Understanding the relationship between inflammation, apoptosis, and diabetes osteoporosis: A bioinformatics approach and experimental verification.

Abstract

Diabetes osteoporosis (DOP) is a chronic metabolic bone disease. This study aimed to identify potential biomarkers of DOP and explore their underlying mechanisms through bioinformatics methods and experimental verification. Bioinformatics methods were used to identify differentially expressed genes (DEGs) for DOP based on GEO data and the GeneCards database. GO and KEGG enrichment analyses were used to search the key pathways. The STRING website was used to construct a protein-protein interaction (PPI) network and identify key genes. Then, 50 mg/mL glucose was used to interveneosteoblasts (OBs).CCK-8 and Alizarin Red staining were used to investigate the proliferation and differentiation changes in OBs. Flowcytometry was used to investigate apoptosis. The membrane protein chip, WB, and RT-PCR were used to verify the expression of key targets or pathways about DOP. Forty-two common genes were screened between DOP-related targets and DEGs. GO and KEGG enrichment analysis showed that DOP was mainly associated with cytokine-cytokine receptor interactions, and apoptosis. PPI network analysis showed that TNF, IL1A, IL6, IL1B, IL2RA, Fas ligand (FASLG), and Fas cell surface death receptor (FAS) were key up-regulated genes in the occurrence of DOP. The experiment results show that 50 mg/mL glucose significantly inhibited OBs proliferation but presented an increase in apoptosis. Membrane protein chip, WB, and RT-PCR-verified a significantly active in the expression of TNF/FASLG/FAS pathway. High glucose activated the TNF-α/FAS/FASLG pathway and induced the inflammatory microenvironment and apoptosis, then impaired osteogenic differentiation of OBs. These may be an important mechanism for the occurrence and development of DOP.