RESUMO
Rheumatoid arthritis (RA) is an autoimmune inflammatory disease that causes multi-articular synovitis. The illness is characterized by worsening inflammatory synovitis, which causes joint swelling and pain. Synovitis erodes articular cartilage and marginal bone, resulting in joint deterioration. This bone injury is expected to be permanent. Cytokines play a prominent role in the etiology of RA and could be useful as early diagnostic biomarkers. This research was carried out at Riyadh's King Khalid University Hospital (KKUH). Patients were enrolled from the Rheumatology unit. Seventy-eight RA patients were recruited (67 (85.9%) females and 11 (14.1%) males). Patients were selected for participation by convenience sampling. Demographic data were collected, and disease activity measurements at 28 joints were recorded using the disease activity score (DAS-28). Age- and sex-matched controls from the general population were included in the study. A panel of 27 cytokines, chemokines, and growth factors was determined in patient and control sera. Binary logistic regression (BLR) and discriminant analysis (DA) were used to analyze the data. We show that multiple cytokine biomarker profiles successfully distinguished RA patients from healthy controls. IL-17, IL-4, and RANTES were among the most predictive variables and were the only biomarkers incorporated into both BLR and DA predictive models for pooled participants (men and women). In the women-only models, the significant cytokines incorporated in the model were IL-4, IL-17, MIP-1b, and RANTES for the BLR model and IL-4, IL-1Ra, GM-CSF, IL-17, and eotaxin for the DA model. The BLR and DA men-only models contained one cytokine each, eotaxin for BLR and platelet-derived growth factor-bb (PDGF-BB) for DA. We show that BLR has a higher fidelity in identifying RA patients than DA. We also found that the use of gender-specific models marginally improves detection fidelity, indicating a possible benefit in clinical diagnosis. More research is needed to determine whether this conclusion will hold true in various and larger patient populations.
RESUMO
Rheumatoid arthritis (RA) is a complex, multifactorial disorder with an autoimmune etiology. RA is highly heritable and is associated with both human leucocyte antigen (HLA) and non-HLA genes. We investigated the associations of 33 single nucleotide polymorphisms (SNPs) with RA in the Saudi population. METHODS: This study included 105 patients with RA and an equal number of age- and sex-matched controls. The patients with RA attended outpatient clinics at King Khalid University Hospital in Riyadh, Saudi Arabia. Blood samples were collected, and DNA was extracted using Qiagen kits. Primers were designed for the 33 selected SNPs using the MassEXTEND primers program, and samples were genotyped on the Sequenom MassARRAY iPLEX platform. The allele frequencies and genotypes were determined for each SNP, and the results obtained for the patients were compared to those for the controls. RESULTS: The allele and genotype frequencies of six SNPs were significantly associated with RA: rs1188934, rs10919563, rs3087243, rs1980422, rs10499194, and rs629326. The minor alleles of rs1188934, rs10919563, rs10499194, and rs629326 were protective, with odds ratios of 0.542, 0.597, 0.589, and 0.625, and p-values of 0.002, 0.023, 0.013 and 0.036, respectively. In addition, the heterozygote frequencies of two SNPs (rs6859219 and rs11586238) were significantly higher in the controls than in the patients. CONCLUSIONS: There is considerable heterogeneity in the genetics of RA in different populations, and the SNPs that are associated with RA in some populations are not in others. We studied 33 SNPs and only eight were associated with RA. The remaining SNPs showed no allelic or genotypic associations with RA.
