Identification of novel genes for glucose metabolism based upon expression pattern in human islets and effect on insulin secretion and glycemia

Unraveling the significance of PPP1R1A gene in pancreatic β-cell function: A study in INS-1 cells and human pancreatic islets

BACKGROUND AND AIMS

The protein phosphatase 1 regulatory inhibitor subunit 1A (PPP1R1A) has been linked with insulin secretion and diabetes mellitus. Yet, its full significance in pancreatic β-cell function remains unclear. This study aims to elucidate the role of the PPP1R1A gene in β-cell biology using human pancreatic islets and rat INS-1 (832/13) cells.

RESULTS

Disruption of Ppp1r1a in INS-1 cells was associated with reduced insulin secretion and impaired glucose uptake; however, cell viability, ROS, apoptosis or proliferation were intact. A significant downregulation of crucial β-cell function genes such as Ins1, Ins2, Pcsk1, Cpe, Pdx1, Mafa, Isl1, Glut2, Snap25, Vamp2, Syt5, Cacna1a, Cacna1d and Cacnb3, was observed upon Ppp1r1a disruption. Furthermore, silencing Pdx1 in INS-1 cells altered PPP1R1A expression, indicating that PPP1R1A is a target gene for PDX1. Treatment with rosiglitazone increased Ppp1r1a expression, while metformin and insulin showed no effect. RNA-seq analysis of human islets revealed high PPP1R1A expression, with α-cells showing the highest levels compared to other endocrine cells. Muscle tissues exhibited greater PPP1R1A expression than pancreatic islets, liver, or adipose tissues. Co-expression analysis revealed significant correlations between PPP1R1A and genes associated with insulin biosynthesis, exocytosis machinery, and intracellular calcium transport. Overexpression of PPP1R1A in human islets augmented insulin secretion and upregulated protein expression of Insulin, MAFA, PDX1, and GLUT1, while silencing of PPP1R1A reduced Insulin, MAFA, and GLUT1 protein levels.

CONCLUSION

This study provides valuable insights into the role of PPP1R1A in regulating β-cell function and glucose homeostasis. PPP1R1A presents a promising opportunity for future therapeutic interventions.

Identification of HDAC9 and ARRDC4 as potential biomarkers and targets for treatment of type 2 diabetes

We aimed to identify the key potential insulin resistance (IR)-related genes and investigate their correlation with immune cell infiltration in type 2 diabetes (T2D). The GSE78721 dataset (68 diabetic patients and 62 controls) was downloaded from the Gene Expression Omnibus database and utilized for single-sample gene set enrichment analysis. IR-related genes were obtained from the Comparative Toxicology Genetics Database, and the final IR-differentially expressed genes (DEGs) were screened by intersecting with the DEGs obtained from the GSE78721 datasets. Functional enrichment analysis was performed, and the networks of the target gene with microRNA, transcription factor, and drug were constructed. Hub genes were identified based on a protein-protein interaction network. Least absolute shrinkage and selection operator regression and Random Forest and Boruta analysis were combined to screen diagnostic biomarkers in T2D, which were validated using the GSE76894 (19 diabetic patients and 84 controls) and GSE9006 (12 diabetic patients and 24 controls) datasets. Quantitative real-time polymerase chain reaction was performed to validate the biomarker expression in IR mice and control mice. In addition, infiltration of immune cells in T2D and their correlation with the identified markers were computed using CIBERSORT. We identified differential immune gene set regulatory T-cells in the GSE78721 dataset, and T2D samples were assigned into three clusters based on immune infiltration. A total of 2094 IR-DEGs were primarily enriched in response to endoplasmic reticulum stress. Importantly, HDAC9 and ARRDC4 were identified as markers of T2D and associated with different levels of immune cell infiltration. HDAC9 mRNA level were higher in the IR mice than in control mice, while ARRDC4 showed the opposite trend. In summary, we discovered potential vital biomarkers that contribute to immune cell infiltration associated with IR, which offers a new sight of immunotherapy for T2D.

Genetic Diversity, Population Structure and Selection Signature in Begait Goats Revealed by Whole-Genome Sequencing

Goats belong to a group of animals called small ruminants and are critical sources of livelihood for rural people. Genomic sequencing can provide information ranging from basic knowledge about goat diversity and evolutionary processes that shape genomes to functional information about genes/genomic regions. In this study, we exploited a whole-genome sequencing data set to analyze the genetic diversity, population structure and selection signatures of 44 individuals belonging to 5 Ethiopian goat populations: 12 Aberegalle (AB), 5 Afar (AF), 11 Begait (BG), 12 Central highlands (CH) and 5 Meafure (MR) goats. Our results revealed the highest genetic diversity in the BG goat population compared to the other goat populations. The pairwise genetic differentiation (FST) among the populations varied and ranged from 0.011 to 0.182, with the closest pairwise value (0.003) observed between the AB and CH goats and a distant correlation (FST = 0.182) between the BG and AB goats, indicating low to moderate genetic differentiation. Phylogenetic tree, ADMIXTURE and principal component analyses revealed a classification of the five Ethiopian goat breeds in accordance with their geographic distribution. We also found three top genomic regions that were detected under selection on chromosomes 2, 5 and 13. Moreover, this study identified different candidate genes related to milk characteristics (GLYCAM1 and SRC), carcass (ZNF385B, BMP-7, PDE1B, PPP1R1A, FTO and MYOT) and adaptive and immune response genes (MAPK13, MAPK14, SCN7A, IL12A, EST1 DEFB116 and DEFB119). In conclusion, this information could be helpful for understanding the genetic diversity and population structure and selection scanning of these important indigenous goats for future genetic improvement and/or as an intervention mechanism.

Validating Fractalkine receptor as a target and identifying candidates for drug discovery against type 2 diabetes

Type 2 diabetes mellitus (T2DM) is one of the most common chronic diseases employing abnormal levels of insulin. Enhancing the insulin production is greatly aided by the regulatory mechanisms of the Fractalkine receptor (CX3CR1) system in islet β-cell function. However, elements including a high-fat diet, obesity, and ageing negatively impact the expression of CX3CR1 in islets. CX3CL1/CX3CR1 receptor-ligand complex is now recognized as a novel therapeutic target. It suggests that T2DM-related β-cell dysfunction may result from lower amount of these proteins. We analyzed the differential expression of CX3CR1 gene samples taken from persons with T2DM using data obtained from the Gene Expression Omnibus database. Homology modeling enabled us to generate the three-dimensional structure of CX3CR1 and a possible binding pocket. The optimized CX3CR1 structure was subjected to rigorous screening against a massive library of 693 million drug-like molecules from the ZINC15 database. This screening process led to the identification of three compounds with strong binding affinity at the identified binding pocket of CX3CR1. To further evaluate the potential of these compounds, molecular dynamics simulations were conducted over a 50 ns time scale to assess the stability of the protein-ligand complexes. These simulations revealed that ZINC000032506419 emerged as the most promising drug-like compound among the three potent molecules. The discovery of ZINC000032506419 holds exciting promise as a potential therapeutic agent for T2D and other related metabolic disorders. These findings pave the way for the development of effective medications to address the complexities of T2DM and its associated metabolic diseases.

An Integrated Map of Cell Type-Specific Gene Expression in Pancreatic Islets

Pancreatic islets consist of multiple cell types that produce hormones required for glucose homeostasis, and islet dysfunction is a major factor in type 1 and type 2 diabetes. Numerous studies have assessed transcription across individual cell types using single-cell assays; however, there is no canonical reference of gene expression in islet cell types that is also easily accessible for researchers to query and use in bioinformatics pipelines. Here we present an integrated map of islet cell type-specific gene expression from 192,203 cells from single-cell RNA sequencing of 65 donors without diabetes, donors who were type 1 diabetes autoantibody positive, donors with type 1 diabetes, and donors with type 2 diabetes from the Human Pancreas Analysis Program. We identified 10 distinct cell types, annotated subpopulations of several cell types, and defined cell type-specific marker genes. We tested differential expression within each cell type across disease states and identified 1,701 genes with significant changes in expression, with most changes observed in β-cells from donors with type 1 diabetes. To facilitate user interaction, we provide several single-cell visualization and reference mapping tools, as well as the open-access analytical pipelines used to create this reference. The results will serve as a valuable resource to investigators studying islet biology.

ARTICLE HIGHLIGHTS

Copy number variation as a tool for implementing pregnancy as an aging model

Copy number variations (CNV) are a major contributor to genome variability and have been linked to aging and other degradable phenotypes such as pregnancy physiology. To demonstrate how pregnancy can be used as a model of aging, we used CNVs from pregnant mice. Candidate CNVs were selected by applying case-control analysis in human centenarians compared with control groups. These CNVs were aligned with the mouse genome and their copy variation was assessed using qRT-PCR in liver and blood tissue samples from pregnant mice throughout pregnancy (baseline; first, second, and third trimester; post-partum). Eight of the ten selected CNVs demonstrated a significant decline/increase trend throughout the pregnancy followed by opposite direction soon after delivery in the liver and blood of the mouse tissues. Furthermore, significant differential expression was detected among the candidate CNVs' close vicinity genes (APA2A, LSS, RBDHF1, PLAAT1, and SCL17A2), but not in the WSCD2 gene. Establishing a genetic link between longevity and pregnancy is a significant step toward implementing the pregnancy process as a model for aging. These results in pregnant mice highlight the mechanism and similarities between pregnancy and aging. Investigating the mechanisms that cause such rejuvenation after labor could change our aging treatment paradigm.

Genetic underpinning of the comorbidity between type 2 diabetes and osteoarthritis

Multimorbidity is a rising public health challenge with important implications for health management and policy. The most common multimorbidity pattern is the combination of cardiometabolic and osteoarticular diseases. Here, we study the genetic underpinning of the comorbidity between type 2 diabetes and osteoarthritis. We find genome-wide genetic correlation between the two diseases and robust evidence for association-signal colocalization at 18 genomic regions. We integrate multi-omics and functional information to resolve the colocalizing signals and identify high-confidence effector genes, including FTO and IRX3, which provide proof-of-concept insights into the epidemiologic link between obesity and both diseases. We find enrichment for lipid metabolism and skeletal formation pathways for signals underpinning the knee and hip osteoarthritis comorbidities with type 2 diabetes, respectively. Causal inference analysis identifies complex effects of tissue-specific gene expression on comorbidity outcomes. Our findings provide insights into the biological basis for the type 2 diabetes-osteoarthritis disease co-occurrence.

Single-cell transcriptomic profiling of human pancreatic islets reveals genes responsive to glucose exposure over 24 hours

Disruption of pancreatic islet function and glucose homeostasis can lead to the development of sustained hyperglycemia, beta cell glucotoxicity, and ultimately type 2 diabetes (T2D). In this study, we sought to explore the effects of hyperglycemia on human pancreatic islet (HPI) gene expression by exposing HPIs from two donors to low (2.8mM) and high (15.0mM) glucose concentrations over 24 hours, assaying the transcriptome at seven time points using single-cell RNA sequencing (scRNA-seq). We modeled time as both a discrete and continuous variable to determine momentary and longitudinal changes in transcription associated with islet time in culture or glucose exposure. Across all cell types, we identified 1,528 genes associated with time, 1,185 genes associated with glucose exposure, and 845 genes associated with interaction effects between time and glucose. We clustered differentially expressed genes across cell types and found 347 modules of genes with similar expression patterns across time and glucose conditions, including two beta cell modules enriched in genes associated with T2D. Finally, by integrating genomic features from this study and genetic summary statistics for T2D and related traits, we nominate 363 candidate effector genes that may underlie genetic associations for T2D and related traits.

Disrupting of family with sequence similarity 105, member A (Fam105a) deteriorates pancreatic β-cell physiology and insulin secretion in INS-1 cells

The role of "Family with sequence similarity 105, member A" (FAM105A) in pancreatic β-cell function in relation to type 2 diabetes mellitus (T2D) is not fully understood. To address this issue, various molecular and functional experiments were conducted on primary human islets and INS-1 cells. RNA-seq expression analysis showed that FAM105A is highly expressed in human islets and its expression is reduced in diabetic islets compared to healthy islets. FAM105A expression correlated negatively with HbA1c levels and body mass index (BMI). Co-expression analysis showed a significant correlation between FAM105A with PDX1, GCK, GLUT1 and INSR, but not the INS gene. Silencing of Fam105a impaired insulin release, content, glucose uptake, and mitochondria ATP content but did not affect cell viability, reactive oxygen species (ROS) or apoptosis levels. Silencing of Fam105a was associated with reduced Pdx1 and Glut2 expression at mRNA and protein levels. RNA-seq analysis of dysregulated genes in Fam105a-silenced cells showed an overall downregulation of gene expression in β-cells and insulin secretion pathway. Disrupting Pdx1 did not affect Fam105a expression in INS-1 cells. Overall, the results suggest that FAM105A plays an important role in pancreatic β-cells biology and may be involved in the development of T2D.

Identification of common signature genes and pathways underlying the pathogenesis association between nonalcoholic fatty liver disease and atherosclerosis

Background

Atherosclerosis (AS) is one of the leading causes of the cardio-cerebral vascular incident. The constantly emerging evidence indicates a close association between nonalcoholic fatty liver disease (NAFLD) and AS. However, the exact molecular mechanisms underlying the correlation between these two diseases remain unclear. This study proposed exploring the common signature genes, pathways, and immune cells among AS and NAFLD.

Methods

The common differentially expressed genes (co-DEGs) with a consistent trend were identified via bioinformatic analyses of the Gene Expression Omnibus (GEO) datasets GSE28829 and GSE49541, respectively. Further, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. We utilized machine learning algorithms of lasso and random forest (RF) to identify the common signature genes. Then the diagnostic nomogram models and receiver operator characteristic curve (ROC) analyses were constructed and validated with external verification datasets. The gene interaction network was established via the GeneMANIA database. Additionally, gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), and immune infiltration analysis were performed to explore the co-regulated pathways and immune cells.

Results

A total of 11 co-DEGs were identified. GO and KEGG analyses revealed that co-DEGs were mainly enriched in lipid catabolic process, calcium ion transport, and regulation of cytokine. Moreover, three common signature genes (PLCXD3, CCL19, and PKD2) were defined. Based on these genes, we constructed the efficiently predictable diagnostic models for advanced AS and NAFLD with the nomograms, evaluated with the ROC curves (AUC = 0.995 for advanced AS, 95% CI 0.971–1.0; AUC = 0.973 for advanced NAFLD, 95% CI 0.938–0.998). In addition, the AUC of the verification datasets had a similar trend. The NOD-like receptors (NLRs) signaling pathway might be the most crucial co-regulated pathway, and activated CD4 T cells and central memory CD4 T cells were significantly excessive infiltration in advanced NAFLD and AS.

Conclusion

We identified three common signature genes (PLCXD3, CCL19, and PKD2), co-regulated pathways, and shared immune features of NAFLD and AS, which might provide novel insights into the molecular mechanism of NAFLD complicated with AS.

Propensity scores as a novel method to guide sample allocation and minimize batch effects during the design of high throughput experiments

BACKGROUND

We developed a novel approach to minimize batch effects when assigning samples to batches. Our algorithm selects a batch allocation, among all possible ways of assigning samples to batches, that minimizes differences in average propensity score between batches. This strategy was compared to randomization and stratified randomization in a case-control study (30 per group) with a covariate (case vs control, represented as β1, set to be null) and two biologically relevant confounding variables (age, represented as β2, and hemoglobin A1c (HbA1c), represented as β3). Gene expression values were obtained from a publicly available dataset of expression data obtained from pancreas islet cells. Batch effects were simulated as twice the median biological variation across the gene expression dataset and were added to the publicly available dataset to simulate a batch effect condition. Bias was calculated as the absolute difference between observed betas under the batch allocation strategies and the true beta (no batch effects). Bias was also evaluated after adjustment for batch effects using ComBat as well as a linear regression model. In order to understand performance of our optimal allocation strategy under the alternative hypothesis, we also evaluated bias at a single gene associated with both age and HbA1c levels in the 'true' dataset (CAPN13 gene).

RESULTS

Pre-batch correction, under the null hypothesis (β1), maximum absolute bias and root mean square (RMS) of maximum absolute bias, were minimized using the optimal allocation strategy. Under the alternative hypothesis (β2 and β3 for the CAPN13 gene), maximum absolute bias and RMS of maximum absolute bias were also consistently lower using the optimal allocation strategy. ComBat and the regression batch adjustment methods performed well as the bias estimates moved towards the true values in all conditions under both the null and alternative hypotheses. Although the differences between methods were less pronounced following batch correction, estimates of bias (average and RMS) were consistently lower using the optimal allocation strategy under both the null and alternative hypotheses.

CONCLUSIONS

Our algorithm provides an extremely flexible and effective method for assigning samples to batches by exploiting knowledge of covariates prior to sample allocation.

DNA methylation in peripheral blood leukocytes for the association with glucose metabolism and invasive breast cancer

BACKGROUND

Insulin resistance (IR) is a well-established factor for breast cancer (BC) risk in postmenopausal women, but the interrelated molecular pathways on the methylome are not explicitly described. We conducted a population-level epigenome-wide association (EWA) study for DNA methylation (DNAm) probes that are associated with IR and prospectively correlated with BC development, both overall and in BC subtypes among postmenopausal women.

METHODS

We used data from Women's Health Initiative (WHI) ancillary studies for our EWA analyses and evaluated the associations of site-specific DNAm across the genome with IR phenotypes by multiple regressions adjusting for age and leukocyte heterogeneities. For our analysis of the top 20 IR-CpGs with BC risk, we used the WHI and the Cancer Genomic Atlas (TCGA), using multiple Cox proportional hazards and logit regressions, respectively, accounting for age, diabetes, obesity, leukocyte heterogeneities, and tumor purity (for TCGA). We further conducted a Gene Set Enrichment Analysis.

RESULTS

We detected several EWA-CpGs in TXNIP, CPT1A, PHGDH, and ABCG1. In particular, cg19693031 in TXNIP was replicated in all IR phenotypes, measured by fasting levels of glucose, insulin, and homeostatic model assessment-IR. Of those replicated IR-genes, 3 genes (CPT1A, PHGDH, and ABCG1) were further correlated with BC risk; and 1 individual CpG (cg01676795 in POR) was commonly detected across the 2 cohorts.

CONCLUSIONS

Our study contributes to better understanding of the interconnected molecular pathways on the methylome between IR and BC carcinogenesis and suggests potential use of DNAm markers in the peripheral blood cells as preventive targets to detect an at-risk group for IR and BC in postmenopausal women.

The human batokine EPDR1 regulates β-cell metabolism and function

OBJECTIVE

Ependymin-Related Protein 1 (EPDR1) was recently identified as a secreted human batokine regulating mitochondrial respiration linked to thermogenesis in brown fat. Despite that EPDR1 is expressed in human pancreatic β-cells and that glucose-stimulated mitochondrial metabolism is critical for stimulus-secretion coupling in β-cells, the role of EPDR1 in β-cell metabolism and function has not been investigated.

METHODS

EPDR1 mRNA levels in human pancreatic islets from non-diabetic (ND) and type 2 diabetes (T2D) subjects were assessed. Human islets, EndoC-βH1 and INS1 832/13 cells were transfected with scramble (control) and EPDR1 siRNAs (EPDR1-KD) or treated with human EPDR1 protein, and glucose-stimulated insulin secretion (GSIS) assessed by ELISA. Mitochondrial metabolism was investigated by extracellular flux analyzer, confocal microscopy and mass spectrometry-based metabolomics analysis.

RESULTS

EPDR1 mRNA expression was upregulated in human islets from T2D and obese donors and positively correlated to BMI of donors. In T2D donors, EPDR1 mRNA levels negatively correlated with HbA1c and positively correlated with GSIS. EPDR1 silencing in human islets and β-cell lines reduced GSIS whereas treatment with human EPDR1 protein increased GSIS. Epdr1 silencing in INS1 832/13 cells reduced glucose- and pyruvate- but not K⁺-stimulated insulin secretion. Metabolomics analysis in Epdr1-KD INS1 832/13 cells suggests diversion of glucose-derived pyruvate to lactate production and decreased malate-aspartate shuttle and the tricarboxylic acid (TCA) cycle activity. The glucose-stimulated rise in mitochondrial respiration and ATP/ADP-ratio was impaired in Epdr1-deficient cells.

CONCLUSION

These results suggests that to maintain glucose homeostasis in obese people, upregulation of EPDR1 may improve β-cell function via channelling glycolysis-derived pyruvate to the mitochondrial TCA cycle.

Islet Gene View-a tool to facilitate islet research

Characterization of gene expression in pancreatic islets and its alteration in type 2 diabetes (T2D) are vital in understanding islet function and T2D pathogenesis. We leveraged RNA sequencing and genome-wide genotyping in islets from 188 donors to create the Islet Gene View (IGW) platform to make this information easily accessible to the scientific community. Expression data were related to islet phenotypes, diabetes status, other islet-expressed genes, islet hormone-encoding genes and for expression in insulin target tissues. The IGW web application produces output graphs for a particular gene of interest. In IGW, 284 differentially expressed genes (DEGs) were identified in T2D donor islets compared with controls. Forty percent of DEGs showed cell-type enrichment and a large proportion significantly co-expressed with islet hormone-encoding genes; glucagon (<i>GCG</i>, 56%), amylin (<i>IAPP</i>, 52%), insulin (<i>INS</i>, 44%), and somatostatin (<i>SST</i>, 24%). Inhibition of two DEGs, <i>UNC5D</i> and <i>SERPINE2</i>, impaired glucose-stimulated insulin secretion and impacted cell survival in a human β-cell model. The exploratory use of IGW could help designing more comprehensive functional follow-up studies and serve to identify therapeutic targets in T2D.

Every islet matters: improving the impact of human islet research

Detailed characterization of human pancreatic islets is key to elucidating the pathophysiology of all forms of diabetes, especially type 2 diabetes. However, access to human pancreatic islets is limited. Pancreatic tissue for islet retrieval can be obtained from brain-dead organ donors or from individuals undergoing pancreatectomy, often referred to as 'living donors'. Different protocols for human islet procurement can substantially impact islet function. This variability, coupled with heterogeneity between individuals and islets, results in analytical challenges to separate genuine disease pathology or differences between human donors from experimental noise. There are currently no international guidelines for human donor phenotyping, islet procurement and functional characterization. This lack of standardization means that substantial investments from multiple international efforts towards improved understanding of diabetes pathology cannot be fully leveraged. In this Perspective, we overview the status of the field of human islet research, highlight the challenges and propose actions that could accelerate research progress and increase understanding of type 2 diabetes to slow its pandemic spreading.

Reduced Retinoic Acid Receptor Beta (Rarβ) Affects Pancreatic β-Cell Physiology

Various studies have suggested a link between vitamin A (VA), all-trans-retinol, and type 2 diabetes (T2D). However, the functional role/expression of vitamin A receptors (Rarα, β, and γ) in pancreatic β-cells is not clear yet. Accordingly, we performed a series of bioinformatics, molecular and functional experiments in human islet and INS-1 cells to evaluate the role of Rarβ on insulin secretion and pancreatic β-cell function. Microarray and RNA-sequencing (RAN-seq) expression analysis showed that RARα, β, and γ are expressed in human pancreatic islets. RNA-seq expression of RARβ in diabetic/hyperglycemic human islets (HbA1c ≥ 6.3%) revealed a significant reduction (p = 0.004) compared to nondiabetic/normoglycemic cells (HbA1c < 6%). The expression of RARβ with INS and PDX1 showed inverse association, while positive correlations were observed with INSR and HbA1c levels. Exploration of the T2D knowledge portal (T2DKP) revealed that several genetic variants in RARβ are associated with BMI. The most associated variant is rs6804842 (p = 1.2 × 10−25). Silencing of Rarβ in INS-1 cells impaired insulin secretion without affecting cell viability or apoptosis. Interestingly, reactive oxygen species (ROS) production levels were elevated and glucose uptake was reduced in Rarβ-silenced cells. mRNA expression of Ins1, Pdx1, NeuroD1, Mafa, Snap25, Vamp2, and Gck were significantly (p < 0.05) downregulated in Rarβ-silenced cells. For protein levels, Pro/Insulin, PDX1, GLUT2, GCK, pAKT/AKT, and INSR expression were downregulated considerably (p < 0.05). The expression of NEUROD and VAMP2 were not affected. In conclusion, our results indicate that Rarβ is an important molecule for β-cell function. Hence, our data further support the potential role of VA receptors in the development of T2D.

Long non-coding RNAs: a valuable biomarker for metabolic syndrome

Long non-coding RNAs (lncRNAs) have become important regulators of gene expression because they affect a wide range of biological processes, such as cell growth, death, differentiation, and aging. More and more evidence suggests that lncRNAs play a role in maintaining metabolic homeostasis. When certain lncRNAs are out of balance, metabolic disorders like diabetes, obesity, and heart disease get worse. In this review, we talk about what we know about how lncRNAs control metabolism, with a focus on diseases caused by long-term inflammation and the characteristics of the metabolic syndrome. We looked at lncRNAs and their molecular targets in the pathogenesis of signaling pathways. We also talked about how lncRNAs are becoming more and more interesting as diagnostic and therapeutic targets for improving metabolic homeostasis.

Gene expression of the endocannabinoid system in endometrium through menstrual cycle

Endocannabinoids mediate cellular functions and their activity is controlled by a complex system of enzymes, membrane receptors and transport molecules. Endocannabinoids are present in endometrium, a cyclical regenerative tissue requiring tightly regulated cellular mechanisms for maturation. The objective of this study was to investigate the gene expression of key elements involved in the endocannabinoid system across the menstrual cycle. RNA was isolated from endometrial tissue and genome-wide gene expression datasets were generated using RNA-sequencing. An a priori set of 70 genes associated with endocannabinoid system were selected from published literature. Gene expression across the menstrual cycle was analyzed using a moderated t test, corrected for multiple testing with Bonferroni’s method. A total of 40 of the 70 genes were present in > 90% of the samples, and significant differential gene expression identified for 29 genes. We identified 4 distinct regulation patterns for synthesizing enzymes, as well as a distinct regulation pattern for degradations and transporting enzymes. This study charts the expression of endometrial endocannabinoid system genes across the menstrual cycle. Altered expression of genes that control endocannabinoid may allow fine control over endocannabinoid concentrations and their influence on cellular function, maturation and differentiation as the endometrium matures through the menstrual cycle.

Proprotein convertase PCSK9 affects expression of key surface proteins in human pancreatic beta cells via intra- and extracellular regulatory circuits

Proprotein convertase subtilisin/kexin type 9 (PCSK9) is involved in the degradation of the low-density lipoprotein receptor. PCSK9 also targets proteins involved in lipid metabolism (very low–density lipoprotein receptor), immunity (major histocompatibility complex I), and viral infection (cluster of differentiation 81). Recent studies have also indicated that PCSK9 loss-of-function mutations are associated with an increased incidence of diabetes; however, the expression and function of PCSK9 in insulin-producing pancreatic beta cells remain unclear. Here, we studied PCSK9 regulation and function by performing loss- and gain-of-function experiments in the human beta cell line EndoC-βH1. We demonstrate that PCSK9 is expressed and secreted by EndoC-βH1 cells. We also found that PCSK9 expression is regulated by cholesterol and sterol regulatory element–binding protein transcription factors, as previously demonstrated in other cell types such as hepatocytes. Importantly, we show that PCSK9 knockdown using siRNA results in deregulation of various elements of the transcriptome, proteome, and secretome, and increases insulin secretion. We also observed that PCSK9 decreases low-density lipoprotein receptor and very low–density lipoprotein receptor levels via an extracellular signaling mechanism involving exogenous PCSK9, as well as levels of cluster of differentiation 36, a fatty acid transporter, through an intracellular signaling mechanism. Finally, we found that PCSK9 regulates the cell surface expression of PDL1 and HLA-ABC, proteins involved in cell–lymphocyte interaction, also via an intracellular mechanism. Collectively, these results highlight PCSK9 as a regulator of multiple cell surface receptors in pancreatic beta cells.

EXOC6 (Exocyst Complex Component 6) Is Associated with the Risk of Type 2 Diabetes and Pancreatic β-Cell Dysfunction

EXOC6 and EXOC6B (EXOC6/6B) components of the exocyst complex are involved in the secretory granule docking. Recently, EXOC6/6B were anticipated as a molecular link between dysfunctional pancreatic islets and ciliated lung epithelium, making diabetic patients more prone to severe SARS-CoV-2 complications. However, the exact role of EXOC6/6B in pancreatic β-cell function and risk of T2D is not fully understood. Herein, microarray and RNA-sequencing (RNA-seq) expression data demonstrated the expression of EXOC6/6B in human pancreatic islets. Expression of EXOC6/6B was not affected by diabetes status. Exploration of the using the translational human pancreatic islet genotype tissue-expression resource portal (TIGER) revealed three genetic variants (rs947591, rs2488071 and rs2488073) in the EXOC6 gene that were associated (p < 2.5 × 10−20) with the risk of T2D. Exoc6/6b silencing in rat pancreatic β-cells (INS1-832/13) impaired insulin secretion, insulin content, exocytosis machinery and glucose uptake without cytotoxic effect. A significant decrease in the expression Ins1, Ins1, Pdx1, Glut2 and Vamp2 was observed in Exoc6/6b-silenced cells at the mRNA and protein levels. However, NeuroD1, Gck and InsR were not influenced compared to the negative control. In conclusion, our data propose that EXOC6/6B are crucial regulators for insulin secretion and exocytosis machinery in β-cells. This study identified several genetic variants in EXOC6 associated with the risk of T2D. Therefore, EXOC6/6B could provide a new potential target for therapy development or early biomarkers for T2D.

MAFA and MAFB regulate exocytosis-related genes in human β-cells

AIMS

Reduced expression of exocytotic genes is associated with functional defects in insulin exocytosis contributing to impaired insulin secretion and type 2 diabetes (T2D) development. MAFA and MAFB transcription factors regulate β-cell physiology, and their gene expression is reduced in T2D β cells. We investigate if loss of MAFA and MAFB in human β cells contributes to T2D progression by regulating genes required for insulin exocytosis.

METHODS

Three approaches were performed: (1) RNAseq analysis with the focus on exocytosis-related genes in MafA^-/- mouse islets, (2) correlational analysis between MAFA, MAFB and exocytosis-related genes in human islets and (3) MAFA and MAFB silencing in human islets and EndoC-βH1 cells followed by functional in vitro studies.

RESULTS

The expression of 30 exocytosis-related genes was significantly downregulated in MafA^-/- mouse islets. In human islets, the expression of 29 exocytosis-related genes correlated positively with MAFA and MAFB. Eight exocytosis-related genes were downregulated in MafA^-/- mouse islets and positively correlated with MAFA and MAFB in human islets. From this analysis, the expression of RAB3A, STXBP1, UNC13A, VAMP2, NAPA, NSF, STX1A and SYT7 was quantified after acute MAFA or MAFB silencing in EndoC-βH1 cells and human islets. MAFA and MAFB silencing resulted in impaired insulin secretion and reduced STX1A, SYT7 and STXBP1 (EndoC-βH1) and STX1A (human islets) mRNA expression. STX1A and STXBP1 protein expression was also impaired in islets from T2D donors which lack MAFA expression.

CONCLUSION

Our data indicate that STXBP1 and STX1A are important MAFA/B-regulated exocytosis genes which may contribute to insulin exocytosis defects observed in MAFA-deficient human T2D β cells.

Plant polyphenols mechanisms of action on insulin resistance and against the loss of pancreatic beta cells

Diabetes mellitus describes a group of metabolic disorders characterized by a prolonged period hyperglycemia with long-lasting detrimental effects on the cardiovascular and nervous systems, kidney, vision, and immunity. Many plant polyphenols are shown to have beneficial activity for the prevention and treatment of diabetes, by different mechanisms. This review article is focused on synthesizing the mechanisms by which polyphenols decrease insulin resistance and inhibit loss of pancreatic islet β-cell mass and function. To achieve the objectives, this review summarizes the results of the researches realized in recent years in clinical trials and in various experimental models, on the effects of foods rich in polyphenols, polyphenolic extracts, and commercially polyphenols on insulin resistance and β-cells death. Dietary polyphenols are able to reduce insulin resistance alleviating the IRS-1/PI3-k/Akt signaling pathway, and to reduce the loss of pancreatic islet β-cell mass and function by several molecular mechanisms, such as protection of the surviving machinery of cells against the oxidative insult; increasing insulin secretion in pancreatic β-cells through activation of the FFAR1; cytoprotective effect on β-cells by activation of autophagy; protection of β-cells to act as activators for anti-apoptotic pathways and inhibitors for apoptotic pathway; stimulating of insulin release, presumably by transient ATP-sensitive K⁺ channel inhibition and whole-cell Ca²⁺ stimulation; involvement in insulin release that act on ionic currents and membrane potential as inhibitor of delayed-rectifier K⁺ current (I_K(DR)) and activator of current. dietary polyphenols could be used as potential anti-diabetic agents to prevent and alleviate diabetes and its complications, but further studies are needed.

Genome-Wide Placental Gene Methylations in Gestational Diabetes Mellitus, Fetal Growth and Metabolic Health Biomarkers in Cord Blood

Gestational diabetes mellitus (GDM) "program" an elevated risk of metabolic syndrome in the offspring. Epigenetic alterations are a suspected mechanism. GDM has been associated with placental DNA methylation changes in some epigenome-wide association studies. It remains unclear which genes or pathways are affected, and whether any placental differential gene methylations are correlated to fetal growth or circulating metabolic health biomarkers. In an epigenome-wide association study using the Infinium MethylationEPIC Beadchip, we sought to identify genome-wide placental differentially methylated genes and enriched pathways in GDM, and to assess the correlations with fetal growth and metabolic health biomarkers in cord blood. The study samples were 30 pairs of term placentas in GDM vs. euglycemic pregnancies (controls) matched by infant sex and gestational age at delivery in the Shanghai Birth Cohort. Cord blood metabolic health biomarkers included insulin, C-peptide, proinsulin, IGF-I, IGF-II, leptin and adiponectin. Adjusting for maternal age, pre-pregnancy BMI, parity, mode of delivery and placental cell type heterogeneity, 256 differentially methylated positions (DMPs,130 hypermethylated and 126 hypomethylated) were detected between GDM and control groups accounting for multiple tests with false discovery rate <0.05 and beta-value difference >0.05. WSCD2 was identified as a differentially methylated gene in both site- and region-level analyses. We validated 7 hypermethylated (CYP1A2, GFRA1, HDAC4, LIMS2, NAV3, PAX6, UPK1B) and 10 hypomethylated (DPP10, CPLX1, CSMD2, GPR133, NRXN1, PCSK9, PENK, PRDM16, PTPRN2, TNXB) genes reported in previous epigenome-wide association studies. We did not find any enriched pathway accounting for multiple tests. DMPs in 11 genes (CYP2D7P1, PCDHB15, ERG, SIRPB1, DKK2, RAPGEF5, CACNA2D4, PCSK9, TSNARE1, CADM2, KCNAB2) were correlated with birth weight (z score) accounting for multiple tests. There were no significant correlations between placental gene methylations and cord blood biomarkers. In conclusions, GDM was associated with DNA methylation changes in a number of placental genes, but these placental gene methylations were uncorrelated to the observed metabolic health biomarkers (fetal growth factors, leptin and adiponectin) in cord blood. We validated 17 differentially methylated placental genes in GDM, and identified 11 differentially methylated genes relevant to fetal growth.

Bioinformatics Analysis Identifies Potential Ferroptosis Key Gene in Type 2 Diabetic Islet Dysfunction

BACKGROUND

Islet β cells dysfunction (IBCD) is a cortical component in pathogenesis of type 2 diabetic mellitus (T2DM). However, the relationship of ferroptosis and IBCD remains unknown. This study was aimed to screen potential ferroptosis key genes to reveal latent physiological and pathological process of IBCD in T2DM.

METHODS

Firstly, T2DM key genes were screened by combining with differentially expressed genes (DEGs) analysis and WGCNA. Then, ferroptosis-related genes (FRGs) in IBCD of T2DM were identified by taking the intersection between T2DM key genes and FRGs. Finally, T2DM-FRGs were validated in another T2DM dataset as well as islet single-cell RNA sequencing dataset and the miRNA regulated T2DM-FRG was predicted by using four miRNA databases.

RESULTS

89 T2DM key genes were identified between DEGs and WGCNA. Then, 3 T2DM-FRGs were screened by taking the intersection of T2DM key genes and FRGs, namely ITGA6, MGST1 and ENO2. At last, MGST1 were validated as the T2DM-FRG in another T2DM islet issues dataset and islet single-cell RNA sequencing dataset.

CONCLUSION

MGST1 may be the potential ferroptosis key gene of IBCD in T2DM.

Abnormal exocrine-endocrine cell cross-talk promotes β-cell dysfunction and loss in MODY8

MODY8 (maturity-onset diabetes of the young, type 8) is a dominantly inherited monogenic form of diabetes associated with mutations in the carboxyl ester lipase (CEL) gene expressed by pancreatic acinar cells. MODY8 patients develop childhood-onset exocrine pancreas dysfunction followed by diabetes during adulthood. However, it is unclear how CEL mutations cause diabetes. In the present study, we report the transfer of CEL proteins from acinar cells to β-cells as a form of cross-talk between exocrine and endocrine cells. Human β-cells show a relatively higher propensity for internalizing the mutant versus the wild-type CEL protein. After internalization, the mutant protein forms stable intracellular aggregates leading to β-cell secretory dysfunction. Analysis of pancreas sections from a MODY8 patient reveals the presence of CEL protein in the few extant β-cells. The present study provides compelling evidence for the mechanism by which a mutant gene expressed specifically in acinar cells promotes dysfunction and loss of β-cells to cause diabetes.

Multivariate alterations in insula - Medial prefrontal cortex linked to genetics in 12q24 in schizophrenia

The direct effect of genetic variations on clinical phenotypes within schizophrenia (SZ) remains elusive. We examined the previously identified association of reduced gray matter concentration in the insula - medial prefrontal cortex and a quantitative trait locus located in 12q24 in a SZ dataset. The main analysis was performed on 1461 SNPs and 830 participants. The highest contributing SNPs were localized in five genes including TMEM119, which encodes a microglial marker, that is associated with neuroinflammation and Alzheimer's disease. The gene set in 12q4 may partially explain brain alterations in SZ, but they may also relate to other psychiatric and developmental disorders.

Arginase 2 and Polyamines in Human Pancreatic Beta Cells: Possible Role in the Pathogenesis of Type 2 Diabetes

Arginase 2 (ARG2) is a manganese metalloenzyme involved in several tissue specific processes, from physiology to pathophysiology. It is variably expressed in extra-hepatic tissues and is located in the mitochondria. In human pancreatic beta cells, ARG2 is downregulated in type 2 diabetes. The enzyme regulates the synthesis of polyamines, that are involved in pancreas development and regulation of beta cell function. Here, we discuss several features of ARG2 and polyamines, which can be relevant to the pathophysiology of type 2 diabetes.

Copine 3 "CPNE3" is a novel regulator for insulin secretion and glucose uptake in pancreatic β-cells

Copine 3 (CPNE3) is a calcium-dependent phospholipid-binding protein that has been found to play an essential role in cancer progression and stages. However, its role in pancreatic β-cell function has not been investigated. Therefore, we performed a serial of bioinformatics and functional experiments to explore the potential role of Cpne3 on insulin secretion and β-cell function in human islets and INS-1 (832/13) cells. RNA sequencing and microarray data revealed that CPNE3 is highly expressed in human islets compared to other CPNE genes. In addition, expression of CPNE3 was inversely correlated with HbA1c and reduced in human islets from hyperglycemic donors. Silencing of Cpne3 in INS-1 cells impaired glucose-stimulated insulin secretion (GSIS), insulin content and glucose uptake efficiency without affecting cell viability or inducing apoptosis. Moreover, mRNA and protein expression of the key regulators in glucose sensing and insulin secretion (Insulin, GLUT2, NeuroD1, and INSR) were downregulated in Cpne3-silenced cells. Taken together, data from the present study provides a new understanding of the role of CPNE3 in maintaining normal β-cell function, which might contribute to developing a novel target for future management of type 2 diabetes therapy.

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.

GNG5 is a novel oncogene associated with cell migration, proliferation, and poor prognosis in glioma

Background

Although many biomarkers have been reported for detecting glioma, the prognosis for the disease remains poor, and therefore, new biomarkers need to be identified. GNG5, which is part of the G-protein family, has been associated with different malignant tumors, though the role of GNG5 in glioma has not been studied. Therefore, we aimed to identify the relationship between GNG5 and glioma prognosis and identify a new biomarker for the diagnosis and treatment of gliomas.

Methods

We used data on more than a thousand gliomas from multiple databases and clinical data to determine the expression of GNG5 in glioma. Based on clinical data and CGGA database, we identified the correlation between GNG5 and multiple molecular and clinical features and prognosis using various analytical methods. Co-expression analysis and GSEA were performed to detect GNG5-related genes in glioma and possible signaling pathways involved. ESTIMATE, ssGSEA, and TIMER were used to detect the relationship between GNG5 and the immune microenvironment. Functional experiments were performed to explore the function of GNG5 in glioma cells.

Results

GNG5 is highly expressed in gliomas, and its expression level is positively correlated with pathological grade, histological type, age, and tumor recurrence and negatively correlated with isocitrate dehydrogenase mutation, 1p/19 co-deletion, and chemotherapy. Moreover, GNG5 as an independent risk factor was negatively correlated with the overall survival time. GSEA revealed the potential signaling pathways involved in GNG5 function in gliomas, including cell adhesion molecules signaling pathway. The ssGSEA, ESTIMATE, and TIMER based analysis indicated a correlation between GNG5 expression and various immune cells in glioma. In vivo and in vitro experiments showed that GNG5 could participate in glioma cell proliferation and migration.

Conclusions

Based on the large data platform and the use of different databases to corroborate results obtained using various datasets, as well as in vitro and in vivo experiments, our study reveals for the first time that GNG5, as an oncogene, is overexpressed in gliomas and can inhibit the proliferation and migration of glioma cells and lead to poor prognosis of patients. Thus, GNG5 is a potential novel biomarker for the clinical diagnosis and treatment of gliomas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-01935-7.

The MafA-target gene PPP1R1A regulates GLP1R-mediated amplification of glucose-stimulated insulin secretion in β-cells

The amplification of glucose-stimulated insulin secretion (GSIS) through incretin signaling is critical for maintaining physiological glucose levels. Incretins, like glucagon-like peptide 1 (GLP1), are a target of type 2 diabetes drugs aiming to enhance insulin secretion. Here we show that the protein phosphatase 1 inhibitor protein 1A (PPP1R1A), is expressed in β-cells and that its expression is reduced in dysfunctional β-cells lacking MafA and upon acute MafA knock down. MafA is a central regulator of GSIS and β-cell function. We observed a strong correlation of MAFA and PPP1R1A mRNA levels in human islets, moreover, PPP1R1A mRNA levels were reduced in type 2 diabetic islets and positively correlated with GLP1-mediated GSIS amplification. PPP1R1A silencing in INS1 (832/13) β-cells impaired GSIS amplification, PKA-target protein phosphorylation, mitochondrial coupling efficiency and also the expression of critical β-cell marker genes like MafA, Pdx1, NeuroD1 and Pax6. Our results demonstrate that the β-cell transcription factor MafA is required for PPP1R1A expression and that reduced β-cell PPP1R1A levels impaired β-cell function and contributed to β-cell dedifferentiation during type 2 diabetes. Loss of PPP1R1A in type 2 diabetic β-cells may explains the unresponsiveness of type 2 diabetic patients to GLP1R-based treatments.

Integrative transcriptomic analysis of pancreatic islets from patients with prediabetes/type 2 diabetes

AIM

To identify new transcriptomic alterations in pancreatic islets associated with metabolic dysfunctions in people with prediabetes (PD)/type 2 diabetes (T2D).

MATERIALS AND METHODS

We collected information from public data repositories T2D related microarray datasets from pancreatic islets. We identified Differential Expressed Genes (DEGs) in non-diabetic (ND) vs people with T2D in each study. To identify relevant DEGs in T2D, we selected those that varied consistently in the different studies for further meta-analysis and functional enrichment analysis. DEGs were also evaluated at the PD stage.

RESULTS

A total of seven microarray datasets were collected and analysed to find the DEGs in each study and meta-analysis was performed with 245 ND and 96 T2D cases. We identified 55 transcriptional alterations potentially associated with specific metabolic dysfunctions in T2D. Meta-analysis showed that 87% of transcripts identified as DEGs (48 out of 55) were confirmed as having statistically significant up- or down-modulation in T2D compared to ND. Notably, nine of these DEGs have not been previously reported as dysregulated in pancreatic islets from people with T2D. Consistently, the most significantly enriched pathways were related to the metabolism and/or development/maintenance of β-cells. Eighteen of the 48 selected DEGs (38%) showed an altered expression in islets from people with PD.

CONCLUSIONS

These results provide new evidence to interpret the pathogenesis of T2D and the transition from PD to T2D. Further studies are necessary to validate its potential use for the development/implementation of efficient new strategies for the prevention, diagnosis/prognosis and treatment of T2D.

Phospholipase C families: Common themes and versatility in physiology and pathology

Phosphoinositide-specific phospholipase Cs (PLCs) are expressed in all mammalian cells and play critical roles in signal transduction. To obtain a comprehensive understanding of these enzymes in physiology and pathology, a detailed structural, biochemical, cell biological and genetic information is required. In this review, we cover all these aspects to summarize current knowledge of the entire superfamily. The families of PLCs have expanded from 13 enzymes to 16 with the identification of the atypical PLCs in the human genome. Recent structural insights highlight the common themes that cover not only the substrate catalysis but also the mechanisms of activation. This involves the release of autoinhibitory interactions that, in the absence of stimulation, maintain classical PLC enzymes in their inactive forms. Studies of individual PLCs provide a rich repertoire of PLC function in different physiologies. Furthermore, the genetic studies discovered numerous mutated and rare variants of PLC enzymes and their link to human disease development, greatly expanding our understanding of their roles in diverse pathologies. Notably, substantial evidence now supports involvement of different PLC isoforms in the development of specific cancer types, immune disorders and neurodegeneration. These advances will stimulate the generation of new drugs that target PLC enzymes, and will therefore open new possibilities for treatment of a number of diseases where current therapies remain ineffective.

The making of insulin in health and disease

The discovery of insulin in 1921 has been one of greatest scientific achievements of the 20th century. Since then, the availability of insulin has shifted the focus of diabetes treatment from trying to keep patients alive to saving and improving the life of millions. Throughout this time, basic and clinical research has advanced our understanding of insulin synthesis and action, both in healthy and pathological conditions. Yet, multiple aspects of insulin production remain unknown. In this review, we focus on the most recent findings on insulin synthesis, highlighting their relevance in diabetes. Graphical abstract.

Application of Single-Cell RNA Sequencing in Pancreatic Cancer and the Endocrine Pancreas

The pancreas is a complex organ composed of an endocrine (pancreatic islets) and an exocrine portion. This mixed cell population has resulted in an implacable barrier to exploring the detailed mechanism and function of each cell type in previous investigative approaches. In recent years, single-cell RNA sequencing (scRNA-seq) technologies have provided in-depth analysis of cell heterogeneity in the pancreas and in pancreatic cancer. It is especially effective in cell-type-specific molecule identification and detection of interactions between cancer cells and the stromal microenvironment. To date, numerous reports have described the application of scRNA-seq in studies of pancreatic islets and pancreatic cancer. The aim of this paper is to review recent advances of pancreatic transcriptomics and pancreatic cancer using scRNA-seq strategies.

mRNA Processing: An Emerging Frontier in the Regulation of Pancreatic β Cell Function

Robust endocrine cell function, particularly β cell function, is required to maintain blood glucose homeostasis. Diabetes can result from the loss or dysfunction of β cells. Despite decades of clinical and basic research, the precise regulation of β cell function and pathogenesis in diabetes remains incompletely understood. In this review, we highlight RNA processing of mRNAs as a rapidly emerging mechanism regulating β cell function and survival. RNA-binding proteins (RBPs) and RNA modifications are primed to be the next frontier to explain many of the poorly understood molecular processes that regulate β cell formation and function, and provide an exciting potential for the development of novel therapeutics. Here we outline the current understanding of β cell specific functions of several characterized RBPs, alternative splicing events, and transcriptome wide changes in RNA methylation. We also highlight several RBPs that are dysregulated in both Type 1 and Type 2 diabetes, and discuss remaining knowledge gaps in the field.

Expression Profile of SARS-CoV-2 Host Receptors in Human Pancreatic Islets Revealed Upregulation of ACE2 in Diabetic Donors

Cellular entry of SARS-CoV-2 is thought to occur through the binding of viral spike S1 protein to ACE2. The entry process involves priming of the S protein by TMPRSS2 and ADAM17, which collectively mediate the binding and promote ACE2 shedding. In this study, microarray and RNA-sequencing (RNA-seq) expression data were utilized to profile the expression pattern of ACE2, ADAM17, and TMPRSS2 in type 2 diabetic (T2D) and non-diabetic human pancreatic islets. Our data show that pancreatic islets express all three receptors irrespective of diabetes status. The expression of ACE2 was significantly increased in diabetic/hyperglycemic islets compared to non-diabetic/normoglycemic. Islets from female donors showed higher ACE2 expression compared to males; the expression of ADAM17 and TMPRSS2 was not affected by gender. The expression of the three receptors was statistically similar in young (≤40 years old) versus old (≥60 years old) donors. Obese (BMI > 30) donors have significantly higher expression levels of ADAM17 and TMPRSS2 relative to those from non-obese donors (BMI < 25). TMPRSS2 expression correlated positively with HbA1c and negatively with age, while ADAM17 and TMPRSS2 correlated positively with BMI. The expression of the three receptors was statistically similar in muscle and subcutaneous adipose tissues obtained from diabetic and nondiabetic donors. Lastly, ACE2 expression was higher in sorted pancreatic β-cell relative to other endocrine cells. In conclusion, ACE2 expression is increased in diabetic human islets. More studies are required to investigate whether variations of ACE2 expression could explain the severity of COVID-19 infection-related symptoms between diabetics and non-diabetic patients.

Epigenetic regulation of insulin action and secretion - role in the pathogenesis of type 2 diabetes

The prevalence of type 2 diabetes (T2D) is rapidly increasing worldwide. Obesity, physical inactivity and ageing increase the risk of T2D. Epigenetic modifications can change due to environmental exposures and may thereby predispose to disease. This review aims at summarizing recent advances in epigenetics related to T2D, with a special focus on impaired insulin action and secretion in humans. There will be an emphasis on analyses in human tissues; both from T2D case-control cohorts and intervention studies. Current data support an important role for epigenetics in the pathogenesis of T2D. Numerous studies have found differential DNA methylation and gene expression in skeletal muscle, adipose tissue, the liver and pancreatic islets from subjects with T2D compared with nondiabetic controls. For example, PDX1 has increased DNA methylation and decreased expression in pancreatic islets from patients with T2D compared with nondiabetic controls. Nongenetic risk factors for T2D such as ageing, unhealthy diets and physical activity do also impact the epigenome in human tissues. Interestingly, physical activity altered DNA methylation of candidate genes for T2D such as THADA in muscle and FTO, KCNQ1 and TCF7L2 in adipose tissue. There is also a strong interaction between genetic and epigenetic factors that together seem to affect T2D. mQTL studies in human adipose tissue and pancreatic islets showed that SNPs associated with DNA methylation levels in numerous sites. Several of these SNPs are also associated with T2D. Recent data also support that DNA methylation of some sites in blood may be developed into biomarkers that predict T2D since methylation of, for example TXNIP, ABCG1 and SREBF1 associated with future T2D. Future studies should use this information for development of new therapies and biomarkers and thereby improve prediction, prevention and treatment of T2D and its complications.

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.

Genetic Variants of the PLCXD3 Gene Are Associated with Risk of Metabolic Syndrome in the Emirati Population

Phosphatidylinositol-specific phospholipase C X domain 3 (PLCXD3) has been shown to influence pancreatic β-cell function by disrupting insulin signaling. Herein, we investigated two genetic variants in the PLCXD3 gene in relation to type 2 diabetes (T2D) or metabolic syndrome (MetS) in the Emirati population. In total, 556 adult Emirati individuals (306 T2D and 256 controls) were genotyped for two PLCXD3 variants (rs319013 and rs9292806) using TaqMan genotyping assays. The frequency distribution of minor homozygous CC genotype of rs9292806 and GG genotype of rs319013 were significantly higher in subjects with MetS compared to Non-MetS (p < 0.01). The minor homozygous rs9292806-CC and rs319013-GG genotypes were significantly associated with increased risk of MetS (adj. OR 2.92; 95% CI 1.61–5.3; p < 0.001) (adj. OR 2.62; 95% CI 1.42–4.83; p = 0.002), respectively. However, no associations were detected with T2D. In healthy participants, the homozygous minor genotypes of both rs9292806 and rs319013 were significantly higher fasting glucose (adj. p < 0.005), HbA1c (adj. p < 0.005) and lower HDL-cholesterol (adj. p < 0.05) levels. Data from T2D Knowledge Portal database disclosed a nominal association of rs319013 and rs9292806 with T2D and components of MetS. Bioinformatics prediction analysis showed a deleterious effect of rs9292806 on the regulatory regions of PLCXD3. In conclusion, this study identifies rs319013 and rs9292806 variants of PLCXD3 as additional risk factors for MetS in the Emirati population.

Gene expression models based on transcription factor binding events confer insight into functional cis-regulatory variants

Motivation

Deciphering the functional roles of cis-regulatory variants is a critical challenge in genome analysis and interpretation. It has been hypothesized that altered transcription factor (TF) binding events are a central mechanism by which cis-regulatory variants impact gene expression levels. However, we lack a computational framework to understand and quantify such mechanistic contributions.

Results

We present TF2Exp, a gene-based framework to predict the impact of altered TF-binding events on gene expression levels. Using data from lymphoblastoid cell lines, TF2Exp models were applied successfully to predict the expression levels of 3196 genes. Alterations within DNase I hypersensitive, CTCF-bound and tissue-specific TF-bound regions were the greatest contributing features to the models. TF2Exp models performed as well as models based on common variants, both in cross-validation and external validation. Combining TF alteration and common variant features can further improve model performance. Unlike variant-based models, TF2Exp models have the unique advantage to evaluate the functional impact of variants in linkage disequilibrium and uncommon variants. We find that adding TF-binding events altered only by uncommon variants could increase the number of predictable genes (R² > 0.05). Taken together, TF2Exp represents a key step towards interpreting the functional roles of cis-regulatory variants in the human genome.

Availability and implementation

The code and model training results are publicly available at https://github.com/wqshi/TF2Exp.

Supplementary information

Supplementary data are available at Bioinformatics online.

Cell-free long non-coding RNAs (LY86-AS1 & HCG27_201and GAS5) as biomarkers for pre-diabetes and type 2 DM in Egypt

Background

Increasing interest has been focused on lncRNAs as potential markers in the pathogenesis and progression of numerous diseases.

Aim

We aimed to investigate the expression pattern and role of cell-free lncRNAs (GAS5, HCG27_201 and LY86-AS1) in pre-diabetic, diabetic and T2DM groups.

Subjects & methods

Quantification of the expression level of cell-free lncRNAs (GAS5, HCG27_201 and LY86-AS1) was performed by real-time PCR in 210 individuals classified in diabetic (T2DM), pre-diabetic and control groups.

Results

Significant differences were observed in the relative expression level of lncRNAs (GAS5, LY86-AS1 and HCG27_201) among the three studied groups. The LncRNA expression levels decreased gradually from the control to the pre-diabetic group and reached the lowest values in the T2DM group. The A receiver operating characteristic curve (ROC) was applied to identify a cut-off value for each of the three genes among our groups. The three lncRNAs showed promising results in discriminating between the diabetic patients and controls, with HCG27_201 gene expression having the best performance. Furthermore, lncRNA expression was able to predict the future development of DM in the pre-diabetics because ROC analysis among diabetics and pre-diabetics revealed considerable results. GAS5 gene expression showed the best performance. Additionally, HCG27_201 expression was the most valuable biomarker for differentiating between pre-diabetics and controls and presented a sensitivity of 91% and specificity of 64%.

Conclusions

We concluded that cell free lncRNAs (GAS5, LY86-AS1 and HCG27_201) could be considered promising diagnostic and predictive biomarkers for DM and that HCG27_201 could act as a potential diagnostic biomarker for pre-diabetes.

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lncRNAs are involved in T2DM pathological process.

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lncRNA showed ability to predict development of DM.

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GAS5, LY86-AS1 and HCG27_201 could be considered as diagnostic biomarkers for DM.

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The three studied lncRNA could also be considered as predictive biomarkers for DM.

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HCG27_201 could act as a potential diagnostic biomarker for pre-diabetes.

CHL1 promotes insulin secretion and negatively regulates the proliferation of pancreatic β cells

Cell adhesion molecule L1-like protein (CHL1) is a member of neural recognition molecules of immunoglobulin superfamily primarily expressing in the nervous system. CHL1 regulates neuronal migration, axonal growth, and dendritic projection. Downregulation of CHL1 has been reported in β cells of patients with type 2 diabetes (T2DM). However, the detailed role of CHL1 in β cells has not been characterized. In this study, Real-Time PCR and Western blot were applied to investigate the tissue/cell distribution and expression of CHL1. Gain- or loss-of function studies were conducted in MIN6 cells to determine the effects of CHL1 on cell proliferation, apoptosis, cell cycle, and insulin secretion. Following silencing of CHL1 in MIN6 cells (si-CHL1), insulin secretion and the number of insulin secretary granules <50 nm from the cell membrane decreased in response to 20 mM glucose. Besides, silencing of CHL1 induced cell proliferation, reduced apoptosis, and prolonged S phase and shortened G1 phase of the cell cycle, contrary to overexpressing of CHL1. The inhibitor of ERK1/2MAPK eliminated the effect of CHL1 deficiency on the proliferation of MIN6 cells. In addition, high-fat diet could result in increased islet volume and β cell proliferation, decreased CHL1 expression and activation of ERK pathway in mice islets. Consequently, CHL1 expression was decreased in islets of high-fat induced mice, which resulted in cell proliferation via ERK pathway and regulation of the cell cycle through p53 pathway. These mechanisms may contribute to pancreatic β cell compensatory hyperplasia in obesity-induced pre-diabetes.

MicroRNA-675-3p regulates IL-1β-stimulated human chondrocyte apoptosis and cartilage degradation by targeting GNG5

Growing evidence has indicated that microRNAs (miRNAs) are modulators of osteoarthritis (OA) development and progression. In this study, we first evaluated the anti-apoptosis and chondroprotective effects of microRNA-675-3p (miR-675-3p) on interleukin-1β (IL-1β)-stimulated human chondrocytes. The overexpression of miR-675-3p inhibited apoptosis and cartilage matrix degradation and promoted cell proliferation in human chondrocytes. Target gene prediction and luciferase reporter assays suggested that G-protein subunit γ 5 (GNG5) may be the target gene of miR-675-3p. The overexpression of miR-675-3p inhibited IL-1β-stimulated chondrocyte apoptosis, and this effect was reversed by the overexpression of GNG5. Finally, we used bioinformatic tools and biological methods to show that the long noncoding RNA X-inactive specific transcript (lncRNA XIST) could bind to miR-675-3p, which affects the expression of GNG5 mRNA. Our findings may substantiate miR-675-3p as a new treatment for OA.

Tissue specific regulation of transcription in endometrium and association with disease

STUDY QUESTION

Are genetic effects on endometrial gene expression tissue specific and/or associated with reproductive traits and diseases?

SUMMARY ANSWER

Analyses of RNA-sequence data and individual genotype data from the endometrium identified novel and disease associated, genetic mechanisms regulating gene expression in the endometrium and showed evidence that these mechanisms are shared across biologically similar tissues.

WHAT IS KNOWN ALREADY

The endometrium is a complex tissue vital for female reproduction and is a hypothesized source of cells initiating endometriosis. Understanding genetic regulation specific to, and shared between, tissue types can aid the identification of genes involved in complex genetic diseases.

STUDY DESIGN, SIZE, DURATION

RNA-sequence and genotype data from 206 individuals was analysed and results were compared with large publicly available datasets.

PARTICIPANTS/MATERIALS, SETTING, METHODS

RNA-sequencing and genotype data from 206 endometrial samples was used to identify the influence of genetic variants on gene expression, via expression quantitative trait loci (eQTL) analysis and to compare these endometrial eQTLs with those in other tissues. To investigate the association between endometrial gene expression regulation and reproductive traits and diseases, we conducted a tissue enrichment analysis, transcriptome-wide association study (TWAS) and summary data-based Mendelian randomisation (SMR) analyses. Transcriptomic data was used to test differential gene expression between women with and without endometriosis.

MAIN RESULTS AND THE ROLE OF CHANCE

A tissue enrichment analysis with endometriosis genome-wide association study summary statistics showed that genes surrounding endometriosis risk loci were significantly enriched in reproductive tissues. A total of 444 sentinel cis-eQTLs (P < 2.57 × 10-9) and 30 trans-eQTLs (P < 4.65 × 10-13) were detected, including 327 novel cis-eQTLs in endometrium. A large proportion (85%) of endometrial eQTLs are present in other tissues. Genetic effects on endometrial gene expression were highly correlated with the genetic effects on reproductive (e.g. uterus, ovary) and digestive tissues (e.g. salivary gland, stomach), supporting a shared genetic regulation of gene expression in biologically similar tissues. The TWAS analysis indicated that gene expression at 39 loci is associated with endometriosis, including five known endometriosis risk loci. SMR analyses identified potential target genes pleiotropically or causally associated with reproductive traits and diseases including endometriosis. However, without taking account of genetic variants, a direct comparison between women with and without endometriosis showed no significant difference in endometrial gene expression.

LARGE SCALE DATA

The eQTL dataset generated in this study is available at http://reproductivegenomics.com.au/shiny/endo_eqtl_rna/. Additional datasets supporting the conclusions of this article are included within the article and the supplementary information files, or are available on reasonable request.

LIMITATIONS, REASONS FOR CAUTION

Data are derived from fresh tissue samples and expression levels are an average of expression from different cell types within the endometrium. Subtle cell-specifc expression changes may not be detected and differences in cell composition between samples and across the menstrual cycle will contribute to sample variability. Power to detect tissue specific eQTLs and differences between women with and without endometriosis was limited by the sample size in this study. The statistical approaches used in this study identify the likely gene targets for specific genetic risk factors, but not the functional mechanism by which changes in gene expression may influence disease risk.

WIDER IMPLICATIONS OF THE FINDINGS

Our results identify novel genetic variants that regulate gene expression in endometrium and the majority of these are shared across tissues. This allows analysis with large publicly available datasets to identify targets for female reproductive traits and diseases. Much larger studies will be required to identify genetic regulation of gene expression that will be specific to endometrium.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by the National Health and Medical Research Council (NHMRC) under project grants GNT1026033, GNT1049472, GNT1046880, GNT1050208, GNT1105321, GNT1083405 and GNT1107258. G.W.M is supported by a NHMRC Fellowship (GNT1078399). J.Y is supported by an ARC Fellowship (FT180100186). There are no competing interests.

Identification of Hub Genes in Type 2 Diabetes Mellitus Using Bioinformatics Analysis

BACKGROUND

Type 2 diabetes mellitus (T2DM) is one of the most common chronic diseases in the world with complicated pathogenesis. This study aimed to identify differentially expressed genes (DEGs) and molecular pathways in T2DM using bioinformatics analysis.

MATERIALS AND METHODS

To explore potential therapeutic targets for T2DM, we analyzed three microarray datasets (GSE50397, GSE38642, and GSE44035) acquired from the Gene Expression Omnibus (GEO) database. DEGs between T2DM islet and normal islet were picked out by the GEO2R tool and Venn diagram software. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) to identify the pathways and functional annotation of DEGs. Then, protein-protein interaction (PPI) of these DEGs was visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes/Proteins (STRING).

RESULTS

In total, we identified 36 DEGs in the three datasets, including 32 up-regulated genes and four down-regulated genes. The improved functions and pathways of the DEGs enriched in cytokine-cytokine receptor interaction, pathways in cancer, PI3K-Akt signaling pathway, and Rheumatoid arthritis. Among them, ten hub genes with a high degree of connectivity were selected. Furthermore, via the re-analysis of DAVID, four genes (IL6, MMP3, MMP1, and IL11) were significantly enriched in the Rheumatoid arthritis pathway.

CONCLUSION

Our study, based on the GEO database, identified four significant up-regulated DEGs and provided novel targets for diagnosis and treatment of T2DM.

Orphan G-protein coupled receptor 183 (GPR183) potentiates insulin secretion and prevents glucotoxicity-induced β-cell dysfunction

The expression and functional impact of most orphan G-protein coupled receptors (GPCRs) in β-cell is not fully understood. Microarray expression indicated that 36 orphan GPCRs are restricted in human islets, while 55 receptors overlapped between human islets and INS-1 cells. GPR183 showed higher expression in diabetic compared to non-diabetic human islets. GPR183 expression co-localized with β-cells while it was lacking in α-cells in human islets. The GPR183 agonist (7α-25-DHC) potentiated insulin secretion and protected against glucotoxicity-induced β-cell damage in human islets. Silencing of GPR183 in INS-1 cells decreased the expression of proinsulin genes, Pdx1, Mafa and impaired insulin secretion with a concomitant decrease in cAMP generation. Cultured INS-1 cells with 7α-25-DHC were associated with increased proliferation and expression of GPR183, INS2, PDX1, NeuroD, and INSR. In conclusion, the beneficial impact of GPR183 activation on β-cell function makes it a potential therapeutic target to prevent or reverse β-cell dysfunction.

Whole Genome Resequencing Reveals Selection Signatures Associated With Important Traits in Ethiopian Indigenous Goat Populations

Ethiopia is considered as the main gateway for the introduction of livestock species, including goat, to the African continent. Ethiopian goats are characterized by their unique adaptive ability, and different physical characteristics in terms of morphology, body size, coat colors, and other important traits. The comparative population genomic analysis provides useful genomic information associated with important traits. Whole-genome resequencing of 44 Ethiopian indigenous goats produced 16 million single-nucleotide polymorphisms (SNPs) as well as 123,577 insertions and deletions. Specifically, 11,137,576, 10,760,581, 10,833,847, 12,229,657 and 10,749,996 putative SNPs were detected in Abergelle, Afar, Begait, Central Highland and Meafure goat populations, respectively. In this study, we used population differentiation (F_ST) and pooled heterozygosity (H_P) Cbased approaches. From the F_ST analysis, we identified 480 outlier windows. The H_P approach detected 108 and 205 outlier windows for Abergelle, and Begait, respectively. About 11 and 5 genes under selective signals were common for both approaches that were associated with important traits. After genome annotation, we found 41 Gene ontology (GO) terms (12 in biological processes, 8 in cellular components and 11 in the molecular function) and 10 Kyoto Encyclopedia of Genes and Genomes pathways. Several of the candidate genes are involved in the reproduction, body weight, fatty acids, and disease related traits. Our investigation contributes to deliver valuable genetic information and paves the way to design conservation strategy, breed management, genetic improvement, and utilization programs. The genomic resources generated in the study will offer an opportunity for further investigations.

The role of deubiquitinating enzymes in gastric cancer

The epigenetic regulation of gene expression (via DNA methylation, histone modification and microRNA interference) contributes to a variety of diseases, particularly cancer. Protein deubiquitination serves a key role in the mechanism underlying histone modification, and consequently influences tumor development and progression. Improved characterization of the role of ubiquitinating enzymes has led to the identification of numerous deubiquitinating enzymes (DUBs) with various functions. Gastric cancer (GC) is a highly prevalent cancer type that exhibits a high mortality rate. Latest analysis about cancer patient revealed that GC is sixth deadliest cancer type, which frequently occur in male (7.2%) than female (4.1%). Complex associations between DUBs and GC progression have been revealed in multiple studies; however, the molecular mechanism underpinning the metastasis and recurrence of GC is yet to be elucidated. Generally, DUBs were upregulated in gastric cancer. The relation of DUBs and tumor size, classification and staging was observed in GC. Besides, 5-yar survival rate of patients with GC is effeccted by expression level of DUBs. Among the highly expressed DUBs, specifically six DUBs namely UCHs, USPs, OTUs, MJDs, JAMMs and MCPIPs effect on this survival rate. Consequently, the association between GC and DUBs has received increasing attention in recent years. Therefore, in the present review, literature investigating the association between DUBs and GC pathophysiology was analyzed and critically appraised.

Loss of ZnT8 function protects against diabetes by enhanced insulin secretion

A rare loss-of-function allele p.Arg138* in SLC30A8 encoding the zinc transporter 8 (ZnT8), which is enriched in Western Finland, protects against type 2 diabetes (T2D). We recruited relatives of the identified carriers and showed that protection was associated with better insulin secretion due to enhanced glucose responsiveness and proinsulin conversion, particularly when compared with individuals matched for the genotype of a common T2D-risk allele in SLC30A8, p.Arg325. In genome-edited human induced pluripotent stem cell (iPSC)-derived β-like cells, we establish that the p.Arg138* allele results in reduced SLC30A8 expression due to haploinsufficiency. In human β cells, loss of SLC30A8 leads to increased glucose responsiveness and reduced KATP channel function similar to isolated islets from carriers of the T2D-protective allele p.Trp325. These data position ZnT8 as an appealing target for treatment aimed at maintaining insulin secretion capacity in T2D.