Review
Biomarkers for immune intervention trials in type 1 diabetes

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Abstract

After many efforts to improve and standardize assays for detecting immune biomarkers in type 1 diabetes (T1D), methods to identify and monitor such correlates of insulitis are coming of age. The ultimate goal is to use these correlates to predict disease progression before onset and regression following therapeutic intervention, which would allow performing smaller and shorter pilot clinical trials with earlier endpoints than those offered by preserved β-cell function or improved glycemic control. Here, too, progress has been made. With the emerging insight that T1D represents a heterogeneous disease, the next challenge is to define patient subpopulations that qualify for personalized medicine or that should be enrolled for immune intervention, to maximize clinical benefit and decrease collateral damage by ineffective or even adverse immune therapeutics. This review discusses the current state of the art, setting the stage for future efforts to monitor disease heterogeneity, progression and therapeutic intervention in T1D.

Highlights

► Immune biomarkers provide relevant endpoints for immune intervention trials. ► T cells are more suitable than autoantibodies to provide such biomarkers. ► T-cell biomarkers yield information on therapeutic safety and immune efficacy. ► The latter may be associated or not with clinical efficacy. ► This information significantly improves the design and outcome of follow-up trials.

Introduction

Type 1 diabetes (T1D) represents a prototypic tissue-specific autoimmune disease [1]. Indeed, progress in unraveling the immune components involved in the pathogenesis of T1D has been spectacular and often more rewarding than for other autoimmune diseases. Several islet antigens (Ags) have been identified with compelling associations with the β-cell destruction process, including (pre)proinsulin [(pre)PI], glutamic acid decarboxylase (GAD)65, insulinoma-associated protein 2 (IA-2), islet-specific glucose-6-phosphatase catalytic subunit-related protein (IGRP) and zinc transporter (ZnT)8 [2], [3], [4]. Additional candidate target molecules expressed by β cells have been revealed and studied, such as chromogranin A, (prepro) islet amyloid polypeptide (ppIAPP), peripherin and an ill-defined 38 kDa protein in insulin secretory granules, but their role in association with clinical T1D remains unclear or controversial [5]. The immunology of diabetes community has been blessed with this large series of T-cell and/or autoantibody (autoAb) targets that can be employed in monitoring the islet autoreactivity of T1D [6]. Islet autoAbs against many of these Ags have proven particularly useful for T1D prediction, but less so for following disease activity and progression after T1D onset or during therapeutic intervention (so called “immune staging”) [7]. This notion is putting a substantial burden on the options to monitor changes in disease activity. It implies that we may have to resort to using cellular autoimmunity to this end, with all the challenges involved in terms of technologies and targets.

New access to the pancreatic lesions of T1D patients through the establishment of an international consortium collecting, distributing and characterizing tissues of diabetic donors (www.jdrfnpod.org) has led spectacular new insights into the immune processes involved in the selective destruction of insulin-producing β cells in pancreatic islets [8]. Seminal recent lessons learned through these studies include additional proofs of the autoimmune nature of T1D, the demonstration of islet-specific CD8+ T cells in destructive insulitic lesions, the unexpectedly low frequencies of islet-infiltrating CD4+ T cells, the apparent lack of CD4+CD25+FoxP3+ T regulatory cells (Tregs) in insulitis, the profound difference in immunopathology between men and mice, an overwhelming heterogeneity in the pathologic lesions and patient population, and the demonstration of focal disease activity much akin to what observed in other tissue-specific autoimmune diseases such as vitiligo [9]. Collectively, these insights have set the stage for new therapeutic strategies that may also prove effective in protecting β cells long after T1D clinical onset. Many of these strategies are currently assessed for clinical efficacy to prevent, stop of reverse disease. Some recent-onset T1D patients have already achieved a lasting remission from insulin dependency for up to seven years, showing proof of principle that T1D may be cured, at least in some patients and at least for a number of years [10]. Yet, there is an urgent need for definition of endpoints and biomarkers of immunological and clinical efficacy to guide therapeutic interventions in T1D. The immune system holds important clues to provide immune correlates of safety and clinical efficacy, both for selecting the appropriate patients for a given therapy and to monitor whether the intervention can preserve β-cell function.

Section snippets

T1D: a T-cell-mediated autoimmune disease

T1D is an autoimmune disease in which CD4+ and CD8+ T cells infiltrate the islets of Langerhans, resulting in β-cell destruction. Although the precise etiologic factors remain barely elusive, an extensive body of data in animal models and more limited studies in man indicate that, contrary to autoAbs [11], CD4+ and CD8+ T cells reactive with islet Ags have a key role in the process of β-cell destruction. The lines of evidence gathered in mouse models have been extensively reviewed, and the

Endpoints in immune intervention trials: metabolic and immune biomarkers

To put into context the endpoints analyzed in T1D intervention trials, the clinical stage at which most of these trials are performed should be kept in mind. While in the NOD mouse models, which is commonly used to preclinically evaluate the efficacy of immune therapeutics, treatment is usually started as early as possible, at a time when the autoimmune progression is still lagging behind, this is not feasible in patients. Indeed, autoAbs are the earlier available biomarkers of T1D risk. While

Why using T cells rather than autoAbs as immune biomarkers for trial monitoring?

AutoAbs remain the mainstay for classifying diabetes cases as autoimmune-mediated (type 1) and for stratifying risk in first-degree relatives. Can their modifications also be used as immune biomarkers in trial follow-ups? This was performed for instance in an anti-CD3 phase II trial in new-onset T1D patients [34]. Despite evidence for a better preservation of residual insulin secretion in anti-CD3- vs. placebo-treated patients, there was no significant change in autoAb titers. Lack of

Measuring T-cell responses in T1D

In front of the advantages of monitoring T-cell rather than autoAb responses, there are also some drawbacks, namely that T-cell assays are technically more demanding [43], [44], [45], [46]. These assays employ live peripheral blood mononuclear cells (PBMCs), which should be prepared and stored following procedures not routinely implemented in clinical laboratories. Following the successful efforts of the Diabetes Antibody Standardization Program (DASP) over the last two decades, the T-Cell

Applications of immune biomarkers for trial monitoring

Monitoring of clinical trials by means of immune biomarkers can address a number of questions posed by immune interventions (Fig. 1). Such questions fall into three main categories: therapeutic safety, i.e. are we causing unwanted immune activation or, conversely, are we inducing generalized immune suppression?; immunological efficacy, i.e. did we achieve the immune deviation that we set out for?; and, ultimately, therapeutic efficacy, i.e. is the immunological change achieved associated with

Some unmet needs for T1D immune staging in immune therapeutic trials

The large majority of T-cell-based immune staging studies have been performed to monitor modifications induced following immune therapy. One aspect that needs more emphasis is that of immune staging before intervention, to identify T-cell profiles associated with clinical responses and thus to help selecting which patients to treat. Specific autoAb specificities (e.g. anti-GAD in the Diamyd GAD trial) have already been used as selection criteria in several immune intervention trials. The

Present and future: immune biomarkers for therapeutic tailoring

Immune surrogate endpoints should be systematically added to clinical and metabolic outcomes in order to comprehensively evaluate trial results. At present, this would allow:

  • 1)

    To understand therapeutic mechanisms behind clinical efficacy.

  • 2)

    To sort out the reasons for lack of clinical efficacy in many trials: is the intervention immunologically ineffective or is the immune effect insufficient to translate into clinical benefit?

  • 3)

    To define pre-treatment and post-treatment immune profiles associated

Conflict of interest statement

The author(s) declare that there are no conflicts of interest.

Acknowledgments

Work reviewed in this article was supported by grants from JDRF (1-2008-106 and 17-2012-559), the European Foundation for the Study of Diabetes (EFSD/JDRF/Novo Nordisk Programme in Type 1 Diabetes Research 2009), ANR Blanc Immunotolerins and INSERM Avenir (to R.M.); and by grants from JDRF (17-2011-660 and 17-2012-547), the Dutch Diabetes Research Foundation, The European Commission (EU-FP7; BetaCellTherapy, NAIMIT and EE-ASI) and the National Research Council (VICI Award, ZonMW) (to B.O.R.).

References (75)

  • T.P. Di Lorenzo et al.

    Translational mini-review series on type 1 diabetes: systematic analysis of T cell epitopes in autoimmune diabetes

    Clin. Exp. Immunol.

    (2007)
  • J.M. Wenzlau et al.

    The cation efflux transporter ZnT8 (Slc30A8) is a major autoantigen in human type 1 diabetes

    Proc. Natl. Acad. Sci. U. S. A.

    (2007)
  • M. Scotto et al.

    Zinc transporter (ZnT)8(186–194) is an immunodominant CD8 (+) T cell epitope in HLA-A2 (+) type 1 diabetic patients

    Diabetologia

    (2012)
  • B.O. Roep

    T-cell responses to autoantigens in IDDM. The search for the Holy Grail

    Diabetes

    (1996)
  • P.J. Bingley et al.

    Proposed guidelines on screening for risk of type 1 diabetes

    Diabetes Care

    (2001)
  • K.T. Coppieters et al.

    Demonstration of islet-autoreactive CD8 T cells in insulitic lesions from recent onset and long-term type 1 diabetes patients

    J. Exp. Med.

    (2012)
  • G.S. Eisenbarth

    Banting Lecture 2009: an unfinished journey: molecular pathogenesis to prevention of type 1A diabetes

    Diabetes

    (2010)
  • J.C. Voltarelli et al.

    Autologous nonmyeloablative hematopoietic stem cell transplantation in newly diagnosed type 1 diabetes mellitus

    JAMA

    (2007)
  • R. Mallone et al.

    To B or not to B: (anti)bodies of evidence on the crime scene of type 1 diabetes?

    Diabetes

    (2011)
  • A. Toma et al.

    Recognition of a subregion of human proinsulin by class I-restricted T cells in type 1 diabetic patients

    Proc. Natl. Acad. Sci. U. S. A.

    (2005)
  • R. Mallone et al.

    CD8+ T-cell responses identify beta-cell autoimmunity in human type 1 diabetes

    Diabetes

    (2007)
  • J.H. Velthuis et al.

    Simultaneous detection of circulating autoreactive CD8+ T-cells specific for different islet cell-associated epitopes using combinatorial MHC multimers

    Diabetes

    (2010)
  • M. Scotto et al.

    HLA-B7-restricted islet epitopes are differentially recognized in type 1 diabetic children and adults and form weak peptide–HLA complexes

    Diabetes

    (2012)
  • G.G. Pinkse et al.

    Autoreactive CD8 T cells associated with beta cell destruction in type 1 diabetes

    Proc. Natl. Acad. Sci. U. S. A.

    (2005)
  • E. Enee et al.

    Equivalent specificity of peripheral blood and islet-infiltrating CD8+ T lymphocytes in spontaneously diabetic HLA-A2 transgenic NOD mice

    J. Immunol.

    (2008)
  • S. Arif et al.

    Autoreactive T cell responses show proinflammatory polarization in diabetes but a regulatory phenotype in health

    J. Clin. Invest.

    (2004)
  • S. Arif et al.

    Peripheral and islet interleukin-17 pathway activation characterizes human autoimmune diabetes and promotes cytokine-mediated beta-cell death

    Diabetes

    (2011)
  • S. Luce et al.

    Single insulin-specific CD8+ T cells show characteristic gene expression profiles in human type 1 diabetes

    Diabetes

    (2011)
  • A. Skowera et al.

    CTLs are targeted to kill beta cells in patients with type 1 diabetes through recognition of a glucose-regulated preproinsulin epitope

    J. Clin. Invest.

    (2008)
  • D. Kronenberg et al.

    Circulating preproinsulin signal peptide-specific CD8 T cells restricted by the susceptibility molecule HLA-A24 are expanded at onset of type 1 diabetes and kill beta-cells

    Diabetes

    (2012)
  • A.G. van Halteren et al.

    Homing of human autoreactive T cells into pancreatic tissue of NOD-scid mice

    Diabetologia

    (2005)
  • I. Jarchum et al.

    In vivo cytotoxicity of insulin-specific CD8+ T-cells in HLA-A*0201 transgenic NOD mice

    Diabetes

    (2007)
  • W.W. Unger et al.

    Islet-specific CTL cloned from a type 1 diabetes patient cause beta-cell destruction after engraftment into HLA-A2 transgenic NOD/SCID/IL2RG null mice

    PLoS One

    (2012)
  • E. Martinuzzi et al.

    The frequency and immunodominance of islet-specific CD8+ T-cell responses change after type 1 diabetes diagnosis and treatment

    Diabetes

    (2008)
  • F. Vendrame et al.

    Recurrence of type 1 diabetes after simultaneous pancreas–kidney transplantation, despite immunosuppression, is associated with autoantibodies and pathogenic autoreactive CD4 T-cells

    Diabetes

    (2010)
  • P. Kulmala et al.

    Prediction of insulin-dependent diabetes mellitus in siblings of children with diabetes. A population-based study. The Childhood Diabetes in Finland Study Group

    J. Clin. Invest.

    (1998)
  • D.J. Klinke

    Extent of beta cell destruction is important but insufficient to predict the onset of type 1 diabetes mellitus

    PLoS One

    (2008)
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