Contrasting Association Results between Existing PheWAS Phenotype Definition Methods and Five Validated Electronic Phenotypes

Joseph B. Leader, Sarah A. Pendergrass, Anurag Verma, David J. Carey, Dustin N. Hartzel, Marylyn D. Ritchie, H. Lester Kirchner

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Phenome-Wide Association Studies (PheWAS) comprehensively investigate the association between genetic variation and a wide array of outcome traits. Electronic health record (EHR) based PheWAS uses various abstractions of International Classification of Diseases, Ninth Revision (ICD-9) codes to identify case/control status for diagnoses that are used as the phenotypic variables. However, there have not been comparisons within a PheWAS between results from high quality derived phenotypes and high-throughput but potentially inaccurate use of ICD-9 codes for case/control definition. For this study we first developed a group of high quality algorithms for five phenotypes. Next we evaluated the association of these "gold standard" phenotypes and 4,636,178 genetic variants with minor allele frequency > 0.01 and compared the results from high-throughput associations at the 3 digit, 5 digit, and PheWAS codes for defining case/control status. We found that certain diseases contained similar patient populations across phenotyping methods but had differences in PheWAS.

Original languageEnglish (US)
Pages (from-to)824-832
Number of pages9
JournalAMIA ... Annual Symposium proceedings. AMIA Symposium
Volume2015
StatePublished - Jan 1 2015

All Science Journal Classification (ASJC) codes

  • Medicine(all)

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