Kristin Brown-Gentry

TL;DR: A novel method to scan phenomic data for genetic associations using International Classification of Disease billing codes, which are available in most EMR systems, and develops a code translation table to automatically define 776 different disease populations and their controls using prevalent ICD9 codes derived from EMR data.

TL;DR: In this article, a large-scale DNA databanks linked to electronic medical record (EMR) systems have been proposed as an approach for rapidly generating large, diverse cohorts for discovery and replication of genotype-phenotype associations.

TL;DR: Using a phenome-wide association study (PheWAS) approach, genetic variants for association with phenotypes available for 70,061 study participants in the Population Architecture using Genomics and Epidemiology (PAGE) network are tested to better characterize the genetic architecture of complex traits and identify novel pleiotropic relationships.

TL;DR: The results of PheWAS can be used to discover novel relationships between SNPs, phenotypes, and networks of interrelated phenotypes; identify pleiotropy; provide novel mechanistic insights; and foster hypothesis generation.

TL;DR: For the associations that did not generalize, differences in effect sizes, allele frequencies, and linkage disequilibrium offer clues to the next generation of association studies for these traits.