A Method for Predicting Allelic Variants of Single Nucleotide Polymorphisms

Title:A Method for Predicting Allelic Variants of Single Nucleotide Polymorphisms

Volume: 24

Author(s): Ekaterina Evgenyevna Tyagunova*, Alexander Sergeevich Zakharov, Galina Valerievna Pavlova, Daria Alexandrovna Ogarkova, Natalia Alexandrovna Zhuchenko and Vladimir Alexeyevich Gushchin

Affiliation:

• Federal State Autonomous Educational Institution of Higher Education First Moscow State Medical University of the Ministry Healthcare of the Russian Federation Named After I. M. Sechenov (Sechenov University), Moscow, Russia
• Federal State Budgetary Scientific Institution 'Scientific Research Institute of Vaccines and Serums Named After I. I. Mechnikov,' Moscow, Russia

Keywords: Predictive model, SNP, ADRB2, SIRT1, PPARG, PPARA, PPARD, PPARGC1A.

Abstract:

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.

Cite this article as:

Tyagunova Evgenyevna Ekaterina*, Zakharov Sergeevich Alexander, Pavlova Valerievna Galina, Ogarkova Alexandrovna Daria, Zhuchenko Alexandrovna Natalia and Gushchin Alexeyevich Vladimir, A Method for Predicting Allelic Variants of Single Nucleotide Polymorphisms, Current Topics in Medicinal Chemistry 2024; 24 () . https://dx.doi.org/10.2174/0115680266328330240828040922