Endocrine-Exocrine Signaling Drives Obesity-Associated Pancreatic Ductal Adenocarcinoma.

Obesity is a major modifiable risk factor for pancreatic ductal adenocarcinoma (PDAC), yet how and when obesity contributes to PDAC progression is not well understood. Leveraging an autochthonous mouse model, we demonstrate a causal and reversible role for obesity in early PDAC progression, showing that obesity markedly enhances tumorigenesis, while genetic or dietary induction of weight loss intercepts cancer development. Molecular analyses of human and murine samples define microenvironmental consequences of obesity that foster tumorigenesis rather than new driver gene mutations, including significant pancreatic islet cell adaptation in obesity-associated tumors. Specifically, we identify aberrant beta cell expression of the peptide hormone cholecystokinin (Cck) in response to obesity and show that islet Cck promotes oncogenic Kras-driven pancreatic ductal tumorigenesis. Our studies argue that PDAC progression is driven by local obesity-associated changes in the tumor microenvironment and implicate endocrine-exocrine signaling beyond insulin in PDAC development.

A Multi-omic Integrative Scheme Characterizes Tissues of Action at Loci Associated with Type 2 Diabetes.

Resolving the molecular processes that mediate genetic risk remains a challenge because most disease-associated variants are non-coding and functional characterization of these signals requires knowledge of the specific tissues and cell-types in which they operate. To address this challenge, we developed a framework for integrating tissue-specific gene expression and epigenomic maps to obtain "tissue-of-action" (TOA) scores for each association signal by systematically partitioning posterior probabilities from Bayesian fine-mapping. We applied this scheme to credible set variants for 380 association signals from a recent GWAS meta-analysis of type 2 diabetes (T2D) in Europeans. The resulting tissue profiles underscored a predominant role for pancreatic islets and, to a lesser extent, adipose and liver, particularly among signals with greater fine-mapping resolution. We incorporated resulting TOA scores into a rule-based classifier and validated the tissue assignments through comparison with data from cis-eQTL enrichment, functional fine-mapping, RNA co-expression, and patterns of physiological association. In addition to implicating signals with a single TOA, we found evidence for signals with shared effects in multiple tissues as well as distinct tissue profiles between independent signals within heterogeneous loci. Lastly, we demonstrated that TOA scores can be directly coupled with eQTL colocalization to further resolve effector transcripts at T2D signals. This framework guides mechanistic inference by directing functional validation studies to the most relevant tissues and can gain power as fine-mapping resolution and cell-specific annotations become richer. This method is generalizable to all complex traits with relevant annotation data and is made available as an R package.

Inferring causal genes at type 2 diabetes GWAS loci through chromosome interactions in islet cells.

Background: Resolving causal genes for type 2 diabetes at loci implicated by genome-wide association studies (GWAS) requires integrating functional genomic data from relevant cell types. Chromatin features in endocrine cells of the pancreatic islet are particularly informative and recent studies leveraging chromosome conformation capture (3C) with Hi-C based methods have elucidated regulatory mechanisms in human islets. However, these genome-wide approaches are less sensitive and afford lower resolution than methods that target specific loci. Methods: To gauge the extent to which targeted 3C further resolves chromatin-mediated regulatory mechanisms at GWAS loci, we generated interaction profiles at 23 loci using next-generation (NG) capture-C in a human beta cell model (EndoC-ßH1) and contrasted these maps with Hi-C maps in EndoC-ßH1 cells and human islets and a promoter capture Hi-C map in human islets. Results: We found improvements in assay sensitivity of up to 33-fold and resolved ~3.6X more chromatin interactions. At a subset of 18 loci with 25 co-localised GWAS and eQTL signals, NG Capture-C interactions implicated effector transcripts at five additional genetic signals relative to promoter capture Hi-C through physical contact with gene promoters. Conclusions: High resolution chromatin interaction profiles at selectively targeted loci can complement genome- and promoter-wide maps.

TIGER: The gene expression regulatory variation landscape of human pancreatic islets.

Genome-wide association studies (GWASs) identified hundreds of signals associated with type 2 diabetes (T2D). To gain insight into their underlying molecular mechanisms, we have created the translational human pancreatic islet genotype tissue-expression resource (TIGER), aggregating >500 human islet genomic datasets from five cohorts in the Horizon 2020 consortium T2DSystems. We impute genotypes using four reference panels and meta-analyze cohorts to improve the coverage of expression quantitative trait loci (eQTL) and develop a method to combine allele-specific expression across samples (cASE). We identify >1 million islet eQTLs, 53 of which colocalize with T2D signals. Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identify eight cASE colocalizations, among which we found a T2D-associated SLC30A8 variant. We make all data available through the TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translates into therapeutic insight and precision medicine for T2D.

Analysis of Differentiation Protocols Defines a Common Pancreatic Progenitor Molecular Signature and Guides Refinement of Endocrine Differentiation.

Several distinct differentiation protocols for deriving pancreatic progenitors (PPs) from human pluripotent stem cells have been described, but it remains to be shown how similar the PPs are across protocols and how well they resemble their in vivo counterparts. Here, we evaluated three differentiation protocols, performed RNA and assay for transposase-accessible chromatin using sequencing on isolated PPs derived with these, and compared them with fetal human pancreas populations. This enabled us to define a shared transcriptional and epigenomic signature of the PPs, including several genes not previously implicated in pancreas development. Furthermore, we identified a significant and previously unappreciated cross-protocol variation of the PPs through multi-omics analysis and demonstrate how such information can be applied to refine differentiation protocols for derivation of insulin-producing beta-like cells. Together, our study highlights the importance of a detailed characterization of defined cell populations derived from distinct differentiation protocols and provides a valuable resource for exploring human pancreatic development.

Deep learning models predict regulatory variants in pancreatic islets and refine type 2 diabetes association signals.

Genome-wide association analyses have uncovered multiple genomic regions associated with T2D, but identification of the causal variants at these remains a challenge. There is growing interest in the potential of deep learning models - which predict epigenome features from DNA sequence - to support inference concerning the regulatory effects of disease-associated variants. Here, we evaluate the advantages of training convolutional neural network (CNN) models on a broad set of epigenomic features collected in a single disease-relevant tissue - pancreatic islets in the case of type 2 diabetes (T2D) - as opposed to models trained on multiple human tissues. We report convergence of CNN-based metrics of regulatory function with conventional approaches to variant prioritization - genetic fine-mapping and regulatory annotation enrichment. We demonstrate that CNN-based analyses can refine association signals at T2D-associated loci and provide experimental validation for one such signal. We anticipate that these approaches will become routine in downstream analyses of GWAS.

Genetic variant effects on gene expression in human pancreatic islets and their implications for T2D.

Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, key tissues and cell-types required for functional inference are absent from large-scale resources. Here we explore the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using data from 420 donors. We find: (a) 7741 cis-eQTLs in islets with a replication rate across 44 GTEx tissues between 40% and 73%; (b) marked overlap between islet cis-eQTL signals and active regulatory sequences in islets, with reduced eQTL effect size observed in the stretch enhancers most strongly implicated in GWAS signal location; (c) enrichment of islet cis-eQTL signals with T2D risk variants identified in genome-wide association studies; and (d) colocalization between 47 islet cis-eQTLs and variants influencing T2D or glycemic traits, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in disease relevant tissues.

T cell epigenetic remodeling and accelerated epigenetic aging are linked to long-term immune alterations in childhood cancer survivors.

BACKGROUND: Cancer treatments have substantially improved childhood cancer survival but are accompanied by long-term complications, notably chronic inflammatory diseases. We hypothesize that cancer treatments could lead to long-term epigenetic changes in immune cells, resulting in increased prevalence of inflammatory diseases in cancer survivors. RESULTS: To test this hypothesis, we established the epigenetic and transcriptomic profiles of immune cells from 44 childhood cancer survivors (CCS, > 16 years old) on full remission (> 5 years) who had received chemotherapy alone or in combination with total body irradiation (TBI) and hematopoietic stem cell transplant (HSCT). We found that more than 10 years post-treatment, CCS treated with TBI/HSCT showed an altered DNA methylation signature in T cell, particularly at genes controlling immune and inflammatory processes and oxidative stress. DNA methylation remodeling in T cell was partially associated with chronic expression changes of nearby genes, increased frequency of type 1 cytokine-producing T cell, elevated systemic levels of these cytokines, and over-activation of related signaling pathways. Survivors exposed to TBI/HSCT were further characterized by an Epigenetic-Aging-Signature of T cell consistent with accelerated epigenetic aging. To investigate the potential contribution of irradiation to these changes, we established two cell culture models. We identified that radiation partially recapitulated the immune changes observed in survivors through a bystander effect that could be mediated by circulating factors. CONCLUSION: Cancer treatments, in particular TBI/HSCT, are associated with long-term immune disturbances. We propose that epigenetic remodeling of immune cells following cancer therapy augments inflammatory- and age-related diseases, including metabolic complications, in childhood cancer survivors.

Electrophysiological properties of human beta-cell lines EndoC-ßH1 and -ßH2 conform with human beta-cells.

Limited access to human islets has prompted the development of human beta cell models. The human beta cell lines EndoC-ßH1 and EndoC-ßH2 are increasingly used by the research community. However, little is known of their electrophysiological and secretory properties. Here, we monitored parameters that constitute the glucose-triggering pathway of insulin release. Both cell lines respond to glucose (6 and 20 mM) with 2- to 3-fold stimulation of insulin secretion which correlated with an elevation of [Ca2+]i, membrane depolarisation and increased action potential firing. Similar to human primary beta cells, KATP channel activity is low at 1 mM glucose and is further reduced upon increasing glucose concentration; an effect that was mimicked by the KATP channel blocker tolbutamide. The upstroke of the action potentials reflects the activation of Ca2+ channels with some small contribution of TTX-sensitive Na+ channels. The repolarisation involves activation of voltage-gated Kv2.2 channels and large-conductance Ca2+-activated K+ channels. Exocytosis presented a similar kinetics to human primary beta cells. The ultrastructure of these cells shows insulin vesicles composed of an electron-dense core surrounded by a thin clear halo. We conclude that the EndoC-ßH1 and -ßH2 cells share many features of primary human ß-cells and thus represent a useful experimental model.

Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci.

Human genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D). However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed by Genome-Wide Association Studies (GWAS). We characterised patterns of chromatin accessibility (ATAC-seq, n = 17) and DNA methylation (whole-genome bisulphite sequencing, n = 10) in human islets, generating high-resolution chromatin state maps through integration with established ChIP-seq marks. We found enrichment of GWAS signals for T2D and fasting glucose was concentrated in subsets of islet enhancers characterised by open chromatin and hypomethylation, with the former annotation predominant. At several loci (including CDC123, ADCY5, KLHDC5) the combination of fine-mapping genetic data and chromatin state enrichment maps, supplemented by allelic imbalance in chromatin accessibility pinpointed likely causal variants. The combination of increasingly-precise genetic and islet epigenomic information accelerates definition of causal mechanisms implicated in T2D pathogenesis.

Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps.

We expanded GWAS discovery for type 2 diabetes (T2D) by combining data from 898,130 European-descent individuals (9% cases), after imputation to high-density reference panels. With these data, we (i) extend the inventory of T2D-risk variants (243 loci, 135 newly implicated in T2D predisposition, comprising 403 distinct association signals); (ii) enrich discovery of lower-frequency risk alleles (80 index variants with minor allele frequency <5%, 14 with estimated allelic odds ratio >2); (iii) substantially improve fine-mapping of causal variants (at 51 signals, one variant accounted for >80% posterior probability of association (PPA)); (iv) extend fine-mapping through integration of tissue-specific epigenomic information (islet regulatory annotations extend the number of variants with PPA >80% to 73); (v) highlight validated therapeutic targets (18 genes with associations attributable to coding variants); and (vi) demonstrate enhanced potential for clinical translation (genome-wide chip heritability explains 18% of T2D risk; individuals in the extremes of a T2D polygenic risk score differ more than ninefold in prevalence).

Ionizing Radiation Potentiates High-Fat Diet-Induced Insulin Resistance and Reprograms Skeletal Muscle and Adipose Progenitor Cells.

Exposure to ionizing radiation increases the risk of chronic metabolic disorders such as insulin resistance and type 2 diabetes later in life. We hypothesized that irradiation reprograms the epigenome of metabolic progenitor cells, which could account for impaired metabolism after cancer treatment. C57Bl/6 mice were treated with a single dose of irradiation and subjected to high-fat diet (HFD). RNA sequencing and reduced representation bisulfite sequencing were used to create transcriptomic and epigenomic profiles of preadipocytes and skeletal muscle satellite cells collected from irradiated mice. Mice subjected to total body irradiation showed alterations in glucose metabolism and, when challenged with HFD, marked hyperinsulinemia. Insulin signaling was chronically disrupted in skeletal muscle and adipose progenitor cells collected from irradiated mice and differentiated in culture. Epigenomic profiling of skeletal muscle and adipose progenitor cells from irradiated animals revealed substantial DNA methylation changes, notably for genes regulating the cell cycle, glucose/lipid metabolism, and expression of epigenetic modifiers. Our results show that total body irradiation alters intracellular signaling and epigenetic pathways regulating cell proliferation and differentiation of skeletal muscle and adipose progenitor cells and provide a possible mechanism by which irradiation used in cancer treatment increases the risk for metabolic disease later in life.

DNA methylation is altered in B and NK lymphocytes in obese and type 2 diabetic human.

OBJECTIVE: Obesity is associated with low-grade inflammation and the infiltration of immune cells in insulin-sensitive tissues, leading to metabolic impairment. Epigenetic mechanisms control immune cell lineage determination, function and migration and are implicated in obesity and type 2 diabetes (T2D). The aim of this study was to determine the global DNA methylation profile of immune cells in obese and T2D individuals in a cell type-specific manner. MATERIAL AND METHODS: Fourteen obese subjects and 11 age-matched lean subjects, as well as 12 T2D obese subjects and 7 age-matched lean subjects were recruited. Global DNA methylation levels were measured in a cell type-specific manner by flow cytometry. We validated the assay against mass spectrometry measures of the total 5-methylcytosine content in cultured cells treated with the hypomethylation agent decitabine (r=0.97, p<0.001). RESULTS: Global DNA methylation in peripheral blood mononuclear cells, monocytes, lymphocytes or T cells was not altered in obese or T2D subjects. However, analysis of blood fractions from lean, obese, and T2D subjects showed increased methylation levels in B cells from obese and T2D subjects and in natural killer cells from T2D patients. In these cell types, DNA methylation levels were positively correlated with insulin resistance, suggesting an association between DNA methylation changes, immune function and metabolic dysfunction. CONCLUSIONS: Both obesity and T2D are associated with an altered epigenetic signature of the immune system in a cell type-specific manner. These changes could contribute to the altered immune functions associated with obesity and insulin resistance.