Sex‐specific Computational Models for Blood Pressure Regulation in the Rat

Abstract

Renal hemodynamics play a critical role in blood pressure regulation, while renal autoregulatory mechanisms maintain kidney function for varying blood pressure. Computational models have been developed of the cardiovascular system to simulate blood pressure regulation in humans, including the seminal model by Guyton et al. (Ann Rev Physiol 1972). Although the Guyton model and its many variants represent mechanisms for renal autoregulation, they appear to fail to adequately maintain glomerular filtration rate for a sufficiently wide range of blood pressure. Additionally, while such human models have clinical values in that they can be used to assess the effects and reveal mechanisms of hypertensive therapeutic treatments, rodent models would be more useful in assisting the interpretation of animal experiments. Finally, despite well‐known sexual dimorphism in blood pressure regulation, all published models are gender neutral Given these observations, the goal of this project is to develop the first sex‐specific computational models of blood pressure regulation for the rat. The resulting models represent the interplay between cardiovascular function, renal hemodynamics, and kidney function. They also include the actions of the renal sympathetic nerve activity and the renin‐angiotensin‐aldosterone system. We applied the models to investigate the cardiovascular effects of antihypertensive treatments including diuretics, angiotensin converting enzyme (ACE) inhibitors, and angiotensin receptor blocker (ARB), and of nonsteroidal anti‐inflammatory drugs (NSAIDs). Simulations were conducted to identify risks factors for acute kidney injury following the administration of a combination of these treatments.Support or Funding InformationThis research was supported by the Canada 150 Research Chair program and by the National Institutes of Health: National Institute of Diabetes and Digestive and Kidney Diseases, grant R01DK106102.This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.