Description: Single Nucleotide Polymorphism (SNP) is a variation at a single position in a DNA sequence among individuals of the same species. These changes can occur anywhere in the genome, including coding and non-coding regions, and are the most common form of genetic variation in humans. SNPs can influence how a person responds to certain medications, their susceptibility to diseases, and other phenotypic traits. Each SNP is defined by the presence of different nucleotides at a specific position, which can result in variations in the amino acid sequence of proteins or in the regulation of gene expression. Due to their abundance and stability, SNPs are valuable tools in genetic association studies and in identifying genetic markers for various health conditions. Additionally, their analysis is fundamental in personal genomics and personalized medicine, where the aim is to tailor medical treatments to the individual genetic characteristics of patients.
History: The concept of SNP was introduced in the 1980s, although its importance was not fully recognized until the 1990s when more advanced DNA sequencing technologies began to be developed. The Human Genome Project, completed in 2003, identified millions of SNPs in the human genome, enabling their use in genetic association studies. Since then, SNPs have been fundamental in genetic and medical research, helping to unravel the complexity of human diseases and variability in treatment responses.
Uses: SNPs are used in a variety of applications, including genetic association studies to identify disease markers, in pharmacogenomics to predict drug responses, and in the study of evolution and genetic diversity. They are also key tools in personalized medicine, where the aim is to tailor treatments to the individual genetic characteristics of patients.
Examples: An example of the use of SNPs is in cancer research, where SNPs associated with an increased risk of developing certain types of cancer have been identified. Another example is in pharmacogenomics, where specific SNPs can predict how a patient metabolizes a drug, allowing for dose adjustments to maximize efficacy and minimize side effects.
