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John M. Higgins, MD
Associate Professor of Systems Biology, Harvard Medical SchoolAssistant Pathologist, Massachusetts General Hospital
Center for Systems BiologyMassachusetts General HospitalSimches Research Building, CPZN 5226185 Cambridge StreetRoom 5.222Boston, MA 02114Phone: 617-643-6129Fax: 617-643-6133Email:email@example.com
I study the dynamics of human pathophysiologic processes by developing mechanistic mathematical descriptions of complex human disease phenotypes and how they change over time. The research combines medical insight, dynamical systems theory, and experiments utilizing clinical specimens, microfluidics, video processing, flow cytometry, simulation, and large-scale analysis of medical databases in pursuit of two goals: (1) advancing fundamental understanding of human pathophysiologic process and their dynamics, and (2) improving patient diagnosis, monitoring, and treatment.
Pathophysiology may be described at the molecular, cellular, tissue and organismal levels and may show clinically significant variation over time scales ranging from less than a second to more than a decade. Using clinical laboratory data and experiments with clinical specimens, we can develop detailed descriptions of pathophysiologic states in terms of clinically relevant and measurable quantities. We can then propose mathematical models describing the interrelationships between these state variables and how those relationships change when perturbed by disease. Models must be consistent with mechanisms established by both existing basic research and clinical experience, and once validated will enable the estimation of dynamic parameters. Personalized estimates of parameters often quantify unmeasurable pathophysiologic processes, revealing new insight into pathophysiology and providing opportunities for novel approaches to diagnosis and patient monitoring. Recent work has focused on population dynamics of cell characteristics in anemia and inflammation due to ischemia, infection, autoimmune disease, and more.
I am developing a mathematical model of vaso-occlusion in sickle cell disease by combining theory from fluid mechanics with experiments using patient samples flowing in microfluidic devices under controlled conditions. With collaborators, I have developed a way to stop and start the flow of sickle cell blood in a network of silicone polymer channels by changing only the oxygen concentration. I hope to understand the physical determinants of in vitro vaso-occlusion and to explore their relevance to clinical management and intervention.
I am also developing a probabilistic model of alloimmunization following red blood cell transfusion. By analyzing several large-scale patient databases, my collaborators and I have identified robust patterns of immunologic response which suggest that only a subset of transfusion recipients are at risk of alloimmunization. We hope to determine if these patterns have implications for human immune response in general and to apply any insights to the improvement of blood bank practices.
View a complete list of Dr. Higgins' publications on the Center for Systems Biology website.
Chaudhury A, Noiret L, Higgins JM. White blood cell population dynam- ics for risk stratification of acute coronary syndrome. Proceedings of theNational Academy of Sciences USA. 2017; 114(46):12344-12349.
Malka R, Nathan DM, Higgins JM. Mechanistic modeling of hemoglobin glycation and red blood cell kinetics enables personalized diabetes monitor- ing. Science Translational Medicine. 2016; 8(359):359ra130.
Patel HH, Patel HR, Higgins JM. Modulation of red blood cell population dynamics is a fundamental homeostatic response to disease. American Journal of Hematology. 2015; 90(5):422-8.Di Caprio G, Stokes C, Higgins JM, Schonbrun E. Proceedings of the National Academy of Sciences of the United States of America. 2015; 112(32):9984-9.
Higgins JM & Mahadevan, L. Physi- ological and pathological population dynamics of circulating human red blood cells. Proceedings of the National Academy of Sciences of the United States of America. 2010; 107: 20587-20592.
Massachusetts General Hospital
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