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The future of genomic prediction of common diseases: big data, better prediction? - A. Cecile J.W. Janssens PhD
The future of genomic prediction of common diseases: big data, better prediction?  
SERC Lunch and Learn #7
Emory University
Department of Human Genetics
Atlanta, GA  
Date
May 23rd, 2013
Length
01:35:02

About the Presentation
Dr. Cecile Janssens, Professor of Translational Epidemiology within Emory’s Rollins School of Public Health, presented on Wednesday, September 11 during SERC’s Lunch and Learn Series. Her research involves the translation of genomics research to applications in clinical and public health practice. The presentation was titled “The Future of Genomic Prediction of Common Diseases: Big Data, Better Prediction”. Her discussion outlined direct-to-consumer personal genome testing such as 23andMe and DeCODEme. These services gather saliva samples, perform whole genome sequencing, and provide consumers with risk percentages for a multitude of chronic diseases. Dr. Janssens’ research suggests knowledge of genetic variants may add little to predicting development of complex, chronic conditions at the individual level. Instead, heritability of disorders, environmental influences, and lifestyle likely play the most essential role in prediction. She concluded genetic risk models are unlikely to add significant prediction to chronic disease development , but are very applicable in modeling outside of predictive health. Personal genome testing, however, may be useful in risk differentiation, identifying rare variants, and potentially predicting chronic disease with high heritability.

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