Development of a Simple Multiplex Electrochemiluminescence (ECL) Assay for Screening Pre-Type 1 Diabetes and Multiple Relevant Autoimmune Diseases

The presence of islet autoantibodies (iAbs) is currently the most reliable biomarker for type 1 diabetes (T1D). The current “gold” standard radio-binding assays that measure four major iAbs to insulin, IAA, GAD65, IA-2A and ZnT8, are laborious and do not fit for large-scale screenings. Around 40% of patients with T1D develop other autoimmune diseases like celiac disease, autoimmune thyroid disease, and so on. It is highly recommended to screen these closely related autoimmune diseases during T1D screening; however, there is no method available. Recently, on the platform of extensively validated high-sensitive and high-specific electrochemiluminescence (ECL) assay, we developed a multiplex ECL assay to combine up to 10 autoantibody assays into one single well with 5 μl of blood sample. It not only allows us to combine multiple iAbs into one but also makes it possible to simultaneously screen T1D and other multiple autoimmune diseases, which in turn facilitates large-scale screenings in the general population

Expression-Based Genome-Wide Association Study Links Vitamin D-Binding Protein With Autoantigenicity in Type 1 Diabetes.

Type 1 diabetes (T1D) is caused by autoreactive T cells that recognize pancreatic islet antigens and destroy insulin-producing β-cells. This attack results from a breakdown in tolerance for self-antigens, which is controlled by ectopic antigen expression in the thymus and pancreatic lymph nodes (PLNs). The autoantigens known to be involved include a set of islet proteins, such as insulin, GAD65, IA-2, and ZnT8. In an attempt to identify additional antigenic proteins, we performed an expression-based genome-wide association study using microarray data from 118 arrays of the thymus and PLNs of T1D mice. We ranked all 16,089 protein-coding genes by the likelihood of finding repeated differential expression and the degree of tissue specificity for pancreatic islets. The top autoantigen candidate was vitamin D-binding protein (VDBP). T-cell proliferation assays showed stronger T-cell reactivity to VDBP compared with control stimulations. Higher levels and frequencies of serum anti-VDBP autoantibodies (VDBP-Abs) were identified in patients with T1D (n = 331) than in healthy control subjects (n = 77). Serum vitamin D levels were negatively correlated with VDBP-Ab levels in patients in whom T1D developed during the winter. Immunohistochemical localization revealed that VDBP was specifically expressed in α-cells of pancreatic islets. We propose that VDBP could be an autoantigen in T1D

Antibodies against insulin measured by electrochemiluminescence predicts insulitis severity and disease onset in non-obese diabetic mice and can distinguish human type 1 diabetes status

Abstract Background The detection of insulin autoantibodies (IAA) aids in the prediction of autoimmune diabetes development. However, the long-standing, gold standard 125I-insulin radiobinding assay (RBA) has low reproducibility between laboratories, long sample processing times and requires the use of newly synthesized radiolabeled insulin for each set of assays. Therefore, a rapid, non-radioactive, and reproducible assay is highly desirable. Methods We have developed electrochemiluminescence (ECL)-based assays that fulfill these criteria in the measurement of IAA and anti-insulin antibodies (IA) in non-obese diabetic (NOD) mice and in type 1 diabetic individuals, respectively. Using the murine IAA ECL assay, we examined the correlation between IAA, histopathological insulitis, and blood glucose in a cohort of female NOD mice from 4 up to 36 weeks of age. We developed a human IA ECL assay that we compared to conventional RBA and validated using samples from 34 diabetic and 59 non-diabetic individuals in three independent laboratories. Results Our ECL assays were rapid and sensitive with a broad dynamic range and low background. In the NOD mouse model, IAA levels measured by ECL were positively correlated with insulitis severity, and the values measured at 8-10 weeks of age were predictive of diabetes onset. Using human serum and plasma samples, our IA ECL assay yielded reproducible and accurate results with an average sensitivity of 84% at 95% specificity with no statistically significant difference between laboratories. Conclusions These novel, non-radioactive ECL-based assays should facilitate reliable and fast detection of antibodies to insulin and its precursors sera and plasma in a standardized manner between laboratories in both research and clinical settings. Our next step is to evaluate the human IA assay in the detection of IAA in prediabetic subjects or those at risk of type 1 diabetes and to develop similar assays for other autoantibodies that together are predictive for the diagnosis of this common disorder, in order to improve prediction and facilitate future therapeutic trials.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Prediction of impending type 1 diabetes through automated dual-label measurement of proinsulin:C-peptide ratio

Background : The hyperglycemic clamp test, the gold standard of beta cell function, predicts impending type 1 diabetes in islet autoantibody-positive individuals, but the latter may benefit from less invasive function tests such as the proinsulin: C-peptide ratio (PI:C). The present study aims to optimize precision of PI:C measurements by automating a dual-label trefoil-type time-resolved fluorescence immunoassay (TT-TRFIA), and to compare its diagnostic performance for predicting type 1 diabetes with that of clamp-derived C-peptide release. Methods : Between-day imprecision (n = 20) and split-sample analysis (n = 95) were used to compare TT-TRFIA (Auto Delfia, Perkin-Elmer) with separate methods for proinsulin (in-house TRFIA) and C-peptide (Elecsys, Roche). High-risk multiple autoantibody-positive firstdegree relatives (n = 49; age 5-39) were tested for fasting PI:C, HOMA2-IR and hyperglycemic clamp and followed for 20-57 months (interquartile range). Results : TT-TRFIA values for proinsulin, C-peptide and PI:C correlated significantly (r(2) = 0.96-0.99; P<0.001) with results obtained with separate methods. TT-TRFIA achieved better between-day % CV for PI:C at three different levels (4.5-7.1 vs 6.7-9.5 for separate methods). In high-risk relatives fasting PI:C was significantly and inversely correlated ( r(s) = -0.596; P<0.001) with first-phase C-peptide release during clamp ( also with second phase release, only available for age 12-39 years; n = 31), but only after normalization for HOMA2-IR. In ROC- and Cox regression analysis, HOMA2-IR-corrected PI:C predicted 2-year progression to diabetes equally well as clamp-derived C-peptide release. Conclusions : The reproducibility of PI:C benefits from the automated simultaneous determination of both hormones. HOMA2-IR-corrected PI:C may serve as a minimally invasive alternative to the more tedious hyperglycemic clamp test

Detection of antibodies directed to the N-terminal region of GAD is dependent on assay format and contributes to differences in the specificity of GAD autoantibody assays for type 1 diabetes

Autoantibodies to glutamate decarboxylase (GADA) are sensitive markers of islet autoimmunity and type 1 diabetes. They form the basis of robust prediction models and are widely used for recruitment of subjects at high risk of type 1 diabetes to prevention trials. However GADA are also found in many individuals at low risk of diabetes progression. To identify the sources of diabetes irrelevant GADA reactivity therefore, we analyzed data from the 2009 and 2010 Diabetes Autoantibody Standardization Program GADA workshop and found that binding of healthy control sera varied according to assay type. Characterization of control sera found positive by radiobinding assay, but negative by ELISA showed that many of these sera reacted to epitopes in the N-terminal region of the molecule. This finding prompted development of an N-terminally truncated GAD65 radiolabel, (35)S-GAD65(96-585), which improved the performance of most GADA radiobinding assays (RBAs) participating in an Islet Autoantibody Standardization Program GADA substudy. These detailed workshop comparisons have identified a source of disease-irrelevant signals in GADA RBAs and suggest that N-terminally truncated GAD labels will enable more specific measurement of GADA in type 1 diabetes

The Clinical Utility of Zinc Transporter 8 Autoantibody Measurement in Diabetes

Maturity onset diabetes of the young (MODY) is caused by single gene mutations that are of autosomal dominant inheritance. Mutations are highly penetrant, and patients often develop a phenotype similar to type 1 or type 2 diabetes. Glucokinase, Hepatic nuclear factor 1a and 4a mutations consists of 80% of MODY cases. Approximately 1% of patients with diabetes have MODY, and it is often misdiagnosed. Diagnosis is important as patients with MODY often have a good prognosis and glycaemic control if they are treated appropriately. The aim of this thesis was to explore the use of islet autoantibodies, in particular a new autoantibody against Zinc Transporter 8, as biomarkers to identify MODY. A literature review of MODY and its important subtypes are discussed. It highlights the major mutation that cause MODY and the management of patients with MODY is also explored. Islet autoantibodies will also be reviewed in the same chapter, with a discussion on established autoantibodies and ZnT8 autoantibodies in relation to type 1 diabetes. Chapter 1 aims to investigate whether ZnT8 autoantibodies are similar to established autoantibodies against GAD and IA-2 as a biomarker in differentiating T1D patients from MODY patients. The prevalence of ZnT8 autoantibodies in MODY patients and the effect of disease duration on antibody prevalence and discriminative power would also be investigated. In Chapter 2, a study was performed to investigate whether islet autoantibodies are useful in the MODY referral setting in ruling out patients for genetic testing. This is a way to rationalise genetic testing at the Exeter molecular genetics referral service. Additionally, other biomarkers will also be investigated, namely C-peptide levels and Type 1 Diabetes Genetic Risk score. Results from the study will have implications to how MODY is diagnosed at the referral service. A discussion of the findings of each chapter, implications and plans for future research will be explored in chapter 3

The risk of progression to type 1 diabetes is highly variable in individuals with multiple autoantibodies following screening

Aims/hypothesis: Young children who develop multiple autoantibodies (mAbs) are at very high risk for type 1 diabetes. We assessed whether a population with mAbs detected by screening is also at very high risk, and how risk varies according to age, type of autoantibodies and metabolic status. Methods: Type 1 Diabetes TrialNet Pathway to Prevention participants with mAbs (n = 1815; age, 12.35 ± 9.39 years; range, 1-49 years) were analysed. Type 1 diabetes risk was assessed according to age, autoantibody type/number (insulin autoantibodies [IAA], glutamic acid decarboxylase autoantibodies [GADA], insulinoma-associated antigen-2 autoantibodies [IA-2A] or zinc transporter 8 autoantibodies [ZnT8A]) and Index60 (composite measure of fasting C-peptide, 60 min glucose and 60 min C-peptide). Cox regression and cumulative incidence curves were utilised in this cohort study. Results: Age was inversely related to type 1 diabetes risk in those with mAbs (HR 0.97 [95% CI 0.96, 0.99]). Among participants with 2 autoantibodies, those with GADA had less risk (HR 0.35 [95% CI 0.22, 0.57]) and those with IA-2A had higher risk (HR 2.82 [95% CI 1.76, 4.51]) of type 1 diabetes. Those with IAA and GADA had only a 17% 5 year risk of type 1 diabetes. The risk was significantly lower for those with Index60 <1.0 (HR 0.23 [95% CI 0.19, 0.30]) vs those with Index60 values ≥1.0. Among the 12% (225/1815) ≥12.0 years of age with GADA positivity, IA-2A negativity and Index60 <1.0, the 5 year risk of type 1 diabetes was 8%. Conclusions/interpretation: Type 1 diabetes risk varies substantially according to age, autoantibody type and metabolic status in individuals screened for mAbs. An appreciable proportion of older children and adults with mAbs appear to have a low risk of progressing to type 1 diabetes at 5 years. With this knowledge, clinical trials of type 1 diabetes prevention can better target those most likely to progress

Novel flow cytometric immunoassay for detection of proinsulin autoantibodies in diabetes mellitus employing a recombinant autoantigen expressed in E. coli

Introduction: Insulin and proinsulin autoantibodies (IAA/PAA) are usually the first markers to appear in patients with type 1 Diabetes Mellitus (T1DM) and their prevalence ranges from 10 to 60% in the child-adolescent population. The reference method for IAA/PAA detection is the Radioligand Binding Assay (RBA), a highly specific and sensitive technique, but expensive and polluting. The aim of this work was to develop a novel flow cytometric microsphere-based immunoassay (FloCMIA) for PAA detection, employing recombinant human proinsulin (PI), as an alternative method to RBA, less expensive and harmful to the environment. Materials and Methods: Human PI was expressed as Thioredoxin fusion protein (TrxPI) in E. coli and a fraction was biotinylated. A double paratope model was used in which samples were incubated with TrxPI–biotin and microspheres adsorbed with TrxPI. The immune complexes were revealed using Streptavidin–Phycoerythrin. The geometric mean of the signals was analyzed, and the results were expressed as Standard Deviation scores (SDs). Sera from 100 normal human control and from 111 type 1 diabetic patients were evaluated by FloCMIA. To correlate the novel assay with RBA, 51 diabetic patients were selected, spanning a wide range of PAA reactivity by RBA. Results: The study of ROC curves allowed choosing a cut-off value of 3.0 SDs and the AUC was 0.705, indicating that FloCMIA has fair ability to distinguish between samples from each group. A prevalence of 50% for PAA was obtained in the population of diabetic patients studied. The specificity was 96% and the analytical sensitivity (percentage of patients RBA positive, also positive by FloCMIA) was 69%. There was a substantial agreement between methods (kappa statistic=0.700). Conclusions: A novel immunoassay based on flow cytometry that uses easy-to produce recombinant PI was developed. This assay constitutes an innovative and cost-effective alternative to RBA for the determination of PAA in patients’ sera. The method developed here, presents good performance and a wide dynamic range together with a small required sample volume. Furthermore, these results make it possible to develop multiplex immunoassays that allow the combined detection of autoantibodies present in T1DM and other related autoimmune diseases.Fil: Sabljic, Adriana Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Bombicino, Silvina Sonia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Marfía, Juan Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Guerra, Luciano Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Microbiología, Inmunología y Biotecnología. Cátedra de Inmunología; ArgentinaFil: Penas Steinhardt, Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Lujan. Departamento de Cs.basicas. Laboratorio de Genomica Computacional.; ArgentinaFil: Faccinetti, Natalia Ines. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Microbiología, Inmunología y Biotecnología. Cátedra de Inmunología; ArgentinaFil: Iacono, Ruben Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Poskus, Edgardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Trabucchi, Aldana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Valdez, Silvina Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; Argentin

Optimizing Multiplexed Detections of Diabetes Antibodies via Quantitative Microfluidic Droplet Array

Sensitive, single volume detections of multiple diabetes antibodies can provide immunoprofiling and early screening of at‐risk patients. To advance the state‐of‐the‐art suspension assays for diabetes antibodies, porous hydrogel droplets are leveraged in microfluidic serpentine arrays to enhance reagent transport. This spatially multiplexed assay is applied to the detection of antibodies against insulin, glutamic acid decarboxylase, and insulinoma‐associated protein 2. Optimization of assay protocol results in a shortened assay time of 2 h, with better than 20 pg mL Supporting Information detection limits across all three antibodies. Specificity and cross‐reactivity tests show negligible background, nonspecific antibody–antigen, and nonspecific antibody–antibody bindings. Multiplexed detections are able to measure within 15% of target concentrations from low to high ranges. The technique enables quantifications of as little as 8000 molecules in each 500 µm droplet in a single volume, multiplexed assay format, a breakthrough necessary for the adoption of diabetes panels for clinical screening and monitoring in the future.To advance state‐of‐the‐art suspension assays for diabetes antibodies, porous hydrogel droplets are leveraged in microfluidic serpentine arrays to enhance the detection of antibodies against insulin, glutamic acid decarboxylase, and insulinoma associated protein‐2. The technique enables sensitive detection in a single volume, multiplexed format to facilitate assay adoption for clinical screening and monitoring in the future.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141961/1/smll201702323-sup-0001-S1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/141961/2/smll201702323_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/141961/3/smll201702323.pd