Prognostic analysis and validation of diagnostic marker genes in patients with osteoporosis - Wang, Xing; Pei, Zhiwei; Hao, Ting; Ariben, Jirigala; Li, Siqin; He, Wanxiong; Kong, Xiangyu; Chang, Jiale; Zhao, Zhenqun; Zhang, Baoxin (Frontiers in Immunology, 2022)
Backgrounds: As a systemic skeletal dysfunction, osteoporosis (OP) is characterized by low bone mass, bone microarchitectural damage, and high global incidence. Methods: Data were obtained from GEO, GeneCards, STRING, GEPIA2 and other databases. R software was used to identify differentially expressed genes (DEGs) and perform functional analysis. We combined LASSO logistic regression and random forest algorithm to screen for diagnostic markers of OP, and the diagnostic value was assessed by receiver operating characteristic (ROC) curve. Molecular signature subtypes were identified using a consensus clustering approach, and prognostic analysis was performed on them. The level of immune cell infiltration was assessed by the CIBERSORT algorithm. The hub gene was obtained underlying the CytoHubba algorithm, and the serum samples of osteoporosis patients and healthy adults were detected by RT-qPCR, and the interaction network between the hub gene and miRNA, transcription factor，RNA binding protein and drugs was constructed. Results: A total of 40 DEGs, 14 OP-related differential genes, 6 OP diagnostic marker genes, 4 OP diagnostic marker key genes, and 10 hub genes (TNF, RARRES2, FLNA, STXBP2, EGR2, MAP4K2, NFKBIA, JUNB, SPI1, CTSD) were obtained. RT-qPCR detection results showed that 8 of them were significantly different. Enrichment analysis showed that they were mainly related to MAPK signaling pathway, TNF signaling pathway, apoptosis and Salmonella infection. RT-qPCR detection results showed that MAPK signaling pathway (p38, TRAF6), NF-kappa B signaling pathway (c-FLIP, MIP1β) are significantly different. The analysis of immune cell infiltration suggested that Monocytes, T cells CD4 memory activated, B cells memory and B cells naïve may be related to the occurrence and development of OP. Conclusions: We identified 6 novel OP diagnostic marker genes and 10 OP-Hub genes. These genes can be used to improve the prognostic performance of OP and to identify potential relationships between the immune microenvironment and OP. Our research will provide insights into the potential therapeutic targets and pathogenesis of the development of osteoporosis.