Proteostasis regulators modulate proteasomal activity and gene expression to attenuate multiple phenotypes in Fabry disease

The lysosomal storage disorder Fabry disease is characterized by a deficiency of the lysosomal enzyme \u3b1-Galactosidase A. The observation that missense variants in the encoding GLA gene often lead to structural destabilization, endoplasmic reticulum retention and proteasomal degradation of the misfolded, but otherwise catalytically functional enzyme has resulted in the exploration of alternative therapeutic approaches. In this context, we have investigated proteostasis regulators (PRs) for their potential to increase cellular enzyme activity, and to reduce the disease-specific accumulation of the biomarker globotriaosylsphingosine in patient-derived cell culture. The PRs also acted synergistically with the clinically approved 1-deoxygalactonojirimycine, demonstrating the potential of combination treatment in a therapeutic application. Extensive characterization of the effective PRs revealed inhibition of the proteasome and elevation of GLA gene expression as paramount effects. Further analysis of transcriptional patterns of the PRs exposed a variety of genes involved in proteostasis as potential modulators. We propose that addressing proteostasis is an effective approach to discover new therapeutic targets for diseases involving folding and trafficking-deficient protein mutants

RA-specific expression profiles and new candidate genes

Objective: To identify rheumatoid arthritis- (RA)-specific profiles of differentially expressed genes. Methods: Synovial tissues from RA and osteoarthritis (OA) patients and from normal joints were selected according to their disease-characteristic histology. Gene expression was analyzed using DNA microarrays (GeneChip; Unigene-array) and representational difference analysis (RDA). Data were validated on larger cohorts of patients by RT-PCR. Results: Nine hundred and eighty genes were significantly regulated in RA synovial tissue as compared with non-RA. Specialized cluster analysis identified a set of 312 genes as sufficient of unequivocally discriminating RA from non-RA patterns (class discovery). Genes of highest regulation were associated with leukocyte activation (chemokines, chemokine receptors, B- and T-cell genes), endothelial and angiogenic activation, tissue destruction and remodelling [MMP-3, BMP-4, TIMPs]. Interestingly, a large set of genes was down-regulated in RA (TGF-β superfamily, apoptosis-related genes, transcription factors). Osteopontin-like genes (n=46) — up-regulated in RA — and glutathione peroxidase-3-like genes (n=85) — down-regulated in RA — yielded the highest correlation coefficients (>0.94). Megakaryocyte stimulating factor (MSF), down-regulated in a subset of RA, may hold the key to subclassification: a loss-of-function mutation in the MSF-encoding gene leads to synovial hyperplasia in camptodactyly–arthropathy–coxa vara–pericarditis syndrome, and, as in RA, also to pericardial involvement. A further candidate, vitamin-D3-up-regulated protein-1 (VDUP-1), is regulated like MSF and predisposes to premature coronary artery disease when mutated, again a feature of a subset of RA. Conclusion: RA specific gene profiles were identified and are useful to improve diagnostics of the disease. Novel gene candidates not yet in the focus of RA pathogenesis have been identified that are likely to further the understanding of RA

Expression Profiling of PBMC-based Diagnostic Gene Markers Isolated from Vasculitis Patients

Vasculitis (angiitis) is a systemic autoimmune disease that often causes fatal symptoms. We aimed to isolate cDNA markers that would be useful for diagnosing not only vasculitis but also other autoimmune diseases. For this purpose, we used stepwise subtractive hybridization and cDNA microarray analyses to comprehensively isolate the genes whose expressions are augmented in peripheral blood mononuclear cells (PBMCs) pooled from vasculitis patients. Subsequently, we used quantitative real-time polymerase chain reaction (qRT–PCR) to examine the mRNA levels of each candidate gene in individual patients. These analyses indicated that seven genes exhibit remarkably augmented expression in many vasculitis patients. Of these genes, we analyzed G0/G1 switch gene 2 (G0S2) further because G0S2 expression is also enhanced in the PBMCs of patients with systemic lupus erythematodes (SLE). We generated G0S2 transgenic mice that ubiquitously overexpress human G0S2. Although we did not observe any obvious vasculitis-related histopathologic findings in these mice, these mice are unhealthy as they produce only few offspring and showed elevated serum levels of two autoimmunity-related antibodies, anti-nuclear antibody, and anti-double strand DNA antibody. Thus, our large-scale gene profiling study may help finding sensitive and specific DNA markers for diagnosing autoimmune diseases including vasculitis and SLE

Personalized medicine in psoriasis: developing a genomic classifier to predict histological response to Alefacept

<p>Abstract</p> <p>Background</p> <p>Alefacept treatment is highly effective in a select group patients with moderate-to-severe psoriasis, and is an ideal candidate to develop systems to predict who will respond to therapy. A clinical trial of 22 patients with moderate to severe psoriasis treated with alefacept was conducted in 2002-2003, as a mechanism of action study. Patients were classified as responders or non-responders to alefacept based on histological criteria. Results of the original mechanism of action study have been published. Peripheral blood was collected at the start of this clinical trial, and a prior analysis demonstrated that gene expression in PBMCs differed between responders and non-responders, however, the analysis performed could not be used to predict response.</p> <p>Methods</p> <p>Microarray data from PBMCs of 16 of these patients was analyzed to generate a treatment response classifier. We used a discriminant analysis method that performs sample classification from gene expression data, via "nearest shrunken centroid method". Centroids are the average gene expression for each gene in each class divided by the within-class standard deviation for that gene.</p> <p>Results</p> <p>A disease response classifier using 23 genes was created to accurately predict response to alefacept (12.3% error rate). While the genes in this classifier should be considered as a group, some of the individual genes are of great interest, for example, cAMP response element modulator (CREM), v-MAF avian musculoaponeurotic fibrosarcoma oncogene family (MAFF), chloride intracellular channel protein 1 (CLIC1, also called NCC27), NLR family, pyrin domain-containing 1 (NLRP1), and CCL5 (chemokine, cc motif, ligand 5, also called regulated upon activation, normally T expressed, and presumably secreted/RANTES).</p> <p>Conclusions</p> <p>Although this study is small, and based on analysis of existing microarray data, we demonstrate that a treatment response classifier for alefacept can be created using gene expression of PBMCs in psoriasis. This preliminary study may provide a useful tool to predict response of psoriatic patients to alefacept.</p

Robust computational reconstitution – a new method for the comparative analysis of gene expression in tissues and isolated cell fractions

BACKGROUND: Biological tissues consist of various cell types that differentially contribute to physiological and pathophysiological processes. Determining and analyzing cell type-specific gene expression under diverse conditions is therefore a central aim of biomedical research. The present study compares gene expression profiles in whole tissues and isolated cell fractions purified from these tissues in patients with rheumatoid arthritis and osteoarthritis. RESULTS: The expression profiles of the whole tissues were compared to computationally reconstituted expression profiles that combine the expression profiles of the isolated cell fractions (macrophages, fibroblasts, and non-adherent cells) according to their relative mRNA proportions in the tissue. The mRNA proportions were determined by trimmed robust regression using only the most robustly-expressed genes (1/3 to 1/2 of all measured genes), i.e. those showing the most similar expression in tissue and isolated cell fractions. The relative mRNA proportions were determined using several different chip evaluation methods, among which the MAS 5.0 signal algorithm appeared to be most robust. The computed mRNA proportions agreed well with the cell proportions determined by immunohistochemistry except for a minor number of outliers. Genes that were either regulated (i.e. differentially-expressed in tissue and isolated cell fractions) or robustly-expressed in all patients were identified using different test statistics. CONCLUSION: Robust Computational Reconstitution uses an intermediate number of robustly-expressed genes to estimate the relative mRNA proportions. This avoids both the exclusive dependence on the robust expression of individual, highly cell type-specific marker genes and the bias towards an equal distribution upon inclusion of all genes for computation

Validation Study of Existing Gene Expression Signatures for Anti-TNF Treatment in Patients with Rheumatoid Arthritis

So far, there are no means of identifying rheumatoid arthritis (RA) patients who will fail to respond to tumour necrosis factor blocking agents (anti-TNF), prior to treatment. We set out to validate eight previously reported gene expression signatures predicting therapy outcome. Genome-wide expression profiling using Affymetrix GeneChip Exon 1.0 ST arrays was performed on RNA isolated from whole blood of 42 RA patients starting treatment with infliximab or adalimumab. Clinical response according to EULAR criteria was determined at week 14 of therapy. Genes that have been reported to be associated with anti-TNF treatment were extracted from our dataset. K-means partition clustering was performed to assess the predictive value of the gene-sets. We performed a hypothesis-driven analysis of the dataset using eight existing gene sets predictive of anti-TNF treatment outcome. The set that performed best reached a sensitivity of 71% and a specificity of 61%, for classifying the patients in the current study. We successfully validated one of eight previously reported predictive expression profile. This replicated expression signature is a good starting point for developing a prediction model for anti-TNF treatment outcome that can be used in a daily clinical setting. Our results confirm that gene expression profiling prior to treatment is a useful tool to predict anti-TNF (non) response

The NAMPT inhibitor FK866 reverts the damage in spinal cord injury

<p>Abstract</p> <p>Background</p> <p>Emerging data implicate nicotinamide phosphoribosyl transferase (NAMPT) in the pathogenesis of cancer and inflammation. NAMPT inhibitors have proven beneficial in inflammatory animal models of arthritis and endotoxic shock as well as in autoimmune encephalitis. Given the role of inflammatory responses in spinal cord injury (SCI), the effect of NAMPT inhibitors was examined in this setting.</p> <p>Methods</p> <p>We investigated the effects of the NAMPT inhibitor FK866 in an experimental compression model of SCI.</p> <p>Results</p> <p>Twenty-four hr following induction of SCI, a significant functional deficit accompanied widespread edema, demyelination, neuron loss and a substantial increase in TNF-α, IL-1β, PAR, NAMPT, Bax, MPO activity, NF-κB activation, astrogliosis and microglial activation was observed. Meanwhile, the expression of neurotrophins BDNF, GDNF, NT3 and anti-apoptotic Bcl-2 decreased significantly. Treatment with FK866 (10 mg/kg), the best known and characterized NAMPT inhibitor, at 1 h and 6 h after SCI rescued motor function, preserved perilesional gray and white matter, restored anti-apoptotic and neurotrophic factors, prevented the activation of neutrophils, microglia and astrocytes and inhibited the elevation of NAMPT, PAR, TNF-α, IL-1β, Bax expression and NF-κB activity.</p> <p>We show for the first time that FK866, a specific inhibitor of NAMPT, administered after SCI, is capable of reducing the secondary inflammatory injury and partly reduce permanent damage. We also show that NAMPT protein levels are increased upon SCI in the perilesional area which can be corrected by administration of FK866.</p> <p>Conclusions</p> <p>Our findings suggest that the inflammatory component associated to SCI is the primary target of these inhibitors.</p