Abstract. Focal articular cartilage defects do not heal and, left untreated, progress to more widespread degenerative changes. A promising new approach for the repair of articular cartilage defects is the application of cell-based regenerative therapies using mesenchymal stromal cells (MSCs). MSCs are however present in a number of tissues and studies suggest that they vary in their proliferation, cell surface characterisation and differentiation. As the phenotypic properties of MSCs vary depending on tissue source, a systematic comparison of the transcriptomic signature would allow a better understanding of these differences between tissues, and allow the identification of markers specific to a MSC source that is best suited for clinical application. Tissue was used from patients undergoing total knee replacement surgery for osteoarthritis following ethical approval and informed consent. MSCs were isolated from bone, cartilage, synovium and infrapatellar fat pad. MSC number and expansion were quantified. Following expansion in culture, MSCs were characterised using flow cytometry with several cell surface markers; the cells from all sources were positive for CD44, CD90 and CD105. Their differentiation potential was assessed through tri-lineage differentiation assays. In addition, bulk mRNA-sequencing was used to determine the transcriptomic signatures. Differentially expressed (DE) genes were predicted. An enrichment analysis focused on the DE genes, against GO and pathway databases (KEGG and Reactome) was performed;
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.
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. 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.Objectives
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