Text Mining of Rheumatoid Arthritis and Diabetes Mellitus to Understand the Mechanisms of Chinese Medicine in Different Diseases with Same Treatment.

Objective: To identify the commonalities between rheumatoid arthritis (RA) and diabetes mellitus (DM) to understand the mechanisms of Chinese medicine (CM) in different diseases with the same treatment.

Methods: A text mining approach was adopted to analyze the commonalities between RA and DM according to CM and biological elements. The major commonalities were subsequently verified in RA and DM rat models, in which herbal formula for the treatment of both RA and DM identified via text mining was used as the intervention.

Results: Similarities were identified between RA and DM regarding the CM approach used for diagnosis and treatment, as well as the networks of biological activities affected by each disease, including the involvement of adhesion molecules, oxidative stress, cytokines, T-lymphocytes, apoptosis, and inflammation. The Ramulus Cinnamomi-Radix Paeoniae Alba-Rhizoma Anemarrhenae is an herbal combination used to treat RA and DM. This formula demonstrated similar effects on oxidative stress and inflammation in rats with collagen-induced arthritis, which supports the text mining results regarding the commonalities between RA and DM.

Conclusion: Commonalities between the biological activities involved in RA and DM were identified through text mining, and both RA and DM might be responsive to the same intervention at a specific stage.