ICA512(IA-2) epitope specific assays distinguish transient from diabetes associated autoantibodies

Advances in Type 1 Diabetes Prediction Using Islet Autoantibodies: Beyond a Simple Count

Islet autoantibodies are key markers for the diagnosis of type 1 diabetes. Since their discovery, they have also been recognized for their potential to identify at-risk individuals prior to symptoms. To date, risk prediction using autoantibodies has been based on autoantibody number; it has been robustly shown that nearly all multiple-autoantibody-positive individuals will progress to clinical disease. However, longitudinal studies have demonstrated that the rate of progression among multiple-autoantibody-positive individuals is highly heterogenous. Accurate prediction of the most rapidly progressing individuals is crucial for efficient and informative clinical trials and for identification of candidates most likely to benefit from disease modification. This is increasingly relevant with the recent success in delaying clinical disease in presymptomatic subjects using immunotherapy, and as the field moves toward population-based screening. There have been many studies investigating islet autoantibody characteristics for their predictive potential, beyond a simple categorical count. Predictive features that have emerged include molecular specifics, such as epitope targets and affinity; longitudinal patterns, such as changes in titer and autoantibody reversion; and sequence-dependent risk profiles specific to the autoantibody and the subject's age. These insights are the outworking of decades of prospective cohort studies and international assay standardization efforts and will contribute to the granularity needed for more sensitive and specific preclinical staging. The aim of this review is to identify the dynamic and nuanced manifestations of autoantibodies in type 1 diabetes, and to highlight how these autoantibody features have the potential to improve study design of trials aiming to predict and prevent disease.

Immune checkpoint inhibitors and diabetes: Mechanisms and predictors

The emergence of immune checkpoint inhibitors in the arsenal of cancer immunotherapy was a breakthrough which provided hope to many cancer patients. However, not long has passed since their discovery that some adverse effects were associated with these promising therapeutic agents. Immune checkpoint inhibitors dysregulate host immunity and may precipitate autoimmune diseases including diabetes mellitus. In this review, we go beyond the case reports towards understanding the underlying mechanisms by which Programmed cell death 1 (PD-1) and Programmed death ligand-1 (PD-L1) inhibitors precipitate diabetes. We discuss the role of PD-1/PD-L1 in autoimmunity and the use of mice models to describe their involvement in diabetes. We also reviewed the genetic anomalies in PD-1/PD-L1genes and their link to diabetes. Finally, we present the studies conducted to identify patients at risk of developing autoimmune diseases as an adverse effect for PD-1/PD-L1 use. Understanding these issues can guide researchers to find a way to circumvent the autoimmune adverse reactions seen with PD-1/PD-L1 inhibitors without affecting their antitumor activity.

The next big idea

George S. Eisenbarth will remain in our memories as a brilliant scientist and great collaborator. His quest to discover the cause and prevention of type 1 (autoimmune) diabetes started from building predictive models based on immunogenetic markers. Despite his tremendous contributions to our understanding of the natural history of pre-type 1 diabetes and potential mechanisms, George left us with several big questions to answer before his quest is completed.

The core cysteines, (C909) of islet antigen-2 and (C945) of islet antigen-2β, are crucial to autoantibody binding in type 1 diabetes

Cysteines are thought integral to conformational epitopes of islet antigen-2 (IA-2) autoantibodies (IA-2A), possibly through disulfide bond formation. We therefore investigated which cysteines are critical to IA-2A binding in patients with newly diagnosed type 1 diabetes. All 10 cysteines in the intracellular domain of IA-2 were modified to serine by site-directed mutagenesis, and the effects of these changes on autoantibody binding in comparison with wild-type control were investigated by radiobinding assay. Mutation of the protein tyrosine phosphatase (PTP) core cysteine (C909) in IA-2 caused large reductions in autoantibody binding. In contrast, little or no reduction in binding was seen following substitution of the other cysteines. Modification of the core cysteine (C945) in IA-2β also greatly reduced autoantibody binding. Lysine substitution of glutamate-836 in IA-2 or glutamate-872 in IA-2β resulted in modest reductions in binding and identified a second epitope region. Binding to IA-2 PTP and IA-2β PTP was almost abolished by mutation of both the core cysteine and these glutamates. The core cysteine is key to the major PTP conformational epitope, but disulfide bonding contributes little to IA-2A epitope integrity. In most patients, at disease onset, >90% of antibodies binding to the PTP domain of IA-2 recognize just two epitope regions.

Autoantibodies in diabetes

Islet cell autoantibodies are strongly associated with the development of type 1 diabetes. The appearance of autoantibodies to one or several of the autoantigens-GAD65, IA-2, or insulin-signals an autoimmune pathogenesis of beta-cell killing. A beta-cell attack may be best reflected by the emergence of autoantibodies dependent on the genotype risk factors, isotype, and subtype of the autoantibodies as well as their epitope specificity. It is speculated that progression to beta-cell loss and clinical onset of type 1 diabetes is reflected in a developing pattern of epitope-specific autoantibodies. Although the appearance of autoantibodies does not follow a distinct pattern, the presence of multiple autoantibodies has the highest positive predictive value for type 1 diabetes. In the absence of reliable T-cell tests, dissection of autoantibody responses in subjects of genetic risk should prove useful in identifying triggers of islet autoimmunity by examining seroconversion and maturation of the autoantibody response that may mark time to onset of type 1 diabetes. The complexity of the disease process is exemplified by multiple clinical phenotypes, including autoimmune diabetes masquerading as type 2 diabetes in youth and adults. Autoantibodies may also provide prognostic information in clinically heterogeneous patient populations when examined longitudinally.

Microarray analysis in Tourette syndrome postmortem putamen

Gene expression patterns in the postmortem putamen of patients with Tourette syndrome (TS) were investigated using cDNA microarrays. A cDNA neuroarray comprising 1537 genes known to be related to neurological or neuropsychiatric disorders was used to compare patient samples (n=3) with those from control subjects (n=4). Z test and Z ratio were used to analyze results; seven genes were found to be upregulated according to our definition (P<0.1, two-tailed, for Z test; P<0.05 for Z ratio) and three were found to be downregulated. Validation experiments were performed using reverse transcription polymerase chain reaction (RT-PCR) and semiquantitative Western blot analyses. RT-PCR showed concordance with microarray in seven of nine selected genes. In contrast, Western blot analyses performed with five proteins showed that only two of five had similar trends between protein content and level of gene expression. The authors note the inherent difficulty in applying microarray technology to complex neurological disorders such as the TS and conclude that further investigations are required to understand how altered expression of these genes is related to the pathophysiology of the disorder.

Stratification of type 1 diabetes risk on the basis of islet autoantibody characteristics

Family history of type 1 diabetes and autoantibodies to the islet antigens insulin (IAA), glutamate decarboxylase (GADA), and the protein tyrosine phosphatase-like protein IA-2 (IA-2A) are strong predictors of type 1 diabetes, but the rate of progression to diabetes in multiple islet autoantibody-positive relatives varies widely. We asked whether detailed characterization of islet autoantibodies that included determination of titer, epitope specificity, and IgG subclass would improve diabetes prediction in a large cohort of autoantibody-positive relatives. The study shows a strong association between risk and high titer, broad antibody responses to IA-2 and insulin. The highest risks were associated with high-titer IA-2A and IAA, IgG2, IgG3, and/or IgG4 subclass of IA-2A and IAA, and antibodies to the IA-2-related molecule IA-2beta. Using models based on these antibody characteristics, autoantibody-positive relatives can be classified into groups with risks of diabetes ranging from 7 to 89% within 5 years.

The use of phage display to distinguish insulin autoantibody (IAA) from insulin antibody (IA) idiotypes

AIM/HYPOTHESIS

Radiobinding assays (RBA) are unable to differentiate insulin autoantibodies (IAA) from insulin antibodies (IA). We sought to establish whether random peptide phage display might generate reagents with which to distinguish IAA idiotopes from IA idiotopes.

METHODS

Two insulin-binding sera were used to select phagotopes from a phage library. The first, designated IAS, came from an insulin-treated patient with the insulin autoimmune syndrome, and was known to contain both IA and a high titre of human insulin specific (B30 threonine dependent) IAA. The second, designated IDD, was taken from a newly-diagnosed IAA(+) Type 1 diabetic patient. Phage colonies selected by insulin-purified IgG extracts of IAS and IDD were selected at random for DNA sequencing, and tested for their reactivity with insulin antibodies and ability to distinguish disease-associated idiotopes.

RESULTS

Seven phagotopes bound IAS and the phagotope designated IAS-9, corresponding to sequence KRSRLDV, gave the highest binding standard deviation (SD) score. Seven phagotopes bound IDD and the phagotope designated IDD-10, corresponding to sequence LGRGGSK, bound most strongly. IAS-9 was able to displace insulin binding in IAS and all of ten insulin-treated Type 2 diabetic patients, but not the IAA present in any of the eight patients with newly-diagnosed Type 1 diabetes. IDD-10, on the other hand, could displace insulin binding detected in the sera of eight patients with untreated Type 1 diabetes (IAA), but not in IAS or sera of the insulin-treated Type 2 diabetics.

CONCLUSION

Phagotopes provide reagents which between them can distinguish positively as well as negatively diabetes-associated IAA from non-diabetes associated IAA and from IA.