1
|
Chen Y, Shen M, Gu Y, Xu X, Bian L, Yang F, Chen S, Ji L, Liu J, Zhu J, Zhang Z, Fu Q, Cai Y, Chen H, Xu K, Sun M, Zheng X, Shen J, Zhou H, Zhang M, Haskins K, Yu L, Yang T, Shi Y. Pivotal epitopes for islet antigen-specific CD8 + T cell detection improve classification of suspected type 1 diabetes with the HLA-A*0201 allele. Immunol Res 2025; 73:65. [PMID: 40133500 DOI: 10.1007/s12026-025-09616-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2024] [Accepted: 03/03/2025] [Indexed: 03/27/2025]
Abstract
A proportion of patients with new-onset diabetes share similar symptoms with type 1 diabetes (T1D) patients but they are negative for islet antigen-specific autoantibodies. This study was to develop an islet antigen-specific CD8+ T-cell assay to provide autoimmune evidence regarding these "suspected" T1D patients. HLA-A*0201 individuals with autoAbs+ T1D, autoAbs- suspected T1D, and type 2 diabetes, along with HLA-A*0201 healthy controls were recruited. Using interferon-γ enzyme-linked immunospot assays, the percentages of participants in each group with various islet antigen-specific CD8+ T cells were determined. Sixteen out of the 28 islet antigen-specific epitopes tested were T1D specific, meaning that there was a significantly (P < 0.05) greater epitope positivity rate in the autoAbs+ T1D cohort than in the healthy controls. Using a cutoff value of two positive epitopes, the 16-epitope panel led to a sensitivity of 75.0% and a specificity of 94.4% regarding the autoAbs+ T1D patients. Even when using an optimized five-epitope panel, the results were highly accurate. Notably, in the application phase of the study, 77.8% of a new cohort of autoAbs- suspected T1D patients exhibited positivity when using the five-epitope optimized panel. This highly accurate method, especially for pediatric patients, will improve clinical diagnosis and etiological classification of autoimmune T1D.
Collapse
Affiliation(s)
- Yang Chen
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Min Shen
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Yong Gu
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Xinyu Xu
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Lingling Bian
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
- Department of Endocrinology, Yancheng City No. 1 People's Hospital, Yancheng, 224005, Jiangsu, China
| | - Fan Yang
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
- Department of Endocrinology, The Affiliated Wuxi No.2 People'S Hospital of Nanjing Medical University, Wuxi, 214000, Jiangsu, China
| | - Shuang Chen
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Li Ji
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
- Department of Emergency Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Jin Liu
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
- Department of Pediatrics, Huai'an First People's Hospital, Huai'an, 223300, Jiangsu, China
| | - Jing Zhu
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
- Department of Endocrinology, The Third Affiliated Hospital of Soochow University, Changzhou, 213000, Jiangsu, China
| | - Zheng Zhang
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
- Department of Critical Care Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Qi Fu
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Yun Cai
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Heng Chen
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Kuanfeng Xu
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Min Sun
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Xuqin Zheng
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Jie Shen
- HLA Laboratory, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Hongwen Zhou
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Mei Zhang
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Kathryn Haskins
- Department of Immunology and Microbiology, University of Colorado School of Medicine, Aurora, CO, 80045, USA
| | - Liping Yu
- Barbara Davis Center for Childhood Diabetes, University of Colorado at Denver and Health Sciences Center, 1775 North Ursula Street, Aurora, CO, 80045, USA
| | - Tao Yang
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
| | - Yun Shi
- Department of Endocrinology & Metabolism, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
| |
Collapse
|
2
|
Lacorcia M, Bhattacharjee P, Foster A, Hardy MY, Tye-Din JA, Karas JA, Wentworth JM, Cameron FJ, Mannering SI. BASTA, a simple whole-blood assay for measuring β cell antigen-specific CD4 + T cell responses in type 1 diabetes. Sci Transl Med 2025; 17:eadt2124. [PMID: 40106580 DOI: 10.1126/scitranslmed.adt2124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2024] [Accepted: 02/21/2025] [Indexed: 03/22/2025]
Abstract
Type 1 diabetes (T1D) is an autoimmune disease where T cells mediate the destruction of the insulin-producing β cells found within the islets of Langerhans in the pancreas. Autoantibodies to β cell antigens are the only tests available to detect β cell autoimmunity. T cell responses to β cell antigens, which are known to cause T1D, can only be measured in research settings because of the complexity of assays and the large blood volumes required. Here, we describe the β cell antigen-specific T cell assay (BASTA). BASTA is a simple whole-blood assay that can detect human CD4+ T cell responses to β cell antigens by measuring antigen-stimulated interleukin-2 (IL-2) production. BASTA is both more sensitive and specific than the CFSE (carboxyfluorescein diacetate succinimidyl ester)-based proliferation assay. We used BASTA to identify the regions of preproinsulin that stimulated T cell responses specifically in blood from people with T1D. BASTA can be done with as little as 2 to 3 milliliters of blood. We found that effector memory CD4+ T cells are the primary producers of IL-2 in response to preproinsulin peptides. We then evaluated responses to individual and pooled preproinsulin peptides in a cross-sectional study of pediatric patients: without T1D, without T1D but with a first-degree relative with T1D, or diagnosed with T1D. In contrast with other preproinsulin peptides, full-length C-peptide (PI33-63) showed high specificity for T1D [area under the curve (AUC) = 0.86)]. We suggest that BASTA will be a useful tool for monitoring changes in β cell-specific CD4+ T cell responses both in research and clinical settings.
Collapse
Affiliation(s)
- Matthew Lacorcia
- Immunology and Diabetes Unit, St. Vincent's Institute of Medical Research, Fitzroy, Victoria 3065, Australia
| | - Pushpak Bhattacharjee
- Immunology and Diabetes Unit, St. Vincent's Institute of Medical Research, Fitzroy, Victoria 3065, Australia
| | - Abby Foster
- Immunology and Diabetes Unit, St. Vincent's Institute of Medical Research, Fitzroy, Victoria 3065, Australia
| | - Melinda Y Hardy
- Immunology Division, Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia
- Department of Medical Biology, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Jason A Tye-Din
- Immunology Division, Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia
- Department of Medical Biology, University of Melbourne, Parkville, Victoria 3010, Australia
- Department of Gastroenterology, Royal Melbourne Hospital, Parkville, Victoria 3050, Australia
| | - John A Karas
- School of Chemistry, University of Melbourne, Parkville, Victoria 3010, Australia
| | - John M Wentworth
- Immunology and Diabetes Unit, St. Vincent's Institute of Medical Research, Fitzroy, Victoria 3065, Australia
- Department of Diabetes and Endocrinology, Royal Melbourne Hospital, Parkville, Victoria 3050, Australia
- Department of Medicine, Royal Melbourne Hospital, Parkville, Victoria 3050, Australia
| | - Fergus J Cameron
- Department of Endocrinology and Diabetes, Royal Children's Hospital, Parkville, Victoria 3052, Australia
- Murdoch Children's Research Institute, Parkville, Victoria 3052, Australia
- Department of Paediatrics, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Stuart I Mannering
- Immunology and Diabetes Unit, St. Vincent's Institute of Medical Research, Fitzroy, Victoria 3065, Australia
- Department of Medicine, University of Melbourne, St. Vincent's Hospital, Fitzroy, Victoria 3065, Australia
| |
Collapse
|
3
|
Herold KC, Delong T, Perdigoto AL, Biru N, Brusko TM, Walker LSK. The immunology of type 1 diabetes. Nat Rev Immunol 2024; 24:435-451. [PMID: 38308004 PMCID: PMC7616056 DOI: 10.1038/s41577-023-00985-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/15/2023] [Indexed: 02/04/2024]
Abstract
Following the seminal discovery of insulin a century ago, treatment of individuals with type 1 diabetes (T1D) has been largely restricted to efforts to monitor and treat metabolic glucose dysregulation. The recent regulatory approval of the first immunotherapy that targets T cells as a means to delay the autoimmune destruction of pancreatic β-cells highlights the critical role of the immune system in disease pathogenesis and tends to pave the way for other immune-targeted interventions for T1D. Improving the efficacy of such interventions across the natural history of the disease will probably require a more detailed understanding of the immunobiology of T1D, as well as technologies to monitor residual β-cell mass and function. Here we provide an overview of the immune mechanisms that underpin the pathogenesis of T1D, with a particular emphasis on T cells.
Collapse
Affiliation(s)
- Kevan C Herold
- Department of Immunobiology, Yale University, New Haven, CT, USA.
- Department of Internal Medicine, Yale University, New Haven, CT, USA.
| | - Thomas Delong
- Anschutz Medical Campus, University of Colorado, Denver, CO, USA
| | - Ana Luisa Perdigoto
- Department of Internal Medicine, Yale University, New Haven, CT, USA
- Internal Medicine, VA Connecticut Healthcare System, West Haven, CT, USA
| | - Noah Biru
- Department of Immunobiology, Yale University, New Haven, CT, USA
| | - Todd M Brusko
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida Diabetes Institute, Gainesville, FL, USA
| | - Lucy S K Walker
- Institute of Immunity & Transplantation, University College London, London, UK.
- Division of Infection & Immunity, University College London, London, UK.
| |
Collapse
|
4
|
Ettinger RA, Buitinga M, Vandamme C, Afonso G, Gomez R, Arribas-Layton D, Bissenova S, Speake C, Reijonen H, Kinnunen T, Overbergh L, Mallone R, Kwok WW, James EA. Technical Validation and Utility of an HLA Class II Tetramer Assay for Type 1 Diabetes: A Multicenter Study. J Clin Endocrinol Metab 2023; 109:183-196. [PMID: 37474341 DOI: 10.1210/clinem/dgad434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 06/28/2023] [Accepted: 06/17/2023] [Indexed: 07/22/2023]
Abstract
CONTEXT Validated assays to measure autoantigen-specific T-cell frequency and phenotypes are needed for assessing the risk of developing diabetes, monitoring disease progression, evaluating responses to treatment, and personalizing antigen-based therapies. OBJECTIVE Toward this end, we performed a technical validation of a tetramer assay for HLA-DRA-DRB1*04:01, a class II allele that is strongly associated with susceptibility to type 1 diabetes (T1D). METHODS HLA-DRA-DRB1*04:01-restricted T cells specific for immunodominant epitopes from islet cell antigens GAD65, IGRP, preproinsulin, and ZnT8, and a reference influenza epitope, were enumerated and phenotyped in a single staining tube with a tetramer assay. Single and multicenter testing was performed, using a clone-spiked specimen and replicate samples from T1D patients, with a target coefficient of variation (CV) less than 30%. The same assay was applied to an exploratory cross-sectional sample set with 24 T1D patients to evaluate the utility of the assay. RESULTS Influenza-specific T-cell measurements had mean CVs of 6% for the clone-spiked specimen and 11% for T1D samples in single-center testing, and 20% and 31%, respectively, for multicenter testing. Islet-specific T-cell measurements in these same samples had mean CVs of 14% and 23% for single-center and 23% and 41% for multicenter testing. The cross-sectional study identified relationships between T-cell frequencies and phenotype and disease duration, sex, and autoantibodies. A large fraction of the islet-specific T cells exhibited a naive phenotype. CONCLUSION Our results demonstrate that the assay is reproducible and useful to characterize islet-specific T cells and identify correlations between T-cell measures and clinical traits.
Collapse
Affiliation(s)
- Ruth A Ettinger
- Center for Translational Immunology, Benaroya Research Institute, Seattle, WA 98101, USA
| | - Mijke Buitinga
- Laboratory for Clinical and Experimental Endocrinology, KU Leuven, 3000 Leuven, Belgium
| | - Céline Vandamme
- Department of Clinical Microbiology, Institute of Clinical Medicine, University of Eastern Finland, 70210 Kuopio, Finland
| | - Georgia Afonso
- Diabetes and Autoimmunity Research Laboratory, Université Paris Cité, Institut Cochin, CNRS, INSERM, 75014 Paris, France
| | - Rebecca Gomez
- Center for Translational Immunology, Benaroya Research Institute, Seattle, WA 98101, USA
| | - David Arribas-Layton
- Department of Immunology and Theranostics, City of Hope Medical Center, Beckman Research Institute, Duarte, CA 91010, USA
| | - Samal Bissenova
- Laboratory for Clinical and Experimental Endocrinology, KU Leuven, 3000 Leuven, Belgium
| | - Cate Speake
- Center for Interventional Immunology, Benaroya Research Institute, Seattle, WA 98101, USA
| | - Helena Reijonen
- Department of Immunology and Theranostics, City of Hope Medical Center, Beckman Research Institute, Duarte, CA 91010, USA
| | - Tuure Kinnunen
- Department of Clinical Microbiology, Institute of Clinical Medicine, University of Eastern Finland, 70210 Kuopio, Finland
- Eastern Finland Laboratory Centre (ISLAB), 70210 Kuopio, Finland
| | - Lut Overbergh
- Laboratory for Clinical and Experimental Endocrinology, KU Leuven, 3000 Leuven, Belgium
| | - Roberto Mallone
- Diabetes and Autoimmunity Research Laboratory, Université Paris Cité, Institut Cochin, CNRS, INSERM, 75014 Paris, France
- Department of Internal Medicine, Assistance Publique Hôpitaux de Paris, Service de Diabétologie et Immunologie Clinique, Cochin Hospital, 75014 Paris, France
| | - William W Kwok
- Center for Translational Immunology, Benaroya Research Institute, Seattle, WA 98101, USA
| | - Eddie A James
- Center for Translational Immunology, Benaroya Research Institute, Seattle, WA 98101, USA
| |
Collapse
|
5
|
Atkinson MA, Mirmira RG. The pathogenic "symphony" in type 1 diabetes: A disorder of the immune system, β cells, and exocrine pancreas. Cell Metab 2023; 35:1500-1518. [PMID: 37478842 PMCID: PMC10529265 DOI: 10.1016/j.cmet.2023.06.018] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 06/22/2023] [Accepted: 06/28/2023] [Indexed: 07/23/2023]
Abstract
Type 1 diabetes (T1D) is widely considered to result from the autoimmune destruction of insulin-producing β cells. This concept has been a central tenet for decades of attempts seeking to decipher the disorder's pathogenesis and prevent/reverse the disease. Recently, this and many other disease-related notions have come under increasing question, particularly given knowledge gained from analyses of human T1D pancreas. Perhaps most crucial are findings suggesting that a collective of cellular constituents-immune, endocrine, and exocrine in origin-mechanistically coalesce to facilitate T1D. This review considers these emerging concepts, from basic science to clinical research, and identifies several key remaining knowledge voids.
Collapse
Affiliation(s)
- Mark A Atkinson
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL 32610, USA.
| | - Raghavendra G Mirmira
- Departments of Medicine and Pediatrics, The University of Chicago, Chicago, IL 60637, USA
| |
Collapse
|
6
|
Arif S, Domingo-Vila C, Pollock E, Christakou E, Williams E, Tree TIM. Monitoring islet specific immune responses in type 1 diabetes clinical immunotherapy trials. Front Immunol 2023; 14:1183909. [PMID: 37283770 PMCID: PMC10240960 DOI: 10.3389/fimmu.2023.1183909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 05/02/2023] [Indexed: 06/08/2023] Open
Abstract
The number of immunotherapeutic clinical trials in type 1 diabetes currently being conducted is expanding, and thus there is a need for robust immune-monitoring assays which are capable of detecting and characterizing islet specific immune responses in peripheral blood. Islet- specific T cells can serve as biomarkers and as such can guide drug selection, dosing regimens and immunological efficacy. Furthermore, these biomarkers can be utilized in patient stratification which can then benchmark suitability for participation in future clinical trials. This review focusses on the commonly used immune-monitoring techniques including multimer and antigen induced marker assays and the potential to combine these with single cell transcriptional profiling which may provide a greater understanding of the mechanisms underlying immuno-intervention. Although challenges remain around some key areas such as the need for harmonizing assays, technological advances mean that multiparametric information derived from a single sample can be used in coordinated efforts to harmonize biomarker discovery and validation. Moreover, the technologies discussed here have the potential to provide a unique insight on the effect of therapies on key players in the pathogenesis of T1D that cannot be obtained using antigen agnostic approaches.
Collapse
|
7
|
Limanaqi F, Vicentini C, Saulle I, Clerici M, Biasin M. The role of endoplasmic reticulum aminopeptidases in type 1 diabetes mellitus. Life Sci 2023; 323:121701. [PMID: 37059356 DOI: 10.1016/j.lfs.2023.121701] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 04/05/2023] [Accepted: 04/11/2023] [Indexed: 04/16/2023]
Abstract
Type-I diabetes mellitus (T1DM) is generally considered as a chronic, T-cell mediated autoimmune disease. This notwithstanding, both the endogenous characteristics of β-cells, and their response to environmental factors and exogenous inflammatory stimuli are key events in disease progression and exacerbation. As such, T1DM is now recognized as a multifactorial condition, with its onset being influenced by both genetic predisposition and environmental factors, among which, viral infections represent major triggers. In this frame, endoplasmic reticulum aminopeptidase 1 (ERAP1) and 2 (ERAP2) hold center stage. ERAPs represent the main hydrolytic enzymes specialized in trimming of N-terminal antigen peptides to be bound by MHC class I molecules and presented to CD8+ T cells. Thus, abnormalities in ERAPs expression alter the peptide-MHC-I repertoire both quantitatively and qualitatively, fostering both autoimmune and infectious diseases. Although only a few studies succeeded in determining direct associations between ERAPs variants and T1DM susceptibility/outbreak, alterations of ERAPs do impinge on a plethora of biological events which might indeed contribute to the disease development/exacerbation. Beyond abnormal self-antigen peptide trimming, these include preproinsulin processing, nitric oxide (NO) production, ER stress, cytokine responsiveness, and immune cell recruitment/activity. The present review brings together direct and indirect evidence focused on the immunobiological role of ERAPs in T1DM onset and progression, covering both genetic and environmental aspects.
Collapse
Affiliation(s)
- Fiona Limanaqi
- Department of Biomedical and Clinical Sciences, University of Milan, Via G.B. Grassi, 20122 Milan, Italy; Department of Pathophysiology and Transplantation, University of Milan, Via Francesco Sforza, 20122 Milan, Italy
| | - Chiara Vicentini
- Department of Biomedical and Clinical Sciences, University of Milan, Via G.B. Grassi, 20122 Milan, Italy
| | - Irma Saulle
- Department of Biomedical and Clinical Sciences, University of Milan, Via G.B. Grassi, 20122 Milan, Italy; Department of Pathophysiology and Transplantation, University of Milan, Via Francesco Sforza, 20122 Milan, Italy
| | - Mario Clerici
- Department of Pathophysiology and Transplantation, University of Milan, Via Francesco Sforza, 20122 Milan, Italy; Don C. Gnocchi Foundation, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Foundation, Via A. Capecelatro 66, 20148 Milan, Italy
| | - Mara Biasin
- Department of Biomedical and Clinical Sciences, University of Milan, Via G.B. Grassi, 20122 Milan, Italy.
| |
Collapse
|
8
|
Roep BO. The need and benefit of immune monitoring to define patient and disease heterogeneity, mechanisms of therapeutic action and efficacy of intervention therapy for precision medicine in type 1 diabetes. Front Immunol 2023; 14:1112858. [PMID: 36733487 PMCID: PMC9887285 DOI: 10.3389/fimmu.2023.1112858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 01/04/2023] [Indexed: 01/18/2023] Open
Abstract
The current standard of care for type 1 diabetes patients is limited to treatment of the symptoms of the disease, insulin insufficiency and its complications, not its cause. Given the autoimmune nature of type 1 diabetes, immunology is critical to understand the mechanism of disease progression, patient and disease heterogeneity and therapeutic action. Immune monitoring offers the key to all this essential knowledge and is therefore indispensable, despite the challenges and costs associated. In this perspective, I attempt to make this case by providing evidence from the past to create a perspective for future trials and patient selection.
Collapse
|
9
|
Halliez C, Ibrahim H, Otonkoski T, Mallone R. In vitro beta-cell killing models using immune cells and human pluripotent stem cell-derived islets: Challenges and opportunities. Front Endocrinol (Lausanne) 2023; 13:1076683. [PMID: 36726462 PMCID: PMC9885197 DOI: 10.3389/fendo.2022.1076683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 12/23/2022] [Indexed: 01/19/2023] Open
Abstract
Type 1 diabetes (T1D) is a disease of both autoimmunity and β-cells. The β-cells play an active role in their own demise by mounting defense mechanisms that are insufficient at best, and that can become even deleterious in the long term. This complex crosstalk is important to understanding the physiological defense mechanisms at play in healthy conditions, their alterations in the T1D setting, and therapeutic agents that may boost such mechanisms. Robust protocols to develop stem-cell-derived islets (SC-islets) from human pluripotent stem cells (hPSCs), and islet-reactive cytotoxic CD8+ T-cells from peripheral blood mononuclear cells offer unprecedented opportunities to study this crosstalk. Challenges to develop in vitro β-cell killing models include the cluster morphology of SC-islets, the relatively weak cytotoxicity of most autoimmune T-cells and the variable behavior of in vitro expanded CD8+ T-cells. These challenges may however be highly rewarding in light of the opportunities offered by such models. Herein, we discuss these opportunities including: the β-cell/immune crosstalk in an islet microenvironment; the features that make β-cells more sensitive to autoimmunity; therapeutic agents that may modulate β-cell vulnerability; and the possibility to perform analyses in an autologous setting, i.e., by generating T-cell effectors and SC-islets from the same donor.
Collapse
Affiliation(s)
- Clémentine Halliez
- Université Paris Cité, Institut Cochin, CNRS, INSERM, Paris, France
- Assistance Publique Hôpitaux de Paris, Service de Diabétologie et Immunologie Clinique, Cochin Hospital, Paris, France
| | - Hazem Ibrahim
- Stem Cells and Metabolism Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Timo Otonkoski
- Assistance Publique Hôpitaux de Paris, Service de Diabétologie et Immunologie Clinique, Cochin Hospital, Paris, France
- Department of Pediatrics, Helsinki University Hospital, Helsinki, Finland
| | - Roberto Mallone
- Université Paris Cité, Institut Cochin, CNRS, INSERM, Paris, France
- Assistance Publique Hôpitaux de Paris, Service de Diabétologie et Immunologie Clinique, Cochin Hospital, Paris, France
| |
Collapse
|
10
|
Postigo-Fernandez J, Firdessa-Fite R, Creusot RJ. Preclinical evaluation of a precision medicine approach to DNA vaccination in type 1 diabetes. Proc Natl Acad Sci U S A 2022; 119:e2110987119. [PMID: 35385352 PMCID: PMC9169641 DOI: 10.1073/pnas.2110987119] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 02/09/2022] [Indexed: 12/21/2022] Open
Abstract
Antigen-specific immunotherapy involves the delivery of self-antigens as proteins or peptides (or using nucleic acids encoding them) to reestablish tolerance. The Endotope platform supports the optimal presentation of endogenously expressed epitopes on appropriate major histocompatibility complex (MHC) class I and II molecules. Using specific epitopes that are disease-relevant (including neoepitopes and mimotopes) and restricted to the subject’s MHC haplotypes provides a more focused and tailored way of targeting autoreactive T cells. We evaluated the efficacy of an Endotope DNA vaccine tailored to the nonobese diabetic (NOD) mouse in parallel to one expressing the Proinsulin protein, a central autoantigen in NOD mice, and assessed the influence of several parameters (e.g., route, dosing frequency, disease stage) on diabetes prevention. Secretion of encoded peptides and intradermal delivery of DNA offered more effective disease prevention. Long-term weekly treatments were needed to achieve protection that can persist after discontinuation, likely mediated by regulatory T cells induced by at least one epitope. Although epitopes were presented for at least 2 wk, weekly treatments were needed, at least initially, to achieve significant protection. While Endotope and Proinsulin DNA vaccines were effective at both the prediabetic normoglycemic and dysglycemic stages of disease, Proinsulin provided better protection in the latter stage, particularly in animals with slower progression of disease, and Endotope limited insulitis the most in the earlier stage. Thus, our data support the possibility of applying a precision medicine approach based on tailored epitopes for the treatment of tissue-specific autoimmune diseases with DNA vaccines.
Collapse
Affiliation(s)
- Jorge Postigo-Fernandez
- Columbia Center for Translational Immunology, Department of Medicine, Columbia University Irving Medical Center, New York, NY 10032
- Naomi Berrie Diabetes Center, Columbia University Irving Medical Center, New York, NY 10032
| | - Rebuma Firdessa-Fite
- Columbia Center for Translational Immunology, Department of Medicine, Columbia University Irving Medical Center, New York, NY 10032
- Naomi Berrie Diabetes Center, Columbia University Irving Medical Center, New York, NY 10032
| | - Rémi J. Creusot
- Columbia Center for Translational Immunology, Department of Medicine, Columbia University Irving Medical Center, New York, NY 10032
- Naomi Berrie Diabetes Center, Columbia University Irving Medical Center, New York, NY 10032
| |
Collapse
|
11
|
Anderson AM, Landry LG, Alkanani AA, Pyle L, Powers AC, Atkinson MA, Mathews CE, Roep BO, Michels AW, Nakayama M. Human islet T cells are highly reactive to preproinsulin in type 1 diabetes. Proc Natl Acad Sci U S A 2021; 118:e2107208118. [PMID: 34611019 PMCID: PMC8521679 DOI: 10.1073/pnas.2107208118] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/16/2021] [Indexed: 01/29/2023] Open
Abstract
Cytotoxic CD8 T lymphocytes play a central role in the tissue destruction of many autoimmune disorders. In type 1 diabetes (T1D), insulin and its precursor preproinsulin are major self-antigens targeted by T cells. We comprehensively examined preproinsulin specificity of CD8 T cells obtained from pancreatic islets of organ donors with and without T1D and identified epitopes throughout the entire preproinsulin protein and defective ribosomal products derived from preproinsulin messenger RNA. The frequency of preproinsulin-reactive T cells was significantly higher in T1D donors than nondiabetic donors and also differed by individual T1D donor, ranging from 3 to over 40%, with higher frequencies in T1D organ donors with HLA-A*02:01. Only T cells reactive to preproinsulin-related peptides isolated from T1D donors demonstrated potent autoreactivity. Reactivity to similar regions of preproinsulin was also observed in peripheral blood of a separate cohort of new-onset T1D patients. These findings have important implications for designing antigen-specific immunotherapies and identifying individuals that may benefit from such interventions.
Collapse
Affiliation(s)
- Amanda M Anderson
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO 80045
| | - Laurie G Landry
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO 80045
| | - Aimon A Alkanani
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO 80045
| | - Laura Pyle
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO 80045
- Department of Biostatistics and Informatics, University of Colorado School of Public Health, Aurora, CO 80045
| | - Alvin C Powers
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232
- Medical Service, Veterans Affairs Tennessee Valley Healthcare System, Nashville, TN 37212
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Mark A Atkinson
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL 32610
| | - Clayton E Mathews
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL 32610
| | - Bart O Roep
- Department of Diabetes Immunology, Diabetes and Metabolism Research Institute, Beckman Research Institute of City of Hope, Duarte, CA 91010
- Department of Internal Medicine, Leiden University Medical Center, 2300RC Leiden, The Netherlands
| | - Aaron W Michels
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO 80045
- Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO 80045
- Department of Immunology and Microbiology, University of Colorado School of Medicine, Aurora, CO 80045
| | - Maki Nakayama
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO 80045;
- Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO 80045
- Department of Immunology and Microbiology, University of Colorado School of Medicine, Aurora, CO 80045
| |
Collapse
|
12
|
Simmons KM, Mitchell AM, Alkanani AA, McDaniel KA, Baschal EE, Armstrong T, Pyle L, Yu L, Michels AW. Failed Genetic Protection: Type 1 Diabetes in the Presence of HLA-DQB1*06:02. Diabetes 2020; 69:1763-1769. [PMID: 32439825 PMCID: PMC7372070 DOI: 10.2337/db20-0038] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Accepted: 05/13/2020] [Indexed: 12/16/2022]
Abstract
Certain HLA class II genes increase the risk for type 1 diabetes (T1D) development while others provide protection from disease development. HLA class II alleles encode MHC proteins on antigen-presenting cells, which function to present peptides and activate CD4 T cells. The DRB1*15:01 (DR15)-DQA1*01:02-DQB1*06:02 (DQ6) haplotype provides dominant protection across all stages of T1D and is a common haplotype found in Caucasians. However, it is present in <1% of people with T1D. Knowing which metabolic, immunologic, and genetic features are unique to individuals who fail genetic protection and develop T1D is important for defining the underlying mechanisms of DQB1*06:02-mediated protection. We describe a T1D cohort with DQB1*06:02 (n = 50) and compare them to individuals with T1D and without DQB1*06:02 (n = 2,759) who were identified over the last 26 years at the Barbara Davis Center for Diabetes. The age at diagnosis was similar between the cohorts and normally distributed throughout childhood and early adulthood. The average hemoglobin A1c was 10.8 ± 2.8% (95 ± 7 mmol/mol) at diagnosis in those DQB1*06:02 positive. The majority of T1D DQB1*06:02 + individuals were positive for one or more islet autoantibodies; however, there was a greater proportion who were islet autoantibody negative compared with those T1D DQB1*06:02 - individuals. Interestingly, DQB1*03:02, which confers significant T1D risk, was present in only those DQB1*06:02 + individuals with islet autoantibodies. This is one of the largest studies examining patients presenting with clinical T1D in the presence of DQB1*06:02, which provides a population to study the mechanisms of failed genetic protection against T1D.
Collapse
Affiliation(s)
- Kimber M Simmons
- Barbara Davis Center for Diabetes, University of Colorado, Aurora, CO
| | - Angela M Mitchell
- Barbara Davis Center for Diabetes, University of Colorado, Aurora, CO
| | - Aimon A Alkanani
- Barbara Davis Center for Diabetes, University of Colorado, Aurora, CO
| | | | - Erin E Baschal
- Barbara Davis Center for Diabetes, University of Colorado, Aurora, CO
| | - Taylor Armstrong
- Barbara Davis Center for Diabetes, University of Colorado, Aurora, CO
| | - Laura Pyle
- Barbara Davis Center for Diabetes, University of Colorado, Aurora, CO
| | - Liping Yu
- Barbara Davis Center for Diabetes, University of Colorado, Aurora, CO
| | - Aaron W Michels
- Barbara Davis Center for Diabetes, University of Colorado, Aurora, CO
| |
Collapse
|
13
|
Hanna SJ, Powell WE, Long AE, Robinson EJS, Davies J, Megson C, Howell A, Jones TJ, Ladell K, Price DA, Dayan CM, Williams AJK, Gillespie KM, Wong FS. Slow progressors to type 1 diabetes lose islet autoantibodies over time, have few islet antigen-specific CD8 + T cells and exhibit a distinct CD95 hi B cell phenotype. Diabetologia 2020; 63:1174-1185. [PMID: 32157332 PMCID: PMC7228996 DOI: 10.1007/s00125-020-05114-7] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Accepted: 01/13/2020] [Indexed: 02/07/2023]
Abstract
AIMS/HYPOTHESIS The aim of this study was to characterise islet autoantibody profiles and immune cell phenotypes in slow progressors to type 1 diabetes. METHODS Immunological variables were compared across peripheral blood samples obtained from slow progressors to type 1 diabetes, individuals with newly diagnosed or long-standing type 1 diabetes, and healthy individuals. Polychromatic flow cytometry was used to characterise the phenotypic attributes of B and T cells. Islet autoantigen-specific B cells were quantified using an enzyme-linked immunospot (ELISpot) assay and islet autoantigen-specific CD8+ T cells were quantified using peptide-HLA class I tetramers. Radioimmunoassays were used to detect islet autoantibodies. Sera were assayed for various chemokines, cytokines and soluble receptors via ELISAs. RESULTS Islet autoantibodies were lost over time in slow progressors. Various B cell subsets expressed higher levels of CD95 in slow progressors, especially after polyclonal stimulation, compared with the corresponding B cell subsets in healthy donors (p < 0.05). The phenotypic characteristics of CD4+ and CD8+ T cells were similar in slow progressors and healthy donors. Lower frequencies of CD4+ T cells with a central memory phenotype (CD27int, CD127+, CD95int) were observed in slow progressors compared with healthy donors (mean percentage of total CD4+ T cells was 3.00% in slow progressors vs 4.67% in healthy donors, p < 0.05). Autoreactive B cell responses to proinsulin were detected at higher frequencies in slow progressors compared with healthy donors (median no. of spots was 0 in healthy donors vs 24.34 in slow progressors, p < 0.05) in an ELISpot assay. Islet autoantigen-specific CD8+ T cell responses were largely absent in slow progressors and healthy donors. Serum levels of DcR3, the decoy receptor for CD95L, were elevated in slow progressors compared with healthy donors (median was 1087 pg/ml in slow progressors vs 651 pg/ml in healthy donors, p = 0.06). CONCLUSIONS/INTERPRETATION In this study, we found that slow progression to type 1 diabetes was associated with a loss of islet autoantibodies and a distinct B cell phenotype, consistent with enhanced apoptotic regulation of peripheral autoreactivity via CD95. These phenotypic changes warrant further studies in larger cohorts to determine their functional implications.
Collapse
Affiliation(s)
- Stephanie J Hanna
- Division of Infection and Immunity, Cardiff University School of Medicine, Heath Park, Cardiff, CF14 4XN, UK
| | - Wendy E Powell
- Division of Infection and Immunity, Cardiff University School of Medicine, Heath Park, Cardiff, CF14 4XN, UK
| | - Anna E Long
- Diabetes and Metabolism, Bristol Medical School, University of Bristol, Bristol, UK
| | - Emma J S Robinson
- Division of Infection and Immunity, Cardiff University School of Medicine, Heath Park, Cardiff, CF14 4XN, UK
| | - Joanne Davies
- Division of Infection and Immunity, Cardiff University School of Medicine, Heath Park, Cardiff, CF14 4XN, UK
| | - Clare Megson
- Diabetes and Metabolism, Bristol Medical School, University of Bristol, Bristol, UK
| | - Alexandra Howell
- Division of Infection and Immunity, Cardiff University School of Medicine, Heath Park, Cardiff, CF14 4XN, UK
| | - Taz J Jones
- Division of Infection and Immunity, Cardiff University School of Medicine, Heath Park, Cardiff, CF14 4XN, UK
| | - Kristin Ladell
- Division of Infection and Immunity, Cardiff University School of Medicine, Heath Park, Cardiff, CF14 4XN, UK
| | - David A Price
- Division of Infection and Immunity, Cardiff University School of Medicine, Heath Park, Cardiff, CF14 4XN, UK
| | - Colin M Dayan
- Division of Infection and Immunity, Cardiff University School of Medicine, Heath Park, Cardiff, CF14 4XN, UK
| | | | - Kathleen M Gillespie
- Diabetes and Metabolism, Bristol Medical School, University of Bristol, Bristol, UK
| | - F Susan Wong
- Division of Infection and Immunity, Cardiff University School of Medicine, Heath Park, Cardiff, CF14 4XN, UK.
| |
Collapse
|
14
|
Wiedeman AE, Muir VS, Rosasco MG, DeBerg HA, Presnell S, Haas B, Dufort MJ, Speake C, Greenbaum CJ, Serti E, Nepom GT, Blahnik G, Kus AM, James EA, Linsley PS, Long SA. Autoreactive CD8+ T cell exhaustion distinguishes subjects with slow type 1 diabetes progression. J Clin Invest 2020; 130:480-490. [PMID: 31815738 PMCID: PMC6934185 DOI: 10.1172/jci126595] [Citation(s) in RCA: 122] [Impact Index Per Article: 24.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Accepted: 10/08/2019] [Indexed: 12/22/2022] Open
Abstract
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.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | - Cate Speake
- Diabetes Program, Benaroya Research Institute (BRI) at Virginia Mason, Seattle, Washington, USA
| | - Carla J. Greenbaum
- Diabetes Program, Benaroya Research Institute (BRI) at Virginia Mason, Seattle, Washington, USA
| | | | - Gerald T. Nepom
- Translational Research Program
- Immune Tolerance Network (ITN), Bethesda, Maryland, USA
| | | | | | | | | | | |
Collapse
|
15
|
Speake C, Skinner SO, Berel D, Whalen E, Dufort MJ, Young WC, Odegard JM, Pesenacker AM, Gorus FK, James EA, Levings MK, Linsley PS, Akirav EM, Pugliese A, Hessner MJ, Nepom GT, Gottardo R, Long SA. A composite immune signature parallels disease progression across T1D subjects. JCI Insight 2019; 4:126917. [PMID: 31671072 PMCID: PMC6962023 DOI: 10.1172/jci.insight.126917] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 10/29/2019] [Indexed: 02/06/2023] Open
Abstract
At diagnosis, most people with type 1 diabetes (T1D) produce measurable levels of endogenous insulin, but the rate at which insulin secretion declines is heterogeneous. To explain this heterogeneity, we sought to identify a composite signature predictive of insulin secretion, using a collaborative assay evaluation and analysis pipeline that incorporated multiple cellular and serum measures reflecting β cell health and immune system activity. The ability to predict decline in insulin secretion would be useful for patient stratification for clinical trial enrollment or therapeutic selection. Analytes from 12 qualified assays were measured in shared samples from subjects newly diagnosed with T1D. We developed a computational tool (DIFAcTO, Data Integration Flexible to Account for different Types of data and Outcomes) to identify a composite panel associated with decline in insulin secretion over 2 years following diagnosis. DIFAcTO uses multiple filtering steps to reduce data dimensionality, incorporates error estimation techniques including cross-validation and sensitivity analysis, and is flexible to assay type, clinical outcome, and disease setting. Using this novel analytical tool, we identified a panel of immune markers that, in combination, are highly associated with loss of insulin secretion. The methods used here represent a potentially novel process for identifying combined immune signatures that predict outcomes relevant for complex and heterogeneous diseases like T1D.
Collapse
Affiliation(s)
- Cate Speake
- Benaroya Research Institute at Virginia Mason, Seattle, Washington, USA
| | - Samuel O. Skinner
- Benaroya Research Institute at Virginia Mason, Seattle, Washington, USA
| | - Dror Berel
- Vaccines and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Elizabeth Whalen
- Benaroya Research Institute at Virginia Mason, Seattle, Washington, USA
| | - Matthew J. Dufort
- Benaroya Research Institute at Virginia Mason, Seattle, Washington, USA
| | - William Chad Young
- Vaccines and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Jared M. Odegard
- Benaroya Research Institute at Virginia Mason, Seattle, Washington, USA
| | - Anne M. Pesenacker
- University of British Columbia BC Children’s Hospital Research Institute, Vancouver, British Columbia, Canada
| | - Frans K. Gorus
- Diabetes Research Center, Medical School and University Hospital (UZ Brussel), Brussels Free University Vrije Universiteit Brussel, Brussels, Belgium
| | - Eddie A. James
- Benaroya Research Institute at Virginia Mason, Seattle, Washington, USA
| | - Megan K. Levings
- University of British Columbia BC Children’s Hospital Research Institute, Vancouver, British Columbia, Canada
| | - Peter S. Linsley
- Benaroya Research Institute at Virginia Mason, Seattle, Washington, USA
| | - Eitan M. Akirav
- Research Institute, Islet Biology, New York University Winthrop Hospital, Mineola, New York, USA
- Stony Brook University School of Medicine, Stony Brook, New York, USA
| | - Alberto Pugliese
- Diabetes Research Institute, Department of Medicine, Division of Diabetes Endocrinology and Metabolism, Department of Microbiology and Immunology, Miller School of Medicine, University of Miami, Miami, Florida, USA
| | | | - Gerald T. Nepom
- Benaroya Research Institute at Virginia Mason, Seattle, Washington, USA
- Immune Tolerance Network, Bethesda, Maryland, USA
| | - Raphael Gottardo
- Vaccines and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - S. Alice Long
- Benaroya Research Institute at Virginia Mason, Seattle, Washington, USA
| |
Collapse
|
16
|
Yang JHM, Khatri L, Mickunas M, Williams E, Tatovic D, Alhadj Ali M, Young P, Moyle P, Sahni V, Wang R, Kaur R, Tannahill GM, Beaton AR, Gerlag DM, Savage COS, Napolitano Rosen A, Waldron-Lynch F, Dayan CM, Tree TIM. Phenotypic Analysis of Human Lymph Nodes in Subjects With New-Onset Type 1 Diabetes and Healthy Individuals by Flow Cytometry. Front Immunol 2019; 10:2547. [PMID: 31749806 PMCID: PMC6842967 DOI: 10.3389/fimmu.2019.02547] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Accepted: 10/14/2019] [Indexed: 12/18/2022] Open
Abstract
Background: Ultrasound guided sampling of human lymph node (LN) combined with advanced flow cytometry allows phenotypic analysis of multiple immune cell subsets. These may provide insights into immune processes and responses to immunotherapies not apparent from analysis of the blood. Methods: Ultrasound guided inguinal LN samples were obtained by both fine needle aspiration (FNA) and core needle biopsy in 10 adults within 8 weeks of diagnosis of type 1 diabetes (T1D) and 12 age-matched healthy controls at two study centers. Peripheral blood mononuclear cells (PBMC) were obtained on the same occasion. Samples were transported same day to the central laboratory and analyzed by multicolour flow cytometry. Results: LN sampling was well-tolerated and yielded sufficient cells for analysis in 95% of cases. We confirmed the segregation of CD69+ cells into LN and the predominance of CD8+ Temra cells in blood previously reported. In addition, we demonstrated clear enrichment of CD8+ naïve, FOXP3+ Treg, class-switched B cells, CD56bright NK cells and plasmacytoid dendritic cells (DC) in LNs as well as CD4+ T cells of the Th2 phenotype and those expressing Helios and Ki67. Conventional NK cells were virtually absent from LNs as were Th22 and Th1Th17 cells. Paired correlation analysis of blood and LN in the same individuals indicated that for many cell subsets, especially those associated with activation: such as CD25+ and proliferating (Ki67+) T cells, activated follicular helper T cells and class-switched B cells, levels in the LN compartment could not be predicted by analysis of blood. We also observed an increase in Th1-like Treg and less proliferating (Ki67+) CD4+ T cells in LN from T1D compared to control LNs, changes which were not reflected in the blood. Conclusions: LN sampling in humans is well-tolerated. We provide the first detailed “roadmap” comparing immune subsets in LN vs. blood emphasizing a role for differentiated effector T cells in the blood and T cell regulation, B cell activation and memory in the LN. For many subsets, frequencies in blood, did not correlate with LN, suggesting that LN sampling would be valuable for monitoring immuno-therapies where these subsets may be impacted.
Collapse
Affiliation(s)
- Jennie H M Yang
- Department of Immunobiology, School of Immunology & Microbial Sciences (SIMS), King's College London, London, United Kingdom.,NIHR Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust and King's College London, London, United Kingdom
| | - Leena Khatri
- Department of Immunobiology, School of Immunology & Microbial Sciences (SIMS), King's College London, London, United Kingdom.,NIHR Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust and King's College London, London, United Kingdom
| | - Marius Mickunas
- Department of Immunobiology, School of Immunology & Microbial Sciences (SIMS), King's College London, London, United Kingdom.,NIHR Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust and King's College London, London, United Kingdom
| | - Evangelia Williams
- Department of Immunobiology, School of Immunology & Microbial Sciences (SIMS), King's College London, London, United Kingdom.,NIHR Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust and King's College London, London, United Kingdom
| | - Danijela Tatovic
- Diabetes/Autoimmunity Research Group, Cardiff University School of Medicine, Cardiff, United Kingdom
| | - Mohammad Alhadj Ali
- Diabetes/Autoimmunity Research Group, Cardiff University School of Medicine, Cardiff, United Kingdom
| | | | - Penelope Moyle
- Experimental Medicine and Immunotherapeutics (EMIT), Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Vishal Sahni
- GlaxoSmithKline Medicines Research Centre, Stevenage, United Kingdom
| | - Ryan Wang
- GlaxoSmithKline Medicines Research Centre, Stevenage, United Kingdom
| | - Rejbinder Kaur
- GlaxoSmithKline Medicines Research Centre, Stevenage, United Kingdom
| | | | - Andrew R Beaton
- GlaxoSmithKline Medicines Research Centre, Stevenage, United Kingdom
| | - Danielle M Gerlag
- GlaxoSmithKline Medicines Research Centre, Stevenage, United Kingdom
| | | | | | - Frank Waldron-Lynch
- Experimental Medicine and Immunotherapeutics (EMIT), Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Colin M Dayan
- Diabetes/Autoimmunity Research Group, Cardiff University School of Medicine, Cardiff, United Kingdom
| | - Timothy I M Tree
- Department of Immunobiology, School of Immunology & Microbial Sciences (SIMS), King's College London, London, United Kingdom.,NIHR Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust and King's College London, London, United Kingdom
| |
Collapse
|
17
|
Speake C, Bahnson HT, Wesley JD, Perdue N, Friedrich D, Pham MN, Lanxon-Cookson E, Kwok WW, Sehested Hansen B, von Herrath M, Greenbaum CJ. Systematic Assessment of Immune Marker Variation in Type 1 Diabetes: A Prospective Longitudinal Study. Front Immunol 2019; 10:2023. [PMID: 31572352 PMCID: PMC6753618 DOI: 10.3389/fimmu.2019.02023] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2019] [Accepted: 08/09/2019] [Indexed: 01/06/2023] Open
Abstract
Immune analytes have been widely tested in efforts to understand the heterogeneity of disease progression, risk, and therapeutic responses in type 1 diabetes (T1D). The future clinical utility of such analytes as biomarkers depends on their technical and biological variability, as well as their correlation with clinical outcomes. To assess the variability of a panel of 91 immune analytes, we conducted a prospective study of adults with T1D (<3 years from diagnosis), at 9–10 visits over 1 year. Autoantibodies and frequencies of T-cell, natural killer cell, and myeloid subsets were evaluated; autoreactive T-cell frequencies and function were also measured. We calculated an intraclass correlation coefficient (ICC) for each marker, which is a relative measure of between- and within-subject variability. Of the 91 analytes tested, we identified 35 with high between- and low within-subject variability, indicating their potential ability to be used to stratify subjects. We also provide extensive data regarding technical variability for 64 of the 91 analytes. To pilot the concept that ICC can be used to identify analytes that reflect biological outcomes, the association between each immune analyte and C-peptide was also evaluated using partial least squares modeling. CD8 effector memory T-cell (CD8 EM) frequency exhibited a high ICC and a positive correlation with C-peptide, which was also seen in an independent dataset of recent-onset T1D subjects. More work is needed to better understand the mechanisms underlying this relationship. Here we find that there are a limited number of technically reproducible immune analytes that also have a high ICC. We propose the use of ICC to define within- and between-subject variability and measurement of technical variability for future biomarker identification studies. Employing such a method is critical for selection of analytes to be tested in the context of future clinical trials aiming to understand heterogeneity in disease progression and response to therapy.
Collapse
Affiliation(s)
- Cate Speake
- Benaroya Research Institute at Virginia Mason, Seattle, WA, United States
| | - Henry T Bahnson
- Benaroya Research Institute at Virginia Mason, Seattle, WA, United States
| | - Johnna D Wesley
- Novo Nordisk Research Center Inc., Seattle, WA, United States
| | - Nikole Perdue
- Novo Nordisk Research Center Inc., Seattle, WA, United States
| | - David Friedrich
- Novo Nordisk Research Center Inc., Seattle, WA, United States
| | - Minh N Pham
- Novo Nordisk Research Center Inc., Seattle, WA, United States
| | | | - William W Kwok
- Benaroya Research Institute at Virginia Mason, Seattle, WA, United States
| | | | | | - Carla J Greenbaum
- Benaroya Research Institute at Virginia Mason, Seattle, WA, United States
| |
Collapse
|
18
|
Ahmed S, Cerosaletti K, James E, Long SA, Mannering S, Speake C, Nakayama M, Tree T, Roep BO, Herold KC, Brusko TM. Standardizing T-Cell Biomarkers in Type 1 Diabetes: Challenges and Recent Advances. Diabetes 2019; 68:1366-1379. [PMID: 31221801 PMCID: PMC6609980 DOI: 10.2337/db19-0119] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2019] [Accepted: 04/20/2019] [Indexed: 12/17/2022]
Abstract
Type 1 diabetes (T1D) results from the progressive destruction of pancreatic β-cells in a process mediated primarily by T lymphocytes. The T1D research community has made dramatic progress in understanding the genetic basis of the disease as well as in the development of standardized autoantibody assays that inform both disease risk and progression. Despite these advances, there remains a paucity of robust and accepted biomarkers that can effectively inform on the activity of T cells during the natural history of the disease or in response to treatment. In this article, we discuss biomarker development and validation efforts for evaluation of T-cell responses in patients with and at risk for T1D as well as emerging technologies. It is expected that with systematic planning and execution of a well-conceived biomarker development pipeline, T-cell-related biomarkers would rapidly accelerate disease progression monitoring efforts and the evaluation of intervention therapies in T1D.
Collapse
Affiliation(s)
- Simi Ahmed
- Immunotherapies Program, Research, JDRF, New York, NY
| | | | - Eddie James
- Benaroya Research Institute at Virginia Mason, Seattle, WA
| | - S Alice Long
- Benaroya Research Institute at Virginia Mason, Seattle, WA
| | | | - Cate Speake
- Benaroya Research Institute at Virginia Mason, Seattle, WA
| | - Maki Nakayama
- Departments of Pediatrics and Integrated Immunology, Barbara Davis Center for Diabetes, University of Colorado, Aurora, CO
| | - Timothy Tree
- Department of Immunobiology, King's College London, London, U.K
| | - Bart O Roep
- Department of Diabetes Immunobiology, City of Hope Diabetes & Metabolism Research Institute, Duarte, CA
| | - Kevan C Herold
- Departments of Immunobiology and Medicine, Yale School of Medicine, New Haven, CT
| | - Todd M Brusko
- Department of Pathology, University of Florida Diabetes Institute, Gainesville, FL
| |
Collapse
|
19
|
Gonzalez-Duque S, Azoury ME, Colli ML, Afonso G, Turatsinze JV, Nigi L, Lalanne AI, Sebastiani G, Carré A, Pinto S, Culina S, Corcos N, Bugliani M, Marchetti P, Armanet M, Diedisheim M, Kyewski B, Steinmetz LM, Buus S, You S, Dubois-Laforgue D, Larger E, Beressi JP, Bruno G, Dotta F, Scharfmann R, Eizirik DL, Verdier Y, Vinh J, Mallone R. Conventional and Neo-antigenic Peptides Presented by β Cells Are Targeted by Circulating Naïve CD8+ T Cells in Type 1 Diabetic and Healthy Donors. Cell Metab 2018; 28:946-960.e6. [PMID: 30078552 DOI: 10.1016/j.cmet.2018.07.007] [Citation(s) in RCA: 165] [Impact Index Per Article: 23.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2018] [Revised: 05/20/2018] [Accepted: 07/11/2018] [Indexed: 10/28/2022]
Abstract
Although CD8+ T-cell-mediated autoimmune β cell destruction occurs in type 1 diabetes (T1D), the target epitopes processed and presented by β cells are unknown. To identify them, we combined peptidomics and transcriptomics strategies. Inflammatory cytokines increased peptide presentation in vitro, paralleling upregulation of human leukocyte antigen (HLA) class I expression. Peptide sources featured several insulin granule proteins and all known β cell antigens, barring islet-specific glucose-6-phosphatase catalytic subunit-related protein. Preproinsulin yielded HLA-A2-restricted epitopes previously described. Secretogranin V and its mRNA splice isoform SCG5-009, proconvertase-2, urocortin-3, the insulin gene enhancer protein ISL-1, and an islet amyloid polypeptide transpeptidation product emerged as antigens processed into HLA-A2-restricted epitopes, which, as those already described, were recognized by circulating naive CD8+ T cells in T1D and healthy donors and by pancreas-infiltrating cells in T1D donors. This peptidome opens new avenues to understand antigen processing by β cells and for the development of T cell biomarkers and tolerogenic vaccination strategies.
Collapse
Affiliation(s)
- Sergio Gonzalez-Duque
- INSERM, U1016, Cochin Institute, 75014 Paris, France; CNRS, UMR8104, Cochin Institute, 75014 Paris, France; Paris Descartes University, Sorbonne Paris Cité, 75014 Paris, France; ESPCI Paris, PSL University, Spectrométrie de Masse Biologique et Protéomique, CNRS USR3149, 75005 Paris, France
| | - Marie Eliane Azoury
- INSERM, U1016, Cochin Institute, 75014 Paris, France; CNRS, UMR8104, Cochin Institute, 75014 Paris, France; Paris Descartes University, Sorbonne Paris Cité, 75014 Paris, France
| | - Maikel L Colli
- Université Libre de Bruxelles Center for Diabetes Research and Welbio, Medical Faculty, Université Libre de Bruxelles, 1070 Brussels, Belgium
| | - Georgia Afonso
- INSERM, U1016, Cochin Institute, 75014 Paris, France; CNRS, UMR8104, Cochin Institute, 75014 Paris, France; Paris Descartes University, Sorbonne Paris Cité, 75014 Paris, France
| | - Jean-Valery Turatsinze
- Université Libre de Bruxelles Center for Diabetes Research and Welbio, Medical Faculty, Université Libre de Bruxelles, 1070 Brussels, Belgium
| | - Laura Nigi
- University of Siena, Department of Medicine, Surgery and Neuroscience, Diabetes Unit and Fondazione Umberto di Mario ONLUS, Toscana Life Sciences, 53100 Siena, Italy
| | - Ana Ines Lalanne
- INSERM, U1016, Cochin Institute, 75014 Paris, France; CNRS, UMR8104, Cochin Institute, 75014 Paris, France; Paris Descartes University, Sorbonne Paris Cité, 75014 Paris, France
| | - Guido Sebastiani
- University of Siena, Department of Medicine, Surgery and Neuroscience, Diabetes Unit and Fondazione Umberto di Mario ONLUS, Toscana Life Sciences, 53100 Siena, Italy
| | - Alexia Carré
- INSERM, U1016, Cochin Institute, 75014 Paris, France; CNRS, UMR8104, Cochin Institute, 75014 Paris, France; Paris Descartes University, Sorbonne Paris Cité, 75014 Paris, France
| | - Sheena Pinto
- DKFZ, Division of Developmental Immunology, 69120 Heidelberg, Germany
| | - Slobodan Culina
- INSERM, U1016, Cochin Institute, 75014 Paris, France; CNRS, UMR8104, Cochin Institute, 75014 Paris, France; Paris Descartes University, Sorbonne Paris Cité, 75014 Paris, France
| | - Noémie Corcos
- INSERM, U1016, Cochin Institute, 75014 Paris, France; CNRS, UMR8104, Cochin Institute, 75014 Paris, France; Paris Descartes University, Sorbonne Paris Cité, 75014 Paris, France
| | - Marco Bugliani
- University of Pisa, Department of Clinical and Experimental Medicine, 56124 Pisa, Italy
| | - Piero Marchetti
- University of Pisa, Department of Clinical and Experimental Medicine, 56124 Pisa, Italy
| | - Mathieu Armanet
- Assistance Publique Hôpitaux de Paris, Cell Therapy Unit, Saint Louis Hospital, 75010 Paris, France
| | - Marc Diedisheim
- INSERM, U1016, Cochin Institute, 75014 Paris, France; CNRS, UMR8104, Cochin Institute, 75014 Paris, France; Paris Descartes University, Sorbonne Paris Cité, 75014 Paris, France; Assistance Publique Hôpitaux de Paris, Service de Diabétologie, Cochin Hospital, 75014 Paris, France
| | - Bruno Kyewski
- DKFZ, Division of Developmental Immunology, 69120 Heidelberg, Germany
| | - Lars M Steinmetz
- Stanford University, School of Medicine, Department of Genetics and Stanford Genome Technology Center, Stanford, CA 94305, USA; European Molecular Biology Laboratory, Genome Biology Unit, 69117 Heidelberg, Germany
| | - Søren Buus
- Panum Institute, Department of International Health, Immunology and Microbiology, 2200 Copenhagen, Denmark
| | - Sylvaine You
- INSERM, U1016, Cochin Institute, 75014 Paris, France; CNRS, UMR8104, Cochin Institute, 75014 Paris, France; Paris Descartes University, Sorbonne Paris Cité, 75014 Paris, France
| | - Daniele Dubois-Laforgue
- INSERM, U1016, Cochin Institute, 75014 Paris, France; CNRS, UMR8104, Cochin Institute, 75014 Paris, France; Paris Descartes University, Sorbonne Paris Cité, 75014 Paris, France; Assistance Publique Hôpitaux de Paris, Service de Diabétologie, Cochin Hospital, 75014 Paris, France
| | - Etienne Larger
- INSERM, U1016, Cochin Institute, 75014 Paris, France; CNRS, UMR8104, Cochin Institute, 75014 Paris, France; Paris Descartes University, Sorbonne Paris Cité, 75014 Paris, France; Assistance Publique Hôpitaux de Paris, Service de Diabétologie, Cochin Hospital, 75014 Paris, France
| | - Jean-Paul Beressi
- Centre Hospitalier de Versailles André Mignot, Service de Diabétologie, 78150 Le Chesnay, France
| | - Graziella Bruno
- University of Turin, Department of Medical Sciences, 10126 Turin, Italy
| | - Francesco Dotta
- University of Siena, Department of Medicine, Surgery and Neuroscience, Diabetes Unit and Fondazione Umberto di Mario ONLUS, Toscana Life Sciences, 53100 Siena, Italy
| | - Raphael Scharfmann
- INSERM, U1016, Cochin Institute, 75014 Paris, France; CNRS, UMR8104, Cochin Institute, 75014 Paris, France; Paris Descartes University, Sorbonne Paris Cité, 75014 Paris, France
| | - Decio L Eizirik
- Université Libre de Bruxelles Center for Diabetes Research and Welbio, Medical Faculty, Université Libre de Bruxelles, 1070 Brussels, Belgium
| | - Yann Verdier
- ESPCI Paris, PSL University, Spectrométrie de Masse Biologique et Protéomique, CNRS USR3149, 75005 Paris, France
| | - Joelle Vinh
- ESPCI Paris, PSL University, Spectrométrie de Masse Biologique et Protéomique, CNRS USR3149, 75005 Paris, France
| | - Roberto Mallone
- INSERM, U1016, Cochin Institute, 75014 Paris, France; CNRS, UMR8104, Cochin Institute, 75014 Paris, France; Paris Descartes University, Sorbonne Paris Cité, 75014 Paris, France; Assistance Publique Hôpitaux de Paris, Service de Diabétologie, Cochin Hospital, 75014 Paris, France.
| |
Collapse
|