The Han Lab Research
Our research focuses on understanding the genetic and environmental etiology of complex disease and developing and evaluating efficient screening strategies based on etiological understanding. The areas of our research interests include statistical genetics, molecular epidemiology, cancer screening, health policy modeling, and risk prediction modeling. We have developed various statistical methods to analyze high-dimensional data to identify genetic and environmental risk factors and their interactions for complex disease. These approaches include employing a unified framework that integrates a class of disease risk models for modeling the joint effects of genes and environmental exposures and using a set of constraints that are biologically plausible in order to increase the power of tests and to reduce false-positives.
Currently we are working on various projects that aim to:
- Evaluate the genetic, environment, and clinical risk factors for second primary lung cancer to establish efficient screening strategies for lung cancer survivors
- Identify gene-gene interactions for Alzheimer’s disease applying a graphical model based module search to incorporate biological network/pathway and functional information.
- Evaluate genetic, epigenetic, and metabolomic biomarker predictors of PTSD and Resilience following TBI
- Develop efficient risk-based screening strategies for lung cancer using an algorithm for simulating lifetime trajectories of risk factors for lung cancer
- Evaluate the interactions among traumatic brain injury, sex, and apolipoprotein E(APOE4) on the risk of developing Alzheimer’s disease using large case-control study data