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Nilanjan Chatterjee

National Cancer Institute

Large genome-wide association studies are now consistently pointing towards an extremely polygenic model for complex diseases. Such models may involve thousands of susceptibility markers, each conferring only a modest risk, but collectively they could be explaining substantial variation in disease-risks in populations. Further, a few large studies of gene-environment interactions indicate that genetic and environmental risk-factors may broadly act in a multiplicative fashion on the risk of a number of different cancers and possibly other diseases. In this talk, I will explore how under such emerging models for disease architecture, the performance of polygenic risk prediction models are expected to improve in the future with increasing sample size,  incorporation of functional information and integration of next generation sequencing or genotyping technologies that can provide coverage for low frequency and rare variants. Further, using results from recent studies on bladder and breast cancers, I will illustrate potential implications for multiplicative gene-environment interactions for targeted prevention for these two malignancies both of which have modifiable risk-factors. These analyses will highlight both challenges and opportunities for using genetic information for personalized disease prevention.

More information about Nilanjan Chatterjee may be found at

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