Clinical Functional Assignment of TPMT and NUDT15 Alleles by the Clinical Pharmacogenetics Implementation Consortium Pharmacogene Curation Expert Panel
Aug 2026· Clinical pharmacology and therapy· 0 citations· 51 references
Medicine
TL;DR
The work presented here includes the first designation of decreased function alleles for both TPMT and NUDT15, reflecting new clinical data that demonstrate partial loss of enzymatic activity and reduced dose tolerance.
Abstract
The Clinical Pharmacogenetics Implementation Consortium (CPIC) TPMT/NUDT15 Pharmacogene Curation Expert Panel (PCEP) conducted a comprehensive review of clinical, laboratory, and computational evidence to determine the clinical function assignments for TPMT and NUDT15 star alleles. These genes are critical for the metabolism of thiopurines, which are widely used in the treatment of cancer and autoimmune disorders. Standardized allele function assignment is essential for predicting metabolizer phenotypes and pharmacogenetics‐guided thiopurine dosing. The work presented here includes the first designation of decreased function alleles for both TPMT and NUDT15, reflecting new clinical data that demonstrate partial loss of enzymatic activity and reduced dose tolerance. The panel also reclassified several alleles previously assigned uncertain or unknown function. The functional assignments were informed by a standardized framework incorporating clinical data, such as thiopurine tolerance and toxicity, as well as in vitro protein activity, ex vivo enzymatic measurements, and in silico variant effect prediction tools. These updates enhance the precision of genotype‐to‐phenotype mapping and support more personalized thiopurine therapy across diverse patient populations.
Personalized pharmacotherapy requires systematic consideration of genetic factors influencing drug efficacy and safety. The accumulation of large-scale whole-exome sequencing (WES) resources provides an opportunity to assess population frequencies of clinically significant pharmacogenetic variants; however, the a...
A. Buianova, V. Cheranev, A. Shmitko et al.· Human Genomics· 0 citations
This dimensionality dominates the data, and a supervised ESM-2 sequence baseline was benchmarked against the ESM1v zero-shot ensemble and AlphaMissense under position-based 5-fold cross-validation, together with three architectural extensions: AlphaFold structural features, multi-task learning across paired assays, and...
It is proposed that the strategic integration of genome-wide analyses, sequencing, multi-omics data, and hypothesis-driven genetic studies may accelerate the clinical adoption of pharmacogenetics and contribute to more effective precision medicine in psychiatry.
M. Pjevac, J. Bon, Vita Dolžan· Frontiers in Genetics· 0 citations
Assessment of several computational approaches using a dataset of pharmacogenomic variants with either clinical annotations or functional characterization by deep mutational scanning, with an additional focus on CYP2C9, a clinically relevant drug-metabolizing enzyme, indicates that computational models can complement i...
F. Pucci, Pauline Hermans, Matsvei Tsishyn et al.· bioRxiv· 0 citations
A pediatric PGx interpretation model that includes mandatory reporting of patient age, ontogenetic adjustment, evidence-level stratification, and multidisciplinary clinical assessment is proposed that includes mandatory reporting of patient age, ontogenetic adjustment, and multidisciplinary clinical assessment.
A. A. Buianova, V. Cheranev, M. I. Kuznetsov et al.· medRxiv· 0 citations
Overall, LP-WGS provides broader variant coverage and improved resolution for selected pharmacogenes but did not resolve all clinically important loci, and these findings support further evaluation of LP-WGS as a scalable PGx screening approach, especially where long-term genomic data reuse is a priority.
F. Hodel, C. Thorball, D. Haefliger et al.· medRxiv· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.