PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 21, 2026Biophysical Journal0 citations

BPS2026 – Computational modeling of pediatric atrial electrophysiology: Age-dependent biomarkers and the role of patient-specific heart rates

View Full Paper
GEGabriella M. EllksDGDevon GuerrelliSSShatha Salameh

Key Points

  • The study aims to characterize age-dependent electrophysiological properties in pediatric patients, considering individual heart rates.
  • Utilized computational modeling based on gene expression data from 117 pediatric patients.
  • Simulated patient-specific heart rates using Morotti human atrial myocyte model.
  • Analyzed age and heart rate-specific changes in action potentials and calcium transients.
  • Younger groups demonstrated shorter action potential durations and slower upstroke velocities.
  • Observed smaller calcium transients and less triangular shaped action potentials in younger patients.
  • Electrophysiological biomarkers altered significantly with age and heart rates.

Abstract

During pediatric development, cardiomyocyte maturation alters excitation-contraction coupling, ion channel expression, and intercalated disc formation, significantly influencing action potentials and calcium transients. While developmental shifts are recognized, the progression of these electrophysiological properties through early life lacks comprehensive characterization, despite their relevance to pediatric treatment, drug therapies, and surgical procedures. Our prior work using computational modeling has uncovered age-dependent changes in cardiac electrophysiology and mechanisms of maturation. Prior simulations based on gene expression data from pediatric atrial tissue ( n = 117) reproduced critical changes in action potentials (APs) and calcium transients (CaTs) characteristics. Significant prior work has established rate-dependent changes in cardiac APs and CaTs; however, our initial work did not account for patient-specific heart rates, known to generally decrease with age. This study builds on our prior work by examining the role of individualized heart rates in influencing age-dependent trends in cardiac electrophysiological dynamics. We use a previously generated physiological population based on gene expression of 117 pediatric patients (age: 5 days, 32 years), with each patient represented by a population of 155 control cells (accounting for inherent variability) and thus resulting in a total 18,135 cells, and simulated each patient-specific cell with patient-specific (ECG-based) heart rate using the Morotti human atrial myocyte model. We analyzed AP and CaT biomarkers, statistical trends, and alternans presence by age and heart rate groups. Age- and heart rate-specific simulations predict that the younger groups exhibit shorter AP duration, slower upstroke velocity, smaller CaTs, and less triangular shaped APs, consistent with immature on channel expression and calcium handling. Our work reveals that electrophysiological biomarkers change with development and heart rate and ultimately seeks to advance our understanding of developmental electrophysiology and improve the precision of pediatric cardiac care.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Ellks et al. (2026) studied this question.

synapsesocial.com/papers/69990df65b97ab4c14ac2c1bhttps://doi.org/10.1016/j.bpj.2025.11.1285
Ask AI
Helpful
Bookmark
Share
View Full Paper