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

Autor(es)

Zhou, Yitian ^[1] ; Dagli Hernandez, Carolina ^{[2, 1]} ; Lauschke, Volker M. ^[1]

Afiliação do(s) autor(es)

^[1] Karolinska Inst, Dept Physiol & Pharmacol, S-17177 Stockholm - Sweden

^[2] Univ Sao Paulo, Sch Pharmaceut Sci, Dept Clin & Toxicol Anal, BR-05508000 Sao Paulo - Brazil

• Tipo de documento: Artigo Científico
• Fonte: BRITISH JOURNAL OF CANCER; v. 123, n. 12, p. 1782-1789, DEC 8 2020.
• Citações Web of Science: 0

Resumo

Background Inter-individual differences in dihydropyrimidine dehydrogenase (DPYDencoding 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 analyseDPYDandTPMTgenetic variability based on sequencing data from 138,842 individuals across eight populations. Results The algorithm accurately predicted in vivo consequences ofDPYDandTPMTvariants (accuracy 91.4% compared to 95.3% in vitro). Further analysis showed high genetic complexity of DPD deficiency, advocating for sequencing-basedDPYDprofiling, whereas genotyping of four variants inTPMTwas 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 ofDPYDandTPMTvariability published to date with important implications for population-adjusted genetic profiling strategies of fluoropyrimidine and thiopurine risk factors and precision public health. (AU)

• Processo FAPESP: 19/19009-4 - Análise de predição in silico de funcionalidade de farmacogenes e desenvolvimento de um escore farmacogenético para pacientes com hipercolesterolemia familial
• Beneficiário: Carolina Dagli Hernandez
• Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - Doutorado Direto