Adam Asare

Identification of a B cell signature associated with renal transplant tolerance in humans

Establishing long-term allograft acceptance without the requirement for continuous immunosuppression, a condition known as allograft tolerance, is a highly desirable therapeutic goal in solid organ transplantation. Determining which recipients would benefit from withdrawal or minimization of immunosuppression would be greatly facilitated by biomarkers predictive of tolerance. In this study, we identified the largest reported cohort to our knowledge of tolerant renal transplant recipients, as defined by stable graft function and receiving no immunosuppression for more than 1 year, and compared their gene expression profiles and peripheral blood lymphocyte subsets with those of subjects with stable graft function who are receiving immunosuppressive drugs as well as healthy controls. In addition to being associated with clinical and phenotypic parameters, renal allograft tolerance was strongly associated with a B cell signature using several assays. Tolerant subjects showed increased expression of multiple B cell differentiation genes, and a set of just 3 of these genes distinguished tolerant from nontolerant recipients in a unique test set of samples. This B cell signature was associated with upregulation of CD20 mRNA in urine sediment cells and elevated numbers of peripheral blood naive and transitional B cells in tolerant participants compared with those receiving immunosuppression. These results point to a critical role for B cells in regulating alloimmunity and provide a candidate set of genes for wider-scale screening of renal transplant recipients.

Efficacy of Remission-Induction Regimens for ANCA-Associated Vasculitis

BACKGROUND The 18-month efficacy of a single course of rituximab as compared with conventional immunosuppression with cyclophosphamide followed by azathioprine in patients with severe (organ-threatening) antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis is unknown. METHODS In a multicenter, randomized, double-blind, double-dummy, noninferiority trial, we compared rituximab (375 mg per square meter of body-surface area administered once a week for 4 weeks) followed by placebo with cyclophosphamide administered for 3 to 6 months followed by azathioprine for 12 to 15 months. The primary outcome measure was complete remission of disease by 6 months, with the remission maintained through 18 months. RESULTS A total of 197 patients were enrolled. As reported previously, 64% of the patients in the rituximab group, as compared with 53% of the patients in the cyclophosphamide-azathioprine group, had a complete remission by 6 months. At 12 and 18 months, 48% and 39%, respectively, of the patients in the rituximab group had maintained the complete remissions, as compared with 39% and 33%, respectively, in the comparison group. Rituximab met the prespecified criteria for noninferiority (P<0.001, with a noninferiority margin of 20%). There was no significant difference between the groups in any efficacy measure, including the duration of complete remission and the frequency or severity of relapses. Among the 101 patients who had relapsing disease at baseline, rituximab was superior to conventional immunosuppression at 6 months (P=0.01) and at 12 months (P=0.009) but not at 18 months (P=0.06), at which time most patients in the rituximab group had reconstituted B cells. There was no significant between-group difference in adverse events. CONCLUSIONS In patients with severe ANCA-associated vasculitis, a single course of rituximab was as effective as continuous conventional immunosuppressive therapy for the induction and maintenance of remissions over the course of 18 months. (Funded by the National Institute of Allergy and Infectious Diseases and others; RAVE ClinicalTrials.gov number, NCT00104299.)

Analysis of T-Cell Assays to Measure Autoimmune Responses in Subjects With Type 1 Diabetes Results of a Blinded Controlled Study

Type 1 diabetes is a chronic autoimmune disease mediated by autoreactive T-cells. Several experimental therapies targeting T-cells are in clinical trials. To understand how these therapies affect T-cell responses in vivo, assays that directly measure human T-cell function are needed. In a blinded, multicenter, case-controlled study conducted by the Immune Tolerance Network, we tested responses in an immunoblot and T-cell proliferative assay to distinguish type 1 diabetic patients from healthy control subjects. Peripheral blood cells from 39 healthy control subjects selected for DR4 and 23 subjects with recently diagnosed type 1 diabetes were studied. Autoantibody responses were measured in serum samples. Positive responses in both assays were more common in peripheral blood mononuclear cells from new-onset type 1 diabetic patients compared with control subjects. The proliferative, immunoblot, and autoantibody assays had sensitivities of 58, 91, and 78% with specificities of 94, 83, and 85%, respectively. When cellular assays were combined with autoantibody measurements, the sensitivity of the measurements was 75% with 100% specificity. We conclude that cellular assays performed on peripheral blood have a high degree of accuracy in discriminating responses in subjects with type 1 diabetes from healthy control subjects. They may be useful for assessment of cellular autoimmune responses involved in type 1 diabetes.

Differential gene expression profiles are dependent upon method of peripheral blood collection and RNA isolation

BackgroundRNA isolation and purification steps greatly influence the results of gene expression profiling. There are two commercially available products for whole blood RNA collection, PAXgene™ and Tempus™ blood collection tubes, and each comes with their own RNA purification method. In both systems the blood is immediately lysed when collected into the tube and RNA stabilized using proprietary reagents. Both systems enable minimal blood handling procedures thus minimizing the risk of inducing changes in gene expression through blood handling or processing. Because the RNA purification steps could influence the total RNA pool, we examined the impact of RNA isolation, using the PAXgene™ or Tempus™ method, on gene expression profiles.ResultsUsing microarrays as readout of RNA from stimulated whole blood we found a common set of expressed transcripts in RNA samples from either PAXgene™ or Tempus™. However, we also found several to be uniquely expressed depending on the type of collection tube, suggesting that RNA purification methods impact results of differential gene expression profiling. Specifically, transcripts for several known PHA-inducible genes, including IFNγ, IL13, IL2, IL3, and IL4 were found to be upregulated in stimulated vs. control samples when RNA was isolated using the ABI Tempus™ method, but not using the PAXgene™ method (p < 0.01, FDR corrected). Sequenom Quantiative Gene Expression (QGE) (SanDiego, CA) measures confirmed IL2, IL4 and IFNγ up-regulation in Tempus™ purified RNA from PHA stimulated cells while only IL2 was up-regulated using PAXgene™ purified (p < 0.05).ConclusionHere, we demonstrate that peripheral blood RNA isolation methods can critically impact differential expression results, particularly in the clinical setting where fold-change differences are typically small and there is inherent variability within biological cohorts. A modified method based upon the Tempus™ system was found to provide high yield, good post-hybridization array quality, low variability in expression measures and was shown to produce differential expression results consistent with the predicted immunologic effects of PHA stimulation.

Increased T Cell Proliferative Responses to Islet Antigens Identify Clinical Responders to Anti-CD20 Monoclonal Antibody (Rituximab) Therapy in Type 1 Diabetes

Type 1 diabetes mellitus is believed to be due to the autoimmune destruction of β-cells by T lymphocytes, but a single course of rituximab, a monoclonal anti-CD20 B lymphocyte Ab, can attenuate C-peptide loss over the first year of disease. The effects of B cell depletion on disease-associated T cell responses have not been studied. We compare changes in lymphocyte subsets, T cell proliferative responses to disease-associated target Ags, and C-peptide levels of participants who did (responders) or did not (nonresponders) show signs of β-cell preservation 1 y after rituximab therapy in a placebo-controlled TrialNet trial. Rituximab decreased B lymphocyte levels after four weekly doses of mAb. T cell proliferative responses to diabetes-associated Ags were present at baseline in 75% of anti-CD20– and 82% of placebo-treated subjects and were not different over time. However, in rituximab-treated subjects with significant C-peptide preservation at 6 mo (58%), the proliferative responses to diabetes-associated total (p = 0.032), islet-specific (p = 0.048), and neuronal autoantigens (p = 0.005) increased over the 12-mo observation period. This relationship was not seen in placebo-treated patients. We conclude that in patients with type 1 diabetes mellitus, anti-B cell mAb causes increased proliferative responses to diabetes Ags and attenuated β-cell loss. The way in which these responses affect the disease course remains unknown.

Neutrophil-Related Gene Expression and Low-Density Granulocytes Associated With Disease Activity and Response to Treatment in Antineutrophil Cytoplasmic Antibody-Associated Vasculitis

To discover biomarkers involved in the pathophysiology of antineutrophil cytoplasmic antibody–associated vasculitis (AAV) and to determine whether low‐density granulocytes (LDGs) contribute to gene expression signatures in AAV.

Per-Channel Basis Normalization Methods for Flow Cytometry Data

Between‐sample variation in high‐throughput flow cytometry data poses a significant challenge for analysis of large‐scale data sets, such as those derived from multicenter clinical trials. It is often hard to match biologically relevant cell populations across samples because of technical variation in sample acquisition and instrumentation differences. Thus, normalization of data is a critical step before analysis, particularly in large‐scale data sets from clinical trials, where group‐specific differences may be subtle and patient‐to‐patient variation common. We have developed two normalization methods that remove technical between‐sample variation by aligning prominent features (landmarks) in the raw data on a per‐channel basis. These algorithms were tested on two independent flow cytometry data sets by comparing manually gated data, either individually for each sample or using static gating templates, before and after normalization. Our results show a marked improvement in the overlap between manual and static gating when the data are normalized, thereby facilitating the use of automated analyses on large flow cytometry data sets. Such automated analyses are essential for high‐throughput flow cytometry.

Longitudinal Studies of a B Cell Derived Signature of Tolerance in Renal Transplant Recipients

Biomarkers of transplant tolerance would enhance the safety and feasibility of clinical tolerance trials and potentially facilitate management of patients receiving immunosuppression. To this end, we examined blood from spontaneously tolerant renal transplant recipients and patients enrolled in two interventional tolerance trials using flow cytometry and gene expression profiling. Using a previously reported tolerant cohort as well as newly identified tolerant patients, we confirmed our previous finding that tolerance was associated with increased expression of B cell–associated genes relative to immunosuppressed patients. This was not accounted for merely by an increase in total B cell numbers, but was associated with the increased frequencies of transitional and naïve B cells. Moreover, serial measurements of gene expression demonstrated that this pattern persisted over several years, although patients receiving immunosuppression also displayed an increase in the two most dominant tolerance‐related B cell genes, IGKV1D‐13 and IGLL‐1, over time. Importantly, patients rendered tolerant via induction of transient mixed chimerism, and those weaned to minimal immunosuppression, showed similar increases in IGKV1D‐13 as did spontaneously tolerant individuals. Collectively, these findings support the notion that alterations in B cells may be a common theme for tolerant kidney transplant recipients, and that it is a useful monitoring tool in prospective trials.

High‐throughput flow cytometry data normalization for clinical trials

Flow cytometry datasets from clinical trials generate very large datasets and are usually highly standardized, focusing on endpoints that are well defined apriori. Staining variability of individual makers is not uncommon and complicates manual gating, requiring the analyst to adapt gates for each sample, which is unwieldy for large datasets. It can lead to unreliable measurements, especially if a template‐gating approach is used without further correction to the gates. In this article, a computational framework is presented for normalizing the fluorescence intensity of multiple markers in specific cell populations across samples that is suitable for high‐throughput processing of large clinical trial datasets. Previous approaches to normalization have been global and applied to all cells or data with debris removed. They provided no mechanism to handle specific cell subsets. This approach integrates tightly with the gating process so that normalization is performed during gating and is local to the specific cell subsets exhibiting variability. This improves peak alignment and the performance of the algorithm. The performance of this algorithm is demonstrated on two clinical trial datasets from the HIV Vaccine Trials Network (HVTN) and the Immune Tolerance Network (ITN). In the ITN data set we show that local normalization combined with template gating can account for sample‐to‐sample variability as effectively as manual gating. In the HVTN dataset, it is shown that local normalization mitigates false‐positive vaccine response calls in an intracellular cytokine staining assay. In both datasets, local normalization performs better than global normalization. The normalization framework allows the use of template gates even in the presence of sample‐to‐sample staining variability, mitigates the subjectivity and bias of manual gating, and decreases the time necessary to analyze large datasets.

Power enhancement via multivariate outlier testing with gene expression arrays

Motivation: As the use of microarrays in human studies continues to increase, stringent quality assurance is necessary to ensure accurate experimental interpretation. We present a formal approach for microarray quality assessment that is based on dimension reduction of established measures of signal and noise components of expression followed by parametric multivariate outlier testing. Results: We applied our approach to several data resources. First, as a negative control, we found that the Affymetrix and Illumina contributions to MAQC data were free from outliers at a nominal outlier flagging rate of α=0.01. Second, we created a tunable framework for artificially corrupting intensity data from the Affymetrix Latin Square spike-in experiment to allow investigation of sensitivity and specificity of quality assurance (QA) criteria. Third, we applied the procedure to 507 Affymetrix microarray GeneChips processed with RNA from human peripheral blood samples. We show that exclusion of arrays by this approach substantially increases inferential power, or the ability to detect differential expression, in large clinical studies. Availability: http://bioconductor.org/packages/2.3/bioc/html/arrayMvout.html and http://bioconductor.org/packages/2.3/bioc/html/affyContam.html affyContam (credentials: readonly/readonly) Contact: aasare@immunetolerance.org; stvjc@channing.harvard.edu