Multi-Cell-Type Openness-Weighted Association Studies for Trait-Associated Genomic Segments Prioritization.

Area of Science:

• Genomics
• Computational Biology
• Disease Genetics

Background:

• Openness-weighted association study (OWAS) uses predicted chromatin accessibility to prioritize genome-wide association study (GWAS) signals.
• Identifying cell types relevant to complex traits for OWAS is challenging, and many traits involve multiple cell types.

Purpose of the Study:

• To develop OWAS-joint, an efficient framework for prioritizing disease-associated genomic segments by aggregating predicted chromatin accessibility across multiple cell types.
• To enhance the biological interpretation of non-coding variants in complex diseases.

Main Methods:

• Developed OWAS-joint, a framework aggregating predicted chromatin accessibility across multiple cell types.
• Conducted simulation studies to compare OWAS-joint with the single-cell-type OWAS method.
• Applied OWAS-joint to six complex human traits.

Main Results:

• OWAS-joint demonstrated greater statistical power than OWAS in simulations.
• OWAS-joint segments explained higher or comparable heritability to OWAS segments.
• OWAS-joint segments showed high replication rates in independent cohorts.

Conclusions:

• OWAS-joint offers an advantage over single-cell-type OWAS for prioritizing disease-associated genomic segments.
• The method enhances biological interpretation of disease mechanisms, particularly for non-coding regions.