Objective
A surprising feature of type 1 diabetes is that the immune system destroys pancreatic β-cells but not neighboring α-cells, even though both β- and α-cells are exposed to inflammatory mediators and become dysfunctional. Dysfunction, however, progresses to death for β-cells but not α-cells. In the present project, our overarching goal is to clarify why α-cells are more resistant than β-cells to the damage inherent to type 1 diabetes, and then to translate this information into novel approaches to prevent β-cell death. We will use advanced bioinformatic tools to mine available single cell RNA sequencing databases of β- and α-cells from normoglycemic individuals or individuals affected by type 1 diabetes, together with our own datasets of β- and α-cells exposed in vitro to relevant stresses, to define potentially “protective” genes that are preferentially expressed in α-cells. Then, we will use iPSC-derived islet-like cells, EndoC β-H1 and primary human islets to validate the bioinformatic findings, i.e., we will perform experiments where “protective genes” observed in α-cells are overexpressed in β-cells to determine if this leads to protection against diabetogenic stresses.
Background Rationale
Type 1 diabetes is a chronic metabolic disease characterized by immune-mediated destruction of pancreatic β-cells. There is no cure for this autoimmune disorder and its incidence is increasing on a worldwide basis. Notably, the neighboring glucagon-producing α-cells, which are also exposed to inflammatory mediators in diabetes, show functional impairment but contrary to the fate of β-cells, do not undergo cell death. This may be due to the α-cell enhanced capacity to endure viral infections and endoplasmic reticulum stress, which allows them to better survive early stressors that may cause β-cell death and consequently amplify antigen presentation to the immune system. Based on previous data from the host laboratory and on single cell RNA Sequencing performed by the Human Pancreas Analysis Program and re-analyzed by the host lab, several potential differences between α- and β-cells have been identified, but the full magnitude of these differences that may explain α-cells’ resistance to immune-induced cell damage remains to be clarified. We hypothesize that key inflammation-induced mechanisms divergent between α- and β-cells may explain their different molecular signatures in T1D. Discovering these cell-specific signatures may allow us to identify key genes that could be targeted for therapy in order to boost the resistance of β-cells to the autoimmune-mediated destruction.
Description of Project
Type 1 diabetes is a chronic metabolic disease characterized by immune-mediated destruction of pancreatic β-cells. Notably, the neighboring glucagon-producing α-cells, which are also exposed to inflammatory mediators in diabetes, show functional impairment but contrary to the fate of β-cells, do not undergo cell death. This may be due to the α-cell enhanced capacity to endure viral infections and endoplasmic reticulum stress, which allows them to better survive early stressors that may cause β-cell death and consequently amplify antigen presentation to the immune system. Based on previous data from the host laboratory and on single cell RNA Sequencing, a method that allows detection of mRNAs at cell level, performed by the Human Pancreas Analysis Program and re-analyzed by the host lab, several potential differences between α- and β-cells have been identified, but the full magnitude of these differences that may explain α-cells’ resistance to immune-induced cell damage remains to be clarified. Discovering these α-cell specific signatures may allow us to identify key genes that could be targeted for therapy in order to boost the resistance of β-cells to the autoimmune-mediated destruction. Against this background, the aims of the present project are: 1. To mine available RNA sequencing (bulk and single cell RNA-Seq) data from individuals with T1D and compare them to our own datasets of in vitro stressed α- and β-cells; 2. Use advanced bioinformatic strategies for data integration to identify key gene signatures, networks and pathways that are common or divergent between α- and β-cells, to define potentially “protective” genes that are preferentially expressed in α-cells; 3. Use induced pluripotent stem cells (iPSC)-derived human islet-like cells, the pure human β-cell line EndoC β-H1 and primary human islets to study the newly genes and pathways identified. We will perform experiments where “protective genes” observed in α-cells are overexpressed in β-cells to determine if this leads to protection against diabetogenic stresses. The ultimate objective of the present project is to translate our findings into targeted strategies that preserve β-cells viability in the early stages of type 1 diabetes.
Anticipated Outcome
We anticipate the discovery of key genes and pathways that mediate α-cell resistance/β-cell damage during T1D. Using advanced bioinformatic approaches, at least in part generated by the host group, we will “mine” these cell-specific pathways to identify potential targets that could be modulated in order to protect β-cells from the autoimmune attack. Some of these potential targets are already being evaluated and giving promising preliminary results. We anticipate discovering at least 3 new genes that will be validated in human islet cells as targets for potential therapies to protect β-cells in T1D.
Relevance to T1D
The goal of the present project is to translate our findings into the discovery of novel approaches for the treatment of T1D. The host laboratory has already successfully used this approach to identify potential therapeutic targets and their corresponding drugs for T1D and other autoimmune diseases. Two of these newly identified agents, JAK1/2 and TYK2 inhibitors, have been validated by the host lab and others as protecting β-cells in vitro against cytokine-induced inflammatory responses, dysfunction and death. Importantly, JAK1/2 inhibitors have been recently shown in a phase II clinical trial, to at least in part preserve C-peptide production in individuals with early type 1 diabetes. A similar approach will be used here, i.e. we will screen our bulk transcriptomes of purified iPSC- derived β- and α-like cells exposed to diabetic conditions to identify chemicals that may either revert or promote interesting gene expression patterns. Promising agents will be tested in vitro, in iPSC-derived islet-like organoids exposed to immune stressors. We expect that novel, relevant, and targetable genes and pathways will be discovered and translated into new therapies during the present and future follow up projects.