Bioinformatics Analysis and Experimental Validation of Endoplasmic Reticulum Stress-Related Genes in Osteoporosis.

BACKGROUND

Endoplasmic reticulum stress (ERS) is closely associated with Osteoporosis (OP). In order to explore the role of ERS related genes in OP and its molecular mechanism.

METHODS

OP-related transcriptome data were retrieved from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was applied to screen OP-related genes. Differentially expressed ERS-related genes (DE-ERSGs) between OP and controls were identified by overlapping OP-related, differentially expressed genes (DEGs), and ERS-related genes. ERS-related genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to explore their functions. Receiver operating characteristic (ROC) curves assessed the diagnostic value of DE-ERSGs, and comparative toxicogenomics database (CTD) was used to predict targeting agents for key DE-ERSGs. Finally, biomarker expression was verified by real time quantitative polymerase chain reaction (RT-qPCR).

RESULTS

A total of 10 DE-ERSGs were screened in OP patients. GO and KEGG analyses indicated their enrichment in Alcoholic liver disease, Endometrial cancer, and Glycerolipid metabolism. ROC curve analysis revealed that RPN2, FOXO3, ERGIC2, and MYO9A had significant diagnostic value, thus being identified as key DE-ERSGs. Moreover, the key DE-ERSGs-drug interaction network showed that some drugs such as bisphenol A, Cisplatin, Cyclosporine, and Valproic Acid might play roles by targeting key DE-ERSGs in OP. The expression validation analysis of key DE-ERSGs revealed that RPN2, ERGIC2, and MYO9A was significantly expressed in the GSE62402. Ultimately, The blood samples RT-qPCR verification results show that RPN2, ERGIC2, and MYO9A were significantly lower in OP samples compared to normal samples (p < 0.05), whereas there was no difference in the expression levels of FOXO3.

CONCLUSION

RPN2, FOXO3, ERGIC2 and MYO9A as the biomarkers associated with ERS in OP by bioinformatics analysis, which may provide new biological targets for clinical treatment.