PheWAS - phenome-wide association studies
Current methods to identify gene-disease associations primarily rely on clinical trials or observational cohorts to identify patients. At Vanderbilt, we have used an EMR-linked DNA biobank called BioVU to derive case and controls populations using data within the EMR to define clinical phenotypes. Genetic data for these EMR-linked association studies are redeposited into BioVU for future EMR-linked studies. This has opened the possibility of "reverse GWAS" or "Phenome-wide association studies" (PheWAS).
PheWAS using ICD9 codes
Our initial studies in PheWAS have been performed using a custom-developed grouping of International Classification of Disease, 9th edition (ICD9) codes. These grouping loosely follow the 3-digit (category) and section groupings defined with the ICD9 code system itself, but vary to include, for example, all hypertension codes (401-405) as one grouping. Each custom PheWAS code group also has an associated control group that excludes other related conditions (e.g., a patient with psoriatic arthritis cannot be a control for rheumatoid arthritis). Such grouping are based on other similar work.
Performing PheWAS using ICD9 codes replicates previously known gene-disease associations for 4/7 diseases (see pubication). They were multiple sclerosis, rheumatoid arthritis, Crohn's disease, and ischemic heart disease.
The files necessary to perform PheWAS are available below:
- code translation file: This file groups ICD9 codes into "phewas codes" of like ICD9 codes. It also defines control ranges ("phewas_exclude_range") for each "phewas code".
- phewas.pl: A PERL script that takes as its input tab-delimited genotype files, a file containing all ICD9 files for an individual, and a file with race and gender for each individual. It has various options available in the header of the file.
PheWAS by Josh Denny, MD MS is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States License.
Users should reference: Denny JC, Ritchie MD, Basford M, Pulley J, Bastarache L, Brown-Gentry K, Wang D, Masys DR, Roden DM, Crawford DC. PheWAS: Demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations. Bioinformatics. 2010 Mar 24. [Epub ahead of print] PMID: 20335276