Genome-wide association studies (GWAS) have made clear that single-nucleotide variants () that occur at multiple locations across the genome can be associated with a specific condition or trait, also known as a . Phenome-wide association studies (PheWAS) invert the idea of a by searching for phenotypes associated with specific SNVs across the range of thousands of human phenotypes, or the 鈥減henome鈥� (Figure). Analogous to GWAS, PheWAS have shown that specific genetic variations may be associated with multiple conditions and traits.

The key requirement for PheWAS is a data set that includes a broad range of phenotypes ascertained in large numbers of patients. The technique was developed with electronic health records (EHRs) linked to DNA databases^1-4 to find phenotypic associations with target SNVs. More recently, PheWAS has been used to analyze other types of data sets that include genetic information linked with extensive phenotype data. Example data sets include the UK Biobank, an epidemiologic cohort of 500鈥�000 individuals with dense phenotypic data obtained by standardized questionnaires and other phenotyping methods (including incorporation of EHR data), and data held by the genetic testing company 23andMe, in which phenotype information has been solicited by questionnaires from more than 10 million participants.⁵