Blanca Rodriguez

BACKGROUND: Mechanistic cardiac simulations are increasingly used in research, pharmaceutical development, and regulatory science, yet most existing human cardiomyocyte models lack the generality required for predictive translation across scales. Our recently developed T-World model overcomes this barrier by reproducing all major cellular arrhythmia mechanisms and showing comprehensive agreement with experimental and clinical data. Here, we aimed to demonstrate the utility of T-World for organ-level and translational research, from ionic mechanisms of arrhythmogenesis to emergent whole-heart physiology. METHODS: T-World was embedded into anatomically realistic models of biventricular electrophysiology and electromechanics derived from clinical imaging for organ-scale simulations. Drug safety was assessed using populations-of-single-cell models exposed to 60 compounds with updated CredibleMeds annotations. Mechanistic drug-efficacy studies on mexiletine were conducted using long QT syndrome type 2 model variants. Disease applications included arrhythmia mechanisms in human type 2 diabetes and the proarrhythmic potential of Na _V 1.8, a neuronal sodium channel ectopically expressed in cardiac disease. RESULTS: T-World reproduced human-like ECG morphology and ventricular mechanics (ejection fraction of 61%) and generated ventricular fibrillation under physiologically relevant ischemic conditions without parameter tuning. In the drug safety assessment of torsadogenic risk, T-World achieved 87% accuracy and 100% specificity, and exposed incomplete pharmacological descriptions based on in vitro measurements for lidocaine and cilostazol. Mexiletine simulations revealed that both I _NaL and I _CaL inhibition underlie its antiarrhythmic benefit in long QT syndrome type 2. Cellular simulations of type 2 diabetes remodeling explained heightened vulnerability to early afterdepolarizations and increased risk of alternans associated with diastolic dysfunction, mechanistically linked to SERCA (sarco/endoplasmic reticulum Ca ²⁺ ATPase) reduction. Finally, even minor expression of Na _V 1.8 can directly trigger early afterdepolarizations through uniquely right-shifted activation and inactivation properties. CONCLUSIONS: T-World provides a unified, human-specific open-source platform bridging cellular mechanisms with organ-level dynamics and translational outcomes. Its predictive performance across arrhythmia, contraction, drug safety/mechanisms, and disease physiology makes it a powerful tool for multiscale cardiac research, therapeutic discovery, and next-generation cardiac digital twins.

BACKGROUND: Cardiovascular disease is the leading global cause of morbidity and mortality. New technologies are needed to improve mechanistic understanding and inform therapeutic strategies. Human-centric cardiac simulations show great promise; however, existing cellular models can reproduce only a few arrhythmia-driving behaviors and show important discrepancies with experimental data. We aimed to develop a new model overcoming this lack of generality, which markedly limits the predictivity and translational utility of virtual cardiomyocytes. METHODS: We developed T-World, a novel virtual human cardiomyocyte, using data-driven differential equations to describe sex-specific excitation-contraction coupling, mechanical contraction, β-adrenergic signaling, and its effects on cellular targets. The model contains several key innovations, including a new approach to coupling L-type calcium channels and ryanodine receptors, with updated calcium-dependent-inactivation of the former and novel calcium-induced refractoriness and complete reparameterization of the latter. We also redeveloped the sodium-potassium pump and made major improvements to the sodium-calcium exchanger formulation. RESULTS: T-World shows broad agreement with experimental data on rate-dependent action potential (AP), calcium handling, and contraction properties. Extensively validated on independent data, T-World demonstrates strong predictive performance, for example, in drug-induced AP changes. The model reproduces the effects of sympathetic stimulation, including AP duration shortening and increased calcium-transient amplitude and contractility. Importantly, it recapitulates for the first time all key cellular mechanisms driving life-threatening arrhythmias (early and delayed afterdepolarizations, alternans, and steep S1-S2 restitution), including experimentally observed responses to interventions such as sympathetic activation, SERCA (sarco/endoplasmic reticulum Ca ²⁺ ATPase) inhibition, and AP prolongation. Combined with the model’s ability to simulate physiological sex-specific differences in electrophysiology, this revealed increased proclivity of female cardiomyocytes to early afterdepolarizations and steep restitution of AP duration. CONCLUSIONS: T-World is a highly general and predictive open-source computer model of a human ventricular cardiomyocyte, suitable for multiscale research studies investigating determinants of arrhythmogenesis.

Type 2 diabetes is a highly prevalent metabolic disease that significantly impacts the heart and contributes to an increased risk of cardiac complications, notably heart failure with preserved ejection fraction and cardiac arrhythmias, which can cause sudden cardiac death. In type 2 diabetes chronic hyperglycaemia and insulin resistance lead to subcellular changes, including dysregulation of calcium/calmodulin‐dependent protein kinase II (CaMKII), intracellular sodium and calcium handling and potassium currents, all of which impair cardiac contractility and repolarisation. Type 2 diabetes induces diffuse myocardial fibrosis and anatomical remodelling, which contribute to diastolic and systolic dysfunction, and the formation of a pro‐arrhythmic substrate. Impaired connexin 43‐mediated conduction and cardiac autonomic neuropathy further promote cardiac electrophysiological and mechanical dysfunction. Clinical studies using the ECG and cardiac imaging modalities have been successful in detecting some of these changes; however our mechanistic understanding of type 2 diabetes‐driven cardiac disorders remains limited. Recent advances in multiscale computational modelling and simulation of human cardiac electrophysiology and mechanics provide new opportunities to study diabetes‐induced cardiac remodelling in silico by unravelling disease mechanisms across different scales and assisting in the development of novel therapies. Here we review key pathophysiological mechanisms of electrophysiological, structural and nervous cardiac remodelling in type 2 diabetes; their clinical implications; and the cardiac effects of common glucose‐lowering pharmacological agents commonly taken by diabetes patients. We discuss the potential of human‐based computational cardiac modelling and simulation in this context to deepen our mechanistic understanding, and guide more precise prevention and treatment of diabetes‐driven cardiac arrhythmias and diastolic dysfunction. image

The electrocardiogram (ECG) is modulated by torso-heart anatomy, and this challenges patients' diagnosis and risk stratification. This study aims to quantify how torso-heart anatomical factors affect sex-differences in ECG biomarkers in acute and chronic myocardial infarction (MI). We exploit the perfect control of AI-augmented multiscale modelling and simulation, based on clinical magnetic resonance imaging (MRI) data and ECGs for model construction and validation. A cohort of 1720 torso-ventricular anatomies (50% female) was constructed from MRIs of healthy and post-MI participants in the UK Biobank study. 8600 ECG simulations were performed considering anatomical variability and 3 electrophysiological stages (healthy, acutely ischemic, and infarcted). The effect of cardiac size, position, and orientation on each ECG biomarker was quantified. Female anatomies had larger distances between the infarct and ECG electrodes (relative to cardiac size), and larger angles between the infarct normal and ECG lead axes, both primarily caused by their more superior cardiac position. This reduced ST-elevation and caused low-amplitude late depolarisation and repolarisation tails to be missed, shortening QRS duration (QRSd) and T-peak-to-end interval (TpTe). The position and orientation of the heart impacted TpTe more severely than QRSd. AI-enabled mechanistic modelling and simulation identify smaller ventricles, superior cardiac position, and different ventricular orientation as key anatomical contributors of shorter QRS and T waves, and lower ST-elevation, in female versus male anatomies. This provides a blueprint for quantifying the impact of anatomical sex differences on functional markers and enables future work in tailoring clinical guidelines considering unique patient anatomy to reduce biased outcomes.

BACKGROUND: Fabry disease (FD) is an X-linked lysosomal storage disorder caused by α-Gal A (α-galactosidase A) deficiency, resulting in multiorgan accumulation of sphingolipid, namely globotriaosylceramide. This triggers ventricular myocardial hypertrophy, fibrosis, and inflammation, driving arrhythmia and sudden death. Atrial fibrillation is common, yet the cellular mechanisms accounting for this are unknown. METHODS: To address this, we conducted ECG analysis from a large cohort of 115 adults with FD at varying cardiomyopathy stages. ECG P-wave characteristics were compared with non-FD controls. Cellular contractile and electrophysiological function were examined in a novel atrial cellular FD model developed and imputed into in silico atrial models to provide insight into mechanisms of arrhythmia. Induced pluripotent stem cells were genome-edited using Clustered Regularly Interspaced Short Palindromic Repeats-Cas9 to introduce the GLA p. N215S variant and differentiated into induced pluripotent stem cell-derived atrial cardiomyocytes (iPSC-CMs). Contraction, calcium handling, and electrophysiology experiments were conducted. Bi-atrial in silico models were developed with cellular changes as in GLA p. N215S iPSC-CMs. RESULTS: ECG analysis demonstrated P-wave duration and PQ interval shortening in FD adults before the onset of cardiomyopathy. Patients with FD exhibited a higher incidence of premature atrial contractions and increased risk of atrial fibrillation compared with healthy controls. GLA p. N215S iPSC-CMs were deficient in α-Gal A and exhibited globotriaosylceramide accumulation. Atrial GLA p. N215S iPSC-CMs demonstrated a more positive diastolic membrane potential, faster action potential upstroke velocity, greater incidence of delayed afterdepolarizations, greater contraction force, and alterations in calcium handling compared with wild-type iPSC-CMs. Simulations with these changes in the in silico models resulted in similar P-wave morphology changes to those seen in early FD cardiomyopathy and increased atrial fibrillation vulnerability. CONCLUSIONS: These findings provide novel insights into underpinning mechanisms for atrial arrhythmia and a rationale for early P-wave changes in FD. These may be targeted to develop therapeutic strategies to reduce the arrhythmic burden in FD.

Background: Cardiometabolic disturbances play a central role in the pathogenesis of heart failure with preserved ejection fraction (HFpEF). Due to its complexity, HFpEF is a challenging condition to treat, making phenotype-specific disease management a promising approach. However, HFpEF phenotypes are heterogenous and there is a lack of detailed evidence on the different, sex-specific profiles of cardiometabolic multimorbidity and metabolic syndrome present in HFpEF. Methods: We performed a retrospective, modified cross-sectional study examining a subset of participants in the UK Biobank, an ongoing multi-centre prospective cohort study in the United Kingdom. We defined HFpEF as a record of a heart failure diagnosis using ICD-10 code I50, coupled with a left ventricular ejection fraction (LVEF) ≥ 50% derived from cardiac magnetic resonance (CMR) imaging. We examined sex-specific differences in cardiometabolic comorbidity burden and metabolic syndrome, performed latent class analysis (LCA) to identify distinct clusters of patients based on their cardiometabolic profile, and compared CMR imaging-derived parameters of left ventricular function at rest in the different clusters identified to reflect possible differences in adverse cardiac remodelling. Results: We ascertained HFpEF in 445 participants, of which 299 (67%) were men and 146 (33%) women. The median age was 70 years old (interquartile range: [66.0–74.0]). A combination of hypertension and obesity was the most prevalent cardiometabolic pattern both in men and women with HFpEF. Most men had 2–3 clinical cardiometabolic comorbidities while most women had 1–2, despite a similar metabolic syndrome profile (p = 0.05). LCA revealed three distinct, clinically relevant phenogroups, namely (1) a most male and multimorbid group (n = 117); (2) a group with a high prevalence of severe obesity, abnormal waist circumference and with the highest relative proportion of females (n = 116); and finally (3) a group with an apparently lower comorbidity burden aside from hypertension (n = 212). There were significant differences in clinical measurements and medication across the three phenogroups identified. Cardiac output at rest was significantly higher in group 2 vs. group 3 (males: median 5.6 L/min vs. 5.2 L/min, p < 0.05; females: 5.1 L/min vs. 4.4 L/min, p < 0.01). Absolute global longitudinal strain was significantly lower in women in group 1 vs. group 2 (−17.6% vs. −18.5%, p < 0.05). Conclusion: Women with cardiometabolic HFpEF had a lower comorbidity burden compared to men despite a similar metabolic syndrome profile. Based on patients’ cardiometabolic profile, we identified three distinct subgroups which differed in body shape and mass, lipid biomarker and medication profile, as well as in cardiac output at rest both in men and women. These factors may affect disease trajectory, treatment options and outcomes in those subgroups. Subject to further validation, our findings provide a refined characterisation of the cardiometabolic HFpEF phenotype, contributing towards a better understanding of the condition to enable phenotype-specific disease management. Graphical

Modelling and simulation are essential in biomedicine, and specifically in computational cardiology. Reliable, efficient and accurate solvers are critical. This study presents an open source, GPU-based cardiac electrophysiology solver for scalable digital twin multiscale simulations (M ono A lg 3D), incorporating conduction system calibration and performance optimization. The solver employs the monodomain equation coupled with the Purkinje network, solved via the finite volume method, featuring a GPU-based linear solver and concurrent simulation dispatch with MPI. We demonstrate a 10.94× speedup over a CPU-based solution and scalability by running 512 simulations on 128 compute nodes, completing all coarse-mesh simulations in less than 24 minutes and fine-mesh simulations in 303 minutes. We also demonstrate integration into a cardiac digital twin pipeline for personalisation based on clinical data. The proposed open source solver enhances computational efficiency and physiological fidelity, enabling large-scale, high-speed cardiac simulations. This work marks a significant step toward fast and scalable cardiac simulations on GPU architectures, with integration in a Digital Twin personalisation pipeline including the conduction system.