87 intersection genes Calebin-A targets associated with NAFLD. PPI network analysis introduced 10 hub genes (TP53, TNF, STAT3, HSP90AA1, PTGS2, HDAC6, ABCB1, CCT2, NR1I2, and GUSB). In KEGG enrichment, most were associated with Sphingolipid, vascular endothelial growth factor A (VEGFA), C-type lectin receptor, and mitogen-activated protein kinase (MAPK) signaling pathways. The biological processes described in 87 intersection genes are mostly concerned with regulating the apoptotic process, cytokine production, and intracellular signal transduction. Molecular docking results also directed that Calebin-A had a high affinity to bind hub proteins linked to NAFLD.

Conclusion

Here, we showed that Calebin-A, through its effect on several critical genes/ proteins and pathways, might repress the progression of NAFLD.

Microarray-based Detection of Critical Overexpressed Genes in the Progression of Hepatic Fibrosis in Non-alcoholic Fatty Liver Disease: A Protein-protein Interaction Network Analysis

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is a prevalent cause of chronic liver disease and encompasses a broad spectrum of disorders, including simple steatosis, steatohepatitis, fibrosis, cirrhosis, and liver cancer. However, due to the global epidemic of NAFLD, where invasive liver biopsy is the gold standard for diagnosis, it is necessary to identify a more practical method for early NAFLD diagnosis with useful therapeutic targets; as such, molecular biomarkers could most readily serve these aims. To this end, we explored the hub genes and biological pathways in fibrosis progression in NAFLD patients.

METHODS

Raw data from microarray chips with GEO accession GSE49541 were downloaded from the Gene Expression Omnibus database, and the R package (Affy and Limma) was applied to investigate differentially expressed genes (DEGs) involved in the progress of low- (mild 0-1 fibrosis score) to high- (severe 3-4 fibrosis score) fibrosis stage NAFLD patients. Subsequently, significant DEGs with pathway enrichment were analyzed, including gene ontology (GO), KEGG and Wikipathway. In order to then explore critical genes, the protein-protein interaction network (PPI) was established and visualized using the STRING database, with further analysis undertaken using Cytoscape and Gephi software. Survival analysis was undertaken to determine the overall survival of the hub genes in the progression of NAFLD to hepatocellular carcinoma.

RESULTS

A total of 311 significant genes were identified, with an expression of 278 being upregulated and 33 downregulated in the high vs. low group. Gene functional enrichment analysis of these significant genes demonstrated major involvement in extracellular matrix (ECM)-receptor interaction, protein digestion and absorption, and the AGE-RAGE signaling pathway. The PPI network was constructed with 196 nodes and 572 edges with PPI enrichment using a p-value < 1.0 e-16. Based on this cut-off, we identified 12 genes with the highest score in four centralities: Degree, Betweenness, Closeness, and Eigenvector. Those twelve hub genes were CD34, THY1, CFTR, COL3A1, COL1A1, COL1A2, SPP1, THBS1, THBS2, LUM, VCAN, and VWF. Four of these hub genes, namely CD34, VWF, SPP1, and VCAN, showed significant association with the development of hepatocellular carcinoma.

CONCLUSION

This PPI network analysis of DEGs identified critical hub genes involved in the progression of fibrosis and the biological pathways through which they exert their effects in NAFLD patients. Those 12 genes offer an excellent opportunity for further focused research to determine potential targets for therapeutic applications.

Comparison of Antioxidant Capacity and Network Pharmacology of Phloretin and Phlorizin against Neuroinflammation in Traumatic Brain Injury

Neuroinflammation is a hallmark of traumatic brain injury (TBI)'s acute and chronic phases. Despite the medical and scientific advances in recent years, there is still no effective treatment that mitigates the oxidative and inflammatory damage that affects neurons and glial cells. Therefore, searching for compounds with a broader spectrum of action that can regulate various inflammatory signaling pathways is of clinical interest. In this study, we determined not only the in vitro antioxidant capacity of apple pomace phenolics, namely, phlorizin and its metabolite, phloretin, but we also hypothesize that the use of these bioactive molecules may have potential use in TBI. We explored the antioxidant effects of both compounds in vitro (DPPH, iron-reducing capacity (IRC), and Folin-Ciocalteu reducing capacity (FCRC)), and using network pharmacology, we investigated the proteins involved in their protective effects in TBI. Our results showed that the antioxidant properties of phloretin were superior to those of phlorizin in the DPPH (12.95 vs. 3.52 mg ascorbic acid equivalent (AAE)/L), FCRC (86.73 vs. 73.69 mg gallic acid equivalent (GAE)/L), and iron-reducing capacity (1.15 vs. 0.88 mg GAE/L) assays. Next, we examined the molecular signature of both compounds and found 11 proteins in common to be regulated by them and involved in TBI. Meta-analysis and GO functional enrichment demonstrated their implication in matrix metalloproteinases, p53 signaling, and cell secretion/transport. Using MCODE and Pearson's correlation analysis, a subcluster was generated. We identified ESR1 (estrogen receptor alpha) as a critical cellular hub being regulated by both compounds and with potential therapeutic use in TBI. In conclusion, our study suggests that because of their vast antioxidant effects, probably acting on estrogen receptors, phloretin and phlorizin may be repurposed for TBI treatment due to their ease of obtaining and low cost.

Effect of Curcumin on Attenuation of Liver Cirrhosis via Genes/Proteins and Pathways: A System Pharmacology Study

Background: Liver cirrhosis is a life-threatening seqsuel of many chronic liver disorders of varying etiologies. In this study, we investigated protein targets of curcumin in liver cirrhosis based on a bioinformatics approach. Methods: Gene/protein associations with curcumin and liver cirrhosis were probed in drug−gene and gene−diseases databases including STITCH/DGIdb/DisGeNET/OMIM/DISEASES/CTD/Pharos and SwissTargetPrediction. Critical clustering groups (MCODE), hub candidates and critical hub genes in liver cirrhosis were identified, and connections between curcumin and liver cirrhosis-related genes were analyzed via Venn diagram. Interaction of hub genes with curcumin by molecular docking using PyRx-virtual screening tools was performed. Results: MCODE analysis indicated three MCODEs; the cluster (MCODE 1) comprised 79 nodes and 881 edges (score: 22.59). Curcumin database interactions recognized 318 protein targets. Liver cirrhosis genes and curcumin protein targets analysis demonstrated 96 shared proteins, suggesting that curcumin may influence 20 candidate and 13 hub genes, covering 81% of liver cirrhosis critical genes and proteins. Thirteen shared proteins affected oxidative stress regulation, RNA, telomerase activity, cell proliferation, and cell death. Molecular docking analysis showed the affinity of curcumin binding hub genes (Binding affinity: ΔG < −4.9 kcal/mol). Conclusions: Curcumin impacted on several critical liver cirrhosis genes mainly involved in extracellular matrix communication, focal adhesion, and the response to oxidative stress.

Therapeutic Role of Curcumin in Diabetes: An Analysis Based on Bioinformatic Findings

BACKGROUND

Diabetes is an increasingly prevalent global disease caused by the impairment in insulin production or insulin function. Diabetes in the long term causes both microvascular and macrovascular complications that may result in retinopathy, nephropathy, neuropathy, peripheral arterial disease, atherosclerotic cardiovascular disease, and cerebrovascular disease. Considerable effort has been expended looking at the numerous genes and pathways to explain the mechanisms leading to diabetes-related complications. Curcumin is a traditional medicine with several properties such as being antioxidant, anti-inflammatory, anti-cancer, and anti-microbial, which may have utility for treating diabetes complications. This study, based on the system biology approach, aimed to investigate the effect of curcumin on critical genes and pathways related to diabetes.

METHODS

We first searched interactions of curcumin in three different databases, including STITCH, TTD, and DGIdb. Subsequently, we investigated the critical curated protein targets for diabetes on the OMIM and DisGeNET databases. To find important clustering groups (MCODE) and critical hub genes in the network of diseases, we created a PPI network for all proteins obtained for diabetes with the aid of a string database and Cytoscape software. Next, we investigated the possible interactions of curcumin on diabetes-related genes using Venn diagrams. Furthermore, the impact of curcumin on the top scores of modular clusters was analysed. Finally, we conducted biological process and pathway enrichment analysis using Gene Ontology (GO) and KEGG based on the enrichR web server.

RESULTS

We acquired 417 genes associated with diabetes, and their constructed PPI network contained 298 nodes and 1651 edges. Next, the analysis of centralities in the PPI network indicated 15 genes with the highest centralities. Additionally, MCODE analysis identified three modular clusters, which highest score cluster (MCODE 1) comprises 19 nodes and 92 edges with 10.22 scores. Screening curcumin interactions in the databases identified 158 protein targets. A Venn diagram of genes related to diabetes and the protein targets of curcumin showed 35 shared proteins, which observed that curcumin could strongly interact with ten of the hub genes. Moreover, we demonstrated that curcumin has the highest interaction with MCODE1 among all MCODs. Several significant biological pathways in KEGG enrichment associated with 35 shared included the AGE-RAGE signaling pathway in diabetic complications, HIF-1 signaling pathway, PI3K-Akt signaling pathway, TNF signaling, and JAK-STAT signaling pathway. The biological processes of GO analysis were involved with the cellular response to cytokine stimulus, the cytokine-mediated signaling pathway, positive regulation of intracellular signal transduction and cytokine production in the inflammatory response.

CONCLUSION

Curcumin targeted several important genes involved in diabetes, supporting the previous research suggesting that it may have utility as a therapeutic agent in diabetes.