Assessing the functional consequence of loss of function variants using electronic medical record and large-scale
Patrick Sleiman1, Jonathan Bradfield2, Frank Mentch2
1Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia Philadelphia, PA, USA ; Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania Philadelphia, PA, USA.
Abstract:
Estimates from large scale genome sequencing studies indicate that each human carries up to 20 genetic variants that are predicted to results in loss of function (LOF) of protein-coding genes. While some are known disease-causing variants or common, tolerated, LOFs in non-essential genes, the majority remain of unknown consequence. We explore the possibility of using imputed GWAS data from large biorepositories such as the electronic medical record and genomics (eMERGE) consortium to determine the effects of rare LOFs. Here, we show that two hypocholesterolemia-associated LOF mutations in the PCSK9 gene can be accurately imputed into large-scale GWAS datasets which raises the possibility of assessing LOFs through genomics-linked medical records.
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