Quantifying the integrated physiological effects of endothelin-1 on cardiovascular and renal function in healthy subjects: a mathematical modeling analysis.

Endothelin-1 (ET-1) is a potent vasoconstrictor with strong anti-natriuretic and anti-diuretic effects. While many experimental studies have elucidated the mechanisms of ET-1 through its two receptors, ETA and ETB, the complexity of responses and sometimes conflicting data make it challenging to understand the effects of ET-1, as well as potential therapeutic antagonism of ET-1 receptors, on human physiology. In this study, we aimed to develop an integrated and quantitative description of ET-1 effects on cardiovascular and renal function in healthy humans by coupling existing experimental data with a mathematical model of ET-1 kinetics and an existing mathematical model of cardiorenal function. Using a novel agnostic and iterative approach to incorporating and testing potential mechanisms, we identified a minimal set of physiological actions of endothelin-1 through ETA and ETB receptors by fitting the physiological responses (changes in blood pressure, renal blood flow, glomerular filtration rate (GFR), and sodium/water excretion) to ET-1 infusion, with and without ETA/ETB antagonism. The identified mechanisms align with previous experimental studies on ET-1 and offer novel insights into the relative magnitude and significance of endothelin's effects. This model serves as a foundation for further investigating the mechanisms of ET-1 and its antagonists.

Understanding heterogeneous mechanisms of heart failure with preserved ejection fraction through cardiorenal mathematical modeling.

In contrast to heart failure (HF) with reduced ejection fraction (HFrEF), effective interventions for HF with preserved ejection fraction (HFpEF) have proven elusive, in part because it is a heterogeneous syndrome with incompletely understood pathophysiology. This study utilized mathematical modeling to evaluate mechanisms distinguishing HFpEF and HFrEF. HF was defined as a state of chronically elevated left ventricle end diastolic pressure (LVEDP > 20mmHg). First, using a previously developed cardiorenal model, sensitivities of LVEDP to potential contributing mechanisms of HFpEF, including increased myocardial, arterial, or venous stiffness, slowed ventricular relaxation, reduced LV contractility, hypertension, or reduced venous capacitance, were evaluated. Elevated LV stiffness was identified as the most sensitive factor. Large LV stiffness increases alone, or milder increases combined with either decreased LV contractility, increased arterial stiffness, or hypertension, could increase LVEDP into the HF range without reducing EF. We then evaluated effects of these mechanisms on mechanical signals of cardiac outward remodeling, and tested the ability to maintain stable EF (as opposed to progressive EF decline) under two remodeling assumptions: LV passive stress-driven vs. strain-driven remodeling. While elevated LV stiffness increased LVEDP and LV wall stress, it mitigated wall strain rise for a given LVEDP. This suggests that if LV strain drives outward remodeling, a stiffer myocardium will experience less strain and less outward dilatation when additional factors such as impaired contractility, hypertension, or arterial stiffening exacerbate LVEDP, allowing EF to remain normal even at high filling pressures. Thus, HFpEF heterogeneity may result from a range of different pathologic mechanisms occurring in an already stiffened myocardium. Together, these simulations further support LV stiffening as a critical mechanism contributing to elevated cardiac filling pressures; support LV passive strain as the outward dilatation signal; offer an explanation for HFpEF heterogeneity; and provide a mechanistic explanation distinguishing between HFpEF and HFrEF.

A quantitative systems pharmacology model of plasma potassium regulation by the kidney and aldosterone.

Plasma potassium regulation within a narrow range is vital for life. The risk for hyperkalemia increases when kidney function is impaired and with therapeutic interventions such as mineralocorticoid receptor antagonists (MRAs). The kidney maintains potassium homeostasis by matching potassium intake and excretion, in part through the action of aldosterone. A mechanistic mathematical model was developed and used to investigate the effect of renal impairment and MRAs on plasma potassium levels. The model describes renal potassium filtration, reabsorption, and secretion along the nephron; potassium-aldosterone regulatory feedbacks; whole body potassium balance; and the pharmacologic effects of MRAs. The model was calibrated by fitting (1) the plasma potassium and aldosterone response to potassium infusion in humans on high/low potassium diets, and (2) the acute potassium excretion response to spironolactone. The model was validated by predicting steady-state plasma potassium with sustained spironolactone treatment in hyperaldosteronism patients. The model was then used to demonstrate that (1) declining renal function alone has a small effect on plasma potassium for GFR > 30 ml/min, but an increasing effect as GFR approaches end stage renal disease (GFR ~ 15 ml/min) (2) the effect of increasing potassium intake has minimal effect at normal GFRs but increasing effect on plasma potassium as GFR declines, and 3) MRAs have a minor effect on plasma potassium when GFR is normal, but cause larger increases as GFR falls below 60 ml/min. This model provides a quantitative framework for investigating integrated impacts of diseases and therapies in this complex system.

Predicted Cardiac Functional Responses to Renal Actions of SGLT2i in the DAPACARD Trial Population: A Mathematical Modeling Analysis.

Sodium-glucose cotransporter-2 inhibitors (SGLT2is) have been shown to reduce the risk of worsening heart failure (HF) in subjects with HF and a reduced ejection fraction (HFrEF) in multiple clinical trials. The DAPACARD clinical trial was conducted to examine the effects of dapagliflozin on cardiac substrate uptake, myocardial efficiency, and myocardial contractile work in subjects with type 2 diabetes mellitus. As a complement to the clinical study, a mechanistic mathematical model of cardiorenal physiology was used to quantify the influence of established natriuretic/diuretic effects of SGLT2i on cardiac function (myocardial efficiency and global longitudinal strain). Virtual participants reflecting the participant-level characteristics in the DAPACARD trial were produced by varying model parameters over physiologically plausible ranges. A second virtual population was generated by inducing a state of HFrEF in the DAPACARD virtual participants with type 2 diabetes mellitus for comparison. Cardiac responses to placebo and SGLT2i were simulated over 42 days. Cardiac hemodynamic improvements were predicted in DAPACARD-HFrEF virtual participants but not in DAPACARD virtual participants. In particular, the natriuresis/diuresis induced by SGLT2i improved the global longitudinal strain and myocardial efficiency in DAPACARD-HFrEF virtual participants within the first 14 days (change from baseline: global longitudinal strain, -0.95%; and myocardial efficiency, 0.34%), whereas the global longitudinal strain and myocardial efficiency in DAPACARD virtual participants were slightly worse (change from baseline: global longitudinal strain, 0.35%; and myocardial efficiency: -0.01%). The results of the DAPACARD virtual participants modeling were in line with the clinical data but do not preclude additional effects from other mechanisms of SGLT2i.

Cardiorenal Systems Modeling: Left Ventricular Hypertrophy and Differential Effects of Antihypertensive Therapies on Hypertrophy Regression.

Cardiac and renal function are inextricably connected through both hemodynamic and neurohormonal mechanisms, and the interaction between these organ systems plays an important role in adaptive and pathophysiologic remodeling of the heart, as well as in the response to renally acting therapies. Insufficient understanding of the integrative function or dysfunction of these physiological systems has led to many examples of unexpected or incompletely understood clinical trial results. Mathematical models of heart and kidney physiology have long been used to better understand the function of these organs, but an integrated model of renal function and cardiac function and cardiac remodeling has not yet been published. Here we describe an integrated cardiorenal model that couples existing cardiac and renal models, and expands them to simulate cardiac remodeling in response to pressure and volume overload, as well as hypertrophy regression in response to angiotensin receptor blockers and beta-blockers. The model is able to reproduce different patterns of hypertrophy in response to pressure and volume overload. We show that increases in myocyte diameter are adaptive in pressure overload not only because it normalizes wall shear stress, as others have shown before, but also because it limits excess volume accumulation and further elevation of cardiac stresses by maintaining cardiac output and renal sodium and water balance. The model also reproduces the clinically observed larger LV mass reduction with angiotensin receptor blockers than with beta blockers. We further provide a mechanistic explanation for this difference by showing that heart rate lowering with beta blockers limits the reduction in peak systolic wall stress (a key signal for myocyte hypertrophy) relative to ARBs.

Predicted Cardiac Hemodynamic Consequences of the Renal Actions of SGLT2i in the DAPA-HF Study Population: A Mathematical Modeling Analysis.

The Dapagliflozin and Prevention of Adverse Outcomes in Heart Failure (DAPA-HF) study demonstrated that dapagliflozin, a sodium-glucose cotransporter-2 inhibitor (SGLT2i), reduced heart failure hospitalization and cardiovascular death in patients with heart failure with reduced ejection fraction (HF-rEF), with and without type 2 diabetes mellitus. Multiple potential mechanisms have been proposed to explain this benefit, which may be multifactorial. This study aimed to quantify the contribution of the known natriuretic/diuretic effects of SGLT2is to changes in cardiac hemodynamics, remodeling, and fluid homeostasis in the setting of HF-rEF. An integrated cardiorenal mathematical model was used to simulate inhibition of SGLT2 and its consequences on cardiac hemodynamics in a virtual population of HF-rEF patients generated by varying model parameters over physiologically plausible ranges and matching to baseline characteristics of individual DAPA-HF trial patients. Cardiovascular responses to placebo and SGLT2i over time were then simulated. The baseline characteristics of the HF-rEF virtual population and DAPA-HF were in good agreement. SGLT2i-induced diuresis and natriuresis that reduced blood volume and interstitial fluid volume, relative to placebo within 14 days. This resulted in decreased left ventricular end-diastolic volume and pressure, indicating reduced cardiac preload. Thereafter, blood volume and interstitial fluid volume again began to accumulate, but pressures and volumes remained shifted lower relative to placebo. After 1 year, left ventricle mass was lower and ejection fraction was higher than placebo. These simulations considered only hemodynamic consequences of the natriuretic/diuretic effects of SGLT2i, as other mechanisms may contribute additional benefits besides those predictions.

Renal Effects of Dapagliflozin in People with and without Diabetes with Moderate or Severe Renal Dysfunction: Prospective Modeling of an Ongoing Clinical Trial.

Sodium glucose cotransporter 2 inhibitors (SGLT2i) reduce cardiovascular events and onset and progression of renal disease by mechanisms that remain incompletely understood but may include clearance of interstitial congestion and reduced glomerular hydrostatic pressure. The ongoing DAPASALT mechanistic clinical study will evaluate natriuretic, diuretic, plasma/extracellular volume, and blood pressure responses to dapagliflozin in people with type 2 diabetes with normal or impaired renal function (D-PRF and D-IRF, respectively) and in normoglycemic individuals with renal impairment (N-IRF). In this study, a mathematical model of renal physiology, pathophysiology, and pharmacology was used to prospectively predict changes in sodium excretion, blood and interstitial fluid volume (IFV), blood pressure, glomerular filtration rate, and albuminuria in DAPASALT. After validating the model with previous diabetic nephropathy trials, virtual patients were matched to DAPASALT inclusion/exclusion criteria, and the DAPASALT protocol was simulated. Predicted changes in glycosuria, blood pressure, glomerular filtration rate, and albuminuria were consistent with other recent studies in similar populations. Predicted albuminuria reductions were 46% in D-PRF, 34.8% in D-IRF, and 14.2% in N-IRF. The model predicts a similarly large IFV reduction between D-PRF and D-IRF and less, but still substantial, IFV reduction in N-IRF, even though glycosuria is attenuated in groups with impaired renal function. When DAPASALT results become available, comparison with these simulations will provide a basis for evaluating how well we understand the cardiorenal mechanism(s) of SGLT2i. Meanwhile, these simulations link dapagliflozin's renal mechanisms to changes in IFV and renal biomarkers, suggesting that these benefits may extend to those with impaired renal function and individuals without diabetes. SIGNIFICANCE STATEMENT: Mechanisms of SGLT2 inhibitors' cardiorenal benefits remain incompletely understood. We used a mathematical model of renal physiology/pharmacology to prospectively predict responses to dapagliflozin in the ongoing DAPASALT study. Key predictions include similarly large interstitial fluid volume (IFV) reductions between subjects with normal and impaired renal function and less, but still substantial, IFV reduction in those without diabetes, even though glycosuria is attenuated in these groups. Comparing prospective simulations and study results will assess how well we understand the cardiorenal mechanism(s) of SGLT2 inhibitors.

Cardiac and renal function interactions in heart failure with reduced ejection fraction: A mathematical modeling analysis.

Congestive heart failure is characterized by suppressed cardiac output and arterial filling pressure, leading to renal retention of salt and water, contributing to further volume overload. Mathematical modeling provides a means to investigate the integrated function and dysfunction of heart and kidney in heart failure. This study updates our previously reported integrated model of cardiac and renal functions to account for the fluid exchange between the blood and interstitium across the capillary membrane, allowing the simulation of edema. A state of heart failure with reduced ejection fraction (HF-rEF) was then produced by altering cardiac parameters reflecting cardiac injury and cardiovascular disease, including heart contractility, myocyte hypertrophy, arterial stiffness, and systemic resistance. After matching baseline characteristics of the SOLVD clinical study, parameters governing rates of cardiac remodeling were calibrated to describe the progression of cardiac hemodynamic variables observed over one year in the placebo arm of the SOLVD clinical study. The model was then validated by reproducing improvements in cardiac function in the enalapril arm of SOLVD. The model was then applied to prospectively predict the response to the sodium-glucose co-transporter 2 (SGLT2) inhibitor dapagliflozin, which has been shown to reduce heart failure events in HF-rEF patients in the recent DAPAHF clinical trial by incompletely understood mechanisms. The simulations predict that dapagliflozin slows cardiac remodeling by reducing preload on the heart, and relieves congestion by clearing interstitial fluid without excessively reducing blood volume. This provides a quantitative mechanistic explanation for the observed benefits of SGLT2i in HF-rEF. The model also provides a tool for further investigation of heart failure drug therapies.

Erratum: Publisher Correction: Mathematical model of hemodynamic mechanisms and consequences of glomerular hypertension in diabetic mice.

[This corrects the article DOI: 10.1038/s41540-018-0077-9.].

Benchmarking renin suppression and blood pressure reduction of direct renin inhibitor imarikiren through quantitative systems pharmacology modeling.

Multiple classes of antihypertensive drugs inhibit components of the renin-angiotensin-aldosterone system (RAAS). The primary physiological effector of the RAAS is angiotensin II (AngII) bound to the AT1 receptor (AT1-bound AngII). There is a strong non-linear feedback from AT1-bound AngII on renin secretion. Since AT1-bound AngII is not readily measured experimentally, plasma renin concentration (PRC) and/or activity (PRA) are typically measured to indicate RAAS suppression. We investigated the RAAS suppression of imarikiren hydrochloride (TAK-272; SCO-272), a direct renin inhibitor currently under clinical development. We employed a previously developed quantitative system pharmacology (QSP) model to benchmark renin suppression and blood pressure regulation with imarikiren compared to other RAAS therapies. A pharmacokinetic (PK) model of imarikiren was linked with the existing QSP model, which consists of a mechanistic representation of the RAAS pathway coupled with a model of blood pressure regulation and volume homeostasis. The PK and pharmacodynamic effects of imarikiren were calibrated by fitting drug concentration, PRA, and PRC data, and trough AT1-bound AngII suppression was simulated. We also prospectively simulated expected mean arterial pressure reduction in a cohort of hypertensive virtual patients. These predictions were benchmarked against predictions for several other (previously calibrated) RAAS monotherapies and dual-RAAS therapies. Our analysis indicates that low doses (5-10 mg) of imarikiren are comparable to current RAAS therapies, and at higher doses (25-200 mg), RAAS suppression may be equivalent to existing dual-RAAS combinations (at registered doses). This study illustrates application of QSP modeling to predict phase II endpoints from phase I data.

Mathematical model of hemodynamic mechanisms and consequences of glomerular hypertension in diabetic mice.

Many preclinically promising therapies for diabetic kidney disease fail to provide efficacy in humans, reflecting limited quantitative translational understanding between rodent models and human disease. To quantitatively bridge interspecies differences, we adapted a mathematical model of renal function from human to mice, and incorporated adaptive and pathological mechanisms of diabetes and nephrectomy to describe experimentally observed changes in glomerular filtration rate (GFR) and proteinuria in db/db and db/db UNX (uninephrectomy) mouse models. Changing a small number of parameters, the model reproduced interspecies differences in renal function. Accounting for glucose and Na+ reabsorption through sodium glucose cotransporter 2 (SGLT2), increasing blood glucose and Na+ intake from normal to db/db levels mathematically reproduced glomerular hyperfiltration observed experimentally in db/db mice. This resulted from increased proximal tubule sodium reabsorption, which elevated glomerular capillary hydrostatic pressure (P gc) in order to restore sodium balance through increased GFR. Incorporating adaptive and injurious effects of elevated P gc, we showed that preglomerular arteriole hypertrophy allowed more direct transmission of pressure to the glomerulus with a smaller mean arterial pressure rise; Glomerular hypertrophy allowed a higher GFR for a given P gc; and P gc-driven glomerulosclerosis and nephron loss reduced GFR over time, while further increasing P gc and causing moderate proteinuria, in agreement with experimental data. UNX imposed on diabetes increased P gc further, causing faster GFR decline and extensive proteinuria, also in agreement with experimental data. The model provides a mechanistic explanation for hyperfiltration and proteinuria progression that will facilitate translation of efficacy for novel therapies from mouse models to human.

Evaluation of renal and cardiovascular protection mechanisms of SGLT2 inhibitors: model-based analysis of clinical data.

The mechanisms of cardiovascular and renal protection observed in clinical trials of sodium-glucose cotransporter 2 (SGLT2) inhibitors (SGLT2i) are incompletely understood and likely multifactorial, including natriuretic, diuretic, and antihypertensive effects, glomerular pressure reduction, and lowering of plasma and interstitial fluid volume. To quantitatively evaluate the contribution of proposed SGLT2i mechanisms of action on changes in renal hemodynamics and volume status, we coupled a mathematical model of renal function and volume homeostasis with clinical data in healthy subjects administered 10 mg of dapagliflozin once daily. The minimum set of mechanisms necessary to reproduce observed clinical responses (urinary sodium and water excretion, serum creatinine and sodium) was determined, and important unobserved physiological variables (glomerular pressure, blood and interstitial fluid volume) were then simulated. We further simulated the response to SGLT2i in diabetic virtual patients with and without renal impairment. Multiple mechanisms were required to explain the observed response: 1) direct inhibition of sodium and glucose reabsorption through SGLT2, 2) SGLT2-driven inhibition of Na+/H+ exchanger 3 sodium reabsorption, and 3) osmotic diuresis coupled with peripheral sodium storage. The model also showed that the consequences of these mechanisms include lowering of glomerular pressure, reduction of blood and interstitial fluid volume, and mild blood pressure reduction, in agreement with clinical observations. The simulations suggest that these effects are more significant in diabetic patients than healthy subjects and that while glucose excretion may diminish with renal impairment, improvements in glomerular pressure and blood volume are not diminished at lower glomerular filtration rate, suggesting that cardiorenal benefits of SGLT2i may be sustained in renally impaired patients.

Model-Based Evaluation of Proximal Sodium Reabsorption Through SGLT2 in Health and Diabetes and the Effect of Inhibition With Canagliflozin.

Sodium-glucose cotransporter 2 inhibitors (SGLT2i) reduce glucose levels in diabetes by inhibiting renal glucose reabsorption in the proximal tubule (PT), resulting in urinary glucose excretion. A recent large cardiovascular outcomes trial suggested that the SGLT2i empagliflozin may also decrease risk of renal dysfunction. Because sodium (Na) and glucose reabsorption are coupled through SGLT2, it is hypothesized that the renal benefits may be derived from lowering Na reabsorption in the PT, which would lead to favorable renal hemodynamic changes. However, the quantitative contribution of SGLT2 to PT Na reabsorption, as well as the differences between healthy and diabetic subjects, and the impact of SGLT2i on PT Na reabsorption are unknown. In this study we extended an existing mathematical model of glucose dynamics to account for renal glucose filtration and excretion. We utilized this model to quantify glucose and Na reabsorption through SGLT2 in healthy, controlled, and uncontrolled diabetes and following treatment with canagliflozin. In healthy, controlled diabetic, and uncontrolled diabetic states, Na reabsorption through SGLT2 was found to be 5.7%, 11.5%, and 13.7% of total renal Na reabsorption, and 7.1% to 9.5%, 14.4% to 19.2%, and 17.1% to 22.8% of sodium reabsorption in the PT alone. The model predicted that treatment of controlled diabetes with canagliflozin returns PT Na reabsorption through SGLT2 to normal levels. The degree of increased PT Na reabsorption due to SGLT2 is likely sufficient to drive pathologic changes in renal hemodynamics, and restoration of normal Na reabsorption through SGLT2 may contribute to beneficial renal effects of SGLT2 inhibition.

Multiscale Mathematical Model of Drug-Induced Proximal Tubule Injury: Linking Urinary Biomarkers to Epithelial Cell Injury and Renal Dysfunction.

Drug-induced nephrotoxicity is a major cause of acute kidney injury, and thus detecting the potential for nephrotoxicity early in the drug development process is critical. Various urinary biomarkers exhibit different patterns following drug-induced injury, which may provide greater information than traditional biomarkers like serum creatinine. In this study, we developed a multiscale quantitative systems pharmacology model relating drug exposure to proximal tubule (PT) epithelial cell injury and subsequently to expression of multiple urinary biomarkers and organ-level functional changes. We utilized urinary kidney injury molecule-1 (Kim-1), alpha glutathione S-transferase, albumin (αGST), glucose, and urine volume time profiles as well as serum creatinine and histopathology data obtained from rats treated with the nephrotoxicant cisplatin to develop the model. Although the model was developed using single-dose response to cisplatin, the model predicted the serum creatinine response to multidose cisplatin regimens. Further, using only the urinary Kim-1 response to gentamicin (a nephrotoxicant with a distinctly different injury time course than cisplatin), the model detected and predicted mild to moderate PT injury, as confirmed with histopathology, even when serum creatinine was unchanged. Thus, the model is generalizable, and can be used to deconvolute the underlying degree and time course of drug-induced PT injury and renal dysfunction from a small number of urinary biomarkers, and may provide a tool to determine optimal dosing regimens that minimize renal injury.

Primary proximal tubule hyperreabsorption and impaired tubular transport counterregulation determine glomerular hyperfiltration in diabetes: a modeling analysis.

Glomerular hypertension and hyperfiltration in early diabetes are associated with development and progression of diabetic kidney disease. The tubular hypothesis of diabetic hyperfiltration proposes that it is initiated by a primary increase in sodium (Na) reabsorption in the proximal tubule (PT) and the resulting tubuloglomerular feedback (TGF) response and lowering of Bowman space pressure (PBow). Here we utilized a mathematical model of the human kidney to investigate over acute and chronic timescales the mechanisms responsible for the magnitude of the hyperfiltration response. The model implicates that the primary hyperreabsorption of Na in the PT produces a Na imbalance that is only partially restored by the hyperfiltration induced by TGF and changes in PBow Thus secondary adaptations are needed to restore Na balance. This may include neurohumoral transport regulation and/or pressure-natriuresis (i.e., the decrease in Na reabsorption in response to increased renal perfusion pressure). We explored the role of each tubular segment in contributing to this compensation and the consequences of impairment in tubular compensation. The simulations indicate that impaired secondary downregulation of transport potentiated the rise in glomerular hypertension and hyperfiltration needed to restore Na balance at a given level of primary PT hyperreabsorption. Therefore, we propose for the first time that both the extent of primary PT hyperreabsorption and the degree of impairment of the distal tubular responsiveness to regulatory signals determine the level of glomerular hypertension and hyperfiltration in the diabetic kidney, thereby extending the tubule-centric concept of diabetic hyperfiltration and potential therapeutic approaches beyond the proximal tubule.

Exposure-response modeling of flow-mediated dilation provides an unbiased and informative measure of endothelial function.

The brachial artery flow-mediated dilation (FMD) test is the most widely utilized method to evaluate endothelial function noninvasively in humans by calculating the percent change in diameter (FMD%). However, the underutilized velocity and diameter time course data, coupled with confounding influences in shear exposure, noise, and upward bias, make the FMD test less desirable. In this study, we developed an exposure-response, model-based approach that not only quantifies FMD based on the rich velocity and diameter data, it overcomes previously acknowledged challenges. FMD data were obtained from 15 apparently healthy participants, each exposed to four different cuff occlusion durations. The velocity response following cuff release was described by an exponential model with two parameters defining peak velocity and rate of decay. Shear exposure derived from velocity was used to drive the diameter response model, which consists of additive constriction and dilation terms. Three parameters describing distinct aspects of the vascular response to shear (magnitude of the initial constriction response, and magnitude and time constant of the dilation response) were estimated for both the individuals and population. These parameters are independent of shear exposure. Thus this approach produces identifiable and physiologically meaningful parameters that may provide additional information for comparing differences between experimental groups or over time, and provides a means to completely account for shear exposure.NEW & NOTEWORTHY While flow-mediated dilation (FMD) is a valuable tool for evaluating endothelial function, analytical challenges include confounding influences of shear exposure, upward bias, and underutilization of rich time course data collected during FMD testing. We have developed an exposure-response, model-based approach that quantifies endothelial function based on the velocity and diameter data and fully accounts for shear exposure. It produces physiologically meaningful parameters that may provide useful information for comparing differences between experimental groups or over time.

A model-based approach to investigating the pathophysiological mechanisms of hypertension and response to antihypertensive therapies: extending the Guyton model.

Reproducibly differential responses to different classes of antihypertensive agents are observed among hypertensive patients and may be due to interindividual differences in hypertension pathology. Computational models provide a tool for investigating the impact of underlying disease mechanisms on the response to antihypertensive therapies with different mechanisms of action. We present the development, calibration, validation, and application of an extension of the Guyton/Karaaslan model of blood pressure regulation. The model incorporates a detailed submodel of the renin-angiotensin-aldosterone system (RAAS), allowing therapies that target different parts of this pathway to be distinguished. Literature data on RAAS biomarker and blood pressure responses to different classes of therapies were used to refine the physiological actions of ANG II and aldosterone on renin secretion, renal vascular resistance, and sodium reabsorption. The calibrated model was able to accurately reproduce the RAAS biomarker and blood pressure responses to combinations of dual-RAAS agents, as well as RAAS therapies in combination with diuretics or calcium channel blockers. The final model was used to explore the impact of underlying mechanisms of hypertension on the blood pressure response to different classes of antihypertensive agents. Simulations indicate that the underlying etiology of hypertension can impact the magnitude of response to a given class of therapy, making a patient more sensitive to one class and less sensitive others. Given that hypertension is usually the result of multiple mechanisms, rather than a single factor, these findings yield insight into why combination therapy is often required to adequately control blood pressure.