Chinese Journal of Tissue Engineering Research ›› 2026, Vol. 30 ›› Issue (5): 1311-1319.doi: 10.12307/2026.045

Previous Articles     Next Articles

Gene-predicted associations between 731 immune cell phenotypes and rheumatoid arthritis

Liu Fengzhi1, Dong Yuna2, Tian Wenyi1, Wang Chunlei3, Liang Xiaodong1, Bao Lin4   

  1. 1College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250355, Shandong Province, China; 2Laizhou People’s Hospital, Laizhou 261400, Shandong Province, China; 3Wang Orthopaedic Hospital in Taian, Taian 271000, Shandong Province, China; 4The 960 Hospital of the Joint Logistics Support Force of the Chinese PLA, Jinan 250031, Shandong Province, China
  • Received:2024-12-03 Accepted:2025-02-15 Online:2026-02-18 Published:2025-06-28
  • Contact: 鲍霖，主管技师，中国人民解放军联勤保障部队第九六〇医院，山东省济南市 250031 通讯作者：梁晓东，博士，副教授，硕士生导师，山东中医药大学中医学院，山东省济南市 250355 https://orcid.org/0009-0006-6374-9512 (刘凤芝)
  • About author:刘凤芝，女，山东省菏泽市人，汉族，山东中医药大学在读硕士，主要从事中药学方面的研究。

PDF

32

Abstract: BACKGROUND: Rheumatoid arthritis is widely prevalent worldwide, with its high incidence and universality that considerably affects patients’ quality of life. Previous studies have focused on a few immune cells or cytokines, whereas this study comprehensively provides a more complete view of the immune mechanisms in rheumatoid arthritis.
OBJECTIVE: To explore the causal relationship between 731 immune cell phenotypes and rheumatoid arthritis using the Mendelian randomization method, thereby providing evidence of causality.
METHODS: The 731 immune cell phenotypes used in this study were sourced from the GWAScatalog database, jointly developed by the National Human Genome Research Institute (NHGRI) and the European Bioinformatics Institute (EBI). The rheumatoid arthritis data were from the Finngen database, developed by the Finnish Institute for Molecular Medicine (FIMM). The inverse variance weighting method was employed as the primary analytical approach. Additionally, multiple analytical methods, including MR-Egger, weighted mode, simple mode, and weighted median, were concurrently utilized to complement the final results. Sensitivity analyses (Cochran’s Q test, MR-Egger regression, and MR-presso analysis) were also conducted to verify the stability and feasibility of the data.
RESULTS AND CONCLUSION: (1) After excluding results through heterogeneity testing, the inverse variance weighting analysis indicated that 10 absolute cell counts, 15 median fluorescence intensities of surface antigen levels, 1 morphological characteristic, and 9 relative cell counts had a causal relationship with the occurrence of rheumatoid arthritis. (2) According to cell classification, this study found that seven types of B cells, seven types of classical dendritic cells, six types of mature T cells, four types of monocytes, three types of myeloid cells, three types of TBNK cells (lymphocyte subset T cells, B cells and natural killer cells), and five types of Tregs had a causal association with the occurrence of rheumatoid arthritis. (3) Through comprehensive bidirectional two-sample MR analysis, we demonstrated the complex causal relationships between multiple immune phenotypes and rheumatoid arthritis, highlighting the intricate interaction patterns between the immune system and rheumatoid arthritis. These results provide new biomarkers for the early screening and diagnosis of rheumatoid arthritis in China, and help to improve the diagnostic accuracy and sensitivity.

Key words: immunocyte, immune cell phenotype, Mendelian randomization, rheumatoid arthritis, causal relationship

CLC Number: