Bioinformatics analysis of differentially expressed genes involved in human developmental chondrogenesis

Identifying the key genes regulating mesenchymal stem cells chondrogenic differentiation: an in vitro study

Background

Mesenchymal stem cells (MSCs) possess the potential to differentiate into chondrocytes, which makes them an ideal source for healing cartilage defects. Here, we seek to identify the essential genes participating in MSCs chondrogenesis.

Methods

Human MSCs were induced for chondrogenesis for 7, 14, and 21 days using a high-density micromass culture system, and RNA was extracted for RNA-seq.

Results

A total of 6247 differentially expressed genes (DEGs) were identified on day 7, and 85 DEGs were identified on day 14. However, no significant DEGs was identified on day 21. The top 30 DEGs at day 7, including COL9A3, COL10A1, and CILP2, are closely related to extracellular matrix organization. While the top 30 DEGs at day 14 revealed that inflammation-related genes were enriched, including CXCL8, TLR2, and CCL20. We also conducted protein–protein interaction (PPI) networks analysis using the search tool for the retrieval of interacting genes (STRING) database and identified key hub genes, including CXCL8, TLR2, CCL20, and MMP3. The transcriptional factors were also analyzed, identifying the top 5 TFs: LEF1, FOXO1, RORA, BHLHE41, and SOX5. We demonstrated one particular TF, RORA, in promoting early MSCs chondrogenesis.

Conclusions

Taken together, our results suggested that these DEGs may have a complex effect on MSCs chondrogenesis both synergistically and solitarily.

Gene Expression Microarray Data Identify Hub Genes Involved in Osteoarthritis

The present study was performed to explore the underlying molecular mechanisms and screen hub genes of osteoarthritis (OA) via bioinformatics analysis. In total, twenty-five OA synovial tissue samples and 25 normal synovial tissue samples were derived from three datasets, namely, GSE55457, GSE55235, and GSE1919, and were used to identify the differentially expressed genes (DEGs) of OA by R language. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of DEGs were conducted using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). A Venn diagram was built to show the potential hub genes identified in all three datasets. The STRING database was used for constructing the protein–protein interaction (PPI) networks and submodules of DEGs. We identified 507 upregulated and 620 downregulated genes. Upregulated DEGs were significantly involved in immune response, MHC class II receptor activity, and presented in the extracellular region, while downregulated DEGs were mainly enriched in response to organic substances, extracellular region parts, and cadmium ion binding. Results of KEGG analysis indicated that the upregulated DEGs mainly existed in cell adhesion molecules (CAMs), while downregulated DEGs were significantly involved in the MAPK signaling pathway. A total of eighteen intersection genes were identified across the three datasets. These include Nell-1, ATF3, RhoB, STC1, and VEGFA. In addition, 10 hub genes including CXCL12, CXCL8, CCL20, and CCL4 were found in the PPI network and module construction. Identification of DEGs and hub genes associated with OA may be helpful for revealing the molecular mechanisms of OA and further promotes the development of relevant biomarkers and drug targets.

Recent Advances in Pharmacological Intervention of Osteoarthritis: A Biological Aspect

Osteoarthritis (OA) is a degenerative joint disease in the musculoskeletal system with a relatively high incidence and disability rate in the elderly. It is characterized by the degradation of articular cartilage, inflammation of the synovial membrane, and abnormal structure in the periarticular and subchondral bones. Although progress has been made in uncovering the molecular mechanism, the etiology of OA is still complicated and unclear. Nevertheless, there is no treatment method that can effectively prevent or reverse the deterioration of cartilage and bone structure. In recent years, in the field of pharmacology, research focus has shifted to disease prevention and early treatment rather than disease modification in OA. Biologic agents become more and more attractive as their direct or indirect intervention effects on the initiation or development of OA. In this review, we will discuss a wide spectrum of biologic agents ranging from DNA, noncoding RNA, exosome, platelet-rich plasma (PRP), to protein. We searched for key words such as OA, DNA, gene, RNA, exosome, PRP, protein, and so on. From the pharmacological aspect, stem cell therapy is a very special technique, which is not included in this review. The literatures ranging from January 2016 to August 2021 were included and summarized. In this review, we aim to help readers have a complete and precise understanding of the current pharmacological research progress in the intervention of OA from the biological aspect and provide an indication for the future translational studies.

Knockdown of long noncoding RNA HOTAIR inhibits osteoarthritis chondrocyte injury by miR-107/CXCL12 axis

BACKGROUND

Osteoarthritis (OA) is a joint disease characterized via destruction of cartilage. Chondrocyte damage is associated with cartilage destruction during OA. Long noncoding RNAs (lncRNAs) are implicated in the regulation of chondrocyte damage in OA progression. This study aims to investigate the role and underlying mechanism of lncRNA homeobox antisense intergenic RNA (HOTAIR) in OA chondrocyte injury.

METHODS

Twenty-three OA patients and healthy controls without OA were recruited. Chondrocytes were isolated from OA cartilage tissues. HOTAIR, microRNA-107 (miR-107) and C-X-C motif chemokine ligand 12 (CXCL12) levels were measured by quantitative real-time polymerase chain reaction and western blot. Cell proliferation, apoptosis and extracellular matrix (ECM) degradation were measured using cell counting kit-8, flow cytometry and western blot. The target interaction was explored by bioinformatics, luciferase reporter and RNA immunoprecipitation assays.

RESULTS

HOTAIR expression was enhanced, and miR-107 level was reduced in OA cartilage samples. HOTAIR overexpression inhibited cell proliferation, but induced cell apoptosis and ECM degradation in chondrocytes. HOTAIR knockdown caused an opposite effect. MiR-107 was sponged and inhibited via HOTAIR, and knockdown of miR-107 mitigated the effect of HOTAIR silence on chondrocyte injury. CXCL12 was targeted by miR-107. CXCL12 overexpression attenuated the roles of miR-107 overexpression or HOTAIR knockdown in the proliferation, apoptosis and ECM degradation. CXCL12 expression was decreased by HOTAIR silence, and restored by knockdown of miR-107.

CONCLUSION

HOTAIR knockdown promoted chondrocyte proliferation, but inhibited cell apoptosis and ECM degradation in OA chondrocytes by regulating the miR-107/CXCL12 axis.

Bioinformatics analysis of differentially expressed genes in subchondral bone in early experimental osteoarthritis using microarray data

Background

Osteoarthritis (OA) is the most common arthritic disease in humans, affecting the majority of individuals over 65 years of age. The aim of this study is to identify the gene expression profile specific to subchondral bone in OA by comparing the different expression profiles in experimental and sham-operation groups.

Methods

Gene expression profile GSE30322 was downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were obtained by limma package. And Database for Annotation, Visualization and Integrated Discovery (DAVID) databases were further used to identify the potential gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Furthermore, a protein–protein interaction (PPI) network was constructed and significant modules were extracted.

Results

Totally, 588 DEGs were identified including 199 upregulated DEGs and 389 downregulated DEGs screened in OA and sham-operation. GO showed that DEGs were significantly enhanced for ribosomal subunit export from nucleus and molting cycle. KEGG pathway analysis revealed that target genes were enriched in thiamine metabolism.

Conclusion

These key candidate DEGs that affect the progression of OA, and these genes might serve as potential therapeutic targets for OA.