Chinese Journal of Tissue Engineering Research ›› 2026, Vol. 30 ›› Issue (10): 2629-2640.doi: 10.12307/2026.617

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Relationship between inflammatory factors and rheumatoid arthritis: a large-sample analysis based on the FinnGen R10 database and genome-wide association studies

Jiang Kai1, Rong Yifa1, Jia Haifeng1, Li Hanzheng1, Lu Bowen1, Liang Xuezhen1, Li Gang2   

  1. 1The First Clinical Medical College of Shandong University of Traditional Chinese Medicine, Jinan 250355, Shandong Province, China; 2Department of Micro-Orthopedics, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan 250014, Shandong Province, China
  • Received:2025-03-01 Accepted:2025-06-13 Online:2026-04-08 Published:2025-09-01
  • Contact: Li Gang, MD, Doctoral supervisor, Department of Micro-Orthopedics, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan 250014, Shandong Province, China
  • About author:Jiang Kai, MS candidate, The First Clinical Medical College of Shandong University of Traditional Chinese Medicine, Jinan 250355, Shandong Province, China

Abstract: BACKGROUND: Rheumatoid arthritis is a chronic, systemic autoimmune disease, and its pathogenesis involves multiple inflammatory factors and metabolites. However, the causal relationships are not yet clear. In China, although the diagnosis and treatment of rheumatoid arthritis have improved in recent years, some patients still suffer from disabilities due to a lack of early diagnosis and standardized treatment.
OBJECTIVE: To assess the potential causal relationships between inflammatory factors and rheumatoid arthritis using Mendelian randomization methods, providing new support and perspectives for clinical research in order to fill the gap in the understanding of the relationship between the pathogenesis of rheumatoid arthritis and inflammatory factors, thereby providing new potential targets and guidance for the treatment and prevention of rheumatoid arthritis.
METHODS: The disease data were obtained from a genome-wide association study in the FinnGen R10 database, including genetic data from 13 621 patients with rheumatoid arthritis and 262 844 healthy controls. The 91 inflammatory factors were derived from a meta-analysis of 11 cohorts, involving 14 824 participants of European descent. For the forward Mendelian randomization analysis, a P-value of < 5 × 10−6 was used to identify instrumental variables related to inflammatory factors and rheumatoid arthritis. For the reverse Mendelian randomization analysis, a P-value of < 5 × 10−8 was used to identify instrumental variables related to rheumatoid arthritis and inflammatory factors. The linkage disequilibrium parameters for both forward and reverse analyses were set at 0.001, and the genetic distance was set at 10 000 kb. Only instrumental variables with an F-statistic greater than 10 were considered, and confounding factors were removed. The causal relationships between the 91 inflammatory factors and rheumatoid arthritis were studied using methods such as inverse variance weighting, MR-Egger, weighted median, simple mode, and weighted mode, with inverse variance weighting being the primary method. A P-value of < 0.05 was considered significant. Heterogeneity and horizontal pleiotropy were excluded if their P-values were > 0.05. Reverse Mendelian randomization analysis was also conducted to exclude reverse causality.
RESULTS AND CONCLUSION: (1) C-C motif chemokine 23 [odds ratio (OR): 0.921, P=0.006], fibroblast growth factor 19 (OR=0.906, P=0.046), interleukin-12 subunit beta (OR=0.899, P=0.009), interleukin-2 (OR=0.889, P=0.024), and leukemia inhibitory factor receptor (OR=0.876, P=0.047) have protective effects on rheumatoid arthritis. (2) In contrast, C-C motif chemokine 19 (OR=1.118, P=0.032), C-C motif chemokine 4 (OR=1.107, P=0.004), interleukin-7 (OR=1.211, P=0.018), and tumor necrosis factor (OR=1.119, P=0.040) have detrimental effects on rheumatoid arthritis. These findings provide new insights and evidence for the role of inflammatory factors in rheumatoid arthritis, filling the gap in this field and potentially leading to new strategies for the prevention and treatment of rheumatoid arthritis.

Key words: Mendelian randomization, inflammatory factors, rheumatoid arthritis, causal relationship, genome-wide association study, single nucleotide polymorphism, protective factors, risk factors

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