Non-targeted metabolomics identify polyamine metabolite acisoga as novel biomarker for reduced left ventricular function.

Aims: Chronic heart failure with reduced ejection fraction remains a major health issue. To date, no reliable biomarker is available to predict reduced left ventricular ejection fraction (LV-EF). We aimed to identify novel circulating biomarkers for reduced left ventricular function using untargeted serum metabolomics in two independent patient cohorts. Methods and results: Echocardiography and non-targeted serum metabolomics were conducted in two patient cohorts with varying left ventricular function: (1) 25 patients with type 2 diabetes with established cardiovascular disease or high cardiovascular risk (LV-EF range 20–66%) (discovery cohort) and (2) 37 patients hospitalized for myocardial infarction (LV-EF range 25–60%) (validation cohort). In the discovery cohort, untargeted metabolomics revealed seven metabolites performing better than N-terminal pro-B-type natriuretic peptide in the prediction of impaired left ventricular function shown by LV-EF. For only one of the metabolites, acisoga, the predictive value for LV-EF could be confirmed in the validation cohort (r = −0.37, P = 0.02). In the discovery cohort, acisoga did not only correlate with LV-EF (r = −60, P = 0.0016), but also with global circumferential strain (r = 0.67, P = 0.0003) and global longitudinal strain (r = 0.68, P = 0.0002). Similar results could be detected in the discovery cohort in a 6 month follow-up proofing stability of these results over time. With an area under the curve of 0.86 in the receiver operating characteristic analysis, acisoga discriminated between patients with normal EF and LV-EF < 40%. Multivariate analysis exposed acisoga as independent marker for impairment of LV-EF (Beta = −0.71, P = 0.004). Conclusions: We found the polyamine metabolite acisoga to be elevated in patients with impaired LV-EF in two independent cohorts. Our analyses suggest that acisoga may be a valuable biomarker to detect patients with heart failure with reduced ejection fraction

Cross-omics analysis revealed gut microbiome-related metabolic pathways underlying atherosclerosis development after antibiotics treatment.

Objective: The metabolic influence of gut microbiota plays a pivotal role in the pathogenesis of cardiometabolic diseases. Antibiotics affect intestinal bacterial diversity, and long-term usage has been identified as an independent risk factor for atherosclerosis-driven events. The aim of this study was to explore the interaction between gut dysbiosis by antibiotics and metabolic pathways with the impact on atherosclerosis development.Methods: We combined oral antibiotics with different diets in an Apolipoprotein E-knockout mouse model linking gut microbiota to atherosclerotic lesion development via an integrative cross-omics approach including serum metabolomics and cecal 16S rRNA targeted metagenomic sequencing. We further investigated patients with carotid atherosclerosis compared to control subjects with comparable cardiovascular risk.Results: Here, we show that increased atherosclerosis by antibiotics was connected to a loss of intestinal diversity and alterations of microbial metabolic functional capacity with a major impact on the host serum metabolome. Pathways that were modulated by antibiotics and connected to atherosclerosis included diminished tryptophan and disturbed lipid metabolism. These pathways were related to the reduction of certain members of Bacteroidetes and Clostridia by antibiotics in the gut. Patients with atherosclerosis presented a similar metabolic signature as those induced by antibiotics in our mouse model.Conclusion: Taken together, this work provides insights into the complex interaction between intestinal microbiota and host metabolism. Our data highlight that detrimental effects of antibiotics on the gut flora are connected to a pro-atherogenic metabolic phenotype beyond classical risk factors