The importance of the microbiome in epidemiologic research
By Mark Wanner
Estimates of the precise numbers vary, but it’s widely known that we have several times more microbial cells on and in our bodies than our own cells. And overall those microbial cells express a nearly 30-fold greater variety of protein-encoding genes than ours do, often working in concert with our own systems. It’s no wonder that some scientists are beginning to consider the sum total of us plus our microbiomes as a whole, rather than as separate entities. In this context, our microbiomes need to be factored into all analyses of how we interact with our environments, such as in epidemiology.
In a new paper published in the Annals of Epidemiology, JAX Professor George Weinstock, Ph.D., and Postdoctoral Associate Blake Hanson, Ph.D., assess the role of the microbiome within the traditional epidemiological triangle: the host (us), the agent (e.g., a change agent such as a pathogen) and the environment. The authors argue that the microbiome should be considered its own entity, expanding the triangle by another factor. It’s not an easy task—microbiome data sets are typically massive and unwieldy, containing more variables per sample than number of samples. Therefore statistical power and advanced analysis methods are mandatory for working with the data to obtain reproducible results and meaningful clinical translation.
Associating the complex dynamics of our microbial communities with human health is a significant challenge. To quote the authors, “There is still work to be done in characterizing microbiome development, ecological stability, and variation, and there is a great need for further development of statistical methodologies for dealing with large-scale epidemiologic data.” If set up carefully and done well, however, microbiome research holds significant promise for better understanding of human health and discovering new therapeutic targets.
Hanson BM, Weinstock GM, The importance of the microbiome in epidemiologic research, Annals of Epidemiology (2016), doi: 10.1016/j.annepidem.2016.03.008.