Genes, the Environment, and Individualized Health
Nilanjan Chatterjee is committed to harnessing genetic and environmental data to improve clinical decision-making.
The more researchers study the genetic origins of diseases, the more evident the complexity of the relationship becomes. The picture is further complicated when the interplay between genes and environmental exposures are considered. Though it’s been established that many diseases result from some combination of genes and a broadly defined list of environmental exposures, much remains to be understood.
Dr. Nilanjan Chatterjee, a recently announced Bloomberg Distinguished Professor of Biostatistics and Oncology, has dedicated his career to elucidating the combined influence of genetic predisposition and environmental exposure on disease incidence. Although his research interests are diverse - spanning cancers of the breast, lung, and bladder, and chronic diseases such as type 2 diabetes – they are linked by a common thread: the use of genetic data to promote the individualization of patient care. In one illustrative example, Dr. Chatterjee tested several statistical models to stratify women into high or moderate risk of breast cancer. Dr. Chatterjee and his colleagues not only found the model that could best predict breast cancer risk, but he and his team outlined how this type of modeling could be used to individualize recommendations for health intervention. The model, for instance, was able to calculate the difference in the 10-year risk of breast cancer based on whether a woman receives menopausal hormonal therapy (MHT) or not. The impact of MHT on absolute risk of breast cancer varied substantially based on the woman’s genetic predisposition and family history, demonstrating the potential utility of the model in guiding the risk-benefit assessment for use of MHT in individual women.
In addition to developing models for his own work, Dr. Chatterjee also provides tools others can use to improve the quality of their research. For example, recognizing that the standard models used in many genome-wide association studies are limited by assumptions, Dr. Chatterjee published series of new methods that allow investigators to increase study power while taking into account heterogeneity in gene-disease relationships by exposure status and disease subtype. These methods have been applied in many genetic association studies of cancers and other diseases to obtain insight into complex genetic architecture and gene-environment interactions.
Dr. Chatterjee’s commitment to harnessing practical clinical information from genetic data and to sharing his insights and methods with the research community bode well for the future of individualized health at Johns Hopkins and beyond. Hopkins inHealth is excited to welcome Dr. Chatterjee as the head of its Study Design and Analysis Core, where he intends to stimulate discussion among Hopkins leadership on how to best advance individualized health, while also consulting and collaborating with researchers interested in developing novel tools, methods, and software.
More can be found about Dr. Chatterjee’s many accomplishments in a recent article published on The Hub.