A person’s background exposures provide the context for the development of his/her disease. Understanding the underlying biological mechanisms important for the development or progression of disease depends on this context. Traditional epidemiologic approaches have relied on stratification or
adjustment using regression models, however, this as major limitations when we are dealing with big datasets. This is especially true given the relatively small sample sizes in genomic studies combined with the extraordinarily large number of potential risk factors limits our ability to fully understand an individual’s exposure profile and its impact on biology and disease. In this presentation, I will introduce an integrative analysis framework for understanding disease, using pancreatic cancer as an example, and propose how we can use technology to increase our impact as public health professionals.
Presented by: Rick Jansen, PhD, MS, (he/him) NDSU Associate Professor of Public Health, Biostatistician at Sanford Health