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Description
Systemic lupus erytematosus (SLE) is an autoimmune disease where the immune system is reactive to self antigens resulting in manifestations like glomerulonephritis and arthritis. The immune system also affects the central nervous system (known as CNS-SLE) leading to neuropsychiatric manifestations such as depression, cognitive impairment, psychosis and seizures. A subset of pathogenic brain-reactive autoantibodies (BRAA) is hypothesized to bind to integral membrane brain proteins, affecting their function, leading to CNS-SLE. I have tested this BRAA hypothesis, using our lupus-mouse model the MRL/lpr mice, and have found it to be a reasonable explanation for some of the manifestations of CNS-SLE. Even when the MRL/lpr had a reduced autoimmune phenotype, their low BRAA sera levels correlated with CNS involvement. The correlation existed between BRAA levels to integral membrane protein and depressive-like behavior. These results were the first to show a correlation between behavioral changes and BRAA levels from brain membrane antigen as oppose to cultured neuronal cells. More accurate means of predicting and diagnosing lupus and CNS-SLE is necessary. Using microarray technology I was able to determine peptide sets that could be predictive and diagnostic of lupus and each specific CNS manifestation. To knowledge no test currently exists that can effectively diagnose lupus and distinguish between each CNS manifestations. Using the peptide sets, I was able to determine possible natural protein biomarkers for each set as well as for five monoclonal BRAA from one MRL/lpr. These biomarkers can provide specific targets for therapy depending on the manifestation. It was necessary to investigate how these BRAA enter the brain. I hypothesized that substance P plays a role in altering the blood-brain barrier (BBB) allowing these BRAA to enter and affect brain function, when bound to its neurokinin-1 receptor (NK-1R). Western blotting results revealed an increase in the levels of NK-1R in the brain of the MRL/lpr compared to the MRL/mp. These MRL/lpr with increased levels of both NK-1R and BRAA displayed CNS dysfunction. Together, these results demonstrate that NK-1R may play a role in CNS manifestations. Overall, the research conducted here, add to the role that BRAA are playing in CNS-lupus.
ContributorsWilliams, Stephanie (Author) / Hoffman, Steven A (Thesis advisor) / Conrad, Cheryl (Committee member) / Chen, Julian (Committee member) / Orchinik, Miles (Committee member) / Arizona State University (Publisher)
Created2011
Description
Immunosignaturing is a new immunodiagnostic technology that uses random-sequence peptide microarrays to profile the humoral immune response. Though the peptides have little sequence homology to any known protein, binding of serum antibodies may be detected, and the pattern correlated to disease states. The aim of my dissertation is to analyze the factors affecting the binding patterns using monoclonal antibodies and determine how much information may be extracted from the sequences. Specifically, I examined the effects of antibody concentration, competition, peptide density, and antibody valence. Peptide binding could be detected at the low concentrations relevant to immunosignaturing, and a monoclonal's signature could even be detected in the presences of 100 fold excess naive IgG. I also found that peptide density was important, but this effect was not due to bivalent binding. Next, I examined in more detail how a polyreactive antibody binds to the random sequence peptides compared to protein sequence derived peptides, and found that it bound to many peptides from both sets, but with low apparent affinity. An in depth look at how the peptide physicochemical properties and sequence complexity revealed that there were some correlations with properties, but they were generally small and varied greatly between antibodies. However, on a limited diversity but larger peptide library, I found that sequence complexity was important for antibody binding. The redundancy on that library did enable the identification of specific sub-sequences recognized by an antibody. The current immunosignaturing platform has little repetition of sub-sequences, so I evaluated several methods to infer antibody epitopes. I found two methods that had modest prediction accuracy, and I developed a software application called GuiTope to facilitate the epitope prediction analysis. None of the methods had sufficient accuracy to identify an unknown antigen from a database. In conclusion, the characteristics of the immunosignaturing platform observed through monoclonal antibody experiments demonstrate its promise as a new diagnostic technology. However, a major limitation is the difficulty in connecting the signature back to the original antigen, though larger peptide libraries could facilitate these predictions.
ContributorsHalperin, Rebecca (Author) / Johnston, Stephen A. (Thesis advisor) / Bordner, Andrew (Committee member) / Taylor, Thomas (Committee member) / Stafford, Phillip (Committee member) / Arizona State University (Publisher)
Created2011