RESUMEN

INTRODUCTION: Single nucleotide polymorphisms (SNPs) are pivotal in clinical genetics, serving to link genotypes with disease susceptibility and response to environmental factors, including pharmacogenetics. They also play a crucial role in population genetics for mapping the human genome and localizing genes. Despite their utility, challenges arise when molecular genetic studies yield insufficient or uninformative data, particularly for socially significant diseases. This study aims to address these gaps by proposing a method to predict allelic variants of SNPs. METHOD: Using quantitative PCR and analyzing body composition data from 150 patients with their voluntary informed consent, we employed IBM SPSS Statistics 29.0 for data analysis. Our prototype formula, exemplified by allelic variant ADRB2 (rs1042713) = 0.257 + 0.639 * allelic variant ADRB2 (rs1042714) - 0.314 * allelic variant ADRB3 (rs4994) + 0.191 * allelic variant PPARA (rs4253778) - 0.218 * allelic variant PPARD (rs2016520) + 0.027 * body weight + 0.00001 * body weight², demonstrates the feasibility of predicting SNP allelic variants. RESULTS: This method holds promise for diverse diseases, including those of significant social impact, due to its potential to streamline and economize molecular genetic research. Its ability to stratify disease risk in the absence of complete SNP data makes it particularly compelling for clinical and laboratory geneticists. CONCLUSION: However, its translation into clinical practice necessitates the establishment of a comprehensive SNP database, especially for frequently analyzed SNPs within the implementing institution.