Cargando…

Imputation of TPMT defective alleles for the identification of patients with high-risk phenotypes

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 w...

Descripción completa

Detalles Bibliográficos
Autores principales: Almoguera, Berta, Vazquez, Lyam, Connolly, John J., Bradfield, Jonathan, Sleiman, Patrick, Keating, Brendan, Hakonarson, Hakon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4026736/
https://www.ncbi.nlm.nih.gov/pubmed/24860591
http://dx.doi.org/10.3389/fgene.2014.00096
_version_ 1782316891783561216
author Almoguera, Berta
Vazquez, Lyam
Connolly, John J.
Bradfield, Jonathan
Sleiman, Patrick
Keating, Brendan
Hakonarson, Hakon
author_facet Almoguera, Berta
Vazquez, Lyam
Connolly, John J.
Bradfield, Jonathan
Sleiman, Patrick
Keating, Brendan
Hakonarson, Hakon
author_sort Almoguera, Berta
collection PubMed
description 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. Material and 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%. Conclusion: 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.
format Online
Article
Text
id pubmed-4026736
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-40267362014-05-23 Imputation of TPMT defective alleles for the identification of patients with high-risk phenotypes Almoguera, Berta Vazquez, Lyam Connolly, John J. Bradfield, Jonathan Sleiman, Patrick Keating, Brendan Hakonarson, Hakon Front Genet Genetics 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. Material and 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%. Conclusion: 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. Frontiers Media S.A. 2014-05-12 /pmc/articles/PMC4026736/ /pubmed/24860591 http://dx.doi.org/10.3389/fgene.2014.00096 Text en Copyright © 2014 Almoguera, Vazquez, Connolly, Bradfield, Sleiman, Keating and Hakonarson. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Almoguera, Berta
Vazquez, Lyam
Connolly, John J.
Bradfield, Jonathan
Sleiman, Patrick
Keating, Brendan
Hakonarson, Hakon
Imputation of TPMT defective alleles for the identification of patients with high-risk phenotypes
title Imputation of TPMT defective alleles for the identification of patients with high-risk phenotypes
title_full Imputation of TPMT defective alleles for the identification of patients with high-risk phenotypes
title_fullStr Imputation of TPMT defective alleles for the identification of patients with high-risk phenotypes
title_full_unstemmed Imputation of TPMT defective alleles for the identification of patients with high-risk phenotypes
title_short Imputation of TPMT defective alleles for the identification of patients with high-risk phenotypes
title_sort imputation of tpmt defective alleles for the identification of patients with high-risk phenotypes
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4026736/
https://www.ncbi.nlm.nih.gov/pubmed/24860591
http://dx.doi.org/10.3389/fgene.2014.00096
work_keys_str_mv AT almogueraberta imputationoftpmtdefectiveallelesfortheidentificationofpatientswithhighriskphenotypes
AT vazquezlyam imputationoftpmtdefectiveallelesfortheidentificationofpatientswithhighriskphenotypes
AT connollyjohnj imputationoftpmtdefectiveallelesfortheidentificationofpatientswithhighriskphenotypes
AT bradfieldjonathan imputationoftpmtdefectiveallelesfortheidentificationofpatientswithhighriskphenotypes
AT sleimanpatrick imputationoftpmtdefectiveallelesfortheidentificationofpatientswithhighriskphenotypes
AT keatingbrendan imputationoftpmtdefectiveallelesfortheidentificationofpatientswithhighriskphenotypes
AT hakonarsonhakon imputationoftpmtdefectiveallelesfortheidentificationofpatientswithhighriskphenotypes