Identifying subgroups of patients with type 2 diabetes based on real-world traditional chinese medicine electronic medical records

作者：Shuai Zhao, Hengfei Li, Xuan Jing, Xuebin Zhang, Ronghua Li, Yinghao Li, Chenguang Liu, Jie Chen, Guoxia Li, Wenfei Zheng, Qian Li, Xue Wang, Letian Wang, Yuanyuan Sun, Yunsheng Xu, Shihua Wang · 发表于：Frontiers in Pharmacology · 年份：2023 · DOI：10.3389/fphar.2023.1210667 · 被引用次数：4 · 研究领域：Traditional Chinese Medicine Studies、Chromatography in Natural Products、Traditional Chinese Medicine Analysis

Introduction: Type 2 diabetes (T2D) is a multifactorial complex chronic disease with a high prevalence worldwide, and Type 2 diabetes patients with different comorbidities often present multiple phenotypes in the clinic. Thus, there is a pressing need to improve understanding of the complexity of the clinical Type 2 diabetes population to help identify more accurate disease subtypes for personalized treatment. Methods: Here, utilizing the traditional Chinese medicine (TCM) clinical electronic medical records (EMRs) of 2137 Type 2 diabetes inpatients, we followed a heterogeneous medical record network (HEMnet) framework to construct heterogeneous medical record networks by integrating the clinical features from the electronic medical records, molecular interaction networks and domain knowledge. Results: Of the 2137 Type 2 diabetes patients, 1347 were male (63.03%), and 790 were female (36.97%). Using the HEMnet method, we obtained eight non-overlapping patient subgroups. For example, in H3, Poria, Astragali Radix, Glycyrrhizae Radix et Rhizoma, Cinnamomi Ramulus, and Liriopes Radix were identified as significant botanical drugs. Cardiovascular diseases (CVDs) were found to be significant comorbidities. Furthermore, enrichment analysis showed that there were six overlapping pathways and eight overlapping Gene Ontology terms among the herbs, comorbidities, and Type 2 diabetes in H3. Discussion: Our results demonstrate that identification of the Type 2 diabetes subgroup based on ...