Evie Melanitou

Investigation of secreted protein transcripts as early biomarkers for type 1 diabetes in the mouse model

Type 1 diabetes (T1D) represents a serious health burden in the world, complicated by the fact that disease onset can be preceded by a long time period without evident clinical signs. It would be then of critical importance to detect the disease in its early stages. In this direction, we seek here to identify early preinflammatory markers for autoimmune diabetes, mining our previously reported transcriptome data relevant to distinct early sub-phenotypes in the NOD mouse, associated with early insulin autoantibodies (E-IAA). More specifically we focus on secreted or transmembrane protein transcripts, identifying in this category 71 differentially expressed transcripts which are regulated at the early preinflammatory stages of T1D in the pancreatic lymph nodes (PLN). Following the expression patterns of these 71 transcripts, correspondence analysis (a multivariate analysis method) reveals a clear-cut segregation of the individual samples according to the early subphenotype used. Thus the 71 transcripts coding for secreted proteins constitute a candidate-set of predictive biomarkers for the development of autoimmune damage of the β cells of the pancreas. The majority of these genes have human orthologs and accordingly they represent potential candidate biomarkers for the human disease. In addition, for predictive purposes, the analysis reveals the possibility to reduce significantly the size of the candidate-set in practice, with various genes displaying identical expression profiles.

Functional Genomics in Early Autoimmunity

Abstract: The molecular mechanisms initiating the autoimmune process in type 1 diabetes mellitus (T1DM) remain unknown, and studies aiming to address this question have been compromised by the difficulty of predicting the disease at an early age both in humans and in animal models. An additional hindrance in selecting individuals at an early age has been the complex genetic inheritance of autoimmune diabetes, implicating not only several genes but also environmental factors. We have previously demonstrated the predictive value of insulin autoantibodies (IAAs) at an early age, between three to five weeks in the NOD mouse. Animals positive for early appearance of IAAs (E‐IAAs) develop autoimmune diabetes earlier. We showed a correlation between the presence of IAAs in the mothers during pregnancy, E‐IAAs in the litters, and the early appearance of T1DM. NOD mice, E‐IAA‐positive, within litters from IAA‐positive mothers during pregnancy, develop diabetes earlier and at a much greater rate than animals that are IAA‐negative and from IAA‐negative mothers. The molecular mechanisms responsible for this early autoimmune subphenotype were addressed by a global approach to differential gene expression analysis in the pancreatic lymph nodes (PaLNs). Although the data analysis is currently in progress, gene expression signatures were observed that are characteristic for PaLNs with regard to the presence or absence of IAAs. Overall, these data are consistent with the hypothesis of an early environmental influence from the autoimmune maternal environment on the genetic predisposition of the offspring, characterized by specific gene signatures leading to autoimmune disease.

Autoimmunity and autoinflammation: A systems view on signaling pathway dysregulation profiles

Introduction Autoinflammatory and autoimmune disorders are characterized by aberrant changes in innate and adaptive immunity that may lead from an initial inflammatory state to an organ specific damage. These disorders possess heterogeneity in terms of affected organs and clinical phenotypes. However, despite the differences in etiology and phenotypic variations, they share genetic associations, treatment responses and clinical manifestations. The mechanisms involved in their initiation and development remain poorly understood, however the existence of some clear similarities between autoimmune and autoinflammatory disorders indicates variable degrees of interaction between immune-related mechanisms. Methods Our study aims at contributing to a holistic, pathway-centered view on the inflammatory condition of autoimmune and autoinflammatory diseases. We have evaluated similarities and specificities of pathway activity changes in twelve autoimmune and autoinflammatory disorders by performing meta-analysis of publicly available gene expression datasets generated from peripheral blood mononuclear cells, using a bioinformatics pipeline that integrates Self Organizing Maps and Pathway Signal Flow algorithms along with KEGG pathway topologies. Results and conclusions The results reveal that clinically divergent disease groups share common pathway perturbation profiles. We identified pathways, similarly perturbed in all the studied diseases, such as PI3K-Akt, Toll-like receptor, and NF-kappa B signaling, that serve as integrators of signals guiding immune cell polarization, migration, growth, survival and differentiation. Further, two clusters of diseases were identified based on specifically dysregulated pathways: one gathering mostly autoimmune and the other mainly autoinflammatory diseases. Cluster separation was driven not only by apparent involvement of pathways implicated in adaptive immunity in one case, and inflammation in the other, but also by processes not explicitly related to immune response, but rather representing various events related to the formation of specific pathophysiological environment. Thus, our data suggest that while all of the studied diseases are affected by activation of common inflammatory processes, disease-specific variations in their relative balance are also identified.

[25]Selected methods related to the mouse as a model system

Publisher Summary The power of model systems for the study of genome structure and function and for the dissection of complex traits is, by now, well established. For a variety of reasons, the mouse remains the experimental mammal of choice for genetic research. The possibility of establishing crosses that exploit the many strains and mutations accumulated over the years constitutes just one reason for the extensive use of the mouse as a model system. This chapter presents insights into some of the strengths and originality of mouse genetics that may prove of help to nonmouse geneticists and highlights selected techniques that have contributed to the progress made in mouse genetics. The initial steps in positional cloning involve the definition of the genetic interval containing a disease gene or mutation. The size of the genetic interval depends on both the number of informative meioses and the number of polymorphic markers available for the region under study. The genus, Mus , has been divided into a complex species containing the four major biochemical groupings— Mus musculus domesticus , Mus m. musculus , Mus castaneus , and Mus bactrianus ,—all of which can be treated as subspecies, in addition to several distinct species such as the western Mediterranean mouse, M. spretus . The degree of fertility among different members of the genus ranges from complete sterility to reduced fertility and is correlated with the degree of taxon divergence.

Genetic architecture of early pre-inflammatory stage transcription signatures of autoimmune diabetes in the pancreatic lymph nodes of the NOD mouse reveals significant gene enrichment on chromosomes 6 and 7.

Autoimmune diseases are characterized by the stimulation of an excessive immune response to self-tissues by inner and/or outer organism factors. Common characteristics in their etiology include a complex genetic predisposition and environmental triggers as well as the implication of the major histocompatibility (MHC) locus on human chromosome 6p21. A restraint number of non-MHC susceptibility genes, part of the genetic component of type 1 diabetes have been identified in human and in animal models, while the complete spectrum of genes involved remains unknown. We elaborate herein patterns of chromosomal organization of 162 genes differentially expressed in the pancreatic lymph nodes of Non-Obese Diabetic mice, carefully selected by early sub-phenotypic evaluation (presence or absence of insulin autoantibodies). Chromosomal assignment of these genes revealed a non-random distribution on five chromosomes (47%). Significant gene enrichment was observed in particular for two chromosomes, 6 and 7. While a subset of these genes coding for secreted proteins showed significant enrichment on both chromosomes, the overall pool of genes was significantly enriched on chromosome 7. The significance of this unexpected gene distribution on the mouse genome is discussed in the light of novel findings indicating that genes affecting common diseases map to recombination “hotspot” regions of mammalian genomes. The genetic architecture of transcripts differentially expressed in specific stages of autoimmune diabetes offers novel venues towards our understanding of patterns of inheritance potentially affecting the pathological disease mechanisms.