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Published on: November 29, 2024
Cardiac remodelling in type 2 diabetes: Pathophysiological mechanisms and opportunities for multiscale computational
Ambre Bertrand1, Jakub Tomek2, Blanca Rodriguez1
1Department of Computer Science, University of Oxford, Oxford, UK.
Abstract:
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.
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