(97) used bioinformatics to systematically analyze the GSE97779 and GSE10500 expression profiles of SMs in RA patients, identifying 10 candidate genes (FN1, VEGFA, HGF, SERPINA1, MMP9, PPBP, CD44, FPR2, IGF1, and ITGAM) that may be used in the future diagnosis, prognosis, and treatment of RA. Here, FPR2 is linked to rheumatoid arthritis.