The metabolic pattern could be used for early detection of stable ischemic heart disease and hypertensive heart disease

Abstract

Introduction Cardiovascular diseases are a leading cause of morbidity and mortality worldwide accounting for 32% of all deaths across EU countries. Ischemic heart disease (IHD), known also as coronary artery disease (CAD) comprised 17% of all deaths. For up to 20% of patients, the first manifestation of IHD is sudden cardiac arrest occurring outside the hospital. Estonia stands out with the much higher prevalence of the cardiovascular diseases than Western-European countries. In Estonia, half of deaths are caused by circulatory system diseases according to the Estonian Causes of Death Registry. An urgent necessity for more sensitive biomarkers identifying altered health conditions specifically among the variety of patients with different risk factors is foreseeable. Metabolomics of human biofluids has turned into a rapidly developing area and as a quantitative molecular level method may offer extra advantages in clarification of the pathogenesis and therapy monitoring. Methods We profiled the metabolic pattern of serum of patients classified according to International Classification of Diseases (ICD10). Most of the patients were treated with statins, ACE-inhibitors (ACEI) or angiotensin receptor blockers (ARB) and acetylsalicylic acid as an anticholesterol, an antihypertensive, and an anticoagulant medication. The control group was selected from healthy volunteers without known heart and vascular diseases and without medication. This study was performed in accordance with the Helsinki Declaration and was approved by the Tallinn Medical Research Ethics Committee. The filtered venous serum from age and gender matched IHD patients ICD10 coded I20 (n = 12), I25.2 (n = 6), I11 (n = 25) and control individuals (n = 20) were analyzed using one-dimensional proton nuclear magnetic resonance (1H NMR) spectroscopy. These spectra were used for metabolic profiling and concentration calibration (Chenomx Inc) followed by statistical analysis using one-way Anova and principal component analysis (PCA). Results The study evaluates serum of 43 individuals of Estonian origin. We identified from serum spectra about 83 metabolites. The metabolite concentrations are in good accordance with results provided by clinical chemistry reference values, the Human Metabolome Database (HMDB) library and various studies. The IHD patients are characterized by the increased concentration of acetylacetate, choline, pyruvate, betaine, formate and by the decreased concentration of alanine, creatine, glycine, histidine, lactate, proline, urea and other biomolecules. The major implications found in the serum of IHD patients are related to energy metabolism. A number of calibrated metabolites are related to human microbiome according to the information provided in the literature: trimethylamine-N-oxide (TMAO), formate and hippuric acid. Interestingly, the altered health conditions might be potentially characterized by altered microbiome. Chemometrics analysis showed a significant distinction between the patients and control individuals. The metabolic profile of ischemic patients with or without previous myocardial infarction appears to be similar. The pattern of HHD patients follows the changes of the serum of IHD patients in regard of some amino acids concentrations but is negatively correlated in regard to formate and 3-hydroxybutyrate. Conclusion PCA of 1H NMR detected serum metabolites exhibit a significant difference among the IHD patients, HHD patients and control individuals. These data demonstrate that metabolomics approach may be useful for the early detection of some circulatory diseases, for detection of synergistic pathways involved in the development of altered health conditions, and molecular understanding of particular health condition. This relatively inexpensive, non-invasive and reproducible approach may be useful for the molecular understanding and early prevention of health conditions, improvement of surveillance and therapy. This work was supported by the Estonian Research Council grant PUT 1534.