MHC class II tetramers Nepom, Gerald T
The Journal of immunology (1950),
2012-Mar-15, 2012-03-15, 20120315, Letnik:
188, Številka:
6
Journal Article
Recenzirano
Odprti dostop
MHC class II tetramers have emerged as an important tool for characterization of the specificity and phenotype of CD4 T cell immune responses, useful in a large variety of disease and vaccine ...studies. Issues of specific T cell frequency, biodistribution, and avidity, coupled with the large genetic diversity of potential class II restriction elements, require targeted experimental design. Translational opportunities for immune disease monitoring are driving the rapid development of HLA class II tetramer use in clinical applications, together with innovations in tetramer production and epitope discovery.
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.
► Influenza vaccination elicits a potent interferon signature carried by neutrophils ► Pneumococcal vaccination induces early inflammatory, myeloid transcriptional profile ► Pneumococcal vaccination elicits a potent antibody-secreting cell signature
A combination of genetic and immunological features is useful for prediction of autoimmune diabetes. Patterns of immune response correspond to the progression from a preclinical phase of disease to ...end-stage islet damage, with biomarkers indicating transition from susceptibility to active autoimmunity, and to a final loss of immune regulation. Here, we review the markers that provide evidence for immunological checkpoint failure and that also provide tools for assessment of individualized disease risk. When viewed in the context of genetic variation that influences immune response thresholds, progression from susceptibility to overt disease displays predictable modalities of clinical presentation resulting from a sequential series of failed homeostatic checkpoints for selection and activation of immunity.
There is no detailed comparison of allergen-specific immunoglobulin responses following sublingual immunotherapy (SLIT) and subcutaneous immunotherapy (SCIT).
We sought to compare nasal and systemic ...timothy grass pollen (TGP)-specific antibody responses during 2 years of SCIT and SLIT and 1 year after treatment discontinuation in a double-blind, double-dummy, placebo-controlled trial.
Nasal fluid and serum were obtained yearly (per-protocol population, n = 84). TGP-specific IgA1, IgA2, IgG4, IgG, and IgE were measured in nasal fluids by ELISA. TGP-specific IgA1, IgA2, and Phleum pratense (Phl p)1, 2, 4, 5b, 6, 7, 11, and 12 IgE and IgG4 were measured in sera by ELISA and ImmunoCAP, respectively.
At years 2 and 3, TGP-IgA1/2 levels in nasal fluid were elevated in SLIT compared with SCIT (4.2- and 3.0-fold for IgA1, 2.0- and 1.8-fold for IgA2, respectively; all P < .01). TGP-IgA1 level in serum was elevated in SLIT compared with SCIT at years 1, 2, and 3 (4.6-, 5.1-, and 4.7-fold, respectively; all P < .001). Serum TGP-IgG level was higher in SCIT compared with SLIT (2.8-fold) at year 2. Serum TGP-IgG4 level was higher in SCIT compared with SLIT at years 1, 2, and 3 (10.4-, 27.4-, and 5.1-fold, respectively; all P < .01). Serum IgG4 levels to Phl p1, 2, 5b, and 6 were increased at years 1, 2, and 3 in SCIT and SLIT compared with placebo (Phl p1: 11.8- and 3.9-fold; Phl p2: 31.6- and 4.4-fold; Phl p5b: 135.5- and 5.3-fold; Phl p6: 145.4- and 14.7-fold, respectively, all at year 2 when levels peaked; P < .05). IgE to TGP in nasal fluid increased in the SLIT group at year 2 but not at year 3 compared with SCIT (2.8-fold; P = .04) and placebo (3.1-fold; P = .02). IgA to TGP and IgE and IgG4 to TGP components stratified participants according to treatment group and clinical response.
The observed induction of IgA1/2 in SLIT and IgG4 in SCIT suggest key differences in the mechanisms of action.
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Genetics of type 1A diabetes Concannon, Patrick; Rich, Stephen S; Nepom, Gerald T
The New England journal of medicine,
04/2009, Letnik:
360, Številka:
16
Journal Article
The goal of personalized medicine is to match the right drugs to the right patients at the right time. Personalized medicine has been most successful in cases where there is a clear genetic linkage ...between a disease and a therapy. This is not the case with type 1 diabetes (T1D), a genetically complex immune-mediated disease of β-cell destruction. Researchers over decades have traced the natural history of disease sufficiently to use autoantibodies as predictive biomarkers for disease risk and to conduct successful clinical trials of disease-modifying therapy. Recent studies, however, have highlighted heterogeneity associated with progression, with nonuniform rate of insulin loss and distinct features of the peri-diagnostic period. Likewise, there is heterogeneity in immune profiles and outcomes in response to therapy. Unexpectedly, from these studies demonstrating perplexing complexity in progression and response to therapy, new biomarker-based principles are emerging for how to achieve personalized therapies for T1D. These include therapy timed to periods of disease activity, use of patient stratification biomarkers to align therapeutic target with disease endotype, pharmacodynamic biomarkers to achieve personalized dosing and appropriate combination therapies, and efficacy biomarkers for "treat-to-target" strategies. These principles provide a template for application of personalized medicine to complex diseases.
Myelin-reactive T cells have been identified in patients with multiple sclerosis (MS) and healthy subjects with comparable frequencies, but the contribution of these autoreactive T cells to disease ...pathology remains unknown. A total of 13,324 T cell libraries generated from blood of 23 patients and 22 healthy controls were interrogated for reactivity to myelin antigens. Libraries derived from CCR6(+) myelin-reactive T cells from patients with MS exhibited significantly enhanced production of interferon-γ (IFN-γ), interleukin-17 (IL-17), and granulocyte-macrophage colony-stimulating factor (GM-CSF) compared to healthy controls. Single-cell clones isolated by major histocompatibility complex/peptide tetramers from CCR6(+) T cell libraries also secreted more proinflammatory cytokines, whereas clones isolated from controls secreted more IL-10. The transcriptomes of myelin-specific CCR6(+) T cells from patients with MS were distinct from those derived from healthy controls and, notably, were enriched in T helper cell 17 (TH17)-induced experimental autoimmune encephalitis gene signatures, and gene signatures derived from TH17 cells isolated other human autoimmune diseases. These data, although not causal, imply that functional differences between antigen-specific T cells from MS and healthy controls are fundamental to disease development and support the notion that IL-10 production from myelin-reactive T cells may act to limit disease progression or even pathogenesis.
Although most patients with type 1 diabetes (T1D) retain some functional insulin-producing islet β cells at the time of diagnosis, the rate of further β 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 β 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.
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