Classifying Integrated Signature Molecules in Macrophages of Rheumatoid Arthritis, Osteoarthritis, and Periodontal Disease: An Omics-Based Study.
Prachi SaoYamini ChandLamya Ahmed Al-KeridisMohd SaeedNawaf AlshammariSachidanand SinghPublished in: Current issues in molecular biology (2022)
Rheumatoid arthritis (RA), osteoarthritis (OA), and periodontal disease (PD) are chronic inflammatory diseases that are globally prevalent, and pose a public health concern. The search for a potential mechanism linking PD to RA and OA continues, as it could play a significant role in disease prevention and treatment. Recent studies have linked RA, OA, and PD to Porphyromonas gingivalis (PG), a periodontal bacterium, through a similar dysregulation in an inflammatory mechanism. This study aimed to identify potential gene signatures that could assist in early diagnosis as well as gain insight into the molecular mechanisms of these diseases. The expression data sets with the series IDs GSE97779, GSE123492, and GSE24897 for macrophages of RA, OA synovium, and PG stimulated macrophages (PG-SM), respectively, were retrieved and screened for differentially expressed genes (DEGs). The 72 common DEGs among RA, OA, and PG-SM were further subjected to gene-gene correlation analysis. A GeneMANIA interaction network of the 47 highly correlated DEGs comprises 53 nodes and 271 edges. Network centrality analysis identified 15 hub genes, 6 of which are DEGs ( API5 , ATE1 , CCNG1 , EHD1 , RIN2 , and STK39 ). Additionally, two significantly up-regulated non-hub genes ( IER3 and RGS16 ) showed interactions with hub genes. Functional enrichment analysis of the genes showed that "apoptotic regulation" and "inflammasomes" were among the major pathways. These eight genes can serve as important signatures/targets, and provide new insights into the molecular mechanism of PG-induced RA, OA, and PD.
Keyphrases
- rheumatoid arthritis
- genome wide
- genome wide identification
- bioinformatics analysis
- disease activity
- knee osteoarthritis
- public health
- dna methylation
- ankylosing spondylitis
- genome wide analysis
- interstitial lung disease
- transcription factor
- copy number
- network analysis
- cell death
- artificial intelligence
- gene expression
- squamous cell carcinoma
- big data
- rectal cancer
- early stage
- binding protein
- risk assessment
- neoadjuvant chemotherapy
- idiopathic pulmonary fibrosis