Associations of plasma acylcarnitine and bile acid levels with incidence of coronary heart disease in Chinese adults

Abstract

Objective: To explore the associations of plasma acylcarnitine and bile acid levels with the risk of incident coronary heart disease (CHD) in Chinese adults. Methods: The baseline survey of China Kadoorie Biobank (CKB) took place in 10 areas across China during 2004-2008, and the first resurvey took place from July to October 2008, with collection of data via questionnaire, physical examination and blood samples. The current study was based on 2 159 individuals with targeted mass spectrometry metabolomic measurements from the first resurvey of CKB. The associations of acylcarnitines and bile acids with incident CHD were assessed using Cox proportional hazards regression models. Unweighted metabolites scores were constructed to assess the overall effect of acylcarnitines and bile acids on incident CHD. The impact of metabolites on the performance of CHD prediction model was evaluated with the receiver operating characteristic (ROC) area under the curve (AUC). Follow-up for CHD incidence was censored on December 31, 2018. Results: The mean age of the participants was (53.1±9.8) years and 754 were males (34.9%). During (10.5±0.1) years of follow-up, 140 cases of CHD were recorded. Four metabolites including acylcarnitines C3-OH, C5:1, C5:1-DC, and deoxycholic acid (DCA) showed associations with CHD incidence and the HR (95%CI) were 1.474 (1.230-1.767), 0.761 (0.637-0.909), 0.773 (0.650-0.918), and 1.309 (1.113-1.539), respectively [false discovery rate (FDR)0.05]. All metabolite scores, including short-chain, medium-chain, long-chain acylcarnitines, primary and secondary bile acids scores were associated with the risk of CHD (FDR0.05). Compared to the traditional models, the addition of DCA or 4 key metabolites increased the AUC of the predictive model from 0.803 (0.761-0.845) to 0.812 (0.772-0.852) and 0.817 (0.778-0.857), respectively (all P0.05). Conclusions: Acylcarnitine and bile acid levels are associated with the risk of CHD, and DCA or 4 key metabolites can improve the predictive ability for CHD incidence.