Genome-wide association studies (GWAS) are a relatively new way to identify genes involved in an organism's traits. This method searches the genome for small variations, called single nucleotide polymorphisms (SNPs) that occur more frequently in organisms with a particular trait than in organisms without the trait. One use of GWAS is to identify SNPs associated with human traits. Each study can look at hundreds, thousands, or millions of SNPs at the same time. Data from GWAS show correlations between genetic variations and traits that are used to pinpoint genes that may contribute to developing the trait. Further research can identify if and how the genes may influence the trait.
Because genome-wide association studies examine SNPs across the genome, they represent a promising way to study traits in which many genetic variations contribute to the characteristics of an organism related to that trait. This approach has already identified SNPs related to several complex conditions including diabetes, heart abnormalities, Parkinson disease, and Crohn disease. Future genome-wide association studies may identify SNPs associated with other chronic diseases, as well as variations that affect a subject's response to certain drugs and influence interactions between a subject's genes and the environment.
GWAS commonly examine one trait at a time. Occasionally they examine several related traits with the hopes of increasing power; in such a setting, the traits are not generally smoothly varying in any way such as time or space. However, with the advent of wearables for health and the “quantified self” movement; the broad deployment of cheap sensors and the approaching ubiquity of electronic health records, abundant data from ubiquity of function-valued traits will be available for analysis by GWAS. Longitudinal traits are one example of function-valued traits—traits which can be viewed as a smooth function of some variable. For example, that variable could be time in a clinical history corresponding to a longitudinal trait, or it could be position in the genome corresponding to a spatial trait such as chromatin accessibility.