Upregulation of insulin mRNA translation upon hyperglycemia in pancreatic islet β-cells involves several RNA-binding proteins. Here, we found that G3BP1, a stress granule marker downregulated in islets of subjects with type 2 diabetes, binds to insulin mRNA in glucose concentration-dependent manner. We show in mouse insulinoma MIN6-K8 cells exposed to fasting glucose levels that G3BP1 and its paralog G3BP2 colocalize to cytosolic condensates with eIF3b, phospho-AMPKαThr172 and Ins1/2 mRNA. Glucose stimulation dissolves G3BP1+/2+ condensates with cytosolic redistribution of their components. The aldolase inhibitor aldometanib prevents the glucose- and pyruvate-induced dissolution of G3BP1+/2+ condensates, increases phospho-AMPKαThr172 levels and reduces those of phospho-mTORSer2448. G3BP1 or G3BP2 depletion precludes condensate assembly. KO of G3BP1 decreases Ins1/2 mRNA abundance and translation as well as proinsulin levels, and impaires glucose-stimulated insulin secretion. Further, other insulin secretagogues such as exendin-4 and palmitate, but not high KCl, prompts the dissolution of G3BP1+/2+ condensates. G3BP1+/2+/Ins mRNA+ condensates are also found in primary mouse and human β-cells. Hence, G3BP1+/2+ condensates represent a conserved glycolysis/aldolase-regulated compartment for the physiological storage and protection of insulin mRNA in resting β-cells.

Porcine circovirus type 2 (PCV2) is the main pathogen causing postweaning multisystemic wasting syndrome, which leads to enormous losses for porcine industry. However, the regulatory mechanism of PCV2 replication in host cells remains not been clarified. Here, pig DNMT3B was identified as be a host regulator associated with PCV2 infection via RNA-seq analysis. We demonstrated that upregulation of DNMT3B expression can effectively inhibit PCV2 replication in PK15 cells. Besides, TMEM37 acts as a key downstream target of DNMT3B in PCV2-infected PK15 cells. TMEM37 knockdown significantly slowed Ca2+ influx, and thus inhibited PCV2 replication. Taken together, DNMT3B is required for the PCV2-based infection regulation in host cells. Our findings indicated that DNMT3B inhibits PCV2 replication via targeting TMEM37 to regulate Ca2+ influx in PK15 cells, which offering a theoretical foundation for the use of this gene as a key biomarker for breeding strategies seeking to improve porcine disease resistance.

Monkeypox (Mpox) is a major global human health threat after COVID-19. Its treatment becomes complicated with type-2 diabetes (T2D). It may happen due to the influence of both disease-causing common host key genes (cHKGs). Therefore, it is necessary to explore both disease-causing cHKGs to reveal their shared pathogenetic mechanisms and candidate drugs as their common treatments without adverse side effect. This study aimed to address these issues. At first, 3 transcriptomics datasets for each of Mpox and 6 T2D datasets were analyzed and found 52 common host differentially expressed genes (cHDEGs) that can separate both T2D and Mpox patients from the control samples. Then top-ranked six cHDEGs (HSP90AA1, B2M, IGF1R, ALD1HA1, ASS1, and HADHA) were detected as the T2D-causing cHKGs that are associated with the complexity of Mpox through the protein-protein interaction network analysis. Then common pathogenetic processes between T2D and Mpox were disclosed by cHKG-set enrichment analysis with biological processes, molecular functions, cellular components and Kyoto Encyclopedia of Genes and Genomes pathways, and regulatory network analysis with transcription factors and microRNAs. Finally, cHKG-guided top-ranked three drug molecules (tecovirimat, vindoline, and brincidofovir) were recommended as the repurposable common therapeutic agents for both Mpox and T2D by molecular docking. The absorption, distribution, metabolism, excretion, and toxicity and drug-likeness analysis of these drug molecules indicated their good pharmacokinetics properties. The 100-ns molecular dynamics simulation results (root mean square deviation, root mean square fluctuation, and molecular mechanics generalized born surface area) with the top-ranked three complexes ASS1-tecovirimat, ALDH1A1-vindoline, and B2M-brincidofovir exhibited good pharmacodynamics properties. Therefore, the results provided in this article might be important resources for diagnosis and therapies of Mpox patients who are also suffering from T2D.

The forkhead box O1 (FoxO1), the first discovered member of the FoxO family, is a critical transcription factor predominantly found in insulin-secreting and insulin-sensitive tissues. In the pancreas of adults, FoxO1 expression is restricted to islet β cells. We determined that in human islet microarray datasets, FoxO1 expression is higher than other FoxO transcription factors. Our analyses of three human islet datasets revealed that FoxO1 expression tends to shows a negative correlation with type 2 diabetes and no correlation with body mass index (BMI) between individuals with low levels of HbA1C (or ND, non-diabetic) and high levels of HbA1C (or T2D, type 2 diabetes). However, FoxO1 function is multifaceted and mainly regulated by post-translational modifications including phosphorylation and deacetylation that involved in pancreatic β cell function and insulin sensitivity. This study summarized the molecular mechanisms underlying the role of FoxO1 activity in pancreatic β-cell dysfunction and insulin resistance in T2D. In addition, we collected the clinical trials of FoxO1 inhibitor and agonist in diabetes, and discussed the therapeutic potential of FoxO1 activity in diabetes treatment.

Pancreatic islets maintain glucose homeostasis through coordinated action of their constituent endocrine and affiliate cell types and are central to type 2 diabetes (T2D) genetics and pathophysiology. Our understanding of robust human islet cell type-specific alterations in T2D remains limited. Here, we report comprehensive single cell transcriptome profiling of 245,878 human islet cells from a 48-donor cohort spanning non-diabetic (ND), pre-diabetic (PD), and T2D states, identifying 14 distinct cell types detected in every donor from each glycemic state. Cohort analysis reveals ~25-30% loss of functional beta cell mass in T2D vs. ND or PD donors resulting from (1) reduced total beta cell numbers/proportions and (2) reciprocal loss of 'high function' and gain of senescent β -cell subpopulations. We identify in T2D β -cells 511 differentially expressed genes (DEGs), including new (66.5%) and validated genes (e.g., FXYD2, SLC2A2, SYT1), and significant neuronal transmission and vitamin A metabolism pathway alterations. Importantly, we demonstrate newly identified DEG roles in human β -cell viability and/or insulin secretion and link 47 DEGs to diabetes-relevant phenotypes in knockout mice, implicating them as potential causal islet dysfunction genes. Additionally, we nominate as candidate T2D causal genes and therapeutic targets 27 DEGs for which T2D genetic risk variants (GWAS SNPs) and pathophysiology (T2D vs. ND) exert concordant expression effects. We provide this freely accessible atlas for data exploration, analysis, and hypothesis testing. Together, this study provides new genomic resources for and insights into T2D pathophysiology and human islet dysfunction.

Type 2 diabetes (T2D) has become a significant global health threat, yet its precise causes and mechanisms remain unclear. This study aims to identify gene expression patterns specific to T2D pancreatic islet cells and to explore the potential role of pancreatic stellate cells (PSCs) in T2D progression through regulatory networks involving lncRNA-mRNA interactions.

In this study, we screened for upregulated genes in T2D pancreatic islet samples using bulk sequencing (bulkseq) datasets and mapped these gene expression profiles onto three T2D single-cell RNA sequencing (scRNAseq) datasets. The identified T2D-specific gene features were further validated in an additional T2D scRNAseq dataset, a T1D scRNAseq dataset, and a T2D bulkseq dataset. To investigate regulatory networks, we analyzed the potential lncRNA-mRNA interactions within T2D peripheral blood mononuclear cell (PBMC) bulkseq data.

Our analysis identified a specific gene panel-COL1A2, VCAN, and SULF1-that was consistently upregulated in T2D pancreatic islet samples. Expression of this gene panel was strongly associated with the activation of pancreatic stellate cells (PSCs), suggesting a unique T2D-specific signature characterized by COL1A2hi/VCANhi/SULF1hi PSCs. This signature was exclusive to T2D and was not observed in Type 1 diabetes (T1D) samples, indicating a distinct role for activated PSCs in T2D progression. Furthermore, we identified six long non-coding RNAs (lncRNAs) that potentially interact with the COL1A2hi/VCANhi/SULF1hi PSCs. These lncRNAs were mapped to a lncRNA-mRNA network, suggesting they may modulate immune responses and potentially reshape the immune microenvironment in T2D.

Our findings highlight the potential immune-regulatory role of PSCs in T2D and suggest that PSC-related lncRNA-mRNA networks could serve as novel therapeutic targets for T2D treatment. This research provides insights into PSCs as a modulator in T2D progression, paving the way for innovative treatment strategies.

Proinsulin translation and folding is crucial for glucose homeostasis. However, islet β-cell control of Proinsulin translation remains incompletely understood. Here, we identify OSGEP, an enzyme responsible for t6A37 modification of tRNANNU that tunes glucose metabolism in β-cells. Global Osgep deletion causes glucose intolerance, while β-cell-specific deletion induces hyperglycemia and glucose intolerance due to impaired insulin activity. Transcriptomics and proteomics reveal activation of the unfolded protein response (UPR) and apoptosis signaling pathways in Osgep-deficient islets, linked to an increase in misfolded Proinsulin from reduced t6A37 modification. Osgep overexpression in pancreas rescues insulin secretion and mitigates diabetes in high-fat diet mice. Osgep enhances translational fidelity and alleviates UPR signaling, highlighting its potential as a therapeutic target for diabetes. Individuals carrying the C allele at rs74512655, which promotes OSGEP transcription, may show reduced susceptibility to T2DM. These findings show OSGEP is essential for islet β-cells and a potential diabetes therapy target.

Glucose-stimulated insulin secretion (GSIS) in pancreatic β-cells is metabolically regulated and progressively diminished during the development of type 2 diabetes (T2D). This dynamic process is tightly coupled with fatty acid metabolism, but the underlying mechanisms remain poorly understood. Fatty acid 2-hydroxylase (FA2H) catalyzes the conversion of fatty acids to chiral specific (R)-2-hydroxy fatty acids ((R)-2-OHFAs), which influences cell metabolism. However, little is known about its potential coupling with GSIS in pancreatic β cells. Here, we showed that Fa2h knockout decreases plasma membrane localization and protein level of glucose transporter 2 (GLUT2), which is essential for GSIS, thereby controlling blood glucose homeostasis. Conversely, FA2H overexpression increases GLUT2 on the plasma membrane and enhances GSIS. Mechanistically, FA2H suppresses the internalization and trafficking of GLUT2 to the lysosomes for degradation. Overexpression of wild-type FA2H, but not its mutant with impaired hydroxylase activity in the pancreatic β-cells, improves glucose tolerance by promoting insulin secretion. Levels of 2-OHFAs and Fa2h gene expression are lower in high-fat diet-induced obese mouse islets with impaired GSIS. Moreover, lower gene expression of FA2H is observed in a set of human T2D islets when the insulin secretion index is significantly suppressed, indicating the potential involvement of FA2H in regulating mouse and human GSIS. Collectively, our results identified an FA chemical switch to maintain the proper response of GSIS in pancreatic β cells and provided a new perspective on the β-cell failure that triggers T2D.

Endoplasmic reticulum (ER) and inflammatory stress responses contribute to islet dysfunction in type 2 diabetes (T2D). Comprehensive genomic understanding of these human islet stress responses and whether T2D-associated genetic variants modulate them is lacking. Here, comparative transcriptome and epigenome analyses of human islets exposed ex vivo to these stressors revealed 30% of expressed genes and 14% of islet cis-regulatory elements (CREs) as stress responsive, modulated largely in an ER- or cytokine-specific fashion. T2D variants overlapped 86 stress-responsive CREs, including 21 induced by ER stress. We linked the rs6917676-T T2D risk allele to increased islet ER-stress-responsive CRE accessibility and allele-specific β cell nuclear factor binding. MAP3K5, the ER-stress-responsive putative rs6917676 T2D effector gene, promoted stress-induced β cell apoptosis. Supporting its pro-diabetogenic role, MAP3K5 expression correlated inversely with human islet β cell abundance and was elevated in T2D β cells. This study provides genome-wide insights into human islet stress responses and context-specific T2D variant effects.

We postulated that type 2 diabetes (T2D) predisposes patients to exocrine pancreatic diseases through (epi)genetic mechanisms. We explored the methylome (using MethylationEPIC arrays) of the exocrine pancreas in 141 donors, assessing the impact of T2D. An epigenome-wide association study of T2D identified hypermethylation in an enhancer of the pancreatic lipase-related protein 1 (PNLIPRP1) gene, associated with decreased PNLIPRP1 expression. PNLIPRP1 null variants (found in 191,000 participants in the UK Biobank) were associated with elevated glycemia and LDL cholesterol. Mendelian randomization using 2.5M SNP Omni arrays in 111 donors revealed that T2D was causal of PNLIPRP1 hypermethylation, which in turn was causal of LDL cholesterol. Additional AR42J rat exocrine cell analyses demonstrated that Pnliprp1 knockdown induced acinar-to-ductal metaplasia, a known prepancreatic cancer state, and increased cholesterol levels, reversible with statin. This (epi)genetic study suggests a role for PNLIPRP1 in human metabolism and exocrine pancreatic function, with potential implications for pancreatic diseases.

Defective glucose-stimulated insulin secretion (GSIS) and β-cell senescence are hallmarks in diabetes. The mitochondrial enzyme pyruvate carboxylase (PC) has been shown to promote GSIS and β-cell proliferation in the clonal β-cell lines, yet its physiological relevance remains unknown. Here, we provide animal and human data showing a role of PC in protecting β-cells against senescence and maintaining GSIS under different physiological and pathological conditions. β-cell-specific deletion of PC impaired GSIS and induced β-cell senescence in the mouse models under either a standard chow diet or prolonged high-fat diet feeding. Transcriptomic analysis indicated that p53-related senescence and cell cycle arrest are activated in PC-deficient islets. Overexpression of PC inhibited hyperglycemia- and aging-induced p53-related senescence in human and mouse islets as well as INS-1E β-cells, whereas knockdown of PC provoked senescence. Mechanistically, PC interacted with MDM2 to prevent its degradation via the MDM2 binding motif, which in turn restricts the p53-dependent senescent program in β-cells. On the contrary, the regulatory effects of PC on GSIS and the tricarboxylic acid (TCA) anaplerotic flux are p53-independent. We illuminate a function of PC in controlling β-cell senescence through the MDM2-p53 axis.

Primary cilia are sensory organelles present in many cell types, partaking in various signaling processes. Primary cilia of pancreatic beta cells play pivotal roles in paracrine signaling and their dysfunction is linked to diabetes. Yet, the structural basis for their functions is unclear. We present three-dimensional reconstructions of beta cell primary cilia by electron and expansion microscopy. These cilia are spatially confined within deep ciliary pockets or narrow spaces between cells, lack motility components and display an unstructured axoneme organization. Furthermore, we observe a plethora of beta cell cilia-cilia and cilia-cell interactions with other islet and non-islet cells. Most remarkably, we have identified and characterized axo-ciliary synapses between beta cell cilia and the cholinergic islet innervation. These findings highlight the beta cell cilia's role in islet connectivity, pointing at their function in integrating islet intrinsic and extrinsic signals and contribute to understanding their significance in health and diabetes.

Glucose homeostasis is mainly under the control of the pancreatic islet hormones insulin and glucagon, which, respectively, stimulate glucose uptake and utilization by liver, fat, and muscle and glucose production by the liver. The balance between the secretions of these hormones is under the control of blood glucose concentrations. Indeed, pancreatic islet β-cells and α-cells can sense variations in glycemia and respond by an appropriate secretory response. However, the secretory activity of these cells is also under multiple additional metabolic, hormonal, and neuronal signals that combine to ensure the perfect control of glycemia over a lifetime. The central nervous system (CNS), which has an almost absolute requirement for glucose as a source of metabolic energy and thus a vital interest in ensuring that glycemic levels never fall below ∼5 mM, is equipped with populations of neurons responsive to changes in glucose concentrations. These neurons control pancreatic islet cell secretion activity in multiple ways: through both branches of the autonomic nervous system, through the hypothalamic-pituitary-adrenal axis, and by secreting vasopressin (AVP) in the blood at the level of the posterior pituitary. Here, we present the autonomic innervation of the pancreatic islets; the mechanisms of neuron activation by a rise or a fall in glucose concentration; how current viral tracing, chemogenetic, and optogenetic techniques allow integration of specific glucose sensing neurons in defined neuronal circuits that control endocrine pancreas function; and, finally, how genetic screens in mice can untangle the diversity of the hypothalamic mechanisms controlling the response to hypoglycemia.

The rapid rise in the availability and scale of scRNA-seq data needs scalable methods for integrative analysis. Though many methods for data integration have been developed, few focus on understanding the heterogeneous effects of biological conditions across different cell populations in integrative analysis. Our proposed scalable approach, scParser, models the heterogeneous effects from biological conditions, which unveils the key mechanisms by which gene expression contributes to phenotypes. Notably, the extended scParser pinpoints biological processes in cell subpopulations that contribute to disease pathogenesis. scParser achieves favorable performance in cell clustering compared to state-of-the-art methods and has a broad and diverse applicability.

Discerning the mechanisms driving type 2 diabetes (T2D) pathophysiology from genome-wide association studies (GWAS) remains a challenge. To this end, we integrated omics information from 16 multi-tissue and multi-ancestry expression, protein, and metabolite quantitative trait loci (QTL) studies and 46 multi-ancestry GWAS for T2D-related traits with the largest, most ancestrally diverse T2D GWAS to date. Of the 1,289 T2D GWAS index variants, 716 (56%) demonstrated strong evidence of colocalization with a molecular or T2D-related trait, implicating 657 cis-effector genes, 1,691 distal-effector genes, 731 metabolites, and 43 T2D-related traits. We identified 773 of these cis- and distal-effector genes using either expression QTL data from understudied ancestry groups or inclusion of T2D index variants enriched in underrepresented populations, emphasizing the value of increasing population diversity in functional mapping. Linking these variants, genes, metabolites, and traits into a network, we elucidated mechanisms through which T2D-associated variation may impact disease risk. Finally, we showed that drugs targeting effector proteins were enriched in those approved to treat T2D, highlighting the potential of these results to prioritize drug targets for T2D. These results represent a leap in the molecular characterization of T2D-associated genetic variation and will aid in translating genetic findings into novel therapeutic strategies.

Chronic low-grade inflammation of the pancreatic islets is the characteristic of type 2 diabetes (T2D), and some of the immune checkpoints may play important roles in the pancreatic islet inflammation. Thus, we aim to explore the immune checkpoint genes (ICGs) associated with T2D, thereby revealing the role of ICGs in the pathogenesis of T2D based on bioinformatic analyses.

Differentially expressed genes (DEGs) and immune checkpoint genes (ICGs) of islets between T2D and control group were screened from datasets of the Gene Expression Omnibus (GEO). A risk model was built based on the coefficients of ICGs calculated by ridge regression. Functional enrichment analysis and immune cell infiltration estimation were conducted. Correlations between ICGs and hub genes, T2D-related disease genes, insulin secretion genes, and beta cell function-related genes were analyzed. Finally, we conducted RT-PCR to verify the expression of these ICGs.

In total, pancreatic islets from 19 cases of T2D and 84 healthy subjects were included. We identified 458 DEGs. Six significantly upregulated ICGs (CD44, CD47, HAVCR2, SIRPA, TNFSF9, and VTCN1) in T2D were screened out. These ICGs were significantly correlated with several hub genes and T2D-related genes; furthermore, they were correlated with insulin secretion and β cell function-related genes. The analysis of immune infiltration showed that the concentrations of eosinophils, T cells CD4 naive, and T cells regulatory (Tregs) were significantly higher, but CD4 memory resting T cells and monocytes were lower in islets of T2D patients. The infiltrated immune cells in T2D pancreatic islet were associated with these six ICGs. Finally, the expression levels of four ICGs were confirmed by RT-PCR, and three ICGs were validated in another independent dataset.

In conclusion, the identified ICGs may play an important role in T2D. Identification of these differential genes may provide new clues for the diagnosis and treatment of T2D.

Pancreatic β cells play an essential role in the control of systemic glucose homeostasis as they sense blood glucose levels and respond by secreting insulin. Upon stimulating glucose uptake in insulin-sensitive tissues post-prandially, this anabolic hormone restores blood glucose levels to pre-prandial levels. Maintaining physiological glucose levels thus relies on proper β-cell function. To fulfill this highly specialized nutrient sensor role, β cells have evolved a unique genetic program that shapes its distinct cellular metabolism. In this review, the unique genetic and metabolic features of β cells will be outlined, including their alterations in type 2 diabetes (T2D). β cells selectively express a set of genes in a cell type-specific manner; for instance, the glucose activating hexokinase IV enzyme or Glucokinase (GCK), whereas other genes are selectively "disallowed", including lactate dehydrogenase A (LDHA) and monocarboxylate transporter 1 (MCT1). This selective gene program equips β cells with a unique metabolic apparatus to ensure that nutrient metabolism is coupled to appropriate insulin secretion, thereby avoiding hyperglycemia, as well as life-threatening hypoglycemia. Unlike most cell types, β cells exhibit specialized bioenergetic features, including supply-driven rather than demand-driven metabolism and a high basal mitochondrial proton leak respiration. The understanding of these unique genetically programmed metabolic features and their alterations that lead to β-cell dysfunction is crucial for a comprehensive understanding of T2D pathophysiology and the development of innovative therapeutic approaches for T2D patients.

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.

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.

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.

Pancreatic β-cell failure due to a reduction in function and mass has been defined as a primary contributor to the progression of type 2 diabetes (T2D). Reserving insulin-producing β-cells and hence restoring insulin production are gaining attention in translational diabetes research, and β-cell replenishment has been the main focus for diabetes treatment. Significant findings in β-cell proliferation, transdifferentiation, pluripotent stem cell differentiation, and associated small molecules have served as promising strategies to regenerate β-cells. In this review, we summarize current knowledge on the mechanisms implicated in β-cell dynamic processes under physiological and diabetic conditions, in which genetic factors, age-related alterations, metabolic stresses, and compromised identity are critical factors contributing to β-cell failure in T2D. The article also focuses on recent advances in therapeutic strategies for diabetes treatment by promoting β-cell proliferation, inducing non-β-cell transdifferentiation, and reprograming stem cell differentiation. Although a significant challenge remains for each of these strategies, the recognition of the mechanisms responsible for β-cell development and mature endocrine cell plasticity and remarkable advances in the generation of exogenous β-cells from stem cells and single-cell studies pave the way for developing potential approaches to cure 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.

The damage to the endocrine pancreas among patients with diseases of the exocrine pancreas (DP) leads to reduced glycemic deterioration, ultimately resulting in diabetes of the exocrine pancreas (DEP). The present research aims to investigate the mechanism responsible for glycemic deterioration in DP patients, and to identify useful biomarkers, with the ultimate goal of enhancing clinical practice awareness. Gene expression profiles of patients with DP in this study were acquired from the Gene Expression Omnibus database. The original study defines DP patients to belong in one of three categories: non-diabetic (ND), impaired glucose tolerance (IGT) and DEP, which correspond to normoglycemia, early and late glycemic deterioration, respectively. After ensuring quality control, the discovery cohort included 8 ND, 20 IGT, and 12 DEP, while the validation cohort included 27 ND, 15 IGT, and 20 DEP. Gene set enrichment analysis (GSEA) employed differentially expressed genes (DEGs), while immunocyte infiltration was determined using single sample gene set enrichment analysis (ssGSEA). Additionally, correlation analysis was conducted to establish the link between clinical characteristics and immunocyte infiltration. The least absolute shrinkage and selection operator regression and random forest combined to identify biomarkers indicating glycemic deterioration in DP patients. These biomarkers were further validated through independent cohorts and animal experiments. With glycemic deterioration, biological processes in the pancreatic islets such as nutrient metabolism and complex immune responses are disrupted in DP patients. The expression of ACOT4, B2M, and ACKR2 was upregulated, whereas the expression of CACNA1F was downregulated. Immunocyte infiltration in the islet microenvironment showed a significant positive correlation with the age, body mass index (BMI), HbA1c and glycemia at the 2-h of patients. It was a crucial factor in glycemic deterioration. Additionally, B2M demonstrated a significant positive correlation with immunocyte infiltration and clinical features. Quantitative real-time PCR (qRT-PCR) and western blotting confirmed the upregulation in B2M. Immunofluorescent staining suggested the alteration of B2M was mainly in the alpha cells and beta cells. Overall, the study showed that gradually increased immunocyte infiltration was a significant contributor to glycemic deterioration in patients with DP, and it also highlighted B2M as a biomarker.

Type 2 diabetes (T2D) mellitus has emerged as a major global health concern that has accelerated in recent years due to poor diet and lifestyle. Afflicted individuals have high blood glucose levels that stem from the inability of the pancreas to make enough insulin to meet demand. Although medication can help to maintain normal blood glucose levels in individuals with chronic disease, many of these medicines are outdated, have severe side effects, and often become less efficacious over time, necessitating the need for insulin therapy. G protein-coupled receptors (GPCRs) regulate many physiologic processes, including blood glucose levels. In pancreatic β cells, GPCRs regulate β-cell growth, apoptosis, and insulin secretion, which are all critical in maintaining sufficient β-cell mass and insulin output to ensure euglycemia. In recent years, new insights into the signaling of incretin receptors and other GPCRs have underscored the potential of these receptors as desirable targets in the treatment of diabetes. The signaling of these receptors is modulated by GPCR kinases (GRKs) that phosphorylate agonist-activated GPCRs, marking the receptor for arrestin binding and internalization. Interestingly, genome-wide association studies using diabetic patient cohorts link the GRKs and arrestins with T2D. Moreover, recent reports show that GRKs and arrestins expressed in the β cell serve a critical role in the regulation of β-cell function, including β-cell growth and insulin secretion in both GPCR-dependent and -independent pathways. In this review, we describe recent insights into GPCR signaling and the importance of GRK function in modulating β-cell physiology. SIGNIFICANCE STATEMENT: Pancreatic β cells contain a diverse array of G protein-coupled receptors (GPCRs) that have been shown to improve β-cell function and survival, yet only a handful have been successfully targeted in the treatment of diabetes. This review discusses recent advances in our understanding of β-cell GPCR pharmacology and regulation by GPCR kinases while also highlighting the necessity of investigating islet-enriched GPCRs that have largely been unexplored to unveil novel treatment strategies.

Diabetes is a spectrum of metabolic diseases affecting millions of people worldwide. The loss of pancreatic β-cell mass by either autoimmune destruction or apoptosis, in type 1-diabetes (T1D) and type 2-diabetes (T2D), respectively, represents a pathophysiological process leading to insulin deficiency. Therefore, therapeutic strategies focusing on restoring β-cell mass and β-cell insulin secretory capacity may impact disease management. This study took advantage of powerful integrative bioinformatic tools to scrutinize publicly available diabetes-associated gene expression data to unveil novel potential molecular targets associated with β-cell dysfunction.

A comprehensive literature search for human studies on gene expression alterations in the pancreas associated with T1D and T2D was performed. A total of 6 studies were selected for data extraction and for bioinformatic analysis. Pathway enrichment analyses of differentially expressed genes (DEGs) were conducted, together with protein-protein interaction networks and the identification of potential transcription factors (TFs). For noncoding differentially expressed RNAs, microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), which exert regulatory activities associated with diabetes, identifying target genes and pathways regulated by these RNAs is fundamental for establishing a robust regulatory network.

Comparisons of DEGs among the 6 studies showed 59 genes in common among 4 or more studies. Besides alterations in mRNA, it was possible to identify differentially expressed miRNA and lncRNA. Among the top transcription factors (TFs), HIPK2, KLF5, STAT1 and STAT3 emerged as potential regulators of the altered gene expression. Integrated analysis of protein-coding genes, miRNAs, and lncRNAs pointed out several pathways involved in metabolism, cell signaling, the immune system, cell adhesion, and interactions. Interestingly, the GABAergic synapse pathway emerged as the only common pathway to all datasets.

This study demonstrated the power of bioinformatics tools in scrutinizing publicly available gene expression data, thereby revealing potential therapeutic targets like the GABAergic synapse pathway, which holds promise in modulating α-cells transdifferentiation into β-cells.

Over the last two decades, increased availability of human pancreatic tissues has allowed for major expansions in our understanding of islet biology in health and disease. Indeed, studies of fixed and frozen pancreatic tissues, as well as efforts using viable isolated islets obtained from organ donors, have provided significant insights toward our understanding of diabetes. However, the procedures associated with islet isolation result in distressed cells that have been removed from any surrounding influence. The pancreas tissue slice technology was developed as an in situ approach to overcome certain limitations associated with studies on isolated islets or fixed tissue. In this Perspective, we discuss the value of this novel platform and review how pancreas tissue slices, within a short time, have been integrated in numerous studies of rodent and human islet research. We show that pancreas tissue slices allow for investigations in a less perturbed organ tissue environment, ranging from cellular processes, over peri-islet modulations, to tissue interactions. Finally, we discuss the considerations and limitations of this technology in its future applications. We believe the pancreas tissue slices will help bridge the gap between studies on isolated islets and cells to the systemic conditions by providing new insight into physiological and pathophysiological processes at the organ level.

Human pancreas tissue slices represent a novel platform to study human islet biology in close to physiological conditions. Complementary to established technologies, such as isolated islets, single cells, and histological sections, pancreas tissue slices help bridge our understanding of islet physiology and pathophysiology from single cell to intact organ. Diverse sources of viable human pancreas tissue, each with distinct characteristics to be considered, are available to use in tissue slices for the study of diabetes pathogenesis.

Glucagon-like peptide 1 (GLP-1R) and glucose-dependent insulinotropic polypeptide (GIPR) receptors are G-protein-coupled receptors involved in glucose homeostasis. Diabetogenic conditions decrease β-arrestin 2 (ARRB2) levels in human islets. In mouse β cells, ARRB2 dampens insulin secretion by partially uncoupling cyclic AMP (cAMP)/protein kinase A (PKA) signaling at physiological doses of GLP-1, whereas at pharmacological doses, the activation of extracellular signal-related kinase (ERK)/cAMP-responsive element-binding protein (CREB) requires ARRB2. In contrast, GIP-potentiated insulin secretion needs ARRB2 in mouse and human islets. The GIPR-ARRB2 axis is not involved in cAMP/PKA or ERK signaling but does mediate GIP-induced F-actin depolymerization. Finally, the dual GLP-1/GIP agonist tirzepatide does not require ARRB2 for the potentiation of insulin secretion. Thus, ARRB2 plays distinct roles in regulating GLP-1R and GIPR signaling, and we highlight (1) its role in the physiological context and the possible functional consequences of its decreased expression in pathological situations such as diabetes and (2) the importance of assessing the signaling pathways engaged by the agonists (biased/dual) for therapeutic purposes.

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.

The variation in quality between the human islet samples represents a major problem for research, especially when used as control material. The assays assessing the quality of human islets used in research are non-standardized and limited, with many important parameters not being consistently assessed. High-throughput studies aimed at characterizing the diversity and segregation markers among apparently functionally healthy islet preps are thus a requirement. Here, we designed a pilot study to comprehensively identify the diversity of global proteome signatures and the deviation from normal homeostasis in randomly selected human-isolated islet samples.

By using Tandem Mass Tag 16-plex proteomics, we focused on the recurrently observed disparity in the detected insulin abundance between the samples, used it as a segregating parameter, and analyzed the correlated changes in the proteome signature and homeostasis by pathway analysis.

In this pilot study, we showed that insulin protein abundance is a predictor of human islet homeostasis and quality. This parameter is independent of other quality predictors within their acceptable range, thus being able to further stratify islets samples of apparent good quality. Human islets with low amounts of insulin displayed changes in their metabolic and signaling profile, especially in regard to energy homeostasis and cell identity maintenance. We further showed that xenotransplantation into diabetic hosts is not expected to improve the pre-transplantation signature, as it has a negative effect on energy balance, antioxidant activity, and islet cell identity.

Insulin protein abundance predicts significant changes in human islet homeostasis among random samples of apparently good quality.

Intramuscular fat (IMF) content is the major indicator for evaluating chicken meat quality due to its positive correlation with tenderness, juiciness, and flavor. An increasing number of studies are focusing on the functions of microRNAs (miRNAs) in intramuscular adipocyte differentiation. However, little is known about the association of miR-128-3p with intramuscular adipocyte differentiation. Our previous RNA-seq results indicated that miR-128-3p was differentially expressed at different periods in chicken intramuscular adipocytes, revealing a possible association with intramuscular adipogenesis. The purpose of this research was to investigate the biological functions and regulatory mechanism of miR-128-3p in chicken intramuscular adipogenesis.

The results of a series of assays confirmed that miR-128-3p could promote the proliferation and inhibit the differentiation of intramuscular adipocytes. A total of 223 and 1,050 differentially expressed genes (DEGs) were identified in the mimic treatment group and inhibitor treatment group, respectively, compared with the control group. Functional enrichment analysis revealed that the DEGs were involved in lipid metabolism-related pathways, such as the MAPK and TGF-β signaling pathways. Furthermore, target gene prediction analysis showed that miR-128-3p can target many of the DEGs, such as FDPS, GGT5, TMEM37, and ASL2. The luciferase assay results showed that miR-128-3p targeted the 3' UTR of FDPS. The results of subsequent functional assays demonstrated that miR-128-3p acted as an inhibitor of intramuscular adipocyte differentiation by targeting FDPS.

miR-128-3p inhibits chicken intramuscular adipocyte differentiation by downregulating FDPS. Our findings provide a theoretical basis for the study of lipid metabolism and reveal a potential target for molecular breeding to improve meat quality.

This study aimed to evaluate the endometrial transcriptomic patterns in the early secretory phase (ESP) and mid-secretory phase (MSP) of the natural menstrual cycle before in vitro fertilization and embryo transfer (IVF-ET).

Thirty patients whose endometrial tissues were obtained from the ESP or MSP of a natural menstrual cycle immediately before IVF-ET were included. Endometrial dating was histologically confirmed as ESP (cycle days 16-18) or MSP (cycle days 19-21), according to the noyes criteria. The patients were divided into two groups depending on the IVF-ET outcome: pregnant (n=14; 7 in ESP and 7 in MSP) or non-pregnant (n=16; 8 in ESP and 8 in MSP). Differentially expressed genes (DEGs) in the MSP, compared to the ESP, were identified using NanoString nCounter (NanoString Technologies, Seattle, WA, USA) data for both the pregnant and non-pregnant groups.

Thirteen DEGs in the pregnant group and 11 DEGs in the non-pregnant group were identified in the MSP compared to those in the ESP. In both groups, adrenoceptor alpha 2A, interleukin 1 receptor-associated kinase 2, a disintegrin and metalloproteinase with thrombospondin repeats 15 (ADAMTS15), serpin family E member 1, integrin subunit beta 3, transmembrane protein 252 (TMEM252), huntingtin associated protein 1, C2 calcium-dependent domain containing 4A, and integrin subunit alpha 2 were upregulated in the MSP, compared to the ESP. TMEM37, galactosidase beta 1 like 2, Rho family GTPase 3, and cytochrome P450 family 24 subfamily A member 1 were upregulated in the MSP only in the pregnant group. ADAMTS8 was downregulated and monoamine oxidase A was upregulated in the MSP only in the non-pregnant group.

Transcriptomic patterns in the endometrium immediately before IVF-ET appear to differ according to the IVF-ET outcome. These novel DEGs, which have not been previously studied, may have functional significance during the window of implantation and serve as potential biomarkers of endometrial receptivity.

Obesity and type 2 diabetes (T2D) remain major global healthcare challenges, and developing therapeutics necessitates using nonhuman primate models. Here, we present a transcriptomic and proteomic atlas of all the major organs of cynomolgus monkeys with spontaneous obesity or T2D in comparison to healthy controls. Molecular changes occur predominantly in the adipose tissues of individuals with obesity, while extensive expression perturbations among T2D individuals are observed in many tissues such as the liver and kidney. Immune-response-related pathways are upregulated in obesity and T2D, whereas metabolism and mitochondrial pathways are downregulated. Moreover, we highlight some potential therapeutic targets, including SLC2A1 and PCSK1 in obesity as well as SLC30A8 and SLC2A2 in T2D. Our study provides a resource for exploring the complex molecular mechanism of obesity and T2D and developing therapies for these diseases, with limitations including lack of hypothalamus, isolated islets of Langerhans, longitudinal data, and body fat percentage.

Novel biomarkers are key to addressing the ongoing pandemic of type 2 diabetes mellitus. While new technologies have improved the potential of identifying such biomarkers, at the same time there is an increasing need for informed prioritization to ensure efficient downstream verification. We have built BALDR, an automated pipeline for biomarker comparison and prioritization in the context of diabetes. BALDR includes protein, gene, and disease data from major public repositories, text-mining data, and human and mouse experimental data from the IMI2 RHAPSODY consortium. These data are provided as easy-to-read figures and tables enabling direct comparison of up to 20 biomarker candidates for diabetes through the public website https://baldr.cpr.ku.dk.

Aging biomarkers are a combination of biological parameters to (i) assess age-related changes, (ii) track the physiological aging process, and (iii) predict the transition into a pathological status. Although a broad spectrum of aging biomarkers has been developed, their potential uses and limitations remain poorly characterized. An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower? This review aims to address this need. Here, we summarize our current knowledge of biomarkers developed for cellular, organ, and organismal levels of aging, comprising six pillars: physiological characteristics, medical imaging, histological features, cellular alterations, molecular changes, and secretory factors. To fulfill all these requisites, we propose that aging biomarkers should qualify for being specific, systemic, and clinically relevant.