Genetic and Epigenetic Fine-Mapping of Causal Autoimmune Disease Variants

By K. Farh, A. Marson, Jiang Zhu, Markus Kleinewietfeld, William J. Housley, Samantha P. Beik, N. Shoresh, Holly J. Whitton, R. J. Ryan, Alexander A. Shishkin and 11 more. 2014

1,818 citations recorded by the source corpus.

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.

Subfields: Immunology, Molecular Biology

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Citations in the corpus

A SPECTRAL APPROACH INTEGRATING FUNCTIONAL GENOMIC ANNOTATIONS FOR CODING AND NONCODING VARIANTS (2016, background): “The shift from supervised (CADD, GWAVA) to unsupervised algorithms as discussed here reduces the dependence on existing databases of observed variants, previously characterized elements and existing models of mutation, and allows extensions to cell type/tissue specific scores [16, 17, 37, 40, 41, 42”
Genetic Drivers of Epigenetic and Transcriptional Variation in Human Immune Cells (2016, background): “…studies (GWAS) have contributed to expanding catalogs of implicated genes and pathways for many complex human diseases (Hindorff et al., 2009) and are beginning to shed light on shared and unique etiological and pathological components of disease (Farh et al., 2015; Jostins et al., 2012).”
Sequential regulatory activity prediction across chromosomes with convolutional neural networks (2017, methodology): “Having established meaningful signal in the predictions, we analyzed a set of 1170 loci associated with 40 autoimmune diseases and blood cell traits that were fine mapped using the linkage-based statistical method PICS (Farh et al. 2015) .”
Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases (2016, background): “These reference epigenomes, combined with other genomics data, have provided functional and causal insights about several human disease (De Jager et al., 2014; Farh et al., 2015; Yao, Tak, Berman, & Farnham, 2014).”
Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease (2017, positive): “(43) interrogated ChIP-seq data from ENCODE and found allele-specific binding of the AP-1 transcription factor to the major (C) allele in heterozygous cell lines and suggested that the T allele of rs17293632 increases risk of Crohn’s disease by disrupting AP-1 regulation of SMAD3 expression.”
An expanded view of complex traits: from polygenic to omnigenic (2017, background): “For example, risk variants for autoimmune diseases show particular enrichment in active chromatin regions of immune cells (Maurano et al.; 2012; Farh et al., 2015; Kundaje et al., 2015).”
Multiple Sclerosis Genomic Map implicates peripheral immune cells & microglia in susceptibility (2019, background): “Although the T cell component plays an important role, functional and epigenomic annotation studies have begun to suggest that other elements of the immune system may be involved as well (7, 8).”
Primary sclerosing cholangitis - a comprehensive review. (2017, background): “The main outcome of PSC genetic studies has been the positioning of PSC as an autoimmune disease (82).”