The use of gene arrays and corresponding connectivity mapping (Cmap) to identify novel anti-ageing ingredients

Osteoarthritis related epigenetic variations in miRNA expression and DNA methylation

Osteoarthritis (OA) is chronic arthritis characterized by articular cartilage degradation. However, a comprehensive regulatory network for OA-related microRNAs and DNA methylation modifications has yet to be established. Thus, we aimed to identify epigenetic changes in microRNAs and DNA methylation and establish the regulatory network between miRNAs and DNA methylation. The mRNA, miRNA, and DNA methylation expression profiles of healthy or osteoarthritis articular cartilage samples were downloaded from Gene Expression Omnibus (GEO) database, including GSE169077, GSE175961, and GSE162484. The differentially expressed genes (DEGs), differentially expressed miRNAs (DEMs), and differentially methylated genes (DMGs) were analyzed by the online tool GEO2R. DAVID and STRING databases were applied for functional enrichment analysis and protein-protein interaction (PPI) network. Potential therapeutic compounds for the treatment of OA were identified by Connectivity map (CMap) analysis. A total of 1424 up-regulated DEGs, 1558 down-regulated DEGs, 5 DEMs with high expression, 6 DEMs with low expression, 1436 hypermethylated genes, and 455 hypomethylated genes were selected. A total of 136 up-regulated and 65 downregulated genes were identified by overlapping DEGs and DEMs predicted target genes which were enriched in apoptosis and circadian rhythm. A total of 39 hypomethylated and 117 hypermethylated genes were obtained by overlapping DEGs and DMGs, which were associated with ECM receptor interactions and cellular metabolic processes, cell connectivity, and transcription. Moreover, The PPI network showed COL5A1, COL6A1, LAMA4, T3GAL6A, and TP53 were the most connective proteins. After overlapping of DEGs, DMGs and DEMs predicted targeted genes, 4 up-regulated genes and 11 down-regulated genes were enriched in the Axon guidance pathway. The top ten genes ranked by PPI network connectivity degree in the up-regulated and downregulated overlapping genes of DEGs and DMGs were further analyzed by the CMap database, and nine chemicals were predicted as potential drugs for the treatment of OA. In conclusion, TP53, COL5A1, COL6A1, LAMA4, and ST3GAL6 may play important roles in OA genesis and development.

Epigenetic Biomarkers Screening of Non-Coding RNA and DNA Methylation Based on Peripheral Blood Monocytes in Smokers

This study aims to use bioinformatics methods to determine the epigenetic changes in microRNA expression and DNA methylation caused by cigarette smoking. The data of mRNA, miRNA expression, and methylation microarray were obtained from the GEO database to filter differentially expressed genes (DEGs), differentially expressed miRNAs (DEMs), and methylated CpG probes (DMPs) through the limma package. The R clusterProfile package was used for functional annotation and enrichment analysis. The protein-protein interaction (PPI) network was constructed by the String database and visualized in Cytoscape software. Starbase database was employed to predict lncRNA and CirRNA based on the sequence of miRNA, and to establish a regulatory network of ceRNA. By overlapping DEG and DEM, 107 down-miRNA-targeted up-regulated genes and 65 up-miRNA-target down-regulated genes were obtained, which were mainly enriched in autophagy signaling pathways and protein ubiquitination pathways, respectively. In addition, 324 genes with low methylation and high expression and 204 genes with high methylation and low expression were respectively related to the degeneration of the nervous system and the function of the cardiovascular system. Interestingly, 43 genes were up-regulated under the dual regulation of reduced miRNA and hypomethylation, while 14 genes were down-regulated under the dual regulation of increased miRNA and hypermethylation. Ten chemicals have been identified as putative therapeutic agents for pathological conditions caused by smoking. In addition, among these genes, HSPA4, GRB2, PRKCA, and BCL2L1 could play a fundamental role in related diseases caused by smoking and may be used as the biomarkers for precise diagnosis and targets for future therapies of smoking-related diseases.

Identification of hub genes, key pathways, and therapeutic agents in Hutchinson-Gilford Progeria syndrome using bioinformatics analysis

BACKGROUND

Hutchinson-Gilford Progeria syndrome (HGPS) is a rare lethal premature and accelerated aging disease caused by mutations in the lamin A/C gene. Nevertheless, the mechanisms of cellular damage, senescence, and accelerated aging in HGPS are not fully understood. Therefore, we aimed to screen potential key genes, pathways, and therapeutic agents of HGPS by using bioinformatics methods in this study.

METHODS

The gene expression profile of GSE113648 and GSE41751 were retrieved from the gene expression omnibus database and analyzed to identify the differentially expressed genes (DEGs) between HGPS and normal controls. Then, gene ontology and the Kyoto encyclopedia of genes and genomes pathway enrichment analysis were carried out. To construct the protein-protein interaction (PPI) network, we used STRING and Cytoscape to make module analysis of these DEGs. Besides, the connectivity map (cMAP) tool was used as well to predict potential drugs.

RESULTS

As a result, 180 upregulated DEGs and 345 downregulated DEGs were identified, which were significantly enriched in pathways in cancer and PI3K-Akt signaling pathway. The top centrality hub genes fibroblast growth factor 2, decorin, matrix metallopeptidase2, and Fos proto-oncogene, AP-1 transcription factor subunit were screened out as the critical genes among the DEGs from the PPI network. Dexibuprofen and parthenolide were predicted to be the possible agents for the treatment of HGPS by cMAP analysis.

CONCLUSION

This study identified key genes, signal pathways and therapeutic agents, which might help us improve our understanding of the mechanisms of HGPS and identify some new therapeutic agents for HGPS.

Screening of key genes and prediction of therapeutic agents in Arsenic-induced lung carcinoma

BACKGROUND

Evidence indicates that inorganic arsenic (iAs) can directly damage cells and result in malignant transformation with unclear complicated mechanisms. In the present study, we aimed to explore the possible molecules, pathways and therapeutic agents by using bioinformatics methods.

METHODS

Microarray-based data were retrieved and analyzed to screen the differentially expressed genes (DEGs) between iAs-treated lung cells and controls. Then, the functions of DEGs were annotated and the hub genes were filtrated. The key genes were selected from the hub genes through validation in The Cancer Genome Atlas (TCGA) cohorts. Possible drugs were predicted by using CMAP tool.

RESULTS

Two datasets (GSE33520 and GSE36684) were retrieved, and 61 up-regulated and 228 down-regulated DEGs were screened out, which were enriched in various pathways, particularly metabolism-related pathways. Among the DEGs, four hub genes including MTIF2, ACOX1, CAV1, and MRPL17, which might affect lung cancer prognosis, were selected as the key genes. Interestingly, Quinostatin was predicted to be a potential agent reversing iAs-induced lung cell malignant transformation.

CONCLUSION

The present study sheds novel insights into the mechanisms of iAs-induced lung cell malignant transformation and identified several potential small agents for iAs toxicity prevention and therapy.

Microarray-based data mining reveals key genes and potential therapeutic drugs for Cadmium-induced prostate cell malignant transformation

Increasing evidence showed that Cadmium (Cd) can accumulate in the body and damage cells, resulting in cancerigenesis of the prostate with complex mechanisms. In the present study, we aimed to explore the possible key genes, pathways and therapeutic drugs using bioinformatics methods. Microarray-based data were retrieved and analyzed to screen differentially expressed genes (DEGs) between Cd-treated prostate cells and controls. Then, functions of the DEGs were annotated and hub genes were screened. Next, key genes were selected from the hub genes via validation in a prostate cancer cohort from The Cancer Genome Atlas (TCGA). Afterward, potential drugs were further predicted. Consequently, a gene expression profile, GSE9951, was retrieved. Then, 361 up-regulated and 30 down-regulated DEGs were screened out, which were enriched in various pathways. Among the DEGs, seven hub genes (HSPA5, HSP90AB1, RHOA, HSPD1, MAD2L1, SKP2, and CCT2) were dysregulated in prostate cancer compared to normal controls, and two of them (HSPD1 and CCT2) might influence the prostate cancer prognosis. Lastly, ionomycin was predicted to be a potential agent reversing Cd-induced prostate cell malignant transformation. In summary, the present study provided novel evidence regarding the mechanisms of Cd-induced prostate cell malignant transformation, and identified ionomycin as a potential small molecule against Cd toxicity.

Identifying key genes, pathways and screening therapeutic agents for manganese-induced Alzheimer disease using bioinformatics analysis

Alzheimer disease (AD) is a progressive neurodegenerative disease, the etiology of which remains largely unknown. Accumulating evidence indicates that elevated manganese (Mn) in brain exerts toxic effects on neurons and contributes to AD development. Thus, we aimed to explore the gene and pathway variations through analysis of high through-put data in this process.To screen the differentially expressed genes (DEGs) that may play critical roles in Mn-induced AD, public microarray data regarding Mn-treated neurocytes versus controls (GSE70845), and AD versus controls (GSE48350), were downloaded and the DEGs were screened out, respectively. The intersection of the DEGs of each datasets was obtained by using Venn analysis. Then, gene ontology (GO) function analysis and KEGG pathway analysis were carried out. For screening hub genes, protein-protein interaction network was constructed. At last, DEGs were analyzed in Connectivity Map (CMAP) for identification of small molecules that overcome Mn-induced neurotoxicity or AD development.The intersection of the DEGs obtained 140 upregulated and 267 downregulated genes. The top 5 items of biological processes of GO analysis were taxis, chemotaxis, cell-cell signaling, regulation of cellular physiological process, and response to wounding. The top 5 items of KEGG pathway analysis were cytokine-cytokine receptor interaction, apoptosis, oxidative phosphorylation, Toll-like receptor signaling pathway, and insulin signaling pathway. Afterwards, several hub genes such as INSR, VEGFA, PRKACB, DLG4, and BCL2 that might play key roles in Mn-induced AD were further screened out. Interestingly, tyrphostin AG-825, an inhibitor of tyrosine phosphorylation, was predicted to be a potential agent for overcoming Mn-induced neurotoxicity or AD development.The present study provided a novel insight into the molecular mechanisms of Mn-induced neurotoxicity or AD development and screened out several small molecular candidates that might be critical for Mn neurotoxicity prevention and Mn-induced AD treatment.

Identification of key genes and pathways and therapeutic agents in cadmium-treated liver cells: A bioinformatics study

Evidence indicates that Cadmium (Cd) can accumulate in liver, which results in acute or chronic cell damage with unclear complex mechanisms. Thus, we aimed to explore the possible molecules and pathways by using bioinformatics methods Consequently, two datasets (GSE8865 and GSE31286) were retrieved and the differentially expressed genes (DEGs) were screened out. The intersection of the DEGs included seven up-regulated and forty-three down-regulated genes, which were mainly enriched in biological cell proliferation items, and were enriched in several metabolism-related pathways. Among the DEGs, several hub genes such as EGR1, FOSL1, ITGA2, EDN1, and IER3 were screened out through protein-protein interaction analysis. Interestingly, BW-B70C was predicted to be a potential agent for attenuating Cd-induced liver cell damage. The present study gave a novel insight into the mechanisms of Cd-induced liver cell damage or malignant transformation and identified several small agents that might be critical for Cd toxicity prevention and treatment.

In vivo topical application of acetyl aspartic acid increases fibrillin-1 and collagen IV deposition leading to a significant improvement of skin firmness

OBJECTIVE

Acetyl aspartic acid (A-A-A) was discovered through gene array analysis with corresponding Cmap analysis. We found that A-A-A increased keratinocyte regeneration, inhibited dermal matrix metalloprotease (MMP) expression and relieved fibroblast stiffness through reduction of the fibroblast stiffness marker F-actin. Dermal absorption studies showed successful delivery to both the epidermal and dermal regions, and in-use trial demonstrated that 1% A-A-A was well tolerated. In this study, the aim was to investigate whether A-A-A could stimulate the synthesis of extracellular matrix supporting proteins in vivo and thereby improving the viscoelastic properties of human skin by conducting a dual histological and biophysical clinical study.

METHOD

Two separate double-blind vehicle-controlled in vivo studies were conducted using a 1% A-A-A containing oil-in-water (o/w) emulsion. In the histological study, 16 female volunteers (>55 years of age) exhibiting photodamaged skin on their forearm were included, investigating the effect of a 12-day treatment of A-A-A on collagen IV (COLIV) and fibrillin-1. In a subsequent pilot study, 0.1% retinol was used for comparison to A-A-A (1%). The biomechanical properties of the skin were assessed in a panel of 16 women (>45 years of age) using the standard Cutometer MPA580 after topical application of the test products for 28 days. The use of multiple suction enabled the assessment of F4, an area parameter specifically representing skin firmness.

RESULTS

Twelve-day topical application of 1% A-A-A significantly increased COLIV and fibrillin with 13% and 6%, respectively, compared to vehicle. 1% A-A-A and 0.1% retinol were found to significantly reduce F4 after 28 days of treatment by 15.8% and 14.7%, respectively, in the pilot Cutometer study. No significant difference was found between retinol and A-A-A. However, only A-A-A exhibited a significant effect vs. vehicle on skin firmness which indicated the incremental benefit of A-A-A as a skin-firming active ingredient.

CONCLUSION

In this study, we showed the in vivo efficacy of 1% A-A-A both on a protein level (fibrillin and collagen IV) and on a clinical end point, specifically skin firmness, providing proof that, acetyl aspartic acid has a strong potential as an anti-ageing 'cosmeceutical' ingredient answering the needs of our key consumer base.