Polymorphisms in STAT4 and PTPRC genes in rheumatoid arthritis: a Brazilian study and meta-analysis of susceptibility...

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by persistent synovial inflammation and progressive joint destruction. Genetic factors play a key role in its pathogenesis and may also influence therapeutic response. This study aimed to investigate the association of the STAT4 rs7574865-T and PTPRC rs10919563-A polymorphisms with RA susceptibility and response to TNF inhibitor (TNFi) treatment in a Brazilian population. A case-control study was conducted including 295 RA patients treated with TNFi and 303 healthy controls. Genotyping of rs7574865 (STAT4) and rs10919563 (PTPRC) was performed. Associations with RA susceptibility, TNFi treatment response, and therapy discontinuation due to adverse events were evaluated under different genetic models. A meta-analysis integrating our results with previously published studies was also conducted. The rs7574865-T allele was associated with increased RA risk (OR: 1.43; 95% CI: 1.03-1.99; p = 0.036; p perm = 0.042), reduced response to TNFi (OR: 0.28; 95% CI: 0.07-0.99; p = 0.047; p perm = 0.058), and higher likelihood of treatment discontinuation due to adverse events (OR: 1.89; 95% CI: 1.01-3.58; p = 0.047;p perm = 0.034). After permutation-based correction (1,000 iterations), all associations remained consistent except for the recessive model in TNFi response, which became non-significant (p_perm = 0.058). The meta-analysis confirmed a 40% increased RA susceptibility in T allele carriers. No significant association was observed for rs10919563-A regarding RA risk or TNFi response. A genetic interaction between STAT4 (G/T) and PTPRC (A/A, p = 0.008; G/G, p = 0.017) genotypes was observed, suggesting an increased RA risk for these genotype combinations, without significant correlation with TNFi treatment outcomes. Our findings reinforce the role of STAT4 rs7574865-T in RA susceptibility and TNFi treatment outcomes and highlight the potential for personalized therapeutic strategies based on genetic profiles.