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

Yitian Zhou,Volker M Lauschke,Carolina Dagli Hernandez

doi:10.1038/s41416-020-01084-0

Yitian Zhou, Volker M Lauschke + Show 1 more

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https://doi.org/10.1038/s41416-020-01084-0

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BackgroundInter-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.MethodsWe 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.ResultsThe 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.ConclusionThese 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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Inter-individual differences in dihydropyrimidine dehydrogenase (DPYD encoding DPD) and thiopurine Smethyltransferase (TPMT) activity are important predictors for fluoropyrimidine and thiopurine toxicity
Using all variations with known in vivo consequences as benchmark data set, we show that our pharmacogenetically trained ensemble classifier substantially outperforms all previous non-gene-specific prediction methods and achieved predictive accuracy similar to in vitro experiments
Benchmarking of the ADME prediction framework on DPYD and TPMT variants with known in vivo consequences To test the predictive power of the ADMEoptimised prediction framework (APF) algorithm, we first defined a gold-standard data set for DPYD and TPMT that included all variants with well-characterised functional effects in vivo in humans

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Inter-individual differences in dihydropyrimidine dehydrogenase (DPYD encoding DPD) and thiopurine Smethyltransferase (TPMT) activity are important predictors for fluoropyrimidine and thiopurine toxicity. 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. Genetic profiling has identified a multitude of variations that can guide selection and dosing of chemotherapeutic drugs.[1] Two of the most important examples of such pharmacogenetic biomarkers that have transitioned from research into clinical practice are germline variations in the dihydropyrimidine dehydrogenase (DPYD encoding DPD) and thiopurine Smethyltransferase (TPMT) genes.[2,3,4]. Recent meta-analyses confirmed robust associations of DPYD I560S, D949V as well as of the intronic splice variant rs75017182 and the associated haplotype HapB3 with fluoropyrimidine toxicity,[8,9,10] and prospective testing for these variants followed by genotype-guided upfront dose adjustments significantly increased patient safety.[11,12,13]

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