- Farh, Kyle Kai-How;
- Marson, Alexander;
- Zhu, Jiang;
- Kleinewietfeld, Markus;
- Housley, William J;
- Beik, Samantha;
- Shoresh, Noam;
- Whitton, Holly;
- Ryan, Russell JH;
- Shishkin, Alexander A;
- Hatan, Meital;
- Carrasco-Alfonso, Marlene J;
- Mayer, Dita;
- Luckey, C John;
- Patsopoulos, Nikolaos A;
- De Jager, Philip L;
- Kuchroo, Vijay K;
- Epstein, Charles B;
- Daly, Mark J;
- Hafler, David A;
- Bernstein, Bradley E
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.