Genetic and epigenetic fine mapping of causal autoimmune disease variants

Kyle Kai-How Farh, Alexander Marson (), Jiang Zhu, Markus Kleinewietfeld, William J. Housley, Samantha Beik, Noam Shoresh, Holly Whitton, Russell J. H. Ryan, Alexander A. Shishkin, Meital Hatan, Marlene J. Carrasco-Alfonso, Dita Mayer, C. John Luckey, Nikolaos A. Patsopoulos, Philip L. De Jager, Vijay K. Kuchroo, Charles B. Epstein, Mark J. Daly, David A. Hafler and Bradley E. Bernstein
Additional contact information
Kyle Kai-How Farh: Broad Institute of MIT and Harvard
Alexander Marson: University of California
Jiang Zhu: Broad Institute of MIT and Harvard
Markus Kleinewietfeld: Broad Institute of MIT and Harvard
William J. Housley: Yale School of Medicine
Samantha Beik: Broad Institute of MIT and Harvard
Noam Shoresh: Broad Institute of MIT and Harvard
Holly Whitton: Broad Institute of MIT and Harvard
Russell J. H. Ryan: Broad Institute of MIT and Harvard
Alexander A. Shishkin: Broad Institute of MIT and Harvard
Meital Hatan: Broad Institute of MIT and Harvard
Marlene J. Carrasco-Alfonso: Brigham and Women’s Hospital and Harvard Medical School
Dita Mayer: Brigham and Women’s Hospital and Harvard Medical School
C. John Luckey: Brigham and Women’s Hospital and Harvard Medical School
Nikolaos A. Patsopoulos: Broad Institute of MIT and Harvard
Philip L. De Jager: Broad Institute of MIT and Harvard
Vijay K. Kuchroo: Center for Neurologic Diseases, Brigham and Women’s Hospital, Harvard Medical School
Charles B. Epstein: Broad Institute of MIT and Harvard
Mark J. Daly: Broad Institute of MIT and Harvard
David A. Hafler: Broad Institute of MIT and Harvard
Bradley E. Bernstein: Broad Institute of MIT and Harvard

Nature, 2015, vol. 518, issue 7539, 337-343

Abstract: Abstract 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.

Date: 2015
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DOI: 10.1038/nature13835

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