Jared Erwin

Adverse drug events (ADEs) are a serious problem causing over 100,000 hospitalizations in the U.S. annually. One key component in the response to a drug is our genetic variation. Identifying and using genetic information to avoid ADEs is an already proven method that needs further expansion. The eMERGE PGx project collected electronic medical records (EMR) along with targeted DNA variant data in order to create a useful dataset for pharmacogenetic studies. In this research, an automated approach to identify potential adverse drug events (ADE) in the eMERGE PGx cohort is presented. Data from the EMR is examined through the lens of a database of known adverse drug events: the Drug Evidence Base. Diagnosis codes that were known to be adverse events and appeared in a participant’s medical record following a medication order were labeled as a potential ADE. These potential ADEs were used as phenotypes for genetic associations tests at the single variant, gene, and gene-set level. The results were two findings of two single variants, 10 genes and one gene set having a significant association with one more adverse drug events. These results add to the body of knowledge that continues to grow around variation in drug response.