Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 107, Issue 47, Pages 20587-20592Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1012747107
Keywords
hematology; mathematical modeling; medical sciences; stochastic differential equations; systems biology
Categories
Funding
- Harvard Medical School Research Information Technology Group
- National Institute of Diabetes and Digestive and Kidney Diseases [DK083242]
- National Heart, Lung, and Blood Institute [HL091331]
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The systems controlling the number, size, and hemoglobin concentrations of populations of human red blood cells (RBCs), and their dysregulation in anemia, are poorly understood. After release from the bone marrow, RBCs undergo reduction in both volume and total hemoglobin content by an unknown mechanism [Lew VL, et al. (1995) Blood 86:334-341; Waugh RE, et al. (1992) Blood 79:1351-1358]; after similar to 120 d, responding to an unknown trigger, they are removed. We used theory from statistical physics and data from the hospital clinical laboratory [d'Onofrio G, et al. (1995) Blood 85:818-823] to develop a master equation model for RBC maturation and clearance. The model accurately identifies patients with anemia and distinguishes thalassemia-trait anemia from iron-deficiency anemia. Strikingly, it also identifies many pre-anemic patients several weeks before anemia becomes clinically detectable. More generally we illustrate how clinical laboratory data can be used to develop and to test a dynamic model of human pathophysiology with potential clinical utility.
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