The pathogenicity of self-antigen decreases at high levels of autoantigenicity: a computational approach

Quantifying immunoregulation by autoantigen-specific T-regulatory type 1 cells in mice with simultaneous hepatic and extra-hepatic autoimmune disorders

Nanoparticles (NPs) displaying autoimmune disease-relevant peptide-major histocompatibility complex class II molecules (pMHCII-NPs) trigger cognate T-regulatory type 1 (Tr1)-cell formation and expansion, capable of reversing organ-specific autoimmune responses. These pMHCII-NPs that display epitopes from mitochondrial protein can blunt the progression of both autoimmune hepatitis (AIH) and experimental autoimmune encephalomyelitis (EAE) in mice carrying either disease. However, with co-morbid mice having both diseases, these pMHCII-NPs selectively treat AIH. In contrast, pMHCII-NPs displaying central nervous system (CNS)-specific epitopes can efficiently treat CNS autoimmunity, both in the absence and presence of AIH, without having any effects on the progression of the latter. Here, we develop a compartmentalized population model of T-cells in co-morbid mice to identify the mechanisms by which Tr1 cells mediate organ-specific immunoregulation. We perform time-series simulations and bifurcation analyses to study how varying physiological parameters, including local cognate antigenic load and rates of Tr1-cell recruitment and retention, affect T-cell allocation and Tr1-mediated immunoregulation. Various regimes of behaviour, including 'competitive autoimmunity' where pMHCII-NP-treatment fails against both diseases, are identified and compared with experimental observations. Our results reveal that a transient delay in Tr1-cell recruitment to the CNS, resulting from inflammation-dependent Tr1-cell allocation, accounts for the liver-centric effects of AIH-specific pMHCII-NPs in co-morbid mice as compared with mice exclusively having EAE. They also suggest that cognate autoantigen expression and local Tr1-cell retention are key determinants of effective regulatory-cell function. These results thus provide new insights into the rules that govern Tr1-cell recruitment and their autoregulatory function.

The dual role of autoimmune regulator in maintaining normal expression level of tissue-restricted autoantigen in the thymus: A modeling investigation

The expression level of tissue-restricted autoantigens (TSA) in the thymus is crucial for the negative selection of autoreactive T cells during central tolerance. The autoimmune regulator factor (AIRE) plays an important role in the positive regulation of these TSA in medullary thymic epithelial cells and, consequently, in the negative selection of high-avidity autoreactive T cells. Recent studies, however, revealed that thymic islet cell autoantigen (ICA69) expression level in non-obese diabetic (NOD) mice, prone to developing type 1 diabetes (T1D), is reduced due to an increase in the binding affinity of AIRE to the Ica1-promoter region, which regulates ICA69 protein synthesis. This seemed to suggest that AIRE acts as a transcriptional repressor of Ica1 gene in the thymus, causing down regulation in the expression level of ICA69. To investigate this hypothesis and the apparent dual role of AIRE in negative selection, we develop a series of mathematical models of increasing complexity describing the temporal dynamics of self-reactive T cells, AIRE-mRNA and AIRE-(in)dependent thymic TSA-associated genes. The goal is to understand how changing the binding affinity of AIRE to Ica1-promoter affects both T-cell tolerance and the dual role of the transcription factor. Using stability analysis and numerical computations, we show that the model possesses a bistable switch, consisting of healthy and autoimmune states, in the expression level of Ica1 gene with respect to AIRE binding affinity, and that it can capture the experimentally observed dual role of AIRE. We also show that the model must contain a positive feedback loop exerted by T cells on AIRE expression (e.g., via lymphotoxin released by T cells) to produce bistability. Our results suggest that the expression-level of AIRE-mRNA in the healthy state is lower than that of the autoimmune state, and that negative selection is very sensitive to parameter perturbations in T-cell avidity.

Continuum model of T-cell avidity: Understanding autoreactive and regulatory T-cell responses in type 1 diabetes

Type 1 diabetes (T1D) is an autoimmune disease that results from the destruction of insulin-secreting pancreatic β cells, leading to abolition of insulin secretion and onset of diabetes. Cytotoxic CD4(+) and CD8(+) T cells, activated by antigen presenting cells (APCs), are both implicated in disease onset and progression. Regulatory T cells (Tregs), on the other hand, play a leading role in regulating immunological tolerance and resistant homoeostasis in T1D by suppressing effector T cells (Teffs). Recent data indicates that after activation, conventional Teffs transiently produce interleukin IL-2, a cytokine that acts as a growth factor for both Teffs and Tregs. Tregs suppress Teffs through IL-2 deprivation, competition and Teff conversion into inducible Tregs (iTregs). To investigate the interactions of these components during T1D progression, a mathematical model of T-cell dynamics is developed as a predictor of β-cell loss, with the underlying hypothesis that avidity of Teffs and Tregs, i.e., the binding affinity of T-cell receptors to peptide-major histocompatibility complexes on host cells, is continuum. The model is used to infer a set of criteria that determines susceptibility to T1D in high risk subjects. Our findings show that diabetes onset is guided by the absence of Treg-to-Teff dominance at specific high avidities, rather than over the whole range of avidity, and that the lack of overall dominance of Teffs-to-Tregs over time is the underlying cause of the "honeymoon period", the remission phase observed in some T1D patients. The model also suggests that competition between Teffs and Tregs is more effective than Teff-induction into iTregs in suppressing Teffs, and that a prolonged full width at half maximum of IL-2 release is a necessary condition for curbing disease onset. Finally, the model provides a rationale for observing rapid and slow progressors of T1D based on modest heterogeneity in the kinetic parameters.

The cross-priming capacity and direct presentation potential of an autoantigen are separable and inversely related properties

We investigated whether a prevalent epitope of the β-cell-specific autoantigen islet-specific glucose-6-phosphatase catalytic subunit-related protein (IGRP206-214) reaches regional Ag-presentation pathways via unprocessed polypeptide chains, as free IGRP206-214 peptide or via preformed IGRP206-214/K(d) complexes. This was accomplished by expressing bacterial artificial chromosome transgenes encoding wild-type (stable) or ubiquitinated (unstable) forms of IGRP in IGRP-deficient NOD mice carrying MHC class I-deficient β-cells, dendritic cells, or B cells. We investigated the ability of the pancreatic lymph nodes of these mice to prime naive IGRP206-214-reactive CD8(+) T cells in vivo, either in response to spontaneous Ag shedding, or to synchronized forms of β-cell necrosis or apoptosis. When IGRP was made unstable by targeting it for proteasomal degradation within β-cells, the cross-priming, autoimmune-initiating potential of this autoantigen (designated autoantigenicity) was impaired. Yet at the same time, the direct presentation, CTL-targeting potential of IGRP (designated pathogenicity) was enhanced. The appearance of IGRP206-214 in regional Ag-presentation pathways was dissociated from transfer of IGRP206-214 or IGRP206-214/K(d) from β cells to dendritic cells. These results indicate that autoantigenicity and pathogenicity are separable and inversely related properties and suggest that pathogenic autoantigens, capable of efficiently priming CTLs while marking target cells for CTL-induced killing, may have a critical balance of these two properties.

Unraveling the contribution of pancreatic beta-cell suicide in autoimmune type 1 diabetes

In type 1 diabetes, an autoimmune disease mediated by autoreactive T-cells that attack insulin-secreting pancreatic beta-cells, it has been suggested that disease progression may additionally require protective mechanisms in the target tissue to impede such auto-destructive mechanisms. We hypothesize that the autoimmune attack against beta-cells causes endoplasmic reticulum stress by forcing the remaining beta-cells to synthesize and secrete defective insulin. To rescue beta-cell from the endoplasmic reticulum stress, beta-cells activate the unfolded protein response to restore protein homeostasis and normal insulin synthesis. Here we investigate the compensatory role of unfolded protein response by developing a multi-state model of type 1 diabetes that takes into account beta-cell destruction caused by pathogenic autoreactive T-cells and apoptosis triggered by endoplasmic reticulum stress. We discuss the mechanism of unfolded protein response activation and how it counters beta-cell extinction caused by an autoimmune attack and/or irreversible damage by endoplasmic reticulum stress. Our results reveal important insights about the balance between beta-cell destruction by autoimmune attack (beta-cell homicide) and beta-cell apoptosis by endoplasmic reticulum stress (beta-cell suicide). It also provides an explanation as to why the unfolded protein response may not be a successful therapeutic target to treat type 1 diabetes.

Autoimmune responses in T1DM: quantitative methods to understand onset, progression, and prevention of disease

Understanding the physiological processes that underlie autoimmune disorders and identifying biomarkers to predict their onset are two pressing issues that need to be thoroughly sorted out by careful thought when analyzing these diseases. Type 1 diabetes (T1D) is a typical example of such diseases. It is mediated by autoreactive cytotoxic CD4⁺ and CD8⁺ T-cells that infiltrate the pancreatic islets of Langerhans and destroy insulin-secreting β-cells, leading to abnormal levels of glucose in affected individuals. The disease is also associated with a series of islet-specific autoantibodies that appear in high-risk subjects (HRS) several years prior to the onset of diabetes-related symptoms. It has been suggested that T1D is relapsing-remitting in nature and that islet-specific autoantibodies released by lymphocytic B-cells are detectable at different stages of the disease, depending on their binding affinity (the higher, the earlier they appear). The multifaceted nature of this disease and its intrinsic complexity make this disease very difficult to analyze experimentally as a whole. The use of quantitative methods, in the form of mathematical models and computational tools, to examine the disease has been a very powerful tool in providing predictions and insights about the underlying mechanism(s) regulating its onset and development. Furthermore, the models developed may have prognostic implications by aiding in the enrollment of HRS into trials for T1D prevention. In this review, we summarize recent advances made in determining T- and B-cell involvement in T1D using these quantitative approaches and delineate areas where mathematical modeling can make further contributions in unraveling certain aspect of this disease.

Evolutionary dynamics of human autoimmune disease genes and malfunctioned immunological genes

Background

One of the main issues of molecular evolution is to divulge the principles in dictating the evolutionary rate differences among various gene classes. Immunological genes have received considerable attention in evolutionary biology as candidates for local adaptation and for studying functionally important polymorphisms. The normal structure and function of immunological genes will be distorted when they experience mutations leading to immunological dysfunctions.

Results

Here, we examined the fundamental differences between the genes which on mutation give rise to autoimmune or other immune system related diseases and the immunological genes that do not cause any disease phenotypes. Although the disease genes examined are analogous to non-disease genes in product, expression, function, and pathway affiliation, a statistically significant decrease in evolutionary rate has been found in autoimmune disease genes relative to all other immune related diseases and non-disease genes. Possible ways of accumulation of mutation in the three steps of the central dogma (DNA-mRNA-Protein) have been studied to trace the mutational effects predisposed to disease consequence and acquiring higher selection pressure. Principal Component Analysis and Multivariate Regression Analysis have established the predominant role of single nucleotide polymorphisms in guiding the evolutionary rate of immunological disease and non-disease genes followed by m-RNA abundance, paralogs number, fraction of phosphorylation residue, alternatively spliced exon, protein residue burial and protein disorder.

Conclusions

Our study provides an empirical insight into the etiology of autoimmune disease genes and other immunological diseases. The immediate utility of our study is to help in disease gene identification and may also help in medicinal improvement of immune related disease.

Investigating the role of T-cell avidity and killing efficacy in relation to type 1 diabetes prediction

During the progression of the clinical onset of Type 1 Diabetes (T1D), high-risk individuals exhibit multiple islet autoantibodies and high-avidity T cells which progressively destroy beta cells causing overt T1D. In particular, novel autoantibodies, such as those against IA-2 epitopes (aa1-577), had a predictive rate of 100% in a 10-year follow up (rapid progressors), unlike conventional autoantibodies that required 15 years of follow up for a 74% predictive rate (slow progressors). The discrepancy between these two groups is thought to be associated with T-cell avidity, including CD8 and/or CD4 T cells. For this purpose, we build a series of mathematical models incorporating first one clone then multiple clones of islet-specific and pathogenic CD8 and/or CD4 T cells, together with B lymphocytes, to investigate the interaction of T-cell avidity with autoantibodies in predicting disease onset. These models are instrumental in examining several experimental observations associated with T-cell avidity, including the phenomenon of avidity maturation (increased average T-cell avidity over time), based on intra- and cross-clonal competition between T cells in high-risk human subjects. The model shows that the level and persistence of autoantibodies depends not only on the avidity of T cells, but also on the killing efficacy of these cells. Quantification and modeling of autoreactive T-cell avidities can thus determine the level of risk associated with each type of autoantibodies and the timing of T1D disease onset in individuals that have been tested positive for these autoantibodies. Such studies may lead to early diagnosis of the disease in high-risk individuals and thus potentially serve as a means of staging patients for clinical trials of preventive or interventional therapies far before disease onset.

On how monospecific memory-like autoregulatory CD8+ T cells can blunt diabetogenic autoimmunity: a computational approach

We have recently shown that during progression to autoimmune diabetes in NOD mice, memory autoreactive regulatory CD8(+) T cells arising from low-avidity precursors can be expanded to therapeutic levels using nanoparticles coated with disease-relevant peptide-major histocompatibility complexes (pMHCs). Here we examine the dynamics of memory autoregulatory CD8(+) T cells specific for islet-specific glucose-6-phosphatase catalytic subunit-related protein(206-214), a prevalent β cell autoantigen; their high-avidity counterparts (dominant effectors); and all other autoreactive non-islet-specific glucose-6-phosphatase catalytic subunit-related protein(206-214)-specific CD8(+) T cell specificities (subdominant effectors) in response to pMHC-coated nanoparticle (pMHC-nanoparticle) therapy. We combine experimental data with mathematical modeling to investigate the clonal competition dynamics of these T cell pools. To mimic the response diversity observed in NOD mice, we simulated many individual mice, using a wide range of parameters, and averaged the results as done experimentally. We find that under certain circumstances, pMHC-nanoparticle-induced expansion of autoregulatory CD8(+) T cells can effectively suppress the expansion of dominant and subdominant effectors simultaneously but, in some few cases, can lead to the substitution (or switching) of one effector population by another. The model supports the idea that disease suppression is based on the elimination of autoantigen-loaded APCs by the expanded autoregulatory CD8(+) T cells. The model also predicts that treatment strategies that operate by selectively inhibiting autoantigen-loaded APCs, such as the pMHC-nanoparticle approach, have the highest promise to blunt polyclonal, multiantigen-specific autoimmune responses in vivo without impairing systemic immunity.