High-resolution DNA accessibility profiles increase the discovery and interpretability of genetic associations

Abstract

Genetic risk for common autoimmune diseases is influenced by hundreds of small effect, mostly non-coding variants, enriched in regulatory regions active in adaptive-immune cell types. DNaseI hypersensitivity sites (DHSs) are a genomic mark for regulatory DNA. Here, we generated a single DHSs annotation from fifteen deeply sequenced DNase-seq experiments in adaptive-immune as well as non-immune cell types. Using this annotation we quantified accessibility across cell types in a matrix format amenable to statistical analysis, deduced the subset of DHSs unique to adaptive-immune cell types, and grouped DHSs by cell-type accessibility profiles. Measuring enrichment with cell-type-specific TF binding sites as well as proximal gene expression and function, we show that accessibility profiles grouped DHSs into coherent regulatory functions. Using the adaptive-immune-specific DHSs as input (0.37% of genome), we associated DHSs to six autoimmune diseases with GWAS data. Associated loci showed higher replication rates when compared to loci identified by GWAS or by considering all DHSs, allowing the additional discovery of 327 loci (FDR<0.005) below typical GWAS significance threshold, 52 of which are novel and replicating discoveries. Finally, we integrated DHS associations from six autoimmune diseases, using a network model (bird-eye view) and a regulatory Manhattan plot schema (per locus). Taken together, we described and validated a strategy to leverage finely resolved regulatory priors, enhancing the discovery, interpretability, and resolution of genetic associations, and providing actionable insights for follow up work.