Phenome-wide association study

In genetics and genetic epidemiology, a phenome-wide association study, abbreviated PheWAS, is a study design in which the association between single-nucleotide polymorphisms or other types of DNA variants is tested across a large number of different phenotypes.[1] The aim of PheWAS studies (or PheWASs) is to examine the causal linkage between known sequence differences and any type of trait, including molecular, biochemical, cellular, and especially clinical diagnoses and outcomes.[2][3][4] It is a complementary approach to the genome-wide association study, or GWAS, methodology.[5] A fundamental difference between GWAS and PheWAS designs is the direction of inference: in a PheWAS it is from exposure (the DNA variant) to many possible outcomes, that is, from SNPs to differences in phenotypes and disease risk. In a GWAS, the polarity of analysis is from one or a few phenotypes to many possible DNA variants.[6] The approach has proven useful in rediscovering previously reported genotype-phenotype associations,[2][7] as well as in identifying new ones.[8]

The PheWAS approach was originally developed due to the widespread availability of both anonymized human clinical electronic health record (EHR) data and matched genotype data. At the same time massive genome and phenome data sets for model organisms were being assembled that also proved effective for PheWAS.[9] PheWASs have also been conducted using data from existing epidemiological studies.[6] In 2010, a proof-of-concept PheWAS study was published based on EHR billing codes from a single study site.[10] Though this study was generally underpowered, its results suggested the potential existence of new associations between multiple phenotypes, possibly due to a common underlying cause. As of 2016, this study is the oldest PheWAS in the EHR-linked eMERGE database.[6] This paper also coined the abbreviation "PheWAS".[11] As of 2019, PheWAS in the EHR has been conducted using ICD-9-CM,[12] ICD-10, and ICD-10-CM[13] diagnosis codes.