Leveraging Polygenic Functional Enrichment to Improve GWAS Power

Area of Science:

• Genetics
• Genomics
• Statistical Genetics

Background:

• Genome-Wide Association Studies (GWAS) are powerful for identifying genetic variants associated with complex traits.
• Incorporating functional genomics data can improve the power and precision of GWAS.
• Existing methods may not fully leverage diverse genomic annotations for association analysis.

Purpose of the Study:

• To develop and validate a novel method, FINDOR, for enhancing GWAS power using polygenic functional enrichment.
• To assess the performance of FINDOR in controlling false-positive rates and increasing the detection of associated loci.
• To evaluate the utility of FINDOR across various complex traits and diseases using large-scale genetic datasets.

Main Methods:

• Developed FINDOR, a method integrating coding, conserved, regulatory, and LD-related genomic annotations into GWAS.
• Utilized simulations with real genotypes to evaluate FINDOR's performance.
• Applied FINDOR to 27 complex traits and diseases from the UK Biobank interim release (N=130K).
• Replicated newly identified loci in independent datasets.
• Applied FINDOR to the full UK Biobank release (N=416K).

Main Results:

• FINDOR correctly controls the false-positive rate at null loci.
• Achieved a 9%-38% increase in detected independent associations at causal loci in simulations.
• Increased genome-wide significant loci by 13% on average across traits (20% for diseases) compared to unweighted p-values.
• Replicated additional loci with a significant replication slope (0.66-0.69).
• Detected an additional 583 GWAS loci in the full UK Biobank release.

Conclusions:

• Leveraging functional enrichment via FINDOR robustly increases GWAS power.
• FINDOR provides a statistically sound approach to integrate diverse genomic annotations for enhanced genetic discovery.
• The method demonstrates significant improvements in identifying associated loci for complex traits and diseases.