StatusThe thesis was presented on the 14 September, 2017
Approved by NCAA on the 11 May, 2018
Abstract– 1.11 Mb / in romanian
4.49 Mb /
The thesis include introduction, five chapters, general conclusions and recommendations, 441 references, a total volume of 159 pages, 29 figures, 28 tables and 18 annexes. Obtained results were published in 19 scientific papers.
Field of investigation: Human and animal genetics.
The purpose of the research consists in identification of candidate genes by exploratory analysis of microarray data and their association with expression level of coronary artery disease with/without atrial fibrillation, cardiomyopathy and congenital aortic stenosis.
Objectives of the thesis: identification of candidate genes causing the cardiovascular diseases, based on microarray datasets from NCBI, GEO; evaluation of the gene expression potential involved in cardiovascular diseases in children and adults; estimating the variability of gene expression associated with cardiovascular diseases; establishing the expression profile of one set of genes under certain pathological conditions.
Scientific novelty and originality. For the first time was evaluated the expression of a set of 18 genes in patients with different cardiovascular pathologies in the Republic of Moldova was evaluated at the blood level. The molecular study revealed the differential gene expression according to the clinical phenotype and the age of the subjects, and established specific expression profiles for ischemic cardiopathy with / without atrial fibrillation, congenital aortic stenosis, cardiomyopathy, and demonstrated the implication of candidate genes in the pathogenesis of cardiovascular diseases.
The most important solved scientific problem consists in the establishing of the expression patterns specific to each clinical studied phenotype, demonstrating the homogeneity of the transcripts content of the investigated genes in healthy subjects and the high heterogeneity in the patients, which confirms the variability of gene expression between the different physiological states of the organism in order to optimize the procedure for stratification of the patients with cardiovascular diseases.
The theoretical significance. The work reflects an exploratory proceeding of analysis and interpretation of the results of microarray tests, with the identification not only of the genes with established, but also of other groups of genes potentially involved in cardiovascular pathologies. The obtained results from bioinformatics and molecular genetic investigations deepen the knowledge about the contribution of genetic factors in the pathogenesis of the targeted pathological conditions.
The applicative value of the work. By PCR with specific primers, 18 genes associated with various biological processes important in the molecular pathogenesis of cardiovascular diseases were highlighted. The bioinformatics strategy of extracting and analyzing the microarray expression data allowed identifying genes of priority and potential role in cardiovascular diseases. The transcriptional profiles of genes validated by laboratory methods have been used in the stratification of patients with cardiomyopathy, ischemic cardiopathy with / without atrial fibrillation and congenital aortic stenosis.
Implementation of scientific results. The methodology of extracting and analyzing of microarray expression data is applied in identifying of the genes with potential role in different biological processes within the Centre of Functional Genetics (CFG) of UnASM. The obtained and presented data in the thesis will serve as a scientific-didactic material for the courses of Molecular Biology and Genetic Analysis Methods at the Department of Biology of the Faculty of Natural Sciences, UnASM. The specific primers, developed for the study of 18 gene expression in subjects with cardiovascular disease, are used in the CFG of UnASM and are recommended for subsequent genetic and molecular research. The established expression patterns for the studied cardiovascular diseases can be recommended in patient detection and stratification.