Multi-Cellular Network Model Predicts Alterations in Glomerular Endothelial Structure in Diabetic Kidney Disease

Area of Science:

• Nephrology
• Cell Biology
• Computational Biology

Background:

• Diabetic kidney disease (DKD) involves glomerular endothelial cell (GEC) dysfunction, affecting fenestrations and glomerular filtration.
• Current models struggle to fully explain the cellular mechanisms behind GEC fenestration changes in DKD.

Purpose of the Study:

• To investigate the molecular mechanisms driving GEC fenestration alterations in DKD using a computational network model.
• To identify key signaling pathways and potential therapeutic targets for preserving GEC fenestration integrity.

Main Methods:

• Developed a logic-based protein-protein interaction network model with normalized Hill functions.
• Integrated signaling pathways involving actin remodeling, Rho-kinase, calcium, and VEGF signaling.
• Simulated hyperglycemia effects in diabetic mice models.

Main Results:

• Identified key drivers of fenestration loss and size changes in GECs.
• Modeled hyperglycemia-induced significant fenestration loss and increased fenestration size.
• Demonstrated that glycemic control is less effective in later stages of DKD.

Conclusions:

• Hyperglycemia-induced signaling dysregulation critically impacts GEC fenestrations in DKD.
• Early glycemic control can mitigate but not fully prevent fenestration damage.
• Targeting Rho-associated kinase, VEGF-A, NFκB, and actin stress fibers may offer novel therapeutic strategies for DKD.