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PRSet: Pathway-based polygenic risk score analyses and software.

Shing Wan Choi1, Judit García-González1, Yunfeng Ruan2

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Summary
This summary is machine-generated.

Introducing pathway polygenic risk scores (PRSs) and the PRSet software, this study reveals a novel approach to understanding complex diseases. Pathway PRSs offer improved disease stratification and insights into genetic liability across genomic pathways.

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Area of Science:

  • Genetics and Bioinformatics
  • Computational Biology
  • Precision Medicine

Background:

  • Polygenic risk scores (PRSs) aggregate genome-wide risk alleles into a single genetic liability measure.
  • Current PRS methods can lose critical information due to the genome's functional substructure and disease heterogeneity.
  • Complex diseases may be underpinned by multiple genetic liabilities rather than a single genome-wide score.

Purpose of the Study:

  • To introduce a 'pathway polygenic' paradigm for disease risk assessment.
  • To present PRSet, a software tool for computing and analyzing pathway-based PRSs.
  • To evaluate the utility of pathway PRSs for pathway enrichment analysis and disease stratification.

Main Methods:

  • Developed PRSet software to calculate polygenic scores across genomic pathways for individuals.
  • Benchmarked PRSet for pathway enrichment analysis against established methods (MAGMA, LD score regression).
  • Assessed pathway PRS performance for disease stratification using a supervised approach, comparing against genome-wide PRSs (C+T, lassosum).

Main Results:

  • Pathway PRSs demonstrated comparable power to MAGMA and LD score regression for pathway enrichment with >10,000 individuals.
  • Pathway PRSs provide individual-level genetic liability estimates for each pathway, enabling new applications.
  • Pathway PRSs outperformed standard genome-wide PRSs in disease subtype classification in 20 out of 21 tested scenarios.

Conclusions:

  • Pathway PRSs offer a more nuanced understanding of complex disease genetic architecture.
  • PRSet facilitates the analysis of pathway-based genetic liabilities.
  • Pathway PRSs hold promise for identifying therapeutic targets, understanding disease heterogeneity, and advancing precision medicine.