title: Understanding the molecular mechanism of interventions in treating rheumatoid arthritis patients with corresponding traditional chinese medicine patterns based on bioinformatics approach.
abstract: Better effectiveness would be achieved when interventions are used in treating patients with a specific traditional Chinese medicine (TCM) pattern. In this paper, the effectiveness in treating rheumatoid arthritis (RA) patients in a randomized clinical trial as reanalyzed after the patients were classified into different TCM patterns and the underlying mechanism of how the TCM pattern influences the clinical effectiveness of interventions (TCM and biomedicine therapy) was explored. The pharmacological networks of interventions were builtup with protein and protein interaction analyses based on all the related targeted proteins obtained from PubChem. The underlying mechanism was explored by merging the pharmacological networks with the molecular networks of TCM cold and hot patterns in RA. The results show that the TCM therapy is better in treating the RA patients with TCM hot pattern, and the biomedical therapy is better in the RA patients with cold pattern. The pharmacological network of TCM intervention is merged well with the molecular network of TCM hot pattern, and the pharmacological network of biomedical therapy is merged well with the network of cold pattern. The finding indicates that molecular network analysis could give insight into the full understanding of the underlying mechanism of how TCM pattern impacts the efficacy.
authors.affiliation: Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Science, Beijing 100700, China.
authors.forename: Miao
authors.initials: M
authors.lastname: Jiang
authors.forename: Cheng
authors.initials: C
authors.lastname: Lu
authors.forename: Gao
authors.initials: G
authors.lastname: Chen
authors.forename: Cheng
authors.initials: C
authors.lastname: Xiao
authors.forename: Qinglin
authors.initials: Q
authors.lastname: Zha
authors.forename: Xuyan
authors.initials: X
authors.lastname: Niu
authors.forename: Shilin
authors.initials: S
authors.lastname: Chen
authors.forename: Aiping
authors.initials: A
authors.lastname: Lu