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

Characterizing Common and Rare Variations in Nontraditional Glycemic Biomarkers Using Multivariate Approaches on Multiancestry ARIC Study

Genetic studies of nontraditional glycemic biomarkers, glycated albumin and fructosamine, can shed light on unknown aspects of type 2 diabetes genetics and biology. We performed a multiphenotype genome-wide association study of glycated albumin and fructosamine from 7,395 White and 2,016 Black participants in the Atherosclerosis Risk in Communities (ARIC) study on common variants from genotyped/imputed data. We discovered two genome-wide significant loci, one mapping to a known type 2 diabetes gene (ARAP1/STARD10) and another mapping to a novel region (UGT1A complex of genes), using multiomics gene-mapping strategies in diabetes-relevant tissues. We identified additional loci that were ancestry- and sex-specific (e.g., PRKCA in African ancestry, FCGRT in European ancestry, TEX29 in males). Further, we implemented multiphenotype gene-burden tests on whole-exome sequence data from 6,590 White and 2,309 Black ARIC participants. Ten variant sets annotated to genes across different variant aggregation strategies were exome-wide significant only in multiancestry analysis, of which CD1D, EGFL7/AGPAT2, and MIR126 had notable enrichment of rare predicted loss of function variants in African ancestry despite smaller sample sizes. Overall, 8 of 14 discovered loci and genes were implicated to influence these biomarkers via glycemic pathways, and most of them were not previously implicated in studies of type 2 diabetes. This study illustrates improved locus discovery and potential effector gene discovery by leveraging joint patterns of related biomarkers across the entire allele frequency spectrum in multiancestry analysis. Future investigation of the loci and genes potentially acting through glycemic pathways may help us better understand the risk of developing type 2 diabetes.

ARTICLE HIGHLIGHTS

Exploring pancreatic beta-cell subgroups and their connectivity

Functional pancreatic islet beta cells are essential to ensure glucose homeostasis across species from zebrafish to humans. These cells show significant heterogeneity, and emerging studies have revealed that connectivity across a hierarchical network is required for normal insulin release. Here, we discuss current thinking and areas of debate around intra-islet connectivity, cellular hierarchies and potential "controlling" beta-cell populations. We focus on methodologies, including comparisons of different cell preparations as well as in vitro and in vivo approaches to imaging and controlling the activity of human and rodent islet preparations. We also discuss the analytical approaches that can be applied to live-cell data to identify and study critical subgroups of cells with a disproportionate role in control Ca2+ dynamics and thus insulin secretion (such as "first responders", "leaders" and "hubs", as defined by Ca2+ responses to glucose stimulation). Possible mechanisms by which this hierarchy is achieved, its physiological relevance and how its loss may contribute to islet failure in diabetes mellitus are also considered. A glossary of terms and links to computational resources are provided.

Ethnicity-related differences in mitochondrial regulation by insulin stimulation in diabetes

Mitochondrial dysfunction has long been implicated in the development of insulin resistance, which is a hallmark of type 2 diabetes. However, recent studies reveal ethnicity-related differences in mitochondrial processes, underscoring the need for nuance in studying mitochondrial dysfunction and insulin sensitivity. Furthermore, the higher prevalence of type 2 diabetes among African Americans and individuals of African descent has brought attention to the role of ethnicity in disease susceptibility. In this review, which covers existing literature, genetic studies, and clinical data, we aim to elucidate the complex relationship between mitochondrial alterations and insulin stimulation by considering how mitochondrial dynamics, contact sites, pathways, and metabolomics may be differentially regulated across ethnicities, through mechanisms such as single nucleotide polymorphisms (SNPs). In addition to achieving a better understanding of insulin stimulation, future studies identifying novel regulators of mitochondrial structure and function could provide valuable insights into ethnicity-dependent insulin signaling and personalized care.

Multiple genetic variants at the SLC30A8 locus affect local super-enhancer activity and influence pancreatic β-cell survival and function

Variants at the SLC30A8 locus are associated with type 2 diabetes (T2D) risk. The lead variant, rs13266634, encodes an amino acid change, Arg325Trp (R325W), at the C-terminus of the secretory granule-enriched zinc transporter, ZnT8. Although this protein-coding variant was previously thought to be the sole driver of T2D risk at this locus, recent studies have provided evidence for lowered expression of SLC30A8 mRNA in protective allele carriers. In the present study, we examined multiple variants that influence SLC30A8 allele-specific expression. Epigenomic mapping has previously identified an islet-selective enhancer cluster at the SLC30A8 locus, hosting multiple T2D risk and cASE associations, which is spatially associated with the SLC30A8 promoter and additional neighboring genes. Here, we show that deletion of variant-bearing enhancer regions using CRISPR-Cas9 in human-derived EndoC-βH3 cells lowers the expression of SLC30A8 and several neighboring genes and improves glucose-stimulated insulin secretion. While downregulation of SLC30A8 had no effect on beta cell survival, loss of UTP23, RAD21, or MED30 markedly reduced cell viability. Although eQTL or cASE analyses in human islets did not support the association between these additional genes and diabetes risk, the transcriptional regulator JQ1 lowered the expression of multiple genes at the SLC30A8 locus and enhanced stimulated insulin secretion.

Multiple genetic variants at the SLC30A8 locus affect local super-enhancer activity and influence pancreatic β-cell survival and function

Variants at the SLC30A8 locus are associated with type 2 diabetes (T2D) risk. The lead variant, rs13266634, encodes an amino acid change, Arg325Trp (R325W), at the C-terminus of the secretory granule-enriched zinc transporter, ZnT8. Although this protein-coding variant was previously thought to be the sole driver of T2D risk at this locus, recent studies have provided evidence for lowered expression of SLC30A8 mRNA in protective allele carriers. In the present study, combined allele-specific expression (cASE) analysis in human islets revealed multiple variants that influence SLC30A8 expression. Epigenomic mapping identified an islet-selective enhancer cluster at the SLC30A8 locus, hosting multiple T2D risk and cASE associations, which is spatially associated with the SLC30A8 promoter and additional neighbouring genes. Deletions of variant-bearing enhancer regions using CRISPR-Cas9 in human-derived EndoC-βH3 cells lowered the expression of SLC30A8 and several neighbouring genes, and improved insulin secretion. Whilst down-regulation of SLC30A8 had no effect on beta cell survival, loss of UTP23, RAD21 or MED30 markedly reduced cell viability. Although eQTL or cASE analyses in human islets did not support the association between these additional genes and diabetes risk, the transcriptional regulator JQ1 lowered the expression of multiple genes at the SLC30A8 locus and enhanced stimulated insulin secretion.

Characterizing common and rare variations in non-traditional glycemic biomarkers using multivariate approaches on multi-ancestry ARIC study

Glycated hemoglobin, fasting glucose, glycated albumin, and fructosamine are biomarkers that reflect different aspects of the glycemic process. Genetic studies of these glycemic biomarkers can shed light on unknown aspects of type 2 diabetes genetics and biology. While there exists several GWAS of glycated hemoglobin and fasting glucose, very few GWAS have focused on glycated albumin or fructosamine. We performed a multi-phenotype GWAS of glycated albumin and fructosamine from 7,395 White and 2,016 Black participants in the Atherosclerosis Risk in Communities (ARIC) study on the common variants from genotyped/imputed data. We found 2 genome-wide significant loci, one mapping to known type 2 diabetes gene (ARAP1/STARD10, p = 2.8 × 10-8) and another mapping to a novel gene (UGT1A, p = 1.4 × 10-8) using multi-omics gene mapping strategies in diabetes-relevant tissues. We identified additional loci that were ancestry-specific (e.g., PRKCA from African ancestry individuals, p = 1.7 × 10-8) and sex-specific (TEX29 locus in males only, p = 3.0 × 10-8). Further, we implemented multi-phenotype gene-burden tests on whole-exome sequence data from 6,590 White and 2,309 Black ARIC participants. Eleven genes across different rare variant aggregation strategies were exome-wide significant only in multi-ancestry analysis. Four out of 11 genes had notable enrichment of rare predicted loss of function variants in African ancestry participants despite smaller sample size. Overall, 8 out of 15 loci/genes were implicated to influence these biomarkers via glycemic pathways. This study illustrates improved locus discovery and potential effector gene discovery by leveraging joint patterns of related biomarkers across entire allele frequency spectrum in multi-ancestry analyses. Most of the loci/genes we identified have not been previously implicated in studies of type 2 diabetes, and future investigation of the loci/genes potentially acting through glycemic pathways may help us better understand risk of developing type 2 diabetes.

PIMT Controls Insulin Synthesis and Secretion through PDX1

Pancreatic beta cell function is an important component of glucose homeostasis. Here, we investigated the function of PIMT (PRIP-interacting protein with methyl transferase domain), a transcriptional co-activator binding protein, in the pancreatic beta cells. We observed that the protein levels of PIMT, along with key beta cell markers such as PDX1 (pancreatic and duodenal homeobox 1) and MafA (MAF bZIP transcription factor A), were reduced in the beta cells exposed to hyperglycemic and hyperlipidemic conditions. Consistently, PIMT levels were reduced in the pancreatic islets isolated from high fat diet (HFD)-fed mice. The RNA sequencing analysis of PIMT knockdown beta cells identified that the expression of key genes involved in insulin secretory pathway, Ins1 (insulin 1), Ins2 (insulin 2), Kcnj11 (potassium inwardly-rectifying channel, subfamily J, member 11), Kcnn1 (potassium calcium-activated channel subfamily N member 1), Rab3a (member RAS oncogene family), Gnas (GNAS complex locus), Syt13 (synaptotagmin 13), Pax6 (paired box 6), Klf11 (Kruppel-Like Factor 11), and Nr4a1 (nuclear receptor subfamily 4, group A, member 1) was attenuated due to PIMT depletion. PIMT ablation in the pancreatic beta cells and in the rat pancreatic islets led to decreased protein levels of PDX1 and MafA, resulting in the reduction in glucose-stimulated insulin secretion (GSIS). The results from the immunoprecipitation and ChIP experiments revealed the interaction of PIMT with PDX1 and MafA, and its recruitment to the insulin promoter, respectively. Importantly, PIMT ablation in beta cells resulted in the nuclear translocation of insulin. Surprisingly, forced expression of PIMT in beta cells abrogated GSIS, while Ins1 and Ins2 transcript levels were subtly enhanced. On the other hand, the expression of genes, PRIP/Asc2/Ncoa6 (nuclear receptor coactivator 6), Pax6, Kcnj11, Syt13, Stxbp1 (syntaxin binding protein 1), and Snap25 (synaptosome associated protein 25) associated with insulin secretion, was significantly reduced, providing an explanation for the decreased GSIS upon PIMT overexpression. Our findings highlight the importance of PIMT in the regulation of insulin synthesis and secretion in beta cells.

High-throughput genetic clustering of type 2 diabetes loci reveals heterogeneous mechanistic pathways of metabolic disease

AIMS/HYPOTHESIS

Type 2 diabetes is highly polygenic and influenced by multiple biological pathways. Rapid expansion in the number of type 2 diabetes loci can be leveraged to identify such pathways.

METHODS

We developed a high-throughput pipeline to enable clustering of type 2 diabetes loci based on variant-trait associations. Our pipeline extracted summary statistics from genome-wide association studies (GWAS) for type 2 diabetes and related traits to generate a matrix of 323 variants × 64 trait associations and applied Bayesian non-negative matrix factorisation (bNMF) to identify genetic components of type 2 diabetes. Epigenomic enrichment analysis was performed in 28 cell types and single pancreatic cells. We generated cluster-specific polygenic scores and performed regression analysis in an independent cohort (N=25,419) to assess for clinical relevance.

RESULTS

We identified ten clusters of genetic loci, recapturing the five from our prior analysis as well as novel clusters related to beta cell dysfunction, pronounced insulin secretion, and levels of alkaline phosphatase, lipoprotein A and sex hormone-binding globulin. Four clusters related to mechanisms of insulin deficiency, five to insulin resistance and one had an unclear mechanism. The clusters displayed tissue-specific epigenomic enrichment, notably with the two beta cell clusters differentially enriched in functional and stressed pancreatic beta cell states. Additionally, cluster-specific polygenic scores were differentially associated with patient clinical characteristics and outcomes. The pipeline was applied to coronary artery disease and chronic kidney disease, identifying multiple overlapping clusters with type 2 diabetes.

CONCLUSIONS/INTERPRETATION

Our approach stratifies type 2 diabetes loci into physiologically interpretable genetic clusters associated with distinct tissues and clinical outcomes. The pipeline allows for efficient updating as additional GWAS become available and can be readily applied to other conditions, facilitating clinical translation of GWAS findings. Software to perform this clustering pipeline is freely available.

Loci for insulin processing and secretion provide insight into type 2 diabetes risk

Insulin secretion is critical for glucose homeostasis, and increased levels of the precursor proinsulin relative to insulin indicate pancreatic islet beta-cell stress and insufficient insulin secretory capacity in the setting of insulin resistance. We conducted meta-analyses of genome-wide association results for fasting proinsulin from 16 European-ancestry studies in 45,861 individuals. We found 36 independent signals at 30 loci (p value < 5 × 10-8), which validated 12 previously reported loci for proinsulin and ten additional loci previously identified for another glycemic trait. Half of the alleles associated with higher proinsulin showed higher rather than lower effects on glucose levels, corresponding to different mechanisms. Proinsulin loci included genes that affect prohormone convertases, beta-cell dysfunction, vesicle trafficking, beta-cell transcriptional regulation, and lysosomes/autophagy processes. We colocalized 11 proinsulin signals with islet expression quantitative trait locus (eQTL) data, suggesting candidate genes, including ARSG, WIPI1, SLC7A14, and SIX3. The NKX6-3/ANK1 proinsulin signal colocalized with a T2D signal and an adipose ANK1 eQTL signal but not the islet NKX6-3 eQTL. Signals were enriched for islet enhancers, and we showed a plausible islet regulatory mechanism for the lead signal in the MADD locus. These results show how detailed genetic studies of an intermediate phenotype can elucidate mechanisms that may predispose one to disease.

An in vitro approach to understand contribution of kidney cells to human urinary extracellular vesicles

Extracellular vesicles (EV) are membranous particles secreted by all cells and found in body fluids. Established EV contents include a variety of RNA species, proteins, lipids and metabolites that are considered to reflect the physiological status of their parental cells. However, to date, little is known about cell-type enriched EV cargo in complex EV mixtures, especially in urine. To test whether EV secretion from distinct human kidney cells in culture differ and can recapitulate findings in normal urine, we comprehensively analysed EV components, (particularly miRNAs, long RNAs and protein) from conditionally immortalised human kidney cell lines (podocyte, glomerular endothelial, mesangial and proximal tubular cells) and compared to EV secreted in human urine. EV from cell culture media derived from immortalised kidney cells were isolated by hydrostatic filtration dialysis (HFD) and characterised by electron microscopy (EM), nanoparticle tracking analysis (NTA) and Western blotting (WB). RNA was isolated from EV and subjected to miRNA and RNA sequencing and proteins were profiled by tandem mass tag proteomics. Representative sets of EV miRNAs, RNAs and proteins were detected in each cell type and compared to human urinary EV isolates (uEV), EV cargo database, kidney biopsy bulk RNA sequencing and proteomics, and single-cell transcriptomics. This revealed that a high proportion of the in vitro EV signatures were also found in in vivo datasets. Thus, highlighting the robustness of our in vitro model and showing that this approach enables the dissection of cell type specific EV cargo in biofluids and the potential identification of cell-type specific EV biomarkers of kidney disease.

Biochemical Activation and Regulatory Functions of Trans-Regulatory KLF14 and Its Association with Genetic Polymorphisms

Krüpple-Like family of transcription factor-14 (KLF14) is a master trans-regulatory gene that has multiple biological regulatory functions and is involved in many pathological mechanisms. It controls the expressions of several other genes which are involved in multiple regulatory functions. KLF14 plays a significant role in lipid metabolism, glucose regulation and insulin sensitivity. Cell apoptosis, proliferation, and differentiation are regulated by the KLF14 gene, and up-regulation of KLF14 prevents cancer progression. KLF14 has been used as an epigenetic biomarker for the estimation of chronological age due to the presence of different age-related CpG sites on genes that become methylated with age. Different genome-wide association studies have identified several KLF14 variants in adipose tissues. These single nucleotide polymorphisms in KLF14 have been associated with dyslipidemia, insulin resistance, and glucose intolerance. Moreover, the prevalence of genetic polymorphism is different in different populations due to ethnic differences and epigenetic modifications. In addition, environmental and physiological factors such as diet, age, gender, and obesity are also responsible for genetic mutations in KLF14.

Cholesterol Redistribution in Pancreatic β-Cells: A Flexible Path to Regulate Insulin Secretion

Pancreatic β-cells, by secreting insulin, play a key role in the control of glucose homeostasis, and their dysfunction is the basis of diabetes development. The metabolic milieu created by high blood glucose and lipids is known to play a role in this process. In the last decades, cholesterol has attracted significant attention, not only because it critically controls β-cell function but also because it is the target of lipid-lowering therapies proposed for preventing the cardiovascular complications in diabetes. Despite the remarkable progress, understanding the molecular mechanisms responsible for cholesterol-mediated β-cell function remains an open and attractive area of investigation. Studies indicate that β-cells not only regulate the total cholesterol level but also its redistribution within organelles, a process mediated by vesicular and non-vesicular transport. The aim of this review is to summarize the most current view of how cholesterol homeostasis is maintained in pancreatic β-cells and to provide new insights on the mechanisms by which cholesterol is dynamically distributed among organelles to preserve their functionality. While cholesterol may affect virtually any activity of the β-cell, the intent of this review is to focus on early steps of insulin synthesis and secretion, an area still largely unexplored.

A composite strategy of genome-wide association study and copy number variation analysis for carcass traits in a Duroc pig population

BACKGROUND

Carcass traits are important in pig breeding programs for improving pork production. Understanding the genetic variants underlies complex phenotypes can help explain trait variation in pigs. In this study, we integrated a weighted single-step genome-wide association study (wssGWAS) and copy number variation (CNV) analyses to map genetic variations and genes associated with loin muscle area (LMA), loin muscle depth (LMD) and lean meat percentage (LMP) in Duroc pigs.

RESULTS

Firstly, we performed a genome-wide analysis for CNV detection using GeneSeek Porcine SNP50 Bead chip data of 3770 pigs. A total of 11,100 CNVs were detected, which were aggregated by overlapping 695 CNV regions (CNVRs). Next, we investigated CNVs of pigs from the same population by whole-genome resequencing. A genome-wide analysis of 21 pigs revealed 23,856 CNVRs that were further divided into three categories (851 gain, 22,279 loss, and 726 mixed), which covered 190.8 Mb (~ 8.42%) of the pig autosomal genome. Further, the identified CNVRs were used to determine an overall validation rate of 68.5% for the CNV detection accuracy of chip data. CNVR association analyses identified one CNVR associated with LMA, one with LMD and eight with LMP after applying stringent Bonferroni correction. The wssGWAS identified eight, six and five regions explaining more than 1% of the additive genetic variance for LMA, LMD and LMP, respectively. The CNVR analyses and wssGWAS identified five common regions, of which three regions were associated with LMA and two with LMP. Four genes (DOK7, ARAP1, ELMO2 and SLC13A3) were highlighted as promising candidates according to their function.

CONCLUSIONS

We determined an overall validation rate for the CNV detection accuracy of low-density chip data and constructed a genomic CNV map for Duroc pigs using resequencing, thereby proving a value genetic variation resource for pig genome research. Furthermore, our study utilized a composite genetic strategy for complex traits in pigs, which will contribute to the study for elucidating the genetic architecture that may be influenced and regulated by multiple forms of variations.

Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10-9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.

Shared Genetic Basis and Causal Relationship Between Television Watching, Breakfast Skipping and Type 2 Diabetes: Evidence From a Comprehensive Genetic Analysis

Background

Epidemiological investigations have established unhealthy lifestyles, such as excessive leisurely sedentary behavior (especially TV/television watching) and breakfast skipping, increase the risk of type 2 diabetes (T2D), but the causal relationship is unclear. We aimed to understand how single nucleotide variants contribute to the co-occurrence of unhealthy lifestyles and T2D, thereby providing meaningful insights into disease mechanisms.

Methods

Combining summary statistics from genome-wide association studies (GWAS) on TV watching (N = 422218), breakfast skipping (N = 193860) and T2D (N = 159208) in European pedigrees, we conducted comprehensive pairwise genetic analysis, including high-definition likelihood (HDL-method), cross-phenotype association studies (CPASSOC), GWAS-eQTL colocalization analysis and transcriptome-wide association studies (TWAS), to understand the genetic overlap between them. We also performed bidirectional two-sample Mendelian randomization (MR) analysis for causal inference using genetic instrumental variables, and two-step MR mediation analysis was used to assess any effects explained by body mass index, lipid traits and glycemic traits.

Results

HDL-method showed that T2D shared a strong genetic correlation with TV watching (rg = 0.26; P = 1.63×10-29) and skipping breakfast (rg = 0.15; P =2.02×10-6). CPASSOC identifies eight independent SNPs shared between T2D and TV watching, including one novel shared locus. TWAS and CPASSOC showed that shared genes were enriched in lung, esophageal, adipose, and thyroid tissues and highlighted potential shared regulatory pathways for lipoprotein metabolism, pancreatic β-cell function, cellular senescence and multi-mediator factors. MR showed TV watching had a causal effect on T2D (βIVW = 0.629, PIVW = 1.80×10-10), but no significant results were observed between breakfast skipping and T2D. Mediation analysis provided evidence that body mass index, fasting glucose, hemoglobin A1c and high-density lipoprotein are potential factors that mediate the causal relationship between TV and T2D.

Conclusions

Our findings provide strong evidence of shared genetics and causation between TV watching and T2D and facilitate our identification of common genetic architectures shared between them.

Deep Resequencing of 9 Candidate Genes Identifies a Role for ARAP1 and IGF2BP2 in Modulating Insulin Secretion Adjusted for Insulin Resistance in Obese Southern Europeans

Type 2 diabetes is characterized by impairment in insulin secretion, with an established genetic contribution. We aimed to evaluate common and low-frequency (1–5%) variants in nine genes strongly associated with insulin secretion by targeted sequencing in subjects selected from the extremes of insulin release measured by the disposition index. Collapsing data by gene and/or function, the association between disposition index and nonsense variants were significant, also after adjustment for confounding factors (OR = 0.25, 95% CI = 0.11–0.59, p = 0.001). Evaluating variants individually, three novel variants in ARAP1, IGF2BP2 and GCK, out of eight reaching significance singularly, remained associated after adjustment. Constructing a genetic risk model combining the effects of the three variants, only carriers of the ARAP1 and IGF2BP2 variants were significantly associated with a reduced probability to be in the lower, worst, extreme of insulin secretion (OR = 0.223, 95% CI = 0.105–0.473, p < 0.001). Observing a high number of normal glucose tolerance between carriers, a regression posthoc analysis was performed. Carriers of genetic risk model variants had higher probability to be normoglycemic, also after adjustment (OR = 2.411, 95% CI = 1.136–5.116, p = 0.022). Thus, in our southern European cohort, nonsense variants in all nine candidate genes showed association with better insulin secretion adjusted for insulin resistance, and we established the role of ARAP1 and IGF2BP2 in modulating insulin secretion.

Stem Cell-Derived β Cells: A Versatile Research Platform to Interrogate the Genetic Basis of β Cell Dysfunction

Pancreatic β cell dysfunction is a central component of diabetes progression. During the last decades, the genetic basis of several monogenic forms of diabetes has been recognized. Genome-wide association studies (GWAS) have also facilitated the identification of common genetic variants associated with an increased risk of diabetes. These studies highlight the importance of impaired β cell function in all forms of diabetes. However, how most of these risk variants confer disease risk, remains unanswered. Understanding the specific contribution of genetic variants and the precise role of their molecular effectors is the next step toward developing treatments that target β cell dysfunction in the era of personalized medicine. Protocols that allow derivation of β cells from pluripotent stem cells, represent a powerful research tool that allows modeling of human development and versatile experimental designs that can be used to shed some light on diabetes pathophysiology. This article reviews different models to study the genetic basis of β cell dysfunction, focusing on the recent advances made possible by stem cell applications in the field of diabetes research.

Identification of direct transcriptional targets of NFATC2 that promote β cell proliferation

The transcription factor NFATC2 induces β cell proliferation in mouse and human islets. However, the genomic targets that mediate these effects have not been identified. We expressed active forms of Nfatc2 and Nfatc1 in human islets. By integrating changes in gene expression with genomic binding sites for NFATC2, we identified approximately 2200 transcriptional targets of NFATC2. Genes induced by NFATC2 were enriched for transcripts that regulate the cell cycle and for DNA motifs associated with the transcription factor FOXP. Islets from an endocrine-specific Foxp1, Foxp2, and Foxp4 triple-knockout mouse were less responsive to NFATC2-induced β cell proliferation, suggesting the FOXP family works to regulate β cell proliferation in concert with NFATC2. NFATC2 induced β cell proliferation in both mouse and human islets, whereas NFATC1 did so only in human islets. Exploiting this species difference, we identified approximately 250 direct transcriptional targets of NFAT in human islets. This gene set enriches for cell cycle-associated transcripts and includes Nr4a1. Deletion of Nr4a1 reduced the capacity of NFATC2 to induce β cell proliferation, suggesting that much of the effect of NFATC2 occurs through its induction of Nr4a1. Integration of noncoding RNA expression, chromatin accessibility, and NFATC2 binding sites enabled us to identify NFATC2-dependent enhancer loci that mediate β cell proliferation.

STARD3: A Prospective Target for Cancer Therapy

Cancer is one of the major causes of death in developed countries and current therapies are based on surgery, chemotherapeutic agents, and radiation. To overcome side effects induced by chemo- and radiotherapy, in recent decades, targeted therapies have been proposed in second and even first lines. Targeted drugs act on the essential pathways involved in tumor induction, progression, and metastasis, basically all the hallmark of cancers. Among emerging pathways, the cholesterol metabolic pathway is a strong candidate for this purpose. Cancer cells have an accelerated metabolic rate and require a continuous supply of cholesterol for cell division and membrane renewal. Steroidogenic acute regulatory related lipid transfer (START) proteins are a family of proteins involved in the transfer of lipids and some of them are important in non-vesicular cholesterol transportation within the cell. The alteration of their expression levels is implicated in several diseases, including cancers. In this review, we report the latest discoveries on StAR-related lipid transfer protein domain 3 (STARD3), a member of the START family, which has a potential role in cancer, focusing on the structural and biochemical characteristics and mechanisms that regulate its activity. The role of the STARD3 protein as a molecular target for the development of cancer therapies is also discussed. As STARD3 is a key protein in the cholesterol movement in cancer cells, it is of interest to identify inhibitors able to block its activity.

Multi-omics profiling of living human pancreatic islet donors reveals heterogeneous beta cell trajectories towards type 2 diabetes

Most research on human pancreatic islets is conducted on samples obtained from normoglycaemic or diseased brain-dead donors and thus cannot accurately describe the molecular changes of pancreatic islet beta cells as they progress towards a state of deficient insulin secretion in type 2 diabetes (T2D). Here, we conduct a comprehensive multi-omics analysis of pancreatic islets obtained from metabolically profiled pancreatectomized living human donors stratified along the glycemic continuum, from normoglycemia to T2D. We find that islet pools isolated from surgical samples by laser-capture microdissection display remarkably more heterogeneous transcriptomic and proteomic profiles in patients with diabetes than in non-diabetic controls. The differential regulation of islet gene expression is already observed in prediabetic individuals with impaired glucose tolerance. Our findings demonstrate a progressive, but disharmonic, remodelling of mature beta cells, challenging current hypotheses of linear trajectories toward precursor or transdifferentiation stages in T2D. Furthermore, through integration of islet transcriptomics with preoperative blood plasma lipidomics, we define the relative importance of gene coexpression modules and lipids that are positively or negatively associated with HbA1c levels, pointing to potential prognostic markers.

Sexually dimorphic roles for the type 2 diabetes-associated C2cd4b gene in murine glucose homeostasis

AIMS/HYPOTHESIS

Variants close to the VPS13C/C2CD4A/C2CD4B locus are associated with altered risk of type 2 diabetes in genome-wide association studies. While previous functional work has suggested roles for VPS13C and C2CD4A in disease development, none has explored the role of C2CD4B.

METHODS

CRISPR/Cas9-induced global C2cd4b-knockout mice and zebrafish larvae with c2cd4a deletion were used to study the role of this gene in glucose homeostasis. C2 calcium dependent domain containing protein (C2CD)4A and C2CD4B constructs tagged with FLAG or green fluorescent protein were generated to investigate subcellular dynamics using confocal or near-field microscopy and to identify interacting partners by mass spectrometry.

RESULTS

Systemic inactivation of C2cd4b in mice led to marked, but highly sexually dimorphic changes in body weight and glucose homeostasis. Female C2cd4b mice displayed unchanged body weight compared with control littermates, but abnormal glucose tolerance (AUC, p = 0.01) and defective in vivo, but not in vitro, insulin secretion (p = 0.02). This was associated with a marked decrease in follicle-stimulating hormone levels as compared with wild-type (WT) littermates (p = 0.003). In sharp contrast, male C2cd4b null mice displayed essentially normal glucose tolerance but an increase in body weight (p < 0.001) and fasting blood glucose (p = 0.003) after maintenance on a high-fat and -sucrose diet vs WT littermates. No metabolic disturbances were observed after global inactivation of C2cd4a in mice, or in pancreatic beta cell function at larval stages in C2cd4a null zebrafish. Fasting blood glucose levels were also unaltered in adult C2cd4a-null fish. C2CD4B and C2CD4A were partially localised to the plasma membrane, with the latter under the control of intracellular Ca2+. Binding partners for both included secretory-granule-localised PTPRN2/phogrin.

CONCLUSIONS/INTERPRETATION

Our studies suggest that C2cd4b may act centrally in the pituitary to influence sex-dependent circuits that control pancreatic beta cell function and glucose tolerance in rodents. However, the absence of sexual dimorphism in the impact of diabetes risk variants argues for additional roles for C2CD4A or VPS13C in the control of glucose homeostasis in humans.

DATA AVAILABILITY

The datasets generated and/or analysed during the current study are available in the Biorxiv repository ( www.biorxiv.org/content/10.1101/2020.05.18.099200v1 ). RNA-Seq (GSE152576) and proteomics (PXD021597) data have been deposited to GEO ( www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE152576 ) and ProteomeXchange ( www.ebi.ac.uk/pride/archive/projects/PXD021597 ) repositories, respectively.

Single-cell chromatin accessibility identifies pancreatic islet cell type- and state-specific regulatory programs of diabetes risk

Single-nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq) creates new opportunities to dissect cell type-specific mechanisms of complex diseases. Since pancreatic islets are central to type 2 diabetes (T2D), we profiled 15,298 islet cells by using combinatorial barcoding snATAC-seq and identified 12 clusters, including multiple alpha, beta and delta cell states. We cataloged 228,873 accessible chromatin sites and identified transcription factors underlying lineage- and state-specific regulation. We observed state-specific enrichment of fasting glucose and T2D genome-wide association studies for beta cells and enrichment for other endocrine cell types. At T2D signals localized to islet-accessible chromatin, we prioritized variants with predicted regulatory function and co-accessibility with target genes. A causal T2D variant rs231361 at the KCNQ1 locus had predicted effects on a beta cell enhancer co-accessible with INS and genome editing in embryonic stem cell-derived beta cells affected INS levels. Together our findings demonstrate the power of single-cell epigenomics for interpreting complex disease genetics.

Chromatin 3D interaction analysis of the STARD10 locus unveils FCHSD2 as a regulator of insulin secretion

Using chromatin conformation capture, we show that an enhancer cluster in the STARD10 type 2 diabetes (T2D) locus forms a defined 3-dimensional (3D) chromatin domain. A 4.1-kb region within this locus, carrying 5 T2D-associated variants, physically interacts with CTCF-binding regions and with an enhancer possessing strong transcriptional activity. Analysis of human islet 3D chromatin interaction maps identifies the FCHSD2 gene as an additional target of the enhancer cluster. CRISPR-Cas9-mediated deletion of the variant region, or of the associated enhancer, from human pancreas-derived EndoC-βH1 cells impairs glucose-stimulated insulin secretion. Expression of both STARD10 and FCHSD2 is reduced in cells harboring CRISPR deletions, and lower expression of STARD10 and FCHSD2 is associated, the latter nominally, with the possession of risk variant alleles in human islets. Finally, CRISPR-Cas9-mediated loss of STARD10 or FCHSD2, but not ARAP1, impairs regulated insulin secretion. Thus, multiple genes at the STARD10 locus influence β cell function.

Genome-wide discovery of genetic loci that uncouple excess adiposity from its comorbidities

Obesity is a major risk factor for cardiometabolic diseases. Nevertheless, a substantial proportion of individuals with obesity do not suffer cardiometabolic comorbidities. The mechanisms that uncouple adiposity from its cardiometabolic complications are not fully understood. Here, we identify 62 loci of which the same allele is significantly associated with both higher adiposity and lower cardiometabolic risk. Functional analyses show that the 62 loci are enriched for genes expressed in adipose tissue, and for regulatory variants that influence nearby genes that affect adipocyte differentiation. Genes prioritized in each locus support a key role of fat distribution (FAM13A, IRS1 and PPARG) and adipocyte function (ALDH2, CCDC92, DNAH10, ESR1, FAM13A, MTOR, PIK3R1 and VEGFB). Several additional mechanisms are involved as well, such as insulin-glucose signalling (ADCY5, ARAP1, CREBBP, FAM13A, MTOR, PEPD, RAC1 and SH2B3), energy expenditure and fatty acid oxidation (IGF2BP2), browning of white adipose tissue (CSK, VEGFA, VEGFB and SLC22A3) and inflammation (SH2B3, DAGLB and ADCY9). Some of these genes may represent therapeutic targets to reduce cardiometabolic risk linked to excess adiposity.

Normal and defective pathways in biogenesis and maintenance of the insulin storage pool

Both basal and glucose-stimulated insulin release occur primarily by insulin secretory granule exocytosis from pancreatic β cells, and both are needed to maintain normoglycemia. Loss of insulin-secreting β cells, accompanied by abnormal glucose tolerance, may involve simple exhaustion of insulin reserves (which, by immunostaining, appears as a loss of β cell identity), or β cell dedifferentiation, or β cell death. While various sensing and signaling defects can result in diminished insulin secretion, somewhat less attention has been paid to diabetes risk caused by insufficiency in the biosynthetic generation and maintenance of the total insulin granule storage pool. This Review offers an overview of insulin biosynthesis, beginning with the preproinsulin mRNA (translation and translocation into the ER), proinsulin folding and export from the ER, and delivery via the Golgi complex to secretory granules for conversion to insulin and ultimate hormone storage. All of these steps are needed for generation and maintenance of the total insulin granule pool, and defects in any of these steps may, weakly or strongly, perturb glycemic control. The foregoing considerations have obvious potential relevance to the pathogenesis of type 2 diabetes and some forms of monogenic diabetes; conceivably, several of these concepts might also have implications for β cell failure in type 1 diabetes.

Characterization of progression-related alternative splicing events in testicular germ cell tumors

Accumulating evidence supports the significance of aberrant alternative splicing (AS) events in cancer; however, genome-wide profiling of progression-free survival (PFS)-related AS events in testicular germ cell tumors (TGCT) has not been reported. Here, we analyzed high-throughput RNA-sequencing data and percent-spliced-in values for 150 patients with TGCT. Using univariate and multivariate Cox regression analysis and a least absolute shrinkage and selection operator method, we identified the top 15 AS events most closely associated with disease progression. A risk-associated AS score (ASS) for the 15 AS events was calculated for each patient. ASS, pathological stage, and T stage were significantly associated with disease progression by univariate analysis, but only ASS and pathological stage remained significant by multivariate analysis. The ability of these variables to predict 5-year progression was assessed using receiver operating characteristic curve analysis. ASS had stronger predictive value than a combination of age, pathological stage, and T stage (area under the curve = 0.899 and 0.715, respectively). Furthermore, Kaplan–Meier analysis of patients with low and high ASS demonstrated that high ASS was associated with significantly worse PFS than low ASS (P = 1.46 × 10⁻⁷). We also analyzed the biological functions of the PFS-related AS-related genes and found enrichment in pathways associated with DNA repair and modification. Finally, we identified a regulatory network of splicing factors with expression levels that correlated significantly with AS events in TGCT. Collectively, this study identifies a novel method for risk stratification of patients and provides insight into the molecular events underlying TGCT.

Insulin granule biogenesis and exocytosis

Insulin is produced by pancreatic β-cells, and once released to the blood, the hormone stimulates glucose uptake and suppresses glucose production. Defects in both the availability and action of insulin lead to elevated plasma glucose levels and are major hallmarks of type-2 diabetes. Insulin is stored in secretory granules that form at the trans-Golgi network. The granules undergo extensive modifications en route to their release sites at the plasma membrane, including changes in both protein and lipid composition of the granule membrane and lumen. In parallel, the insulin molecules also undergo extensive modifications that render the hormone biologically active. In this review, we summarize current understanding of insulin secretory granule biogenesis, maturation, transport, docking, priming and eventual fusion with the plasma membrane. We discuss how different pools of granules form and how these pools contribute to insulin secretion under different conditions. We also highlight the role of the β-cell in the development of type-2 diabetes and discuss how dysregulation of one or several steps in the insulin granule life cycle may contribute to disease development or progression.

Functional Genomics in Pancreatic β Cells: Recent Advances in Gene Deletion and Genome Editing Technologies for Diabetes Research

The inheritance of variants that lead to coding changes in, or the mis-expression of, genes critical to pancreatic beta cell function can lead to alterations in insulin secretion and increase the risk of both type 1 and type 2 diabetes. Recently developed clustered regularly interspaced short palindromic repeats (CRISPR/Cas9) gene editing tools provide a powerful means of understanding the impact of identified variants on cell function, growth, and survival and might ultimately provide a means, most likely after the transplantation of genetically "corrected" cells, of treating the disease. Here, we review some of the disease-associated genes and variants whose roles have been probed up to now. Next, we survey recent exciting developments in CRISPR/Cas9 technology and their possible exploitation for β cell functional genomics. Finally, we will provide a perspective as to how CRISPR/Cas9 technology may find clinical application in patients with diabetes.

Metabolic and functional specialisations of the pancreatic beta cell: gene disallowance, mitochondrial metabolism and intercellular connectivity

All forms of diabetes mellitus involve the loss or dysfunction of pancreatic beta cells, with the former predominating in type 1 diabetes and the latter in type 2 diabetes. Deeper understanding of the coupling mechanisms that link glucose metabolism in these cells to the control of insulin secretion is therefore likely to be essential to develop new therapies. Beta cells display a remarkable metabolic specialisation, expressing high levels of metabolic sensing enzymes, including the glucose transporter GLUT2 (encoded by SLC2A2) and glucokinase (encoded by GCK). Genetic evidence flowing from both monogenic forms of diabetes and genome-wide association studies for the more common type 2 diabetes, supports the importance for normal glucose-stimulated insulin secretion of metabolic signalling via altered ATP generation, while also highlighting unsuspected roles for Zn2+ storage, intracellular lipid transfer and other processes. Intriguingly, genes involved in non-oxidative metabolic fates of the sugar, such as those for lactate dehydrogenase (LDHA) and monocarboxylate transporter-1 ([MCT-1] SLC16A1), as well as the acyl-CoA thioesterase (ACOT7) and others, are selectively repressed ('disallowed') in beta cells. Furthermore, mutations in genes critical for mitochondrial oxidative metabolism, such as TRL-CAG1-7 encoding tRNALeu, are linked to maternally inherited forms of diabetes. Correspondingly, impaired Ca2+ uptake into mitochondria, or collapse of a normally interconnected mitochondrial network, are associated with defective insulin secretion. Here, we suggest that altered mitochondrial metabolism may also impair beta cell-beta cell communication. Thus, we argue that defective oxidative glucose metabolism is central to beta cell failure in diabetes, acting both at the level of single beta cells and potentially across the whole islet to impair insulin secretion. Graphical abstract.

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.

Dietary substitution of SFA with MUFA within high-fat diets attenuates hyperinsulinaemia and pancreatic islet dysfunction

Preliminary evidence has suggested that high-fat diets (HFD) enriched with SFA, but not MUFA, promote hyperinsulinaemia and pancreatic hypertrophy with insulin resistance. The objective of this study was to determine whether the substitution of dietary MUFA within a HFD could attenuate the progression of pancreatic islet dysfunction seen with prolonged SFA-HFD. For 32 weeks, C57BL/6J mice were fed either: (1) low-fat diet, (2) SFA-HFD or (3) SFA-HFD for 16 weeks, then switched to MUFA-HFD for 16 weeks (SFA-to-MUFA-HFD). Fasting insulin was assessed throughout the study; islets were isolated following the intervention. Substituting SFA with MUFA-HFD prevented the progression of hyperinsulinaemia observed in SFA-HFD mice (P < 0·001). Glucose-stimulated insulin secretion from isolated islets was reduced by SFA-HFD, yet not fully affected by SFA-to-MUFA-HFD. Markers of β-cell identity (Ins2, Nkx6.1, Ngn3, Rfx6, Pdx1 and Pax6) were reduced, and islet inflammation was increased (IL-1β, 3·0-fold, P = 0·007; CD68, 2·9-fold, P = 0·001; Il-6, 1·1-fold, P = 0·437) in SFA-HFD - effects not seen with SFA-to-MUFA-HFD. Switching to MUFA-HFD can partly attenuate the progression of SFA-HFD-induced hyperinsulinaemia, pancreatic inflammation and impairments in β-cell function. While further work is required from a mechanistic perspective, dietary fat may mediate its effect in an IL-1β-AMP-activated protein kinase α1-dependent fashion. Future work should assess the potential translation of the modulation of metabolic inflammation in man.

Transcription Factor KLF14 and Metabolic Syndrome

Metabolic syndrome (MetSyn) is a combination of metabolic abnormalities that lead to the development of cardiovascular disease (CVD) and Type 2 Diabetes (T2D). Although various criteria for defining MetSyn exist, common abnormalities include abdominal obesity, elevated serum triglyceride, insulin resistance, and blood glucose, decreased high-density lipoprotein cholesterol (HDL-C), and hypertension. MetSyn prevalence has been increasing with the rise of obesity worldwide, with significantly higher prevalence in women compared with men and in Hispanics compared with Whites. Affected individuals are at a higher risk of developing T2D (5-fold) and CVD (2-fold). Heritability estimates for individual components of MetSyn vary between 40 and 70%, suggesting a strong contribution of an individual's genetic makeup to disease pathology. The advent of next-generation sequencing technologies has enabled large-scale genome-wide association studies (GWAS) into the genetics underlying MetSyn pathogenesis. Several such studies have implicated the transcription factor KLF14, a member of the Krüpple-like factor family (KLF), in the development of metabolic diseases, including obesity, insulin resistance, and T2D. How KLF14 regulates these metabolic traits and increases the risk of developing T2D, atherosclerosis, and liver dysfunction is still unknown. There have been some debate and controversial results with regards to its expression profile and functionality in various tissues, and a systematic review of current knowledge on KLF14 is lacking. Here, we summarize the research progress made in understanding the function of KLF14 and describe common attributes of its biochemical, physiological, and pathophysiological roles. We also discuss the current challenges in understanding the role of KLF14 in metabolism and provide suggestions for future directions.

The type 2 diabetes gene product STARD10 is a phosphoinositide-binding protein that controls insulin secretory granule biogenesis

OBJECTIVE

Risk alleles for type 2 diabetes at the STARD10 locus are associated with lowered STARD10 expression in the β-cell, impaired glucose-induced insulin secretion, and decreased circulating proinsulin:insulin ratios. Although likely to serve as a mediator of intracellular lipid transfer, the identity of the transported lipids and thus the pathways through which STARD10 regulates β-cell function are not understood. The aim of this study was to identify the lipids transported and affected by STARD10 in the β-cell and the role of the protein in controlling proinsulin processing and insulin granule biogenesis and maturation.

METHODS

We used isolated islets from mice deleted selectively in the β-cell for Stard10 (βStard10KO) and performed electron microscopy, pulse-chase, RNA sequencing, and lipidomic analyses. Proteomic analysis of STARD10 binding partners was executed in the INS1 (832/13) cell line. X-ray crystallography followed by molecular docking and lipid overlay assay was performed on purified STARD10 protein.

RESULTS

βStard10KO islets had a sharply altered dense core granule appearance, with a dramatic increase in the number of "rod-like" dense cores. Correspondingly, basal secretion of proinsulin was increased versus wild-type islets. The solution of the crystal structure of STARD10 to 2.3 Å resolution revealed a binding pocket capable of accommodating polyphosphoinositides, and STARD10 was shown to bind to inositides phosphorylated at the 3' position. Lipidomic analysis of βStard10KO islets demonstrated changes in phosphatidylinositol levels, and the inositol lipid kinase PIP4K2C was identified as a STARD10 binding partner. Also consistent with roles for STARD10 in phosphoinositide signalling, the phosphoinositide-binding proteins Pirt and Synaptotagmin 1 were amongst the differentially expressed genes in βStard10KO islets.

CONCLUSION

Our data indicate that STARD10 binds to, and may transport, phosphatidylinositides, influencing membrane lipid composition, insulin granule biosynthesis, and insulin processing.

A CRISPR/Cas9 genome editing pipeline in the EndoC-βH1 cell line to study genes implicated in beta cell function

Type 2 diabetes (T2D) is a global pandemic with a strong genetic component, but most causal genes influencing the disease risk remain unknown. It is clear, however, that the pancreatic beta cell is central to T2D pathogenesis. In vitro gene-knockout (KO) models to study T2D risk genes have so far focused on rodent beta cells. However, there are important structural and functional differences between rodent and human beta cell lines. With that in mind, we have developed a robust pipeline to create a stable CRISPR/Cas9 KO in an authentic human beta cell line (EndoC-βH1). The KO pipeline consists of a dual lentiviral sgRNA strategy and we targeted three genes ( INS, IDE, PAM) as a proof of concept. We achieved a significant reduction in mRNA levels and complete protein depletion of all target genes. Using this dual sgRNA strategy, up to 94 kb DNA were cut out of the target genes and the editing efficiency of each sgRNA exceeded >87.5%. Sequencing of off-targets showed no unspecific editing. Most importantly, the pipeline did not affect the glucose-responsive insulin secretion of the cells. Interestingly, comparison of KO cell lines for NEUROD1 and SLC30A8 with siRNA-mediated knockdown (KD) approaches demonstrate phenotypic differences. NEUROD1-KO cells were not viable and displayed elevated markers for ER stress and apoptosis. NEUROD1-KD, however, only had a modest elevation, by 34%, in the pro-apoptotic transcription factor CHOP and a gene expression profile indicative of chronic ER stress without evidence of elevated cell death. On the other hand, SLC30A8-KO cells demonstrated no reduction in K ATP channel gene expression in contrast to siRNA silencing. Overall, this strategy to efficiently create stable KO in the human beta cell line EndoC-βH1 will allow for a better understanding of genes involved in beta cell dysfunction, their underlying functional mechanisms and T2D pathogenesis.

From Genetic Association to Molecular Mechanisms for Islet-cell Dysfunction in Type 2 Diabetes

Genome-wide association studies (GWAS) have identified over 400 signals robustly associated with risk for type 2 diabetes (T2D). At the vast majority of these loci, the lead single nucleotide polymorphisms (SNPs) reside in noncoding regions of the genome, which hampers biological inference and translation of genetic discoveries into disease mechanisms. The study of these T2D risk variants in normoglycemic individuals has revealed that a significant proportion are exerting their disease risk through islet-cell dysfunction. The central role of the islet is also demonstrated by numerous studies, which have shown an enrichment of these signals in islet-specific epigenomic annotations. In recent years the emergence of authentic human beta-cell lines, and advances in genome-editing technologies coupled with improved protocols differentiating human pluripotent stem cells into beta-like cells has opened up new opportunities for T2D disease modeling. Here we review the current understanding on the genetic basis of T2D focusing on approaches, which have facilitated the identification of causal variants and their effector transcripts in human islets. We will present examples of functional studies based on animal and conventional cellular systems and highlight the potential of novel stem cell-based T2D disease models.

Analysis of the genetic variants associated with circulating levels of sgp130. Results from the IMPROVE study

The genes regulating circulating levels of soluble gp130 (sgp130), the antagonist of the inflammatory response in atherosclerosis driven by interleukin 6, are largely unknown. Aims of the present study were to identify genetic loci associated with circulating sgp130 and to explore the potential association between variants associated with sgp130 and markers of subclinical atherosclerosis. The study is based on IMPROVE (n = 3703), a cardiovascular multicentre study designed to investigate the determinants of carotid intima media thickness, a measure of subclinical atherosclerosis. Genomic DNA was genotyped by the CardioMetaboChip and ImmunoChip. About 360,842 SNPs were tested for association with log-transformed sgp130, using linear regression adjusted for age, gender, and population stratification using PLINK v1.07. A p value of 1 × 10⁻⁵ was chosen as threshold for significance value. In an exploratory analysis, SNPs associated with sgp130 were tested for association with c-IMT measures. We identified two SNPs significantly associated with sgp130 levels and 24 showing suggestive association with sgp130 levels. One SNP (rs17688225) on chromosome 14 was positively associated with sgp130 serum levels (β = 0.03 SE = 0.007, p = 4.77 × 10⁻⁵) and inversely associated with c-IMT (c-IMT_mean–maxβ = −0.001 SE = 0.005, p = 0.0342). Our data indicate that multiple loci regulate sgp130 levels and suggest a possible common pathway between sgp130 and c-IMT measures.

Identifying the association between single nucleotide polymorphisms in KCNQ1, ARAP1, and KCNJ11 and type 2 diabetes mellitus in a Chinese population

Background: Type 2 diabetes mellitus (T2DM) has a high global prevalence, and insufficient insulin secretion is one of the major reasons for its development. Therefore, investigating the association between T2DM and the single nucleotide polymorphisms (SNPs) in genes associated with insulin secretion is necessary. Methods: T2DM (1,194) and nondiabetic (NDM) (1,292) subjects were enrolled and the ten single nucleotide polymorphisms (SNPs) in KCNQ1, ARAP1, and KCNJ11 associated with insulin secretion were genotyped in a Chinese population. Results: Our data revealed that the rs2237897T allele in KCNQ1 is the protective allele for T2DM (P<0.001, OR=0.793; 95%CI: 0.705-0.893). However, the A allele of rs1552224 in ARAP1 may be a risk factor for T2DM (P=0.002, OR=12.070; 95% CI: 1.578-92.337). The haplotype analysis revealed that rs151290-rs2237892CC and rs2237895-rs2237897CC in KCNQ1 constitute the risk haplotype in T2DM development (P=0.010, OR=1.160; 95% CI: 1.037-1.299 and P=0.004, OR=1.192; 95% CI: 1.057-1.344). Moreover, rs2237895-rs2237897AT in KCNQ1 constitutes the protective haplotype in T2DM (P=0.001, OR=0.819; 95% CI: 0.727-0.923). In the inheritance models analysis, the rs2283228 (C/A-C/C) genotype is the protective factor compared to the A/A genotype (P=0.005, OR=0.79; 95% CI: 0.68-0.93). For rs2237897, the C/T-T/T genotype is the protective factor compared to the C/C genotype (P<0.001, OR=0.74; 95% CI: 0.63-0.87). Furthermore, when compared with the rs2237897 (C/T-T/T) genotype, rs2237897C/C genotype showed higher HbA1C levels (8.731±2.697 vs 9.282±2.921, P=0.001). Conclusion: Our results revealed that genetic variations in KCNQ1 and ARAP1 were associated with T2DM susceptibility in a Chinese population.

Pancreatic Islet Transcriptional Enhancers and Diabetes

PURPOSE OF REVIEW

Common genetic variants that associate with type 2 diabetes risk are markedly enriched in pancreatic islet transcriptional enhancers. This review discusses current advances in the annotation of islet enhancer variants and their target genes.

RECENT FINDINGS

Recent methodological advances now allow genetic and functional mapping of diabetes causal variants at unprecedented resolution. Mapping of enhancer-promoter interactions in human islets has provided a unique appreciation of the complexity of islet gene regulatory processes and enabled direct association of noncoding diabetes risk variants to their target genes. The recently improved human islet enhancer annotations constitute a framework for the interpretation of diabetes genetic signals in the context of pancreatic islet gene regulation. In the future, integration of existing and yet to come regulatory maps with genetic fine-mapping efforts and in-depth functional characterization will foster the discovery of novel diabetes molecular risk mechanisms.

A CRISPR/Cas9 genome editing pipeline in the EndoC-βH1 cell line to study genes implicated in beta cell function

Type 2 diabetes (T2D) is a global pandemic with a strong genetic component, but most causal genes influencing the disease risk remain unknown. It is clear, however, that the pancreatic beta cell is central to T2D pathogenesis. In vitro gene-knockout (KO) models to study T2D risk genes have so far focused on rodent beta cells. However, there are important structural and functional differences between rodent and human beta cell lines. With that in mind, we have developed a robust pipeline to create a stable CRISPR/Cas9 KO in an authentic human beta cell line (EndoC-βH1). The KO pipeline consists of a dual lentiviral sgRNA strategy and we targeted three genes ( INS, IDE, PAM) as a proof of concept. We achieved a significant reduction in mRNA levels and complete protein depletion of all target genes. Using this dual sgRNA strategy, up to 94 kb DNA were cut out of the target genes and the editing efficiency of each sgRNA exceeded >87.5%. Sequencing of off-targets showed no unspecific editing. Most importantly, the pipeline did not affect the glucose-responsive insulin secretion of the cells. Interestingly, comparison of KO cell lines for NEUROD1 and SLC30A8 with siRNA-mediated knockdown (KD) approaches demonstrate phenotypic differences. NEUROD1-KO cells were not viable and displayed elevated markers for ER stress and apoptosis. NEUROD1-KD, however, only had a modest elevation, by 34%, in the pro-apoptotic transcription factor CHOP and a gene expression profile indicative of chronic ER stress without evidence of elevated cell death. On the other hand, SLC30A8-KO cells demonstrated no reduction in K ATP channel gene expression in contrast to siRNA silencing. Overall, this strategy to efficiently create stable KO in the human beta cell line EndoC-βH1 will allow for a better understanding of genes involved in beta cell dysfunction, their underlying functional mechanisms and T2D pathogenesis.

Laser capture microdissection of human pancreatic islets reveals novel eQTLs associated with type 2 diabetes

OBJECTIVE

Genome wide association studies (GWAS) for type 2 diabetes (T2D) have identified genetic loci that often localise in non-coding regions of the genome, suggesting gene regulation effects. We combined genetic and transcriptomic analysis from human islets obtained from brain-dead organ donors or surgical patients to detect expression quantitative trait loci (eQTLs) and shed light into the regulatory mechanisms of these genes.

METHODS

Pancreatic islets were isolated either by laser capture microdissection (LCM) from surgical specimens of 103 metabolically phenotyped pancreatectomized patients (PPP) or by collagenase digestion of pancreas from 100 brain-dead organ donors (OD). Genotyping (> 8.7 million single nucleotide polymorphisms) and expression (> 47,000 transcripts and splice variants) analyses were combined to generate cis-eQTLs.

RESULTS

After applying genome-wide false discovery rate significance thresholds, we identified 1,173 and 1,021 eQTLs in samples of OD and PPP, respectively. Among the strongest eQTLs shared between OD and PPP were CHURC1 (OD p-value=1.71 × 10^-24; PPP p-value = 3.64 × 10^-24) and PSPH (OD p-value = 3.92 × 10^-26; PPP p-value = 3.64 × 10^-24). We identified eQTLs in linkage-disequilibrium with GWAS loci T2D and associated traits, including TTLL6, MLX and KIF9 loci, which do not implicate the nearest gene. We found in the PPP datasets 11 eQTL genes, which were differentially expressed in T2D and two genes (CYP4V2 and TSEN2) associated with HbA1c but none in the OD samples.

CONCLUSIONS

eQTL analysis of LCM islets from PPP led us to identify novel genes which had not been previously linked to islet biology and T2D. The understanding gained from eQTL approaches, especially using surgical samples of living patients, provides a more accurate 3-dimensional representation than those from genetic studies alone.

Type 2 diabetes genetic loci informed by multi-trait associations point to disease mechanisms and subtypes: A soft clustering analysis

BACKGROUND

Type 2 diabetes (T2D) is a heterogeneous disease for which (1) disease-causing pathways are incompletely understood and (2) subclassification may improve patient management. Unlike other biomarkers, germline genetic markers do not change with disease progression or treatment. In this paper, we test whether a germline genetic approach informed by physiology can be used to deconstruct T2D heterogeneity. First, we aimed to categorize genetic loci into groups representing likely disease mechanistic pathways. Second, we asked whether the novel clusters of genetic loci we identified have any broad clinical consequence, as assessed in four separate subsets of individuals with T2D.

METHODS AND FINDINGS

In an effort to identify mechanistic pathways driven by established T2D genetic loci, we applied Bayesian nonnegative matrix factorization (bNMF) clustering to genome-wide association study (GWAS) results for 94 independent T2D genetic variants and 47 diabetes-related traits. We identified five robust clusters of T2D loci and traits, each with distinct tissue-specific enhancer enrichment based on analysis of epigenomic data from 28 cell types. Two clusters contained variant-trait associations indicative of reduced beta cell function, differing from each other by high versus low proinsulin levels. The three other clusters displayed features of insulin resistance: obesity mediated (high body mass index [BMI] and waist circumference [WC]), "lipodystrophy-like" fat distribution (low BMI, adiponectin, and high-density lipoprotein [HDL] cholesterol, and high triglycerides), and disrupted liver lipid metabolism (low triglycerides). Increased cluster genetic risk scores were associated with distinct clinical outcomes, including increased blood pressure, coronary artery disease (CAD), and stroke. We evaluated the potential for clinical impact of these clusters in four studies containing individuals with T2D (Metabolic Syndrome in Men Study [METSIM], N = 487; Ashkenazi, N = 509; Partners Biobank, N = 2,065; UK Biobank [UKBB], N = 14,813). Individuals with T2D in the top genetic risk score decile for each cluster reproducibly exhibited the predicted cluster-associated phenotypes, with approximately 30% of all individuals assigned to just one cluster top decile. Limitations of this study include that the genetic variants used in the cluster analysis were restricted to those associated with T2D in populations of European ancestry.

CONCLUSION

Our approach identifies salient T2D genetically anchored and physiologically informed pathways, and supports the use of genetics to deconstruct T2D heterogeneity. Classification of patients by these genetic pathways may offer a step toward genetically informed T2D patient management.

Neuronatin regulates pancreatic β cell insulin content and secretion

Neuronatin (Nnat) is an imprinted gene implicated in human obesity and widely expressed in neuroendocrine and metabolic tissues in a hormone- and nutrient-sensitive manner. However, its molecular and cellular functions and precise role in organismal physiology remain only partly defined. Here we demonstrate that mice lacking Nnat globally or specifically in β cells display impaired glucose-stimulated insulin secretion leading to defective glucose handling under conditions of nutrient excess. In contrast, we report no evidence for any feeding or body weight phenotypes in global Nnat-null mice. At the molecular level neuronatin augments insulin signal peptide cleavage by binding to the signal peptidase complex and facilitates translocation of the nascent preprohormone. Loss of neuronatin expression in β cells therefore reduces insulin content and blunts glucose-stimulated insulin secretion. Nnat expression, in turn, is glucose-regulated. This mechanism therefore represents a novel site of nutrient-sensitive control of β cell function and whole-animal glucose homeostasis. These data also suggest a potential wider role for Nnat in the regulation of metabolism through the modulation of peptide processing events.

Insights into Islet Differentiation and Maturation through Proteomic Characterization of a Human iPSC-Derived Pancreatic Endocrine Model

PURPOSE

Great progresses have been made for generating in vitro pluripotent stem cell pancreatic β-like cells. However, the maturation stage of the cells still requires in vivo maturation to recreate the environmental niche. A deeper understanding of the factors promoting maturation of the cells is of great interest for clinical applications.

EXPERIMENTAL DESIGN

Label-free mass spectrometry based proteomic analysis is performed on samples from a longitudinal study of differentiation of human induced pluripotent stem cells toward glucose responsive insulin producing cells.

RESULTS

Proteome patterns correlate with specific transcription factor gene expression levels during in vitro differentiation, showing the relevance of the technology for identification of pancreatic-specific markers. The analysis of proteomes of the implanted cells in a longitudinal study shows that the neovascularization process linked to the extracellular matrix environment is time-dependent and conditions the proper maturation of the cells in β-like cells secreting insulin in response to glucose.

CONCLUSIONS AND CLINICAL RELEVANCE

Proteomic profiling is valuable to qualify and better understand in vivo maturation of progenitor cells toward β-cells. This is critical for future clinical trials where in vivo maturation still needs to be improved for robustness and effectiveness of cell therapy. Novel biomarkers for predicting the efficiency of maturation represents noninvasive monitoring tools for following efficiency of the implant.

Genome-scale portrait and evolutionary significance of human-specific core promoter tri- and tetranucleotide short tandem repeats

BACKGROUND

While there is an ongoing trend to identify single nucleotide substitutions (SNSs) that are linked to inter/intra-species differences and disease phenotypes, short tandem repeats (STRs)/microsatellites may be of equal (if not more) importance in the above processes. Genes that contain STRs in their promoters have higher expression divergence compared to genes with fixed or no STRs in the gene promoters. In line with the above, recent reports indicate a role of repetitive sequences in the rise of young transcription start sites (TSSs) in human evolution.

RESULTS

Following a comparative genomics study of all human protein-coding genes annotated in the GeneCards database, here we provide a genome-scale portrait of human-specific short- and medium-size (≥ 3-repeats) tri- and tetranucleotide STRs and STR motifs in the critical core promoter region between - 120 and + 1 to the TSS and evidence of skewing of this compartment in reference to the STRs that are not human-specific (Levene's test p < 0.001). Twenty-five percent and 26% enrichment of human-specific transcripts was detected in the tri and tetra human-specific compartments (mid-p < 0.00002 and mid-p < 0.002, respectively).

CONCLUSION

Our findings provide the first evidence of genome-scale skewing of STRs at a specific region of the human genome and a link between a number of these STRs and TSS selection/transcript specificity. The STRs and genes listed here may have a role in the evolution and development of characteristics and phenotypes that are unique to the human species.

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.

Skewing of the genetic architecture at the ZMYM3 human-specific 5' UTR short tandem repeat in schizophrenia

Differential expansion of a number of human short tandem repeats (STRs) at the critical core promoter and 5' untranslated region (UTR) support the hypothesis that at least some of these STRs may provide a selective advantage in human evolution. Following a genome-wide screen of all human protein-coding gene 5' UTRs based on the Ensembl database ( http://www.ensembl.org ), we previously reported that the longest STR in this interval is a (GA)₃₂, which belongs to the X-linked zinc finger MYM-type containing 3 (ZMYM3) gene. In the present study, we analyzed the evolutionary implication of this region across evolution and examined the allele and genotype distribution of the "exceptionally long" STR by direct sequencing of 486 Iranian unrelated male subjects consisting of 196 cases of schizophrenia (SCZ) and 290 controls. We found that the ZMYM3 transcript containing the STR is human-specific (ENST00000373998.5). A significant allele variance difference was observed between the cases and controls (Levene's test for equality of variances F = 4.00, p < 0.03). In addition, six alleles were observed in the SCZ patients that were not detected in the control group ("disease-only" alleles) (mid p exact < 0.0003). Those alleles were at the extreme short and long ends of the allele distribution curve and composed 4% of the genotypes in the SCZ group. In conclusion, we found skewing of the genetic architecture at the ZMYM3 STR in SCZ. Further, we found a bell-shaped distribution of alleles and selection against alleles at the extreme ends of this STR. The ZMYM3 STR sets a prototype, the evolutionary course of which determines the range of alleles in a particular species. Extreme "disease-only" alleles and genotypes may change our perspective of adaptive evolution and complex disorders. The ZMYM3 gene "exceptionally long" STR should be sequenced in SCZ and other human-specific phenotypes/characteristics.

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.

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.

Support for "Disease-Only" Genotypes and Excess of Homozygosity at the CYTH4 Primate-Specific GTTT-Repeat in Schizophrenia

OBJECTIVE

The role of short tandem repeats (STRs) in the control of gene expression among species is being increasingly understood following the identification of several instances in which certain STRs occur identically, or expand differentially, in primates versus nonprimates. These STRs may regulate genes that participate in characteristics that are associated with the divergence of primates from sibling orders (e.g., brain higher order functions). The CYTH4 gene contains the longest tetranucleotide STR in its core promoter, at 7-repeats, and links to the evolution of human and nonhuman primates. Allele and genotype distribution of this STR were studied in patients affected by schizophrenia (SCZ) and controls.

METHODS

High-resolution data were obtained on the allele and genotype distribution of the CYTH4 STR and a novel C > T single-nucleotide polymorphism (SNP) at its immediate upstream sequence in 255 patients with SCZ and 249 controls. Each sample was sequenced twice using the fluorescent dye termination method.

RESULTS

Novel alleles were detected at the long extreme of the GTTT-repeat, at 10- and 11-repeats, in the SCZ cases and controls. Excess of homozygosity was observed for the entire range of alleles across the GTTT-repeat and the C > T SNP in the SCZ patients in comparison with the controls (Yates corrected p < 0.011). Three genotypes consisting of the 11-repeat allele (i.e., 11/11, 10/11, and 7/11) were detected only in the SCZ patients (i.e., disease-only genotypes), and contributed to 2.3% of the SCZ genotypes (Mid p exact <0.007). The frequency of the 11-repeat allele was estimated at 0.02 and 0.006 in the SCZ patients and controls, respectively (Mid p exact <0.006).

CONCLUSION

This indicates that STR genotypes that are absent in the control group may be risk factors for SCZ. Future studies are warranted to test the significance of our findings.