Lack of tumor necrosis factor alpha gene polymorphism ‐857c/t (rs1799724) association in Pakistani rheumatoid arthritis patients. (28th April 2016) - Sadaf, Tayyaba; John, Peter; Bhatti, Attya; Jahangir, Sidrah; Kiani, Aysha K.; Gill, Farah A.; Malik, Javed M.
Abstract: Background: Rheumatoid arthritis (RA) is a common systemic autoimmune disease, influenced greatly by the pro‐inflammatory cytokine tumor necrosis factor‐ alpha (TNF‐α). Single nucleotide polymorphisms (SNPs) in regulatory regions of the TNF‐α gene play a significant role in disease development and pathogenesis. The aim of this study was to investigate the association of TNF‐α ‐857C/T (rs1799724) SNP with RA activity or severity in our Pakistani study group. Methods: The study included 134 (116 women, 18 men) patients with RA and 134 ethnically matched healthy controls (108 women, 26 men). Each patient's disease activity was measured by Disease Activity Score of 28 joints. The genotypes were determined in all included individuals following allele‐specific polymerase chain reaction along with the prerequisite internal amplification controls. Statistical analysis including chi‐square/Fischer exact test and one‐way analysis of variance; nonparametric Kruskal–Wallis test was employed using Graphpad Prism 6 software for association study. Results: The prevalence of TNF‐α ‐857C/T (rs1799724) polymorphism was not differentially distributed between RA patients and controls in either allele frequency, with odds ratio (95% CI) of 0.9661 (0.6714–1.390) and P ‐value of 0.8527, or genotype frequency with χ 2 of 0.5015 and P ‐value of 0.7782. Moreover, no correlation was found when genotype frequency distribution was analyzed with disease severity ( P = 0.6321 and Kruskal–Wallis statistics of 1.098). Conclusion: The study demonstrated ‐857C/T (rs1799724) polymorphism may not have influenced RA susceptibility in our study group. However, investigations of genetic variability influence on disease outcome in large prospective cohorts are required, so the complicated interconnection of genetic and environmental elements can be emulated for better understanding.