An untargeted metabolomics analysis suggests pathophysiological changes for post cardiac arrest syndrome

Cardiac arrest (CA) is a significant cause of mortality worldwide. However, the differences of untargeted metabolomics of CA patients have rarely been described.

CA patients and controls were enrolled at the Emergency Department of Peking University Third Hospital between September 2022 and August 2023 in this prospective cohort study. Medical record data were utilized, and blood samples were analyzed via ultrahigh-performance liquid chromatography-tandem mass spectrometry. Comparison was made between CA patients vs controls and survivors vs non- survivors. Multivariate feature selection by sparse partial least squares discriminant analysis and metabolite set enrichment analysis were used to identify metabolites and biological pathways.Correlation analysis between these metabolites included in Significant enrichment pathways and clinical laboratory indicators was conducted.

23 controls and 23 CA patients met the inclusion criteria. Principal component analysis and partial least squares discriminant analysis indicated a clear separation between the patients with CA and the healthy controls. A total of 348 differentially abundant metabolites, consisting of 132 upregulated metabolites and 216 downregulated metabolites, were screened between the above two groups. The CA group included 16 non-survivors and 7 survivors. Compared with non-survivors, 85 differentially abundant metabolites in survivors were upregulated, and 283 metabolites were downregulated. Choline metabolism in cancer and glycerophospholipid metabolism, were upregulated and enriched by Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, whereas tryptophan metabolism, steroid hormone biosynthesis and alanine, aspartate and glutamate metabolism, and were downregulated. L-kynurenine, PLCs, cortisol and L-glutamate were correlated with some laboratory indicators.

Differentially abundant metabolites and pathways discovered by metabolomics analysis may explained the pathophysiological changes of post CA syndrome. Some metabolites were hopeful to be prognostic biomarkers for post CA syndrome. Further pre-clinical and clinical researches need to study the mechanism of these findings.