Walter and Eliza Hall Institute of Medical Research

About: Walter and Eliza Hall Institute of Medical Research is a nonprofit organization based out in Melbourne, Victoria, Australia. It is known for research contribution in the topics: Antigen & Immune system. The organization has 5012 authors who have published 10620 publications receiving 873561 citations.

Induction of autoimmune diabetes by oral administration of autoantigen.

Abstract: An antigen administered orally can induce immunological tolerance to a subsequent challenge with the same antigen. Evidence has been provided for the efficacy of this approach in the treatment of human autoimmune diseases such as rheumatoid arthritis and multiple sclerosis. However, oral administration of autoantigen in mice was found to induce a cytotoxic T lymphocyte response that could lead to the onset of autoimmune diabetes. Thus, feeding autoantigen can cause autoimmunity, which suggests that caution should be used when applying this approach to the treatment of human autoimmune diseases.

The cellular and molecular basis for malaria parasite invasion of the human red blood cell.

Abstract: Malaria is a major disease of humans caused by protozoan parasites from the genus Plasmodium. It has a complex life cycle; however, asexual parasite infection within the blood stream is responsible for all disease pathology. This stage is initiated when merozoites, the free invasive blood-stage form, invade circulating erythrocytes. Although invasion is rapid, it is the only time of the life cycle when the parasite is directly exposed to the host immune system. Significant effort has, therefore, focused on identifying the proteins involved and understanding the underlying mechanisms behind merozoite invasion into the protected niche inside the human erythrocyte.

Gene dosage--limiting role of Aire in thymic expression, clonal deletion, and organ-specific autoimmunity.

Abstract: Inactivation of the autoimmune regulator (Aire) gene causes a rare recessive disorder, autoimmune polyendocrine syndrome 1 (APS1), but it is not known if Aire-dependent tolerance mechanisms are susceptible to the quantitative genetic changes thought to underlie more common autoimmune diseases. In mice with a targeted mutation, complete loss of Aire abolished expression of an insulin promoter transgene in thymic epithelium, but had no effect in pancreatic islets or the testes. Loss of one copy of Aire diminished thymic expression of the endogenous insulin gene and the transgene, resulting in a 300% increase in islet-reactive CD4 T cells escaping thymic deletion in T cell receptor transgenic mice, and dramatically increased progression to diabetes. Thymic deletion induced by antigen under control of the thyroglobulin promoter was abolished in Aire homozygotes and less efficient in heterozygotes, providing an explanation for thyroid autoimmunity in APS1. In contrast, Aire deficiency had no effect on thymic deletion to antigen controlled by a systemic H-2K promoter. The sensitivity of Aire-dependent thymic deletion to small reductions in function makes this pathway a prime candidate for more subtle autoimmune quantitative trait loci, and suggests that methods to increase Aire activity would be a potent strategy to lower the incidence of organ-specific autoimmunity.

Empirical array quality weights in the analysis of microarray data

Abstract: Assessment of array quality is an essential step in the analysis of data from microarray experiments. Once detected, less reliable arrays are typically excluded or "filtered" from further analysis to avoid misleading results. In this article, a graduated approach to array quality is considered based on empirical reproducibility of the gene expression measures from replicate arrays. Weights are assigned to each microarray by fitting a heteroscedastic linear model with shared array variance terms. A novel gene-by-gene update algorithm is used to efficiently estimate the array variances. The inverse variances are used as weights in the linear model analysis to identify differentially expressed genes. The method successfully assigns lower weights to less reproducible arrays from different experiments. Down-weighting the observations from suspect arrays increases the power to detect differential expression. In smaller experiments, this approach outperforms the usual method of filtering the data. The method is available in the limma software package which is implemented in the R software environment. This method complements existing normalisation and spot quality procedures, and allows poorer quality arrays, which would otherwise be discarded, to be included in an analysis. It is applicable to microarray data from experiments with some level of replication.