Uticaj ekspresije gena uključenih u apoptozu, redoks statusa i patogenezu na tip kardiomiopatije
Grujić, Jelena, 1993-
Filipović, Nenad, 1970-
Stanković, Vesna, 1964-
Velicki, Lazar, 1980-
Stojković-Filipović, Jelena, 1974-
Uvod: U doktorskoj disertaciji „Uticaj ekspresije gena uključenih u apoptozu,redoks status i patogenezu na tip kardiomiopatije“ istražuju se molekularni igenetski mehanizmi hipertrofične kardiomiopatije. Kardiomiopatije su vodećiuzrok srčane insuficijencije i iznenadne smrti. Ova studija analizira genetskepolimorfizme u genima MYBPC3 i MYH7 i njihovu korelaciju sa kliničkimpodacima pacijenata.Cilj: Cilj je istraživanje ekspresije gena povezanih sa apoptozom, redoks statusomi patogenezom hipertrofične kardiomiopatije, kao i analiza genetskih i kliničkihpodataka primenom veštačke inteligencije radi preciznije dijagnoze ipersonalizovanog lečenja.Materijal i metode: Primenjene su metode molekularne biologije, kao što su qRTPCR za analizu ekspresije gena i polimorfizama, napredne statističke analize ialgoritmi mašinskog učenja, uključujući Random Forest, za klasifikacijupacijenata na osnovu genetskih profila.Rezultati: Grupa pacijenata sa hipertrofičnom kardiomiopatijom pokazala jestabilnu kliničku sliku između dve posete. PCR analiza je ukazala na smanjenjeekspresije ispitivanih gena, što ističe njihovu ulogu u patogenezi bolesti.Klasifikacioni model koji kombinuje kliničke i genetske podatke postigao jetačnost od 92%.Zaključak: Istraživanje potvrđuje važnost multidimenzionalnog pristupa kojikombinuje genetske i kliničke podatke za bolje razumevanje hipertrofičnekardiomiopatije, razvoj biomarkera i personalizovane terapije.
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Introduction: The doctoral dissertation titled “The Impact of Gene Expression Involved inApoptosis, Redox Status, and Pathogenesis on the Type of Cardiomyopathy” investigatesmolecular and genetic mechanisms underlying hypertrophic cardiomyopathy.Cardiomyopathies are major causes of heart disease and leading risk factors for heart failureand sudden cardiac death. This study focuses on genetic predispositions, particularlypolymorphisms in the MYBPC3 and MYH7 genes, and examines correlations betweenclinical and genetic data.Aim: The dissertation aims to analyze the expression of genes related to apoptosis, redoxstatus, and hypertrophic cardiomyopathy pathogenesis using artificial intelligence tointegrate clinical and genetic data for precise diagnosis and personalized treatment. It alsoinvestigates polymorphisms associated with hypertrophic cardiomyopathy.Materials and Methods: Molecular biology techniques, such as qRT-PCR, were used toanalyze gene expression and polymorphisms. Advanced statistical analysis and machinelearning algorithms, including Random Forest, were applied to classify patients and evaluatethe significance of genetic factors in cardiac risk.Results: Patients with hypertrophic cardiomyopathy showed stable clinical profiles betweenvisits. Genotyping revealed genotype distributions consistent with Hardy-Weinbergequilibrium. Gene expression analysis indicated a general decrease in expression,highlighting their role in pathogenesis. A classification model combining clinical andgenetic data achieved 92% accuracy, demonstrating the value of a multidimensionalapproach in analysis.Conclusion: The study highlights the need for larger samples to enhance statisticalsignificance and supports the development of biomarkers and personalized therapies.
srpski
2024
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