Rheumatoid arthritis (RA), a chronic autoimmune disease of unknown etiology, is characterized by synovitis, pannus formation, and destruction of joints and cartilage. RA-related health complications and long-term comorbidities can markedly decrease life expectancy, and cardiovascular morbidity and mortality are relatively high. Cardiovascular diseases and sudden death are the main reasons of premature mortality in patients with RA¹. Approximately 30%–60% increase in risk of cardiovascular events and 50% increase in risk of death due to cardiovascular disease were reported in patients with RA because of accelerated atherosclerosis².

Evidence supports the hypothesis that the pathology of RA and that of atherosclerosis pathology share many common molecular pathways and exhibit analogous mechanisms³. Atherosclerotic plaque has many similarities to RA synovium, such as recruiting of blood-borne mononuclear cells, upregulation of cytokines, and complex interactions of immune cells with resident cell types³. The common pathophysiological mechanisms may provide insights into the common pathogenesis of RA and atherosclerosis. Therefore, the relationship between these diseases has attracted increasingly interest. Tamami et al. reported RA patients who have visceral adiposity have a specifically high risk for atherosclerosis⁴. In 2020, a study proposed the use of QRESEARCH risk estimator version 3 and the European League Against Rheumatism mSCORE for identifying patients with RA who are at a high risk of carotid plaques⁵. In addition, Dessein et al. determined the performance of the Framingham score and the Systematic Coronary Risk Evaluation tool in assessing patients with RA who are at high risk of atherosclerosis⁶. Furthermore, the development of atherosclerosis in patients with RA seems to be influenced by a genetic component. This topic has been the focus of numerous bioinformatics studies that mostly concentrated on genetic polymorphisms. To be specific, the association of the paraoxonase 1 gene polymorphism with carotid plaques in RA was demonstrated in a series of 168 North American patients⁷. Moreover, a Spanish group proved the potential protective effect of the IL33 rs3939286 allele T against the risk of subclinical atherosclerosis in patients with RA. However, a number of studies have also reported negative results on this aspect. One study failed to confirm the association of CRP, HNF1A, LEPR, GCKR, NLRP3, IL1F10, PPP1R3B, ASCL1, HNF4A, and SALL1 with cardiovascular disease in RA⁸. Another work reported that 15 polymorphisms, including TCF21, LPA, HHIPL1, RASD1-PEMT, MRPS6, CYP17A1-CNNM2-NT5C2, SMG6-SRR, PHACTR1, WDR12, and COL4A1-COL4A2, are not associated with atherosclerosis in RA⁹. Meanwhile, no relationships among ABO rs579459, PPAP2B rs17114036, ADAMTS7 rs3825807, PIK3CG rs17398575, EDNRA rs1878406, and subclinical atherosclerosis in RA were found¹⁰. Therefore, in consideration of previous studies, the molecular mechanism in patients with RA complicated with atherosclerosis is controversial and needs further study.

With the rapid development of microarray techniques, differentially expressed genes (DEGs) among different groups of people can be detected. Microarray techniques can illustrate gene expression and identify special proteins produced by genes¹¹. Therefore, disease-related molecules can be identified by using these tools. Thus, in this study, we aim to explore the potential overlapping key genes, pathway networks, and transcription factors (TFs) related to the pathogenesis of RA and atherosclerosis through a combination of microarray and bioinformatics analyses.