ArticleHeliyon2023
Lipidome, central carbon metabolites, and sleep rhythm in coronary heart disease with nontraditional risks: An exploratory pilot study.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed, 0 citations in OpenAlex.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aims: Altered 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. Methods: From 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. Results: Using 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). Conclusion: In 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.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.