![]() ![]() These conditions are largely caused by extremely rare genetic variants that ultimately induce a detrimental change to protein function, which leads to the disease state. For example, a SNP with a minor allele ( ) frequency of 0.40 implies that 40% of a population has the allele versus the more common allele (the major allele), which is found in 60% of the population.Ĭommonly occurring SNPs lie in stark contrast to genetic variants that are implicated in more rare genetic disorders, such as cystic fibrosis. The frequency of a SNP is given in terms of the minor allele frequency or the frequency of the less common allele. SNPs typically have two alleles, meaning within a population there are two commonly occurring base-pair possibilities for a SNP location. SNPs are notably a type of common genetic variation many SNPs are present in a large proportion of human populations. SNPs are by far the most abundant form of genetic variation in the human genome. SNPs can have functional consequences, however, causing amino acid changes, changes to mRNA transcript stability, and changes to transcription factor binding affinity. For the purposes of genetic studies, SNPs are typically used as markers of a genomic region, with the large majority of them having a minimal impact on biological systems. SNPs are single base-pair changes in the DNA sequence that occur with high frequency in the human genome. The modern unit of genetic variation is the single nucleotide polymorphism or SNP. We focus here on the application of GWAS to common diseases that have a complex multifactorial etiology. The goal of this chapter is to introduce and review GWAS technology, study design and analytical strategies as an important example of translational bioinformatics. Genome-wide association studies, for better or for worse, have ushered in the exciting era of personalized medicine and personal genetic testing. The widespread availability of low-cost technology for measuring an individual's genetic background has been harnessed by businesses that are now marketing genetic testing directly to the consumer. This type of genetic test has given rise to a new field called personalized medicine that aims to tailor healthcare to individual patients based on their genetic background and other biological features. These results, and more recent validation studies, have led to genetic tests for warfarin dosing that can be used in a clinical setting. A recent GWAS revealed DNA sequence variations in several genes that have a large influence on warfarin dosing. Determining the appropriate dose for each patient is important and believed to be partly controlled by genes. For example, warfarin is a blood-thinning drug that helps prevent blood clots in patients. Pharmacogenetics has the goal of identifying DNA sequence variations that are associated with drug metabolism and efficacy as well as adverse effects. Accordingly, one of the most successful applications of GWAS has been in the area of pharmacology. While understanding the complexity of human health and disease is an important objective, it is not the only focus of human genetics. Understanding the biological basis of genetic effects will play an important role in developing new pharmacologic therapies. Not only were DNA sequence variations in this gene associated with AMD but the biological basis for the effect was demonstrated. One of the early successes of GWAS was the identification of the Complement Factor H gene as a major risk factor for age-related macular degeneration or AMD –. The ultimate goal of GWAS is to use genetic risk factors to make predictions about who is at risk and to identify the biological underpinnings of disease susceptibility for developing new prevention and treatment strategies. We will focus here on the genome-wide association study or GWAS that measures and analyzes DNA sequence variations from across the human genome in an effort to identify genetic risk factors for diseases that are common in the population. There are many different technologies, study designs and analytical tools for identifying genetic risk factors. A central goal of human genetics is to identify genetic risk factors for common, complex diseases such as schizophrenia and type II diabetes, and for rare Mendelian diseases such as cystic fibrosis and sickle cell anemia. ![]()
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