Daily injections of anakinra markedly improved clinical and laboratory manifestations in patients with neonatal-onset multisystem inflammatory disease, with or without CIAS1 mutations. (ClinicalTrials.gov number, NCT00069329 [ClinicalTrials.gov].).

T-cell depletion facilitates reduced immunosuppression following organ transplantation and has been suggested to be pro-tolerant. However, the characteristics of post-depletional T cells have not been evaluated as they relate to tolerance induction. We therefore studied patients undergoing profound T-cell depletion with alemtuzumab or rabbit anti-thymocyte globulin following renal transplantation, evaluating the phenotype and functional characteristics of their residual cells. Naïve T cells and T cells with potential regulatory function (CD4+CD25+) were not prevalent following aggressive depletion. Rather, post-depletion T cells were of a single phenotype (CD3+CD4+CD45RA-CD62L-CCR7-) consistent with depletion-resistant effector memory T cells that expanded in the first month and were uniquely prevalent at the time of rejection. These cells were resistant to steroids, deoxyspergualin or sirolimus in vitro, but were calcineurin-inhibitor sensitive. These data demonstrate that therapeutic depletion begets a limited population of functional memory-like T cells that are easily suppressed with certain immunosuppressants, but cannot be considered uniquely pro-tolerant.

T-cell depletion alone does not induce tolerance in humans. These data underscore a prominent role for early responding monocytes in human allograft rejection.

Polymorphisms in IL-2, IL-6, IL-10, and IFN-gamma genes are associated with their protein production after anti-CD3/CD28 stimulation. The profound effect of the IL-2 gene polymorphism in homozygous individuals may serve as a marker for those that could mount the most vigorous allo- or autoimmune responses, or perhaps become tolerant more easily.

Polymorphisms in the regulatory regions of cytokine genes are associated with high and low cytokine production and may modulate the magnitude of alloimmune responses following transplantation. Ethnicity influences allograft half-life and the incidence of acute and chronic rejection. We have questioned whether ethnic-based differences in renal allograft survival could be due in part to inheritance of cytokine polymorphisms. To address that question, we studied the inheritance patterns for polymorphisms in several cytokine genes (IL-2, IL-6, IL-10, TNF-a, TGF-b, and IFNg) within an ethnically diverse study population comprised of 216 Whites, 58 Blacks, 25 Hispanics, and 31 Asians. Polymorphisms were determined by allele-specific polymerase chain reaction and restriction fragment length analysis. We found striking differences in the distribution of cytokine polymorphisms among ethnic populations. Specifically, significant differences existed between Blacks and both Whites and Asians in the distribution of the polymorphic alleles for IL-2. Blacks, Hispanics and Asians demonstrated marked differences in the inheritance of IL-6 alleles and IL-10 genotypes that result in high expression when compared with Whites. Those of Asian descent exhibited an increase in IFN-g genotypes that result in low expression as compared to Whites. In contrast, we did not find significant ethnic-based differences in the inheritance of polymorphic alleles for TNF-a. Our results show that the inheritance of certain cytokine gene polymorphisms is strongly associated with ethnicity. These differences may contribute to the apparent influence of ethnicity on allograft outcome.

Objective To investigate a targeted set of biochemical biomarkers as predictors of clinically relevant osteoarthritis (OA) progression. Methods Eighteen biomarkers were measured at baseline, 12 months (M) and 24 M in serum (s) and/or urine (u) of cases (n=194) from the OA initiative cohort with knee OA and radiographic and persistent pain worsening from 24 to 48 M and controls (n=406) not meeting both end point criteria. Primary analyses used multivariable regression models to evaluate the association between biomarkers (baseline and time-integrated concentrations (TICs) over 12 and 24 M, transposed to z values) and case status, adjusted for age, sex, body mass index, race, baseline radiographic joint space width, Kellgren-Lawrence grade, pain and pain medication use. For biomarkers with adjusted p<0.1, the c-statistic (area under the curve (AUC)), net reclassification index and the integrated discrimination improvement index were used to further select for hierarchical multivariable discriminative analysis and to determine the most predictive and parsimonious model. Results The 24 M TIC of eight biomarkers significantly predicted case status (ORs per 1 SD change in biomarker): sCTXI 1.28, sHA 1.22, sNTXI 1.25, uC2C-HUSA 1.27, uCTXII, 1.37, uNTXI 1.29, uCTXIα 1.32, uCTXIβ 1.27. 24 M TIC of uCTXII (1.47–1.72) and uC2C-Human Urine Sandwich Assay (HUSA) (1.36–1.50) both predicted individual group status (pain worsening, joint space loss and their combination). The most predictive and parsimonious combinatorial model for case status consisted of 24 M TIC uCTXII, sHA and sNTXI (AUC 0.667 adjusted). Baseline uCTXII and uCTXIα both significantly predicted case status (OR 1.29 and 1.20, respectively). Conclusions Several systemic candidate biomarkers hold promise as predictors of pain and structural worsening of OA.

Human pancreatic islets are a major focus of diabetes research due to their key role in glucose homeostasis and their potential for transplantation in the treatment of type 1 diabetes. Currently, no comprehensive analysis of baseline or glucose-stimulated islet gene expression is available. Using oligonucleotide microarrays we analyzed isolated intact human islets incubated at low and high glucose. We identified approximately 6000 islet genes, several with clinical implications, as well as a number of glucose-regulated genes. Interestingly, two transforming growth factor beta (TGFbeta) superfamily members were highly regulated by glucose. One of them, PDF, was found to have a very high expression level compared to other TGFbeta superfamily members. Quantitative reverse transcriptase polymerase chain reaction confirmed these results and demonstrated that the highly expressed PDF was approximately 10-fold down- regulated by glucose while other TGFbeta superfamily members and target genes were up-regulated. These results suggest that a highly regulated TGFbeta signaling cascade exists in human islets, and that PDF may play a central role in islet biology. Since TGFbeta is involved in differentiation and immune modulation, this novel pathway may link glucose metabolism, immune response and development of human islets. We report here the first gene expression profile of intact human islets. These and similar analyses will provide better understanding of human islet biology and enhance the development of novel diabetes therapies.

Purpose We describe the outcome of the Biomarkers Consortium CSF Proteomics Project, a public-private partnership of government, academia, non-profit, and industry. The goal of this study was to evaluate a multiplexed mass spectrometry-based approach for the qualification of candidate Alzheimer’s Disease (AD) biomarkers using CSF samples from the AD Neuroimaging Initiative (ADNI). Experimental Design Reproducibility of sample processing, analytic variability, and ability to detect a variety of analytes of interest were thoroughly investigated. Multiple approaches to statistical analyses assessed whether panel analytes were associated with baseline pathology (MCI, AD) vs. Healthy Controls (CN) or associated with progression for MCI patients, and included: (i) univariate association analyses, (ii) univariate prediction models, (iii) exploratory multivariate analyses, and (iv) supervised multivariate analysis. Results A robust targeted mass spectrometry-based approach for the qualification of candidate AD biomarkers was developed. The results identified several peptides with potential diagnostic or predictive utility, with the most significant differences observed for the following peptides for differentiating (including peptides from Hemoglobin A (HBA), Hemoglobin B (HBB), and Superoxide dismutase (SODE)) or predicting (including peptides from Neuronal pentraxin-2 (NPTX2), Neurosecretory protein VGF (VGF), and Secretogranin-2 (SCG2)) progression vs. non-progression from mild cognitive impairment to AD. Conclusions and Clinical Relevance These data provide potential insights into the biology of CSF in AD and MCI progression and provide a novel tool for AD researchers and clinicians working to improve diagnostic accuracy, evaluation of treatment efficacy, and early diagnosis.