Congenital heart defects (CHDs) represent the most prevalent congenital developmental anomaly, affecting approximately 1% of children. They are a leading cause of neonatal mortality, morbidity, and long-term disability, and thus pose a significant public health challenge. The etiology of CHDs remains unexplained in 50 to 70% of cases, with diagnostic yield limited by both clinical and genetic heterogeneity. This doctoral thesis aims to clarify the genetic etiology of CHDs in a representative patient cohort. A concurrent diagnostic strategy was employed, utilizing both molecular karyotyping and next-generation sequencing (NGS) in individuals with isolated and syndromic CHDs. The study included 609 patients who underwent genetic diagnostics at the Department of Medical Genetics, University Medical Centre Ljubljana, between January 2013 and December 2024. Phenotypic data were systematically characterized through retrospective review of medical records. A genetic cause was identified in 20.2% of all CHD patients, with a diagnostic yield of 28.3% in syndromic cases and 9% in isolated cases. In total, 65 distinct genetic causes were identified, including 29 known microdeletion or microduplication syndromes and 36 monogenic causes. Among the monogenic causes, seven novel causal variants in six genes were discovered in this population. Establishing a genetic diagnosis in patients with isolated CHDs provides substantial clinical benefits by informing treatment plans and optimizing long-term follow-up, particularly in neonatal care. The study integrated internationally validated clinical genetic panels, the Exomiser tool, analysis of genes essential for embryonic heart development, and GWAS-associated genes. This approach led to the identification of 15 novel candidate genes (USP15, USP34, MYOM2, FBLN2, XAB2, CTBP2, CMYA5, JMJD1C, SPTBN5, FLRT2, RXRA, TAGLN, MYH7B, TFDP2, TOX2) that may contribute to the molecular pathology of CHDs. To evaluate the involvement of these candidate genes in CHD development, a protein-protein interaction analysis was performed between candidate genes and those with established etiological links to CHD. Bioinformatic analyses were conducted using the Cytoscape platform and integrated applications including STRING, cytoHubba, Metascape, and g:Profiler. Based on the integrated analysis and supporting literature, RXRA and USP15 are proposed as the most promising candidate genes potentially implicated in CHD pathogenesis.
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