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Genetic and Epigenetic Fine-Mapping of Causal Autoimmune Disease Variants

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 the...

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Detalles Bibliográficos
Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4336207/
https://www.ncbi.nlm.nih.gov/pubmed/25363779
http://dx.doi.org/10.1038/nature13835
Descripción
Sumario: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 noncoding, 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 noncoding risk variants, including those that alter gene expression, affect non-canonical sequence determinants not well-explained by current gene regulatory models.