Influence of the expression of genes involved in apoptosis, redox status and pathogenesis on the cardiomyopathy type

[J. N. Pavić]

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Uvod: U doktorskoj disertaciji „Uticaj ekspresije gena uključenih u apoptozu, redoks status i patogenezu na tip kardiomiopatije“ istražuju se molekularni i genetski mehanizmi hipertrofične kardiomiopatije. Kardiomiopatije su vodeći uzrok srčane insuficijencije i iznenadne smrti. Ova studija analizira genetske polimorfizme u genima MYBPC3 i MYH7 i njihovu korelaciju sa kliničkim podacima pacijenata. Cilj: Cilj je istraživanje ekspresije gena povezanih sa apoptozom, redoks statusom i patogenezom hipertrofične kardiomiopatije, kao i analiza genetskih i kliničkih podataka primenom veštačke inteligencije radi preciznije dijagnoze i personalizovanog lečenja. Materijal i metode: Primenjene su metode molekularne biologije, kao što su qRTPCR za analizu ekspresije gena i polimorfizama, napredne statističke analize i algoritmi mašinskog učenja, uključujući Random Forest, za klasifikaciju pacijenata na osnovu genetskih profila. Rezultati: Grupa pacijenata sa hipertrofičnom kardiomiopatijom pokazala je stabilnu kliničku sliku između dve posete. PCR analiza je ukazala na smanjenje ekspresije ispitivanih gena, što ističe njihovu ulogu u patogenezi bolesti. Klasifikacioni model koji kombinuje kliničke i genetske podatke postigao je tačnost od 92%. Zaključak: Istraživanje potvrđuje važnost multidimenzionalnog pristupa koji kombinuje genetske i kliničke podatke za bolje razumevanje hipertrofične kardiomiopatije, razvoj biomarkera i personalizovane terapije.

Introduction: The doctoral dissertation titled “The Impact of Gene Expression Involved in Apoptosis, Redox Status, and Pathogenesis on the Type of Cardiomyopathy” investigates molecular and genetic mechanisms underlying hypertrophic cardiomyopathy. Cardiomyopathies are major causes of heart disease and leading risk factors for heart failure and sudden cardiac death. This study focuses on genetic predispositions, particularly polymorphisms in the MYBPC3 and MYH7 genes, and examines correlations between clinical and genetic data. Aim: The dissertation aims to analyze the expression of genes related to apoptosis, redox status, and hypertrophic cardiomyopathy pathogenesis using artificial intelligence to integrate clinical and genetic data for precise diagnosis and personalized treatment. It also investigates polymorphisms associated with hypertrophic cardiomyopathy. Materials and Methods: Molecular biology techniques, such as qRT-PCR, were used to analyze gene expression and polymorphisms. Advanced statistical analysis and machine learning algorithms, including Random Forest, were applied to classify patients and evaluate the significance of genetic factors in cardiac risk. Results: Patients with hypertrophic cardiomyopathy showed stable clinical profiles between visits. Genotyping revealed genotype distributions consistent with Hardy-Weinberg equilibrium. Gene expression analysis indicated a general decrease in expression, highlighting their role in pathogenesis. A classification model combining clinical and genetic data achieved 92% accuracy, demonstrating the value of a multidimensional approach in analysis. Conclusion: The study highlights the need for larger samples to enhance statistical significance and supports the development of biomarkers and personalized therapies.

kardiomiopatija, ekspresija gena, apoptoza, redoks status, polimorfizam gena, precizna medicina, personalizovana terapija, mašinsko učenje, molekularna biologija, kardiovaskularna oboljenja.

cardiomyopathy, gene expression, apoptosis, redox status, gene polymorphism, precision medicine, personalized therapy, machine learning, molecular biology, cardiovascular diseases.

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