Type 1 diabetes (T1D) is a very serious autoimmune disease resulting from self- destruction of the insulin producing pancreatic ? cells. A disorder without a cure, T1D has seen a pronounced increase in its frequency over the last half-century at a global level. Despite advances in disease management, it remains a disorder that instills major morbidity (e.g., blindness, kidney and heart disease, risk for hypoglycemia) and mortality challenges on those afflicted. We portend a major reason that the community of T1D researchers has seen limited progress, over many decades, in attempts to identify therapies capable of preventing and/or reversing the disease is tied to a collective lack in understanding the mechanisms of disease development in humans; especially in terms of knowing the specific contributions of islet endocrine cells and the immune system to the disorder, including and especially their interplay with each other. This application proposes to test the hypothesis that a highly innovative technique known as High Multiplexed Imaging (HMI), that when applied to rare but informative pancreatic tissues from those with or at varying levels of risk for T1D as well as control tissues, will unlock research mysteries surrounding the disorder that have existed for many years. That hypothesis will be tested in this proposal by the performance of two interactive specific aims, the first being to establish HMI as a tool for pancreatic tissue analysis, while the second involves characterization of islet and immune system cells in T1D by HMI using validated antibodies. Importantly, to achieve said goals with maximal probability for success, we have formed a team well poised to address the lofty challenges associated with our proposal. This proposal combines the efforts of three well-established investigators that developed HMI (Bodenmiller), have provided crucial information regarding islet cell plasticity (Herrera), and helped define the natural history of T1D in both humans and the NOD mouse model of the disease (Atkinson). Our team is committed to not only generate information vital for our own proposed project goals but in addition, to generating data for the entire Human Islet Research Network (HIRN) collective. In sum, we firmly believe this study will result in a technological means for providing novel information regarding the pathogenesis of T1D; knowledge that should prove beneficial for attempts seeking to prevent and/or reverse the disorder.
Type 1 diabetes is a very serious autoimmune disease resulting from the self-destruction of insulin producing pancreatic beta cells; a disease without a cure, a disorder that is increasing in its frequency at a global level, and a malady that instills major morbidity (e.g., blindness, kidney and heart disease, significant life-style challenges) and mortality on those afflicted. We portend a major reason that the community of type 1 diabetes researchers has seen limited progress in identifying a means to prevent and/or reverse the disease, despite decades of attempts to do so, is tied to our collective lack in understanding the mechanisms of disease development in humans; especially in terms of knowing the specific contributions of islet cells and the immune system to the disorder...as well as their interplay. This application proposes utilization of a highly innovative technique known as High Multiplexed Imaging (HMI) that when applied to rare but informative pancreatic tissues, should help unlock research mysteries that have existed for years, forming the groundwork for more effective methods seeking to benefit the lives of those with the disease.
|Chevrier, Stéphane; Crowell, Helena L; Zanotelli, Vito R T et al. (2018) Compensation of Signal Spillover in Suspension and Imaging Mass Cytometry. Cell Syst 6:612-620.e5|
|Cigliola, Valentina; Ghila, Luiza; Thorel, Fabrizio et al. (2018) Pancreatic islet-autonomous insulin and smoothened-mediated signalling modulate identity changes of glucagon+ ?-cells. Nat Cell Biol 20:1267-1277|
|Basco, Davide; Zhang, Quan; Salehi, Albert et al. (2018) ?-cell glucokinase suppresses glucose-regulated glucagon secretion. Nat Commun 9:546|
|Schulz, Daniel; Zanotelli, Vito Riccardo Tomaso; Fischer, Jana Raja et al. (2018) Simultaneous Multiplexed Imaging of mRNA and Proteins with Subcellular Resolution in Breast Cancer Tissue Samples by Mass Cytometry. Cell Syst 6:25-36.e5|
|Rapsomaniki, Maria Anna; Lun, Xiao-Kang; Woerner, Stefan et al. (2018) CellCycleTRACER accounts for cell cycle and volume in mass cytometry data. Nat Commun 9:632|
|Pelissier Vatter, Fanny A; Schapiro, Denis; Chang, Hang et al. (2018) High-Dimensional Phenotyping Identifies Age-Emergent Cells in Human Mammary Epithelia. Cell Rep 23:1205-1219|
|Wasserfall, Clive; Nick, Harry S; Campbell-Thompson, Martha et al. (2017) Persistence of Pancreatic Insulin mRNA Expression and Proinsulin Protein in Type 1 Diabetes Pancreata. Cell Metab 26:568-575.e3|