Genomics of Islet (Dys)function and Type 2 Diabetes

Discovery of type 2 diabetes mellitus with correlation and optimization driven hybrid deep learning approach

Diabetes mellitus is a severe condition that has the potential to impair strength. The disease known as diabetes mellitus, which is a chronic condition, is brought on by a significant rise in blood glucose levels. The diagnosis of this condition is made using a variety of chemical and physical testing. Diabetes, however, can harm the organs if it goes undetected. This study develops a hybrid deep-learning technique to recognize Type 2 diabetes mellitus. The data is cleaned up at the pre-processing stage using a data transformation technique based on the Yeo-Jhonson transformation. The tanimoto similarity is used in the feature selection process to select the best features from the data. To prepare data for future processing, data augmentation is performed. The Deep Residual Network and the Rider-based Neural Network are recommended and trained separately for the T2DM identification using the Competitive Multi-Verse Rider Optimizer. The outputs generated by the RideNN and DRN classifiers are blended using correlation-based fusion. The suggested CMVRO-based NN-DRN has shown improved performance with the highest accuracy of 91.4%, sensitivity of 94.8%, and specificity of 90.1%.

Skeletal muscle overexpression of sAnk1.5 in transgenic mice does not predispose to type 2 diabetes

Genome-wide association studies (GWAS) and cis-expression quantitative trait locus (cis-eQTL) analyses indicated an association of the rs508419 single nucleotide polymorphism (SNP) with type 2 diabetes (T2D). rs508419 is localized in the muscle-specific internal promoter (P2) of the ANK1 gene, which drives the expression of the sAnk1.5 isoform. Functional studies showed that the rs508419 C/C variant results in increased transcriptional activity of the P2 promoter, leading to higher levels of sAnk1.5 mRNA and protein in skeletal muscle biopsies of individuals carrying the C/C genotype. To investigate whether sAnk1.5 overexpression in skeletal muscle might predispose to T2D development, we generated transgenic mice (TgsAnk1.5/+) in which the sAnk1.5 coding sequence was selectively overexpressed in skeletal muscle tissue. TgsAnk1.5/+ mice expressed up to 50% as much sAnk1.5 protein as wild-type (WT) muscles, mirroring the difference reported between individuals with the C/C or T/T genotype at rs508419. However, fasting glucose levels, glucose tolerance, insulin levels and insulin response in TgsAnk1.5/+ mice did not differ from those of age-matched WT mice monitored over a 12-month period. Even when fed a high-fat diet, TgsAnk1.5/+ mice only presented increased caloric intake, but glucose disposal, insulin tolerance and weight gain were comparable to those of WT mice fed a similar diet. Altogether, these data indicate that sAnk1.5 overexpression in skeletal muscle does not predispose mice to T2D susceptibility.

Bulk and single-cell transcriptome analyses of islet tissue unravel gene signatures associated with pyroptosis and immune infiltration in type 2 diabetes

INTRODUCTION

Type 2 diabetes (T2D) is a common chronic heterogeneous metabolic disorder. However, the roles of pyroptosis and infiltrating immune cells in islet dysfunction of patients with T2D have yet to be explored. In this study, we aimed to explore potential crucial genes and pathways associated with pyroptosis and immune infiltration in T2D.

METHODS

To achieve this, we performed a conjoint analysis of three bulk RNA-seq datasets of islets to identify T2D-related differentially expressed genes (DEGs). After grouping the islet samples according to their ESTIMATE immune scores, we identified immune- and T2D-related DEGs. A clinical prediction model based on pyroptosis-related genes for T2D was constructed. Weighted gene co-expression network analysis was performed to identify genes positively correlated with pyroptosis-related pathways. A protein-protein interaction network was established to identify pyroptosis-related hub genes. We constructed miRNA and transcriptional networks based on the pyroptosis-related hub genes and performed functional analyses. Single-cell RNA-seq (scRNA-seq) was conducted using the GSE153885 dataset. Dimensionality was reduced using principal component analysis and t-distributed statistical neighbor embedding, and cells were clustered using Seurat. Different cell types were subjected to differential gene expression analysis and gene set enrichment analysis (GSEA). Cell-cell communication and pseudotime trajectory analyses were conducted using the samples from patients with T2D.

RESULTS

We identified 17 pyroptosis-related hub genes. We determined the abundance of 13 immune cell types in the merged matrix and found that these cell types were correlated with the 17 pyroptosis-related hub genes. Analysis of the scRNA-seq dataset of 1892 islet samples from patients with T2D and controls revealed 11 clusters. INS and IAPP were determined to be pyroptosis-related and candidate hub genes among the 11 clusters. GSEA of the 11 clusters demonstrated that the myc, G2M checkpoint, and E2F pathways were significantly upregulated in clusters with several differentially enriched pathways.

DISCUSSION

This study elucidates the gene signatures associated with pyroptosis and immune infiltration in T2D and provides a critical resource for understanding of islet dysfunction and T2D pathogenesis.

Single-Cell Chromatin Accessibility Data Combined with GWAS Improves Detection of Relevant Cell Types in 59 Complex Phenotypes

Several disease risk variants reside on non-coding regions of DNA, particularly in open chromatin regions of specific cell types. Identifying the cell types relevant to complex traits through the integration of chromatin accessibility data and genome-wide association studies (GWAS) data can help to elucidate the mechanisms of these traits. In this study, we created a collection of associations between the combinations of chromatin accessibility data (bulk and single-cell) with an array of 201 complex phenotypes. We integrated the GWAS data of these 201 phenotypes with bulk chromatin accessibility data from 137 cell types measured by DNase-I hypersensitive sequencing and found significant results (FDR adjusted p-value ≤ 0.05) for at least one cell type in 21 complex phenotypes, such as atopic dermatitis, Graves’ disease, and body mass index. With the integration of single-cell chromatin accessibility data measured by an assay for transposase-accessible chromatin with high-throughput sequencing (scATAC-seq), taken from 111 adult and 111 fetal cell types, the resolution of association was magnified, enabling the identification of further cell types. This resulted in the identification of significant correlations (FDR adjusted p-value ≤ 0.05) between 15 categories of single-cell subtypes and 59 phenotypes ranging from autoimmune diseases like Graves’ disease to cardiovascular traits like diastolic/systolic blood pressure.

mTORC1 is required for epigenetic silencing during β-cell functional maturation

Objective

The mechanistic target of rapamycin complex 1 (mTORC1) is a key molecule that links nutrients, hormones, and growth factors to cell growth/function. Our previous studies have shown that mTORC1 is required for β-cell functional maturation and identity maintenance; however, the underlying mechanism is not fully understood. This work aimed to understand the underlying epigenetic mechanisms of mTORC1 in regulating β-cell functional maturation.

Methods

We performed Microarray, MeDIP-seq and ATAC-seq analysis to explore the abnormal epigenetic regulation in 8-week-old immature βRapKO islets. Moreover, DNMT3A was overexpressed in βRapKO islets by lentivirus, and the transcriptome changes and GSIS function were analyzed.

Results

We identified two major epigenetic silencing mechanisms, DNMT3A-dependent DNA methylation and PRC2-dependent H3K27me3 modification, which are responsible for functional immaturity of Raptor-deficient β-cell. Overexpression of DNMT3A partially reversed the immature transcriptome pattern and restored the impaired GSIS in Raptor-deficient β-cells. Moreover, we found that Raptor directly regulated PRC2/EED and H3K27me3 expression levels, as well as a group of immature genes marked with H3K27me3. Combined with ATAC-seq, MeDIP-seq and ChIP-seq, we identified β-cell immature genes with either DNA methylation and/or H3K27me3 modification.

Conclusion

The present study advances our understanding of the nutrient sensor mTORC1, by integrating environmental nutrient supply and epigenetic modification, i.e., DNMT3A-mediated DNA methylation and PRC2-mediated histone methylation in regulating β-cell identity and functional maturation, and therefore may impact the disease risk of type 2 diabetes.

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Rescued DNMT3A expression in Raptor-deficient islets partially reversed the abnormal induction of immature genes.

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EED/H3K27me3 were impaired in Raptor-ablated β-cell.

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DNA methylation and H3K27me3 are required for mTORC1-dependent epigenetic silencing of immature genes in β-cell.

Secretory granule exocytosis and its amplification by cAMP in pancreatic β-cells

The sequence of events for secreting insulin in response to glucose in pancreatic β-cells is termed "stimulus-secretion coupling". The core of stimulus-secretion coupling is a process which generates electrical activity in response to glucose uptake and causes Ca²⁺ oscillation for triggering exocytosis of insulin-containing secretory granules. Prior to exocytosis, the secretory granules are mobilized and docked to the plasma membrane and primed for fusion with the plasma membrane. Together with the final fusion with the plasma membrane, these steps are named the exocytosis process of insulin secretion. The steps involved in the exocytosis process are crucial for insulin release from β-cells and considered indispensable for glucose homeostasis. We recently confirmed a signature of defective exocytosis process in human islets and β-cells of obese donors with type 2 diabetes (T2D). Furthermore, cyclic AMP (cAMP) potentiates glucose-stimulated insulin secretion through mechanisms including accelerating the exocytosis process. In this mini-review, we aimed to organize essential knowledge of the secretory granule exocytosis and its amplification by cAMP. Then, we suggest the fatty acid translocase CD36 as a predisposition in β-cells for causing defective exocytosis, which is considered a pathogenesis of T2D in relation to obesity. Finally, we propose potential therapeutics of the defective exocytosis based on a CD36-neutralizing antibody and on Apolipoprotein A-I (ApoA-I), for improving β-cell function in T2D.

Discoveries in Pancreatic Physiology and Disease Biology Using Single-Cell RNA Sequencing

Transcriptome analysis is used to study gene expression in human tissues. It can promote the discovery of new therapeutic targets for related diseases by characterizing the endocrine function of pancreatic physiology and pathology, as well as the gene expression of pancreatic tumors. Compared to whole-tissue RNA sequencing, single-cell RNA sequencing (scRNA-seq) can detect transcriptional activity within a single cell. The scRNA-seq had an invaluable contribution to discovering previously unknown cell subtypes in normal and diseased pancreases, studying the functional role of rare islet cells, and studying various types of cells in diabetes as well as cancer. Here, we review the recent in vitro and in vivo advances in understanding the pancreatic physiology and pathology associated with single-cell sequencing technology, which may provide new insights into treatment strategy optimization for diabetes and pancreatic cancer.

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.

A genome-wide association study identifies novel candidate genes for susceptibility to diabetes mellitus in non-obese cats

Diabetes mellitus (DM) is a common feline endocrinopathy, which is similar to human type 2 diabetes (T2DM) in terms of its pathophysiology. T2DM occurs due to peripheral insulin resistance and/or β-cell dysfunction. Several studies have identified genetic and environmental factors that contribute to susceptibility to human T2DM. In cats, environmental factors such as obesity and physical inactivity have been linked with DM, although to date, the only genetic association that has been demonstrated is with a polymorphism in the feline MC4R gene. The aim of this study was to perform a genome-wide association study (GWAS) to identify polymorphisms associated with feline DM. Illumina Infinium 63k iSelect DNA arrays were used to analyse genomic DNA samples from 200 diabetic domestic shorthair cats and 399 non-diabetic control cats. Data was analysed using PLINK whole genome data analysis toolset. A linear model analysis, EMMAX, was done to test for population structure and HAPLOVIEW was used to identify haplotype blocks surrounding the significant SNPs to assist with candidate gene nomination. A total of 47,497 SNPs were available for analysis. Four SNPs were identified with genome-wide significance: chrA2.4150731 (p_raw = 9.94 x10^-8); chrUn17.115508 (p_raw = 6.51 x10^-8); chrUn17.394136 (p_raw = 2.53 x10^-8); chrUn17.314128 (p_raw = 2.53 x10^-8) as being associated with DM. The first SNP is located within chromosome A2, less than 4kb upstream of the dipeptidyl-peptidase-9 (DPP9) gene, a peptidase involved in incretin inactivation. The remaining three SNPs are located within a haplotype block towards the end of chromosome A3; within this region, genes of interest include TMEM18 and ACP1, both previously associated with T2DM. This study indicates a polygenic component to susceptibility to DM in cats and has highlighted several loci and candidate genes worthy of further investigation.

Functional characterization of T2D-associated SNP effects on baseline and ER stress-responsive β cell transcriptional activation

Genome-wide association studies (GWAS) have linked single nucleotide polymorphisms (SNPs) at >250 loci in the human genome to type 2 diabetes (T2D) risk. For each locus, identifying the functional variant(s) among multiple SNPs in high linkage disequilibrium is critical to understand molecular mechanisms underlying T2D genetic risk. Using massively parallel reporter assays (MPRA), we test the cis-regulatory effects of SNPs associated with T2D and altered in vivo islet chromatin accessibility in MIN6 β cells under steady state and pathophysiologic endoplasmic reticulum (ER) stress conditions. We identify 1,982/6,621 (29.9%) SNP-containing elements that activate transcription in MIN6 and 879 SNP alleles that modulate MPRA activity. Multiple T2D-associated SNPs alter the activity of short interspersed nuclear element (SINE)-containing elements that are strongly induced by ER stress. We identify 220 functional variants at 104 T2D association signals, narrowing 54 signals to a single candidate SNP. Together, this study identifies elements driving β cell steady state and ER stress-responsive transcriptional activation, nominates causal T2D SNPs, and uncovers potential roles for repetitive elements in β cell transcriptional stress response and T2D genetics.

Advancing Diabetic Retinopathy Research: Analysis of the Neurovascular Unit in Zebrafish

Diabetic retinopathy is one of the most important microvascular complications associated with diabetes mellitus, and a leading cause of vision loss or blindness worldwide. Hyperglycaemic conditions disrupt microvascular integrity at the level of the neurovascular unit. In recent years, zebrafish (Danio rerio) have come into focus as a model organism for various metabolic diseases such as diabetes. In both mammals and vertebrates, the anatomy and the function of the retina and the neurovascular unit have been highly conserved. In this review, we focus on the advances that have been made through studying pathologies associated with retinopathy in zebrafish models of diabetes. We discuss the different cell types that form the neurovascular unit, their role in diabetic retinopathy and how to study them in zebrafish. We then present new insights gained through zebrafish studies. The advantages of using zebrafish for diabetic retinopathy are summarised, including the fact that the zebrafish has, so far, provided the only animal model in which hyperglycaemia-induced retinal angiogenesis can be observed. Based on currently available data, we propose potential investigations that could advance the field further.

Identification of two novel subgroups in patients with diabetes mellitus and their association with clinical outcomes: A two-step cluster analysis

Aims/Introduction

The aim of this study was to determine whether distinct subphenotypes of patients with type 2 diabetes in the European classification exist in Chinese populations, and to further establish novel subphenotypes more suitable for Chinese populations.

Material and Methods

The research retrospectively analyzed 5414 patients with type 2 diabetes from the National Clinical Research Center for Metabolic Diseases Diabetes Center in China, and a two‐step cluster analysis was carried out. First, we confirmed the European classification in Chinese populations by six parameters, including age at disease onset, body mass index, glycosylated hemoglobin, homeostatic model assessment 2 to estimate β‐cell function and insulin resistance, and glutamate decarboxylase antibodies. Furthermore, triglycerides and uric acid were added to refine the cluster analysis, and Cox regression was used to evaluate the risk of diabetic complications.

Results

Just three clusters were replicated in our cohort according to Emma Ahlqvist's European classification. When other variables were added to the cluster analysis, seven subgroups were identified, including five clusters of the European classification and two novel subgroups, namely, uric acid‐related diabetes and inheritance‐related diabetes. Compared with patients with inheritance‐related diabetes, patients with severe insulin‐resistant diabetes showed a higher risk of diabetic peripheral neuropathy, hypertension and chronic kidney disease, and the uric acid‐related diabetes subgroup showed a higher risk of coronary heart disease, cerebral vascular disease and end‐stage renal disease. Patients with severe insulin‐deficient diabetes showed a higher risk of diabetic retinopathy and diabetic foot than those with inheritance‐related diabetes. Furthermore, there were sex‐specific associations between subgroups and clinical outcomes. No significant difference was observed in the prevalence of cancer in each subgroup.

Conclusions

Seven subgroups of type 2 diabetes were identified in Chinese populations, with distinct characteristics and disparate clinical outcomes. This etiology‐based stratification might contribute to the diagnosis and management of type 2 diabetes.

Effects of family history of diabetes on pancreatic β-cell function and diabetic ketoacidosis in newly diagnosed patients with type 2 diabetes: a cross-sectional study in China

OBJECTIVE

To investigate the association between a parental and/or sibling history of diabetes and clinical characteristics.

DESIGN

A cross-sectional study.

SETTING

The data were collected from the endocrinology department of The Second Xiangya Hospital of Central South University from June 2017 to October 2019.

PARTICIPANTS

A total of 894 newly diagnosed patients with type 2 diabetes were recruited. Data on clinical characteristics were collected from patient medical records. Pancreatic β-cell function and insulin resistance were calculated with the homeostatic model assessment. SPSS V.25.0 was used to perform the analysis.

RESULTS

The percentages of patients with parental and sibling histories of diabetes were 14.8% and 9.8%, respectively. The prevalence of diabetic ketoacidosis (DKA) was 3.9%. Compared with those with no parental history of diabetes, patients with a parental history of diabetes were characterised by early-onset disease (41.70±10.88 vs 51.17±14.09 years), poor glycaemic control of fasting blood glucose (10.84±5.21 vs 8.91±4.38 mmol/L) and a high prevalence of DKA (7.6% vs 3.3%). The patients with a sibling history of diabetes had later disease onset (56.05±9.86 vs 49.09±14.29 years) and lower BMI (24.49±3.48 vs 25.69±3.86 kg/m²) than those with no sibling history of diabetes. Univariate regression suggested that both parental history (p=0.037) and sibling history (p=0.011) of diabetes were associated with β-cell function; however, multiple regression analysis showed that only a sibling history of diabetes was associated with β-cell function (p=0.038). Univariate regression revealed a positive correlation between parental history of diabetes (p=0.023, OR=2.416, 95% CI 1.132 to 5.156) and DKA. Unfortunately, this correlation was not statistically significant for either patients with a parental history (p=0.234, OR=1.646, 95% CI 0.724 to 3.743) or those with a sibling history (p=0.104, OR=2.319, 95% CI 0.841 to 6.389) after adjustments for confounders.

CONCLUSION

A sibling history of diabetes was associated with poor β-cell function, and a parental history of diabetes was associated with poor glycaemic control and a high prevalence of DKA.

Single-Cell Transcriptional Profiling of Mouse Islets Following Short-Term Obesogenic Dietary Intervention

Obesity is closely associated with adipose tissue inflammation and insulin resistance. Dysglycemia and type 2 diabetes results when islet β cells fail to maintain appropriate insulin secretion in the face of insulin resistance. To clarify the early transcriptional events leading to β-cell failure in the setting of obesity, we fed male C57BL/6J mice an obesogenic, high-fat diet (60% kcal from fat) or a control diet (10% kcal from fat) for one week, and islets from these mice (from four high-fat- and three control-fed mice) were subjected to single-cell RNA sequencing (sc-RNAseq) analysis. Islet endocrine cell types (α cells, β cells, δ cells, PP cells) and other resident cell types (macrophages, T cells) were annotated by transcript profiles and visualized using Uniform Manifold Approximation and Projection for Dimension Reduction (UMAP) plots. UMAP analysis revealed distinct cell clusters (11 for β cells, 5 for α cells, 3 for δ cells, PP cells, ductal cells, endothelial cells), emphasizing the heterogeneity of cell populations in the islet. Collectively, the clusters containing the majority of β cells showed the fewest gene expression changes, whereas clusters harboring the minority of β cells showed the most changes. We identified that distinct β-cell clusters downregulate genes associated with the endoplasmic reticulum stress response and upregulate genes associated with insulin secretion, whereas others upregulate genes that impair insulin secretion, cell proliferation, and cell survival. Moreover, all β-cell clusters negatively regulate genes associated with immune response activation. Glucagon-producing α cells exhibited patterns similar to β cells but, again, in clusters containing the minority of α cells. Our data indicate that an early transcriptional response in islets to an obesogenic diet reflects an attempt by distinct populations of β cells to augment or impair cellular function and/or reduce inflammatory responses as possible harbingers of ensuing insulin resistance.

Association of ABCG1 gene methylation and its dynamic change status with incident type 2 diabetes mellitus: the Rural Chinese Cohort Study

To explore whether DNA methylation of the ATP-binding cassette G1 (ABCG1) gene and its dynamic change are associated with incident type 2 diabetes mellitus (T2DM). We conducted a nested case-control study with 286 pairs of T2DM cases and matched controls nested in the Rural Chinese Cohort Study. Conditional logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for incident T2DM risk according to ABCG1 methylation level at baseline and its dynamic change at follow-up examination. Spearman's rank correlation coefficients were used to analyze the association between ABCG1 methylation and its possible risk factors in the control group. We found that T2DM risk increased by 16% (OR = 1.16, 95% CI = 1.02-1.31) with each 1% increase in DNA methylation levels of the ABCG1 loci CpG13 and CpG14. DNA methylation change of the ABCG1 locus CpG15 during the 6-year follow-up was associated with increased T2DM risk: T2DM risk increased by 78% in the upper tertile group (methylation gain ≥5%) versus lower tertile group (methylation gain <1%) (OR = 1.78, 95% CI = 1.01-3.15). Furthermore, body mass index was positively correlated with the DNA methylation level of the ABCG1 loci CpG13, CpG14 and CpG15. In conclusion, DNA methylation levels of the ABCG1 loci CpG13 and CpG14 and the methylation gain of locus CpG15 were positively associated with incident T2DM risk, which may suggest a possible etiologic pattern for T2DM and potentially improve T2DM prediction in rural Chinese people.

Genetic variants in glutamate cysteine ligase confer protection against type 2 diabetes

Oxidative stress contributes to the pathogenesis of type 2 diabetes (T2D). This study investigated whether single nucleotide polymorphisms (SNPs) at genes encoding glutamate cysteine ligase catalytic (rs12524494, rs17883901, rs606548, rs636933, rs648595, rs761142 at GCLC) and modifier (rs2301022, rs3827715, rs7517826, rs41303970 at GCLM) subunits are associated with susceptibility to type 2 diabetes. 2096 unrelated Russian subjects were enrolled for the study. Genotyping was done with the use of the MassArray System. Plasma levels of reactive oxygen species (ROS) and glutathione in the study subjects were analyzed by fluorometric and colorimetric assays, respectively.The present study found, for the first time, an association of SNP rs41303970 in the GCLM gene with a decreased risk of T2D (P = 0.034, Q = 0.17). Minor alleles such as rs12524494-G GCLC gene (P = 0.026, Q = 0.17) and rs3827715-C GCLM gene (P = 0.03, Q = 0.17) were also associated with reduced risk for T2D. Protective effects of variant alleles such as rs12524494-G at GCLC (P = 0.02, Q = 0.26) and rs41303970-A GCLM (P = 0.013, Q = 0.25) against the risk of T2D were seen solely in nonsmokers. As compared with healthy controls, diabetic patients had markedly increased levels of ROS and decreased levels of total GSH in plasma. Interestingly, fasting blood glucose level positively correlated with oxidized glutathione concentration (r_s = 0.208, P = 0.01). Three SNPs rs17883901, rs636933, rs648595 at GCLC and one rs2301022 at GCLM were associated with decreased levels of ROS, while SNPs rs7517826, rs41303970 at GCLM were associated with increased levels of total GSH in plasma. Single nucleotide polymorphisms in genes encoding glutamate cysteine ligase subunits confer protection against type 2 diabetes and their effects are mediated through increased levels of glutathione.

Review of methods for detecting glycemic disorders

Prediabetes (intermediate hyperglycemia) consists of two abnormalities, impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) detected by a standardized 75-gram oral glucose tolerance test (OGTT). Individuals with isolated IGT or combined IFG and IGT have increased risk for developing type 2 diabetes (T2D) and cardiovascular disease (CVD). Diagnosing prediabetes early and accurately is critical in order to refer high-risk individuals for intensive lifestyle modification. However, there is currently no international consensus for diagnosing prediabetes with HbA1c or glucose measurements based upon American Diabetes Association (ADA) and the World Health Organization (WHO) criteria that identify different populations at risk for progressing to diabetes. Various caveats affecting the accuracy of interpreting the HbA1c including genetics complicate this further. This review describes established methods for detecting glucose disorders based upon glucose and HbA1c parameters as well as novel approaches including the 1-hour plasma glucose (1-h PG), glucose challenge test (GCT), shape of the glucose curve, genetics, continuous glucose monitoring (CGM), measures of insulin secretion and sensitivity, metabolomics, and ancillary tools such as fructosamine, glycated albumin (GA), 1,5- anhydroglucitol (1,5-AG). Of the approaches considered, the 1-h PG has considerable potential as a biomarker for detecting glucose disorders if confirmed by additional data including health economic analysis. Whether the 1-h OGTT is superior to genetics and omics in providing greater precision for individualized treatment requires further investigation. These methods will need to demonstrate substantially superiority to simpler tools for detecting glucose disorders to justify their cost and complexity.

Identification of potential markers for type 2 diabetes mellitus via bioinformatics analysis

Type 2 diabetes mellitus (T2DM) is a multifactorial and multigenetic disease, and its pathogenesis is complex and largely unknown. In the present study, microarray data (GSE201966) of β-cell enriched tissue obtained by laser capture microdissection were downloaded, including 10 control and 10 type 2 diabetic subjects. A comprehensive bioinformatics analysis of microarray data in the context of protein-protein interaction (PPI) networks was employed, combined with subcellular location information to mine the potential candidate genes for T2DM and provide further insight on the possible mechanisms involved. First, differential analysis screened 108 differentially expressed genes. Then, 83 candidate genes were identified in the layered network in the context of PPI via network analysis, which were either directly or indirectly linked to T2DM. Of those genes obtained through literature retrieval analysis, 27 of 83 were involved with the development of T2DM; however, the rest of the 56 genes need to be verified by experiments. The functional analysis of candidate genes involved in a number of biological activities, demonstrated that 46 upregulated candidate genes were involved in ‘inflammatory response’ and ‘lipid metabolic process’, and 37 downregulated candidate genes were involved in ‘positive regulation of cell death’ and ‘positive regulation of cell proliferation’. These candidate genes were also involved in different signaling pathways associated with ‘PI3K/Akt signaling pathway’, ‘Rap1 signaling pathway’, ‘Ras signaling pathway’ and ‘MAPK signaling pathway’, which are highly associated with the development of T2DM. Furthermore, a microRNA (miR)-target gene regulatory network and a transcription factor-target gene regulatory network were constructed based on miRNet and NetworkAnalyst databases, respectively. Notably, hsa-miR-192-5p, hsa-miR-124-5p and hsa-miR-335-5p appeared to be involved in T2DM by potentially regulating the expression of various candidate genes, including procollagen C-endopeptidase enhancer 2, connective tissue growth factor and family with sequence similarity 105, member A, protein phosphatase 1 regulatory inhibitor subunit 1 A and C-C motif chemokine receptor 4. Smad5 and Bcl6, as transcription factors, are regulated by ankyrin repeat domain 23 and transmembrane protein 37, respectively, which might also be used in the molecular diagnosis and targeted therapy of T2DM. Taken together, the results of the present study may offer insight for future genomic-based individualized treatment of T2DM and help determine the underlying molecular mechanisms that lead to T2DM.

Advances of single-cell genomics and epigenomics in human disease: where are we now?

Cellular heterogeneity is revolutionizing the way to study, monitor and dissect complex diseases. This has been possible with the technological and computational advances associated to single-cell genomics and epigenomics. Deeper understanding of cell-to-cell variation and its impact on tissue function will open new avenues for early disease detection, accurate diagnosis and personalized treatments, all together leading to the next generation of health care. This review focuses on the recent discoveries that single-cell genomics and epigenomics have facilitated in the context of human health. It highlights the potential of single-cell omics to further advance the development of personalized treatments and precision medicine in cancer, diabetes and chronic age-related diseases. The promise of single-cell technologies to generate new insights about the differences in function between individual cells is just emerging, and it is paving the way for identifying biomarkers and novel therapeutic targets to tackle age, complex diseases and understand the effect of life style interventions and environmental factors.

Multiomic Profiling Identifies cis-Regulatory Networks Underlying Human Pancreatic β Cell Identity and Function

EndoC-βH1 is emerging as a critical human β cell model to study the genetic and environmental etiologies of β cell (dys)function and diabetes. Comprehensive knowledge of its molecular landscape is lacking, yet required, for effective use of this model. Here, we report chromosomal (spectral karyotyping), genetic (genotyping), epigenomic (ChIP-seq and ATAC-seq), chromatin interaction (Hi-C and Pol2 ChIA-PET), and transcriptomic (RNA-seq and miRNA-seq) maps of EndoC-βH1. Analyses of these maps define known (e.g., PDX1 and ISL1) and putative (e.g., PCSK1 and mir-375) β cell-specific transcriptional cis-regulatory networks and identify allelic effects on cis-regulatory element use. Importantly, comparison with maps generated in primary human islets and/or β cells indicates preservation of chromatin looping but also highlights chromosomal aberrations and fetal genomic signatures in EndoC-βH1. Together, these maps, and a web application we created for their exploration, provide important tools for the design of experiments to probe and manipulate the genetic programs governing β cell identity and (dys)function in diabetes.

EndoC-βH1 is becoming an important cellular model to study genes and pathways governing human β cell identity and function, but its (epi)genomic similarity to primary human islets is unknown. Lawlor et al. complete and compare extensive EndoC and primary human islet multiomic maps to identify shared and distinct genomic circuitry.

Vitamin D metabolites influence expression of genes concerning cellular viability and function in insulin producing β-cells (INS1E)

BACKGROUND

Studies have shown that vitamin D can enhance glucose-stimulated insulin secretion (GSIS) and change the expression of genes in pancreatic β-cells. Still the mechanisms linking vitamin D and GSIS are unknown.

MATERIAL AND METHODS

We used an established β-cell line, INS1E. INS1E cells were pre-treated with 10 nM 1,25(OH)₂vitamin D or 10 nM 25(OH)vitamin D for 72 h and stimulated with 22 mM glucose for 60 min. RNA was extracted for gene expression analysis.

RESULTS

Expression of genes affecting viability, apoptosis and GSIS changed after pre-treatment with both 1,25(OH)₂vitamin D and 25(OH)vitamin D in INS1E cells. Stimulation with glucose after pre-treatment of INS1E cells with 1,25(OH)₂vitamin D resulted in 181 differentially expressed genes, whereas 526 genes were differentially expressed after pre-treatment with 25(OH)vitamin D.

CONCLUSION

Vitamin D metabolites may affect pancreatic β-cells and GSIS through changed gene expression for genes involved in β-cell function and viability.

Epigenetic Modifications Associated with the Pathogenesis of Type 2 Diabetes Mellitus

BACKGROUND AND OBJECTIVE

Type 2 diabetes mellitus (T2DM) is a multifactorial metabolic disorder. Pancreatic β-cell dysfunction and insulin resistance are the most common and crucial events of T2DM. Increasing evidence suggests the association of epigenetic modifications with the pathogenesis of T2DM through the changes in important biological processes including pancreatic β- cell differentiation, development and maintenance of normal β-cell function. Insulin sensitivity by the peripheral glucose uptake tissues is also changed by the altered epigenetic mechanisms. In this review, we discussed the major epigenetic alterations and their effects on β-cell function, insulin secretion and insulin resistance in context of T2DM.

METHODS

We investigated the presently available epigenetic modifications including DNA methylation, posttranslational histone modifications, ATP-dependent chromatin remodeling and non-coding RNAs related to the pathogenesis of T2DM. Published literatures on this topic were searched both on Google Scholar and Pubmed with related keywords and investigated for relevant information.

RESULTS

The epigenetic modifications introduce changes in gene expression which are essential for appropriate β-cell development and functions, insulin secretion and sensitivity resulting in the pathogenesis of T2DM. Interestingly, T2DM could also be a prominent reason for the mentioned epigenetic alterations.

CONCLUSION

This review article emphasized on the epigenetic modifications associated with T2DM and discussed the consequences in deterioration of the disease condition.

Blocking Ca2+ Channel β3 Subunit Reverses Diabetes

Voltage-gated Ca²⁺ channels (Ca_v) are essential for pancreatic beta cell function as they mediate Ca²⁺ influx, which leads to insulin exocytosis. The β3 subunit of Ca_v (Ca_vβ₃) has been suggested to regulate cytosolic Ca²⁺ ([Ca²⁺]_i) oscillation frequency and insulin secretion under physiological conditions, but its role in diabetes is unclear. Here, we report that islets from diabetic mice show Ca_vβ₃ overexpression, altered [Ca²⁺]_i dynamics, and impaired insulin secretion upon glucose stimulation. Consequently, in high-fat diet (HFD)-induced diabetes, Ca_vβ₃-deficient (Ca_vβ₃^−/−) mice showed improved islet function and enhanced glucose tolerance. Normalization of Ca_vβ₃ expression in ob/ob islets by an antisense oligonucleotide rescued the altered [Ca²⁺]_i dynamics and impaired insulin secretion. Importantly, transplantation of Ca_vβ₃^−/− islets into the anterior chamber of the eye improved glucose tolerance in HFD-fed mice. Ca_vβ₃ overexpression in human islets also impaired insulin secretion. We thus suggest that Ca_vβ₃ may serve as a druggable target for diabetes treatment.

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Pancreatic islets from diabetic mice have increased level of Ca_vβ₃

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Overexpression of Ca_vβ₃ in islets alters Ca²⁺ dynamics and impairs insulin secretion

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Deficiency of Ca_vβ₃ prevents islet dysfunction and glucose intolerance in diabetes

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Blocking Ca_vβ₃ improves islet function and glucose tolerance after onset of diabetes

The association of TNF-α -308G/A and -238G/A polymorphisms with type 2 diabetes mellitus: a meta-analysis

Tumor necrosis factor-α (TNF-α) is involved in insulin resistance and has long been a candidate gene implicated in type 2 diabetes mellitus (T2DM), however the association between TNF-α polymorphisms -308G/A and -238G/A and T2DM remains controversial. The present study sought to verify associations between these polymorphisms and T2DM susceptibility using a meta-analysis approach. A total of 49 case-control studies were selected up to October 2018. Statistical analyses were performed by STATA 15.0 software. The odds ratios (ORs) and 95% confidence intervals were calculated to estimate associations. Meta-analyses revealed significant associations between TNF-α -308G/A and T2DM in the allele model (P=0.000); the dominant model (P=0.000); the recessive model (P=0.001); the overdominant model (P=0.008) and the codominant model (P=0.000). Subgroup analyses also showed associations in the allele model (P=0.006); the dominant model (P=0.004) and the overdominant model (P=0.005) in the Caucasian and in the allele model (P=0.007); the dominant model (P=0.014); the recessive model (P=0.000) and the codominant model (P=0.000) in the Asian. There were no associations between TNF-α -238G/A and T2DM in the overall and subgroup populations. Meta-regression, sensitivity analysis and publication bias analysis confirmed that results and data were statistically robust. Our meta-analysis suggests that TNF-α -308G/A is a risk factor for T2DM in Caucasian and Asian populations. It also indicates that TNF-α -238G/A may not be a risk factor for T2DM. More comprehensive studies will be required to confirm these associations.

Bioinformatics analysis of hepatic gene expression profiles in type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is characterized by hyperglycemia. The liver has a critical role in regulating glucose homeostasis. The present study aimed to analyze hepatic gene expression profiles and to identify the key genes and pathways involved in T2DM. Gene expression profiles of 10 patients with T2DM and 7 subjects with normal glucose tolerance were downloaded from the Gene Expression Omnibus database. Subsequently, differentially expressed genes (DEGs) were identified and functional enrichment analysis was performed. In addition, a protein-protein interaction network was built and hub genes were identified. In total, 1,320 DEGs were identified, including 698 up- and 622 downregulated genes, and these were mainly enriched in positive regulation of transcription from RNA polymerase II promoter, cell adhesion, inflammatory response, positive regulation of apoptotic process, signal transduction and the Tolllike receptor signaling pathway. A total of 8 hub genes (G-protein subunit gamma transducin 2, ubiquitinconjugating enzyme E2 D1, glutamate metabotropic receptor 1, G-protein signaling modulator 1, C-X-C motif chemokine ligand 9, neurotensin, purinergic receptor P2Y1 and ring finger protein 41) were screened from the network. The present study may contribute to the elucidation of the hepatic pathology of T2DM.

Navigating the Depths and Avoiding the Shallows of Pancreatic Islet Cell Transcriptomes

Islet gene expression has been widely studied to better understand the transcriptional features that define a healthy β-cell. Transcriptomes of FACS-purified α-, β-, and δ-cells using bulk RNA-sequencing have facilitated our understanding of the complex network of cross talk between islet cells and its effects on β-cell function. However, these approaches were by design not intended to resolve heterogeneity between individual cells. Several recent studies used single-cell RNA sequencing (scRNA-Seq) to report considerable heterogeneity within mouse and human β-cells. In this Perspective, we assess how this newfound ability to assess gene expression at single-cell resolution has enhanced our understanding of β-cell heterogeneity. We conduct a comprehensive assessment of several single human β-cell transcriptome data sets and ask if the heterogeneity reported by these studies showed overlap and concurred with previously known examples of β-cell heterogeneity. We also illustrate the impact of the inevitable limitations of working at or below the limit of detection of gene expression at single cell resolution and their consequences for the quality of single-islet cell transcriptome data. Finally, we offer some guidance on when to opt for scRNA-Seq and when bulk sequencing approaches may be better suited.

Dissecting the Brain/Islet Axis in Metabesity

The high prevalence of type 2 diabetes mellitus (T2DM), together with the fact that current treatments are only palliative and do not avoid major secondary complications, reveals the need for novel approaches to treat the cause of this disease. Efforts are currently underway to identify therapeutic targets implicated in either the regeneration or re-differentiation of a functional pancreatic islet β-cell mass to restore insulin levels and normoglycemia. However, T2DM is not only caused by failures in β-cells but also by dysfunctions in the central nervous system (CNS), especially in the hypothalamus and brainstem. Herein, we review the physiological contribution of hypothalamic neuronal and glial populations, particularly astrocytes, in the control of the systemic response that regulates blood glucose levels. The glucosensing capacity of hypothalamic astrocytes, together with their regulation by metabolic hormones, highlights the relevance of these cells in the control of glucose homeostasis. Moreover, the critical role of astrocytes in the response to inflammation, a process associated with obesity and T2DM, further emphasizes the importance of these cells as novel targets to stimulate the CNS in response to metabesity (over-nutrition-derived metabolic dysfunctions). We suggest that novel T2DM therapies should aim at stimulating the CNS astrocytic response, as well as recovering the functional pancreatic β-cell mass. Whether or not a common factor expressed in both cell types can be feasibly targeted is also discussed.

Vitamin D Increases Glucose Stimulated Insulin Secretion from Insulin Producing Beta Cells (INS1E)

BACKGROUND

Vitamin D affects the pancreatic beta cell function and in vitro studies have shown that vitamin D may influence insulin secretion, apoptosis, and gene regulation. However, the outcomes have differed and there has been uncertainty regarding the effect of different vitamin D metabolites on insulin secretion.

OBJECTIVES

We hypothesized that vitamin D could increase insulin secretion in insulin producing beta cells and investigated the effect of 25(OH) vitamin D and 1,25(OH)₂ vitamin D on insulin secretion.

METHODS

The study was conducted in INS1E cells, an established insulinoma cell line from rat. The cells were divided into three groups; a control group, a group with 1,25(OH)₂ vitamin D enriched medium (10 nM), and a group with 25(OH) vitamin D (10 nM) supplemented medium. After 72 hours of treatment, the cells underwent glucose stimulation at different concentrations (0, 5, 11, and 22 mM) for 60 minutes.

RESULTS

INS1E cells treated with 1,25(OH)₂ vitamin D showed a trend towards increased insulin secretion at all glucose concentrations compared to control cells and at 22 mM glucose, the difference was significant (18.40 +/- 1.97 vs 12.90 +/- 2.22 nmol/L, P < 0.05). However, pretreatment with 25(OH) vitamin D did not show any significant increase in insulin secretion compared to cells without vitamin D treatment. There was no difference in insulin secretion in cells not stimulated with glucose.

CONCLUSIONS

Treatment with 1,25(OH)₂ vitamin D combined with high levels of glucose increased insulin secretion in INS1E cells, whereas 25(OH) vitamin D had no effect. This suggests that glucose stimulated insulin secretion in INS1E beta cells appears to be related to the type of vitamin D metabolite treatment.

Single-cell gene expression analysis reveals β-cell dysfunction and deficit mechanisms in type 2 diabetes

BACKGROUND

Type 2 diabetes (T2D) is one of the most common chronic diseases. Studies on T2D are mainly built upon bulk-cell data analysis, which measures the average gene expression levels for a population of cells and cannot capture the inter-cell heterogeneity. The single-cell RNA-sequencing technology can provide additional information about the molecular mechanisms of T2D at single-cell level.

RESULTS

In this work, we analyze three datasets of single-cell transcriptomes to reveal β-cell dysfunction and deficit mechanisms in T2D. Focused on the expression levels of key genes, we conduct discrimination of healthy and T2D β-cells using five machine learning classifiers, and extracted major influential factors by calculating correlation coefficients and mutual information. Our analysis shows that T2D β-cells are normal in insulin gene expression in the scenario of low cellular stress (especially oxidative stress), but appear dysfunctional under the circumstances of high cellular stress. Remarkably, oxidative stress plays an important role in affecting the expression of insulin gene. In addition, by analyzing the genes related to apoptosis, we found that the TNFR1-, BAX-, CAPN1- and CAPN2-dependent pathways may be crucial for β-cell apoptosis in T2D. Finally, personalized analysis indicates cell heterogeneity and individual-specific insulin gene expression.

CONCLUSIONS

Oxidative stress is an important influential factor on insulin gene expression in T2D. Based on the uncovered mechanism of β-cell dysfunction and deficit, targeting key genes in the apoptosis pathway along with alleviating oxidative stress could be a potential treatment strategy for T2D.

Epigenetics of chronic inflammatory diseases

Chronic, noncommunicable, and inflammation-associated diseases remain the largest cause of morbidity and mortality globally and within the United States. This is mainly due to our limited understanding of the molecular mechanisms that underlie these complex pathologies. The available evidence indicates that studies of epigenetics (traditionally defined as the heritable changes to gene expression that are independent of changes to DNA) are significantly advancing our knowledge of these inflammatory conditions. This review will focus on epigenetic studies of three diseases, that are among the most burdensome globally: cardiovascular disease, the number one cause of deaths worldwide, type 2 diabetes and, Alzheimer’s disease. The current status of epigenetic research, including the ability to predict disease risk, and key pathophysiological defects are discussed. The significance of defining the contribution of epigenetic defects to nonresolving inflammation and aging, each associated with these diseases, is highlighted, as these are likely to provide new insights into inflammatory disease pathogenesis.

Detection of correlated hidden factors from single cell transcriptomes using Iteratively Adjusted-SVA (IA-SVA)

Single cell RNA-sequencing (scRNA-seq) precisely characterizes gene expression levels and dissects variation in expression associated with the state (technical or biological) and the type of the cell, which is averaged out in bulk measurements. Multiple and correlated sources contribute to gene expression variation in single cells, which makes their estimation difficult with the existing methods developed for batch correction (e.g., surrogate variable analysis (SVA)) that estimate orthogonal transformations of these sources. We developed iteratively adjusted surrogate variable analysis (IA-SVA) that can estimate hidden factors even when they are correlated with other sources of variation by identifying a set of genes associated with each hidden factor in an iterative manner. Analysis of scRNA-seq data from human cells showed that IA-SVA could accurately capture hidden variation arising from technical (e.g., stacked doublet cells) or biological sources (e.g., cell type or cell-cycle stage). Furthermore, IA-SVA delivers a set of genes associated with the detected hidden source to be used in downstream data analyses. As a proof of concept, IA-SVA recapitulated known marker genes for islet cell subsets (e.g., alpha, beta), which improved the grouping of subsets into distinct clusters. Taken together, IA-SVA is an effective and novel method to dissect multiple and correlated sources of variation in scRNA-seq data.

Type 2 Diabetes-Associated Genetic Variants Regulate Chromatin Accessibility in Human Islets

Type 2 diabetes (T2D) is a complex disorder in which both genetic and environmental risk factors contribute to islet dysfunction and failure. Genome-wide association studies (GWAS) have linked single nucleotide polymorphisms (SNPs), most of which are noncoding, in >200 loci to islet dysfunction and T2D. Identification of the putative causal variants and their target genes and whether they lead to gain or loss of function remains challenging. Here, we profiled chromatin accessibility in pancreatic islet samples from 19 genotyped individuals and identified 2,949 SNPs associated with in vivo cis-regulatory element use (i.e., chromatin accessibility quantitative trait loci [caQTL]). Among the caQTLs tested (n = 13) using luciferase reporter assays in MIN6 β-cells, more than half exhibited effects on enhancer activity that were consistent with in vivo chromatin accessibility changes. Importantly, islet caQTL analysis nominated putative causal SNPs in 13 T2D-associated GWAS loci, linking 7 and 6 T2D risk alleles, respectively, to gain or loss of in vivo chromatin accessibility. By investigating the effect of genetic variants on chromatin accessibility in islets, this study is an important step forward in translating T2D-associated GWAS SNP into functional molecular consequences.

A neural network based model effectively predicts enhancers from clinical ATAC-seq samples

Enhancers are cis-acting sequences that regulate transcription rates of their target genes in a cell-specific manner and harbor disease-associated sequence variants in cognate cell types. Many complex diseases are associated with enhancer malfunction, necessitating the discovery and study of enhancers from clinical samples. Assay for Transposase Accessible Chromatin (ATAC-seq) technology can interrogate chromatin accessibility from small cell numbers and facilitate studying enhancers in pathologies. However, on average, ~35% of open chromatin regions (OCRs) from ATAC-seq samples map to enhancers. We developed a neural network-based model, Predicting Enhancers from ATAC-Seq data (PEAS), to effectively infer enhancers from clinical ATAC-seq samples by extracting ATAC-seq data features and integrating these with sequence-related features (e.g., GC ratio). PEAS recapitulated ChromHMM-defined enhancers in CD14+ monocytes, CD4+ T cells, GM12878, peripheral blood mononuclear cells, and pancreatic islets. PEAS models trained on these 5 cell types effectively predicted enhancers in four cell types that are not used in model training (EndoC-βH1, naïve CD8+ T, MCF7, and K562 cells). Finally, PEAS inferred individual-specific enhancers from 19 islet ATAC-seq samples and revealed variability in enhancer activity across individuals, including those driven by genetic differences. PEAS is an easy-to-use tool developed to study enhancers in pathologies by taking advantage of the increasing number of clinical epigenomes.

Novel approaches to restore beta cell function in prediabetes and type 2 diabetes

The World Health Organization estimates that diabetes prevalence has risen from 108 million in 1980 to 422 million in 2014, with type 2 diabetes accounting for more than 90% of these cases. Furthermore, the prevalence of prediabetes (impaired fasting glucose and/or impaired glucose tolerance) is more than 40% in some countries and is associated with a global rise in obesity. Therefore it is imperative that we develop new approaches to reduce the development of prediabetes and progression to type 2 diabetes. In this review, we explore the gains made over the past decade by focused efforts to improve insulin secretion by the beta cell or insulin sensitivity of target tissues. We also describe multitasking candidates, which could improve both beta cell dysfunction and peripheral insulin sensitivity. Moreover, we highlight provocative findings indicating that additional glucose regulatory tissues, such as the brain, may be key therapeutic targets. Taken together, the promise of these new multi-faceted approaches reinforces the importance of understanding and tackling type 2 diabetes pathogenesis from a multi-tissue perspective.

Zebrafish as a Model for Obesity and Diabetes

Obesity and diabetes now considered global epidemics. The prevalence rates of diabetes are increasing in parallel with the rates of obesity and the strong connection between these two diseases has been coined as “diabesity.” The health risks of overweight or obesity include Type 2 diabetes mellitus (T2DM), coronary heart disease and cancer of numerous organs. Both obesity and diabetes are complex diseases that involve the interaction of genetics and environmental factors. The underlying pathogenesis of obesity and diabetes are not well understood and further research is needed for pharmacological and surgical management. Consequently, the use of animal models of obesity and/or diabetes is important for both improving the understanding of these diseases and to identify and develop effective treatments. Zebrafish is an attractive model system for studying metabolic diseases because of the functional conservation in lipid metabolism, adipose biology, pancreas structure, and glucose homeostasis. It is also suited for identification of novel targets associated with the risk and treatment of obesity and diabetes in humans. In this review, we highlight studies using zebrafish to model metabolic diseases, and discuss the advantages and disadvantages of studying pathologies associated with obesity and diabetes in zebrafish.

High-Throughput Approaches onto Uncover (Epi)Genomic Architecture of Type 2 Diabetes

Type 2 diabetes (T2D) is a complex disorder that is caused by a combination of genetic, epigenetic, and environmental factors. High-throughput approaches have opened a new avenue toward a better understanding of the molecular bases of T2D. A genome-wide association studies (GWASs) identified a group of the most common susceptibility genes for T2D (i.e., TCF7L2, PPARG, KCNJ1, HNF1A, PTPN1, and CDKAL1) and illuminated novel disease-causing pathways. Next-generation sequencing (NGS)-based techniques have shed light on rare-coding genetic variants that account for an appreciable fraction of T2D heritability (KCNQ1 and ADRA2A) and population risk of T2D (SLC16A11, TPCN2, PAM, and CCND2). Moreover, single-cell sequencing of human pancreatic islets identified gene signatures that are exclusive to α-cells (GCG, IRX2, and IGFBP2) and β-cells (INS, ADCYAP1, INS-IGF2, and MAFA). Ongoing epigenome-wide association studies (EWASs) have progressively defined links between epigenetic markers and the transcriptional activity of T2D target genes. Differentially methylated regions were found in TCF7L2, THADA, KCNQ1, TXNIP, SOCS3, SREBF1, and KLF14 loci that are related to T2D. Additionally, chromatin state maps in pancreatic islets were provided and several non-coding RNAs (ncRNA) that are key to T2D pathogenesis were identified (i.e., miR-375). The present review summarizes major progress that has been made in mapping the (epi)genomic landscape of T2D within the last few years.

Prenatal exposure to diesel exhaust PM2.5 causes offspring β cell dysfunction in adulthood

Environmental stressors that encounter in early-life and cause abnormal fetal and/or neonatal development may increase susceptibility to non-communicable diseases such as diabetes. Maternal exposure to ambient fine particulate matter (PM_2.5) is associated with various fetal abnormalities, suggesting that it may program offspring's susceptibility to diabetes. In the present study, we therefore examined whether maternal exposure to diesel exhaust PM_2.5 (DEP), one of the major sources of ambient PM_2.5 in urban areas, programs adult offspring's glucose metabolism. Female C57Bl/6J mice were intratracheally instilled with DEP or vehicle throughout a 7-wk preconceptional period, gestation, and lactation, and the glucose homeostasis of their adult male offspring was assessed. Intraperitoneal glucose tolerance test (IPGTT) revealed that the maternal exposure to DEP significantly impaired adult male offspring's glucose tolerance. Unexpectedly, it did not influence their insulin sensitivity, whereas it significantly decreased their glucose-induced insulin secretion (GIIS). This deficit in insulin secretion was corroborated by their significant decrease in arginine-induced insulin secretion. Histological analysis demonstrated that the deficit in insulin secretion was accompanied by the decrease in pancreatic islet and β cell sizes. To differentiate the effects of maternal exposure to DEP before birth and during lactation, some offspring were cross-fostered once born. We did not observe any significant effect of cross-fostering on the glucose homeostasis of adult male offspring and the function and morphology of their β cells. Prenatal exposure to DEP programs the morphology and function of β cells and thus homeostatic regulation of glucose metabolism in adult male offspring.

A Common Type 2 Diabetes Risk Variant Potentiates Activity of an Evolutionarily Conserved Islet Stretch Enhancer and Increases C2CD4A and C2CD4B Expression

Genome-wide association studies (GWASs) and functional genomics approaches implicate enhancer disruption in islet dysfunction and type 2 diabetes (T2D) risk. We applied genetic fine-mapping and functional (epi)genomic approaches to a T2D- and proinsulin-associated 15q22.2 locus to identify a most likely causal variant, determine its direction of effect, and elucidate plausible target genes. Fine-mapping and conditional analyses of proinsulin levels of 8,635 non-diabetic individuals from the METSIM study support a single association signal represented by a cluster of 16 strongly associated (p < 10^-17) variants in high linkage disequilibrium (r² > 0.8) with the GWAS index SNP rs7172432. These variants reside in an evolutionarily and functionally conserved islet and β cell stretch or super enhancer; the most strongly associated variant (rs7163757, p = 3 × 10^-19) overlaps a conserved islet open chromatin site. DNA sequence containing the rs7163757 risk allele displayed 2-fold higher enhancer activity than the non-risk allele in reporter assays (p < 0.01) and was differentially bound by β cell nuclear extract proteins. Transcription factor NFAT specifically potentiated risk-allele enhancer activity and altered patterns of nuclear protein binding to the risk allele in vitro, suggesting that it could be a factor mediating risk-allele effects. Finally, the rs7163757 proinsulin-raising and T2D risk allele (C) was associated with increased expression of C2CD4B, and possibly C2CD4A, both of which were induced by inflammatory cytokines, in human islets. Together, these data suggest that rs7163757 contributes to genetic risk of islet dysfunction and T2D by increasing NFAT-mediated islet enhancer activity and modulating C2CD4B, and possibly C2CD4A, expression in (patho)physiologic states.

Arsenic-gene interactions and beta-cell function in the Strong Heart Family Study

We explored arsenic-gene interactions influencing pancreatic beta-cell activity in the Strong Heart Family Study (SHFS). We considered 42 variants selected for associations with either beta-cell function (31 variants) or arsenic metabolism (11 variants) in the SHFS. Beta-cell function was calculated as homeostatic model - beta corrected for insulin resistance (cHOMA-B) by regressing homeostatic model - insulin resistance (HOMA-IR) on HOMA-B and adding mean HOMA-B. Arsenic exposure was dichotomized at the median of the sum of creatinine-corrected inorganic and organic arsenic species measured by high performance liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICPMS). Additive GxE models for cHOMA-B were adjusted for age and ancestry, and accounted for family relationships. Models were stratified by center (Arizona, Oklahoma, North Dakota and South Dakota) and meta-analyzed. The two interactions between higher vs. lower arsenic and SNPs for cHOMA-B that were nominally significant at P < 0.05 were with rs10738708 (SNP overall effect -3.91, P = 0.56; interaction effect with arsenic -31.14, P = 0.02) and rs4607517 (SNP overall effect +16.61, P = 0.03; interaction effect with arsenic +27.02, P = 0.03). The corresponding genes GCK and TUSC1 suggest oxidative stress and apoptosis as possible mechanisms for arsenic impacts on beta-cell function. No interactions were Bonferroni-significant (1.16 × 10^-3). Our findings are suggestive of oligogenic moderation of arsenic impacts on pancreatic β-cell endocrine function, but were not Bonferroni-significant.

Misfolded proinsulin in the endoplasmic reticulum during development of beta cell failure in diabetes

The endoplasmic reticulum (ER) is broadly distributed throughout the cytoplasm of pancreatic beta cells, and this is where all proinsulin is initially made. Healthy beta cells can synthesize 6000 proinsulin molecules per second. Ordinarily, nascent proinsulin entering the ER rapidly folds via the formation of three evolutionarily conserved disulfide bonds (B7-A7, B19-A20, and A6-A11). A modest amount of proinsulin misfolding, including both intramolecular disulfide mispairing and intermolecular disulfide-linked protein complexes, is a natural by-product of proinsulin biosynthesis, as is the case for many proteins. The steady-state level of misfolded proinsulin-a potential ER stressor-is linked to (1) production rate, (2) ER environment, (3) presence or absence of naturally occurring (mutational) defects in proinsulin, and (4) clearance of misfolded proinsulin molecules. Accumulation of misfolded proinsulin beyond a certain threshold begins to interfere with the normal intracellular transport of bystander proinsulin, leading to diminished insulin production and hyperglycemia, as well as exacerbating ER stress. This is most obvious in mutant INS gene-induced Diabetes of Youth (MIDY; an autosomal dominant disease) but also likely to occur in type 2 diabetes owing to dysregulation in proinsulin synthesis, ER folding environment, or clearance.

Identification of key gene pathways and coexpression networks of islets in human type 2 diabetes

PURPOSE

The number of people with type 2 diabetes (T2D) is growing rapidly worldwide. Islet β-cell dysfunction and failure are the main causes of T2D pathological processes. The aim of this study was to elucidate the underlying pathways and coexpression networks in T2D islets.

MATERIALS AND METHODS

We analyzed the differentially expressed genes (DEGs) in the data set GSE41762, which contained 57 nondiabetic and 20 diabetic samples, and developed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Protein-protein interaction (PPI) network, the modules from the PPI network, and the gene annotation enrichment of modules were analyzed as well. Moreover, a weighted correlation network analysis (WGCNA) was applied to screen critical gene modules and coexpression networks and explore the biological significance.

RESULTS

We filtered 957 DEGs in T2D islets. Then GO and KEGG analyses identified that key pathways like inflammatory response, type B pancreatic cell differentiation, and calcium ion-dependent exocytosis were involved in human T2D. Three significant modules were filtered from the PPI network. Ribosome biogenesis, extrinsic apoptotic signaling pathway, and membrane depolarization during action potential were associated with the modules, respectively. Furthermore, coexpression network analysis by WGCNA identified 13 distinct gene modules of T2D islets and revealed four modules, which were strongly correlated with T2D and T2D biomarker hemoglobin A1c (HbA1c). Functional annotation showed that these modules mainly enriched KEGG pathways such as NF-kappa B signaling pathway, tumor necrosis factor signaling pathway, cyclic adenosine monophosphate signaling pathway, and peroxisome proliferators-activated receptor signaling pathway.

CONCLUSION

The results provide potential gene pathways and underlying molecular mechanisms for the prevention, diagnosis, and treatment of T2D.

Vildagliptin loaded triangular DNA nanospheres coated with eudragit for oral delivery and better glycemic control in type 2 diabetes mellitus

Diabetes mellitus type 2 is a multidimensional disease associated with poor glycemic control through compromised sensitivity of pancreatic islet α and β cells against glucose and dwindled secretion of insulin which is linked with the quantity of incretin hormones that are abridged by dipeptidyl peptidase-4 (DPP-4) in diseased condition. Vildagliptin (VG) inhibits DPP-4 therefore regulates the incretins that conversely maintains glycemic control. The safe reach and absorption of VG from intestine was dubious. Therefore we used Electrostatic Attraction Method to develop drug loaded DNA nanotechnology triangles coated by Eudragit (Eud) to make stable nanospheres of Vildagliptin (VG). We further analyzed the formulated nanospheres by AFM, XRD, DSC, SEM, TGA, ATR-FTIR and native PAGE. Additionally the efficacy of formulated nanospheres for drug release and glycemic control was assessed in Db/Db mouse. Our results showed that formulated nanospheres are smooth, spherical, stable and uniform in size ranging from 500 to 2000 nm with drug entrapment efficiency up to 95 ± 2% and extended drug release up to 15 ± 2 h. FTIR and DSC results confirmed the absence of VG-DNA-Eud interaction and XRD studies revealed a change in the crystalline status of the VG in nanospheres. Ex-vivo studies indicate that Eud-DNA-VG nanospheres effectively bypasses the acidic pH of the stomach and enhances glycemic control in Db/Db mouse without any risk of pancreatitis or pancreatic cancer. To the best of our knowledge, this is the first study conclusively reporting that VG loaded DNA Nano-architects coated with Eudragit are stable, safe and may improve therapeutic outcomes after oral delivery.

Effect of diabetes status and hyperglycemia on global DNA methylation and hydroxymethylation

Type 2 diabetes mellitus (T2DM) is characterized by oxidative stress that could lead to chronic micro- and macrovascular complications. We hypothesized that some of the target organ damage is mediated by oxidative alterations in epigenetic mechanisms involving DNA methylation (5mC) and DNA hydroxymethylation (5hmC). We analyzed global DNA methylation and hydroxymethylation in peripheral blood cells in well-controlled and poorly controlled patients with T2DM and compared them with healthy controls. We also analyzed microarrays of DNA methylation and gene expression of other important tissues in the context of diabetes from the GEO database repository and then compared these results with our experimental gene expression data. DNA methylation and, more importantly, DNA hydroxymethylation levels were increased in poorly controlled patients compared to well-controlled and healthy individuals. Both 5mC and 5hmC measurements were correlated with the percentage of glycated hemoglobin, indicating a direct impact of hyperglycemia on changes over the epigenome. The analysis of methylation microarrays was concordant, and 5mC levels were increased in the peripheral blood of T2DM patients. However, the DNA methylation levels were the opposite of those in other tissues, such as the pancreas, adipose tissue and skeletal muscle. We hypothesize that a process of DNA oxidation associated with hyperglycemia may explain the DNA demethylation in which the activity of ten-eleven translocation (TET) proteins is not sufficient to complete the process. High levels of glucose lead to cellular oxidation, which triggers the process of DNA demethylation aided by TET enzymes, resulting in epigenetic dysregulation of the damaged tissues.

FGF-2b and h-PL Transform Duct and Non-Endocrine Human Pancreatic Cells into Endocrine Insulin Secreting Cells by Modulating Differentiating Genes

Background: Diabetes mellitus (DM) is a multifactorial disease orphan of a cure. Regenerative medicine has been proposed as novel strategy for DM therapy. Human fibroblast growth factor (FGF)-2b controls β-cell clusters via autocrine action, and human placental lactogen (hPL)-A increases functional β-cells. We hypothesized whether FGF-2b/hPL-A treatment induces β-cell differentiation from ductal/non-endocrine precursor(s) by modulating specific genes expression. Methods: Human pancreatic ductal-cells (PANC-1) and non-endocrine pancreatic cells were treated with FGF-2b plus hPL-A at 500 ng/mL. Cytofluorimetry and Immunofluorescence have been performed to detect expression of endocrine, ductal and acinar markers. Bromodeoxyuridine incorporation and annexin-V quantified cells proliferation and apoptosis. Insulin secretion was assessed by RIA kit, and electron microscopy analyzed islet-like clusters. Results: Increase in PANC-1 duct cells de-differentiation into islet-like aggregates was observed after FGF-2b/hPL-A treatment showing ultrastructure typical of islets-aggregates. These clusters, after stimulation with FGF-2b/hPL-A, had significant (p < 0.05) increase in insulin, C-peptide, pancreatic and duodenal homeobox 1 (PDX-1), Nkx2.2, Nkx6.1, somatostatin, glucagon, and glucose transporter 2 (Glut-2), compared with control cells. Markers of PANC-1 (Cytokeratin-19, MUC-1, CA19-9) were decreased (p < 0.05). These aggregates after treatment with FGF-2b/hPL-A significantly reduced levels of apoptosis. Conclusions: FGF-2b and hPL-A are promising candidates for regenerative therapy in DM by inducing de-differentiation of stem cells modulating pivotal endocrine genes.

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.

ATP synthase β-subunit abnormality in pancreas islets of rats with polycystic ovary syndrome and type 2 diabetes mellitus

This study investigated the abnormal expression of ATP synthase β-subunit (ATPsyn-β) in pancreas islets of rat model of polycystic ovary syndrome (PCOS) with type 2 diabetes mellitus (T2DM), and the secretion function changes after up-regulation of ATP5b. Sixty female SD rats were divided into three groups randomly and equally. The rat model of PCOS with T2DM was established by free access to the high-carbohydrate/high-fat diet, subcutaneous injections of DHEA, and a single injection of streptozotocin. The pancreas was removed for the detection of the ATPsyn-β expression by immunohistochemical staining, Western blotting and reverse transcription-PCR (RT-PCR). The pancreas islets of the rats were cultured, isolated with collagenase V and purified by gradient centrifugation, and the insulin secretion after treatment with different glucose concentrations was tested. Lentivirus ATP5b was successfully constructed with the vector of GV208 and transfected into the pancreas islets for the over-expression of ATPsyn-β. The insulin secretion and intracellular ATP content were determined after transfection of the PCOS-T2DM pancreas islets with Lenti-ATP5b. The results showed that the expression of ATPsyn-β protein and mRNA was significantly decreased in the pancreas of PCOS-T2DM rats. The ATP content in the pancreas islets was greatly increased and the insulin secretion was improved after the up-regulation of ATPsyn-β in the pancreas islets transfected with lenti-ATP5b. These results indicated that for PCOS, the ATPsyn-β might be one of the key factors for the attack of T2DM.