By Lina Sorg
Diabetic kidney disease (DKD), also called diabetic nephropathy, is a dangerous complication of diabetes and the chief cause of end-stage renal failure, in which the kidneys cease to function. High levels of blood glucose in hyperglycemic diabetics mean that the kidneys filter blood much quicker than usual, which puts strain on the glomeruli (networks of capillaries in the kidney that do initial filtering) and nephrons (filtration units). Unwanted buildup begins in the glomeruli, which pushes the blood with more force through the kidney and damages the filtration barrier; over an extended period of time, this continued stress can impair the kidneys’ ability to filter blood at a normal rate, thus expediting the rate of DKD. In short, hyperglycemia initiates and exacerbates DKD.
A major indicator of the onset of DKD is damage to kidney cells called podocytes, which is difficult to detect. Podocyte cells have central body and radiating arms, and damage to these cells seriously disrupts bodily systems. The past five-ten years have seen an acceleration of the study of podocyte cells.
Hyperglycemia initiates and exacerbates diabetic kidney disease, the primary cause of end-stage renal failure. Image credit: Ashlee Ford Versypt, LS16 minisymposium presentation.
In a minisymposium session called “Mathematical Modeling of Podocytes in Diabetic Kidney Disease” at the SIAM Conference on the Life Sciences, Ashlee Ford Versypt of Oklahoma State University used mathematical modeling to study the link between hyperglycemia, DKD, and factors that contribute to its onset. By simulating and quantitatively describing the dynamics of podocyte damage—taking into account effects of glucose metabolism in the kidney during hyperglycemia, podocyte cell-signaling, biomechanical forces, and nephron hemodynamics, all of which interact across varied length and time scales—she seeks to predict DKD before it hits.
Versypt discussed her research team’s flux balance analysis approach to model blood flow through the kidneys, which involves numerically-solved algebraic equations and a system of partial and ordinary differential equations (ODEs). A system of ODEs, created in MATLAB, represents an intracellular RAS model; RAS is a hormone system regulating blood pressure and fluid balance at systemic and cellular levels. “Right now we’re using steady state data,” Versypt said, adding that the long-term goal is a successful math model to describe steady-state podocytes.
The team’s methods demonstrates a multitude of factors, including biochemical reaction network kinetics, that connect podocyte damage in DKD to diabetic hyperglycemia. It simulates varied intensities and durations of elevated glomerular filtration (GFR) rates that are present during hyperglycemia, uses linear and multilinear functions for primary observations, and includes glucose in the model’s parameters. Versypt also explained two varied approaches to understand filtration. “In approach one, we used classical parameter estimation to fit six different simple models,” she said. They compare these models to the second approach, which is based on information gleaned from published literature.
The research is still in its early stages, as Versypt and her team are working with medical researchers to learn more about podocytes and ultimately obtain a more complete model of the system. “If we can slow down the effects of hyperglycemia, then we can prevent some of the irreversible loss of podocydes,” Versypt said.