Project Update: The Networks of Evolutionary Medicine

By Deryc Painter

The art of medicine consists in amusing the patient while nature cures the disease. - Voltaire (1694-1778)

The application of modern evolutionary theory to a medical conceptualization of health and disease, known as evolutionary medicine (EM), is an approach that is said to have changed the way doctors, scientists, and other health professionals advance biomedical research and clinical practice. Because I’m interested in how an evolutionary perspective of medicine is changing the status quo in the medical and research communities, I studied a list of scientists, doctors, and nurses that have identified themselves as interested in evolutionary medicine, and created two social networks. 

The first is a network between professionals interested in EM and their respective institutions (figure 1). The majority of the institutions in the network have only one or two people interested in evolutionary medicine. Further research may reveal that certain institutions contribute more than others to the EM literature. Without data from their publications (e.g. co-authors and citations), the first network suggests that evolutionary medicine is not centralized around one institution.

The second network (figure 2) uses the same individuals as the first, but connects them by their self-reported interests.  Suddenly, we see what looks like an actual network.  This network indicates that evolutionary medicine is organized around shared interests in topics.  There are still outliers that do not connect to the rest of the network, but the majority of individuals are connected to one another through major topic nodes like physiology, infection, genetics, and behavior.  As the nodes become more distal from these central themes, more specialized topics, like obesity and reproductive ecology, begin to appear.  However, the second network is based on the self-reported interests of individuals, and does not necessarily reflect their area of expertise or research.  Armed with over six thousand abstracts and papers, I am currently in the process of creating a keyword profile for each individual, which will better represent their contributions to evolutionary medicine. 
The third, future network that these keyword profiles will generate should offer insight into the areas of research that are being most influenced by evolutionary medicine.  Using topic modeling and citation networks, I will focus on particular areas of evolutionary medicine, and compare evolutionary medicine papers to papers that use a more classic, clinical approach.  I hypothesize that by comparing the two networks, I will be able to identify trends and patterns that will provide insight into how an evolutionary approach to medicine changes the landscape of biomedical research and practice.