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) progression involves glomerular endothelial cell (GEC) dysfunction, affecting fenestrations and glomerular filtration.
• Cellular mechanisms regulating GEC fenestrations are unclear due to model limitations and in vivo imaging challenges.

Purpose of the Study:

• To investigate glucose-mediated signaling dysregulation impacting GEC fenestration dynamics using a computational model.
• To identify key molecular drivers of fenestration changes in DKD.

Main Methods:

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

Main Results:

• Model predicted hyperglycemia-induced fenestration loss and size increase in GECs.
• Identified Rho-associated kinase (ROCK), VEGF-A, and actin remodeling as key drivers.
• Showed glycemic control is effective pre-diabetically but less so as DKD progresses.

Conclusions:

• Computational modeling provides insights into GEC fenestration regulation in DKD.
• Suggests targeting ROCK, VEGF-A, NFκB, and actin stress fibers as potential therapeutic strategies.
• Highlights the importance of early glycemic control in mitigating DKD-related GEC damage.