Diabetes Susceptibility In Mice Research Articles

Sdef: an R package to synthesize lists of significant features in related experiments

BackgroundIn microarray studies researchers are often interested in the comparison of relevant quantities between two or more similar experiments, involving different treatments, tissues, or species. Typically each experiment reports measures of significance (e.g. p-values) or other measures that rank its features (e.g genes). Our objective is to find a list of features that are significant in all experiments, to be further investigated. In this paper we present an R package called sdef, that allows the user to quantify the evidence of communality between the experiments using previously proposed statistical methods based on the ranked lists of p-values. sdef implements two approaches that address this objective: the first is a permutation test of the maximal ratio of observed to expected common features under the hypothesis of independence between the experiments. The second approach, set in a Bayesian framework, is more flexible as it takes into account the uncertainty on the number of genes differentially expressed in each experiment.ResultsWe used sdef to re-analyze publicly available data i) on Type 2 diabetes susceptibility in mice on liver and skeletal muscle (two experiments); ii) on molecular similarities between mammalian sexes (three experiments). For the first example, we found between 68 and 104 genes commonly perturbed between the two tissues, using the two methods described above, and enrichment of the inflammation pathways, which are related to obesity and diabetes. For the second example, looking at three lists of features, we found 110 genes commonly perturbed between the three tissues, using the same two methods, and enrichment on genes involved in cell development.Conclusionssdef is an R package that provides researchers with an easy and powerful methodology to find lists of features commonly perturbed in two or more experiments to be further investigated. The package is provided with plots and tables to help the user visualize and interpret the results. The Windows, Linux and MacOS versions of the package, together with the documentation are available on the website http://cran.r-project.org/web/packages/sdef/index.html.

The genetics of diabetes susceptibility in mice.

The factors associated with a diabetes-susceptible genotype in mice exhibiting various forms of heritable glucose intolerance syndromes are discussed. Genetic models of insulin-dependent and non-insulin-dependent diabetes in mice are described. Although single gene mutations can be defined for each model that are major contributors to diabetogenic stress, polygenic interactions are required for the expression of a diabetic phenotype, and environmental factors are also contributory. Several strongly penetrant single gene mutations are capable of affecting obesity and insulin-resistant states. Analysis of inbred strain genomic interactions with one of these recessive obesity-producing genes, diabetes (db), suggests that development of a diabetic phenotype is dependent on the strength of an interaction between the db gene and sulfotransferase enzymes. Specifically, diabetes-susceptible vs. resistant inbred strain backgrounds can be distinguished by the extent to which the db mutation elicits an accelerated sequestration by sulfoconjugation of tissue estrogens while androgens remain free. In a male gender- (and Y chromosome-)associated model of transient glucose intolerance, stress as well as a requirement for both adrenal and testicular secretions are each components of the susceptibility background. In the obesity-associated diabetes models, autoimmunity, when it occurs, is a secondary reflection of pancreatic beta cell destruction. The nonobese diabetic (NOD) mouse, in contrast, represents a model in which autoimmunity against beta cells is a primary event in the development of insulin-dependent diabetes. In NOD mice, a gene that is either the unique class II gene in the major histocompatibility complex or is in linkage disequilibrium with this complex makes a major (recessivelike) contribution to diabetes susceptibility. However, diabetogenesis can be mediated only through a multifactorial interaction among this susceptibility locus and multiple unlinked genetic loci regulating immune responsiveness. In addition, the NOD mouse represents one of the best models of diabetes available for demonstrating a critical interaction between heredity and environmental factors. The polygenic nature of the various heritable forms of glucose intolerance syndromes in mice points to a comparable or even greater genetic heterogeneity underlying the major types of diabetes in humans.