Pancreatic islet enhancer clusters enriched in type 2 diabetes risk-associated variants

Abstract

Type 2 diabetes affects over 300 million people, causing severe complications and premature death, yet the underlying molecular mechanisms are largely unknown. Pancreatic islet dysfunction is central for type 2 diabetes pathogenesis, and therefore understanding islet genome regulation could provide valuable mechanistic insights. We have now mapped and examined the function of human islet cis-regulatory networks. We identify genomic sequences that are targeted by islet transcription factors to drive islet-specific gene activity, and show that most such sequences reside in clusters of enhancers that form physical 3D chromatin domains. We find that sequence variants associated with type 2 diabetes and fasting glycemia are enriched in these clustered islet enhancers, and identify trait-associated variants that disrupt DNA-binding and islet enhancer activity. Our studies illustrate how islet transcription factors interact functionally with the epigenome, and provide systematic evidence that dysregulation of islet enhancers is relevant to the mechanisms underlying type 2 diabetes.

Genetic architecture of type 2 diabetes

“…We jointly modeled genetic association and genomic annotation data at T2D GWAS loci using fgwas 38 . Consistent with previous reports 34,35 , associated variants were enriched in coding exons, transcription factor binding sites, and enhancers active in pancreatic islets and adipose tissue (Extended Data Fig. 10).…”

“…Genomic maps of chromatin state or transcription factor binding [32][33][34][35] have been used to prioritize causal variants within credible sets 36,37 . We jointly modeled genetic association and genomic annotation data at T2D GWAS loci using fgwas 38 .…”

10 Years of GWAS Discovery: Biology, Function, and Translation

“…66 The advent of sequence-based -omic analyses have been transformative by allowing functional analyses of risk variants to be pursued on the same genome scale (which has fueled their discovery) and allowing mechanistic inferences to be based on the behavior of the full set of risk loci for a given trait. 67 The maps of regulatory annotations and connections in disease-relevant tissues, generated by projects such as ENCODE, 68 Epigenome RoadMap, 69 and GTEx, 70 have been crucial to interpretation of the non-coding variants that account for the majority of GWAS-identified risk alleles. Tissue-specific resources could become increasingly important, and for neuro-psychiatric disorders in particular, appropriate human brain resources are essential.…”

“…75,80 However, as increasingly diverse populations are genotyped and sequenced, more ethnic-specific alleles 82 From GWAS to Biology. Regulatory information on the key tissues of insulin action (fat, muscle, and liver) 82,83 and equivalent data from pancreatic islet material 67,84 have provided compelling evidence that the variants most strongly associated with T2D (as well as fasting glucose and other related quantitative traits) are preferentially located at active enhancers (particularly stretch enhancers) in pancreatic islets 67,84 and, to a lesser extent, at enhancers active in fat, muscle, and liver. 83,85 Increasing refinement of regulatory annotation has brought more precise localization of these global regulatory effects, for example, emphasizing specific transcription factor genes (such as FOXA2 [MIM: 600288]).…”

Epigenetic dysregulation in pancreatic islets and pathogenesis of type 2 diabetes

“…Integration of their WGBS data with histone modification data generated in human islets by the Roadmap Epigenomics Consortium4 showed that histone modifications associated with active chromatin correlated with a lower degree of methylation (12% for histone H3 lysine 9 acetylation and 8% for histone H3 lysine 4 trimethylation), whereas those associated with repressive chromatin had a higher degree of methylation (50% for histone H3 lysine 27 trimethylation and 80% for histone H3 lysine 9 trimethylation). In addition, combining the WGBS data with published chromatin immunoprecipitation assays with sequencing data5 showed that binding sites of islet‐specific transcription factors ( PDX1 , FOXA2 , NKX6.1 and NKX2.2 ) had a lower degree of methylation (21%–44%). Based on the WGBS data and ribonucleic acid‐sequencing data obtained from the same islet samples, they investigated the relationship between DNA methylation and gene expression levels.…”