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PubMed | University of Amsterdam, Vitiligo Research Foundation, University of Colorado at Denver, Instituto Dermatologico San Gallicano and 14 more.
Type: Journal Article | Journal: Nature genetics | Year: 2016

Vitiligo is an autoimmune disease in which depigmented skin results from the destruction of melanocytes, with epidemiological association with other autoimmune diseases. In previous linkage and genome-wide association studies (GWAS1 and GWAS2), we identified 27 vitiligo susceptibility loci in patients of European ancestry. We carried out a third GWAS (GWAS3) in European-ancestry subjects, with augmented GWAS1 and GWAS2 controls, genome-wide imputation, and meta-analysis of all three GWAS, followed by an independent replication. The combined analyses, with 4,680 cases and 39,586 controls, identified 23 new significantly associated loci and 7 suggestive loci. Most encode immune and apoptotic regulators, with some also associated with other autoimmune diseases, as well as several melanocyte regulators. Bioinformatic analyses indicate a predominance of causal regulatory variation, some of which corresponds to expression quantitative trait loci (eQTLs) at these loci. Together, the identified genes provide a framework for the genetic architecture and pathobiology of vitiligo, highlight relationships with other autoimmune diseases and melanoma, and offer potential targets for treatment.


Seung S.K.,Earle A Chiles Research Institute | Curti B.D.,Earle A Chiles Research Institute | Curti B.D.,Providence Cancer Center | Crittenden M.,Earle A Chiles Research Institute | And 9 more authors.
Science Translational Medicine | Year: 2012

Preclinical models suggest that focal high-dose radiation can make tumors more immunogenic. We performed a pilot study of stereotactic body radiation therapy (SBRT) followed by high-dose interleukin-2 (IL-2) to assess safety and tumor response rate and perform exploratory immune monitoring studies. Patients with metastatic melanoma or renal cell carcinoma (RCC) who had received no previous medical therapy for metastatic disease were eligible. Patients received one, two, or three doses of SBRT (20 Gy per fraction) with the last dose administered 3 days before starting IL-2. IL-2 (600,000 IU per kilogram by means of intravenous bolus infusion) was given every 8 hours for a maximum of 14 doses with a second cycle after a 2-week rest. Patients with regressing disease received up to six IL-2 cycles. Twelve patients were included in the intent-to-treat analysis, and 11 completed treatment per the study design. Response Evaluation Criteria in Solid Tumors criteria were used to assess overall response in nonirradiated target lesions. Eight of 12 patients (66.6%) achieved a complete (CR) or partial response (PR) (1 CR and 7 PR). Six of the patients with PR on computed tomography had a CR by positron emission tomography imaging. Five of seven (71.4%) patients with melanoma had a PR or CR, and three of five (60%) with RCC had a PR. Immune monitoring showed a statistically significantly greater frequency of proliferating CD4+ T cells with an early activated effector memory phenotype (CD3+CD4+Ki67+CD25+FoxP3-CCR7-CD45RA- CD27+CD28+/-) in the peripheral blood of responding patients. SBRT and IL-2 can be administered safely. Because the response rate in patients with melanoma was significantly higher than expected on the basis of historical data, we believe that the combination and investigation of CD4+ effector memory T cells as a predictor of response warrant further study.


Siebert J.C.,CytoAnalytics | Wang L.,Oregon Medical Laser Center | Haley D.P.,Earle A Chiles Research Institute | Romer A.,Oregon Medical Laser Center | And 4 more authors.
Journal of Translational Medicine | Year: 2010

Background: The complex data sets generated by higher-order polychromatic flow cytometry experiments are a challenge to analyze. Here we describe Exhaustive Expansion, a data analysis approach for deriving hundreds to thousands of cell phenotypes from raw data, and for interrogating these phenotypes to identify populations of biological interest given the experimental context.Methods: We apply this approach to two studies, illustrating its broad applicability. The first examines the longitudinal changes in circulating human memory T cell populations within individual patients in response to a melanoma peptide (gp100209-2M) cancer vaccine, using 5 monoclonal antibodies (mAbs) to delineate subpopulations of viable, gp100-specific, CD8+ T cells. The second study measures the mobilization of stem cells in porcine bone marrow that may be associated with wound healing, and uses 5 different staining panels consisting of 8 mAbs each.Results: In the first study, our analysis suggests that the cell surface markers CD45RA, CD27 and CD28, commonly used in historical lower order (2-4 color) flow cytometry analysis to distinguish memory from naïve and effector T cells, may not be obligate parameters in defining central memory T cells (TCM). In the second study, we identify novel phenotypes such as CD29+CD31+CD56+CXCR4+CD90+Sca1-CD44+, which may characterize progenitor cells that are significantly increased in wounded animals as compared to controls.Conclusions: Taken together, these results demonstrate that Exhaustive Expansion supports thorough interrogation of complex higher-order flow cytometry data sets and aids in the identification of potentially clinically relevant findings. © 2010 Siebert et al; licensee BioMed Central Ltd.


Baker P.R.,University of Colorado at Denver | Baschal E.E.,University of Colorado at Denver | Fain P.R.,University of Colorado at Denver | Triolo T.M.,University of Colorado at Denver | And 8 more authors.
Journal of Clinical Endocrinology and Metabolism | Year: 2010

Context: Multiple autoimmune disorders (e.g. Addison's disease, type 1 diabetes, celiac disease) are associated with HLA-DR3, but it is likely that alleles of additional genes in linkage disequilibrium with HLA-DRB1 contribute to disease. Objective: The objective of the study was to characterize major histocompatability complex (MHC) haplotypes conferring extreme risk for autoimmune Addison's disease (AD). Design, Setting, and Participants: Eighty-six 21-hydroxylase autoantibody-positive, nonautoimmune polyendocrine syndrome type 1, Caucasian individuals collected from 1992 to 2009 with clinical AD from 68 families (12 multiplex and 56 simplex) were genotyped for HLA-DRB1, HLA-DQB1, MICA, HLA-B, and HLA-A as well as high density MHC single-nucleotide polymorphism (SNP) analysis for 34. Main Outcome Measures: AD and genotype were measured. Result: Ninety-seven percent of the multiplex individuals had both HLA-DR3 and HLA-B8 vs. 60% of simplex AD patients (P = 9.72 × 10 -4) and 13% of general population controls (P = 3.00 × 10 -19). The genotype DR3/DR4 with B8 was present in 85% of AD multiplex patients, 24% of simplex patients, and 1.5% of control individuals (P = 4.92 × 10-191). The DR3-B8 haplotype of AD patients had HLA-A1 less often (47%) than controls (81%, P = 7.00 × 10-5) and type 1 diabetes patients (73%, P = 1.93 × 10-3). Analysis of 1228 SNPs across the MHC for individuals with AD revealed a shorter conserved haplotype (3.8) with the loss of the extended conserved 3.8.1 haplotype approximately halfway between HLA-B and HLA-A. Conclusion: Extreme risk for AD, especially in multiplex families, is associated with haplotypic DR3 variants, in particular a portion (3.8) but not all of the conserved 3.8.1 haplotype. Copyright © 2010 by The Endocrine Society.


Baschal E.E.,University of Colorado at Denver | Baker P.R.,University of Colorado at Denver | Eyring K.R.,University of Colorado at Denver | Siebert J.C.,CytoAnalytics | And 2 more authors.
Diabetologia | Year: 2011

Aims/hypothesis: We investigated the risk associated with HLA-B*39 alleles in the context of specific HLA-DR/DQ haplotypes. Methods: We studied a readily available dataset from the Type 1 Diabetes Genetics Consortium that consists of 2,300 affected sibling pair families genotyped for both HLA alleles and 2,837 single nucleotide polymorphisms across the major histocompatibility complex region. Results: The B 3906 allele significantly enhanced the risk of type 1 diabetes when present on specific HLA-DR/DQ haplotypes (DRB1 0801-DQB1 0402: p = 1.6 × 10-6, OR 25.4; DRB1 0101-DQB1*0501: p = 4.9 × 10-5, OR 10.3) but did not enhance the risk of DRB1*0401-DQB1*0302 haplotypes. In addition, the B*3901 allele enhanced risk on the DRB1*1601-DQB1*0502 haplotype (p = 3.7 × 10-3, OR 7.2). Conclusions/interpretation: These associations indicate that the B*39 alleles significantly increase risk when present on specific HLA-DR/DQ haplotypes, and HLA-B typing in concert with specific HLA-DR/DQ genotypes should facilitate genetic prediction of type 1 diabetes, particularly in a research setting. © 2011 Springer-Verlag.


Baker P.R.,University of Colorado at Denver | Baschal E.E.,University of Colorado at Denver | Fain P.R.,University of Colorado at Denver | Nanduri P.,University of Colorado at Denver | And 8 more authors.
Journal of Clinical Endocrinology and Metabolism | Year: 2011

Context: Autoimmune Addison's disease (AD) is the major cause of primary adrenal failure in developed nations. Autoantibodies to 21-hydroxylase (21OH-AA) are associated with increased risk of progression to AD. Highest genetic risk is associated with the Major Histocompatibility region (MHC), specifically human leukocyte antigen (HLA)-DR3 haplotypes (containing HLA-B8) and HLA-DR4. Objective: The objective of the study was the further characterization of AD risk associated with MHC alleles. Design, Setting, and Participants: MHC genotypes were determined for HLA-DRB1, DQA1, DQB1, MICA, HLA-B, and HLA-A in 168 total individuals with 21OH-AA (85 with AD at referral and 83 with positive 21OH-AA but without AD at referral). Main Outcome Measure(s): Genotype was evaluated in 21OH-AA-positive individuals. Outcomes were compared with general population controls and type 1 diabetes patients. Results: In HLA-DR4+ individuals, HLA-B15 was found in only one of 55 (2%) with AD vs. 24 of 63 (40%) 21OH-AA-positive nonprogressors (P = 2 × 10-7) and 518 of 1558 (33%) HLA-DR4 patients with type 1 diabetes (P = 1 × 10-8). On prospective follow-up, none of the HLA-B15-positive, 21-hydroxylase-positive individuals progressed to AD vs. 25% non-HLA-B15 autoantibody-positive individuals by life table analysis (P = 0.03). Single nucleotide polymorphism analysis revealed the HLA-DR/DQ region associated with risk and HLA-B15 were separated by multiple intervening single-nucleotide polymorphism haplotypes. Conclusions: HLA-B15 is not associated with protection from 21OH-AA formation but is associated with protection from progression to AD in 21OH-AA-positive individuals. To our knowledge, this isoneof themostdramatic examples of genetic disease suppression in individuals who already have developed autoantibodies and of novel dominant suppression of an autoimmune disease by a class I HLA allele. Copyright © 2011 by The Endocrine Society.


Siebert J.C.,CytoAnalytics | Munsil W.,CytoAnalytics | Rosenberg-Hasson Y.,Stanford University | Davis M.M.,Stanford University | And 2 more authors.
Journal of Translational Medicine | Year: 2012

Background: Systems-level approaches are increasingly common in both murine and human translational studies. These approaches employ multiple high information content assays. As a result, there is a need for tools to integrate heterogeneous types of laboratory and clinical/demographic data, and to allow the exploration of that data by aggregating and/or segregating results based on particular variables (e.g., mean cytokine levels by age and gender).Methods: Here we describe the application of standard data warehousing tools to create a novel environment for user-driven upload, integration, and exploration of heterogeneous data. The system presented here currently supports flow cytometry and immunoassays performed in the Stanford Human Immune Monitoring Center, but could be applied more generally.Results: Users upload assay results contained in platform-specific spreadsheets of a defined format, and clinical and demographic data in spreadsheets of flexible format. Users then map sample IDs to connect the assay results with the metadata. An OLAP (on-line analytical processing) data exploration interface allows filtering and display of various dimensions (e.g., Luminex analytes in rows, treatment group in columns, filtered on a particular study). Statistics such as mean, median, and N can be displayed. The views can be expanded or contracted to aggregate or segregate data at various levels. Individual-level data is accessible with a single click. The result is a user-driven system that permits data integration and exploration in a variety of settings. We show how the system can be used to find gender-specific differences in serum cytokine levels, and compare them across experiments and assay types.Conclusions: We have used the tools and techniques of data warehousing, including open-source business intelligence software, to support investigator-driven data integration and mining of diverse immunological data. © 2012 Siebert et al; licensee BioMed Central Ltd.


Yabu J.M.,Stanford University | Siebert J.C.,CytoAnalytics | Maecker H.T.,Stanford University
PLoS ONE | Year: 2016

Background: Kidney transplantation is the most effective treatment for end-stage kidney disease. Sensitization, the formation of human leukocyte antigen (HLA) antibodies, remains a major barrier to successful kidney transplantation. Despite the implementation of desensitization strategies, many candidates fail to respond. Current progress is hindered by the lack of biomarkers to predict response and to guide therapy. Our objective was to determine whether differences in immune and gene profiles may help identify which candidates will respond to desensitization therapy. Methods and Findings: Single-cell mass cytometry by time-of-flight (CyTOF) phenotyping, gene arrays, and phosphoepitope flow cytometry were performed in a study of 20 highly sensitized kidney transplant candidates undergoing desensitization therapy. Responders to desensitization therapy were defined as 5% or greater decrease in cumulative calculated panel reactive antibody (cPRA) levels, and non-responders had 0% decrease in cPRA. Using a decision tree analysis, we found that a combination of transitional B cell and regulatory T cell (Treg) frequencies at baseline before initiation of desensitization therapy could distinguish responders from non-responders. Using a support vector machine (SVM) and longitudinal data, TRAF3IP3 transcripts and HLA-DR-CD38+CD4+ T cells could also distinguish responders from non-responders. Combining all assays in a multivariate analysis and elastic net regression model with 72 analytes, we identified seven that were highly interrelated and eleven that predicted response to desensitization therapy. Conclusions: Measuring baseline and longitudinal immune and gene profiles could provide a useful strategy to distinguish responders from non-responders to desensitization therapy. This study presents the integration of novel translational studies including CyTOF immunophenotyping in a multivariate analysis model that has potential applications to predict response to desensitization, select candidates, and personalize medicine to ultimately improve overall outcomes in highly sensitized kidney transplant candidates. © 2016 Yabu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


PubMed | CytoAnalytics and Stanford University
Type: Journal Article | Journal: PloS one | Year: 2015

While many age-associated immune changes have been reported, a comprehensive set of metrics of immune aging is lacking. Here we report data from 243 healthy adults aged 40-97, for whom we measured clinical and functional parameters, serum cytokines, cytokines and gene expression in stimulated and unstimulated PBMC, PBMC phenotypes, and cytokine-stimulated pSTAT signaling in whole blood. Although highly heterogeneous across individuals, many of these assays revealed trends by age, sex, and CMV status, to greater or lesser degrees. Age, then sex and CMV status, showed the greatest impact on the immune system, as measured by the percentage of assay readouts with significant differences. An elastic net regression model could optimally predict age with 14 analytes from different assays. This reinforces the importance of multivariate analysis for defining a healthy immune system. These data provide a reference for others measuring immune parameters in older people.


PubMed | CytoAnalytics and Stanford University
Type: Journal Article | Journal: PloS one | Year: 2016

Kidney transplantation is the most effective treatment for end-stage kidney disease. Sensitization, the formation of human leukocyte antigen (HLA) antibodies, remains a major barrier to successful kidney transplantation. Despite the implementation of desensitization strategies, many candidates fail to respond. Current progress is hindered by the lack of biomarkers to predict response and to guide therapy. Our objective was to determine whether differences in immune and gene profiles may help identify which candidates will respond to desensitization therapy.Single-cell mass cytometry by time-of-flight (CyTOF) phenotyping, gene arrays, and phosphoepitope flow cytometry were performed in a study of 20 highly sensitized kidney transplant candidates undergoing desensitization therapy. Responders to desensitization therapy were defined as 5% or greater decrease in cumulative calculated panel reactive antibody (cPRA) levels, and non-responders had 0% decrease in cPRA. Using a decision tree analysis, we found that a combination of transitional B cell and regulatory T cell (Treg) frequencies at baseline before initiation of desensitization therapy could distinguish responders from non-responders. Using a support vector machine (SVM) and longitudinal data, TRAF3IP3 transcripts and HLA-DR-CD38+CD4+ T cells could also distinguish responders from non-responders. Combining all assays in a multivariate analysis and elastic net regression model with 72 analytes, we identified seven that were highly interrelated and eleven that predicted response to desensitization therapy.Measuring baseline and longitudinal immune and gene profiles could provide a useful strategy to distinguish responders from non-responders to desensitization therapy. This study presents the integration of novel translational studies including CyTOF immunophenotyping in a multivariate analysis model that has potential applications to predict response to desensitization, select candidates, and personalize medicine to ultimately improve overall outcomes in highly sensitized kidney transplant candidates.

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