A distal enhancer at risk locus 11q13.5 promotes suppression of colitis by Treg cells

Nasrallah, Rabab; Imianowski, Charlotte J.; Bossini‐Castillo, Lara; Grant, Francis M.; Dogan, Mikail; Placek, Lindsey; Kozhaya, Lina; Kuo, Tsong‐Teh; Sadiyah, Firas; Whiteside, Sarah; Mumbach, Maxwell R.; Glinos, Dafni A.; Vardaka, Panagiota; Whyte, Carly E.; Lozano, Teresa; Fujita, Toshitsugu; Fujii, Hodaka; Liston, Adrian; Andrews, Simon; Cozzani, Adeline; Yang, Jie; Mitra, Suman; Lugli, Enrico; Chang, Howard Y.; Unutmaz, Derya; Trynka, Gosia; Roychoudhuri, Rahul

doi:10.1038/s41586-020-2296-7

Cited by 46 publications

(43 citation statements)

References 45 publications

(18 reference statements)

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“…This positioning of the IPLs then allows for the recruitment of the WDR5-mixed lineage leukaemia protein 1 (MLL1) complex to these promoters to facilitate their H3K4me3 epigenetic priming (70). An example of long-range enhancer gene interactions in conveying autoimmune-disease risk in Treg cells has also recently been published (150). In this work a distal enhancer at the interfere with Treg activity in disease.…”

Section: Chromhmm Statesmentioning

confidence: 96%

3DFAACTS-SNP: Using regulatory T cell-specific epigenomics data to uncover candidate mechanisms of Type-1 Diabetes (T1D) risk

Liu

Sadlon

Wong

et al. 2020

Preprint

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Background: Genome-wide association and fine-mapping studies have enabled the discovery of single nucleotide polymorphisms (SNPs) and other variants that are significantly associated with many autoimmune diseases including type 1 diabetes (T1D). However, many of the SNPs lie in non-coding regions, limiting the identification of mechanisms that contribute to autoimmune disease progression. Methods: Autoimmunity results from a failure of immune tolerance, suggesting that regulatory T cells (Treg) are likely a significant point of impact for this genetic risk, as Treg are critical for immune tolerance. Focusing on T1D as a model of defective function of Treg in autoimmunity, we designed a SNPs filtering workflow called 3 Dimensional Functional Annotation of Accessible Cell Type Specific SNPs (3DFAACTS-SNP) that utilises overlapping profiles of Treg-specific epigenomic data (ATAC-seq, Hi-C and FOXP3-ChIP) to identify regulatory elements potentially driving the effect of variants associated with T1D, and the gene(s) that they control. Results: Using 3DFAACTS-SNP we identified 36 SNPs with plausible Treg-specific mechanisms of action contributing to T1D from 1,228 T1D fine-mapped variants, identifying 119 novel interacting regions resulting in the identification of 51 candidate target genes. We further demonstrated the utility of the workflow by applying it to three other fine-mapped/meta-analysed SNP autoimmune datasets, identifying 17 Treg-centric candidate variants and 35 interacting genes. Finally, we demonstrate the broad utility of 3DFAACTS-SNP for functional annotation of any genetic variation using all common (>10% allele frequency) variants from the Genome Aggregation Database (gnomAD). We identified 7,900 candidate variants and 3,245 candidate target genes, generating a list of potential sites for future T1D or autoimmune research. Conclusions: We demonstrate that it is possible to further prioritise variants that contribute to T1D based on regulatory function and illustrate the power of using cell type specific multi-omics datasets to determine disease mechanisms. The 3DFAACTS-SNP workflow can be customised to any cell type for which the individual datasets for functional annotation have been generated, giving broad applicability and utility.

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Section: Chromhmm Statesmentioning

confidence: 96%

3DFAACTS-SNP: Using regulatory T cell-specific epigenomics data to uncover candidate mechanisms of Type-1 Diabetes (T1D) risk

Liu

Sadlon

Wong

et al. 2020

Preprint

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“…For a number of genetic association signals and different traits, these studies allowed the identification of functional risk variants affecting the tissue-specific regulatory code [18]. To date, there are dozens of examples of GWAS-associated variants affecting regulatory functions in different cell types and disease traits, including some in T1D [48,55,56]. As an example, one recent study [56] focused on a GWAS signal located at human chromosome 11q13.5 and shared by several autoimmune diseases, including Crohn's disease, ulcerative colitis, T1D and asthma.…”

Section: Genetic Variants and The Non-coding Genomementioning

confidence: 99%

“…To date, there are dozens of examples of GWAS-associated variants affecting regulatory functions in different cell types and disease traits, including some in T1D [48,55,56]. As an example, one recent study [56] focused on a GWAS signal located at human chromosome 11q13.5 and shared by several autoimmune diseases, including Crohn's disease, ulcerative colitis, T1D and asthma. Integration of the genetic signal with cell-specific regulatory maps revealed that several associated variants in the locus interfere with the activation of a CD4 + regulatory T cell distal enhancer that induces the expression of LRRC32 and is required for T cell-mediated suppression of colitis.…”

Section: Genetic Variants and The Non-coding Genomementioning

confidence: 99%

The β-Cell Genomic Landscape in T1D: Implications for Disease Pathogenesis

2021

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Purpose of Review Type 1 diabetes (T1D) develops as a consequence of a combination of genetic predisposition and environmental factors. Combined, these events trigger an autoimmune disease that results in progressive loss of pancreatic β cells, leading to insulin deficiency. This article reviews the current knowledge on the genetics of T1D with a specific focus on genetic variation in pancreatic islet regulatory networks and its implication to T1D risk and disease development. Recent Findings Accumulating evidence suggest an active role of β cells in T1D pathogenesis. Based on such observation several studies aimed in mapping T1D risk variants acting at the β cell level. Such studies unravel T1D risk loci shared with type 2 diabetes (T2D) and T1D risk variants potentially interfering with β-cell responses to external stimuli. Summary The characterization of regulatory genomics maps of disease-relevant states and cell types can be used to elucidate the mechanistic role of β cells in the pathogenesis of T1D.

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“…A recent study attempted to characterize an intergenic SNP associated with increased risk for asthma, T1D, allergy, and Crohn's disease. 131 The SNP localizes in an enhancer region that influences expression of the LRRC32 gene, which encodes the protein glyco- and thereby regulate the speed and the overall strength of an immune response. 86,88 From these examples, we suggest that timing enhancers could be more broadly utilized to control the temporal dynamics of the immune system.…”

Section: Lrrc32mentioning

confidence: 99%

“…A recent study attempted to characterize an intergenic SNP associated with increased risk for asthma, T1D, allergy, and Crohn's disease 131 . The SNP localizes in an enhancer region that influences expression of the LRRC32 gene, which encodes the protein glycoprotein A repetitions predominant (GARP).…”

Section: Timing Enhancers In Diseasementioning

confidence: 99%

In search of lost time: Enhancers as modulators of timing in lymphocyte development and differentiation

Chu

Pease

Kueh

2021

Immunological Reviews

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A distal enhancer at risk locus 11q13.5 promotes suppression of colitis by Treg cells

Cited by 46 publications

References 45 publications

3DFAACTS-SNP: Using regulatory T cell-specific epigenomics data to uncover candidate mechanisms of Type-1 Diabetes (T1D) risk

3DFAACTS-SNP: Using regulatory T cell-specific epigenomics data to uncover candidate mechanisms of Type-1 Diabetes (T1D) risk

The β-Cell Genomic Landscape in T1D: Implications for Disease Pathogenesis

In search of lost time: Enhancers as modulators of timing in lymphocyte development and differentiation

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