Researchers at the University of Virginia have developed a new computer model mapping the network that signals how heart cells grow in response to biochemical and mechanical stresses, such as high blood pressure or heart attacks, which can lead to heart failure.
Their work is detailed in an article, "Network Reconstruction and Systems Analysis of Cardiac Myocyte Hypertrophy Signaling," published online in the current issue of the Journal of Biological Chemistry.
The computer model of the cardiac cells' communication network expands on previous models by a factor of 15, and connects pieces of that network, study co-author and assistant professor of biomedical engineering Jeff Saucerman says in a university announcement. The most significant finding, according to the article synopsis: Rather than acting through isolated pathways, cardiac hypertrophy signaling is a highly integrated network.
"Because the signaling network is so large, developing new drug targets for reversing or preventing this growth of the heart is very complicated," biomedical engineering graduate student Karen Ryall, lead author of the paper, said in the announcement. "There's all this crosstalk between pathways that can work around a given intervention. It's hoped that with this project, we can begin to understand the connections between pathways and how this network makes decisions about how to grow in response to different stresses."
Ground-breaking medical research based on computational models is becoming increasingly common, helping scientists learn more about a range of diseases and begin to advance preventive care.
"There is a whole new community of people being trained in mathematics, computer science and engineering, and they are being cross-trained in biology," said Raimond Winslow, director of the Institute for Computational Medicine at Johns Hopkins University in Baltimore. "This allows them to bring a whole new perspective to medical diagnosis and treatment."
Winslow compared the hybrid researchers to engineers, saying, "Computational medicine can help you see how the pieces of the puzzle fit together to give a more holistic picture."
To learn more:
- here's the study abstract
- read the university announcement