Pancreatic β-cell heterogeneity in health and diabetes: classes, sources, and subtypes

A mathematical model for ketosis-prone diabetes suggests the existence of multiple pancreatic β-cell inactivation mechanisms

Ketosis-prone diabetes mellitus (KPD) is a subtype of type 2 diabetes, which presents much like type 1 diabetes, with dramatic hyperglycemia and ketoacidosis. Although KPD patients are initially insulin-dependent, after a few months of insulin treatment, ~ 70% undergo near-normoglycemia remission and can maintain blood glucose without insulin, as in early type 2 diabetes or prediabetes. Here, we propose that these phenomena can be explained by the existence of a fast, reversible glucotoxicity process, which may exist in all people but be more pronounced in those susceptible to KPD. We develop a simple mathematical model of the pathogenesis of KPD, which incorporates this assumption, and show that it reproduces the phenomenology of KPD, including variations in the ability for patients to achieve and sustain remission. These results suggest that a variation of our model may be able to quantitatively describe variations in the course of remission among individuals with KPD.

Subcellular Feature-Based Classification of α and β Cells Using Soft X-ray Tomography

The dysfunction of α and β cells in pancreatic islets can lead to diabetes. Many questions remain on the subcellular organization of islet cells during the progression of disease. Existing three-dimensional cellular mapping approaches face challenges such as time-intensive sample sectioning and subjective cellular identification. To address these challenges, we have developed a subcellular feature-based classification approach, which allows us to identify α and β cells and quantify their subcellular structural characteristics using soft X-ray tomography (SXT). We observed significant differences in whole-cell morphological and organelle statistics between the two cell types. Additionally, we characterize subtle biophysical differences between individual insulin and glucagon vesicles by analyzing vesicle size and molecular density distributions, which were not previously possible using other methods. These sub-vesicular parameters enable us to predict cell types systematically using supervised machine learning. We also visualize distinct vesicle and cell subtypes using Uniform Manifold Approximation and Projection (UMAP) embeddings, which provides us with an innovative approach to explore structural heterogeneity in islet cells. This methodology presents an innovative approach for tracking biologically meaningful heterogeneity in cells that can be applied to any cellular system.

Network representation of multicellular activity in pancreatic islets: Technical considerations for functional connectivity analysis

Within the islets of Langerhans, beta cells orchestrate synchronized insulin secretion, a pivotal aspect of metabolic homeostasis. Despite the inherent heterogeneity and multimodal activity of individual cells, intercellular coupling acts as a homogenizing force, enabling coordinated responses through the propagation of intercellular waves. Disruptions in this coordination are implicated in irregular insulin secretion, a hallmark of diabetes. Recently, innovative approaches, such as integrating multicellular calcium imaging with network analysis, have emerged for a quantitative assessment of the cellular activity in islets. However, different groups use distinct experimental preparations, microscopic techniques, apply different methods to process the measured signals and use various methods to derive functional connectivity patterns. This makes comparisons between findings and their integration into a bigger picture difficult and has led to disputes in functional connectivity interpretations. To address these issues, we present here a systematic analysis of how different approaches influence the network representation of islet activity. Our findings show that the choice of methods used to construct networks is not crucial, although care is needed when combining data from different islets. Conversely, the conclusions drawn from network analysis can be heavily affected by the pre-processing of the time series, the type of the oscillatory component in the signals, and by the experimental preparation. Our tutorial-like investigation aims to resolve interpretational issues, reconcile conflicting views, advance functional implications, and encourage researchers to adopt connectivity analysis. As we conclude, we outline challenges for future research, emphasizing the broader applicability of our conclusions to other tissues exhibiting complex multicellular dynamics.

From stem cells to pancreatic β-cells: strategies, applications, and potential treatments for diabetes

Loss and functional failure of pancreatic β-cells results in disruption of glucose homeostasis and progression of diabetes. Although whole pancreas or pancreatic islet transplantation serves as a promising approach for β-cell replenishment and diabetes therapy, the severe scarcity of donor islets makes it unattainable for most diabetic patients. Stem cells, particularly induced pluripotent stem cells (iPSCs), are promising for the treatment of diabetes owing to their self-renewal capacity and ability to differentiate into functional β-cells. In this review, we first introduce the development of functional β-cells and their heterogeneity and then turn to highlight recent advances in the generation of β-cells from stem cells and their potential applications in disease modeling, drug discovery and clinical therapy. Finally, we have discussed the current challenges in developing stem cell-based therapeutic strategies for improving the treatment of diabetes. Although some significant technical hurdles remain, stem cells offer great hope for patients with diabetes and will certainly transform future clinical practice.

Illuminating the complete ß-cell mass of the human pancreas- signifying a new view on the islets of Langerhans

Pancreatic islets of Langerhans play a pivotal role in regulating blood glucose homeostasis, but critical information regarding their mass, distribution and composition is lacking within a whole organ context. Here, we apply a 3D imaging pipeline to generate a complete account of the insulin-producing islets throughout the human pancreas at a microscopic resolution and within a maintained spatial 3D context. These data show that human islets are far more heterogenous than previously accounted for with regards to their size distribution and cellular make up. By deep tissue 3D imaging, this in-depth study demonstrates that 50% of the human insulin-expressing islets are virtually devoid of glucagon-producing α-cells, an observation with significant implications for both experimental and clinical research.

A novel approach to determine the critical survival threshold of cellular oxygen within spheroids via integrating live/dead cell imaging with oxygen modeling

Defining the oxygen level that induces cell death within 3-D tissues is vital for understanding tissue hypoxia; however, obtaining accurate measurements has been technically challenging. In this study, we introduce a noninvasive, high-throughput methodology to quantify critical survival partial oxygen pressure (pO2) with high spatial resolution within spheroids by using a combination of controlled hypoxic conditions, semiautomated live/dead cell imaging, and computational oxygen modeling. The oxygen-permeable, micropyramid patterned culture plates created a precisely controlled oxygen condition around the individual spheroid. Live/dead cell imaging provided the geometric information of the live/dead boundary within spheroids. Finally, computational oxygen modeling calculated the pO2 at the live/dead boundary within spheroids. As proof of concept, we determined the critical survival pO2 in two types of spheroids: isolated primary pancreatic islets and tumor-derived pseudoislets (2.43 ± 0.08 vs. 0.84 ± 0.04 mmHg), indicating higher hypoxia tolerance in pseudoislets due to their tumorigenic origin. We also applied this method for evaluating graft survival in cell transplantations for diabetes therapy, where hypoxia is a critical barrier to successful transplantation outcomes; thus, designing oxygenation strategies is required. Based on the elucidated critical survival pO2, 100% viability could be maintained in a typically sized primary islet under the tissue pO2 above 14.5 mmHg. This work presents a valuable tool that is potentially instrumental for fundamental hypoxia research. It offers insights into physiological responses to hypoxia among different cell types and may refine translational research in cell therapies.NEW & NOTEWORTHY Our study introduces an innovative combinatory approach for noninvasively determining the critical survival oxygen level of cells within small cell spheroids, which replicates a 3-D tissue environment, by seamlessly integrating three pivotal techniques: cell death induction under controlled oxygen conditions, semiautomated imaging that precisely identifies live/dead cells, and computational modeling of oxygen distribution. Notably, our method ensures high-throughput analysis applicable to various cell types, offering a versatile solution for researchers in diverse fields.

Local Dialogues Between the Endocrine and Exocrine Cells in the Pancreas

For many years, it has been taught in medical textbooks that the endocrine and exocrine parts of the pancreas have separate blood supplies that do not mix. Therefore, they have been studied by different scientific communities, and patients with pancreatic disorders are treated by physicians in different medical disciplines, where endocrine and exocrine function are the focus of endocrinologists and gastroenterologists, respectively. The conventional model that every islet in each pancreatic lobule receives a dedicated arterial blood supply was first proposed in 1932, and it has been inherited to date. Recently, in vivo intravital recording of red blood cell flow in mouse islets as well as in situ structural analysis of 3D pancreatic vasculature from hundreds of islets provided evidence for preferentially integrated pancreatic blood flow in six mammalian species. The majority of islets have no association with the arteriole, and there is bidirectional blood exchange between the two segments. Such vascularization may allow an entire downstream region of islets and acinar cells to be simultaneously exposed to a topologically and temporally specific plasma content, which could underlie an adaptive sensory function as well as common pathogeneses of both portions of the organ in pancreatic diseases, including diabetes.

ARTICLE HIGHLIGHTS

Exendin-4 affects calcium signalling predominantly during activation and activity of beta cell networks in acute mouse pancreas tissue slices

Tight control of beta cell stimulus-secretion coupling is crucial for maintaining homeostasis of energy-rich nutrients. While glucose serves as a primary regulator of this process, incretins augment beta cell function, partly by enhancing cytosolic [Ca2+] dynamics. However, the details of how precisely they affect beta cell recruitment during activation, their active time, and functional connectivity during plateau activity, and how they influence beta cell deactivation remain to be described. Performing functional multicellular Ca2+ imaging in acute mouse pancreas tissue slices enabled us to systematically assess the effects of the GLP-1 receptor agonist exendin-4 (Ex-4) simultaneously in many coupled beta cells with high resolution. In otherwise substimulatory glucose, Ex-4 was able to recruit approximately a quarter of beta cells into an active state. Costimulation with Ex-4 and stimulatory glucose shortened the activation delays and accelerated beta cell activation dynamics. More specifically, active time increased faster, and the time required to reach half-maximal activation was effectively halved in the presence of Ex-4. Moreover, the active time and regularity of [Ca2+]IC oscillations increased, especially during the first part of beta cell response. In contrast, subsequent addition of Ex-4 to already active cells did not significantly enhance beta cell activity. Network analyses further confirmed increased connectivity during activation and activity in the presence of Ex-4, with hub cell roles remaining rather stable in both control experiments and experiments with Ex-4. Interestingly, Ex-4 demonstrated a biphasic effect on deactivation, slightly prolonging beta cell activity at physiological concentrations and shortening deactivation delays at supraphysiological concentrations. In sum, costimulation by Ex-4 and glucose increases [Ca2+]IC during beta cell activation and activity, indicating that the effect of incretins may, to an important extent, be explained by enhanced [Ca2+]IC signals. During deactivation, previous incretin stimulation does not critically prolong cellular activity, which corroborates their low risk of hypoglycemia.

Phogrin Regulates High-Fat Diet-Induced Compensatory Pancreatic β-Cell Growth by Switching Binding Partners

The receptor protein tyrosine phosphatase phogrin primarily localizes to hormone secretory granules in neuroendocrine cells. Concurrent with glucose-stimulated insulin secretion, phogrin translocates to pancreatic β-cell plasma membranes, where it interacts with insulin receptors (IRs) to stabilize insulin receptor substrate 2 (IRS2) that, in turn, contributes to glucose-responsive β-cell growth. Pancreatic β-cell development was not altered in β-cell-specific, phogrin-deficient mice, but the thymidine incorporation rate decreased in phogrin-deficient islets with a moderate reduction in IRS2 protein expression. In this study, we analyzed the β-cell response to high-fat diet stress and found that the compensatory expansion in β-cell mass was significantly suppressed in phogrin-deficient mice. Phogrin-IR interactions occurred only in high-fat diet murine islets and proliferating β-cell lines, whereas they were inhibited by the intercellular binding of surface phogrin under confluent cell culture conditions. Thus, phogrin could regulate glucose-stimulated compensatory β-cell growth by changing its binding partner from another β-cell phogrin to IR in the same β-cells.

Islet autoimmunity in human type 1 diabetes: initiation and progression from the perspective of the beta cell

Type 1 diabetes results from the poorly understood process of islet autoimmunity, which ultimately leads to the loss of functional pancreatic beta cells. Mounting evidence supports the notion that the activation and evolution of islet autoimmunity in genetically susceptible people is contingent upon early life exposures affecting the islets, especially beta cells. Here, we review some of the recent advances and studies that highlight the roles of these changes as well as antigen presentation and stress response pathways in beta cells in the onset and propagation of the autoimmune process in type 1 diabetes. Future progress in this area holds promise for advancing islet- and beta cell-directed therapies that could be implemented in the early stages of the disease and could be combined with immunotherapies.

Delineating mouse β-cell identity during lifetime and in diabetes with a single cell atlas

Although multiple pancreatic islet single-cell RNA-sequencing (scRNA-seq) datasets have been generated, a consensus on pancreatic cell states in development, homeostasis and diabetes as well as the value of preclinical animal models is missing. Here, we present an scRNA-seq cross-condition mouse islet atlas (MIA), a curated resource for interactive exploration and computational querying. We integrate over 300,000 cells from nine scRNA-seq datasets consisting of 56 samples, varying in age, sex and diabetes models, including an autoimmune type 1 diabetes model (NOD), a glucotoxicity/lipotoxicity type 2 diabetes model (db/db) and a chemical streptozotocin β-cell ablation model. The β-cell landscape of MIA reveals new cell states during disease progression and cross-publication differences between previously suggested marker genes. We show that β-cells in the streptozotocin model transcriptionally correlate with those in human type 2 diabetes and mouse db/db models, but are less similar to human type 1 diabetes and mouse NOD β-cells. We also report pathways that are shared between β-cells in immature, aged and diabetes models. MIA enables a comprehensive analysis of β-cell responses to different stressors, providing a roadmap for the understanding of β-cell plasticity, compensation and demise.

Single-cell infrared phenomics identifies cell heterogeneity of individual pancreatic islets in mouse model

Identifying the islet heterogeneity (cell types and the proportion of each subpopulation) and their relevance to function and disease will lead to fundamental information for the prevention and therapies of diabetes. Here, we introduce a single-cell phenotypic essay on the heterogeneity within individual pancreatic islets by using the combination of synchrotron infrared microspectroscopy and quantitative calculation. In a mouse model, the cellular heterogeneities at both the whole pancreas and single intact islet level were identified. The variation of biochemical phenotypes successfully subdivided islet cells into five main groups and quantitatively determined their proportion. These findings not only demonstrate single-cell infrared phenomics as a value complementary technique and strategy for the description of cellular heterogeneity within the pancreatic islets but also provide a quick, label-free optical platform for investigating phenotypic heterogeneity at the small-organelle level with single cell resolution.

Integrated transcriptomics contrasts fatty acid metabolism with hypoxia response in β-cell subpopulations associated with glycemic control

BACKGROUND

Understanding how heterogeneous β-cell function impacts diabetes is imperative for therapy development. Standard single-cell RNA sequencing analysis illuminates some factors driving heterogeneity, but new strategies are required to enhance information capture.

RESULTS

We integrate pancreatic islet single-cell and bulk RNA sequencing data to identify β-cell subpopulations based on gene expression and characterize genetic networks associated with β-cell function in obese SM/J mice. We identify β-cell subpopulations associated with basal insulin secretion, hypoxia response, cell polarity, and stress response. Network analysis associates fatty acid metabolism and basal insulin secretion with hyperglycemic-obesity, while expression of Pdyn and hypoxia response is associated with normoglycemic-obesity.

CONCLUSIONS

By integrating single-cell and bulk islet transcriptomes, our study explores β-cell heterogeneity and identifies novel subpopulations and genetic pathways associated with β-cell function in obesity.

Effects of saponins isolated from Polygonatum sibiricum on H2O2-induced oxidative damage in RIN-m5F cells and its protective effect on pancreas

The damage of islet cells caused by oxidative stress is closely related to diabetes. The aim of this study is to investigate the protective effect of saponins isolated from polygonatum sibiricum (PSS) on pancreas injury by using in vitro and in vivo models. The oxidative stress model of RIN-m5F cells induced by H₂O₂ was established. We found that PSS could decrease the apoptosis of RIN-m5F cells under oxidative stress. After PSS treatment, ROS and MDA levels in cells significantly decreased. Moreover, the levels of SOD and GSH were significantly increased. PSS could increase the insulin secretion level of cells under oxidative stress. The expression level of intracellular Bcl-2 increased, and the expression levels of Bax, caspase-3, caspase-8, and caspase-9 decreased significantly. In addition, the type 2 diabetes mouse model was established. The results showed that PSS had a protective effect on the injury of the pancreas in T2DM mice. PSS can relieve oxidative stress and high glucose-mediated pancreas cytotoxicity. PSS may be a promising candidate for diabetes intervention and functional foods.

Genetic and pharmacologic inhibition of ALDH1A3 as a treatment of β-cell failure

Type 2 diabetes (T2D) is associated with β-cell dedifferentiation. Aldehyde dehydrogenase 1 isoform A3 (ALHD1A3) is a marker of β-cell dedifferentiation and correlates with T2D progression. However, it is unknown whether ALDH1A3 activity contributes to β-cell failure, and whether the decrease of ALDH1A3-positive β-cells (A+) following pair-feeding of diabetic animals is due to β-cell restoration. To tackle these questions, we (i) investigated the fate of A+ cells during pair-feeding by lineage-tracing, (ii) somatically ablated ALDH1A3 in diabetic β-cells, and (iii) used a novel selective ALDH1A3 inhibitor to treat diabetes. Lineage tracing and functional characterization show that A+ cells can be reconverted to functional, mature β-cells. Genetic or pharmacological inhibition of ALDH1A3 in diabetic mice lowers glycemia and increases insulin secretion. Characterization of β-cells following ALDH1A3 inhibition shows reactivation of differentiation as well as regeneration pathways. We conclude that ALDH1A3 inhibition offers a therapeutic strategy against β-cell dysfunction in diabetes.

Quantitative study of 3T MRI qDixon-WIP applied in pancreatic fat infiltration in patients with type 2 diabetes mellitus

OBJECTIVE

To investigate the application value of 3T MRI qDixon-WIP technique in the quantitative measurement of pancreatic fat content in patients with type 2 diabetes mellitus (T2DM).

METHODS

The 3T MRI qDixon-WIP sequence was used to scan the livers and the pancreas of 47 T2DM patients (experimental group) and 48 healthy volunteers (control group). Pancreatic fat fraction (PFF), hepatic fat fraction (HFF), Body mass index (BMI) ratio of pancreatic volume to body surface area (PVI) were measured. Total cholesterol (TC), subcutaneous fat area (SA), triglyceride (TG), abdominal visceral fat area (VA), high density lipoprotein (HDL-c), fasting blood glucose (FPC) and low-density lipoprotein (LDL-c) were collected. The relationship between the experimental group and the control group and between PFF and other indicators was compared. The differences of PFF between the control group and different disease course subgroups were also explored.

RESULTS

There was no significant difference in BMI between the experimental group and the control group (P=0.231). PVI, SA, VA, PFF and HFF had statistical differences (P<0.05). In the experimental group, PFF was highly positively correlated with HFF (r=0.964, P<0.001), it was moderately positively correlated with TG and abdominal fat area (r=0.676, 0.591, P<0.001), and it was weakly positively correlated with subcutaneous fat area (r=0.321, P=0.033). And it had no correlation with FPC, PVI, HDL-c, TC and LDL-c (P>0.05). There were statistical differences in PFF between the control group and the patients with different course of T2DM (P<0.05). There was no significant difference in PFF between T2DM patients with a disease course ≤1 year and those with a disease course <5 years (P>0.05). There were significant differences in PFF between the groups with a disease course of 1-5 years and those with a disease course of more than 5 years (P<0.001).

CONCLUSION

PVI of T2DM patients is lower than normal, but SA, VA, PFF, HFF are higher than normal. The degree of pancreatic fat accumulation in T2DM patients with long disease course was higher than that in patients with short disease course. The qDixon-WIP sequence can provide an important reference for clinical quantitative evaluation of fat content in T2DM patients.

Microtubules in Pancreatic β Cells: Convoluted Roadways Toward Precision

Pancreatic islet β cells regulate glucose homeostasis via glucose-stimulated insulin secretion (GSIS). Cytoskeletal polymers microtubules (MTs) serve as tracks for the transport and positioning of secretory insulin granules. MT network in β cells has unique morphology with several distinct features, which support granule biogenesis (via Golgi-derived MT array), net non-directional transport (via interlocked MT mesh), and control availability of granules at secretion sites (via submembrane MT bundle). The submembrane MT array, which is parallel to the plasma membrane and serves to withdraw excessive granules from the secretion hot spots, is destabilized and fragmented downstream of high glucose stimulation, allowing for regulated secretion. The origin of such an unusual MT network, the features that define its functionality, and metabolic pathways that regulate it are still to a large extent elusive and are a matter of active investigation and debate. Besides the MT network itself, it is important to consider the interplay of molecular motors that drive and fine-tune insulin granule transport. Importantly, activity of kinesin-1, which is the major MT-dependent motor in β cells, transports insulin granules, and has a capacity to remodel MT network, is also regulated by glucose. We discuss yet unknown potential avenues toward understanding how MT network and motor proteins provide control for secretion in coordination with other GSIS-regulating mechanisms.

Phosphatases are predicted to govern prolactin-mediated JAK–STAT signaling in pancreatic beta cells

Patients with diabetes are unable to produce a sufficient amount of insulin to properly regulate their blood glucose levels. One potential method of treating diabetes is to increase the number of insulin-secreting beta cells in the pancreas to enhance insulin secretion. It is known that during pregnancy, pancreatic beta cells proliferate in response to the pregnancy hormone, prolactin (PRL). Leveraging this proliferative response to PRL may be a strategy to restore endogenous insulin production for patients with diabetes. To investigate this potential treatment, we previously developed a computational model to represent the PRL-mediated JAK–STAT signaling pathway in pancreatic beta cells. Here, we applied the model to identify the importance of particular signaling proteins in shaping the response of a population of beta cells. We simulated a population of 10 000 heterogeneous cells with varying initial protein concentrations responding to PRL stimulation. We used partial least squares regression to analyze the significance and role of each of the varied protein concentrations in producing the response of the cell. Our regression models predict that the concentrations of the cytosolic and nuclear phosphatases strongly influence the response of the cell. The model also predicts that increasing PRL receptor strengthens negative feedback mediated by the inhibitor suppressor of cytokine signaling. These findings reveal biological targets that can potentially be used to modulate the proliferation of pancreatic beta cells to enhance insulin secretion and beta cell regeneration in the context of diabetes.

The Effect of Glucose Metabolism and Breastfeeding on the Intestinal Microbiota of Newborns of Women with Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is a pregnancy complication in which women without previously diagnosed diabetes develop chronic hyperglycemia during gestation. The diet and lifestyle of the mother during pregnancy as well as lactation have long-term effects on the child’s health and development. Detection of early risk markers of adult-age chronic diseases that begin during prenatal life and the application of complex nutritional interventions at the right time may reduce the risk of these diseases. Newborns adapt to the ectopic environment by developing intestinal immune homeostasis. Adequate initial colonization of bacteria is necessary for sufficient development of intestinal immunity. The environmental determinant of adequate colonization is breast milk. Although a developing newborn is capable of producing an immune response, the effector immune component requires bacterial stimulation. Breast milk stimulates the proliferation of a well-balanced and diverse microbiota, which initially influences the switch from an intrauterine TH2 predominant to a TH1/TH2 balanced response and the activation of T-regulatory cells by breast milk-stimulated specific organisms (Bifidobacteria, Lactobacillus, and Bacteroides). Breastfeeding in newborns of mothers with diabetes mellitus regulates the adequate immune response of the newborn and prevents diseases of the neonatal and postnatal period.

Microtubules regulate pancreatic β-cell heterogeneity via spatiotemporal control of insulin secretion hot spots

Heterogeneity of glucose-stimulated insulin secretion (GSIS) in pancreatic islets is physiologically important but poorly understood. Here, we utilize mouse islets to determine how microtubules (MTs) affect secretion toward the vascular extracellular matrix at single cell and subcellular levels. Our data indicate that MT stability in the β-cell population is heterogenous, and that GSIS is suppressed in cells with highly stable MTs. Consistently, MT hyper-stabilization prevents, and MT depolymerization promotes the capacity of single β-cell for GSIS. Analysis of spatiotemporal patterns of secretion events shows that MT depolymerization activates otherwise dormant β-cells via initiation of secretion clusters (hot spots). MT depolymerization also enhances secretion from individual cells, introducing both additional clusters and scattered events. Interestingly, without MTs, the timing of clustered secretion is dysregulated, extending the first phase of GSIS and causing oversecretion. In contrast, glucose-induced Ca²⁺ influx was not affected by MT depolymerization yet required for secretion under these conditions, indicating that MT-dependent regulation of secretion hot spots acts in parallel with Ca²⁺ signaling. Our findings uncover a novel MT function in tuning insulin secretion hot spots, which leads to accurately measured and timed response to glucose stimuli and promotes functional β-cell heterogeneity.

High Coexpression of the Ghrelin and LEAP2 Receptor GHSR With Pancreatic Polypeptide in Mouse and Human Islets

Islets represent an important site of direct action of the hormone ghrelin, with expression of the ghrelin receptor (growth hormone secretagogue receptor; GHSR) having been localized variably to alpha cells, beta cells, and/or somatostatin (SST)-secreting delta cells. To our knowledge, GHSR expression by pancreatic polypeptide (PP)-expressing gamma cells has not been specifically investigated. Here, histochemical analyses of Ghsr-IRES-Cre × Cre-dependent ROSA26-yellow fluorescent protein (YFP) reporter mice showed 85% of GHSR-expressing islet cells coexpress PP, 50% coexpress SST, and 47% coexpress PP + SST. Analysis of single-cell transcriptomic data from mouse pancreas revealed 95% of Ghsr-expressing cells coexpress Ppy, 100% coexpress Sst, and 95% coexpress Ppy + Sst. This expression was restricted to gamma-cell and delta-cell clusters. Analysis of several single-cell human pancreatic transcriptome data sets revealed 59% of GHSR-expressing cells coexpress PPY, 95% coexpress SST, and 57% coexpress PPY + SST. This expression was prominent in delta-cell and beta-cell clusters, also occurring in other clusters including gamma cells and alpha cells. GHSR expression levels were upregulated by type 2 diabetes mellitus in beta cells. In mice, plasma PP positively correlated with fat mass and with plasma levels of the endogenous GHSR antagonist/inverse agonist LEAP2. Plasma PP also elevated on LEAP2 and synthetic GHSR antagonist administration. These data suggest that in addition to delta cells, beta cells, and alpha cells, PP-expressing pancreatic cells likely represent important direct targets for LEAP2 and/or ghrelin both in mice and humans.

The β Cell in Diabetes: Integrating Biomarkers With Functional Measures

The pathogenesis of hyperglycemia observed in most forms of diabetes is intimately tied to the islet β cell. Impairments in propeptide processing and secretory function, along with the loss of these vital cells, is demonstrable not only in those in whom the diagnosis is established but typically also in individuals who are at increased risk of developing the disease. Biomarkers are used to inform on the state of a biological process, pathological condition, or response to an intervention and are increasingly being used for predicting, diagnosing, and prognosticating disease. They are also proving to be of use in the different forms of diabetes in both research and clinical settings. This review focuses on the β cell, addressing the potential utility of genetic markers, circulating molecules, immune cell phenotyping, and imaging approaches as biomarkers of cellular function and loss of this critical cell. Further, we consider how these biomarkers complement the more long-established, dynamic, and often complex measurements of β-cell secretory function that themselves could be considered biomarkers.