Transcript Expression Data from Human Islets Links Regulatory Signals from Genome-Wide Association Studies for Type 2 Diabetes and Glycemic Traits to Their Downstream Effectors

Fusion pore in exocytosis: More than an exit gate? A β-cell perspective

Secretory vesicle exocytosis is a fundamental biological event and the process by which hormones (like insulin) are released into the blood. Considerable progress has been made in understanding this precisely orchestrated sequence of events from secretory vesicle docked at the cell membrane, hemifusion, to the opening of a membrane fusion pore. The exact biophysical and physiological regulation of these events implies a close interaction between membrane proteins and lipids in a confined space and constrained geometry to ensure appropriate delivery of cargo. We consider some of the still open questions such as the nature of the initiation of the fusion pore, the structure and the role of the Soluble N-ethylmaleimide-sensitive-factor Attachment protein REceptor (SNARE) transmembrane domains and their influence on the dynamics and regulation of exocytosis. We discuss how the membrane composition and protein-lipid interactions influence the likelihood of the nascent fusion pore forming. We relate these factors to the hypothesis that fusion pore expansion could be affected in type-2 diabetes via changes in disease-related gene transcription and alterations in the circulating lipid profile. Detailed characterisation of the dynamics of the fusion pore in vitro will contribute to understanding the larger issue of insulin secretory defects in diabetes.

Disentangling the Role of Melatonin and its Receptor MTNR1B in Type 2 Diabetes: Still a Long Way to Go?

PURPOSE OF REVIEW

Type 2 diabetes (T2D) is a complex genetic metabolic disorder. T2D heritability has been estimated around 40-70%. In the last decade, exponential progress has been made in identifying T2D genetic determinants, through genome-wide association studies (GWAS). Among single-nucleotide polymorphisms mostly associated with T2D risk, rs10830963 is located in the MTNR1B gene, encoding one of the two receptors of melatonin, a neurohormone involved in circadian rhythms. Subsequent studies aiming to disentangle the role of MTNR1B in T2D pathophysiology led to controversies. In this review, we will tackle them and will try to give some directions to get a better view of MTNR1B contribution to T2D pathophysiology.

RECENT FINDINGS

Recent studies either based on genetic/genomic analyses, clinical/epidemiology data, functional analyses at rs10830963 locus, insulin secretion assays in response to melatonin (involving or not MTNR1B) or animal model analyses have led to strong controversies at each level of interpretation. We discuss possible caveats in these studies and present ways to go beyond these issues, towards a better understanding of T2D molecular mechanisms, keeping in mind that melatonin is a versatile hormone and regulates many functions via its primary role in the body clock.

Gene Editing and Human Pluripotent Stem Cells: Tools for Advancing Diabetes Disease Modeling and Beta-Cell Development

PURPOSE OF REVIEW

This review will focus on the multiple approaches to gene editing and address the potential use of genetically modified human pluripotent stem cell-derived beta cells (SC-β) as a tool to study human beta-cell development and model their function in diabetes. We will explore how new variations of CRISPR/Cas9 gene editing may accelerate our understanding of beta-cell developmental biology, elucidate novel mechanisms that establish and regulate beta-cell function, and assist in pioneering new therapeutic modalities for treating diabetes.

RECENT FINDINGS

Improvements in CRISPR/Cas9 target specificity and homology-directed recombination continue to advance its use in engineering stem cells to model and potentially treat disease. We will review how CRISPR/Cas9 gene editing is informing our understanding of beta-cell development and expanding the therapeutic possibilities for treating diabetes and other diseases. Here we focus on the emerging use of gene editing technology, specifically CRISPR/Cas9, as a means of manipulating human gene expression to gain novel insights into the roles of key factors in beta-cell development and function. Taken together, the combined use of SC-β cells and CRISPR/Cas9 gene editing will shed new light on human beta-cell development and function and accelerate our progress towards developing new therapies for patients with diabetes.

Genetic aetiology of glycaemic traits: approaches and insights

Glycaemic traits such as fasting and post-challenge glucose and insulin measures, as well as glycated haemoglobin (HbA1c), are used to diagnose and monitor diabetes. These traits are risk factors for cardiovascular disease even below the diabetic threshold, and their study can additionally yield insights into the pathophysiology of type 2 diabetes. To date, a diverse set of genetic approaches have led to the discovery of over 97 loci influencing glycaemic traits. In this review, we will focus on recent advances in the genetic aetiology of glycaemic traits, and the resulting biological insights. We will provide a brief overview of results ranging from common, to low- and rare-frequency variant-trait association studies, studies leveraging the diversity across populations, and studies harnessing the power of genetic and genomic approaches to gain insights into the biological underpinnings of these traits.

Diverse type 2 diabetes genetic risk factors functionally converge in a phenotype-focused gene network

Type 2 Diabetes (T2D) constitutes a global health burden. Efforts to uncover predisposing genetic variation have been considerable, yet detailed knowledge of the underlying pathogenesis remains poor. Here, we constructed a T2D phenotypic-linkage network (T2D-PLN), by integrating diverse gene functional information that highlight genes, which when disrupted in mice, elicit similar T2D-relevant phenotypes. Sensitising the network to T2D-relevant phenotypes enabled significant functional convergence to be detected between genes implicated in monogenic or syndromic diabetes and genes lying within genomic regions associated with T2D common risk. We extended these analyses to a recent multiethnic T2D case-control exome of 12,940 individuals that found no evidence of T2D risk association for rare frequency variants outside of previously known T2D risk loci. Examining associations involving protein-truncating variants (PTV), most at low population frequencies, the T2D-PLN was able to identify a convergent set of biological pathways that were perturbed within four of five independent T2D case/control ethnic sets of 2000 to 5000 exomes each. These same pathways were found to be over-represented among both known monogenic or syndromic diabetes genes and genes within T2D-associated common risk loci. Our study demonstrates convergent biology amongst variants representing different classes of T2D genetic risk. Although convergence was observed at the pathway level, few of the contributing genes were found in common between different cohorts or variant classes, most notably between the exome variant sets which suggests that future rare variant studies may be better focusing their power onto a single population of recent common ancestry.

Alpha TC1 and Beta-TC-6 genomic profiling uncovers both shared and distinct transcriptional regulatory features with their primary islet counterparts

Alpha TC1 (αTC1) and Beta-TC-6 (βTC6) mouse islet cell lines are cellular models of islet (dys)function and type 2 diabetes (T2D). However, genomic characteristics of these cells, and their similarities to primary islet alpha and beta cells, are undefined. Here, we report the epigenomic (ATAC-seq) and transcriptomic (RNA-seq) landscapes of αTC1 and βTC6 cells. Each cell type exhibits hallmarks of its primary islet cell counterpart including cell-specific expression of beta (e.g., Pdx1) and alpha (e.g., Arx) cell transcription factors (TFs), and enrichment of binding motifs for these TFs in αTC1/βTC6 cis-regulatory elements. αTC1/βTC6 transcriptomes overlap significantly with the transcriptomes of primary mouse/human alpha and beta cells. Our data further indicate that ATAC-seq detects cell-specific regulatory elements for cell types comprising ≥ 20% of a mixed cell population. We identified αTC1/βTC6 cis-regulatory elements orthologous to those containing type 2 diabetes (T2D)-associated SNPs in human islets for 33 loci, suggesting these cells’ utility to dissect T2D molecular genetics in these regions. Together, these maps provide important insights into the conserved regulatory architecture between αTC1/βTC6 and primary islet cells that can be leveraged in functional (epi)genomic approaches to dissect the genetic and molecular factors controlling islet cell identity and function.

A Type 2 Diabetes-Associated Functional Regulatory Variant in a Pancreatic Islet Enhancer at the ADCY5 Locus

Molecular mechanisms remain unknown for most type 2 diabetes genome-wide association study identified loci. Variants associated with type 2 diabetes and fasting glucose levels reside in introns of ADCY5, a gene that encodes adenylate cyclase 5. Adenylate cyclase 5 catalyzes the production of cyclic AMP, which is a second messenger molecule involved in cell signaling and pancreatic β-cell insulin secretion. We demonstrated that type 2 diabetes risk alleles are associated with decreased ADCY5 expression in human islets and examined candidate variants for regulatory function. rs11708067 overlaps a predicted enhancer region in pancreatic islets. The type 2 diabetes risk rs11708067-A allele showed fewer H3K27ac ChIP-seq reads in human islets, lower transcriptional activity in reporter assays in rodent β-cells (rat 832/13 and mouse MIN6), and increased nuclear protein binding compared with the rs11708067-G allele. Homozygous deletion of the orthologous enhancer region in 832/13 cells resulted in a 64% reduction in expression level of Adcy5, but not adjacent gene Sec22a, and a 39% reduction in insulin secretion. Together, these data suggest that rs11708067-A risk allele contributes to type 2 diabetes by disrupting an islet enhancer, which results in reduced ADCY5 expression and impaired insulin secretion.

Prioritising Causal Genes at Type 2 Diabetes Risk Loci

PURPOSE OF REVIEW

Genome-wide association studies (GWAS) for type 2 diabetes (T2D) risk have identified a large number of genetic loci associated with disease susceptibility. However, progress moving from association signals through causal genes to functional understanding has so far been slow, hindering clinical translation. This review discusses the benefits and limitations of emerging, unbiased approaches for prioritising causal genes at T2D risk loci.

RECENT FINDINGS

Candidate causal genes can be identified by a number of different strategies that rely on genetic data, genomic annotations, and functional screening of selected genes. To overcome the limitations of each particular method, integration of multiple data sets is proving essential for establishing confidence in the prioritised genes. Previous studies have also highlighted the need to support these efforts through identification of causal variants and disease-relevant tissues. Prioritisation of causal genes at T2D risk loci by integrating complementary lines of evidence promises to accelerate our understanding of disease pathology and promote translation into new therapeutics.

Mechanisms of Type 2 Diabetes Risk Loci

PURPOSE OF REVIEW

Deciphering the mechanisms of type 2 diabetes (T2DM) risk loci can greatly inform on disease pathology. This review discusses current knowledge of mechanisms through which genetic variants influence T2DM risk and considerations for future studies.

RECENT FINDINGS

Over 100 T2DM risk loci to date have been identified. Candidate causal variants at risk loci map predominantly to non-coding sequence. Physiological, epigenomic and gene expression data suggest that variants at many known T2DM risk loci affect pancreatic islet regulation, although variants at other loci also affect protein function and regulatory processes in adipose, pre-adipose, liver, skeletal muscle and brain. The effects of T2DM variants on regulatory activity in these tissues appear largely, but not exclusively, due to altered transcription factor binding. Putative target genes of T2DM variants have been defined at an increasing number of loci and some, such as FTO, may entail several genes and multiple tissues. Gene networks in islets and adipocytes have been implicated in T2DM risk, although the molecular pathways of risk genes remain largely undefined. Efforts to fully define the mechanisms of T2DM risk loci are just beginning. Continued identification of risk mechanisms will benefit from combining genetic fine-mapping with detailed phenotypic association data, high-throughput epigenomics data from diabetes-relevant tissue, functional screening of candidate genes and genome editing of cellular and animal models.

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

Application of the experimental design of genome-wide association studies (GWASs) is now 10 years old (young), and here we review the remarkable range of discoveries it has facilitated in population and complex-trait genetics, the biology of diseases, and translation toward new therapeutics. We predict the likely discoveries in the next 10 years, when GWASs will be based on millions of samples with array data imputed to a large fully sequenced reference panel and on hundreds of thousands of samples with whole-genome sequencing data.

Human genetics as a model for target validation: finding new therapies for diabetes

Type 2 diabetes is a global epidemic with major effects on healthcare expenditure and quality of life. Currently available treatments are inadequate for the prevention of comorbidities, yet progress towards new therapies remains slow. A major barrier is the insufficiency of traditional preclinical models for predicting drug efficacy and safety. Human genetics offers a complementary model to assess causal mechanisms for target validation. Genetic perturbations are 'experiments of nature' that provide a uniquely relevant window into the long-term effects of modulating specific targets. Here, we show that genetic discoveries over the past decades have accurately predicted (now known) therapeutic mechanisms for type 2 diabetes. These findings highlight the potential for use of human genetic variation for prospective target validation, and establish a framework for future applications. Studies into rare, monogenic forms of diabetes have also provided proof-of-principle for precision medicine, and the applicability of this paradigm to complex disease is discussed. Finally, we highlight some of the limitations that are relevant to the use of genome-wide association studies (GWAS) in the search for new therapies for diabetes. A key outstanding challenge is the translation of GWAS signals into disease biology and we outline possible solutions for tackling this experimental bottleneck.

Transcribing β-cell mitochondria in health and disease

Background

The recent genome-wide association studies (GWAS) of Type 2 Diabetes (T2D) have identified the pancreatic β-cell as the culprit in the pathogenesis of the disease. Mitochondrial metabolism plays a crucial role in the processes controlling release of insulin and β-cell mass. This notion implies that mechanisms controlling mitochondrial function have the potential to play a decisive pathogenetic role in T2D.

Scope of the review

This article reviews studies demonstrating that there is indeed mitochondrial dysfunction in islets in T2D, and that GWAS have identified a variant in the gene encoding transcription factor B1 mitochondrial (TFB1M), predisposing to T2D due to mitochondrial dysfunction and impaired insulin secretion. Mechanistic studies of the nature of this pathogenetic link, as well as of other mitochondrial transcription factors, are described.

Major conclusions

Based on this, it is argued that transcription and translation in mitochondria are critical processes determining mitochondrial function in β-cells in health and disease.

Interrogating islets in health and disease with single-cell technologies

BACKGROUND

Blood glucose levels are tightly controlled by the coordinated actions of hormone-producing endocrine cells that reside in pancreatic islets. Islet cell malfunction underlies diabetes development and progression. Due to the cellular heterogeneity within islets, it has been challenging to uncover how specific islet cells contribute to glucose homeostasis and diabetes pathogenesis. Recent advances in single-cell technologies and computational methods have opened up new avenues to resolve islet heterogeneity and study islet cell states in health and disease.

SCOPE OF REVIEW

In the past year, a multitude of studies have been published that used single-cell approaches to interrogate the transcriptome and proteome of the different islet cell types. Here, we summarize the conclusions of these studies, as well as discuss the technologies used and the challenges faced with computational analysis of single-cell data from islet studies.

MAJOR CONCLUSIONS

By analyzing single islet cells from rodents and humans at different ages and disease states, the studies reviewed here have provided new insight into endocrine cell function and facilitated a high resolution molecular characterization of poorly understood processes, including regeneration, maturation, and diabetes pathogenesis. Gene expression programs and pathways identified in these studies pave the way for the discovery of new targets and approaches to prevent, monitor, and treat diabetes.

Type-2 diabetes-associated variants with cross-trait relevance: Post-GWAs strategies for biological function interpretation

Genome-wide association studies (GWAs) for type 2 diabetes (T2D) have been successful in identifying many loci with robust association signals. Nevertheless, there is a clear need for post-GWAs strategies to understand mechanism of action and clinical relevance of these variants. The association of several comorbidities with T2D suggests a common etiology for these phenotypes and complicates the management of the disease. In this study, we focused on the genetics underlying these relationships, using systems genomics to identify genetic variation associated with T2D and 12 other traits. GWAs studies summary statistics for pairwise comparisons were obtained for glycemic traits, obesity, coronary artery disease, and lipids from large consortia GWAs meta-analyses. We used a network medicine approach to leverage experimental information about the identified genes and variants with cross traits effects for biological function interpretation. We identified a set of 38 genetic variants with cross traits effects that point to a main network of genes that should be relevant for T2D and its comorbidities. We prioritized the T2D associated genes based on the number of traits they showed association with and the experimental evidence showing their relation to the disease etiology. In this study, we demonstrated how systems genomics and network medicine approaches can shed light into GWAs discoveries, translating findings into a more therapeutically relevant context.

Genomics of Islet (Dys)function and Type 2 Diabetes

Pancreatic islet dysfunction and beta cell failure are hallmarks of type 2 diabetes mellitus (T2DM) pathogenesis. In this review, we discuss how genome-wide association studies (GWASs) and recent developments in islet (epi)genome and transcriptome profiling (particularly single cell analyses) are providing novel insights into the genetic, environmental, and cellular contributions to islet (dys)function and T2DM pathogenesis. Moving forward, study designs that interrogate and model genetic variation [e.g., allelic profiling and (epi)genome editing] will be critical to dissect the molecular genetics of T2DM pathogenesis, to build next-generation cellular and animal models, and to develop precision medicine approaches to detect, treat, and prevent islet (dys)function and T2DM.

Genetic regulatory signatures underlying islet gene expression and type 2 diabetes

Genome-wide association studies (GWAS) have identified >100 independent SNPs that modulate the risk of type 2 diabetes (T2D) and related traits. However, the pathogenic mechanisms of most of these SNPs remain elusive. Here, we examined genomic, epigenomic, and transcriptomic profiles in human pancreatic islets to understand the links between genetic variation, chromatin landscape, and gene expression in the context of T2D. We first integrated genome and transcriptome variation across 112 islet samples to produce dense cis-expression quantitative trait loci (cis-eQTL) maps. Additional integration with chromatin-state maps for islets and other diverse tissue types revealed that cis-eQTLs for islet-specific genes are specifically and significantly enriched in islet stretch enhancers. High-resolution chromatin accessibility profiling using assay for transposase-accessible chromatin sequencing (ATAC-seq) in two islet samples enabled us to identify specific transcription factor (TF) footprints embedded in active regulatory elements, which are highly enriched for islet cis-eQTL. Aggregate allelic bias signatures in TF footprints enabled us de novo to reconstruct TF binding affinities genetically, which support the high-quality nature of the TF footprint predictions. Interestingly, we found that T2D GWAS loci were strikingly and specifically enriched in islet Regulatory Factor X (RFX) footprints. Remarkably, within and across independent loci, T2D risk alleles that overlap with RFX footprints uniformly disrupt the RFX motifs at high-information content positions. Together, these results suggest that common regulatory variations have shaped islet TF footprints and the transcriptome and that a confluent RFX regulatory grammar plays a significant role in the genetic component of T2D predisposition.

Decreased STARD10 Expression Is Associated with Defective Insulin Secretion in Humans and Mice

Genetic variants near ARAP1 (CENTD2) and STARD10 influence type 2 diabetes (T2D) risk. The risk alleles impair glucose-induced insulin secretion and, paradoxically but characteristically, are associated with decreased proinsulin:insulin ratios, indicating improved proinsulin conversion. Neither the identity of the causal variants nor the gene(s) through which risk is conferred have been firmly established. Whereas ARAP1 encodes a GTPase activating protein, STARD10 is a member of the steroidogenic acute regulatory protein (StAR)-related lipid transfer protein family. By integrating genetic fine-mapping and epigenomic annotation data and performing promoter-reporter and chromatin conformational capture (3C) studies in β cell lines, we localize the causal variant(s) at this locus to a 5 kb region that overlaps a stretch-enhancer active in islets. This region contains several highly correlated T2D-risk variants, including the rs140130268 indel. Expression QTL analysis of islet transcriptomes from three independent subject groups demonstrated that T2D-risk allele carriers displayed reduced levels of STARD10 mRNA, with no concomitant change in ARAP1 mRNA levels. Correspondingly, β-cell-selective deletion of StarD10 in mice led to impaired glucose-stimulated Ca²⁺ dynamics and insulin secretion and recapitulated the pattern of improved proinsulin processing observed at the human GWAS signal. Conversely, overexpression of StarD10 in the adult β cell improved glucose tolerance in high fat-fed animals. In contrast, manipulation of Arap1 in β cells had no impact on insulin secretion or proinsulin conversion in mice. This convergence of human and murine data provides compelling evidence that the T2D risk associated with variation at this locus is mediated through reduction in STARD10 expression in the β cell.

The Metabolic Syndrome in Men study: a resource for studies of metabolic and cardiovascular diseases

The Metabolic Syndrome in Men (METSIM) study is a population-based study including 10,197 Finnish men examined in 2005-2010. The aim of the study is to investigate nongenetic and genetic factors associated with the risk of T2D and CVD, and with cardiovascular risk factors. The protocol includes a detailed phenotyping of the participants, an oral glucose tolerance test, fasting laboratory measurements including proton NMR measurements, mass spectometry metabolomics, adipose tissue biopsies from 1,400 participants, and a stool sample. In our ongoing follow-up study, we have, to date, reexamined 6,496 participants. Extensive genotyping and exome sequencing have been performed for essentially all METSIM participants, and >2,000 METSIM participants have been whole-genome sequenced. We have identified several nongenetic markers associated with the development of diabetes and cardiovascular events, and participated in several genetic association studies to identify gene variants associated with diabetes, hyperglycemia, and cardiovascular risk factors. The generation of a phenotype and genotype resource in the METSIM study allows us to proceed toward a "systems genetics" approach, which includes statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein, or metabolite levels, to provide a global view of the molecular architecture of complex traits.

Phenotype and Tissue Expression as a Function of Genetic Risk in Polycystic Ovary Syndrome

Genome-wide association studies and replication analyses have identified (n = 5) or replicated (n = 10) DNA variants associated with risk for polycystic ovary syndrome (PCOS) in European women. However, the causal gene and underlying mechanism for PCOS risk at these loci have not been determined. We hypothesized that analysis of phenotype, gene expression and metformin response as a function of genotype would identify candidate genes and pathways that could provide insight into the underlying mechanism for risk at these loci. To test the hypothesis, subjects with PCOS (n = 427) diagnosed according to the NIH criteria (< 9 menses per year and clinical or biochemical hyperandrogenism) and controls (n = 407) with extensive phenotyping were studied. A subset of subjects (n = 38) underwent a subcutaneous adipose tissue biopsy for RNA sequencing and were subsequently treated with metformin for 12 weeks with standardized outcomes measured. Data were analyzed according to genotype at PCOS risk loci and adjusted for the false discovery rate. A gene variant in the THADA locus was associated with response to metformin and metformin was a predicted upstream regulator at the same locus. Genotype at the FSHB locus was associated with LH levels. Genes near the PCOS risk loci demonstrated differences in expression as a function of genotype in adipose including BLK and NEIL2 (GATA4 locus), GLIPR1 and PHLDA1 (KRR1 locus). Based on the phenotypes, expression quantitative trait loci (eQTL), and upstream regulatory and pathway analyses we hypothesize that there are PCOS subtypes. FSHB, FHSR and LHR loci may influence PCOS risk based on their relationship to gonadotropin levels. The THADA, GATA4, ERBB4, SUMO1P1, KRR1 and RAB5B loci appear to confer risk through metabolic mechanisms. The IRF1, SUMO1P1 and KRR1 loci may confer PCOS risk in development. The TOX3 and GATA4 loci appear to be involved in inflammation and its consequences. The data suggest potential PCOS subtypes and point to the need for additional studies to replicate these findings and identify personalized diagnosis and treatment options for PCOS.

Colocalization of GWAS and eQTL Signals Detects Target Genes

The vast majority of genome-wide association study (GWAS) risk loci fall in non-coding regions of the genome. One possible hypothesis is that these GWAS risk loci alter the individual's disease risk through their effect on gene expression in different tissues. In order to understand the mechanisms driving a GWAS risk locus, it is helpful to determine which gene is affected in specific tissue types. For example, the relevant gene and tissue could play a role in the disease mechanism if the same variant responsible for a GWAS locus also affects gene expression. Identifying whether or not the same variant is causal in both GWASs and expression quantitative trail locus (eQTL) studies is challenging because of the uncertainty induced by linkage disequilibrium and the fact that some loci harbor multiple causal variants. However, current methods that address this problem assume that each locus contains a single causal variant. In this paper, we present eCAVIAR, a probabilistic method that has several key advantages over existing methods. First, our method can account for more than one causal variant in any given locus. Second, it can leverage summary statistics without accessing the individual genotype data. We use both simulated and real datasets to demonstrate the utility of our method. Using publicly available eQTL data on 45 different tissues, we demonstrate that eCAVIAR can prioritize likely relevant tissues and target genes for a set of glucose- and insulin-related trait loci.

Systematic Functional Characterization of Candidate Causal Genes for Type 2 Diabetes Risk Variants

Most genetic association signals for type 2 diabetes risk are located in noncoding regions of the genome, hindering translation into molecular mechanisms. Physiological studies have shown a majority of disease-associated variants to exert their effects through pancreatic islet dysfunction. Systematically characterizing the role of regional transcripts in β-cell function could identify the underlying disease-causing genes, but large-scale studies in human cellular models have previously been impractical. We developed a robust and scalable strategy based on arrayed gene silencing in the human β-cell line EndoC-βH1. In a screen of 300 positional candidates selected from 75 type 2 diabetes regions, each gene was assayed for effects on multiple disease-relevant phenotypes, including insulin secretion and cellular proliferation. We identified a total of 45 genes involved in β-cell function, pointing to possible causal mechanisms at 37 disease-associated loci. The results showed a strong enrichment for genes implicated in monogenic diabetes. Selected effects were validated in a follow-up study, including several genes (ARL15, ZMIZ1, and THADA) with previously unknown or poorly described roles in β-cell biology. We have demonstrated the feasibility of systematic functional screening in a human β-cell model and successfully prioritized plausible disease-causing genes at more than half of the regions investigated.

Single-cell transcriptomes identify human islet cell signatures and reveal cell-type-specific expression changes in type 2 diabetes

Blood glucose levels are tightly controlled by the coordinated action of at least four cell types constituting pancreatic islets. Changes in the proportion and/or function of these cells are associated with genetic and molecular pathophysiology of monogenic, type 1, and type 2 (T2D) diabetes. Cellular heterogeneity impedes precise understanding of the molecular components of each islet cell type that govern islet (dys)function, particularly the less abundant delta and gamma/pancreatic polypeptide (PP) cells. Here, we report single-cell transcriptomes for 638 cells from nondiabetic (ND) and T2D human islet samples. Analyses of ND single-cell transcriptomes identified distinct alpha, beta, delta, and PP/gamma cell-type signatures. Genes linked to rare and common forms of islet dysfunction and diabetes were expressed in the delta and PP/gamma cell types. Moreover, this study revealed that delta cells specifically express receptors that receive and coordinate systemic cues from the leptin, ghrelin, and dopamine signaling pathways implicating them as integrators of central and peripheral metabolic signals into the pancreatic islet. Finally, single-cell transcriptome profiling revealed genes differentially regulated between T2D and ND alpha, beta, and delta cells that were undetectable in paired whole islet analyses. This study thus identifies fundamental cell-type–specific features of pancreatic islet (dys)function and provides a critical resource for comprehensive understanding of islet biology and diabetes pathogenesis.

Single-Cell Sequencing of Human Pancreatic Islets-New Kids on the Block

RNA sequencing of human pancreatic islets has provided important insights into the islet transcriptome but little information on the specific cells. In this issue, Segerstolpe et al. (2016) and Xin et al. (2016b) report on the transcriptome of single pancreatic cells from non-diabetic and type 2 diabetic donors.

RNA Sequencing of Single Human Islet Cells Reveals Type 2 Diabetes Genes

Pancreatic islet cells are critical for maintaining normal blood glucose levels, and their malfunction underlies diabetes development and progression. We used single-cell RNA sequencing to determine the transcriptomes of 1,492 human pancreatic α, β, δ, and PP cells from non-diabetic and type 2 diabetes organ donors. We identified cell-type-specific genes and pathways as well as 245 genes with disturbed expression in type 2 diabetes. Importantly, 92% of the genes have not previously been associated with islet cell function or growth. Comparison of gene profiles in mouse and human α and β cells revealed species-specific expression. All data are available for online browsing and download and will hopefully serve as a resource for the islet research community.

Variation in the glucose transporter gene SLC2A2 is associated with glycemic response to metformin

Metformin is the first-line antidiabetic drug with over 100 million users worldwide, yet its mechanism of action remains unclear1. Here the Metformin Genetics (MetGen) Consortium reports a three-stage genome wide association study (GWAS), consisting of 13,123 participants of different ancestries. The C-allele of rs8192675 in the intron of SLC2A2, which encodes the facilitated glucose transporter GLUT2, was associated with a 0.17% (p=6.6x10^-14) greater metformin induced HbA1c reduction in 10,577 participants of European ancestry. rs8192675 is the top cis-eQTL for SLC2A2 in 1,226 human liver samples, suggesting a key role for hepatic GLUT2 in regulation of metformin action. In obese individuals C-allele homozygotes at rs8192675 had a 0.33% (3.6mmol/mol) greater absolute HbA1c reduction than T-allele homozygotes.This is about half the effect seen with the addition of a DPP-4 inhibitor, and equates to a dose difference of 550mg of metformin, suggesting rs8192675 as a potential biomarker for stratified medicine.

Changes in the expression of the type 2 diabetes-associated gene VPS13C in the β-cell are associated with glucose intolerance in humans and mice

Single nucleotide polymorphisms (SNPs) close to the VPS13C, C2CD4A and C2CD4B genes on chromosome 15q are associated with impaired fasting glucose and increased risk of type 2 diabetes. eQTL analysis revealed an association between possession of risk (C) alleles at a previously implicated causal SNP, rs7163757, and lowered VPS13C and C2CD4A levels in islets from female (n = 40, P < 0.041) but not from male subjects. Explored using promoter-reporter assays in β-cells and other cell lines, the risk variant at rs7163757 lowered enhancer activity. Mice deleted for Vps13c selectively in the β-cell were generated by crossing animals bearing a floxed allele at exon 1 to mice expressing Cre recombinase under Ins1 promoter control (Ins1Cre). Whereas Vps13c(fl/fl):Ins1Cre (βVps13cKO) mice displayed normal weight gain compared with control littermates, deletion of Vps13c had little effect on glucose tolerance. Pancreatic histology revealed no significant change in β-cell mass in KO mice vs. controls, and glucose-stimulated insulin secretion from isolated islets was not altered in vitro between control and βVps13cKO mice. However, a tendency was observed in female null mice for lower insulin levels and β-cell function (HOMA-B) in vivo. Furthermore, glucose-stimulated increases in intracellular free Ca(2+) were significantly increased in islets from female KO mice, suggesting impaired Ca(2+) sensitivity of the secretory machinery. The present data thus provide evidence for a limited role for changes in VPS13C expression in conferring altered disease risk at this locus, particularly in females, and suggest that C2CD4A may also be involved.

Genome-edited human stem cell-derived beta cells: a powerful tool for drilling down on type 2 diabetes GWAS biology

Type 2 diabetes (T2D) is a disease of pandemic proportions, one defined by a complex aetiological mix of genetic, epigenetic, environmental, and lifestyle risk factors. Whilst the last decade of T2D genetic research has identified more than 100 loci showing strong statistical association with disease susceptibility, our inability to capitalise upon these signals reflects, in part, a lack of appropriate human cell models for study. This review discusses the impact of two complementary, state-of-the-art technologies on T2D genetic research: the generation of stem cell-derived, endocrine pancreas-lineage cells and the editing of their genomes. Such models facilitate investigation of diabetes-associated genomic perturbations in a physiologically representative cell context and allow the role of both developmental and adult islet dysfunction in T2D pathogenesis to be investigated. Accordingly, we interrogate the role that patient-derived induced pluripotent stem cell models are playing in understanding cellular dysfunction in monogenic diabetes, and how site-specific nucleases such as the clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 system are helping to confirm genes crucial to human endocrine pancreas development. We also highlight the novel biology gleaned in the absence of patient lines, including an ability to model the whole phenotypic spectrum of diabetes phenotypes occurring both in utero and in adult cells, interrogating the non-coding 'islet regulome' for disease-causing perturbations, and understanding the role of other islet cell types in aberrant glycaemia. This article aims to reinforce the importance of investigating T2D signals in cell models reflecting appropriate species, genomic context, developmental time point, and tissue type.

Type 2 diabetes: genetic data sharing to advance complex disease research

As with other complex diseases, unbiased association studies followed by physiological and experimental characterization have for years formed a paradigm for identifying genes or processes of relevance to type 2 diabetes mellitus (T2D). Recent large-scale common and rare variant genome-wide association studies (GWAS) suggest that substantially larger association studies are needed to identify most T2D loci in the population. To hasten clinical translation of genetic discoveries, new paradigms are also required to aid specialized investigation of nascent hypotheses. We argue for an integrated T2D knowledgebase, designed for a worldwide community to access aggregated large-scale genetic data sets, as one paradigm to catalyse convergence of these efforts.

Common and rare forms of diabetes mellitus: towards a continuum of diabetes subtypes

Insights into the genetic basis of type 2 diabetes mellitus (T2DM) have been difficult to discern, despite substantial research. More is known about rare forms of diabetes mellitus, several of which share clinical and genetic features with the common form of T2DM. In this Review, we discuss the extent to which the study of rare and low-frequency mutations in large populations has begun to bridge the gap between rare and common forms of diabetes mellitus. We hypothesize that the perceived division between these diseases might be due, in part, to the historical ascertainment bias of genetic studies, rather than a clear distinction between disease pathophysiologies. We also discuss possible implications of a new model for the genetic basis of diabetes mellitus subtypes, where the boundary between subtypes becomes blurred.

A 3-year follow-up study of β-cell function in patients with early-onset type 2 diabetes

Insulin resistance and reduced β-cell glucose sensitivity are present in patients with type 2 diabetes. In the present study, we investigated the changes in β-cell function in patients with type 2 diabetes during a 3-year follow-up study. A total of 48 patients with early-onset type 2 diabetes (EOD) and 55 patients with late-onset type 2 diabetes (LOD) were enrolled. Weight, height, waist circumference, hip circumference, blood pressure and plasma levels of lipids, glucose, fasting serum C-peptide (CPR0) and serum C-peptide 6 min after glucagon stimulation (CPR6) were measured. In addition, islet β-cell secretory activity was detected. Subjects with EOD had lower Systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), fasting CPR0, CPR6 and greater glycated hemoglobin A1c (HbA1c), triglyceride (TG) compared with subjects with LOD. CPR0, CPR6 and TG were decreased in both EOD and LOD groups 3 years later. The ratio of β-cell function failure was 29.17 and 10.91% in the EOD and LOD groups, respectively, and there was significant difference between the two groups. A positive correlation was identified between the CPR0 and waist-hip ratio, HbA1c in the EOD group. A similar positive correlation was observed between CPR0 and BMI in the LOD group. Collectively, islet β-cell function has declined in patients with EOD, and this change may be more evident when compared with those with LOD.

Insights into islet development and biology through characterization of a human iPSC-derived endocrine pancreas model

Directed differentiation of stem cells offers a scalable solution to the need for human cell models recapitulating islet biology and T2D pathogenesis. We profiled mRNA expression at 6 stages of an induced pluripotent stem cell (iPSC) model of endocrine pancreas development from 2 donors, and characterized the distinct transcriptomic profiles associated with each stage. Established regulators of endodermal lineage commitment, such as SOX17 (log2 fold change [FC] compared to iPSCs = 14.2, p-value = 4.9 × 10(-5)) and the pancreatic agenesis gene GATA6 (log2 FC = 12.1, p-value = 8.6 × 10(-5)), showed transcriptional variation consistent with their known developmental roles. However, these analyses highlighted many other genes with stage-specific expression patterns, some of which may be novel drivers or markers of islet development. For example, the leptin receptor gene, LEPR, was most highly expressed in published data from in vivo-matured cells compared to our endocrine pancreas-like cells (log2 FC = 5.5, p-value = 2.0 × 10(-12)), suggesting a role for the leptin pathway in the maturation process. Endocrine pancreas-like cells showed significant stage-selective expression of adult islet genes, including INS, ABCC8, and GLP1R, and enrichment of relevant GO-terms (e.g. "insulin secretion"; odds ratio = 4.2, p-value = 1.9 × 10(-3)): however, principal component analysis indicated that in vitro-differentiated cells were more immature than adult islets. Integration of the stage-specific expression information with genetic data from T2D genome-wide association studies revealed that 46 of 82 T2D-associated loci harbor genes present in at least one developmental stage, facilitating refinement of potential effector transcripts. Together, these data show that expression profiling in an iPSC islet development model can further understanding of islet biology and T2D pathogenesis.