ABSTRACT
Genome-wide association studies (GWASs) have identified thousands of genetic variants associated with common polygenic traits. The candidate causal risk variants reside almost exclusively in noncoding regions of the genome and the underlying mechanisms remain elusive for most. Innovative approaches are necessary to understand their biological function. Multimarker analysis of genomic annotation (MAGMA) is a widely used program that nominates candidate risk genes by mapping single-nucleotide polymorphism (SNP) summary statistics from genome-wide association studies to gene bodies. We augmented MAGMA into chromatin-MAGMA (chromMAGMA), a novel method to nominate candidate risk genes based on the presence of risk variants within noncoding regulatory elements (REs). We applied chromMAGMA to a genetic susceptibility dataset for epithelial ovarian cancer (EOC), a rare gynecologic malignancy characterized by high mortality. Disease-specific RE landscapes were defined using H3K27ac chromatin immunoprecipitation-sequence data. This identified 155 unique candidate EOC risk genes across five EOC histotypes; 83% (105/127) of high-grade serous ovarian cancer risk genes had not previously been implicated in this EOC histotype. Risk genes nominated by chromMAGMA converged on mRNA splicing and transcriptional dysregulation pathways. chromMAGMA is a pipeline that nominates candidate risk genes through a gene regulation-focused approach and helps interpret the biological mechanism of noncoding risk variants in complex diseases.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
↵* Jointly directed the study