eSCAN: scan regulatory regions for aggregate association testing using whole-genome sequencing data

Area of Science:

• Genomics
• Statistical Genetics
• Bioinformatics

Background:

• Aggregate association testing in whole-genome sequencing (WGS) data often uses broad genomic windows, limiting biological interpretation.
• Existing methods may not effectively integrate functional genomics data to pinpoint regulatory regions driving associations.

Purpose of the Study:

• To introduce eSCAN (scan the enhancers), a novel method for genome-wide association testing.
• To leverage functional genomics data, like Hi-C, to predefine variant sets within putative enhancer regions.
• To improve statistical power and mechanistic understanding in WGS association studies.

Main Methods:

• eSCAN combines dynamic window selection (similar to SCANG) with the incorporation of putative regulatory regions.
• The method focuses variant set testing on enhancer regions identified through functional genomics data and annotation.
• Extensive simulation studies were conducted to evaluate eSCAN's performance.

Main Results:

• eSCAN demonstrated increased statistical power and improved mechanistic interpretation in simulations.
• Application to blood cell traits in NHLBI Trans-Omics for Precision Medicine WGS data identified more significant signals.
• eSCAN-identified signals were shorter, indicating higher resolution fine-mapping, and explained larger associated regions.

Conclusions:

• eSCAN offers a powerful approach for analyzing WGS data by prioritizing enhancer regions.
• The method enhances the ability to link genetic variants to specific regulatory elements and genes.
• eSCAN provides higher resolution fine-mapping and aids in understanding the biological basis of genetic associations.