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Imatinib is the tyrosine kinase inhibitor used as the gold standard for the treatment of Chronic Myeloid Leukemia. However, about 30% of patients do not respond well to this therapy. Variants in drug administration, distribution, metabolism and excretion (ADME) genes play an important role in drug resistance especially in admixed populations. We investigated 129 patients diagnosed with Chronic Myeloid Leukemia treated with imatinib as first choice therapy. The participants of the study are highly admixed, populations that exhibit genetic diversity and complexity due to the contributions of multiple ancestral groups. Thus, the aim of this work was to investigate the association of 30 SNVs in genes related to response to treatment with Imatinibe in CML. Our results indicated that for the rs2290573 of the ULK3 gene, patients with the recessive AA genotype are three times more likely to develop resistance over time (secondary resistance) (p = 0.019, OR = 3.19, IC 95%= 1.21-8.36). Finally, we performed interaction analysis between the investigated variants and found several associations between SNVs and secondary resistance. We concluded that the variant rs2290573 of the ULK3 gene may be relevant for predicting treatment response of CML with imatinib, as well as possible treatment resistance. The use of predictive biomarkers is an important tool for therapeutic choice of patients, improving their quality of life and treatment efficacy., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

piRNAs are a class of noncoding RNAs that perform functions in epigenetic regulation and silencing of transposable elements, a mechanism conserved among most mammals. At present, there are more than 30,000 known piRNAs in humans, of which more than 80% are derived from intergenic regions, and approximately 20% are derived from the introns and exons of pre-mRNAs. It was observed that the expression of the piRNA profile is specific in several organs, suggesting that they play functional roles in different tissues. In addition, some studies suggest that changes in regions that encode piRNAs may have an impact on their function. To evaluate the conservation of these regions and explore the existence of a seed region, SNP and INDEL variant rates were investigated in several genomic regions and compared to piRNA region variant rates. Thus, data analysis, data collection, cleaning, treatment, and exploration were implemented using the R programming language with the help of the RStudio platform. We found that piRNA regions are highly conserved after considering INDELs and do not seem to present an identifiable seed region after considering SNPs and INDEL variants. These findings may contribute to future studies attempting to determine how polymorphisms in piRNA regions can impact diseases.