Genetic and epigenetic fine mapping of causal autoimmune disease variants

• Published in: Nature (London) Vol. 518; no. 7539; pp. 337 - 343
• Main Authors: 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., 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.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 19.02.2015; Nature Publishing Group
• Subjects: 13; 13/31; 45; 45/15; 45/43; 45/91; 631/208/212/177; Autoimmune diseases; Autoimmune Diseases - genetics; Autoimmune Diseases - immunology; Autoimmune Diseases - pathology; Base Sequence; Causes of; Chromatin - genetics; Chromosome mapping; Consensus Sequence - genetics; Cytokines; Disease; Enhancer Elements, Genetic - genetics; Epigenesis, Genetic - genetics; Epigenetic inheritance; Epigenetics; Epigenomics; Gene expression; Gene loci; Genetic aspects; Genome-wide association studies; Genome-Wide Association Study; Haplotypes; Humanities and Social Sciences; Humans; Immune system; Methods; multidisciplinary; Mutation; Nucleotide Motifs; Organ Specificity; Polymorphism, Single Nucleotide - genetics; Science; Studies; T-Lymphocytes - immunology; T-Lymphocytes - metabolism; Transcription factors; Transcription Factors - metabolism
• ISSN: 0028-0836; 1476-4687; 1476-4687
• DOI: 10.1038/nature13835

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.