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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
Short running title: Improved specificity of autoantibodies to N terminally truncated GAD
Alistair JK Williams1, Vito Lampasona2, Michael Schlosser3, Patricia W Mueller4, David L Pittman5, William E Winter5, Beena Akolkar6, Rebecca Wyatt1, Cristina Brigatti2, Stephanie Krause7, Peter Achenbach7 and Participating Laboratories
1. School of Clinical Sciences, University of Bristol, Bristol, UK 2. Division of Genetics and Cell Biology & Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milan, Italy 3. Department of Medical Biochemistry and Molecular Biology and Institute of Pathophysiology, University Medical Center of Greifswald, Karlsburg, Germany 4. Molecular Risk Assessment Laboratory, Centers for Disease Control and Prevention, Atlanta, GA, USA 5. Department of Pathology, University of Florida, Gainesville, FL, USA 6. Division of Diabetes, Endocrinology, and Metabolic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA 7. Institute of Diabetes Research, Helmholtz Zentrum München, and Forschergruppe Diabetes, Klinikum rechts der Isar, Technische Universität München, Neuherberg, Germany
Correspondence to – Alistair Williams Diabetes and Metabolism, School of Clinical Sciences Learning and Research Building, Southmead Hospital Bristol BS10 5NB Fax: +44 117 323 5336 Tel: +44 117 414 7900 [email protected]
Word count: 2836 Figures: 4 Supplemental figures: 3 Supplemental table: 1 Supplemental appendix: 1
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Diabetes Publish Ahead of Print, published online May 13, 2015 Diabetes Page 2 of 30
ABSTRACT
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
35 prompted development of an N terminally truncated GAD65 radiolabel, 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.
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Accurate prediction of type 1 diabetes depends on islet autoantibody measurement. The
presence of autoantibodies directed against multiple islet antigens confers a high risk of
disease (1; 2), and improved performance of individual islet autoantibody assays would
enable more efficient recruitment of high risk subjects to therapeutic prevention trials.
Autoantibodies to glutamate decarboxylase (GADA) are the most widely used marker for type
1 diabetes, but to achieve optimum disease sensitivity the threshold for GADA positivity is
often set at the 99th percentile, a level that exceeds the lifetime risk of developing the disease
(3). Many individuals found GADA positive with current assays are therefore unlikely to
progress to type 1 diabetes, making the development of more specific GADA assays a high
priority (4).
The Diabetes Antibody Standardization Program (DASP) was established in 2001 with the
aim of improving islet autoantibody assay performance and concordance among laboratories
(5). DASP has facilitated the rapid evaluation and adoption of novel autoantibody assays (6 8)
and this work continues under the mantle of the Islet Autoantibody Standardization Program
(IASP). During the lifetime of DASP/IASP there have been major improvements in assay
performance and comparability, but the specificity of GADA assays can still vary by as much
as 10% between laboratories that achieve similar sensitivity (9).
Closer analysis of recent DASP/IASP workshops has revealed systematic differences in the
reactivity of individual healthy control sera between ELISAs and radiobinding assays
(RBAs). Several control sera showed increased binding of GAD65 in the majority of RBAs,
despite being found negative in most ELISAs, while the converse was true for other control
sera. We therefore investigated the binding characteristics of those control sera found positive
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more commonly by RBA to identify sources of disease irrelevant signals and using this information, set out to develop more specific GADA assays.
RESEARCH DESIGN AND METHODS
DASP/IASP workshops
Analysis was performed on samples included in the 2009 and 2010 DASP workshops as well as a GADA substudy in the 2012 IASP workshop (Supplemental Fig. 1). In each workshop, laboratories received uniquely coded sets of blinded sera from 50 patients with newly diagnosed type 1 diabetes contributed by several centers around the world, together with up to
100 US blood donors without a family history of diabetes as healthy controls (Supplemental
Table 1). Type 1 diabetes was diagnosed by local centers on the basis of clinical characteristics. All samples were collected within 14 days of starting insulin treatment. The 90 control sera included in DASP 2010 were also among the 100 control sera used in DASP
2009. Sera were prepared and frozen in 100 L aliquots and distributed by the Centers for
Disease Control and Prevention or University of Florida as previously described (10).
Laboratories were asked to test samples for GADA using the assay formats of their choice, to provide details of their assay protocols, and to report assay results, including raw data, to
DASP/IASP for analysis. Assays parameters varied between and within different formats.
Major differences included the volume of serum used, buffer constituents, primary incubation time, separation method, washing technique and standardization method. To reduce variation between RBAs the standard method protocol was developed which fixed these aspects of the technique thereby allowing for greater comparability between laboratories (11). In the DASP
2009 workshop, 42 laboratories from 19 countries reported results for 56 GADA assays. In the DASP 2010 workshop, 39 laboratories from 19 countries reported results for 53 GADA
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assays. In the IASP 2012 workshop, 10 laboratories from 7 countries participated in a GADA
substudy using non commercial RBAs (Supplemental Appendix).
Assessment of epitope specificities
The epitope specificities of selected GADA workshop control sera were assessed using
plasmids encoding full length GAD65, GAD67 and truncated GAD65, as well as GAD65 GAD67
chimeras (12). GAD67, GAD67(1 101)/GAD65(96 440)/GAD67(453 593), and GAD67(1
243)/GAD65(235 444)/GAD67(453 593) were cloned into pGEM Teasy (Promega), while
GAD65(1 95)/GAD67(101 593) and GAD67(1 452)/GAD65(445 585) were cloned into pGEM3
(Promega). GAD65(46 585) and GAD65(96 585) were cloned into pTnT (Promega). All
plasmids were provided by Vito Lampasona apart from the pTNT plasmid pThGAD65
encoding full length GAD65 (courtesy of Ake Lernmark). Samples were assayed for GADA
using the standard assay protocol (11) with 35S methionine labeled antigens made by in vitro
transcription and translation of GAD65 GAD67 chimeras, truncated GAD65 and full length
GAD65. To further characterize GADA binding, selected DASP 2010 workshop sera were
also assayed for GADA(1 585) and GADA(96 585) using the standard assay protocol with
and without addition of 5 or 0.05 pmol per well of recombinant full length GAD65 (Diamyd
Medical AB, Stockholm, Sweden). Using this approach, median percentage displacement of
GADA binding was calculated as 100*(cpm label alone – cpm label with unlabeled
GAD)/cpm label alone) with a minimum set at 0%. Lack of displacement at 5 pmol/well
would indicate a lack of specificity for GAD65, while lack of displacement at 0.05pmol/well
would suggest that the antibodies were of low affinity, especially when levels of binding were
low (13; 14).
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For the IASP 2012 GADA substudy, participating laboratories generated 35S labeled GAD using the pTnT plasmid (Promega, Madison, USA) vector encoding GAD65(96 585) distributed by Vito Lampasona, as well as their usual plasmid encoding full length GAD65 or
125 I labeled human recombinant full length GAD65. Prior to the GADA substudy, coded
DASP 2010 sets were assayed by three selected laboratories using both 35S labeled
GAD65(96 585) and GAD65(46 485) encoded in the same vector (Supplemental Figure 1).
Data analysis
Categorical variables were compared using the χ2 test. Areas under the curve (AUCs) for the different assays from receiver operator characteristics (ROC) analysis were compared using the Wilcoxon signed rank test. When laboratory assigned positive negative calls were analyzed according to assay format, only those assays with specificity above 90% were included. For all analyses, a two tailed P value of 0.05 was considered significant. Statistical analyses were performed using the Statistics Package for Social Sciences Version 19 (IBM,
New York, USA).
RESULTS
The pattern of GADA reactivity in healthy individuals is associated with assay format
The median laboratory assigned sensitivities and specificities of GADA assays in the DASP
2010 workshop were 86% (range 34 to 92%) and 94% (range 68 to 100%), respectively.
According to threshold independent measures (10), adjusted sensitivity at 95% specificity
(AS95) and AUC, the commercial ELISA showed the best overall performance (Figure 1).
When assay results were analyzed according to assay format the positive negative calls for
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control sera often clustered according to assay type (Figure 2a). For example, control serum
LQ21235 was scored positive by 8 of 10 laboratories using the commercial ELISA, but none
of the other assays. In contrast, control sera N51532, N56575, N59932, S8531 and N53371
were found positive by none of the laboratories using the commercial ELISA as compared to
19 (54%), 18 (51%), 13 (37%), 10 (29%) and 10 (29%) of the other 35 assays, respectively.
Another difference between assays was that serum N54357 was scored positive by 6 of 8
RBAs using the commercial kit with iodinated GAD65 antigen, but none of the other 37
assays. In contrast to the pattern observed in controls, no clear assay specific differences in
the reactivity of patient sera were seen (data not shown).
Assays show a consistent pattern of reactivity over time
The pattern of positive negative calls for control sera in the DASP 2009 workshop was very
similar to that of DASP 2010 (Figure 2b). The serum found positive exclusively by ELISA in
DASP 2010, LQ21235, was positive in all 9 ELISAs, but none of the other assays. The five
sera found positive by none of the laboratories using the commercial ELISA but at least 30%
of other assays in DASP 2010, were again consistently negative by ELISA and positive in 20
to 71 percent of other assays. Serum N54357 was positive in 6 of 11 commercial RBAs as
well as the only other RBA using iodinated antigen, but in none of the other 38 assays.
Characterization of control samples called positive in DASP 2010
To determine whether the pattern of positivity in controls could be explained by differences in
assay specific reactivity to particular GADA epitopes, selected control samples were assayed
35 by RBA using S labelled GAD65, GAD67 and GAD65/67 chimeras (12) (Figure 3). Of the
three samples found positive more often by ELISA, LQ19277 showed dominant binding to
the N terminal of GAD67 and weak binding to full length GAD65, while sera LQ21235 and 7
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TS23727 recognized epitopes restricted to the N terminal of GAD65 that were dependent on amino acids 46 to 95. However, as expected for a serum found positive exclusively by
ELISA, LQ21235 showed very low levels of binding in these RBA experiments. Of the five control samples found positive more often by RBAs, three (N51532, N56575 and N59932) showed weak reactivity with the middle region of GAD65. A fourth serum (S8531), showed reactivity restricted to the N terminal of GAD65. The fifth serum, N53371, bound predominantly to epitopes in the N terminal region of GAD65 with weaker responses to
GAD67.
35 Specificity of binding to S labelled GAD65(1 585) and GAD65(96 585) in these sera was confirmed by competitive displacement with excess (5 pmol per well) unlabeled GAD65.
Median displacement of GADA binding in all 8 sera was 60% (range 39% to 78%) with 35S
35 GAD65(1 585) and 72% (range 70% to 76%) in the three sera found positive with S
GAD65(96 585) (Supplemental Fig. 2a). This compares with a median displacement of binding in six GADA positive patients (IDS samples 004, 005, 006, 009, 097 and 195) of 87%
35 (range 68% to 98%) and 91% (range 71% to 98%) for S labeled GAD65(1 585) and
GAD65(96 585), respectively (Supplemental Fig. 2b).
To identify sera with low affinity antibodies, GADA binding was competed at a low concentration of unlabeled GAD65. Competition with 0.05 pmol per well unlabeled GAD65 caused median displacement of binding by the six patient sera of 65% (range 40% to 86%)
35 and 76% (range 61% to 87%) with S labeled GAD65(1 585) and GAD65(96 585), respectively (Supplemental Fig. 2d). In contrast, median displacement of binding in the three sera showing weak reactivity with the middle region of GAD65 (N51532, N56575 and
35 N59932) was 0% (range 0% to 15%) with S labeled GAD65(1 585) and 14% (range 9 to
35 24%) with S labeled GAD65(96 585) indicating that these samples had low affinity antibodies (Supplemental Fig. 2c).
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Evaluation of GADA assays using GAD65(46-585) and GAD65(96-585) plasmids
To investigate whether replacing GAD65(1 585) with N terminally truncated GAD65
constructs could improve GADA assay performance, three laboratories assayed a new coded
35 set of samples from DASP 2010 with S labels generated using plasmids encoding GAD65(1
585), GAD65(46 585) and GAD65(96 585). In each laboratory the highest AS95 (88%) was
achieved using the GAD65(96 585) construct (Supplemental Fig. 3).
Evaluation of GAD65(96-585) in the IASP 2012 GADA substudy
The potential of the GAD65(96 585) radiolabel to improve the performance of GADA RBAs
was assessed by 10 laboratories in the IASP 2012 GADA substudy. Participating laboratories
35 125 35 assayed coded IASP sets using both S or I labelled GAD65(1 585) and S labelled
GAD65(96 585). Of the 10 laboratories, 8 showed higher AS95 values with GAD65(96 585)
(Figure 4). Changes in the AS95 with the GAD65(96 585) label ranged widely from 14 to
+20%, showing that even within RBAs the reactivity of different sera is strongly influenced
by local assay conditions.
DISCUSSION
Using data from DASP workshops we have shown that the binding of GAD65 by healthy
control sera segregated according to assay format. Some control sera reacted preferentially in
the commercial ELISA but not in the RBA, while others found positive in many RBAs
showed no binding in ELISAs. A high proportion of the control sera found positive by RBAs
targeted epitopes in the N terminal region of GAD65 which are less commonly recognized by 9
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diabetes relevant antibodies (15 18). These findings prompted the construction of a plasmid encoding GAD65(96 585), suitable for generating N terminally truncated radiolabel. In the
IASP 2012 GADA substudy, 8 of 10 RBAs using this plasmid achieved a higher adjusted sensitivity than those using full length GAD65, indicating that the performance of many RBAs could be improved by use of N terminally truncated GAD radiolabels.
Earlier islet autoantibody workshops have shown differences in assay performance that could be ascribed to particular characteristics. The higher sensitivity of IA 2 autoantibody assays using plasmids expressing the intracellular region (ic) rather than the IA 2(256–556/630–979) or full length constructs led to more widespread adoption of IA 2ic autoantibody assays (10).
The clear superiority of RBAs over ELISAs for measuring insulin autoantibodies (IAA) has meant that RBAs have been used almost exclusively for IAA measurement (19). The differences we observed with GADA assay format were more subtle, but by focusing on signals generated by healthy control sera, we were able to identify an important source of disease irrelevant signals in the N terminus affecting RBAs. Despite the superior overall performance of the GADA ELISA, analogous modification of the capture antigen in the
ELISA format may improve the specificity of the assay. Even in the most robust GADA
ELISAs, false positive signals from sera acquired from healthy individuals contribute significantly to the higher background levels of binding that define assay thresholds, limiting our ability to assign true beta cell autoimmunity.
Birth cohort prospective studies of relatives of patients with type 1 diabetes have shown that diabetes relevant autoantibody epitope reactivity typically spreads from the C terminal and middle (PLP) regions to the N terminal domains of the molecule (12; 16). Autoantibodies to
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the N terminal region typically constitute a relatively minor component of GAD65
autoreactivity and alone confer little association with type 1 diabetes (17). However, we
cannot exclude the possibility that a very small proportion of sera from patients with type 1
diabetes may bind exclusively to the N terminus and will be missed by the truncated antigen.
Furthermore, in patients with other forms of diabetes such as latent autoimmune diabetes in
adults or slowly progressive type 1 diabetes mellitus, epitopes in the N terminal region may
constitute a larger proportion of the anti GAD response (20; 21). The potential benefit of
using truncated antigen to test for these conditions therefore, needs to be evaluated. Cross
reactive N terminal restricted GADA may mark an early phase of autoimmunity in
neurological conditions such as Stiff Person Syndrome (SPS) (22 24), although as those
disorders are rare and SPS itself is associated with very high GADA titers (25), the low level
N terminal restricted antibodies found in healthy controls are more likely attributed to cross
reactivity of irrelevant antibodies.
The commercial ELISA showed good sensitivity and specificity in DASP and IASP
workshops (9). This assay relies on the autoantibody forming a bridge between immobilized
GAD65 on the plate and biotinylated GAD65 in solution with detection by streptavidin
peroxidase (26). Access to N terminal epitopes may be hindered in this configuration
preventing the binding of the N terminally restricted antibodies detected by many RBAs. This
could also partly explain why luminescence immunoprecipitation (LIPS) and
electrochemiluminescence (ECL) assays (27; 28), showed good specificity in recent
workshops. However, we cannot exclude that other mechanisms may be responsible for lack
of binding of these N terminally restricted control sera in the ELISA. Some of the assay
dependent differences in recognition of DASP/IASP control sera are likely to be related to
antibody affinity. The three control sera found reactive with the middle region of GAD in
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RBAs, but negative by ELISA showed minimal displacement at low levels of competing
GAD65 which suggests that these sera contain low affinity antibodies. This may be why these antibodies were not detected by the commercial ELISA or the ECL assay, as the bridging format they employ favors the recognition of high affinity antibodies, which are more closely associated with diabetes progression (17; 29). The performance of RBAs using N terminally truncated GAD65 labels may therefore be further improved by including affinity measurements.
A major strength of this study was the availability of data from a number of DASP and IASP workshops which allowed us to identify consistent patterns in the reactivity of control sera according to assay format. The original design of the DASP workshops (10), with the inclusion of a relatively large number of control sera, has again been vindicated, as it allowed us to identify systematic differences in reactivity which would have been impossible with a smaller number of samples. These sample sets distributed to laboratories are however still limited with regard to sample number, as well as ethnicity, age and their cross sectional nature. Other important systematic variations in GADA binding by healthy control sera may be identified in different cohorts. Furthermore, only 10 laboratories participated fully in the
IASP 2012 GADA substudy, which restricted our ability to determine whether use of the
GAD65(96 585) label could enhance assay performance.
Measurement of GADA is fundamental to most strategies aimed at prediction and characterization of type 1 diabetes, but there has been concern that despite their high sensitivity GADA are often less closely associated with diabetes progression than other islet autoantibodies such as IA 2A and ZnT8A (30). The DASP and IASP workshops have
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revealed assay related differences in binding of GAD65 by control sera that should aid the
development of more specific GADA assays. If the promise shown by the N terminally
truncated GAD65(96 585) antigen probe to improve the specificity of GADA RBAs without
loss of sensitivity is confirmed in large prospective studies, we would advocate its adoption
for population screening in combination with other islet autoantibodies to identify individuals
at high risk of progression to type 1 diabetes.
AUTHOR CONTRIBUTIONS
A.J.K.W., V.L. and P.A. researched data; contributed to the discussion; and wrote the
manuscript. M.S., P.W.M., D.P., W.E.W., R.W., C.B., and S.K. researched data, and
reviewed/edited the manuscript. B.A. reviewed/edited the manuscript. A.J.K.W. is the
guarantor of this work and, as such, had full access to all the data in the study and takes
responsibility for the integrity of the data and the accuracy of the data analysis.
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ACKNOWLEDGEMENTS
DASP was funded at the CDC by PL105 33, 106 310, 106 554, and 107 360 administered by the NIH. IASP was funded at the UFL by CFDA # 93.847: Diabetes, Digestive, and Kidney
Diseases Extramural Research of the National Institute of Diabetes and Digestive and Kidney
Diseases. The authors know of no conflicts of interest relevant to this article. V.L. and C.B were supported by the Italian Ministry of Research “Ivascomar project, Cluster Tecnologico
Nazionale Scienze della Vita ALISEI” and by the Associazione Italiana per la Ricerca sul
Cancro “AIRC bando 5 × 1000 N_12182” grants.
Parts of this study were presented in abstract form at the 49th European Association for the
Study of Diabetes meeting, Barcelona, Spain, 23 27 September 2013 and at the 13th
International Congress of the Immunology of Diabetes Society, Mantra Lorne, Victoria,
Australia, 7 11 December 2013.
The authors are grateful to the patients and healthy donors who have contributed blood to
DASP and IASP as well as their physicians. We also thank Kyla Chandler at the University of
Bristol for assistance with the competitive displacement assays.
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1. Bingley PJ, Gale EA: Progression to type 1 diabetes in islet cell antibody positive relatives in the European Nicotinamide Diabetes Intervention Trial: the role of additional immune, genetic and metabolic markers of risk. Diabetologia 2006;49:881 890 2. Orban T, Sosenko JM, Cuthbertson D, et al.: Pancreatic islet autoantibodies as predictors of type 1 diabetes in the Diabetes Prevention Trial Type 1. Diabetes Care 2009;32:2269 2274 3. Haller MJ, Atkinson MA, Schatz D: Type 1 diabetes mellitus: etiology, presentation, and management. Pediatr Clin North Am 2005;52:1553 1578 4. Liu E, Eisenbarth GS: Accepting clocks that tell time poorly: fluid phase versus standard ELISA autoantibody assays. Clin Immunol 2007;125:120 126 5. Bingley PJ, Williams AJK: Validation of autoantibody assays in type I diabetes: Workshop programme. Autoimmunity 2004;37:257 260 6. Achenbach P, Schlosser M, Williams AJ, et al.: Combined testing of antibody titer and affinity improves insulin autoantibody measurement: Diabetes Antibody Standardization Program. Clin Immunol 2007;122:85 90 7. Schlosser M, Mueller PW, Achenbach P, Lampasona V, Bingley PJ: Diabetes Antibody Standardization Program: First evaluation of assays for autoantibodies to IA 2{beta}. Diabetes Care 2011;34:2410 2412 8. Lampasona V, Schlosser M, Mueller PW, et al.: Diabetes antibody standardization program: first proficiency evaluation of assays for autoantibodies to zinc transporter 8. Clin Chem 2011;57:1693 1702 9. Torn C, Mueller PW, Schlosser M, Bonifacio E, Bingley PJ: Diabetes Antibody Standardization Program: evaluation of assays for autoantibodies to glutamic acid decarboxylase and islet antigen 2. Diabetologia 2008;51:846 852 10. Bingley PJ, Bonifacio E, Mueller PW: Diabetes Antibody Standardization Program: first assay proficiency evaluation. Diabetes 2003;52:1128 1136 11. Bonifacio E, Yu L, Williams AK, et al.: Harmonization of glutamic acid decarboxylase and islet antigen 2 autoantibody assays for national institute of diabetes and digestive and kidney diseases consortia. J Clin Endocrinol Metab 2010;95:3360 3367 12. Bonifacio E, Lampasona V, Bernasconi L, Ziegler AG: Maturation of the humoral autoimmune response to epitopes of GAD in preclinical childhood type 1 diabetes. Diabetes 2000;49:202 208 13. Achenbach P, Guo LH, Gick C, et al.: A simplified method to assess affinity of insulin autoantibodies. Clin Immunol 2010;137:415 421 14. Curnock RM, Reed CR, Rokni S, Broadhurst JW, Bingley PJ, Williams AJ: 'Insulin autoantibody affinity measurement using a single concentration of unlabelled insulin competitor discriminates risk in relatives of patients with type 1 diabetes. Clin Exp Immunol 2012;167:67 72 15. Richter W, Shi Y, Baekkeskov S: Autoreactive epitopes defined by diabetes associated human monoclonal antibodies are localized in the middle and C terminal domains of the smaller form of glutamate decarboxylase. Proc Natl Acad Sci U S A 1993;90:2832 2836 16. Hoppu S, Ronkainen MS, Kulmala P, Akerblom HK, Knip M: GAD65 antibody isotypes and epitope recognition during the prediabetic process in siblings of children with type I diabetes. Clin Exp Immunol 2004;136:120 128 17. Mayr A, Schlosser M, Grober N, et al.: GAD autoantibody affinity and epitope specificity identify distinct immunization profiles in children at risk for type 1 diabetes. Diabetes 2007;56:1527 1533
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18. Fenalti G, Hampe CS, Arafat Y, et al.: COOH terminal clustering of autoantibody and T cell determinants on the structure of GAD65 provide insights into the molecular basis of autoreactivity. Diabetes 2008;57:1293 1301 19. Greenbaum CJ, Palmer JP, Kuglin B, Kolb H: Insulin autoantibodies measured by radioimmunoassay methodology are more related to insulin dependent diabetes mellitus than those measured by enzyme linked immunosorbent assay: results of the Fourth International Workshop on the Standardization of Insulin Autoantibody Measurement. J Clin Endocrinol Metab 1992;74:1040 1044 20. Hampe CS, Kockum I, Landin Olsson M, et al.: GAD65 antibody epitope patterns of type 1.5 diabetic patients are consistent with slow onset autoimmune diabetes. Diabetes Care 2002;25:1481 1482 21. Kobayashi T, Tanaka S, Okubo M, Nakanishi K, Murase T, Lernmark A: Unique epitopes of glutamic acid decarboxylase autoantibodies in slowly progressive type 1 diabetes. J Clin Endocrinol Metab 2003;88:4768 4775 22. Butler MH, Solimena M, Dirkx R, Jr., Hayday A, De Camilli P: Identification of a dominant epitope of glutamic acid decarboxylase (GAD 65) recognized by autoantibodies in stiff man syndrome. J Exp Med 1993;178:2097 2106 23. Kim J, Namchuk M, Bugawan T, et al.: Higher autoantibody levels and recognition of a linear NH2 terminal epitope in the autoantigen GAD65, distinguish stiff man syndrome from insulin dependent diabetes mellitus. J Exp Med 1994;180:595 606 24. Daw K, Ujihara N, Atkinson M, Powers AC: Glutamic acid decarboxylase autoantibodies in stiff man syndrome and insulin dependent diabetes mellitus exhibit similarities and differences in epitope recognition. J Immunol 1996;156:818 825 25. Piquer S, Belloni C, Lampasona V, et al.: Humoral autoimmune responses to glutamic acid decarboxylase have similar target epitopes and subclass that show titer dependent disease association. Clin Immunol 2005;117:31 35 26. Brooking H, Ananieva Jordanova R, Arnold C, et al.: A sensitive non isotopic assay for GAD65 autoantibodies. Clin Chim Acta 2003;331:55 59 27. Burbelo PD, Hirai H, Issa AT, et al.: Comparison of radioimmunoprecipitation with luciferase immunoprecipitation for autoantibodies to GAD65 and IA 2beta. Diabetes Care 2010;33:754 756 28. Miao D, Guyer KM, Dong F, et al.: GAD65 autoantibodies detected by electrochemiluminescence assay identify high risk for type 1 diabetes. Diabetes 62:4174 4178 29. Bender C, Schlosser M, Christen U, Ziegler AG, Achenbach P: GAD autoantibody affinity in schoolchildren from the general population. Diabetologia 2014;57:1911 1918 30. De Grijse J, Asanghanwa M, Nouthe B, et al.: Predictive power of screening for antibodies against insulinoma associated protein 2 beta (IA 2beta) and zinc transporter 8 to select first degree relatives of type 1 diabetic patients with risk of rapid progression to clinical onset of the disease: implications for prevention trials. Diabetologia 2010;53:517 524
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Figure legends
Figure 1. Adjusted sensitivity at 95% specificity (AS95) plotted against the area under the
curve (AUC) from ROC analysis of GADA assays participating in the DASP 2010 workshop.
Using these threshold independent measures, better performance is demonstrated by those
assays located towards the top right hand corner (circled), a cluster that includes all the
commercial ELISAs.
Figure 2. Heatmaps of laboratory defined positive negative calls for (a) the 10 healthy control
sera found positive most often in DASP 2010 and (b) the same sera in DASP 2009 for those
assays with a laboratory defined specificity of more than 90% sorted according to assay type.
Positive negative calls were found to cluster according to assay type; sera shaded in blue were
found positive most commonly by commercial ELISAs, those in yellow by RBAs and the
125 serum shaded in orange by RBAs using I labeled GAD65.
Figure 3. Epitope specificity of 8 healthy control sera from the DASP 2010 workshop that
showed assay related differences in reactivity. The left panel shows the different GAD
constructs used to assess epitope specificity with regions derived from GAD65 in black and
GAD67 in white. The right panel shows reactivity of the control sera with these GAD
constructs and the epitope reactivity ascribed to those sera based on the pattern of binding
with the different constructs. Four sera (S8531, N53371, TS23727, and LQ21235) showed
reactivity with GAD65 N terminal epitopes that was abolished by deletion of the first 95
amino acids. Three control sera (N56575, N51532 and N59932) showed weak reactivity with
the MID region of GAD65 (aa 235 444) and this binding was not reduced by use of the N
terminally truncated labels. 17
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35 125 35 Figure 4. AS95 for ten RBAs using S or I GAD65 (1 585) and S GAD65(96 585) to measure workshop samples in the IASP 2012 GADA substudy. Improved performance of assays using the N terminally truncated GAD is shown by the 8 laboratories that lie above the line of equivalence (hatched line).
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95 LIPS
90 In-house RBA
Commercial 85 ELISA Commercial AS95 AS95 (%) RBA 80 Standard RBA
75 In-house ELISA
70 0.88 0.9 0.92 0.94 0.96 0.98 1 AUC 2a Diabetes Page 20 of 30
Commercial Commercial Standard In-house ELISA RBA RBA RBA LIPS ELISA
Laboratory
ID 132 518 109 505 113 503 604 119 703 704 150 305 702 402 305 501 132 305 209 109 133 123 118 116 118 121 213 114 137 221 507 134 213 156 129 155 153 116 120 301 133 504 153 150 150 scoring + scoring
AUC 0.97 0.97 0.96 0.95 0.94 0.94 0.94 0.94 0.93 0.93 0.92 0.94 0.94 0.93 0.92 0.92 0.92 0.90 0.90 0.94 0.94 0.94 0.93 0.93 0.93 0.93 0.93 0.95 0.95 0.94 0.94 0.93 0.92 0.93 0.93 0.93 0.92 0.92 0.92 0.92 0.91 0.91 0.94 0.91 0.90 % of assays assays of % LQ21235 + + - + + + - + + + ------17 LQ19277 + + - + + + + + + + ------+ ------+ ------26 TS23727 + + + + + + + + + + ------+ + + + + + ------+ + - - - - - + - 43 LQ22058 + + - + + + - + - + - - + + + + + + + - - - - - + ------+ - - - + - + + - - + - + + 50 N51532 ------+ + + + + + + + + - - + + + + + - + - - - + - - - - + + - - + - - - 43 N56575 ------+ + + + + + + + - - - + + + + - - + - - - + - - + - + + - - + - - - 41 N59932 ------+ + + + + + + + ------+ - - + - - - + - - - - + + ------30 S8531 ------+ + - - - + - + - + + + - - - - - + + - - + ------22 N53371 ------+ - + + + + + - - - + - - - + + + ------22 N54357 ------+ + + + + + ------15 2bPage 21 of 30 Diabetes
Commercial Commercial Standard In-house ELISA RBA RBA RBA LIPS
Laboratory
ID 132 136 505 518 518 602 110 109 519 501 136 602 603 132 111 111 113 607 402 209 213 121 116 133 109 504 133 118 152 114 156 116 120 126 221 137 213 150 304 133 115 126 301 155 129 153 507 148 153 405 scoring + scoring
AUC 0.96 0.96 0.95 0.95 0.94 0.93 0.92 0.91 0.91 0.94 0.93 0.92 0.92 0.92 0.92 0.91 0.91 0.91 0.90 0.85 0.95 0.94 0.93 0.93 0.92 0.91 0.91 0.90 0.96 0.95 0.95 0.95 0.94 0.94 0.93 0.93 0.92 0.92 0.92 0.91 0.91 0.90 0.90 0.90 0.89 0.89 0.85 0.85 0.89 0.86 % of assays assays of % LQ21235 + + + + + + + + + ------18 LQ19277 + + + + + + + + ------+ ------+ + ------+ ------+ ------26 TS23727 + + + + + + + + - - - + - + - - + + + - + + + + - + - + + + - + - + - - + - - - - + - - - - - + - - 52 LQ22058 - + + - - + + + - + + + + + + + + + + + + - - - - + ------+ - - - + + - - - - + - - + - - + 48 N51532 ------+ + + + + + + + + + + + + + - + + - + + + - + + + - + + + - - - + - - - + - + + - 58 N56575 ------+ + + + + + + + + + + + + + - + + - + + + - + + + - + + + ------+ + + - - 56 N59932 ------+ + + + + + + + + + + + - + - - - - + + + - - - + - + + + ------+ - - - - 42 S8531 ------+ + + + - + + - - + - - - + - - - - + ------18 N53371 ------+ + + - - - - - + + - + - + - + + - - - - + ------20 N54357 ------+ - - + + + + - - + ------+ ------14 SerumDiabetes LQ19277 N56575 N51532 N59932 S8531 N53371 TS23727Page LQ21235 22 of 30 3 1 95 101 593
GAD65-NH2 - - - - + + + + GAD65 aa1-95 GAD67 aa101-593
1 101 96 440 453 593
GAD65-MID-N ++ + + + - + - ND GAD67 aa1-101 GAD65 aa96-440 GAD67 aa453-593
1 243 235 444 453 593
GAD65-MID ++ + + + - + - - GAD67 aa1-243 GAD65 aa235-444 GAD67 aa453-593
1 452 445 585
GAD65-COOH ++ - - - - + - - GAD67 aa1-452 GAD65 aa445-585
1 593
GAD67 ++ - - - - + - - GAD67 aa1-593
46 585
GAD65(46-585) - + + + - + + + GAD65 aa46-585
96 585
GAD65(96-585) - + + + - - - - GAD65 aa96-585 GAD67 GAD65 GAD65 GAD65 GAD65 GAD67 GAD65 GAD65 Ascribed NH2 Mid Mid Mid NH2 NH2 NH2 specificity GAD65 NH2 4Page 23 of 30 Diabetes 100
90 585) % - 80
70 GADA (96 GADA
AS95 60
50 50 60 70 80 90 100 AS95 GADA (1-585) % Diabetes Page 24 of 30
Ethnicity* Cohort n Male Age (range) White Black Hispanic
DASP2009 Cases 50 33 24.5 yrs (10-32 yrs) 40 1 8
DASP2009 Controls 100 50 20 yrs (18-30 yrs) 80 20 0
DASP2010 Cases 50 22 21.5 yrs (6-50 yrs) 46 1 1
DASP2010 Controls 90 48 20 yrs (18-30 yrs) 71 19 0
IASP2012 Cases 50 28 15 yrs (9-37 yrs) 43 6 1
IASP2012 Controls 90 45 20 yrs (18-30 yrs) 71 19 0
Supplemental table 1. Characteristics of cases with newly-diagnosed type 1 diabetes and healthy controls included in DASP2009, DASP2010 and IASP2012 workshops.
*One DASP 2009 case was Asian and two DASP2010 cases were of unknown ethnicity
Page 25 of 30 Diabetes
DASP2009 Workshop: DASP2010 Workshop: 50 T1D patients and 100 50 T1D patients and 90 blood donor controls blood donor controls
42 laboratories with 56 GADA assays 39 laboratories with 53 GADA assays
3 laboratories assayed DASP2010 35 samples with S-labeled GAD65(1-585), GAD65(46-585) and GAD65(96-585)
IASP2012 GADA substudy: 50 T1D patients and 90 blood donor controls 10 laboratories assayed samples with 35S-labeled
GAD65(1-585) and GAD65(96-585)
Supplemental figure 1. A flow diagram showing the study design; Analysis of GADA assays participating in the DASP2010 and DASP2009 workshops identified systematic differences in the positivity of control samples according to assay type. Some of these differences were
ascribed to altered recognition of epitopes in the N-terminal of GAD65. Three laboratories using radiobinding assays therefore tested two N-terminally truncated GAD constructs to determine whether they could improve assay performance. Ten laboratories then evaluated the performance of GADA assays using either 35S-labeled full-length GAD65(1-585) or N-
terminally truncated GAD65(96-585) in the IASP2012 GADA substudy.
Diabetes Page 26 of 30
1000 14000 a 900 b 12000 800 700 10000 600 8000 500 400 6000
300 4000 GADA binding(cpm) GADA 200 binding(cpm) GADA 2000 100
0 0
Serum Serum
c 1000 d 12000 900 10000 800 700 8000 600
500 6000 400 300 4000
GADA binding(cpm) GADA 200 GADA binding(cpm) GADA 2000 100
0 0
Serum Serum
35 Supplemental figure 2. Binding of S-labeled GAD65(1-585) (blue columns) and GAD65(96- 585) (red columns) with 10 control sera (panels a and c) and 6 patient sera (panels b and d) included in the DASP2010 workshop following competitive displacement with 5 pmol/well
(panels a & b) or 0.05 pmol/well (panels c and d) recombinant GAD65. Filled column areas represent displaced binding and open areas represent binding that does not compete. Patient sera show good displacement of binding at both concentrations of unlabeled GAD, and many control sera are displaced at 5 pmol/well unlabeled antigen. Most control sera however, including three reactive with epitopes in the middle region of GAD65 (N51532,
N56575 and N59932), show limited displacement at 0.05 pmol/well GAD65 which indicates that these sera contain antibodies that are mainly of low affinity. Page 27 of 30 Diabetes
95
90
85
AS95 (%) AS95 80
75
70
GAD(1-585) GAD(46-585) GAD(96-585)
GAD65 construct
Supplemental figure 3. Adjusted sensitivity at 95% specificity (AS95) of RBAs in three
selected laboratories using radiolabel generated from three different GAD65 plasmid
constructs. The N-terminally truncated GAD65(96-585) gave the best performance in all laboratories.
Diabetes Page 28 of 30
Participating Laboratories and contacts for the DASP 2009 GADA workshop
P. Achenbach, A.-G. Ziegler, Diabetes Research Group of the TU Munich, Munich, Germany; J. Furmaniak, FIRS Laboratories RSR Limited, Cardiff, UK; Vinod Gaur, S.M. Marcovina, Northwest Lipid Metabolism and Diabetes Research Laboratory, University of Washington, Seattle, WA, USA; S. Gellert, Endocrinology Lab, Centre for Medical Research, Royal Melbourne Hospital, Melbourne, Australia; F. Gorus, J. De Grijse, P. Goubert, Dept of Clinical Chemistry and Radioimmunology, University of Brussels, Brussels, Belgium; W. A. Hagopian, Pacific North West Research Institute, Seattle, WA, USA; D.M. Harlan, J. Lee, Clinical Research Center, NIH, Bethesda, MD, USA; M. I. Hawa, Center for Diabetes and Metabolic Medicine, London, UK; E. Kawasaki, Department of Metabolism/Diabetes & Clinical Nutrition, Nagasaki University, Hospital of Medicine and Dentistry, Nagasaki, Japan; M. Knip, Hospital for Children and Adolescents, University of Helsinki, Helsinki, Finland; V. Lampasona, Laboratorio Autoimmunita-LIDEA, Diagnostica e Ricerca San Raffaele, Milan, Italy; P.W. Mueller, National Diabetes Laboratory, Centers for Disease Control and Prevention, Atlanta, GA, USA; A. Nilsson, F. Vaziri Sani, Diabetes and Celiac Disease Unit, Lund University, Malmö, Sweden; M. Schlosser, H. Kenk, Department of Medical Biochemistry and Molecular Biology, University of Greifswald, Karlsburg, Germany; C. Tiberti, F. Dotta, Department of Clinical Science, Immunoendocrinology, University of Rome "La Sapienza“, Rome, Italy; P.A. Torjesen, Hormone Laboratory, Aker University Hospital, Oslo, Norway; M. Probst, T. Pfeiffer, S. Torkler, Euroimmun, Lübeck, Germany; R. Uibo, K. Reimand, Department of Immunology, University of Tartu, Tartu, Estonia; A.J.K. Williams, P.J. Bingley, Diabetes and Metabolism, University of Bristol, Bristol, UK; A. Xu, Z. Zhou, G. Huang, Diabetes Center, Institute of Metabolism and Endocrinology, 2nd Xiangya Hospital, Central South University, The University of Hong Kong, Hongkong, China; L. Yu, Barbara Davies Center for Childhood Diabetes, University of Colorado, Aurora, CO, USA; E. Poskus, S. Valdez, A. Cardoso, LIE, School of Pharmacy and Biochemistry, University of Buenos Aires, Buenos Aires, Argentina; M. Atkinson, C. Wasserfall, University of Florida, Gainesville, USA; N. Schloot, F. Zivehe, German Diabetes Center, Institute for Clinical Diabetology, Dusseldorf, Germany; M.R. Batstra, T. Cieremans, Diagnostic Center SSDZ, Medical Laboratories Department of Medical Immunology, Delft, The Netherlands; R. Veijola, Department of Pediatrics, University of Oulu, Oulu, Finland; A.Pollard, J. Couper, Dept. of Paediatrics, Women's & Children's Hospital, Adelaide, Australia; Michael Eckhard, Diabetes and Endocrinology, UKGM, Giessen, Germany; L. Chatenoud, Immunologie Biologique, Hôpital Necker, University of Paris Descartes, Paris, France; T. Kobayashi, Third Department of Internal Medicine, University of Yamanashi, Yamanashi, Japan; I. Johansson, Division of Pediatrics, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden; D. Pittman, Department of Pathology, University of Florida, Gainesville, FL, USA; G. Houen, Department of Clinical Biochemistry and Immunology, Statens Serum Institute, Copenhagen, Denmark; C. Hampe, Jared Radtke, Metabolism, Endocrinology and Nutrition, Department of Medicine, University of Washington, Seattle, WA, USA; A. Esquerda, Clinical Laboratory, Arnau de Vilanova University Hospital, Lleida, Spain; A. Miettinen, Department of Immunology, HUSLAB, University of Helsinki, Helsinki, Finland; M.G. Baroni, Department of Experimental Medicine, University of Rome "La Sapienza“, Rome, Italy; A. Caston-Balderrama, A. Fraser, M. French, Quest Diagnostics, Nichols Institute, San Juan Capistrano, CA, USA; L. Park, Department of Bioengineering, College of Engineering, Hanyang University, Seoul, South Korea; A. Pugliese, Immunogenetics Laboratory, Diabetes Research Institute, University of Miami, Miami, FL, Page 29 of 30 Diabetes
USA; R. Casamitjana, Biochemistry and Molecular Genetics Department, University of Barcelona, Barcelona, Spain; W. Mlynarski, K. Wyka, Laboratory of Immunopathology and Genetics, Department of Pediatrics, Oncology, Hematology and Diabetology, UMED Medical University of Lodz, Lodz, Poland.
Participating Laboratories and contacts for the DASP 2010 GADA workshop
P. Achenbach, A.-G. Ziegler, Diabetes Research Group of the TU Munich, Munich, Germany; J. Furmaniak, FIRS Laboratories RSR Limited, Cardiff, UK; Vinod Gaur, S.M. Marcovina, Northwest Lipid Metabolism and Diabetes Research Laboratory, University of Washington, Seattle, WA, USA; F. Gorus, K. Verhaeghen, P. Goubert, Department of Clinical Chemistry and Radioimmunology, University of Brussels, Brussels, Belgium; M. I. Hawa, Center for Diabetes and Metabolic Medicine, London, UK; W. A. Hagopian, Pacific North West Research Institute, Seattle, WA, USA; M. Knip, Hospital for Children and Adolescents, University of Helsinki, Helsinki, Finland; V. Lampasona, Laboratorio Autoimmunita-LIDEA, Diagnostica e Ricerca San Raffaele, Milan, Italy; P.W. Mueller, C. Mapango, National Diabetes Laboratory, Centers for Disease Control and Prevention, Atlanta, GA, USA; A. Nilsson, Diabetes and Celiac Disease Unit, Lund University, Malmö, Sweden; M. Schlosser, H. Kenk, Department of Medical Biochemistry and Molecular Biology, University of Greifswald, Karlsburg, Germany; C. Tiberti, F. Dotta, Department of Clinical Science, Immunoendocrinology, University of Rome "La Sapienza“, Rome, Italy; P.A. Torjesen, Hormone Laboratory, Aker University Hospital, Oslo, Norway; R. Uibo, K. Reimand, Department of Immunology, University of Tartu, Tartu, Estonia; A.J.K. Williams, P.J. Bingley, Diabetes and Metabolism, University of Bristol, Bristol, UK; L. Yu, Barbara Davies Center for Childhood Diabetes, University of Colorado, Aurora, CO, USA; M.R. Batstra, T. Cieremans, Diagnostic Center SSDZ, Medical Laboratories Department of Medical Immunology, Delft, The Netherlands; R. Veijola, M. Knip, Department of Pediatrics, University of Oulu, Oulu, Finland; A.Pollard, J. Couper, Dept. of Paediatrics, Women's & Children's Hospital, Adelaide, Australia; L. Chatenoud, Immunologie Biologique, Hôpital Necker, University of Paris Descartes, Paris, France; T. Kobayashi, Third Department of Internal Medicine, University of Yamanashi, Yamanashi, Japan; I. Johansson, Division of Pediatrics, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden; D. Pittman, Department of Pathology, University of Florida, Gainesville, FL, USA; G. Houen, Y.M. Moreno, K. Lunau-Christensen, Department of Clinical Biochemistry and Immunology, Statens Serum Institute, Copenhagen, Denmark; C. Hampe, Jared Radtke, Metabolism, Endocrinology and Nutrition, Department of Medicine, University of Washington, Seattle, WA, USA; Aureli Esquerda, Clinical Laboratory, Arnau de Vilanova University Hospital, Lleida, Spain; A. Miettinen, Department of Immunology, HUSLAB, University of Helsinki, Helsinki, Finland; B Ekholm, Diabetes Research Laboratory, Department of Clinical Sciences, Lund University, Sweden; L. Castaño , R. Bilbao, Endocrinology and Diabetes Research Group, Hospital de Cruces, Barakaldo, Bizkaia, Spain; M.R. Christie, Diabetes Research Group, King’s College London, London, UK; C. Giordano, Biomedical Department of Internal and Specialist Medicine, Section of Endocrinology, Diabetology, and Metabolism, University of Palermo, Palermo, Italy; R. Pujol- Borrell, E. Martínez Cáceres, Immunology Lab, LIRAD-BST-HUGTP, Germans Trias Pujol University Hospital, UAB, Badalona, Spain; W. Mlynarski, K. Wyka, Laboratory of Immunopathology and Genetics, Department of Pediatrics, Oncology, Hematology and Diabetes Page 30 of 30
Diabetology, UMED Medical University of Lodz, Lodz, Poland; J. Siftancova, Laboratory of Autoimmune Diseases, Paediatric Department, University Hospital Motol and 2nd Faculty of Medicine, Charles University in Prague, Prague, Czech Republic; T. McDonald, Clinical Chemistry and Immunology, Royal Devon and Exeter Hospital, UK; J. Knezevic Cuca, Immunology of Diabetes Unit, Institute of Clinical Chemistry and Laboratory Medicine, Merkur University Hospital, Zagreb, Croatia; R. Casamitjana, Biochemistry and Molecular Genetics Department, University of Barcelona, Barcelona, Spain; H.-J. Thiesen, Institute for Immunology, STZ für Proteom-Analyse, Rostock, Germany; S. Scheucher, LKH-University Klinikum, Graz, Austria.
Participating Laboratories and contacts for the IASP2012 GADA substudy
P. Achenbach, A.-G. Ziegler, Diabetes Research Group of the TU Munich, Munich, Germany; F. Gorus, K. Verhaeghen, P. Goubert, Department of Clinical Chemistry and Radioimmunology, University of Brussels, Brussels, Belgium; M. Knip, Hospital for Children and Adolescents, University of Helsinki, Helsinki, Finland; M. Schlosser, H. Kenk, Department of Medical Biochemistry and Molecular Biology, University of Greifswald, Karlsburg, Germany; R. Uibo, K. Reimand, Department of Immunology, University of Tartu, Tartu, Estonia; A.J.K. Williams, P.J. Bingley, Diabetes and Metabolism, University of Bristol, Bristol, UK; M.R. Christie, Diabetes Research Group, King’s College London, London, UK; A. Xu, Z. Zhou, G. Huang, Diabetes Center, Institute of Metabolism and Endocrinology, 2nd Xiangya Hospital, Central South University, The University of Hong Kong, Hongkong, China; T Yang, Department of Endocrinology, First Affiliated Hospital of Nanjing Medical University, Nanjing, China; E. Kawasaki, Department of Metabolism/Diabetes & Clinical Nutrition, Nagasaki University, Hospital of Medicine and Dentistry, Nagasaki, Japan.