Project description:Palmer2014 - Effect of IL-1β-Blocking therapies in T2DM - Disease Condition This is the model with disease state initial conditions. A few changes were made to the model equations in order to bypass the circular dependencies apparent in SBML. Coupled algebraic equations for the species Glucose, Insulin and Proinsulin were changed to reactions which represent the ordinary differential equations found in a previously published model by De Gaetano et al (2008), [MODEL1112110003]. This reference was used by the present authors for the algebraic equations. The original Mathematica code, obtained from the supplementary material of the article can be downloaded from the link below: [Palmer2014_notebook.nb]. This model is described in the article: Effects of IL-1β-Blocking Therapies in Type 2 Diabetes Mellitus: A Quantitative Systems Pharmacology Modeling Approach to Explore Underlying Mechanisms. Palmér R, Nyman E, Penney M, Marley A, Cedersund G, Agoram B. CPT Pharmacometrics Syst Pharmacol. 2014 Jun 11;3:e118. Abstract: Recent clinical studies suggest sustained treatment effects of interleukin-1β (IL-1β)-blocking therapies in type 2 diabetes mellitus. The underlying mechanisms of these effects, however, remain underexplored. Using a quantitative systems pharmacology modeling approach, we combined ex vivo data of IL-1β effects on β-cell function and turnover with a disease progression model of the long-term interactions between insulin, glucose, and β-cell mass in type 2 diabetes mellitus. We then simulated treatment effects of the IL-1 receptor antagonist anakinra. The result was a substantial and partly sustained symptomatic improvement in β-cell function, and hence also in HbA1C, fasting plasma glucose, and proinsulin-insulin ratio, and a small increase in β-cell mass. We propose that improved β-cell function, rather than mass, is likely to explain the main IL-1β-blocking effects seen in current clinical data, but that improved β-cell mass might result in disease-modifying effects not clearly distinguishable until >1 year after treatment. This model is hosted on BioModels Database and identified by: MODEL1604270002. To cite BioModels Database, please use: BioModels: Content, Features, Functionality and Use. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Palmer2014 - Effect of IL-1β-Blocking therapies in T2DM - Healthy Condition This is the model with healthy state initial conditions. A few changes were made to the model equations in order to bypass the circular dependencies apparent in SBML. Coupled algebraic equations for the species Glucose, Insulin and Proinsulin were changed to reactions which represent the ordinary differential equations found in a previously published model by De Gaetano et al (2008), [MODEL1112110003]. This reference was used by the present authors for the algebraic equations. The original Mathematica code, obtained from the supplementary material of the article can be downloaded from the link below: [Palmer2014_notebook.nb]. This model is described in the article: Effects of IL-1β-Blocking Therapies in Type 2 Diabetes Mellitus: A Quantitative Systems Pharmacology Modeling Approach to Explore Underlying Mechanisms. Palmér R, Nyman E, Penney M, Marley A, Cedersund G, Agoram B. CPT Pharmacometrics Syst Pharmacol. 2014 Jun 11;3:e118. Abstract: Recent clinical studies suggest sustained treatment effects of interleukin-1β (IL-1β)-blocking therapies in type 2 diabetes mellitus. The underlying mechanisms of these effects, however, remain underexplored. Using a quantitative systems pharmacology modeling approach, we combined ex vivo data of IL-1β effects on β-cell function and turnover with a disease progression model of the long-term interactions between insulin, glucose, and β-cell mass in type 2 diabetes mellitus. We then simulated treatment effects of the IL-1 receptor antagonist anakinra. The result was a substantial and partly sustained symptomatic improvement in β-cell function, and hence also in HbA1C, fasting plasma glucose, and proinsulin-insulin ratio, and a small increase in β-cell mass. We propose that improved β-cell function, rather than mass, is likely to explain the main IL-1β-blocking effects seen in current clinical data, but that improved β-cell mass might result in disease-modifying effects not clearly distinguishable until >1 year after treatment. This model is hosted on BioModels Database and identified by: MODEL1604270002. To cite BioModels Database, please use: BioModels: Content, Features, Functionality and Use. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Endoplasmic reticulum (ER) and inflammatory stress responses are two pathophysiologic factors contributing to islet dysfunction and failure in Type 2 Diabetes (T2D). However, how human islet cells respond to these stressors and whether T2D-associated genetic variants modulate these responses is unknown. To fill this knowledge gap, we profiled transcriptional (RNA-seq) and epigenetic (ATAC-seq) remodeling in human islets exposed to ex vivo ER (thapsigargin) or inflammatory (IL-1β+IFN-γ) stress. 5,427 genes (~32%) were associated with stress responses; most were stressor-specific, including upregulation of genes mediating unfolded protein response (e.g. DDIT3, ATF4) and NFKB signaling (e.g. NFKB1, NFKBIA) in ER stress and cytokine-induced inflammation respectively. Islet single-cell RNA-seq profiling revealed strong but heterogeneous beta cell ER stress responses, including a distinct beta cell subset that highly expressed apoptotic genes. Epigenetic profiling uncovered 14,968 stress-responsive cis-regulatory elements (CREs; ~14%), the majority of which were stressor-specific, and revealed increased accessibility at binding sites of transcription factors that were induced upon stress (e.g. ATF4 for ER stress, IRF8 for cytokine-induced inflammation). Eighty-six stress-responsive CREs overlapped known T2D-associated variants, including 20 residing within CREs that were more accessible upon ER stress. Among these, we linked the rs6917676 T2D risk allele (T) to increased in vivo accessibility of an islet ER stress-responsive CRE and allele-specific beta cell nuclear factor binding in vitro. We showed that MAP3K5, the only ER stress-responsive gene in this locus, promotes beta cell apoptosis. Consistent with its pro-apoptotic and putative diabetogenic roles, MAP3K5 expression inversely correlated with beta cell abundance in human islets and was induced in beta cells from T2D donors. Together, this study provides new genome-wide insights into human islet stress responses and putative mechanisms of T2D genetic variants.

Project description:Endoplasmic reticulum (ER) and inflammatory stress responses are two pathophysiologic factors contributing to islet dysfunction and failure in Type 2 Diabetes (T2D). However, how human islet cells respond to these stressors and whether T2D-associated genetic variants modulate these responses is unknown. To fill this knowledge gap, we profiled transcriptional (RNA-seq) and epigenetic (ATAC-seq) remodeling in human islets exposed to ex vivo ER (thapsigargin) or inflammatory (IL-1β+IFN-γ) stress. 5,427 genes (~32%) were associated with stress responses; most were stressor-specific, including upregulation of genes mediating unfolded protein response (e.g. DDIT3, ATF4) and NFKB signaling (e.g. NFKB1, NFKBIA) in ER stress and inflammation respectively. Islet single-cell RNA-seq profiling revealed strong but heterogeneous beta cell ER stress responses, including a distinct beta cell subset that highly expressed apoptotic genes. Epigenetic profiling uncovered 14,968 stress-responsive cis-regulatory elements (CREs; ~14%), the majority of which were stressor-specific, and revealed increased accessibility at binding sites of transcription factors that were induced upon stress (e.g. ATF4 for ER stress, IRF8 for inflammation). Seventy-six stress-responsive CREs overlapped known T2D-associated variants, including 20 residing within CREs that were more accessible upon ER stress. Among these, we linked the rs6917676 T2D risk allele (T) to increased in vivo accessibility of an islet ER stress-responsive CRE and allele-specific beta-cell nuclear factor binding in vitro. We showed that MAP3K5, the only ER stress-responsive gene in this locus, promotes beta cell apoptosis. Consistent with its pro-apoptotic and putative diabetogenic roles, MAP3K5 expression inversely correlated with beta cell abundance in human islets and was upregulated in beta cells from T2D donors. Together, this study provides new genome-wide insights into human islet stress responses and putative mechanisms of T2D genetic variants.

Dataset Information

The Role of Butyrate as a Histone Deacetylase Inhibitor in Protecting Pancreatic Beta Cells from IL-1β-Induced Dysfunction

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets