Next NIEHS Exposome Webinar on December 2nd

On December 2nd from 11:00-12:30PM EST, Dr. Chirag Patel of Harvard Medical School will discuss “Studying the exposome in large-scale with Environment-wide Association Studies (EWAS): accelerating discovery in environmental health”. Dr. Patel published the first Environment-wide Association Study in 2010 and has continued to advance the field, developing methods to understand the interactions between environmental exposures and the genome in disease risk.

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NIEHS webinar summary:

It is hypothesized that greater than 50% of complex disease risk is attributed to differences in an individual’s environment, but we lack ways of investigating the exposome — the totality of exposure load that occurs throughout a lifetime – in disease risk. Further, we have yet to incorporate the exposome in genome-based investigations, such as genome-wide association studies (GWAS) to assess how environment modifies genetic risk for complex disease. Investigating one or a handful of exposures at a time has led to a highly fragmented literature of epidemiologic association and much of that literature is not reproducible. A new unified study of the environment is required to discover environmental exposures, and how they interact with the genome, in disease.

Here, Dr. Patel will discuss ways of to remedy this problem through a strategy known as the “Environment-wide association study” (EWAS), where investigators assess 100s-1000s of personal exposures simultaneously. Analogous to GWAS, he will show how multiple personal exposures can be assessed simultaneously in terms of their association with diseases such as type 2 diabetes (T2D), heart disease risk factors, preterm birth, and mortality in population-based cohorts. In these studies, Dr. Patel shows how an array of exposures ranging from pollutants, nutrients, and pesticides are associated with these diseases and have effect sizes that are comparable or exceed GWAS findings. He will discuss the hurdles, including biases such as reverse causality, confounding, and challenges of inferring independence in midst of the dense correlation structure of the exposome.