Key result
Genomic tools enhance CV risk stratification, though ancestry bias and integration barriers remain.
Why the study?
Genomic cardiology is an emerging field with substantial potential to improve cardiovascular disease prevention, diagnosis, and treatment, but challenges limit widespread clinical implementation.
Does the integration of genomic information enhance personalized cardiovascular risk stratification and therapeutic decision-making in patients with cardiovascular diseases?
Does the integration of genomic information enhance personalized cardiovascular risk stratification and therapeutic decision-making in patients with cardiovascular diseases?
Genomic cardiology offers promising tools for precision cardiovascular medicine, but equitable implementation requires diverse databases and standardized frameworks.
May support refined risk stratification as enhancers; leaves open equitable adoption pending diverse datasets and prospective validation.
BACKGROUND: Genomic cardiology is an emerging field integrating genetic, molecular, imaging, and digital health data to improve cardiovascular disease (CVD) prevention, diagnosis, and treatment. The genetic architecture of CVD encompasses rare, high-impact variants as well as polygenic susceptibility, both of which influence disease risk, severity, and clinical outcomes. HYPOTHESIS: Integration of genomic information, including rare variants and polygenic risk scores (PRS), with clinical, imaging, biomarker, and artificial intelligence (AI)-based approaches may enhance personalized cardiovascular risk stratification and therapeutic decision-making. METHODS: This review summarizes current applications and emerging developments in genomic cardiology, including whole-genome and whole-exome sequencing, multigene panels, structural variant detection, PRS, multi-omics integration, and AI-assisted risk prediction. Current challenges and emerging therapeutic approaches, including RNA-based therapies and gene editing, are also discussed. RESULTS: Clinical genomic tools are increasingly being incorporated into the evaluation of inherited cardiac conditions. PRS can identify individuals with elevated lifelong CVD risk, although their current clinical utility is primarily as risk-enhancing markers rather than standalone diagnostic tests. Integration of genomic, clinical, imaging, and biomarker data using AI may further improve risk prediction and personalized treatment selection. However, ancestry bias, uncertainty in variant interpretation, limited accessibility, workflow integration barriers, and ethical and privacy concerns remain important challenges. CONCLUSIONS: Genomic cardiology has substantial potential to advance precision cardiovascular medicine. Continued development of diverse genomic databases, standardized clinical implementation frameworks, and emerging genomic therapies will be important for translating genomic advances into equitable and clinically meaningful cardiovascular care.
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Mohsen-Pour et al. (2026) conducted a review in Cardiovascular diseases. Genomic cardiology tools was evaluated. Genomic cardiology tools, including polygenic risk scores and sequencing, show potential to enhance cardiovascular risk stratification, though ancestry bias and integration barriers remain.
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