Genetic and epigenetic fine mapping of causal autoimmune disease variants - Farh, Kyle Kai-How; Marson, Alexander; Zhu, Jiang; Kleinewietfeld, Markus; Housley, William J.; Beik, Samantha; Shoresh, Noam; Whitton, Holly; Ryan, Russell J. H.; Shishkin, Alexander A.; Hatan, Meital; Carrasco-Alfonso, Marlene J.; et al. (Nature (London), 2015)
Genome-wide association studies have identified loci underlying human diseases, but the causal nucleotide changes and mechanisms remain largely unknown. Here we developed a fine-mapping algorithm to identify candidate causal variants for 21 autoimmune diseases from genotyping data. We integrated these predictions with transcription and cis -regulatory element annotations, derived by mapping RNA and chromatin in primary immune cells, including resting and stimulated CD4 + T-cell subsets, regulatory T cells, CD8 + T cells, B cells, and monocytes. We find that ∼90% of causal variants are non-coding, with ∼60% mapping to immune-cell enhancers, many of which gain histone acetylation and transcribe enhancer-associated RNA upon immune stimulation. Causal variants tend to occur near binding sites for master regulators of immune differentiation and stimulus-dependent gene activation, but only 10–20% directly alter recognizable transcription factor binding motifs. Rather, most non-coding risk variants, including those that alter gene expression, affect non-canonical sequence determinants not well-explained by current gene regulatory models. Genome-wide association studies combined with data from epigenomic maps for immune cells have been used to fine-map causal variants for 21 autoimmune diseases; disease risk tends to be linked to single nucleotide polymorphisms in cell-type-specific enhancers, often in regions adjacent to transcription factor binding motifs. Gene variation in autoimmune diseases Hundreds of risk loci for autoimmunity have been identified previously in genome-wide association studies (GWASs), but the implicated loci comprise multiple variants in linkage disequilibrium and rarely alter protein-coding sequence, which complicates their interpretation. This study adopts a new approach for fine mapping causal genetic variants for 21 autoimmune diseases, applying a novel algorithm to GWAS-based loci and integrating genotypic data with epigenomic maps for specialized immune cells. The results implicate a very specific subset of enhancers involved in T-cell stimulation as causal determinants of autoimmune diseases.