Mathematical model of red blood cells may predict risk of anemia

A collaboration between a physician-researcher at Massachusetts General Hospital (MGH) and a mathematician from Harvard University has led to development of a mathematical model reflecting how red blood cells change in size and hemoglobin content during their four-month lifespan.

In their report published online in PNAS Early Edition, John Higgins, MGH Center for Systems Biology and Department of Pathology, and L. Mahadevan,  Harvard School of Engineering and Applied Sciences (SEAS), also describe how their model may be used to provide valuable clinical information.

“This study describes a promising way to predict who is likely to become anemic before they actually do, and it is based on tests routinely performed in hospitals,” says Higgins. “More generally, we found that a type of mathematical analysis commonly used in physics can be applied to clinical data and uncover new details of human physiology which can help improve diagnosis.”

Mahadevan adds, “We show that it is possible to use minimal models to compress the information available in existing clinical data into a few parameters, which can then serve as a quantitative basis for comparing characteristics across the entire population.” He is also a member of the Harvard University Department of Organismic and Evolutionary Biology and the Wyss Institute for Biologically Inspired Engineering.

An assistant professor of systems biology at Harvard Medical School, Higgins notes that the expertise Mahadevan brought to their collaboration was invaluable. “There are very few mathematically sophisticated scientists who are as knowledgeable about biomedicine as Mahadevan, and his boundless curiosity enables or even compels him to understand any necessary aspects of the biological system. He has repeatedly shown how complex math can lead to simple intuitive models of biological phenomena, and it’s these simple models that truly advance our understanding.”

Mahadevan, the de Valpine Professor of Applied Mathematics at the Harvard SEAS and a professor of organismic and evolutionary biology, says, “Bringing clinical data, mathematical and computational expertise and scientific culture together to bear on problems connected to the practice of medicine is precisely what is needed to bring medicine towards becoming a finely tuned quantitative subject. John’s rare combination of knowledge, talents and enthusiasm are a wonderful example of this approach.”

The study was supported by grants from the National Institute for Diabetes and Digestive and Kidney Disease and the National Heart, Lung and Blood Institute.