Identification of Hypertension Subgroups through Topological Analysis of Symptom-Based Patient Similarity

Objective To obtain the subtypes of the clinical hypertension population based on symptoms and to explore the relationship between hypertension and comorbidities. Methods The data set was collected from the Chinese medicine (CM) electronic medical records of 33,458 hypertension inpatients in the Affiliated Hospital of Shandong University of Traditional Chinese Medicine between July 2014 and May 2017. Then, a hypertension disease comorbidity network (HDCN) was built to investigate the complicated associations between hypertension and their comorbidities. Moreover, a hypertension patient similarity network (HPSN) was constructed with patients' shared symptoms, and 7 main hypertension patient subgroups were identified from HPSN with a community detection method to exhibit the characteristics of clinical phenotypes and molecular mechanisms. In addition, the significant symptoms, diseases, CM syndromes and pathways of each main patient subgroup were obtained by enrichment analysis. Results The significant symptoms and diseases of these patient subgroups were associated with different damaged target organs of hypertension. Additionally, the specific phenotypic features (symptoms, diseases, and CM syndromes) were consistent with specific molecular features (pathways) in the same patient subgroup. Conclusion The utility and comprehensiveness of disease classification based on community detection of patient networks using shared CM symptom phenotypes showed the importance of hypertension patient subgroups.

Automated summary

By constructing a hypertension patient similarity network based on shared symptoms, this study identified subtypes of hypertension patients and their associations with different damaged target organs. Specific phenotypic features were found to be consistent with specific molecular features within the same patient subgroup.