PheWAS-ME: a web-app for interactive exploration of multimorbidity patterns in PheWAS

Area of Science:

• Genomics and Bioinformatics
• Computational Biology
• Precision Medicine

Background:

• Electronic health records (EHRs) linked with DNA biobanks offer significant potential for biomedical research.
• Phenome-wide association studies (PheWAS) analyze genetic variants against clinical phenotypes in EHRs.
• Interpreting complex gene-disease associations, especially those involving comorbidities, is challenging with static PheWAS results.

Purpose of the Study:

• To introduce PheWAS-ME, an interactive dashboard for visualizing individual-level genotype and phenotype data alongside PheWAS results.
• To enable researchers to explore multimorbidity patterns and their associations with specific genetic variants.
• To enhance PheWAS analyses by providing tools for deeper investigation of clinical data.

Main Methods:

• Development of an interactive dashboard (PheWAS-ME) integrating genotype, phenotype, and PheWAS data.
• Side-by-side visualization of individual-level data and PheWAS summary statistics.
• Facilitation of exploration for multimorbidity patterns related to genetic variants.

Main Results:

• PheWAS-ME allows for the visualization of individual-level genotype and phenotype data.
• The dashboard facilitates the exploration of multimorbidity patterns within PheWAS analyses.
• Researchers can investigate associations between genetic variants and complex disease patterns.

Conclusions:

• PheWAS-ME enriches PheWAS analyses by providing interactive visualization of complex genetic and clinical data.
• The tool aids in understanding the influence of multimorbidity on gene-disease associations.
• This approach is expected to advance precision medicine research by illuminating intricate biological relationships.