Connecting transcriptomics with computational modeling to reveal developmental adaptations in pediatric human atrial tissue.

Nearly 1% of babies are born with congenital heart disease-many of whom will require heart surgery within the first few years of life. A detailed understanding of cardiac maturation can help to expand our knowledge on cardiac diseases that develop during gestation, identify age-appropriate drug therapies, and inform clinical care decisions related to surgical repair and postoperative management. Yet, to date, our knowledge of the temporal changes that cardiomyocytes undergo during postnatal development is limited. In this study, we collected right atrial tissue samples from pediatric patients ( = 117) undergoing heart surgery. Patients were stratified into five age groups. We measured age-dependent adaptations in cardiac gene expression and used computational modeling to simulate action potential and calcium transients. Enrichment of differentially expressed genes revealed age-dependent changes in several key biological processes (e.g., cell cycle, structural organization), cardiac ion channels, and calcium handling genes. Gene-associated changes in ionic currents exhibited age-dependent trends, with changes in calcium handling () and repolarization () most strongly associated with an age-dependent decrease in the action potential plateau potential and increase in triangulation, respectively. We observed a shift in repolarization reserve, with lower expression in younger patients, a finding potentially tied to an increased amplitude of that could be triggered by elevated sympathetic activation in pediatric patients. Collectively, this study provides valuable insights into age-dependent changes in human cardiac gene expression and electrophysiology, shedding light on molecular mechanisms underlying cardiac maturation and function throughout development. To date, our knowledge of the temporal changes that cardiomyocytes undergo during postnatal development is limited. In this study, we demonstrate age-dependent adaptations in the gene expression profile of >100 atrial tissue samples collected from congenital heart disease patients. We coupled transcriptomics datasets with computational modeling to simulate action potentials and calcium transients for different pediatric age groups.