Allen Institute for Immunology

Mouse CD8 T cell differentiation has been studied extensively in models of infections and cancer, yet no unified framework spans the full spectrum of immunological contexts. We present the CD8 immgenT framework, integrating >200,000 single-cell transcriptomes and 128-plex surface proteomes from 734 samples spanning multiple perturbations, tissues, and timepoints. Unbiased analysis identifies 21 states encompassing naive, effector, circulating memory, tissue-resident memory, progenitor-exhausted, and terminally-exhausted compartments, among others. These states re-emerge with striking molecular convergence across acute/chronic infections, cancer, autoimmunity, aging, and homeostasis, showing that near-identical transcriptional programs support protective or dysfunctional outcomes depending on developmental history and microenvironment. Classic archetypes map to discrete clusters but exhibit unappreciated heterogeneity and overlap, cautioning against rigid nomenclature. We provide validated combinatorial markers, flow cytometry gating strategies, and immgenT reference-based integration for reproducible annotation of new datasets. This universal coordinate system harmonizes fragmented CD8 T cell literature and clarifies relationships across diverse immune challenges.

Abstract Interferons (IFNs) orchestrate diverse immune responses, but distinguishing individual IFN contributions in human transcriptomic data is challenging due to overlapping interferon-stimulated gene (ISG) signatures and limited cell-type-specific datasets. To address this, we generated a single-cell transcriptomic atlas of IFN responses by stimulating primary human T, B, NK, and CD14 monocytes with IFN-I, IFN-II, and IFN-III. This revealed core and cell-type-specific ISG programs across 13 subsets, highlighting distinct functions of IFNs. We developed an algorithm to separate IFN-I and IFN-II activity in transcriptomic data. Applied to multiple myeloma samples, it showed elevated IFN-I and IFN-II responses, with induction therapy reducing only IFN-I. Extending to multiple disease datasets provided a cross-disease overview of IFN-I and IFN-II activities and revealed increased IFN-II activities in T cells during lupus flares. This resource and the accompanying analytical framework enable dissection of IFN-driven transcriptional programs in a cell-type specific manner in human disease.

Abstract Description Antibody-secreting plasma cells (PCs) play both protective and pathogenic roles across various disease contexts. The lifespan of PCs ranges from days to decades, and they exhibit diverse functionality including antibody secretion, cytokine production, and immunoregulation. Currently, we cannot identify, ascribe function to, nor manipulate distinct human PC subsets, preventing targeted therapeutic intervention and selective induction. To discover and characterize human PC subsets, we paired a systems immunology approach with a suite of functional assays investigating cellular identity and behavior. To identify cell surface markers expressed by human PCs, we quantified the expression of hundreds of surface proteins on millions of PCs from healthy human tissues. We then developed a bespoke PC-focused antibody panel and applied it to healthy human bone marrow in a tri-modal single-cell sequencing assay measuring surface protein expression, transcriptomics, and chromatin accessibility. We identified distinct PC subsets and dissected their molecular and epigenetic features. We sorted PC subsets and evaluated their morphology, antibody secretion rates, cytokine production, and longevity. Overall, our deep phenotypic and functional profiling has revealed unappreciated PC subsets and provided the highest resolution assessment of human PC identity reported to date. Our findings promise to enhance the identification, monitoring, and therapeutic manipulation of PCs in clinical settings. Funding Sources Cancer Research Institute Irvington Postdoctoral Fellowship American Society of Hematology Fellow Scholar Award Fred Hutchinson Cancer Center Translational Data Science Integrated Research Center Pilot Award Allen Institute for Immunology Topic Categories Lymphocyte Differentiation and Peripheral Maintenance (LYM)

Abstract Description The Allen Institute for Immunology was founded in 2018 to perform deep, longitudinal profiling of the human immune system in health and disease. We established partnerships to profile healthy adults and children as well as patients at risk for rheumatoid arthritis, with inflammatory bowel disease, with multiple myeloma diagnosis, under treatment for melanoma, and with COVID-19. We sampled the same subjects longitudinally for up to two years, then performed immune profiling using scRNA-seq, 4 high-dimensional flow cytometry panels, plasma or serum proteomics, and clinical lab tests. In total, we profiled >2,300 samples from >450 subjects, including >55 million cells profiled by scRNA-seq to date. To process, analyze, and distribute this data, we developed the Human Immune System Explorer (HISE) platform, a flexible, scalable, cloud-based framework to enable storage, interactive analysis, visualization, and generation of Certificates of Reproducibility that enable inspection and replay of any step of an analysis workflow. We joined our robust, large-scale analytical platform to public-facing visualization tools, scientific context, and data releases, starting with the Human Immune Health Atlas: an expertly annotated dataset of > 1.3 million PBMCs from 108 healthy donors from 11 to 65 years of age. We invite immunologists to explore this resource and our expanding library of immunology data, insights, and tools at https://explore.allenimmunology.org/. Topic Categories Computational and Systems Immunology (COMP)

Abstract Description Some autoimmune diseases, including rheumatoid arthritis (RA), are preceded by a subclinical phase of disease activity. Proactive clinical management is hampered by a lack of biological understanding of this subclinical ‘at-risk’ state and the changes underlying disease development. In a cross-sectional and longitudinal multi-omics study of peripheral immunity in the autoantibody-positive at-risk for RA period, we identified 275 proteins that differentiated ACPA+ at-risk individuals (ARI) from ACPA- controls. A cluster of ACPA+ donors were found to have an inflammatory protein signature that included elevated IL-1B, VEGFA, CXCL3 and CCL4. This inflammatory signature was accompanied by transcriptional reprogramming across all major immune compartments of ARI, including naive, effector and memory T and B cells. By contrast, in longitudinal samples of ARI who developed clinical RA, the transcriptional response was restricted to naive and central memory (CM) CD4 T cells. We discovered a shared activation signature within naive and CM CD4 T cells during progression to clinical RA, highlighted by reduced expression of CD3 components together with elevated STAT5B, ICOS and AKT3. These progressive changes in naive and CM T cells were the same that were diminished in our independent analyses of a second study of RA patients who responded to CTLA4-Ig therapy. Our findings suggest pathogenesis begins prior to clinical symptoms and suggest approaches for proactive early intervention. Topic Categories Translational and Interventional Immunology (TI)

Rheumatoid arthritis (RA) is preceded by an at-risk stage of disease that can be marked by the presence of anticitrullinated protein antibodies (ACPAs) but the absence of clinically apparent synovitis (clinical RA). Preemptive intervention in at-risk individuals could prevent or delay future tissue damage; however, the immunobiology of this stage is unclear. Using integrative multiomics, we longitudinally profiled at-risk individuals, where one-third of participants developed clinical RA on study. We found evidence of systemic inflammation and signatures of activation in naïve T and B cells of at-risk individuals. During progression to clinical RA, proinflammatory skewing of atypical B cells and expansion of memory CD4 T cells with signatures of activation and B cell help were present without elevations in circulating ACPA titers. Epigenetic changes in naïve CD4 T cells suggested a predisposition to differentiate into effector cells capable of B cell help. These findings characterize pathogenesis of the ACPA+ at-risk stage and support the concept that the disease begins much earlier than clinical RA. Additionally, an extensive immune resource of the at-risk stage and progression to clinical RA with interactive tools was developed to enable further investigation.

The generation and maintenance of immunity is a dynamic process that is dependent on age1–3. Here, to better understand its progression, we profiled peripheral immunity in more than 300 healthy adults (25 to 90 years of age) using single-cell RNA sequencing, proteomics and flow cytometry, following 96 adults longitudinally across 2 years with seasonal influenza vaccination. The resulting resource generated a single-cell RNA-sequencing dataset of more than 16 million peripheral blood mononuclear cells with 71 immune cell subsets from our Human Immune Health Atlas and enabled us to interrogate how immune cell composition and states shift with age, chronic viral infection and vaccination. From these data, we demonstrate robust, non-linear transcriptional reprogramming in T cell subsets with age that is not driven by systemic inflammation or chronic cytomegalovirus infection. This age-related reprogramming led to a functional T helper 2 (TH2) cell bias in memory T cells that is linked to dysregulated B cell responses against highly boosted antigens in influenza vaccines. Collectively, this study reveals unique features of the immune ageing process that occur prior to advanced age and provides novel targets for age-related immune modulation. We provide interactive tools for exploring this extensive human immune health resource at https://apps.allenimmunology.org/aifi/insights/dynamics-imm-health-age/.

Age-associated changes in the T cell compartment are well described. However, limitations of current single-modal or bimodal single-cell assays, including flow cytometry, RNA-seq (RNA sequencing) and CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing), have restricted our ability to deconvolve more complex cellular and molecular changes. Here, we profile >300,000 single T cells from healthy children (aged 11–13 years) and older adults (aged 55–65 years) by using the trimodal assay TEA-seq (single-cell analysis of mRNA transcripts, surface protein epitopes and chromatin accessibility), which revealed that molecular programming of T cell subsets shifts toward a more activated basal state with age. Naive CD4+ T cells, considered relatively resistant to aging, exhibited pronounced transcriptional and epigenetic reprogramming. Moreover, we discovered a novel CD8αα+ T cell subset lost with age that is epigenetically poised for rapid effector responses and has distinct inhibitory, costimulatory and tissue-homing properties. Together, these data reveal new insights into age-associated changes in the T cell compartment that may contribute to differential immune responses.