Pharmacogenomics in Diabetes: Population-Specific Insights from Colombia

<b>Background:</b> Pharmacogenomics offers critical insights into interindividual variability in drug response, especially in complex diseases such as diabetes mellitus. However, most pharmacogenomic evidence is derived from populations of European ancestry, limiting its applicability in admixed and underrepresented populations. In Colombia, the lack of population-specific data hampers the implementation of precision medicine strategies in diabetes care. The aim of this study was to identify pharmacogenomic variants significantly associated with diabetes and exhibiting differential allele frequencies between Colombian populations of African and European ancestry. <b>Methods</b>: We extracted 115 variant annotations related to diabetes from PharmGKB and filtered them for statistical significance and availability of allele frequency data. Fourteen single-nucleotide polymorphisms (SNPs) were compared across five Colombian populations using the CÓDIGO genomic diversity database. Principal component analysis (PCA) was performed to assess genetic clustering, and Pearson correlation coefficients were used to assess pharmacogenomic similarity. <b>Results</b>: PCA revealed distinct genetic clustering patterns that aligned with geographical distribution and ancestral origins. Pharmacogenomic divergence was observed between African and European ancestry groups in Colombia, with certain SNPs (e.g., rs8192675-C for metformin, rs7754840-C for DPP-4 inhibitors) showing 2- to 3-fold higher frequency in African ancestry populations. The bibliometric analysis revealed that 76.1% of studies originated from high-income countries and 68.4% of participants were of European ancestry. No studies originated from Africa or low-income countries. <b>Conclusions</b>: Marked ancestry-based differences in pharmacogenomic variant frequencies in Colombian populations may impact drug efficacy and risk of diabetes. The global literature shows a strong geographic and economic bias, underscoring the need for inclusive, population-specific pharmacogenomic research. These findings offer a foundation for implementing precision diabetes therapies in Latin America and advancing equitable genomic medicine.