Urinary metabolomic profiling reveals difference between two traditional Chinese medicine subtypes of coronary heart disease

The World Health Organization has shown that coronary heart disease (CHD) is a more common cause of death than cancer. In traditional Chinese medicine (TCM), CHD is classified as a form of thoracic obstruction that can be divided in different subtypes including Qi stagnation with blood stasis (QS) and Qi deficiency with blood stasis (QD). Different treatment strategies are used based on this subtyping. Owing to the lack of scientific markers in the diagnosis of these subtypes, subjective judgments made by clinicians have limited the objective manner for utility of TCM in the treatment of CHD. Untargeted (UHPLC-QTOF-MS) and targeted (UHPLC-MS/MS) metabolomics approaches were employed to search significantly different metabolites related to the QS or QD subtypes of CHD with angina pectoris in this study. A total of 42 metabolites were obtained in the untargeted metabolomics analysis and 34 amino acids were detected in the targeted metabolomics analysis. In total, 16 metabolites were found significantly different among different groups. The results showed distinct metabolic profiles of urine samples not only between CHD patients and healthy controls, but also between the two subtypes of CHD. Pathway analysis of the significantly varied metabolites revealed that there were subtype-related differences in the activity of pathways. Therefore, urinary metabolomics can reveal the pathological changes of CHD in different subtypes, make the diagnosis of CHD in different subtypes in an objective manner and comprehensive and contribute to personalized treatment by providing scientific evidence.

Automated summary

This study used untargeted and targeted metabolomics approaches to explore the significantly different metabolites related to the Qi stagnation with blood stasis or Qi deficiency with blood stasis subtypes of coronary heart disease (CHD) with angina pectoris. The results showed distinct metabolic profiles not only between CHD patients and healthy controls, but also between the two subtypes of CHD. Pathway analysis revealed subtype-related differences in the activity of pathways, demonstrating the potential of urinary metabolomics in providing evidence for personalized treatment of CHD.