Background: Heart failure (HF) is the most common cause of morbidity and mortality in developed countries. Here, we identify biologically relevant transcripts that are significantly altered in the early phase of myocardial infarction and are associated with the development of post-myocardial infarction HF. Methods: We collected peripheral blood samples from patients with ST-segment elevation myocardial infarction (STEMI): n = 111 and n = 41 patients from the study and validation groups, respectively. Control groups comprised patients with a stable coronary artery disease and without a history of myocardial infarction. Based on plasma NT-proBNP level and left ventricular ejection fraction parameters the STEMI patients were divided into HF and non-HF groups. Microarrays were used to analyze mRNA levels in peripheral blood mononuclear cells (PBMCs) isolated from the study group at four time points and control group. Microarray results were validated by RT-qPCR using whole blood RNA from the validation group. Results: Samples from the first three time points (admission, discharge, and 1 month after AMI) were compared with the samples from the same patients collected 6 months after AMI (stable phase) and with the control group. The greatest differences in transcriptional profiles were observed on admission and they gradually stabilized during the follow-up. We have also identified a set of genes the expression of which on the first day of STEMI differed significantly between patients who developed HF after 6 months of observation and those who did not. RNASE1, FMN1, and JDP2 were selected for further analysis and their early up-regulation was confirmed in HF patients from both the study and validation groups. Significant correlations were found between expression levels of these biomarkers and clinical parameters. The receiver operating characteristic (ROC) curves indicated a good prognostic value of the genes chosen. Conclusions: This study demonstrates an altered gene expression profile in PBMCs during acute myocardial infarction and through the follow-up. The identified gene expression changes at the early phase of STEMI that differentiated the patients who developed HF from those who did not could serve as a convenient tool contributing to the prognosis of heart failure.

Pharmacogenomics aims to correlate inter-individual differences of drug efficacy and/or toxicity with the underlying genetic composition, particularly in genes encoding for protein factors and enzymes involved in drug metabolism and transport. In several European populations, particularly in countries with lower income, information related to the prevalence of pharmacogenomic biomarkers is incomplete or lacking. Here, we have implemented the microattribution approach to assess the pharmacogenomic biomarkers allelic spectrum in 18 European populations, mostly from developing European countries, by analyzing 1,931 pharmacogenomics biomarkers in 231 genes. Our data show significant inter-population pharmacogenomic biomarker allele frequency differences, particularly in 7 clinically actionable pharmacogenomic biomarkers in 7 European populations, affecting drug efficacy and/or toxicity of 51 medication treatment modalities. These data also reflect on the differences observed in the prevalence of high-risk genotypes in these populations, as far as common markers in the CYP2C9, CYP2C19, CYP3A5, VKORC1, SLCO1B1 and TPMT pharmacogenes are concerned. Also, our data demonstrate notable differences in predicted genotype-based warfarin dosing among these populations. Our findings can be exploited not only to develop guidelines for medical prioritization, but most importantly to facilitate integration of pharmacogenomics and to support pre-emptive pharmacogenomic testing. This may subsequently contribute towards significant cost-savings in the overall healthcare expenditure in the participating countries, where pharmacogenomics implementation proves to be cost-effective.

Despite a substantial progress in diagnosis and therapy, acute myocardial infarction (MI) is a major cause of mortality in the general population. A novel insight into the pathophysiology of myocardial infarction obtained by studying gene expression should help to discover novel biomarkers of MI and to suggest novel strategies of therapy. The aim of our study was to establish gene expression patterns in leukocytes from acute myocardial infarction patients. Twenty-eight patients with ST-segment elevation myocardial infarction (STEMI) were included. The blood was collected on the 1^st day of myocardial infarction, after 4–6 days, and after 6 months. Control group comprised 14 patients with stable coronary artery disease, without history of myocardial infarction. Gene expression analysis was performed with Affymetrix Human Gene 1.0 ST microarrays and GCS3000 TG system. Lists of genes showing altered expression levels (fold change >1.5, p<0.05) were submitted to Ingenuity Pathway Analysis. Gene lists from each group were examined for canonical pathways and molecular and cellular functions. Comparing acute phase of MI with the same patients after 6 months (stable phase) and with control group we found 24 genes with changed expression. In canonical analysis three pathways were highlighted: signaling of PPAR (peroxisome proliferator-activated receptor), IL-10 and IL-6 (interleukin 10 and 6). In the acute phase of STEMI, dozens of genes from several pathways linked with lipid/glucose metabolism, platelet function and atherosclerotic plaque stability show altered expression. Up-regulation of SOCS3 and FAM20 genes in the first days of myocardial infarction is observed in the vast majority of patients.

Left ventricular (LV) dysfunction after acute myocardial infarction (AMI) is associated with an increased risk of heart failure (HF) development. Diverse microRNAs (miRNAs) have been shown to appear in the bloodstream following various cardiovascular events. The aim of this study was to identify prognostic miRNAs associated with LV dysfunction following AMI. Patients were divided into subgroups comprising patients who developed or not LV dysfunction within six months of the infarction. miRNA profiles were determined in plasma and serum samples of the patients on the first day of AMI. Levels of 14 plasma miRNAs and 16 serum miRNAs were significantly different in samples from AMI patients who later developed LV dysfunction compared to those who did not. Two miRNAs were up-regulated in both types of material. Validation in an independent group of patients, using droplet digital PCR (ddPCR) confirmed that miR-30a-5p was significantly elevated on admission in those patients who developed LV dysfunction and HF symptoms six months after AMI. A bioinformatics analysis indicated that miR-30a-5p may regulate genes involved in cardiovascular pathogenesis. This study demonstrates, for the first time, a prognostic value of circulating miR-30a-5p and its association with LV dysfunction and symptoms of HF after AMI.

Background: The yeast Saccharomyces cerevisiae can be a useful model for studying cellular mechanisms related to sterol synthesis in humans due to the high similarity of the mevalonate pathway between these organisms. This metabolic pathway plays a key role in multiple cellular processes by synthesizing sterol and nonsterol isoprenoids. Statins are well-known inhibitors of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGR), the key enzyme of the cholesterol synthesis pathway. However, the effects of statins extend beyond their cholesterol-lowering action, since inhibition of HMGR decreases the synthesis of all products downstream in the mevalonate pathway. Using transgenic yeast expressing human HMGR or either yeast HMGR isoenzyme we studied the effects of simvastatin, atorvastatin, fluvastatin and rosuvastatin on the cell metabolism. Results: Statins decreased sterol pools, prominently reducing sterol precursors content while only moderately lowering ergosterol level. Expression of genes encoding enzymes involved in sterol biosynthesis was induced, while genes from nonsterol isoprenoid pathways, such as coenzyme Q and dolichol biosynthesis or protein prenylation, were diversely affected by statin treatment. Statins increased the level of human HMGR protein substantially and only slightly affected the levels of Rer2 and Coq3 proteins involved in non-sterol isoprenoid biosynthesis. Conclusion: Statins influence the sterol pool, gene expression and protein levels of enzymes from the sterol and nonsterol isoprenoid biosynthesis branches and this effect depends on the type of statin administered. Our model system is a cheap and convenient tool for characterizing individual statins or screening for novel ones, and could also be helpful in individualized selection of the most efficient HMGR inhibitors leading to the best response and minimizing serious side effects.

Acute myocardial infarction (AMI) is a life-threatening episode of coronary artery disease. Recently, circulating myocardial-derived microRNAs (miRNAs) have been reported as potential biomarkers of infarction. The present study aimed to identify differentially expressed miRNAs in patients with ST-segment elevation myocardial infarction that could be potentially dysregulated in response to early myocardial damage. miRNA expression profile analysis was performed using the Serum/Plasma Focus miRNA Polymerase Chain Reaction (PCR) panel of Exiqon A/S (Vedbaek, Denmark) on plasma samples of patients on the first day of AMI (admission) and on samples from the identical patients collected six months following AMI. Selected miRNAs were validated by reverse transcription‑quantitative PCR (RT‑qPCR) using independent patients with AMI and a control group of patients with a stable coronary artery disease. Thirty‑two species of plasma miRNA were differentially expressed (P<0.05) on admission compared with six months following AMI. Subsequent validation in an independent patient group confirmed that miR‑133b and miR‑22‑5p were significantly up‑regulated in the serum of patients with AMI. The receiver operating characteristic (ROC) curve analysis demonstrated a diagnostic utility for miR-22-5p, which has not previously been reported to be associated with AMI. Among the selected miRNAs, miR‑22‑5p represents a novel promising biomarker for the diagnosis of AMI.