Rheumatoid arthritis (RA) is a common chronic immune disease. Berberine, as its main active ingredient, was also contained in a variety of medicinal plants such as Berberaceae, Buttercup, and Rutaceae, which are widely used in digestive system diseases in traditional Chinese medicine with anti-inflammatory and antibacterial effects. The aims of this article were to explore the therapeutic effect and mechanism of berberine on rheumatoid arthritis. Cell Counting Kit-8 was used to evaluate the effect of berberine on the proliferation of RA fibroblast-like synoviocyte (RA-FLS) cells. The effect of berberine on matrix metalloproteinase (MMP)-1, MMP-3, receptor activator of nuclear factor kappa-Β ligand (RANKL), tumour necrosis factor alpha (TNF-α), and other factors was determined by enzyme-linked immunoassay (ELISA) kit. Transcriptome technology was used to screen related pathways and the potential targets after berberine treatment, which were verified by reverse transcription-polymerase chain reaction (RT-qPCR) and Western blot (WB) technology.Aims
Methods
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. Genome-wide DNA methylation profiling of articular cartilage from five patients with OA of the knee and five healthy controls was conducted using the Illumina Infinium HumanMethylation450 BeadChip (Illumina, San Diego, California). Other independent genome-wide mRNA expression profiles of articular cartilage from three patients with OA and three healthy controls were obtained from the Gene Expression Omnibus (GEO) database. Integrative pathway enrichment analysis of DNA methylation and mRNA expression profiles was performed using integrated analysis of cross-platform microarray and pathway software. Gene ontology (GO) analysis was conducted using the Database for Annotation, Visualization and Integrated Discovery (DAVID).Aim
Patients and Methods
Several genome-wide association studies (GWAS) of bone mineral density (BMD) have successfully identified multiple susceptibility genes, yet isolated susceptibility genes are often difficult to interpret biologically. The aim of this study was to unravel the genetic background of BMD at pathway level, by integrating BMD GWAS data with genome-wide expression quantitative trait loci (eQTLs) and methylation quantitative trait loci (meQTLs) data We employed the GWAS datasets of BMD from the Genetic Factors for Osteoporosis Consortium (GEFOS), analysing patients’ BMD. The areas studied included 32 735 femoral necks, 28 498 lumbar spines, and 8143 forearms. Genome-wide eQTLs (containing 923 021 eQTLs) and meQTLs (containing 683 152 unique methylation sites with local meQTLs) data sets were collected from recently published studies. Gene scores were first calculated by summary data-based Mendelian randomisation (SMR) software and meQTL-aligned GWAS results. Gene set enrichment analysis (GSEA) was then applied to identify BMD-associated gene sets with a predefined significance level of 0.05.Objectives
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