Metabolic Profiling Identifies 1-MetHis and 3-IPA as Potential Diagnostic Biomarkers for Patients With Acute and Chronic Heart Failure With Reduced Ejection Fraction.

BACKGROUND: Metabolomics has become a valuable tool for identifying potential new biomarkers and metabolic profiles. It has the potential to improve the diagnosis and prognosis of different phenotypes of heart failure. To generate a distinctive metabolic profile, we assessed and compared the metabolic phenotypes of patients with acute decompensated heart failure (ADHF), patients with chronic heart failure (CHF), and healthy controls. METHODS: Plasma metabolites were analyzed by liquid-chromatography mass spectrometry/mass spectrometry and the MxP Quant 500 kit in 15 patients with ADHF, 50 patients with CHF (25 with dilated cardiomyopathy, 25 with ischemic cardiomyopathy), and 13 controls. RESULTS: Of all metabolites identified to be significantly altered, 3-indolepropionic acid and 1-methyl histidine showed the highest concentration differences in ADHF and CHF compared with control. Area under the curve-receiver operating characteristic analysis showed an area under the curve ≥0.8 for 3-indolepropionic acid and 1-methyl histidine, displaying good discrimination capabilities between control and patient cohorts. Additionally, symmetrical dimethylarginine (mean, 1.97±0.61 [SD]; P=0.01) was identified as a suitable biomarker candidate for ADHF and kynurenine (mean, 1.69±0.39 [SD]; P=0.009) for CHF when compared with control, both demonstrating an area under the curve ≥0.85. CONCLUSIONS: Our study provides novel insights into the metabolic differences between ADHF and CHF and healthy controls. We here identify new metabolites for potential diagnostic and prognostic purposes.

Clonal haematopoiesis of indeterminate potential-related mutations and outcome in dilated and ischaemic cardiomyopathy.

AIMS: Clonal haematopoiesis of indeterminate potential (CHIP)-associated mutation is a risk factor for the development of ischaemic cardiomyopathy (ICM), but its association with non-ischaemic dilated cardiomyopathy (DCM) remains unclear. We aimed to determine the prevalence of CHIP in patients with DCM and define its risk for disease progression. METHODS AND RESULTS: Next-generation sequencing targeting 54 common CHIP-associated genes was performed in 48 ICM and 52 DCM patients. The patients were monitored for a median of 3.1 years, and a COX proportional hazards model was used to examine the association between CHIP and adverse clinical outcome with regard to all-cause death or all-cause hospitalization. Overall, the prevalence of CHIP mutations was 19% and 13% in DCM and ICM, respectively. Seventeen per cent of ICM patients over 75 years were CHIP carriers. In DCM cohort, mutation event had already been observed in the patients who were under the age of 45 (13%). Among 54 genes analysed, DNMT3A had the highest mutation frequency, followed by TET2 and CUX1. Kaplan-Meier curve over a median of 3.1 year tracking period showed a trend towards poor clinical outcome in the DCM patients who carried DNMT3A or TET2 mutation; however, such association was not statistically significant. CONCLUSIONS: The prevalence of CHIP is detected at a young age in DCM, and accumulation of mutational frequency in DCM patients is independent of age. However, a larger patient cohort is required to validate the association between CHIP and clinical progression in the DCM patients.