Lipidome, central carbon metabolites, and sleep rhythm in coronary heart disease with nontraditional risks: An exploratory pilot study

Abstract

AimsAltered lipid, energy metabolism and sleep disorders had been linked with coronary heart disease (CHD), however, the metabolic signatures and sleep rhythm in non-obstructive coronary atherosclerosis-CHD remain unclear. This pilot study aims to investigate the lipidome and central carbon metabolites profiles and associated sleep characteristics among CHD patients without traditional risk factors. MethodsFrom January to July 2021, 15 CHD patients and 15 healthy controls were randomly selected from the cardiology unit of Zhongshan Hospital, Shanghai. A total of 464 lipids and 45 central carbon metabolites (CCM) were quantified in blood plasma. Metabolic signatures were selected through orthogonal projections to latent structures discriminant analysis (OPLS-DA) and principal component analysis (PCA) was conducted to link the profiles of identified metabolites with CHD risk, sleep patterns, cardiometabolic traits and cardiac electrophysiologic parameters. ResultsUsing OPLS-DA, we identified 40 metabolites (variable influence on projection >1) that were altered in CHD patients, with 38 lipids, including 25 triacylglycerols (TAGs), 8 diacylglycerols (DAGs), being elevated and two CCM metabolites (i.e., succinic acid and glycolic acid) being reduced. Using PCA, four principal components (PCs) were identified and associated with increased risk of CHD. Specifically, one standard unit increasement in the PC that was characterized by high levels of DAG (18:1) and low succinic acid and the PC that was characterized by high levels of two sphingomyelins [SM (26:0) and SM (24:0)] was associated with 21% [odds ratio (OR) = 1.21, 95% CI: 1.02,1.43] and 14% (OR = 1.14,1.02,1.29) increased risk of CHD, respectively. Further regression analyses confirmed that the identified metabolites and the four PCs were positively associated with TG and ALT. Interestingly, glycolic acid was negatively associated with sleep quality and PSQI. Participants with night sleep mode tended to have a high level of the identified lipids, especially FFA (20:4). ConclusionIn the present pilot study, our findings provide clues on alterations of lipid and energy metabolism in CHD patients without traditional risk factors, with multiple triacylglycerols and diacylglycerols metabolites seemingly elevated and certain nonlipids metabolites (e.g., succinic acid and glycolic acid) decreased in cases. Considering the limit sample size, further studies are warranted to confirm our results.