Association study of TRAF1-C5 polymorphism with susceptibility to rheumatoid arthritis in Tunisian population

Associations of TRAF1/C5 rs10818488 and rs3761847 polymorphisms with genetic susceptibility to rheumatoid arthritis: a case-control study and updated meta-analysis

The results on associations of tumor necrosis factor (TNF)-receptor associated factor 1/complement component 5 (TRAF1/C5) rs10818488 and rs3761847 polymorphisms with rheumatoid arthritis (RA) are controversial, thus this study was performed to examine whether the aforementioned polymorphisms were associated with RA in a Chinese population. Furthermore, an updated meta-analysis was conducted. The polymorphisms were genotyped in 328 Chinese RA patients and 449 healthy controls. Studies examining the association of TRAF1/C5 rs10818488 and/or rs3761847 polymorphism with RA were exhaustively searched. No significant difference in either genotype or allele distribution between RA patients and controls was found. The updated meta-analysis was conducted based on 19 articles including the present study. A significant association of RA with TRAF1/C5 rs10818488 polymorphism G allele in Europeans (OR = 0.843, 95% CI = 0.730-0.975, p = 0.021) and in Asians (OR = 1.070, 95% CI = 1.009-1.136, p = 0.024) was found. Additionally, a significant association of RA with TRAF1/C5 rs10818488 polymorphism G allele under the recessive model in Asians (OR = 1.129, 95% CI = 1.023-1.246, p = 0.016) and in Africans (OR = 0.657, 95% CI = 0.507-0.851, p = 0.001) was found. Only a borderline significant association of RA with TRAF1/C5 rs3761847 polymorphism A allele was found in Europeans. Non-significant associations of RA with TRAF1/C5 rs10818488 and rs3761847 polymorphisms were found in our study. The updated meta-analysis results demonstrate that TRAF1/C5 rs10818488 polymorphism is associated with RA in Europeans, Asians and Africans, and TRAF1/C5 rs3761847 polymorphism is associated with RA in Europeans with borderline significant evidence.

Associations between TRAF1-C5 gene polymorphisms and rheumatoid arthritis: a meta-analysis

OBJECTIVE

The aim of this study is to determine whether tumor necrosis factor receptor-associated factor 1-complement 5 (TRAF1-C5) polymorphisms are associated with susceptibility to rheumatoid arthritis (RA) in different populations.

METHODS

We conducted a meta-analysis of associations between the TRAF1-C5 polymorphisms and RA susceptibility.

RESULTS

A total of 24 comparative studies were included in this meta-analysis, including 22,682 patients with RA and 23,493 controls. The meta-analysis showed an association between the second allele of rs10818488 and RA in Europeans, but not in Asians (OR 1.229, 95% CI 1.094-1.381, p = 0.001; OR 1.060, 95% CI 0.930-1.335, p = 0.092). The meta-analysis also indicated an association between the second allele of rs3761847 and RA in Europeans, but not in Asians (OR 1.156, 95% CI 1.006-1.327, p = 0.041; OR 1.049, 95% CI 0.952-1.156, p = 0.333). The meta-analysis revealed an association between the second allele of the rs2900180 and rs10760130 polymorphisms and RA risk in Europeans (OR 1.224, 95% CI 1.065-1.405, p = 0.004; OR 1.072, 95% CI 1.002-1.147, p = 0.042).

CONCLUSIONS

This meta-analysis confirms that the TRAF1-C5 rs10818488, rs3761847, rs2900180 and rs10760130 polymorphisms are associated with RA susceptibility in Europeans.

NF-κB and Rheumatoid Arthritis: Will Understanding Genetic Risk Lead to a Therapeutic Reward?

NF-κB has long been known to play an important role in autoimmune diseases such as rheumatoid arthritis (RA). Indeed, as our understanding of how NF-κB is utilized has increased, we have been hard put to find a process not associated with this transcription factor family in some way. However, new data originating, in part, from genome-wide association studies have demonstrated that very specific alterations in components of the NF-κB pathway are sufficient to confer increased risk of developing disease. Here we review the data which have identified specific components of the NF-κB pathway, and consider what is known of their mechanisms of action and how these mechanisms might play into the disease process. In addition, the use of genetic information to predict RA is considered.