Inflammatory proteins in plasma are associated with severity of Alzheimer's disease.

Markers of Alzheimer's disease (AD) are being widely sought with a number of studies suggesting blood measures of inflammatory proteins as putative biomarkers. Here we report findings from a panel of 27 cytokines and related proteins in over 350 subjects with AD, subjects with Mild Cognitive Impairment (MCI) and elderly normal controls where we also have measures of longitudinal change in cognition and baseline neuroimaging measures of atrophy. In this study, we identify five inflammatory proteins associated with evidence of atrophy on MR imaging data particularly in whole brain, ventricular and entorhinal cortex measures. In addition, we observed six analytes that showed significant change (over a period of one year) in people with fast cognitive decline compared to those with intermediate and slow decline. One of these (IL-10) was also associated with brain atrophy in AD. In conclusion, IL-10 was associated with both clinical and imaging evidence of severity of disease and might therefore have potential to act as biomarker of disease progression.

Human ß-cell killing by autoreactive preproinsulin-specific CD8 T cells is predominantly granule-mediated with the potency dependent upon T-cell receptor avidity.

The end-stage immunopathology of type 1 diabetes resulting in ß-cell destruction appears to be strongly dominated by cytotoxic CD8 T lymphocytes (CD8 T cells). However, the mechanism of cytotoxicity used by autoreactive CD8 T cells in the human setting remains unknown. Using type 1 diabetes patient-derived preproinsulin-specific CD8 T-cell clones recognizing either an HLA-A2 (A*0201) or HLA-A24 (A*2402)-restricted epitope (peptide of preproinsulin [PPI](15-24), ALWGPDPAAA; or PPI(3-11), LWMRLLPLL), we assessed the use of conventional mediators of cytotoxicity in the destruction of human ß-cells in vitro compared with virus-specific cytotoxic CD8 T-cell clones. We show that PPI-specific CD8 T-cell clones are mainly reliant upon cytotoxic degranulation for inducing ß-cell death. Furthermore, we find that in comparison with virus-specific CD8 T cells, there are differences in the killing potency of PPI-specific CD8 T cells that are not due to cell-intrinsic differences, but rather are mediated by differences in strength of signaling by peptide-HLA ligands. The study highlights the regulation of ß-cell killing as a potential point for therapeutic control, including the possibility of blocking autoreactive CD8 T-cell function without impacting upon general immune competence.

Circulating preproinsulin signal peptide-specific CD8 T cells restricted by the susceptibility molecule HLA-A24 are expanded at onset of type 1 diabetes and kill ß-cells.

Type 1 diabetes results from T cell-mediated ß-cell destruction. The HLA-A*24 class I gene confers significant risk of disease and early onset. We tested the hypothesis that HLA-A24 molecules on islet cells present preproinsulin (PPI) peptide epitopes to CD8 cytotoxic T cells (CTLs). Surrogate ß-cell lines secreting proinsulin and expressing HLA-A24 were generated and their peptide ligandome examined by mass spectrometry to discover naturally processed and HLA-A24-presented PPI epitopes. A novel PPI epitope was identified and used to generate HLA-A24 tetramers and examine the frequency of PPI-specific T cells in new-onset HLA-A*24(+) patients and control subjects. We identified a novel naturally processed and HLA-A24-presented PPI signal peptide epitope (PPI(3-11); LWMRLLPLL). HLA-A24 tetramer analysis reveals a significant expansion of PPI(3-11)-specific CD8 T cells in the blood of HLA-A*24(+) recent-onset patients compared with HLA-matched control subjects. Moreover, a patient-derived PPI(3-11)-specific CD8 T-cell clone shows a proinflammatory phenotype and kills surrogate ß-cells and human HLA-A*24(+) islet cells in vitro. These results indicate that the type 1 diabetes susceptibility molecule HLA-A24 presents a naturally processed PPI signal peptide epitope. PPI-specific, HLA-A24-restricted CD8 T cells are expanded in patients with recent-onset disease. Human islet cells process and present PPI(3-11), rendering themselves targets for CTL-mediated killing.

Combinatorial markers of mild cognitive impairment conversion to Alzheimer's disease--cytokines and MRI measures together predict disease progression.

Progression of people presenting with Mild Cognitive Impairment (MCI) to dementia is not certain and it is not possible for clinicians to predict which people are most likely to convert. The inability of clinicians to predict progression limits the use of MCI as a syndrome for treatment in prevention trials and, as more people present with this syndrome in memory clinics, and as earlier diagnosis is a major goal of health services, this presents an important clinical problem. Some data suggest that CSF biomarkers and functional imaging using PET might act as markers to facilitate prediction of conversion. However, both techniques are costly and not universally available. The objective of our study was to investigate the potential added benefit of combining biomarkers that are more easily obtained in routine clinical practice to predict conversion from MCI to Alzheimer's disease. To explore this we combined automated regional analysis of structural MRI with analysis of plasma cytokines and chemokines and compared these to measures of APOE genotype and clinical assessment to assess which best predict progression. In a total of 205 people with MCI, 77 of whom subsequently converted to Alzheimer's disease, we find biochemical markers of inflammation to be better predictors of conversion than APOE genotype or clinical measures (Area under the curve (AUC) 0.65, 0.62, 0.59 respectively). In a subset of subjects who also had MRI scans the combination of serum markers of inflammation and MRI automated imaging analysis provided the best predictor of conversion (AUC 0.78). These results show that the combination of imaging and cytokine biomarkers provides an improvement in prediction of MCI to AD conversion compared to either datatype alone, APOE genotype or clinical data and an accuracy of prediction that would have clinical utility.

TRANSPATH: an information resource for storing and visualizing signaling pathways and their pathological aberrations.

TRANSPATH is a database about signal transduction events. It provides information about signaling molecules, their reactions and the pathways these reactions constitute. The representation of signaling molecules is organized in a number of orthogonal hierarchies reflecting the classification of the molecules, their species-specific or generic features, and their post-translational modifications. Reactions are similarly hierarchically organized in a three-layer architecture, differentiating between reactions that are evidenced by individual publications, generalizations of these reactions to construct species-independent 'reference pathways' and the 'semantic projections' of these pathways. A number of search and browse options allow easy access to the database contents, which can be visualized with the tool PathwayBuildertrade mark. The module PathoSign adds data about pathologically relevant mutations in signaling components, including their genotypes and phenotypes. TRANSPATH and PathoSign can be used as encyclopaedia, in the educational process, for vizualization and modeling of signal transduction networks and for the analysis of gene expression data. TRANSPATH Public 6.0 is freely accessible for users from non-profit organizations under http://www.gene-regulation.com/pub/databases.html.