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Population-scale predictions of DPD and TPMT phenotypes using a quantitative pharmacogene-specific ensemble classifier

BACKGROUND: Inter-individual differences in dihydropyrimidine dehydrogenase (DPYD encoding DPD) and thiopurine S-methyltransferase (TPMT) activity are important predictors for fluoropyrimidine and thiopurine toxicity. While several variants in these genes are known to decrease enzyme activities, man...

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Autores principales: Zhou, Yitian, Dagli Hernandez, Carolina, Lauschke, Volker M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7722893/
https://www.ncbi.nlm.nih.gov/pubmed/32973300
http://dx.doi.org/10.1038/s41416-020-01084-0
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author Zhou, Yitian
Dagli Hernandez, Carolina
Lauschke, Volker M.
author_facet Zhou, Yitian
Dagli Hernandez, Carolina
Lauschke, Volker M.
author_sort Zhou, Yitian
collection PubMed
description BACKGROUND: Inter-individual differences in dihydropyrimidine dehydrogenase (DPYD encoding DPD) and thiopurine S-methyltransferase (TPMT) activity are important predictors for fluoropyrimidine and thiopurine toxicity. While several variants in these genes are known to decrease enzyme activities, many additional genetic variations with unclear functional consequences have been identified, complicating informed clinical decision-making in the respective carriers. METHODS: We used a novel pharmacogenetically trained ensemble classifier to analyse DPYD and TPMT genetic variability based on sequencing data from 138,842 individuals across eight populations. RESULTS: The algorithm accurately predicted in vivo consequences of DPYD and TPMT variants (accuracy 91.4% compared to 95.3% in vitro). Further analysis showed high genetic complexity of DPD deficiency, advocating for sequencing-based DPYD profiling, whereas genotyping of four variants in TPMT was sufficient to explain >95% of phenotypic TPMT variability. Lastly, we provided population-scale profiles of ethnogeographic variability in DPD and TPMT phenotypes, and revealed striking interethnic differences in frequency and genetic constitution of DPD and TPMT deficiency. CONCLUSION: These results provide the most comprehensive data set of DPYD and TPMT variability published to date with important implications for population-adjusted genetic profiling strategies of fluoropyrimidine and thiopurine risk factors and precision public health.
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spelling pubmed-77228932021-09-25 Population-scale predictions of DPD and TPMT phenotypes using a quantitative pharmacogene-specific ensemble classifier Zhou, Yitian Dagli Hernandez, Carolina Lauschke, Volker M. Br J Cancer Article BACKGROUND: Inter-individual differences in dihydropyrimidine dehydrogenase (DPYD encoding DPD) and thiopurine S-methyltransferase (TPMT) activity are important predictors for fluoropyrimidine and thiopurine toxicity. While several variants in these genes are known to decrease enzyme activities, many additional genetic variations with unclear functional consequences have been identified, complicating informed clinical decision-making in the respective carriers. METHODS: We used a novel pharmacogenetically trained ensemble classifier to analyse DPYD and TPMT genetic variability based on sequencing data from 138,842 individuals across eight populations. RESULTS: The algorithm accurately predicted in vivo consequences of DPYD and TPMT variants (accuracy 91.4% compared to 95.3% in vitro). Further analysis showed high genetic complexity of DPD deficiency, advocating for sequencing-based DPYD profiling, whereas genotyping of four variants in TPMT was sufficient to explain >95% of phenotypic TPMT variability. Lastly, we provided population-scale profiles of ethnogeographic variability in DPD and TPMT phenotypes, and revealed striking interethnic differences in frequency and genetic constitution of DPD and TPMT deficiency. CONCLUSION: These results provide the most comprehensive data set of DPYD and TPMT variability published to date with important implications for population-adjusted genetic profiling strategies of fluoropyrimidine and thiopurine risk factors and precision public health. Nature Publishing Group UK 2020-09-25 2020-12-08 /pmc/articles/PMC7722893/ /pubmed/32973300 http://dx.doi.org/10.1038/s41416-020-01084-0 Text en © The Author(s), under exclusive licence to Cancer Research UK 2020 https://creativecommons.org/licenses/by/4.0/Note This work is published under the standard license to publish agreement. After 12 months the work will become freely available and the license terms will switch to a Creative Commons Attribution 4.0 International (CC BY 4.0).
spellingShingle Article
Zhou, Yitian
Dagli Hernandez, Carolina
Lauschke, Volker M.
Population-scale predictions of DPD and TPMT phenotypes using a quantitative pharmacogene-specific ensemble classifier
title Population-scale predictions of DPD and TPMT phenotypes using a quantitative pharmacogene-specific ensemble classifier
title_full Population-scale predictions of DPD and TPMT phenotypes using a quantitative pharmacogene-specific ensemble classifier
title_fullStr Population-scale predictions of DPD and TPMT phenotypes using a quantitative pharmacogene-specific ensemble classifier
title_full_unstemmed Population-scale predictions of DPD and TPMT phenotypes using a quantitative pharmacogene-specific ensemble classifier
title_short Population-scale predictions of DPD and TPMT phenotypes using a quantitative pharmacogene-specific ensemble classifier
title_sort population-scale predictions of dpd and tpmt phenotypes using a quantitative pharmacogene-specific ensemble classifier
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7722893/
https://www.ncbi.nlm.nih.gov/pubmed/32973300
http://dx.doi.org/10.1038/s41416-020-01084-0
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