Oral desensitization therapy for peanut allergy induces dynamic changes in peanut-specific immune responses.

BACKGROUND: The PALISADE study, an international, phase 3 trial of peanut oral immunotherapy (POIT) with AR101, resulted in desensitization in children and adolescents who were highly allergic to peanut. An improved understanding of the immune mechanism induced in response to food allergen immunotherapy would enable more informed and effective therapeutic strategies. Our main purpose was to examine the immunological changes in blood samples from a subset of peanut-allergic individuals undergoing oral desensitization immunotherapy with AR101. METHODS: Blood samples obtained as part of enrollment screening and at multiple time points during PALISADE study were used to assess basophil and CD4+ T-cell reactivity to peanut. RESULTS: The absence of clinical reactivity to the entry double-blinded placebo-controlled peanut challenge (DBPCFC) was accompanied by a significantly lower basophil sensitivity and T-cell reactivity to peanut compared with DBPCFC reactors. At baseline, peanut-reactive TH2A cells were observed in many but not all peanut-allergic patients and their level in peripheral blood correlates with T-cell reactivity to peanut and with serum peanut-specific IgE and IgG4 levels. POIT reshaped circulating peanut-reactive T-cell responses in a subset-dependent manner. Changes in basophil and T-cell responses to peanut closely paralleled clinical benefits to AR101 therapy and resemble responses in those with lower clinical sensitivity to peanut. However, no difference in peanut-reactive Treg cell frequency was observed between groups. CONCLUSION: Oral desensitization therapy with AR101 leads to decreased basophil sensitivity to peanut and reshapes peanut-reactive T effector cell responses supporting its potential as an immunomodulatory therapy.

The Collaborative Aging Research Using Technology Initiative: An Open, Sharable, Technology-Agnostic Platform for the Research Community.

INTRODUCTION: Future digital health research hinges on methodologies to conduct remote clinical assessments and in-home monitoring. The Collaborative Aging Research Using Technology (CART) initiative was introduced to establish a digital technology research platform that could widely assess activity in the homes of diverse cohorts of older adults and detect meaningful change longitudinally. This paper reports on the built end-to-end design of the CART platform, its functionality, and the resulting research capabilities. METHODS: CART platform development followed a principled design process aiming for scalability, use case flexibility, longevity, and data privacy protection while allowing sharability. The platform, comprising ambient technology, wearables, and other sensors, was deployed in participants' homes to provide continuous, long-term (months to years), and ecologically valid data. Data gathered from CART homes were sent securely to a research server for analysis and future data sharing. RESULTS: The CART system was created, iteratively tested, and deployed to 232 homes representing four diverse cohorts (African American, Latinx, low-income, and predominantly rural-residing veterans) of older adults (n = 301) across the USA. Multiple measurements of wellness such as cognition (e.g., mean daily computer use time = 160-169 min), physical mobility (e.g., mean daily transitions between rooms = 96-155), sleep (e.g., mean nightly sleep duration = 6.3-7.4 h), and level of social engagement (e.g., reports of overnight visitors = 15-45%) were collected across cohorts. CONCLUSION: The CART initiative resulted in a minimally obtrusive digital health-enabled system that met the design principles while allowing for data capture over extended periods and can be widely used by the research community. The ability to monitor and manage health digitally within the homes of older adults is an important alternative to in-person assessments in many research contexts. Further advances will come with wider, shared use of the CART system in additional settings, within different disease contexts, and by diverse research teams.

Things Are Changing so Fast: Integrative Technology for Preserving Cognitive Health and Community History.

Background and Objectives: Multimodal interventions are increasingly targeting multiple cognitive decline risk factors. However, technology remains mostly adjunctive, largely prioritizes age relevancy over cultural relevancy, and often targets individual health without lasting, community-wide deliverables. Meanwhile, African Americans remain overburdened by cognitive risk factors yet underrepresented in cognitive health and technology studies. The Sharing History through Active Reminiscence and Photo-imagery (SHARP) program increases physical, social, and cognitive activity within a culturally meaningful context that produces community deliverables-an oral history archive and cognitive health education. Design and Methods: The SHARP application was tested with 19 African Americans ≥55 years, aiming for an easy, integrative, and culturally meaningful experience. The application guided triads in walks 3 times weekly for 6 months in Portland, Oregon's historically Black neighborhoods; local historical images prompted recorded conversational reminiscence. Focus groups evaluated factors influencing technology acceptance-attitudes about technology, usefulness, usability, and relevance to integrating program goals. Thematic analysis guided qualitative interpretation. Results: Technology acceptance was influenced by group learning, paper-copy replicas for reluctant users, ease of navigation, usefulness for integrating and engaging in health behaviors, relevance to integrating individual benefit and the community priority of preserving history amidst gentrification, and flexibility in how the community uses deliverables. Perceived community benefits sustained acceptance despite intermittent technology failure. Discussion and Implications: We offer applicable considerations for brain health technology design, implementation, and deliverables that integrate modalities, age, and cultural relevance, and individual and community benefit for more meaningful, and thus more motivated community engagement.

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data.

An end-to-end suite of technologies has been established for the unobtrusive and continuous monitoring of health and activity changes occurring in the daily life of older adults over extended periods of time. The technology is aggregated into a system that incorporates the principles of being minimally obtrusive, while generating secure, privacy protected, continuous objective data in real-world (home-based) settings for months to years. The system includes passive infrared presence sensors placed throughout the home, door contact sensors installed on exterior doors, connected physiological monitoring devices (such as scales), medication boxes, and wearable actigraphs. Driving sensors are also installed in participants' cars and computer (PC, tablet or smartphone) use is tracked. Data is annotated via frequent online self-report options that provide vital information with regard to the data that is difficult to infer via sensors such as internal states (e.g., pain, mood, loneliness), as well as data referent to activity pattern interpretation (e.g., visitors, rearranged furniture). Algorithms have been developed using the data obtained to identify functional domains key to health or disease activity monitoring, including mobility (e.g., room transitions, steps, gait speed), physiologic function (e.g., weight, body mass index, pulse), sleep behaviors (e.g., sleep time, trips to the bathroom at night), medication adherence (e.g., missed doses), social engagement (e.g., time spent out of home, time couples spend together), and cognitive function (e.g., time on computer, mouse movements, characteristics of online form completion, driving ability). Change detection of these functions provides a sensitive marker for the application in health surveillance of acute illnesses (e.g., viral epidemic) to the early detection of prodromal dementia syndromes. The system is particularly suitable for monitoring the efficacy of clinical interventions in natural history studies of geriatric syndromes and in clinical trials.

A collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification.

The increased application of high-throughput approaches in translational research has expanded the number of publicly available data repositories. Gathering additional valuable information contained in the datasets represents a crucial opportunity in the biomedical field. To facilitate and stimulate utilization of these datasets, we have recently developed an interactive data browsing and visualization web application, the Gene Expression Browser (GXB). In this note, we describe a curated compendium of 13 public datasets on human breast cancer, representing a total of 2142 transcriptome profiles. We classified the samples according to different immune based classification systems and integrated this information into the datasets. Annotated and harmonized datasets were uploaded to GXB. Study samples were categorized in different groups based on their immunologic tumor response profiles, intrinsic molecular subtypes and multiple clinical parameters. Ranked gene lists were generated based on relevant group comparisons. In this data note, we demonstrate the utility of GXB to evaluate the expression of a gene of interest, find differential gene expression between groups and investigate potential associations between variables with a specific focus on immunologic classification in breast cancer. This interactive resource is publicly available online at: http://breastcancer.gxbsidra.org/dm3/geneBrowser/list.

A curated transcriptome dataset collection to investigate the development and differentiation of the human placenta and its associated pathologies.

Compendia of large-scale datasets made available in public repositories provide a precious opportunity to discover new biomedical phenomena and to fill gaps in our current knowledge. In order to foster novel insights it is necessary to ensure that these data are made readily accessible to research investigators in an interpretable format. Here we make a curated, public, collection of transcriptome datasets relevant to human placenta biology available for further analysis and interpretation via an interactive data browsing interface. We identified and retrieved a total of 24 datasets encompassing 759 transcriptome profiles associated with the development of the human placenta and associated pathologies from the NCBI Gene Expression Omnibus (GEO) and present them in a custom web-based application designed for interactive query and visualization of integrated large-scale datasets ( http://placentalendocrinology.gxbsidra.org/dm3/landing.gsp). We also performed quality control checks using relevant biological markers. Multiple sample groupings and rank lists were subsequently created to facilitate data query and interpretation. Via this interface, users can create web-links to customized graphical views which may be inserted into manuscripts for further dissemination, or e-mailed to collaborators for discussion. The tool also enables users to browse a single gene across different projects, providing a mechanism for  developing new perspectives on the role of a molecule of interest across multiple biological states. The dataset collection we created here is available at: http://placentalendocrinology.gxbsidra.org/dm3.

A curated transcriptome dataset collection to investigate the functional programming of human hematopoietic cells in early life.

Compendia of large-scale datasets made available in public repositories provide an opportunity to identify and fill gaps in biomedical knowledge. But first, these data need to be made readily accessible to research investigators for interpretation. Here we make available a collection of transcriptome datasets to investigate the functional programming of human hematopoietic cells in early life. Thirty two datasets were retrieved from the NCBI Gene Expression Omnibus (GEO) and loaded in a custom web application called the Gene Expression Browser (GXB), which was designed for interactive query and visualization of integrated large-scale data. Quality control checks were performed. Multiple sample groupings and gene rank lists were created allowing users to reveal age-related differences in transcriptome profiles, changes in the gene expression of neonatal hematopoietic cells to a variety of immune stimulators and modulators, as well as during cell differentiation. Available demographic, clinical, and cell phenotypic information can be overlaid with the gene expression data and used to sort samples. Web links to customized graphical views can be generated and subsequently inserted in manuscripts to report novel findings. GXB also enables browsing of a single gene across projects, thereby providing new perspectives on age- and developmental stage-specific expression of a given gene across the human hematopoietic system. This dataset collection is available at: http://developmentalimmunology.gxbsidra.org/dm3/geneBrowser/list.

A curated transcriptome dataset collection to investigate the immunobiology of HIV infection.

Compendia of large-scale datasets available in public repositories provide an opportunity to identify and fill current gaps in biomedical knowledge. But first, these data need to be readily accessible to research investigators for interpretation. Here, we make available a collection of transcriptome datasets relevant to HIV infection. A total of 2717 unique transcriptional profiles distributed among 34 datasets were identified, retrieved from the NCBI Gene Expression Omnibus (GEO), and loaded in a custom web application, the Gene Expression Browser (GXB), designed for interactive query and visualization of integrated large-scale data. Multiple sample groupings and rank lists were created to facilitate dataset query and interpretation via this interface. Web links to customized graphical views can be generated by users and subsequently inserted in manuscripts reporting novel findings, such as discovery notes. The tool also enables browsing of a single gene across projects, which can provide new perspectives on the role of a given molecule across biological systems. This curated dataset collection is available at: http://hiv.gxbsidra.org/dm3/geneBrowser/list.

A compendium of monocyte transcriptome datasets to foster biomedical knowledge discovery.

Systems-scale profiling approaches have become widely used in translational research settings. The resulting accumulation of large-scale datasets in public repositories represents a critical opportunity to promote insight and foster knowledge discovery. However, resources that can serve as an interface between biomedical researchers and such vast and heterogeneous dataset collections are needed in order to fulfill this potential. Recently, we have developed an interactive data browsing and visualization web application, the Gene Expression Browser (GXB). This tool can be used to overlay deep molecular phenotyping data with rich contextual information about analytes, samples and studies along with ancillary clinical or immunological profiling data. In this note, we describe a curated compendium of 93 public datasets generated in the context of human monocyte immunological studies, representing a total of 4,516 transcriptome profiles. Datasets were uploaded to an instance of GXB along with study description and sample annotations. Study samples were arranged in different groups. Ranked gene lists were generated based on relevant group comparisons. This resource is publicly available online at http://monocyte.gxbsidra.org/dm3/landing.gsp.

A curated compendium of monocyte transcriptome datasets of relevance to human monocyte immunobiology research.

Systems-scale profiling approaches have become widely used in translational research settings. The resulting accumulation of large-scale datasets in public repositories represents a critical opportunity to promote insight and foster knowledge discovery. However, resources that can serve as an interface between biomedical researchers and such vast and heterogeneous dataset collections are needed in order to fulfill this potential. Recently, we have developed an interactive data browsing and visualization web application, the Gene Expression Browser (GXB). This tool can be used to overlay deep molecular phenotyping data with rich contextual information about analytes, samples and studies along with ancillary clinical or immunological profiling data. In this note, we describe a curated compendium of 93 public datasets generated in the context of human monocyte immunological studies, representing a total of 4,516 transcriptome profiles. Datasets were uploaded to an instance of GXB along with study description and sample annotations. Study samples were arranged in different groups. Ranked gene lists were generated based on relevant group comparisons. This resource is publicly available online at http://monocyte.gxbsidra.org/dm3/landing.gsp.

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

BACKGROUND: Systems 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. METHODS: State 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. RESULTS: We 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 )]. CONCLUSIONS: We 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.

Modular transcriptional repertoire analyses of adults with systemic lupus erythematosus reveal distinct type I and type II interferon signatures.

OBJECTIVE: The role of interferon-α (IFNα) in the pathogenesis of systemic lupus erythematosus (SLE) is strongly supported by gene expression studies. The aim of this study was to improve characterization of the blood IFN signature in adult SLE patients. METHODS: Consecutive patients were enrolled and followed up prospectively. Microarray data were generated using Illumina BeadChips. A modular transcriptional repertoire was used as a framework for the analysis. RESULTS: Our repertoire of 260 modules, which consisted of coclustered gene sets, included 3 IFN-annotated modules (M1.2, M3.4, and M5.12) that were strongly up-regulated in SLE patients. A modular IFN signature was observed in 54 of 62 patients (87%) or 131 of all 157 samples (83%). The IFN signature was more complex than expected, with each module displaying a distinct activation threshold (M1.2 < M3.4 < M5.12), thus providing a modular score by which to stratify SLE patients based on the presence of 0, 1, 2, or 3 active IFN modules. A similar gradient in modular IFN signature was observed within patients with clinically quiescent disease, for whom moderate/strong modular scores (2 or 3 active IFN modules) were associated with higher anti-double-stranded DNA titers and lower lymphocyte counts than those in patients with absent/mild modular scores (0 or 1 active IFN modules). Longitudinal analyses revealed both stable (M1.2) and variable (M3.4 and M5.12) components of modular IFN signature over time in single patients. Interestingly, mining of other data sets suggested that M3.4 and M5.12 could also be driven by IFNß and IFNγ. CONCLUSION: Modular repertoire analysis reveals complex IFN signatures in SLE, which are not restricted to the previous IFNα signature, but which also involve IFNß and IFNγ.

Molecular signatures of antibody responses derived from a systems biology study of five human vaccines.

Many vaccines induce protective immunity via antibodies. Systems biology approaches have been used to determine signatures that can be used to predict vaccine-induced immunity in humans, but whether there is a 'universal signature' that can be used to predict antibody responses to any vaccine is unknown. Here we did systems analyses of immune responses to the polysaccharide and conjugate vaccines against meningococcus in healthy adults, in the broader context of published studies of vaccines against yellow fever virus and influenza virus. To achieve this, we did a large-scale network integration of publicly available human blood transcriptomes and systems-scale databases in specific biological contexts and deduced a set of transcription modules in blood. Those modules revealed distinct transcriptional signatures of antibody responses to different classes of vaccines, which provided key insights into primary viral, protein recall and anti-polysaccharide responses. Our results elucidate the early transcriptional programs that orchestrate vaccine immunity in humans and demonstrate the power of integrative network modeling.

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.