R PheWAS: data analysis and plotting tools for phenome-wide association studies in the R environment

Area of Science:

• Genetics
• Bioinformatics
• Computational Biology

Background:

• Phenome-wide association studies (PheWAS) are crucial for identifying genetic associations with various phenotypes.
• Existing PheWAS methods can be enhanced for broader applicability and improved analytical flexibility.

Purpose of the Study:

• To present a novel R package implementation for performing PheWAS.
• To enable users to translate International Classification of Diseases, Ninth Revision (ICD-9) codes into PheWAS case and control groups.
• To facilitate the analysis of genetic variants and phenotypes, including continuous measures, with covariate adjustments.

Main Methods:

• The study utilized an R package for PheWAS analysis.
• The package allows for the translation of ICD-9 codes to PheWAS cohorts.
• Analyses were performed on a known genetic association (rs3135388) and a novel continuous phenotype (maximum white blood cell count).

Main Results:

• The PheWAS analysis successfully replicated known associations for the genetic variant rs3135388, near HLA-DRB, with greater significance than the original study.
• A novel PheWAS using maximum white blood cell count (WBC) as a continuous measure identified expected associations with infections, myeloproliferative diseases, and anemia.
• The results validate the performance of the improved classification scheme and the versatility of the PheWAS package.

Conclusions:

• The developed R package provides a robust and flexible platform for conducting Phenome-wide association studies.
• This implementation enhances the ability to discover and replicate genetic associations across a wide range of phenotypes.
• The tool supports both binary and continuous phenotype analyses, offering valuable insights into genotype-phenotype relationships.