Association of PTPRC gene polymorphisms with TNF inhibitor efficacy in rheumatoid arthritis: a systematic review and meta-analysis
João Locke Ferreira de Araújo , Ingrid Marins de Almeida , Suanne Burgos Azevedo , Lilian de Sá Garcia Landeiro , Ryan dos Santos Costa
Journal of Translational Genetics and Genomics ›› 2025, Vol. 9 ›› Issue (4) : 304 -13.
Background: Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease characterized by joint destruction and functional impairment. Tumor Necrosis Factor inhibitors (TNFi) are widely used biologic therapies for RA; however, patient outcomes show significant individual variation. Genetic factors, including polymorphisms in the PTPRC gene, have been investigated as potential predictors of TNFi efficacy, but results remain inconsistent.
Methods: We conducted a systematic review and meta-analysis following PRISMA guidelines to evaluate the association between PTPRC polymorphisms and TNFi treatment response in RA patients. A comprehensive search was performed in PubMed and Scopus databases up to April 2025. Studies were screened and quality assessed using the Q-Genie tool. Meta-analyses employed Mantel-Haenszel methods with fixed and random effects models.
Results: Five studies met eligibility criteria, including data from 12 European cohorts totaling 1,543 RA patients. The main polymorphism assessed was rs10919563. Meta-analysis revealed the rs10919563 A allele was significantly associated with increased odds of non-response to TNFi (allelic model OR: 1.94; 95%CI: 1.31-2.88). The recessive models supported these findings, and no publication bias was detected.
Conclusions: Our results consolidate evidence supporting the PTPRC rs10919563 polymorphism as a potential predictive genetic biomarker for TNFi efficacy in RA, which could be integrated into personalized treatment strategies. Further studies are required to validate clinical utility across diverse populations.
Rheumatoid arthritis / PTPRC gene / tumor necrosis factor inhibitors (TNFi) / genetic polymorphisms / treatment response biomarkers
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