Computational modelling of myocardial metabolism in patients with advanced heart failure.
Beyhoff N., Braun VM., Kirchner M., Finnigan LEM., Knosalla C., Baczkó I., Potapov E., Kintscher U., Grune T., Kuehne T., Holzhütter H-G., Mertins P., Tyler DJ., Milting H., Raman B., Rider OJ., Neubauer S., Berndt N.
AIMS: Perturbations of myocardial metabolism and energy depletion are well-established hallmarks of heart failure (HF), yet methods for their systematic assessment remain limited in humans. This study aimed to determine the ability of computational modelling of patient-specific myocardial metabolism to assess individual bioenergetic phenotypes and their clinical implications in HF. METHODS AND RESULTS: Based on proteomics-derived enzyme quantities in 136 cardiac biopsies, personalized computational models of myocardial metabolism were generated in two independent cohorts of advanced HF patients together with sex- and body mass index-matched non-failing controls. The bioenergetic impact of dynamic changes in substrate availability and myocardial workload were simulated, and the models' ability to predict the myocardial response following left ventricular assist device (LVAD) implantation was assessed. Compared to controls, HF patients had a reduced ATP production capacity (p