Anastasios Papageorgiou

The expanding scope and sensitivity of genomic testing are reshaping hereditary cancer assessment, shifting attention from the detection of genomic variants alone to the more complex task of determining their significance, biological origin, and relevance to clinical management. This review examines the analytical, biological, and clinical factors that shape this process and integrates them within a five-stage translational framework encompassing variant detection, variant interpretation, biological attribution, clinical validity, and utility. Reliable interpretation requires appropriate test and gene selection, recognition of assay limitations and technically challenging variant classes, and evidence-based variant classification. Computational prediction can support variant interpretation when appropriately validated. Polygenic risk models may further refine risk estimation, although their clinical implementation remains limited by validation, calibration, and population-specific performance. Ancestry-related limitations in genomic resources remain relevant to both variant interpretation and risk estimation. Particular attention is given to biological attribution, illustrated by liquid biopsy, where clonal hematopoiesis can confound the origin and clinical interpretation of plasma variants. Genomic findings must ultimately be considered together with phenotype, family history, gene–disease validity, and disease-specific evidence when informing risk assessment, surveillance, prevention, counseling, or treatment. As hereditary cancer testing continues to expand, its value will depend less on the number of findings generated than on how reliably those findings can be translated into meaningful benefit for patients and families.

Cardiovascular diseases (CVDs) are the foremost contributor to global mortality, with a significant inherited factor that has long been recognized but only recently become decipherable. Next-generation sequencing (NGS) has transformed the study of cardiovascular genetics, allowing researchers to move beyond single-gene analyses toward comprehensive assessments of both rare and common genetic variations. This review summarizes how NGS informs clinical practice, from the molecular diagnosis of inherited cardiac disorders and risk prediction using polygenic models to emerging applications in precision therapeutics. It also discusses analytical and ethical challenges and highlights new technologies, such as long-read and single-cell sequencing, that are likely to further advance precision cardiology.

Background/Objectives: Mitochondria are the main organelles for ATP synthesis able to produce energy for several different cellular activities. Cardiac cells require high amounts of energy and, thus, they contain a high number of mitochondria. Consequently, mitochondrial dysfunction in these cells is a crucial factor for the development of cardiovascular diseases. Mitochondria constitute central regulators of cellular metabolism and energy production, producing approximately 90% of the cells’ energy needs in the form of ATP via oxidative phosphorylation. The mitochondria have their own circular, double-stranded DNA encoding 37 genes. Any mitochondrial DNA sequence anomaly may result in defective oxidative phosphorylation and lead to cardiac dysfunction. Methods: In this study, we investigated the potential association between mitochondrial DNA mutation and cardiovascular disease. Cardiac tissue and serum samples were collected from seven patients undergoing coronary artery bypass grafting. Total DNA was extracted from cardiac muscle tissue specimens and serum and each sample was subjected to polymerase chain reaction (PCR) to amplify the NADH dehydrogenase 1 (ND1) gene, which is part of the mitochondrial complex I enzyme complex and was screened for mutations. Results: We identified one patient with a homoplasmic A to G substitution mutation in cardiac tissue DNA and two patients with heteroplasmic A3397G mutation in serum DNA. Specifically, amplicon sequence analysis revealed a homoplasmic A3397G substitution in the ND1 gene in a tissue sample of the patient with ID number 1 and a heteroplasmic mutation in A3397G in serum samples of patients with ID numbers 3 and 6, respectively. The A to G substitution changes the amino acid from methionine (ATA) to valine (GTA) at position 31 of the ND1 gene. Conclusions: The detection of this novel mutation in patients with coronary artery disease may contribute to our understanding of the association between mitochondrial dysfunction and the disease, implying that mitochondria may be key players in the pathogenesis of cardiovascular diseases.