A computational model to understand mouse iron physiology and diseases
It is well known that iron is an essential element for life but is toxic when in excess or in certain forms. Accordingly there are many diseases that result directly from either lack or excess of iron. Iron has also been associated with a wide range of other diseases and may have an important role in aging. Yet many molecular and physiological aspects of iron regulation have only been discovered recently and others are still awaiting elucidation. In the last 18 years, after the discovery of the hormone hepcidin, many details of iron regulation have become better understood and a clearer picture is starting to emerge, at least in qualitative terms. However there is still no good quantitative and dynamic description of iron absorption, distribution, storage and mobilization that agrees with the wide array of phenotypes presented in several iron-related diseases. The present work addresses this issue by developing a mathematical model of iron distribution in mice that was calibrated with existing ferrokinetic data and subsequently validated against data from a series of iron disorders, such as hemochromatosis, {beta}-thalassemia, atransferrinemia and anemia of inflammation. To adequately fit the ferrokinetic data required including the following mechanisms: a) the role of transferrin in deliving iron to tissues, b) the induction of hepcidin by high levels of transferrin-bound iron, c) the ferroportin-dependent hepcidin-regulated iron export from tissues, d) the erythropoietin regulation of erythropoiesis, and e) direct NTBI uptake by the liver. The utility of such a model to simulate disease interventions was demonstrated by using it to investigate the outcome of different schedules of transferrin treatment in {beta}-thalassemia. The present model is a successful step towards a comprehensive mathematical model of iron physiology incorporating cellular and organ level details.