Eomes expression identifies the early bone marrow precursor to classical NK cells.

Natural killer (NK) cells traffic through the blood and mount cytolytic and interferon-γ (IFNγ)-focused responses to intracellular pathogens and tumors. Type 1 innate lymphoid cells (ILC1s) also produce type 1 cytokines but reside in tissues and are not cytotoxic. Whether these differences reflect discrete lineages or distinct states of a common cell type is not understood. Using single-cell RNA sequencing and flow cytometry, we focused on populations of TCF7+ cells that contained precursors for NK cells and ILC1s and identified a subset of bone marrow lineage-negative NK receptor-negative cells that expressed the transcription factor Eomes, termed EomeshiNKneg cells. Transfer of EomeshiNKneg cells into Rag2-/-Il2rg-/- recipients generated functional NK cells capable of preventing metastatic disease. By contrast, transfer of PLZF+ ILC precursors generated a mixture of ILC1s, ILC2s and ILC3s that lacked cytotoxic potential. These findings identified EomeshiNKneg cells as the bone marrow precursor to classical NK cells and demonstrated that the NK and ILC1 lineages diverged early during development.

New Insights on Genes, Gluten, and Immunopathogenesis of Celiac Disease.

Celiac disease (CeD) is a gluten-induced enteropathy that develops in genetically susceptible individuals upon consumption of cereal gluten proteins. It is a unique and complex immune disorder to study as the driving antigen is known and the tissue targeted by the immune reaction can be interrogated. This review integrates findings gained from genetic, biochemical, and immunologic studies, which together have revealed mechanisms of gluten peptide modification and HLA binding, thereby enabling a maladapted anti-gluten immune response. Observations in human samples combined with experimental mouse models have revealed that the gluten-induced immune response involves CD4+ T cells, cytotoxic CD8+ T cells, and B cells; their cross-talks are critical for the tissue-damaging response. The emergence of high-throughput technologies is increasing our understanding of the phenotype, location, and presumably function of the gluten-specific cells, which are all required to identify novel therapeutic targets and strategies for CeD.

Comprehensive Association Analyses of Extraintestinal Manifestations in Inflammatory Bowel Disease.

BACKGROUND & AIMS: Patients with inflammatory bowel disease (IBD) frequently develop extraintestinal manifestations (EIMs) that contribute substantially to morbidity. We assembled the largest multicohort data set to date to investigate the clinical, serologic, and genetic factors associated with EIM complications in IBD. METHODS: Data were available in 12,083 unrelated European ancestry IBD cases with presence or absence of EIMs (eg, ankylosing spondylitis [ankylosing spondylitis and sacroiliitis], primary sclerosing cholangitis [PSC], peripheral arthritis, and skin and ocular manifestations) across 4 cohorts (Cedars-Sinai Medical Center, National Institute for Diabetes and Digestive and Kidney Diseases IBD Genetics Consortium, Sinai Helmsley Alliance for Research Excellence Consortium, and Risk Stratification and Identification of Immunogenetic and Microbial Markers of Rapid Disease Progression in Children with Crohn's Disease cohort). Clinical and serologic parameters were analyzed by means of univariable and multivariable regression analyses using a mixed-effects model. Within-case logistic regression was performed to assess genetic associations. RESULTS: Most EIMs occurred more commonly in female subjects (overall EIM: P = 9.0E-05, odds ratio [OR], 1.2; 95% CI, 1.1-1.4), with CD (especially colonic disease location; P = 9.8E-09, OR, 1.7; 95% CI, 1.4-2.0), and in subjects who required surgery (both CD and UC; P = 3.6E-19, OR, 1.7; 95% CI, 1.5-1.9). Smoking increased risk of EIMs except for PSC, where there was a "protective" effect. Multiple serologic associations were observed, including with PSC (anti-nuclear cytoplasmic antibody; IgG and IgA, anti-Saccharomyces cerevisiae antibodies; and anti-flagellin) and any EIM (anti-nuclear cytoplasmic antibody; IgG and IgA, anti-Saccharomyces cerevisiae antibodies; and anti-Pseudomonas fluorescens-associated sequence). We identified genome-wide significant associations within major histocompatibility complex (ankylosing spondylitis and sacroiliitis, P = 1.4E-15; OR, 2.5; 95% CI, 2.0-3.1; PSC, P = 2.7E-10; OR, 2.8; 95% CI, 2.0-3.8; ocular, P = 2E-08, OR, 3.6; 95% CI, 2.3-5.6; and overall EIM, P = 8.4E-09; OR, 2.2; 95% CI, 1.7-2.9) and CPEB4 (skin, P = 2.7E-08; OR, 1.5; 95% CI, 1.3-1.8). Genetic associations implicated tumor necrosis factor, JAK-STAT, and IL6 as potential targets for EIMs. Contrary to previous reports, only 2% of our subjects had multiple EIMs and most co-occurrences were negatively correlated. CONCLUSIONS: We have identified demographic, clinical, and genetic associations with EIMs that revealed underlying mechanisms and implicated novel and existing drug targets-important steps toward a more personalized approach to IBD management.

Restoring tolerance with antigen delivery.

Strategies that modulate antigen delivery are being tested to reverse autoimmunity.

Pseudo-spectral angle mapping for automated pixel-level analysis of highly multiplexed tissue image data.

The rapid development of highly multiplexed microscopy systems has enabled the study of cells embedded within their native tissue, which is providing exciting insights into the spatial features of human disease [1]. However, computational methods for analyzing these high-content images are still emerging, and there is a need for more robust and generalizable tools for evaluating the cellular constituents and underlying stroma captured by high-plex imaging [2]. To address this need, we have adapted spectral angle mapping - an algorithm used widely in hyperspectral image analysis - to compress the channel dimension of high-plex immunofluorescence images. As many high-plex immunofluorescence imaging experiments probe unique sets of protein markers, existing cell and pixel classification models do not typically generalize well. Pseudospectral angle mapping (pSAM) uses reference pseudospectra - or pixel vectors - to assign each pixel in an image a similarity score to several cell class reference vectors, which are defined by each unique staining panel. Here, we demonstrate that the class maps provided by pSAM can directly provide insight into the prevalence of each class defined by reference pseudospectra. In a dataset of high-plex images of colon biopsies from patients with gut autoimmune conditions, sixteen pSAM class representation maps were combined with instance segmentation of cells to provide cell class predictions. Finally, pSAM detected a diverse set of structure and immune cells when applied to a novel dataset of kidney biopsies imaged with a 43-marker panel. In summary, pSAM provides a powerful and readily generalizable method for evaluating high-plex immunofluorescence image data.