PheWAS and Beyond: The Landscape of Associations with Medical Diagnoses and Clinical Measures across 38,662 Individuals from Geisinger

Anurag Verma, Anastasia Lucas, Shefali S. Verma, Yu Zhang, Navya Josyula, Anqa Khan, Dustin N. Hartzel, Daniel R. Lavage, Joseph Leader, Marylyn D. Ritchie, Sarah A. Pendergrass

Research output: Contribution to journalArticle

18 Scopus citations

Abstract

Most phenome-wide association studies (PheWASs) to date have used a small to moderate number of SNPs for association with phenotypic data. We performed a large-scale single-cohort PheWAS, using electronic health record (EHR)-derived case-control status for 541 diagnoses using International Classification of Disease version 9 (ICD-9) codes and 25 median clinical laboratory measures. We calculated associations between these diagnoses and traits with ∼630,000 common frequency SNPs with minor allele frequency > 0.01 for 38,662 individuals. In this landscape PheWAS, we explored results within diseases and traits, comparing results to those previously reported in genome-wide association studies (GWASs), as well as previously published PheWASs. We further leveraged the context of functional impact from protein-coding to regulatory regions, providing a deeper interpretation of these associations. The comprehensive nature of this PheWAS allows for novel hypothesis generation, the identification of phenotypes for further study for future phenotypic algorithm development, and identification of cross-phenotype associations.

Original languageEnglish (US)
Pages (from-to)592-608
Number of pages17
JournalAmerican Journal of Human Genetics
Volume102
Issue number4
DOIs
StatePublished - Apr 5 2018

All Science Journal Classification (ASJC) codes

  • Genetics
  • Genetics(clinical)

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    Verma, A., Lucas, A., Verma, S. S., Zhang, Y., Josyula, N., Khan, A., Hartzel, D. N., Lavage, D. R., Leader, J., Ritchie, M. D., & Pendergrass, S. A. (2018). PheWAS and Beyond: The Landscape of Associations with Medical Diagnoses and Clinical Measures across 38,662 Individuals from Geisinger. American Journal of Human Genetics, 102(4), 592-608. https://doi.org/10.1016/j.ajhg.2018.02.017