Integrating omics for an improved understanding of cardiac diseases

Abstract

Atrial fibrillation (AF) and heart failure (HF) are diseases affecting approximately 60 million people worldwide each. AF patients suffer from an irregular heartbeat and HF patients experience a loss of pump function. Pharmacological treatments of AF, HF, and related heart muscle diseases (cardiomyopathies) focus predominantly on symptom relief and a more favourable prognosis, while prevention and treatment of underlying causes should be targeted. We searched for genes, proteins, and metabolites related to AF, HF, and cardiomyopathies, because perturbations in genes and proteins contribute to cardiac diseases and dysfunctional energy metabolism fails to meet the high energy demands of the heart to provide the body with blood, which weakens the heart. Indeed, we identified new and confirmed known associations. The findings not only deepen our understanding of cardiac diseases but also provide actionable leads for drug development and personalised therapeutics by pinpointing which drugs target these genes and proteins. Additionally, we evaluated pathogenic genetic variants in the general population, observing many healthy participants carry these variants associated with the inherited cardiomyopathies. Clustering HF patients using proteins, resulted in three subgroups with different rates of progression, which help identify patients in need of timely intervention. These studies show that the integration of data on genes, proteins, and metabolites reflects a promising trend in cardiovascular research, paving the way for more targeted therapeutics. As technology advances and datasets expand, knowledge on pathogenicity can be reevaluated and future studies will elucidate even more mechanisms contributing to cardiac disease, ultimately leading to improved clinical care.