CPM Blog

This package contains methods for performing PheWAS. Please contact PheWAS@vumc.org. if you encounter any errors or apparent bugs. The documentation is done natively in R. The command ?PheWAS once the package is loaded will direct you to the package description, including references to each function and an example. The command vignette("PheWAS-package") will display the package vignette with further "How to's".

PheWAS using ICD9 codes Our EMR-based PheWAS uses 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 Graves disease cannot be a control for thyroiditis).    

Methods to identify gene-disease associations primarily rely on clinical trials or observational cohorts and, more recently, Electronic Medical Record-linked DNA Biobanks.  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). 

MEDI (MEDication Indication) is an ensemble medication indication resource for primary and secondary uses of electronic medical record (EMR) data.  MEDI was created based on multiple commonly used medication resources (RxNorm, MedlinePlus, SIDER 2, and Wikipedia ) and by leveraging both ontology and natural language processing (NLP) techniques.