Effect of Different Degrees of Blood Stasis on Cognitive Function and Plasma Differential Metabolites in Patients with Coronary Heart Disease
10.13422/j.cnki.syfjx.20250964
- VernacularTitle:不同血瘀程度对冠心病患者认知功能及血浆差异代谢物的影响
- Author:
Shihan XU
1
;
Yanfei LIU
1
;
Fenglan LIU
1
;
Qing WANG
1
;
Fengqin XU
1
;
Yue LIU
1
Author Information
1. National Clinical Research Center for Chinese Medicine Cardiology,Key Research Laboratory of Combining Diseases and Evidence to Prevent Vascular Aging,National Administration of Traditional Chinese Medicine,Xiyuan Hospital,China Academy of Chinese Medical Sciences, Beijing 100091,China
- Publication Type:Journal Article
- Keywords:
coronary artery disease;
mild cognitive impairment;
blood stasis score;
metabolomics;
relevance;
phosphatidylcholine;
Logistic regression model
- From:
Chinese Journal of Experimental Traditional Medical Formulae
2025;31(5):167-176
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveTo explore the correlation between the blood stasis score of coronary heart disease(CAD) and mild cognitive impairment(MCI), as well as the changes in plasma metabolic profile of blood stasis in patients with CAD combined with MCI(CADMCI) through a cross-sectional study, and further explore the impact of different degrees of blood stasis on the plasma metabolite profile of CADMCI patients. MethodsAccording to the diagnostic criteria of CAD and CAD blood stasis, patients hospitalized in Xiyuan Hospital of China Academy of Chinese Medical Sciences from October 2022 to October 2023 were continuously included. According to the Montreal Cognitive Assessment(MoCA) scale score, the enrolled patients were divided into CADMCI blood stasis group and CAD blood stasis group. The association between blood stasis score and MCI was analyzed by multivariate Logistic regression model. The receiver operating characteristic(ROC) curve was drawn, and the area under the curve(AUC) was calculated to evaluate the sensitivity and specificity of the model. According to the blood stasis score, the first 30 patients in the CADMCI blood stasis group and CAD blood stasis group were divided into mild blood stasis and severe blood stasis. Ultra performance liquid chromatography-quadrupole-time-of-flight mass spectrometry(UPLC-Q-TOF-MS/MS) was used to detect plasma metabolites in each group of patients. The differential metabolites were screened according to variable importance in the projection(VIP) value≥1, fold change(FC)<0.67 or >1.5, and P<0.05. ROC curve analysis was further used to evaluate the discriminatory efficiency of the screened differential metabolites for each group of samples. ResultsA total of 266 CAD patients were included in this study. Multivariate Logistic regression analysis showed that the CAD blood stasis score was significantly correlated with MCI[odds ratio(OR)=1.619, 95% confidence interval(CI) 1.223-2.142, P<0.001, ROC curve AUC was 0.615(95% CI 0.547-0.683, P=0.001)], indicating that the CAD blood stasis score has a certain predictive value for MCI. Plasma non-targeted metabolomics analysis showed that the main differential metabolites between CAD blood stasis and CADMCI blood stasis were lipid metabolites, among which phosphatidylcholine[20∶4(5Z, 8Z, 11Z, 14Z)/P-18∶1(11Z)] had the best discriminatory efficiency(ROC curve AUC=0.867, 95% CI 0.754-0.942). Further analysis of the differential metabolites between mild and severe blood stasis showed that lipid metabolites were also the main differential metabolites between mild and severe blood stasis. Among them, 1α,25-dihydroxy-2β-(2-hydroxyethoxy) vitamin D3 had the best efficacy in distinguishing mild and severe CAD blood stasis(AUC=0.813, 95% CI 0.649-0.951), and phosphatidylcholine 34∶2 had the best efficacy in distinguishing mild and severe CADMCI blood stasis(AUC=0.819, 95% CI 0.640-0.941). ConclusionThere is a significant correlation between CAD blood stasis score and MCI. Phosphatidylcholine metabolites play an important role in the pathogenesis of CADMCI blood stasis and severe blood stasis. The CAD blood stasis score combined with the detection of phosphatidylcholine metabolites can provide a reference for the development of early and efficient identification strategies for CADMCI.