Cate Speake

Systems Scale Interactive Exploration Reveals Quantitative and Qualitative Differences in Response to Influenza and Pneumococcal Vaccines

Systems immunology approaches were employed to investigate innate and adaptive immune responses to influenza and pneumococcal vaccines. These two non-live vaccines show different magnitudes of transcriptional responses at different time points after vaccination. Software solutions were developed to explore correlates of vaccine efficacy measured as antibody titers at day 28. These enabled a further dissection of transcriptional responses. Thus, the innate response, measured within hours in the peripheral blood, was dominated by an interferon transcriptional signature after influenza vaccination and by an inflammation signature after pneumococcal vaccination. Day 7 plasmablast responses induced by both vaccines was more pronounced after pneumococcal vaccination. Together, these results suggest that comparing global immune responses elicited by different vaccines will be critical to our understanding of the immune mechanisms underpinning successful vaccination.

A phenotypically and functionally distinct human TH2 cell subpopulation is associated with allergic disorders

A unique T helper cell signature in allergic patients isolates the pathogenic cells and provides a target for disease intervention. Defining damaging cells Although T helper type 2 (TH2) cells provide necessary protection from certain types of pathogens, they are also implicated in allergy pathogenesis. Until now, methods to distinguish pathogenic cells that are reactive to allergens from the rest of the TH2 population were very limited. Wambre et al. characterized a population of memory TH2 cells, termed TH2A, that were only found in allergic individuals. They were able to do so without the use of antigen-specific tetramers. These cells decreased in patients that benefited from allergen immunotherapy, indicating that targeting TH2A cells could disrupt allergic responses. Allergen-specific type 2 helper T (TH2) cells play a central role in initiating and orchestrating the allergic and asthmatic inflammatory response pathways. One major factor limiting the use of such atopic disease–causing T cells as both therapeutic targets and clinically useful biomarkers is the lack of an accepted methodology to identify and differentiate these cells from overall nonpathogenic TH2 cell types. We have described a subset of human memory TH2 cells confined to atopic individuals that includes all allergen-specific TH2 cells. These cells are terminally differentiated CD4+ T cells (CD27− and CD45RB−) characterized by coexpression of CRTH2, CD49d, and CD161 and exhibit numerous functional attributes distinct from conventional TH2 cells. Hence, we have denoted these cells with this stable allergic disease–related phenotype as the TH2A cell subset. Transcriptome analysis further revealed a distinct pathway in the initiation of pathogenic responses to allergen, and elimination of these cells is indicative of clinical responses induced by immunotherapy. Together, these findings identify a human TH2 cell signature in allergic diseases that could be used for response-monitoring and designing appropriate immunomodulatory strategies.

Copy number loss of the interferon gene cluster in melanomas is linked to reduced T cell infiltrate and poor patient prognosis.

While immunotherapies are rapidly becoming mainstays of cancer treatment, significant gaps remain in our understanding of how to optimally target them, alone or in combination. Here we describe a novel method to monitor levels of immune cells and pathways in expression data from solid tumors using pre-defined groups or modules of co-regulated immune genes. We show that expression of an interconnected sub-network of type I interferon-stimulated genes (ISGs) in melanomas at the time of diagnosis significantly predicted patient survival, as did, to a lesser extent, sub-networks of T helper/T regulatory and NK/T Cytotoxic cell genes. As a group, poor prognosis tumors with reduced ISG and immune gene levels exhibited significant copy number loss of the interferon gene cluster located at chromosome 9p21.3. Our studies demonstrate a link between type I interferon action and immune cell levels in melanomas, and suggest that therapeutic approaches augmenting both activities may be most beneficial.

An interactive web application for the dissemination of human systems immunology data

AbstractBackgroundSystems immunology approaches have proven invaluable in translational research settings. The current rate at which large-scale datasets are generated presents unique challenges and opportunities. Mining aggregates of these datasets could accelerate the pace of discovery, but new solutions are needed to integrate the heterogeneous data types with the contextual information that is necessary for interpretation. In addition, enabling tools and technologies facilitating investigators’ interaction with large-scale datasets must be developed in order to promote insight and foster knowledge discovery.MethodsState of the art application programming was employed to develop an interactive web application for browsing and visualizing large and complex datasets. A collection of human immune transcriptome datasets were loaded alongside contextual information about the samples.ResultsWe provide a resource enabling interactive query and navigation of transcriptome datasets relevant to human immunology research. Detailed information about studies and samples are displayed dynamically; if desired the associated data can be downloaded. Custom interactive visualizations of the data can be shared via email or social media. This application can be used to browse context-rich systems-scale data within and across systems immunology studies. This resource is publicly available online at [Gene Expression Browser Landing Page (https://gxb.benaroyaresearch.org/dm3/landing.gsp)]. The source code is also available openly [Gene Expression Browser Source Code (https://github.com/BenaroyaResearch/gxbrowser)].ConclusionsWe have developed a data browsing and visualization application capable of navigating increasingly large and complex datasets generated in the context of immunological studies. This intuitive tool ensures that, whether taken individually or as a whole, such datasets generated at great effort and expense remain interpretable and a ready source of insight for years to come.

Low HERV-K(C4) Copy Number Is Associated With Type 1 Diabetes

Complement component C4 (C4) is a highly variable complement pathway gene situated ∼500 kb from DRB1 and DQB1, the genes most strongly associated with many autoimmune diseases. Variations in C4 copy number (CN), length, and isotype create a highly diverse gene cluster in which insertion of an endogenous retrovirus in the ninth intron of C4, termed HERV-K(C4), is a notable component. We investigated the relationship between C4 variation/CN and type 1 diabetes. We found that individuals with type 1 diabetes have significantly fewer copies of HERV-K(C4) and that this effect is not solely due to linkage with known major histocompatibility complex class II susceptibility alleles. We show that HERV-K(C4) is a novel marker of type 1 diabetes that accounts for the disease association previously attributed to some key HLA-DQB1 alleles, raising the possibility that this retroviral insertion element contributes to functional protection against type 1 diabetes.

The Relationship of Immune Cell Signatures to Patient Survival Varies within and between Tumor Types.

Enhancing pre-existing anti-tumor immunity leads to therapeutic benefit for some patients, but why some tumors are more immunogenic than others remains unresolved. We took a unique systems approach to relate patient survival to immune gene expression in >3,500 tumor RNAseq profiles from a dozen tumor types. We found significant links between immune gene expression and patient survival in 8/12 tumor types, with tumors partitioned by gene expression comprising distinct molecular subtypes. T/NK cell genes were most clearly survival-related for melanoma, head and neck, and bladder tumors, whereas myeloid cell genes were most clearly survival-related with kidney and breast tumors. T/NK or myeloid cell gene expression was linked to poor prognosis in bladder and kidney tumors, respectively, suggesting tumor-specific immunosuppressive checkpoints. Our results suggest new biomarkers for existing cancer immunotherapies and identify targets for new immunotherapies.

NETosis‐associated serum biomarkers are reduced in type 1 diabetes in association with neutrophil count

As the immune pathways involved in the pathogenesis of type 1 diabetes (T1D) are not fully understood, biomarkers implicating novel mechanisms of disease are of great interest and call for independent evaluation. Recently, it was reported that individuals with T1D display dramatic elevations in circulating components of neutrophil extracellular traps (NETs), indicating a potential role for NETosis in T1D. Our aim was to evaluate further the potential of NET‐associated proteins as novel circulating biomarkers in T1D. We tested serum from subjects with T1D (n = 44) with a median age of 26·5 years and a median duration of 2·2 years, along with 38 age‐matched controls. T1D subjects did not show elevations in either neutrophil elastase (NE) or proteinase 3 (PR3), as reported previously. In fact, both NE and PR3 levels were reduced significantly in T1D subjects, particularly in subjects within 3 years of diagnosis, consistent with the known reduction in neutrophil counts in recent‐onset T1D. Indeed, levels of both NE and PR3 correlated with absolute neutrophil counts. Therefore, while not ruling out potential local or transient spikes in NETosis activity, the levels of these serum markers do not support a role for systemically elevated NETosis in the T1D population we studied. Rather, a modest reduction in these markers may reflect other important aspects of disease activity associated with reduced neutrophil numbers.

Measurement of Pro-Islet Amyloid Polypeptide (1–48) in Diabetes and Islet Transplants

Context Islet amyloid is a feature of β-cell failure in type 2 diabetes (T2D) and type 1 diabetes (T1D) recipients of islet transplants. Islet amyloid contains islet amyloid polypeptide (IAPP; amylin), a circulating peptide that is produced in β cells by processing of its precursor, proIAPP1-67, via an intermediate form, proIAPP1-48. Elevated proinsulin to C-peptide ratios in the plasma of persons with diabetes suggest defects in β-cell prohormone processing. Objective Determine whether plasma levels of precursor forms of IAPP are elevated in diabetes. Design, Setting, and Patients We developed an immunoassay to detect proIAPP1-48 in human plasma, and we determined the ratio of proIAPP1-48 to mature IAPP in subjects with T1D, T2D, recipients of islet transplants, and healthy controls. Results The proIAPP1-48 immunoassay had a limit of detection of 0.18 ± 0.06 pM and cross-reactivity with intact proIAPP1-67 <15%. Healthy individuals had plasma concentrations of proIAPP1-48 immunoreactivity of 1.5 ± 0.2 pM and a proIAPP1-48 to total IAPP ratio of 0.28 ± 0.03. Plasma concentrations of proIAPP1-48 immunoreactivity were not significantly different in subjects with T2D but were markedly increased in T1D recipients of islet transplants. Children and adults with T1D had reduced mature IAPP levels relative to age-matched controls but an elevated ratio of proIAPP1-48 to total IAPP. Conclusion The β cells in T1D and islet transplants have impaired processing of the proIAPP1-48 intermediate. The ratio of proIAPP1-48-to-IAPP immunoreactivity may have value as a biomarker of β-cell stress and dysfunction.

Single-Cell RNA Sequencing Reveals Expanded Clones of Islet Antigen-Reactive CD4 + T Cells in Peripheral Blood of Subjects with Type 1 Diabetes

The significance of islet Ag-reactive T cells found in peripheral blood of type 1 diabetes (T1D) subjects is unclear, partly because similar cells are also found in healthy control (HC) subjects. We hypothesized that key disease-associated cells would show evidence of prior Ag exposure, inferred from expanded TCR clonotypes, and essential phenotypic properties in their transcriptomes. To test this, we developed single-cell RNA sequencing procedures for identifying TCR clonotypes and transcript phenotypes in individual T cells. We applied these procedures to analysis of islet Ag-reactive CD4+ memory T cells from the blood of T1D and HC individuals after activation with pooled immunodominant islet peptides. We found extensive TCR clonotype sharing in Ag-activated cells, especially from individual T1D subjects, consistent with in vivo T cell expansion during disease progression. The expanded clonotype from one T1D subject was detected at repeat visits spanning >15 mo, demonstrating clonotype stability. Notably, we found no clonotype sharing between subjects, indicating a predominance of “private” TCR specificities. Expanded clones from two T1D subjects recognized distinct IGRP peptides, implicating this molecule as a trigger for CD4+ T cell expansion. Although overall transcript profiles of cells from HC and T1D subjects were similar, profiles from the most expanded clones were distinctive. Our findings demonstrate that islet Ag-reactive CD4+ memory T cells with unique Ag specificities and phenotypes are expanded during disease progression and can be detected by single-cell analysis of peripheral blood.

Evaluation of Candidate Biomarkers of Type 1 Diabetes via the Core for Assay Validation

Recognizing an increasing need for biomarkers that predict clinical outcomes in type 1 diabetes (T1D), JDRF, a major funding organization for T1D research, recently instituted the Core for Assay Validation (CAV) to accelerate the translation of promising assays from discovery to clinical implementation via a process of coordinated evaluation of biomarkers. In this model, the CAV facilitates the validation of candidate assay methods as well as qualification of proposed biomarkers for a specific clinical use in well-characterized patients. We describe here a CAV-driven pilot project aimed at identifying biomarkers that predict the rate of decline in beta cell function after diagnosis. In a formalized pipeline, candidate assays are first assessed for general rationale, technical precision, and biological associations in a cross-sectional cohort. Those with the most favorable characteristics are then applied to placebo arm subjects of T1D intervention trials to assess their predictive correlation with beta cell function. We outline a go/no-go process for advancing candidate assays in a defined qualification pipeline that also allows for the discovery of novel predictive biomarker combinations. This strategy could be a model for other collaborative biomarker development efforts in and beyond T1D.