Screening and verification of hub genes involved in osteoarthritis using bioinformatics

Exploration of the potential mechanism of Duhuo Jisheng Decoction in osteoarthritis treatment by using network pharmacology and molecular dynamics simulation

In this study, the active ingredients of 15 Chinese herbal medicines of Duhuo Jisheng Decoction and their corresponding targets were obtained from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. The microarray data of Osteoarthritis (OA) were obtained through the GEO database for differential analysis and then a drug target-OA-related gene protein-protein interaction (PPI) network was established. The potential targets of Duhuo Jisheng Decoction in the treatment of OA were acquired by intersecting the OA-associated genes with the target genes of active ingredients. Random walk with restart (RWR) analysis of PPI networks was performed using potential targets as seed, and the top 50 genes of affinity coefficients were used as key action genes of Duhuo Jisheng Decoction in the treatment of OA. A drug-active ingredient-gene interaction network was established. AKT1, a key target of Duhuo Jisheng Decoction in the treatment of OA, was obtained by topological analysis of the gene interaction network. Molecular docking and molecular dynamics verified the binding of AKT1 to its corresponding drug active ingredients. CETSA assay demonstrated that the combination of luteolin and AKT1 increased the stability of AKT1, and the combination efficiency was high. In conclusion, the molecular mechanism of Duhuo Jisheng Decoction in treating OA featured by multiple components, targets, and pathways had been further investigated in this study, which is of significance for discovering as well as developing new drugs for this disease. The findings can also offer personalized diagnosis and treatment strategies for patients with OA in clinical practice.

Regulon active landscape reveals cell development and functional state changes of human primary osteoblasts in vivo

BACKGROUND

While transcription factor (TF) regulation is known to play an important role in osteoblast development, differentiation, and bone metabolism, the molecular features of TFs in human osteoblasts at the single-cell resolution level have not yet been characterized. Here, we identified modules (regulons) of co-regulated genes by applying single-cell regulatory network inference and clustering to the single-cell RNA sequencing profiles of human osteoblasts. We also performed cell-specific network (CSN) analysis, reconstructed regulon activity-based osteoblast development trajectories, and validated the functions of important regulons both in vivo and in vitro.

RESULTS

We identified four cell clusters: preosteoblast-S1, preosteoblast-S2, intermediate osteoblasts, and mature osteoblasts. CSN analysis results and regulon activity-based osteoblast development trajectories revealed cell development and functional state changes of osteoblasts. CREM and FOSL2 regulons were mainly active in preosteoblast-S1, FOXC2 regulons were mainly active in intermediate osteoblast, and RUNX2 and CREB3L1 regulons were most active in mature osteoblasts.

CONCLUSIONS

This is the first study to describe the unique features of human osteoblasts in vivo based on cellular regulon active landscapes. Functional state changes of CREM, FOSL2, FOXC2, RUNX2, and CREB3L1 regulons regarding immunity, cell proliferation, and differentiation identified the important cell stages or subtypes that may be predominantly affected by bone metabolism disorders. These findings may lead to a deeper understanding of the mechanisms underlying bone metabolism and associated diseases.

Differential expression of cyclins CCNB1 and CCNG1 is involved in the chondrocyte damage of kashin-beck disease

The purpose of this study was clarify the relationship between the differential expression of cyclins CCNB1 and CCNG1 and chondrocyte damage in Kashin-Beck disease. Systematic review and high-throughput sequencing of chondrocytes derived from Kashin-Beck disease patients were combined to identify the differentially expressed cyclins and cyclin-dependent kinase genes. In parallel, weaned SD rats were treated with low selenium for 4 weeks and then T-2 toxin for 4 weeks. Knee cartilage was collected to harvest chondrocytes for gene expression profiling. Finally, the protein expression levels of CCNB1 and CCNG1 were verified in knee cartilage tissue of Kashin-Beck disease patients and normal controls by immunohistochemical staining. The systematic review found 52 cartilage disease-related cyclins and cyclin-dependent kinase genes, 23 of which were coexpressed in Kashin-Beck disease, including 15 upregulated and 8 downregulated genes. Under the intervention of a low selenium diet and T-2 toxin exposure, CCNB1 (FC = 0.36) and CCNG1 (FC = 0.73) showed a downward expression trend in rat articular cartilage. Furthermore, compared to normal controls, CCNB1 protein in Kashin-Beck disease articular cartilage was 71.98% and 66.27% downregulated in the superficial and middle zones, respectively, and 12.06% upregulated in the deep zone. CCNG1 protein was 45.66% downregulated in the superficial zone and 12.19% and 9.13% upregulated in the middle and deep zones, respectively. The differential expression of cyclins CCNB1 and CCNG1 may be related to articular cartilage damage in Kashin-Beck disease.

Identification of SCRG1 as a Potential Therapeutic Target for Human Synovial Inflammation

Synovial inflammation of joint tissue is the most important cause of tissue damage, joint destruction, and disability and is associated with higher morbidity or mortality. Therefore, this study aims to identify key genes in osteoarthritis synovitis tissue to increase our understanding of the underlying mechanisms of osteoarthritis and identify new therapeutic targets. Five GEO datasets with a total of 41 normal synovial membrane tissues and 45 osteoarthritis synovial membrane samples were used for analysis, and seven common differential genes were identified. The classification model constructed by LASSO analysis showed that six genes including CDKN1A, FOSB, STMN2, SLC2A3, TAC, and SCRG1 can be used as biomarkers of osteoarthritis, and the SCRG1 gene shows importance in osteoarthritis. Furthermore, drug database enrichment found that these six DEGs may be the drug targets of synovitis in osteoarthritis, and Valproic Acid CTD 00006977 may be a potential targeted therapeutic drug of SCRG1. Spearman correlation analysis was performed on the SCRG1 gene, and 27 genes with consistent expression were obtained. Functional analysis showed that 27 genes were mainly involved in metabolism, complement, antigen presentation, apoptosis, and regulation of immune pathways. The co-regulatory network of TFs-miRNA suggested that the SCRG1 gene may be regulated by hsa-miR-363-3p miRNA. In conclusion, SCRG1, as a diagnostic marker of osteoarthritis, co-regulates immune-related pathways through the interaction of related proteins, playing an important role in the occurrence and development of osteoarthritis, which may be a novel drug target.