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已发表论文
类风湿关节炎与纤维肌痛综合征：从文献计量学和生物信息学角度探讨共病研究
Authors Chen G , Yan Z, Wang Y, Tao Q
Received 14 June 2025
Accepted for publication 9 October 2025
Published 21 October 2025 Volume 2025:18 Pages 6811—6827
DOI https://doi.org/10.2147/JMDH.S547111
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 4
Editor who approved publication: Dr David C. Mohr
Guangyao Chen,1,2 Zeran Yan,1,2 Yifei Wang,3 Qingwen Tao1,2
1Department of TCM Rheumatology, China-Japan Friendship Hospital, Beijing, 100029, People’s Republic of China; 2Beijing Key Laboratory for Immune-Mediated Inflammatory Diseases, China-Japan Friendship Hospital, Beijing, 100029, People’s Republic of China; 3The First Clinical Medical School, Beijing University of Chinese Medicine, Beijing, 100700, People’s Republic of China
Correspondence: Qingwen Tao, Department of TCM Rheumatology, China-Japan Friendship Hospital, Beijing, People’s Republic of China, Tel +8613910528490, Email taoqg1@outlook.com
Objective: Rheumatoid arthritis (RA) and fibromyalgia syndrome (FMS) are two common chronic pain disorders which complicate diagnosis and treatment. However, the pathological mechanisms, epidemiological characteristics, and research trends in comorbidities have not yet been systematically reviewed.
Methods: Literature related to RA and FMS published between January 2015 and December 2024 was retrieved from the Web of Science (WOS) database. VOSviewer, CiteSpace, Scimago Graphica, and Excel were used to conduct co-occurrence and clustering analyses of countries, institutions, authors, journals, and keywords to evaluate research dynamics and knowledge structures. GeneCards was used to identify shared gene targets between RA and FMS, whereas Protein-Protein Interaction (PPI) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to explore potential comorbidity mechanisms.
Results: In total, 760 articles were included in the study, with annual publication counts showing periodic fluctuations. The United States consistently ranked first in publication output and formed a highly influential collaborative network. Among the institutions, the University of Michigan and Karolinska Institute tied for first place, but the University of Michigan demonstrated a greater influence. Clinical and Experimental Rheumatology published the highest number of articles, whereas Journal of Rheumatology received the most citations. Author analysis revealed that Daniel J. Clauw published the most articles, received the most citations, and had the highest total link strength. Keyword analysis indicated that the research primarily focused on clinical studies with limited exploration of comorbidity mechanisms. GeneCards identified 216 RA and FMS overlapping genes. PPI and KEGG analyses suggested that inflammatory reactions and neuroactive ligand-receptor interactions play key roles in the mechanisms of comorbidity.
Conclusion: Current research on RA-FMS comorbidity lacks depth and mechanistic insight. Future studies should explore neuroimmune regulation, central sensitization, and inflammation-pain pathways through interdisciplinary collaboration across rheumatology, neuroscience, pain medicine, and bioinformatics to establish a unified comorbidity framework.
Keywords: rheumatoid arthritis, fibromyalgia syndrome, bibliometric analysis, research trends
1Department of TCM Rheumatology, China-Japan Friendship Hospital, Beijing, 100029, People’s Republic of China; 2Beijing Key Laboratory for Immune-Mediated Inflammatory Diseases, China-Japan Friendship Hospital, Beijing, 100029, People’s Republic of China; 3The First Clinical Medical School, Beijing University of Chinese Medicine, Beijing, 100700, People’s Republic of China
Correspondence: Qingwen Tao, Department of TCM Rheumatology, China-Japan Friendship Hospital, Beijing, People’s Republic of China, Tel +8613910528490, Email taoqg1@outlook.com
Objective: Rheumatoid arthritis (RA) and fibromyalgia syndrome (FMS) are two common chronic pain disorders which complicate diagnosis and treatment. However, the pathological mechanisms, epidemiological characteristics, and research trends in comorbidities have not yet been systematically reviewed.
Methods: Literature related to RA and FMS published between January 2015 and December 2024 was retrieved from the Web of Science (WOS) database. VOSviewer, CiteSpace, Scimago Graphica, and Excel were used to conduct co-occurrence and clustering analyses of countries, institutions, authors, journals, and keywords to evaluate research dynamics and knowledge structures. GeneCards was used to identify shared gene targets between RA and FMS, whereas Protein-Protein Interaction (PPI) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to explore potential comorbidity mechanisms.
Results: In total, 760 articles were included in the study, with annual publication counts showing periodic fluctuations. The United States consistently ranked first in publication output and formed a highly influential collaborative network. Among the institutions, the University of Michigan and Karolinska Institute tied for first place, but the University of Michigan demonstrated a greater influence. Clinical and Experimental Rheumatology published the highest number of articles, whereas Journal of Rheumatology received the most citations. Author analysis revealed that Daniel J. Clauw published the most articles, received the most citations, and had the highest total link strength. Keyword analysis indicated that the research primarily focused on clinical studies with limited exploration of comorbidity mechanisms. GeneCards identified 216 RA and FMS overlapping genes. PPI and KEGG analyses suggested that inflammatory reactions and neuroactive ligand-receptor interactions play key roles in the mechanisms of comorbidity.
Conclusion: Current research on RA-FMS comorbidity lacks depth and mechanistic insight. Future studies should explore neuroimmune regulation, central sensitization, and inflammation-pain pathways through interdisciplinary collaboration across rheumatology, neuroscience, pain medicine, and bioinformatics to establish a unified comorbidity framework.
Keywords: rheumatoid arthritis, fibromyalgia syndrome, bibliometric analysis, research trends