title: Imputation of TPMT defective alleles for the identification of patients with high-risk phenotypes.
abstract: BACKGROUND
  The activity of thiopurine methyltransferase (TPMT) is subject to genetic variation. Loss-of-function alleles are associated with various degrees of myelosuppression after treatment with thiopurine drugs, thus genotype-based dosing recommendations currently exist. The aim of this study was to evaluate the potential utility of leveraging genomic data from large biorepositories in the identification of individuals with TPMT defective alleles.
  
  
  METHODS
  TPMT variants were imputed using the 1000 Genomes Project reference panel in 87,979 samples from the biobank at The Children's Hospital of Philadelphia. Population ancestry was determined by principal component analysis using HapMap3 samples as reference. Frequencies of the TPMT imputed alleles, genotypes and the associated phenotype were determined across the different populations. A sample of 630 subjects with genotype data from Sanger sequencing (N = 59) and direct genotyping (N = 583) (12 samples overlapping in the two groups) was used to check the concordance between the imputed and observed genotypes, as well as the sensitivity, specificity and positive and negative predictive values of the imputation.
  
  
  RESULTS
  Two SNPs (rs1800460 and rs1142345) that represent three TPMT alleles ((*)3A, (*)3B, and (*)3C) were imputed with adequate quality. Frequency for the associated enzyme activity varied across populations and 89.36-94.58% were predicted to have normal TPMT activity, 5.3-10.31% intermediate and 0.12-0.34% poor activities. Overall, 98.88% of individuals (623/630) were correctly imputed into carrying no risk alleles (553/553), heterozygous (45/46) and homozygous (25/31). Sensitivity, specificity and predictive values of imputation were over 90% in all cases except for the sensitivity of imputing homozygous subjects that was 80.64%.
  
  
  CONCLUSIONS
  Imputation of TPMT alleles from existing genomic data can be used as a first step in the screening of individuals at risk of developing serious adverse events secondary to thiopurine drugs.
authors.affiliation: Center for Applied Genomics, The Children's Hospital of Philadelphia Philadelphia, PA, USA.
authors.forename: Berta
authors.initials: B
authors.lastname: Almoguera
authors.affiliation: Center for Applied Genomics, The Children's Hospital of Philadelphia Philadelphia, PA, USA.
authors.forename: Lyam
authors.initials: L
authors.lastname: Vazquez
authors.affiliation: Center for Applied Genomics, The Children's Hospital of Philadelphia Philadelphia, PA, USA.
authors.forename: John J
authors.initials: JJ
authors.lastname: Connolly
authors.affiliation: Center for Applied Genomics, The Children's Hospital of Philadelphia Philadelphia, PA, USA.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Bradfield
authors.affiliation: Center for Applied Genomics, The Children's Hospital of Philadelphia Philadelphia, PA, USA ; Department of Pediatrics, University of Pennsylvania Perelman School of Medicine Philadelphia, PA, USA.
authors.forename: Patrick
authors.initials: P
authors.lastname: Sleiman
authors.affiliation: Center for Applied Genomics, The Children's Hospital of Philadelphia Philadelphia, PA, USA ; Department of Pediatrics, University of Pennsylvania Perelman School of Medicine Philadelphia, PA, USA.
authors.forename: Brendan
authors.initials: B
authors.lastname: Keating
authors.affiliation: Center for Applied Genomics, The Children's Hospital of Philadelphia Philadelphia, PA, USA ; Department of Pediatrics, University of Pennsylvania Perelman School of Medicine Philadelphia, PA, USA.
authors.forename: Hakon
authors.initials: H
authors.lastname: Hakonarson
keywords: DNA biobank; Electronic Medical Records; TPMT; genotype imputation; pharmacogenetics