Events

Karin Leiderman

The University of North Carolina at Chapel Hill
Barton Lectures in Computational Mathematics
https://math.unc.edu/faculty-member/leiderman-karin/

When

Date: Wednesday, April 19, 2023
Time: 4:00 pm - 5:00 pm
Location: Petty 150
Dr. Karin Leiderman is an Associate Professor in the Department of Mathematics and the Computational Medicine Program at the University of North Carolina at Chapel Hill. Before joining the faculty at the University of North Carolina, she was an Associate Professor at Colorado School of Mines, an Assistant Professor at the University of California Merced, and a Visiting Assistant Professor at Duke University. She holds a PhD in Mathematics from the University of Utah. Dr. Leiderman’s research is broadly aimed at understanding biological systems using mathematical modeling and computation. She has an active research program focused on studying the influence of biochemical and biophysical mechanisms on blood coagulation, clot formation, and bleeding. Her research has been supported by grants from the NSF, ARO, and NIH, including an NSF CAREER award and two NIH R01s through a multiple PI mechanism. For more information, kindly visit: Leiderman Group Website . Dr. Leiderman is also an active faculty advisor for the UNC Chapel Hill Association for Women in Mathematics Student Chapter. When not working, she enjoys spending time with her husband and two daughters, reading, getting outside with her dog, and doing yoga.

Blood clot formation is a complex and nonlinear process that occurs under flow and on multiple spatial and temporal scales. Defects and perturbations in the clotting system can result in serious bleeding or pathological clot formation, but due its complexity, the responses and their underlying mechanisms are challenging to predict. Mechanistic mathematical models of blood clot formation and coagulation can elucidate biochemical and biophysical mechanisms, help interpret experimental data, and guide experimental design. In this talk I will briefly describe one such model and show how an integrated mathematical and experimental approach has facilitated discovery of previously unrecognized interactions within the clotting system. I will first highlight results from a recent study focused on hemophilia A, a genetic bleeding disorder defined by the deficiency of proteins (clotting factors) necessary to form stable blood clots. Our study was motivated by the clinically observed variability in bleeding frequency and severity in hemophilia A, where clotting factor levels alone are poor predictors of bleeding risk. Our goal was to use the model to answer the question: in cases of hemophilia A with severe deficiency but mild bleeding, what might be compensating for the deficient clotting factor? We performed uncertainty and sensitivity analysis on our model to identify modifiers that enhance the clotting response in the context of hemophilia A. We identified coagulation factor V as a key modifier and confirmed this finding with experimental assays. The mathematical model was used further to propose one potential biochemical mechanism for these observations. I will also discuss our current work in which we extended the model to allow for investigation of alternative mechanisms and modifiers in hemophilia A, as well as identification of modifiers in hemophilia B and C.