Heterogeneity of Diabetes: β-Cells, Phenotypes, and Precision Medicine: Proceedings of an International Symposium of the Canadian Institutes of Health Research's Institute of Nutrition, Metabolism and Diabetes and the U.S. National Institutes of Health's National Institute of Diabetes and Digestive and Kidney Diseases

Abstract

One hundred years have passed since the discovery of insulin-an achievement that transformed diabetes from a fatal illness into a manageable chronic condition. The decades since that momentous achievement have brought ever more rapid innovation and advancement in diabetes research and clinical care. To celebrate the important work of the past century and help to chart a course for its continuation into the next, the Canadian Institutes of Health Research's Institute of Nutrition, Metabolism and Diabetes and the U.S. National Institutes of Health's National Institute of Diabetes and Digestive and Kidney Diseases recently held a joint international symposium, bringing together a cohort of researchers with diverse interests and backgrounds from both countries and beyond to discuss their collective quest to better understand the heterogeneity of diabetes and thus gain insights to inform new directions in diabetes treatment and prevention. This article summarizes the proceedings of that symposium, which spanned cutting-edge research into various aspects of islet biology, the heterogeneity of diabetic phenotypes, and the current state of and future prospects for precision medicine in diabetes.

Figure 1

δ-Cells inhibit β- and α-cells via the inhibitory actions of somatostatin. Controlling the activity of δ-cells are a multitude of nutrients, neurotransmitters, and paracrine and endocrine factors. Examples shown here are not comprehensive.

Figure 2

Pancreatic islets are full of pericytes. A: Z-projection of confocal images of mouse and human pancreatic tissue sections immunostained with an antibody against the mural marker NG2 (neuron-glial antigen 2; green). B: Zoomed images of regions containing islets in image A. Pericyte density in mouse and human islets is higher than in surrounding acinar tissue. This difference is even more striking in the human pancreas. These findings suggest that pancreatic islets in mice and humans are equipped with a mechanism that allows the control of their blood flow independently of the surrounding exocrine tissue. Scale bars are 50 mm in image A and 10 mm in image B.

Figure 3

Schematic depicting a PSC-based strategy to bioengineer human vascular networks that support the engraftment and function of SCβ-cells. iPSC-ECs, induced PSC endothelial cells; iPSC-MCs, induced PSC perivascular cells.

Figure 4

The generation of immune functional HILOs may provide an alternative approach for treating type 1 diabetes without the requirement for systemic immunosuppression. NKT, natural killer T, T1D, type 1 diabetes.

Figure 5

While islet encapsulation blocks direct interactions between immune cells and the islet (1), the large biomaterial barrier creates insufficient nutrient delivery and central necrosis (2). Shedding of antigen and stress signals (3) also leads to activation of innate and adaptive immune cells (4 and 5), resulting in antigen-specific T-cell expansion/activation (6) and broad macrophage recruitment (7). Although unable to directly attack the encapsulated graft, immune cells impart damage by secreting reactive oxygen species and cytokines, which diffuse through the hydrogel (8), and by recruiting fibroblasts and macrophages to create a fibrotic capsule (9). Recent approaches can address these challenges by improving islet vascularization (10) and decreasing the capsule size (11), which improves nutrient delivery and supports islet viability (12). With direct islet–immune interactions still blocked (13), the modulation of indirectly activated immune cells is feasible through moderate systemic immunosuppressants (14), localized soluble drug delivery (15), and/or the use of immunomodulatory materials near (16) or attached to the encapsulating material (17). These approaches can not only stop immune activation, but also convert immune cells toward a tolerogenic/regulatory phenotype (18).

Figure 6

A fully autologous system to model diabetes, as shown here, could serve as a platform to study immune cell–β-cell interactions and to test therapeutics. iPSC, induced PSC; T1D, type 1 diabetes.

Figure 7

Model of diabetes etiopathogenesis based on the Palette Disease Model (78) and Threshold Hypothesis (79) that explain heterogeneity within diabetes types and overlap between diabetes types. Individuals (represented by bars) may have several diabetogenic mechanisms (represented by different colors) that, in combination, may cause glucose to reach a threshold. DM, diabetes mellitus; T1D, type 1 diabetes; T2D, type 2 diabetes.

Figure 8

Potential endocrine and exocrine contributors to the development of post-pancreatitis diabetes in the setting of acute pancreatitis, recurrent acute pancreatitis, or chronic pancreatitis. Research is ongoing to better define the mechanisms of diabetes in these populations. Not displayed on this figure is β-cell autoimmunity, which has been reported in case series of patients with acute or chronic pancreatitis. Acute and chronic pancreatitis represent a spectrum of disease; the percentages above the arrows indicate the approximate proportion of patients whose disease progresses for each diagnosis.

Figure 9

Individualized prediction compared with classification into subtypes: advantages and disadvantages of two strategies to apply a precision medicine approach in type 2 diabetes. A: Classification into subtypes. In this approach, people with type 2 diabetes are subclassified into specific subtypes of type 2 diabetes based on clinical, genetic, phenotypic, and/or biomarker traits with the assumption that these subgroupings may enable more defined stratification for treatment responses and other outcomes. B: Individualized prediction. In this approach, markers from biological and clinical information are used as continuous traits to better predict a person’s individual treatment responses to each drug option, thereby guiding the selection of the optimal treatment for that person. Approach A will propose treatment based on response for the particular subtype identified, whereas approach B recognizes differences in treatment response at an individual level. Reprinted with permission from Dennis (112).

Figure 10

The path to precision diabetes medicine. HEA, health economic assessment. Adapted from Fitipaldi H, McCarthy MI, Florez JC, Franks PW. A global overview of precision medicine in type 2 diabetes. Diabetes 2018;67:1911–1922. Reprinted with permission from Chung et al. (141).