Aim

Osteoarthritis (OA) is caused by complex interactions between genetic and environmental factors. Epigenetic mechanisms control the expression of genes and are likely to regulate the OA transcriptome. We performed integrative genomic analyses to define methylation-gene expression relationships in osteoarthritic cartilage.

Osteoporosis is a systemic skeletal disorder characterized by reduced bone mass and deterioration of bone microarchitecture, which results in increased bone fragility and fracture risk. Casein kinase 2-interacting protein-1 (CKIP-1) is a protein that plays an important role in regulation of bone formation. The effect of CKIP-1 on bone formation is mainly mediated through negative regulation of the bone morphogenetic protein pathway. In addition, CKIP-1 has an important role in the progression of osteoporosis. This review provides a summary of the recent studies on the role of CKIP-1 in osteoporosis development and treatment.

Cite this article: X. Peng, X. Wu, J. Zhang, G. Zhang, G. Li, X. Pan. The role of CKIP-1 in osteoporosis development and treatment. Bone Joint Res 2018;7:173–178. DOI: 10.1302/2046-3758.72.BJR-2017-0172.R1.

Objectives. In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. Methods. We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. Results. A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57). Conclusion. Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and bone formation. Cite this article: J. J. Li, B. Q. Wang, Q. Fei, Y. Yang, D. Li. Identification of candidate genes in osteoporosis by integrated microarray analysis. Bone Joint Res 2016;5:594–601. DOI: 10.1302/2046-3758.512.BJR-2016-0073.R1

Objectives. The molecular mechanism of rheumatoid arthritis (RA) remains elusive. We conducted a protein-protein interaction network-based integrative analysis of genome-wide association studies (GWAS) and gene expression profiles of RA. Methods. We first performed a dense search of RA-associated gene modules by integrating a large GWAS meta-analysis dataset (containing 5539 RA patients and 20 169 healthy controls), protein interaction network and gene expression profiles of RA synovium and peripheral blood mononuclear cells (PBMCs). Gene ontology (GO) enrichment analysis was conducted by DAVID. The protein association networks of gene modules were generated by STRING. Results. For RA synovium, the top-ranked gene module is HLA-A, containing TAP2, HLA-A, HLA-C, TAPBP and LILRB1 genes. For RA PBMCs, the top-ranked gene module is GRB7, consisting of HLA-DRB5, HLA-DRA, GRB7, CD63 and KIT genes. Functional enrichment analysis identified three significant GO terms for RA synovium, including antigen processing and presentation of peptide antigen via major histocompatibility complex class I (false discovery rate (FDR) = 4.86 × 10 – 4), antigen processing and presentation of peptide antigen (FDR = 2.33 × 10 – 3) and eukaryotic translation initiation factor 4F complex (FDR = 2.52 × 10 – 2). Conclusion. This study reported several RA-associated gene modules and their functional association networks. Cite this article: X. Xiao, J. Hao, Y. Wen, W. Wang, X. Guo, F. Zhang. Genome-wide association studies and gene expression profiles of rheumatoid arthritis: an analysis. Bone Joint Res 2016;5:314–319. DOI: 10.1302/2046-3758.57.2000502

Objectives

Effects of insulin-like growth factor 1 (IGF1), fibroblast growth factor 2 (FGF2) and bone morphogenetic protein 2 (BMP2) on the expression of genes involved in the proliferation and differentiation of osteoblasts in culture were analysed. The best sequence of growth factor addition that induces expansion of cells before their differentiation was sought.