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The cytokine network in inflammatory bowel disease (IBD) is a complex, dynamic system that plays an important role in regulating mucosal innate and adaptive immune responses. While several studies have been done to evaluate immunomodulatory profiles in murine IBD, they have been limited to a relatively small number of cytokines that do not take into account its dependency of the interplay of multiple factors, and therefore the diagnostic potential of their cytokine profiles have been inconclusive.MethodsA novel approach of comprehensive serum multiplex cytokine profiling with biometric immunosandwich ELISA's was used to describe the modulation of 16 Th1, Th2, Th17 cytokines and chemokines in both acute and chronic murine models of DSS and TNBS-induced colitis. Advanced multivariate discriminant functional analyses (DFA) was used to identify statistically interrelated sets of variables with the most significant power to discriminate among the groups. Profiles of multiple cytokines seen systemically were also validated locally in colonic mucosa using Western blot analysis and fluorescent immunohistochemistry.ResultsDistinctive disease-specific cytokine profiles were identified with significant correlations to disease activity and duration of disease. TNBS colitis exhibits heightened Th1-Th17 response (increased IL-12 and IL-17) as the disease becomes chronic. In contrast, DSS colitis switches from a Th1-Th17-mediated acute inflammation (increased TNF-α, IL6, IL-17, and KC) to a predominant Th2-mediated inflammatory response (increase in IL-4 and IL-10 and concomitant decrease in TNF-α, IL6, IL-17, and KC) in the chronic state. Moreover, DFA identified discriminatory cytokine profiles that can be sufficiently used to distinguish unaffected controls from diseases, and one disease type from another. IL-6 and IL-12 stratified gender-associated disease activity in chronic colitis.ConclusionsOur studies provide insight into disease immunopathogenesis and illustrate the significant potential of utilizing multiplex cytokine profiles and bioinformatics as diagnostic tools in IBD.

Background Cardiovascular (CV) risk estimation calculators for the general population underperform in patients with rheumatoid arthritis (RA). The purpose of this study was to identify relevant protein biomarkers that could be added to traditional CV risk calculators to improve the capacity of coronary artery calcification (CAC) prediction in individuals with RA. In a second step, we quantify the improvement of this prediction of CAC when these circulating biomarkers are added to standard risk scores. Methods A panel of 141 serum and plasma proteins, which represent a broad base of both CV and RA biology, were evaluated and prioritized as candidate biomarkers. Of these, 39 proteins were selected and measured by commercial ELISA or quantitative mass spectroscopy in 561 individuals with RA in whom a measure of CAC and frozen sera were available. The patients were randomly split 50:50 into a training/validation cohort. Discrimination (using area under the receiver operator characteristic curves) and re-classification (through net reclassification improvement and integrated discrimination improvement calculation) analyses were performed first in the training cohort and replicated in the validation cohort, to estimate the increase in prediction accuracy for CAC using the ACA/AHA (American College of Cardiology and the American Heart Association) score with, compared to without, addition of these circulating biomarkers. Results The model containing ACC/AHA score plus cytokines (osteopontin, cartilage glycoprotein-39, cystatin C, and chemokine (C–C motif) ligand 18) and plus quantitative mass spectroscopy biomarkers (serpin D1, paraoxonase, and clusterin) had a statistically significant positive net reclassifications index and integrated discrimination improvement for the prediction of CAC, using ACC/AHA score without any biomarkers as the reference category. These results were confirmed in the validation cohort. Conclusion In this exploratory analysis, the addition of several circulating CV and RA biomarkers to a standard CV risk calculator yielded significant improvements in discrimination and reclassification for the presence of CAC in individuals with RA.

Objectives To evaluate the performance of individual biomarkers and a multi-biomarker disease activity (MBDA) score in the early rheumatoid arthritis (RA) patient population from the computer assisted management in early rheumatoid arthritis (CAMERA) study. Methods Twenty biomarkers were measured in the CAMERA cohort, in which patients were treated with either intensive or conventional methotrexate-based treatment strategies. The MBDA score was calculated using the concentrations of 12 biomarkers (SAA, IL-6, TNF-RI, VEGF-A, MMP-1, YKL-40, MMP-3, EGF, VCAM-1, leptin, resistin and CRP) according to a previously trained algorithm. The performance of the scores was evaluated relative to clinical disease activity assessments. Change in MBDA score over time was assessed by paired Wilcoxon rank sum test. Logistic regression was used to evaluate the ability of disease activity measures to predict radiographic progression. Results The MBDA score had a significant correlation with the disease activity score based on 28 joints-C reactive protein (DAS28-CRP) (r=0.72; p<0.001) and an area under the receiver operating characteristic curve for distinguishing remission/low from moderate/high disease activity of 0.86 (p<0.001) using a DAS28-CRP cut-off of 2.7. In multivariate analysis the MBDA score, but not CRP, was an independent predictor of disease activity measures. Additionally, mean (SD) MBDA score decreased from 53 (18) at baseline to 39 (16) at 6 months in response to study therapy (p<0.0001). Neither MBDA score nor clinical variables were predictive of radiographic progression. Conclusions This multi-biomarker test performed well in the assessment of disease activity in RA patients in the CAMERA study. Upon further validation, this test could be used to complement currently available disease activity measures and improve patient care and outcomes.

Pyrin, the familial Mediterranean fever protein, is found in association with the cytoskeleton in myeloid/monocytic cells and modulates IL-1β processing, NF-κB activation, and apoptosis. These effects are mediated in part through cognate interactions with the adaptor protein ASC, which shares an N-terminal motif with pyrin. We sought additional upstream regulators of inflammation by using pyrin as the bait in yeast two-hybrid assays. We now show that proline serine threonine phosphatase-interacting protein [PSTPIP1, or CD2-binding protein 1 (CD2BP1)], a tyrosine-phosphorylated protein involved in cytoskeletal organization, also interacts with pyrin. Recently, PSTPIP1/CD2BP1 mutations were shown to cause the syndrome of pyogenic arthritis, pyoderma gangrenosum, and acne (PAPA), a dominantly inherited autoinflammatory disorder mediated predominantly by granulocytes. Endogenous PSTPIP1/CD2BP1 and pyrin are coexpressed in monocytes and granulocytes and can be coimmunoprecipitated from THP-1 cells. The B box segment of pyrin was necessary and the B box/coiled-coil segment sufficient for this interaction, whereas the SH3 and coiled-coil domains of PSTPIP1/CD2BP1 were both necessary, but neither was sufficient, for pyrin binding. The Y344F PSTPIP1/CD2BP1 mutation, which blocks tyrosine phosphorylation, was associated with a marked reduction in pyrin binding in pervanadate-treated cells. PAPA-associated A230T and E250Q PSTPIP1/CD2BP1 mutations markedly increased pyrin binding as assayed by immunoprecipitation and, relative to WT, these mutants were hyperphosphorylated when coexpressed with c-Abl kinase. Consistent with the hypothesis that these mutations exert a dominant-negative effect on the previously reported activity of pyrin, we found increased IL-1β production by peripheral blood leukocytes from a clinically active PAPA patient with the A230T PSTPIP1/CD2BP1 mutation and in cell lines transfected with both PAPA-associated mutants.

The first goal of this study was to measure the oxidative stress (OS) and relate it to lipoprotein variables in 35 renal patients before dialysis (CKD), 37 on hemodialysis (HD) and 63 healthy subjects. The method for OS was based on the ratio of cholesteryl esters (CE) containing C18/C16 fatty acids (R2) measured by gas chromatography (GC) which is a simple, direct, rapid and reliable procedure. The second goal was to investigate and identify a triacylglycerol peak on GC, referred to as TG48 (48 represents the sum of the three fatty acids carbon chain lengths) which was markedly increased in renal patients compared to healthy controls. We measured TG48 in patients and controls. Mass spectrometry (MS) and MS twice in tandem were used to analyze the fatty acid composition of TG48. MS showed that TG48 was abundant in saturated fatty acids (SFAs) that were known for their pro-inflammatory property. TG48 was significantly and inversely correlated with OS. Renal patients were characterized by higher OS and inflammation than healthy subjects. Inflammation correlated strongly with TG, VLDL-cholesterol, apolipoprotein (apo) C-III and apoC-III bound to apoB-containing lipoproteins, but not with either total cholesterol or LDL-cholesterol.In conclusion, we have discovered a new inflammatory factor, TG48. It is characterized with TG rich in saturated fatty acids. Renal patients have increased TG48 than healthy controls.

Disease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment. To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis. Candidate serum protein biomarkers were selected from extensive literature screens, bioinformatics databases, mRNA expression and protein microarray data. Quantitative assays were identified and optimized for measuring candidate biomarkers in RA patient sera. Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity (e.g. the Disease Activity Score 28-C-Reactive Protein [DAS28-CRP], a validated metric commonly used in clinical trials) and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity, assessed by correlation to DAS and area under the receiver operating characteristic curve for classification of low vs. moderate/high disease activity. The effect of comorbidities on the MBDA score was evaluated using linear models with adjustment for multiple hypothesis testing. 130 candidate biomarkers were tested in feasibility studies and 25 were selected for algorithm training. Multi-biomarker statistical models outperformed individual biomarkers at estimating disease activity. Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography. The final MBDA algorithm uses 12 biomarkers to generate an MBDA score between 1 and 100. No significant effects on the MBDA score were found for common comorbidities. We followed a stepwise approach to develop a quantitative serum-based measure of RA disease activity, based on 12-biomarkers, which was consistently associated with clinical disease activity levels.

Gene profiling studies provide important information for key molecules relevant to a disease but are less informative of protein-protein interactions, post-translational modifications and regulation by targeted subcellular localization. Integration of genomic data and construction of functional gene networks may provide additional insights into complex diseases such as systemic lupus erythematosus (SLE). We analyzed gene expression microarray data of bone marrow mononuclear cells (BMMCs) from 20 SLE patients (11 with active disease) and 10 controls. Gene networks were constructed using the bioinformatic tool Ingenuity Gene Network Analysis. In SLE patients, comparative analysis of BMMCs genes revealed a network with 19 central nodes as major gene regulators including ERK, JNK, and p38 MAP kinases, insulin, Ca(2+) and STAT3. Comparison between active versus inactive SLE identified 30 central nodes associated with immune response, protein synthesis, and post-transcriptional modification. A high degree of identity between networks in active SLE and non-Hodgkin's lymphoma (NHL) patients was found, with overlapping central nodes including kinases (MAPK, ERK, JNK, PKC), transcription factors (NF-kappaB, STAT3), and insulin. In validation studies, western blot analysis in splenic B cells from 5-month-old NZB/NZW F1 lupus mice showed activation of STAT3, ITGB2, HSPB1, ERK, JNK, p38, and p32 kinases, and downregulation of FOXO3 and VDR compared to normal C57Bl/6 mice. Gene network analysis of lupus BMMCs identified central gene regulators implicated in disease pathogenesis which could represent targets of novel therapies in human SLE. The high similarity between active SLE and NHL networks provides a molecular basis for the reported association of the former with lymphoid malignancies.

Since Figure 3D is composed of proteins that originate from five separate blots, we are adding the relevant β-actin controls for each of the blot available in the corrected figure. (2013) Correction: Gene Network Analysis of Bone Marrow Mononuclear Cells Reveals Activation of Multiple Kinase Pathways in Human Systemic Lupus Erythematosus.

A major virulence factor of Bacillus anthracis is the anthrax Lethal Toxin (LeTx), a bipartite toxin composed of Protective Antigen and Lethal Factor. Systemic administration of LeTx to laboratory animals leads to death associated with vascular leakage and pulmonary edema. In this study, we investigated whether systemic exposure of mice to LeTx would induce gene expression changes associated with vascular/capillary leakage in lung tissue. We observed enhanced susceptibility of A/J mice to death by systemic LeTx administration compared to the C57BL/6 strain. LeTx-induced groups of both up- and down-regulated genes were observed in mouse lungs 6 h after systemic administration of wild type toxin compared to lungs of mice exposed to an inactive mutant form of the toxin. Lungs of the less susceptible C57BL/6 strain showed 80% fewer differentially expressed genes compared to lungs of the more sensitive A/J strain. Expression of genes known to regulate vascular permeability was modulated by LeTx in the lungs of the more susceptible A/J strain. Unexpectedly, the largest set of genes with altered expression was immune specific, characterized by the up-regulation of lymphoid genes and the down-regulation of myeloid genes. Transcripts encoding neutrophil chemoattractants, modulators of tumor regulation and angiogenesis were also differentially expressed in both mouse strains. These studies provide new directions for the investigation of vascular leakage and pulmonary edema induced by anthrax LeTx.