Science for All Seasons 2019

For just over a decade, scientists have used an approach called the genome-wide association study, or GWAS, to measure the extent to which small, common variations called SNPs (single nucleotide polymorphisms) at millions of sites across the genome affect traits like height or a person's risk of developing diseases like diabetes or heart attack. Thanks to GWAS, researchers have identified tens of thousands SNP-to-trait and SNP-to-disease links. The question today is: How do we put all these data to use to impact human health and advance our understanding of human biology?

Population geneticist Alicia Martin will provide a brief primer on GWAS, and explain how gaps in the diversity of the data available today affect how researchers make use of the data now and in the future. Cardiologist Amit Khera will discuss polygenic scoring, a method that integrates information from millions of SNPs to predict an individual's likelihood of developing a given disease. Cancer biologist J.T. Neal will talk about the challenges of studying the functional roles of the thousands of SNPs associated with disease, the genes and pathways they affect, the cells they impact — and doing it all at massive scale.