TY - JOUR
T1 - PheWAS and Beyond
T2 - The Landscape of Associations with Medical Diagnoses and Clinical Measures across 38,662 Individuals from Geisinger
AU - Verma, Anurag
AU - Lucas, Anastasia
AU - Verma, Shefali S.
AU - Zhang, Yu
AU - Josyula, Navya
AU - Khan, Anqa
AU - Hartzel, Dustin N.
AU - Lavage, Daniel R.
AU - Leader, Joseph
AU - Ritchie, Marylyn D.
AU - Pendergrass, Sarah A.
N1 - Publisher Copyright:
© 2018 American Society of Human Genetics
PY - 2018/4/5
Y1 - 2018/4/5
N2 - 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.
AB - 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.
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U2 - 10.1016/j.ajhg.2018.02.017
DO - 10.1016/j.ajhg.2018.02.017
M3 - Article
C2 - 29606303
AN - SCOPUS:85044160882
SN - 0002-9297
VL - 102
SP - 592
EP - 608
JO - American Journal of Human Genetics
JF - American Journal of Human Genetics
IS - 4
ER -