A phase 2 randomized trial with autologous polyclonal expanded regulatory T cells in children with new-onset type 1 diabetes.

CD4+CD25hiCD127lo/-FOXP3+ regulatory T cells (Tregs) play a key role in preventing autoimmunity. In autoimmune type 1 diabetes (T1D), adoptive transfer of autologous polyclonal Tregs has been shown to be safe in adults in phase 1 clinical trials. We explored factors contributing to efficacy of autologous polyclonal expanded Tregs (expTregs) in a randomized phase 2 multi-center, double-blind, clinical trial (Sanford/Lisata Therapeutics T-Rex phase 2 trial, ClinicalTrials.gov NCT02691247). One hundred ten treated children and adolescents with new-onset T1D were randomized 1:1:1 to high-dose (20 × 106 cells/kilogram) or low-dose (1 × 106 cells/kilogram) treatments or to matching placebo. Cytometry as well as bulk and single-cell RNA sequencing were performed on selected expTregs and peripheral blood samples from participants. The single doses of expTregs were safe but did not prevent decline in residual ß cell function over 1 year compared to placebo (P = 0.94 low dose, P = 0.21 high dose), regardless of age or baseline C-peptide. ExpTregs were highly activated and suppressive in vitro. A transient increase of activated memory Tregs was detectable 1 week after infusion in the high-dose cohort, suggesting effective transfer of expTregs. However, the in vitro fold expansion of expTregs varied across participants, even when accounting for age, and lower fold expansion and its associated gene signature were linked with better C-peptide preservation regardless of Treg dose. These results suggest that a single dose of polyclonal expTregs does not alter progression in T1D; instead, Treg quality may be an important factor.

Impact on in-depth immunophenotyping of delay to peripheral blood processing.

Peripheral blood mononuclear cell (PBMC) immunophenotyping is crucial in tracking activation, disease state, and response to therapy in human subjects. Many studies require shipping of blood from clinical sites to a laboratory for processing to PBMC, which can lead to delays that impact sample quality. We used an extensive cytometry by time-of-flight (CyTOF) immunophenotyping panel to analyze the impacts of delays to processing and distinct storage conditions on cell composition and quality of PBMC from seven adults across a range of ages, including two with rheumatoid arthritis. Two or more days delay to processing resulted in extensive red blood cell contamination and increased variability of cell counts. While total memory and naïve B and T cell populations were maintained, four days delay reduced frequencies of monocytes. Variation across all immune subsets increased with delays of up to seven days in processing. Unbiased clustering analysis to define more granular subsets confirmed changes in PBMC composition, including decreases of classical and non-classical monocytes, basophils, plasmacytoid dendritic cells, and follicular helper T cells, with each subset impacted at a distinct time of delay. Expression of activation markers and chemokine receptors changed by day two, with differential impacts across subsets and markers. Our data support existing recommendations to process PBMC within 36 hours of collection but provide guidance on appropriate immunophenotyping experiments with longer delays.

Abatacept increases T cell exhaustion in early RA individuals who carry HLA risk alleles.

Exhausted CD8 T cells (TEX) are associated with worse outcome in cancer yet better outcome in autoimmunity. Building on our past findings of increased TIGIT+KLRG1+ TEX with teplizumab therapy in type 1 diabetes (T1D), in the absence of treatment we found that the frequency of TIGIT+KLRG1+ TEX is stable within an individual but differs across individuals in both T1D and healthy control (HC) cohorts. This TIGIT+KLRG1+ CD8 TEX population shares an exhaustion-associated EOMES gene signature in HC, T1D, rheumatoid arthritis (RA), and cancer subjects, expresses multiple inhibitory receptors, and is hyporesponsive in vitro, together suggesting co-expression of TIGIT and KLRG1 may broadly define human peripheral exhausted cells. In HC and RA subjects, lower levels of EOMES transcriptional modules and frequency of TIGIT+KLRG1+ TEX were associated with RA HLA risk alleles (DR0401, 0404, 0405, 0408, 1001) even when considering disease status and cytomegalovirus (CMV) seropositivity. Moreover, the frequency of TIGIT+KLRG1+ TEX was significantly increased in RA HLA risk but not non-risk subjects treated with abatacept (CTLA4Ig). The DR4 association and selective modulation with abatacept suggests that therapeutic modulation of TEX may be more effective in DR4 subjects and TEX may be indirectly influenced by cellular interactions that are blocked by abatacept.

Inflammatory bone marrow signaling in pediatric acute myeloid leukemia distinguishes patients with poor outcomes.

High levels of the inflammatory cytokine IL-6 in the bone marrow are associated with poor outcomes in pediatric acute myeloid leukemia (pAML), but its etiology remains unknown. Using RNA-seq data from pre-treatment bone marrows of 1489 children with pAML, we show that > 20% of patients have concurrent IL-6, IL-1, IFNα/ß, and TNFα signaling activity and poorer outcomes. Targeted sequencing of pre-treatment bone marrow samples from affected patients (n = 181) revealed 5 highly recurrent patterns of somatic mutation. Using differential expression analyses of the most common genomic subtypes (~60% of total), we identify high expression of multiple potential drivers of inflammation-related treatment resistance. Regardless of genomic subtype, we show that JAK1/2 inhibition reduces receptor-mediated inflammatory signaling by leukemic cells in-vitro. The large number of high-risk pAML genomic subtypes presents an obstacle to the development of mutation-specific therapies. Our findings suggest that therapies targeting inflammatory signaling may be effective across multiple genomic subtypes of pAML.

Guidelines for standardizing T-cell cytometry assays to link biomarkers, mechanisms, and disease outcomes in type 1 diabetes.

Cytometric immunophenotyping is a powerful tool to discover and implement T-cell biomarkers of type 1 diabetes (T1D) progression and response to clinical therapy. Although many discovery-based T-cell biomarkers have been described, to date, no such markers have been widely adopted in standard practice. The heterogeneous nature of T1D and lack of standardized assays and experimental design across studies is a major barrier to the broader adoption of T-cell immunophenotyping assays. There is an unmet need to harmonize the design of immunophenotyping assays, including those that measure antigen-agnostic cell populations, such that data collected from different clinical trial sites and T1D cohorts are comparable, yet account for cohort-specific features and different drug mechanisms of action. In these Guidelines, we aim to provide expert advice on how to unify aspects of study design and practice. We provide recommendations for defining cohorts, method implementation, as well as tools for data analysis and reporting by highlighting and building on selected successes. Harmonization of cytometry-based T-cell assays will allow researchers to better integrate findings across trials, ultimately enabling the identification and validation of biomarkers of disease progression and treatment response in T1D.

Deep immune phenotyping reveals similarities between aging, Down syndrome, and autoimmunity.

Individuals with Down syndrome show cellular and clinical features of dysregulated aging of the immune system, including a shift from naïve to memory T cells and increased incidence of autoimmunity. However, a quantitative understanding of how various immune compartments change with age in Down syndrome remains lacking. Here, we performed deep immunophenotyping of a cohort of individuals with Down syndrome across the life span, selecting for autoimmunity-free individuals. We simultaneously interrogated age- and sex-matched healthy controls and people with type 1 diabetes as a representative autoimmune disease. We built an analytical software, IMPACD (Iterative Machine-assisted Permutational Analysis of Cytometry Data), that enabled us to rapidly identify many features of immune dysregulation in Down syndrome shared with other autoimmune diseases. We found quantitative and qualitative dysregulation of naïve CD4+ and CD8+ T cells in individuals with Down syndrome and identified interleukin-6 as a candidate driver of some of these changes, thus extending the consideration of immunopathologic cytokines in Down syndrome beyond interferons. We used immune cellular composition to generate three linear models of aging (immune clocks) trained on control participants. All three immune clocks demonstrated advanced immune aging in individuals with Down syndrome. One of these clocks, informed by Down syndrome­relevant biology, also showed advanced immune aging in individuals with type 1 diabetes. Orthologous RNA sequencing­derived immune clocks also demonstrated advanced immune aging in individuals with Down syndrome. Together, our findings demonstrate an approach to studying immune aging in Down syndrome that may have implications in other autoimmune diseases.

A simple strategy for sample annotation error detection in cytometry datasets.

Mislabeling samples or data with the wrong participant information can affect study integrity and lead investigators to draw inaccurate conclusions. Quality control to prevent these types of errors is commonly embedded into the analysis of genomic datasets, but a similar identification strategy is not standard for cytometric data. Here, we present a method for detecting sample identification errors in cytometric data using expression of human leukocyte antigen (HLA) class I alleles. We measured HLA-A*02 and HLA-B*07 expression in three longitudinal samples from 41 participants using a 33-marker CyTOF panel designed to identify major immune cell types. 3/123 samples (2.4%) showed HLA allele expression that did not match their longitudinal pairs. Furthermore, these same three samples' cytometric signature did not match qPCR HLA class I allele data, suggesting that they were accurately identified as mismatches. We conclude that this technique is useful for detecting sample-labeling errors in cytometric analyses of longitudinal data. This technique could also be used in conjunction with another method, like GWAS or PCR, to detect errors in cross-sectional data. We suggest widespread adoption of this or similar techniques will improve the quality of clinical studies that utilize cytometry.

The many faces of islet antigen-specific CD8 T cells: clues to clinical outcome in type 1 diabetes.

Immune monitoring enables a better understanding of disease processes and response to therapy, but has been challenging in the setting of chronic autoimmunity because of unknown etiology, variable and protracted kinetics of the disease process, heterogeneity across patients and the complexity of immune interactions. To begin to parse this complexity, we focus here on type 1 diabetes (T1D) and CD8 T cells as a cell type that has features that are associated with different stages of disease, rates of progression and response to therapy. Specifically, we discuss the current understanding of the role of autoreactive CD8 T cells in disease outcome, which implicates particular CD8 functional subsets, rather than unique antigens or total number of autoreactive T cells. Next, we discuss how autoreactive CD8 T-cell features can be reflected in measures of global CD8 T cells, and then pull these concepts together by highlighting immune therapies recently shown to modulate both CD8 T cells and disease progression. We end by discussing outstanding questions about the role of specific subsets of autoreactive CD8 T cells in disease progression and how they may be optimally modulated to treat and prevent T1D.

Autoreactive CD8+ T cell exhaustion distinguishes subjects with slow type 1 diabetes progression.

Although most patients with type 1 diabetes (T1D) retain some functional insulin-producing islet ß cells at the time of diagnosis, the rate of further ß cell loss varies across individuals. It is not clear what drives this differential progression rate. CD8+ T cells have been implicated in the autoimmune destruction of ß cells. Here, we addressed whether the phenotype and function of autoreactive CD8+ T cells influence disease progression. We identified islet-specific CD8+ T cells using high-content, single-cell mass cytometry in combination with peptide-loaded MHC tetramer staining. We applied a new analytical method, DISCOV-R, to characterize these rare subsets. Autoreactive T cells were phenotypically heterogeneous, and their phenotype differed by rate of disease progression. Activated islet-specific CD8+ memory T cells were prevalent in subjects with T1D who experienced rapid loss of C-peptide; in contrast, slow disease progression was associated with an exhaustion-like profile, with expression of multiple inhibitory receptors, limited cytokine production, and reduced proliferative capacity. This relationship between properties of autoreactive CD8+ T cells and the rate of T1D disease progression after onset make these phenotypes attractive putative biomarkers of disease trajectory and treatment response and reveal potential targets for therapeutic intervention.

Overexpression of TLR7 promotes cell-intrinsic expansion and autoantibody production by transitional T1 B cells.

Toll-like receptor (TLR), a ligand for single-stranded RNA, has been implicated in the development of pathogenic anti-RNA autoantibodies both in systemic lupus erythematous (SLE) patients and in murine models of lupus. It is still unclear, however, where and how TLR7-mediated interactions affect the development of autoreactive B cells. We found that overexpression of TLR7 in transgenic mice (TLR7.1Tg) leads to marked alterations of transitional (T1) B cells, associated with their expansion and proliferation within the splenic red pulp (RP). This phenotype was intrinsic to the T1 subset of B cells and occurred independently of type 1 IFN signals. Overexpression of RNase in TLR7.1Tg mice significantly limited the expansion and proliferation of T1 cells, indicating that endogenous RNA complexes are driving their activation. TLR7.1Tg T1 cells were hyper-responsive to anti-IgM and TLR7 ligand stimulation in vitro and produced high concentrations of class-switched IgG2b and IgG2c, including anti-RNA antibodies. Our results demonstrate that initial TLR7 stimulation of B cells occurs at the T1 stage of differentiation in the splenic RP and suggest that dysregulation of TLR7 expression in T1 cells can result in production of autoantibodies.

Contrasting mechanisms of interferon-α inhibition by intravenous immunoglobulin after induction by immune complexes versus Toll-like receptor agonists.

OBJECTIVE: Plasmacytoid dendritic cells (PDCs) produce high concentrations of interferon-α (IFNα) following exposure to immune complexes containing nucleic acids. We previously reported that serum from healthy donors inhibits IFNα production by PDCs in response to systemic lupus erythematosus (SLE) immune complexes, and that inhibition is mediated, in part, by IgG. IgG is the major component of intravenous immunoglobulin and is well known to exert antiinflammatory properties. Although suppression of inflammation by the sialylated subfraction of IgG has been implicated in some models, the mechanism of IFNα inhibition by IgG and the importance of sialylation have not been studied. METHODS: SLE immune complexes or synthetic Toll-like receptor (TLR) agonists were used to stimulate total or individual cell-depleted human mononuclear cell cultures in the presence or absence of IgG, Fc fragments, F(ab')2 fragments, and their sialylated or unsialylated subfractions. Cytokines were quantified by enzyme-linked immunosorbent assay. RESULTS: We identified 2 distinct mechanisms by which IgG inhibits IFNα production. First, IgG Fc fragments inhibited SLE immune complex-stimulated IFNα production via a sialic acid-independent mechanism, by inhibiting immune complex binding to Fcγ receptor IIa on PDCs. In contrast, the F(ab')2 fragment of the sialylation-enriched fraction of IgG inhibited TLR-7 or TLR-9 agonist-induced IFNα production but did not require the sialic acid residue itself. The inhibitory activity of IgG on TLR agonist-induced IFNα required monocyte production of prostaglandin E2, a potent suppressor of IFNα production by PDCs. CONCLUSION: IgG attenuates IFNα production by PDCs by both cell surface receptor and intracellular pathways, depending on the nature of the inducing stimulus.

TNF-α and TGF-ß counter-regulate PD-L1 expression on monocytes in systemic lupus erythematosus.

Monocytes in patients with systemic lupus erythematosus (SLE) are hyperstimulatory for T lymphocytes. We previously found that the normal program for expression of a negative costimulatory molecule programmed death ligand-1 (PD-L1) is defective in SLE patients with active disease. Here, we investigated the mechanism for PD-L1 dysregulation on lupus monocytes. We found that PD-L1 expression on cultured SLE monocytes correlated with TNF-α expression. Exogenous TNF-α restored PD-L1 expression on lupus monocytes. Conversely, TGF-ß inversely correlated with PD-L1 in SLE and suppressed expression of PD-L1 on healthy monocytes. Therefore, PD-L1 expression in monocytes is regulated by opposing actions of TNF-α and TGF-ß. As PD-L1 functions to fine tune lymphocyte activation, dysregulation of cytokines resulting in reduced expression could lead to loss of peripheral T cell tolerance.

Plasmacytoid dendritic cells and C1q differentially regulate inflammatory gene induction by lupus immune complexes.

Immune complexes (ICs) play a pivotal role in causing inflammation in systemic lupus erythematosus (SLE). Yet, it remains unclear what the dominant blood cell type(s) and inflammation-related gene programs stimulated by lupus ICs are. To address these questions, we exposed normal human PBMCs or CD14(+) isolated monocytes to SLE ICs in the presence or absence of C1q and performed microarray analysis and other tests for cell activation. By microarray analysis, we identified genes and pathways regulated by SLE ICs that are both type I IFN dependent and independent. We also found that C1q-containing ICs markedly reduced expression of the majority of IFN-response genes and also influenced the expression of multiple other genes induced by SLE ICs. Surprisingly, IC activation of isolated CD14(+) monocytes did not upregulate CD40 and CD86 and only modestly stimulated inflammatory gene expression. However, when monocyte subsets were purified and analyzed separately, the low-abundance CD14(dim) ("patrolling") subpopulation was more responsive to ICs. These observations demonstrate the importance of plasmacytoid dendritic cells, CD14(dim) monocytes, and C1q as key regulators of inflammatory properties of ICs and identify many pathways through which they act.

Identification and characterization of dynein genes in Tetrahymena.

We describe the protocol through which we identify and characterize dynein subunit genes in the ciliated protozoan Tetrahymena thermophila. The gene(s) of interest is found by searching the Tetrahymena genome, and it is characterized in silico including the prediction of the open reading frame and identification of likely introns. The gene is then characterized experimentally, including the confirmation of the exon-intron organization of the gene and the measurement of the expression of the gene in nondeciliated and reciliating cells. In order to understand the function of the gene product, the gene is modified-for example, deleted, overexpressed, or epitope-tagged-using the straightforward gene replacement strategies available with Tetrahymena. The effect(s) of the dynein gene modification is evaluated by examining transformants for ciliary traits including cell motility, ciliogenesis, cell division, and the engulfment of particles through the oral apparatus. The multistepped protocol enables undergraduate students to engage in short- and long-term experiments. In our laboratory during the last 6 years, more than two dozen undergraduate students have used these methods to investigate dynein subunit genes.

Dynein light chain family in Tetrahymena thermophila.

Dyneins are large protein complexes that produce directed movement on microtubules. In situ, dyneins comprise combinations of heavy, intermediate, light-intermediate, and light chains. The light chains regulate the locations and activities of dyneins but their functions are not completely understood. We have searched the recently sequenced Tetrahymena thermophila macronuclear genome to describe the entire family of dynein light chains expressed in this organism. We identified fourteen genes encoding putative dynein light chains and seven genes encoding light chain-like proteins. RNA-directed PCR revealed that all 21 genes were expressed. Quantitative real time reverse transcription PCR showed that many of these genes were upregulated after deciliation, indicating that these proteins are present in cilia. Using the nomenclature developed in Chlamydomonas, Tetrahymena expresses two isoforms each of LC2, LC4, LC7, and Tctex1, three isoforms of p28, and six LC8/LC8-like isoforms. Tetrahymena also expresses two LC3-like genes. No Tetrahymena orthologue was found for Chlamydomonas LC5 or LC6. This study provides a complete description of the different genes and isoforms of the dynein light chains that are expressed in Tetrahymena, a model organism in which the targeted manipulation of genes is straightforward.