Research characterizes allelic variability in B-cell acute lymphoblastic leukemia children, suggesting preemptive genotyping to reduce treatment toxicity.
Objective To characterize the allelic and diplotype variability of TPMT and NUDT15 in pediatric patients with B-cell acute lymphoblastic leukemia from the central-southern region of Mexico. Methods Samples from 275 pediatric B-cell acute lymphoblastic leukemia patients were analyzed. Next-generation sequencing was used for TPMT and NUDT15 genotyping. Alleles and diplotypes were assessed according to the Clinical Pharmacogenetics Implementation Consortium guidelines. Their geographic distribution was compared across Mexican states and global populations. In-silico analyses were conducted to assess the structural and functional impact of TPMT variants not associated with star alleles. Results The wild-type *1 allele, associated with normal enzymatic activity, was predominant in both genes: TPMT (94.15%) and NUDT15 (90.45%). TPMT showed greater allelic diversity compared with previous studies in Mexican populations. Alleles conferring absent or indeterminate enzymatic activity in TPMT were distributed across six diplotypes (11.62%), with *3A allele (4.73%) and *1 / *3A diplotype (9.45%) being the most frequent. Additionally, two unclassified TPMT variants, p.G126A and p.D137Y, were identified. For NUDT15 , three non-wild-type diplotypes were observed (19.09%), with the *2 allele (6.74%) and *1* / 2 diplotype (13.48%) being the most prevalent. Conclusion Approximately 28% of patients carried TPMT and/or NUDT15 variants associated with non-wild-type enzymatic activity, increasing the risk of mercaptopurine-induced myelotoxicity. Preemptive genotyping is essential to reduce toxicity, optimize treatment, and advance precision medicine in this population. Additionally, the two TPMT variants p.G126A and p.D137Y, currently not classified within Clinical Pharmacogenetics Implementation Consortium-defined star alleles, highlight the need for functional validation and potential clinical classification to improve pharmacogenetic interpretation in diverse populations.
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García-Solorio et al. (2026) studied this question.
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