Identification of novel biomarkers and candidate small molecule drugs in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis of high-throughput data

Abstract

Background: Rheumatoid arthritis (RA) and osteoarthritis (OA) are two major types of joint diseases. The present study aimed to identify hub genes involved in the pathogenesis and further explore the potential treatment targets of RA and OA. Methods: The gene expression profile of GSE12021 was downloaded from Gene Expression Omnibus (GEO). Total 31 samples (12 RA, 10 OA and 9 NC samples) were used. The differentially expressed genes (DEGs) in RA versus NC, OA versus NC and RA versus OA groups were screened using limma package. We also verified the DEGs in GSE55235 and GSE100786. Functional annotation and protein–protein interaction (PPI) network construction of OA- and RA-specific DEGs were performed. Finally, the candidate small molecules as potential drugs to treat RA and OA were predicted in CMap database. Results: 165 up-regulated and 163 down-regulated DEGs between RA and NC samples, 73 up-regulated and 293 down-regulated DEGs between OA and NC samples, 92 up-regulated and 98 down-regulated DEGs between RA and OA samples were identified. Immune response and TNF signaling pathway were significantly enriched pathways for RA- and OA-specific DEGs, respectively. The hub genes were mainly associated with ‘Primary immunodeficiency’ (RA vs. NC group), ‘Ribosome’ (OA vs. NC group), and ‘Chemokine signaling pathway’ (RA vs. OA group). Arecoline and Cefamandole were the most promising small molecule to reverse the RA and OA gene expression. Conclusion: Our findings suggest new insights into the underlying pathogenesis of RA and OA, which may improve the diagnosis and treatment of these intractable chronic diseases.

Classifying Integrated Signature Molecules in Macrophages of Rheumatoid Arthritis, Osteoarthritis, and Periodontal Disease: An Omics-Based Study

“…However, most of the research is concentrated on one disease at a time [ 54 , 55 ]. Recent advances in the study of RA and PD, OA and PD, RA and OA, as well as RA, OA, and PD separately, have been made by utilizing the data generated from high-throughput technologies (DNA microarrays and RNAseq), and Omics-based techniques [ 5 , 6 , 8 , 16 , 20 , 37 , 39 , 56 , 57 , 58 ]. However, their applicability is limited when it comes to identifying integrated signature molecules for RA, OA, and PD together.…”

“…A t -test in the Limma package was performed to determine the p -value of each gene symbol. The following criteria were used to identify significant DEGs: p -value ≤ 0.05 and log2-fold change (logFC) ≥ ±1 [ 8 ]. Gene annotations were retrieved from the GEO database and prob ids were transformed into gene symbols; genes with the lowest p -values were chosen in the case of duplicate genes.…”

“…A study [ 7 ] found a correlation between the severity of OA and rising levels of systemic inflammatory markers, such as lipopolysaccharides (LPS) produced by bacteria. Despite having different pathogeneses, both RA and OA share phenotypic traits, cells, and molecular properties [ 8 ]. Furthermore, research shows that RA and OA significantly alter the oral microbiome [ 3 ].…”

Unraveling the Genetic Basis of Fertility Restoration for Cytoplasmic Male Sterile Line WNJ01A Originated From Brassica juncea in Brassica napus

“…The PPI network (confidence score > 0.7), with KEGG annotations, was visualized using Cytoscape ( Shannon et al, 2003 ). The hub genes were identified using the Cytoscape plugin CytoHubba ( Song et al, 2020 ; Zuo et al, 2020 ).…”

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

“…For the six marker genes previously identified, we found that SCRG1, CDKN1A, SLC2A3 genes were significantly expressed in all microarray and RNA-seq datasets, and only SCRG1 gene showed an increased expression trend in all datasets. SCRG1 has also been observed to be specifically expressed in human articular cartilage (29)(30)(31), so we considered that SCRG1 might be a key regulatory factor in the development of synovial inflammation. In order to understand the role of SCRG1 in OA, we performed gene expression correlation analysis to predict SCRG1 gene function by protein-protein interaction.…”