Detection of antibodies directed to the N-terminal region ... · However GADA are also found in many individuals at low risk of diabetes progression. To identify the sources of diabetes

1

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 Lampasona

2, Michael Schlosser

3, Patricia W Mueller

4, David L

Pittman5, William E Winter

5, Beena Akolkar

6, Rebecca Wyatt

1, Cristina Brigatti

2, Stephanie

Krause7, Peter Achenbach

7 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

Page 1 of 30 Diabetes

Diabetes Publish Ahead of Print, published online May 13, 2015

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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

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.

Page 2 of 30Diabetes

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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


4

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 µL 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


5

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 35

S-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).


6

For the IASP 2012 GADA substudy, participating laboratories generated 35

S-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

125I-labeled human recombinant full-length GAD65. Prior to the GADA substudy, coded

DASP 2010 sets were assayed by three selected laboratories using both 35

S-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


7

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

by RBA using 35

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


8

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.

Specificity of binding to 35

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 35

S-

GAD65(1-585) and 72% (range 70% to 76%) in the three sera found positive with 35

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%

(range 68% to 98%) and 91% (range 71% to 98%) for 35

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%)

and 76% (range 61% to 87%) with 35

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

N59932) was 0% (range 0% to 15%) with 35

S-labeled GAD65(1-585) and 14% (range 9 to

24%) with 35

S-labeled GAD65(96-585) indicating that these samples had low affinity

antibodies (Supplemental Fig. 2c).


9

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

set of samples from DASP 2010 with 35

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

assayed coded IASP sets using both 35

S or 125

I labelled GAD65(1-585) and 35

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


10

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


11

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


12

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


13

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.


14

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.


15

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17

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

serum shaded in orange by RBAs using 125

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.


18

Figure 4. AS95 for ten RBAs using 35

S or 125

I-GAD65 (1-585) and 35

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).


70

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0.88 0.9 0.92 0.94 0.96 0.98 1

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1 Page 19 of 30 Diabetes

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LQ21235 + + - + + + - + + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 17

LQ19277 + + - + + + + + + + - - - - - - + - - - - - - - - + - - - - - - - - - - - - - - - - - - - 26

TS23727 + + + + + + + + + + - - - - - - - - - - - - + + + + + + - - - - - - - - + + - - - - - + - 43

LQ22058 + + - + + + - + - + - - + + + + + + + - - - - - + - - - - - - + - - - + - + + - - + - + + 50

N51532 - - - - - - - - - - - + + + + + + + + + - - + + + + + - + - - - + - - - - + + - - + - - - 43

N56575 - - - - - - - - - - - + + + + + + + + - - - + + + + - - + - - - + - - + - + + - - + - - - 41

N59932 - - - - - - - - - - - + + + + + + + + - - - - - - + - - + - - - + - - - - + + - - - - - - 30

S8531 - - - - - - - - - - - - - - - + + - - - + - + - + + + - - - - - + + - - + - - - - - - - - 22

N53371 - - - - - - - - - - - - - - - - - - - - - - + - + + + + + - - - + - - - + + + - - - - - - 22

N54357 - - - - - - - - - - - - - + + + + + + - - - - - - - - - - - - - - - - - - - - - - - - - - 15

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LQ21235 + + + + + + + + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 18

LQ19277 + + + + + + + + - - - - - - + - - - - - - + + - - - - - - - - - - + - - - - - - - + - - - - - - - - 26

TS23727 + + + + + + + + - - - + - + - - + + + - + + + + - + - + + + - + - + - - + - - - - + - - - - - + - - 52

LQ22058 - + + - - + + + - + + + + + + + + + + + + - - - - + - - - - - - - + - - - + + - - - - + - - + - - + 48

N51532 - - - - - - - - - + + + + + + + + + + + + + + - + + - + + + - + + + - + + + - - - + - - - + - + + - 58

N56575 - - - - - - - - - + + + + + + + + + + + + + + - + + - + + + - + + + - + + + - - - - - - - + + + - - 56

N59932 - - - - - - - - - + + + + + + + + + + + + - + - - - - + + + - - - + - + + + - - - - - - - + - - - - 42

S8531 - - - - - - - - - - - - - - - - - - - - - + + + + - + + - - + - - - + - - - - + - - - - - - - - - - 18

N53371 - - - - - - - - - - - - - - - - - - - + + + - - - - - + + - + - + - + + - - - - + - - - - - - - - 20

N54357 - - - - - - - - - - + - - + + + + - - + - - - - - - - - - - - - - - - - + - - - - - - - - - - - - 14

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Serum LQ19277 N56575 N51532 N59932 S8531 N53371 TS23727 LQ21235

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 aa46-585

96 585

- + + + - - - -

GAD65 aa96-585

Ascribed GAD67

NH2

GAD65

Mid

GAD65

Mid

GAD65

Mid

GAD65

NH2

GAD67 GAD65

NH2

GAD65

NH2

specificity GAD65

NH2

3

GAD65(46-585)

GAD65(96-585)


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-585

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4 Page 23 of 30 Diabetes

Cohort n Male Age (range)

Ethnicity*

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


DASP2009 Workshop:

50 T1D patients and 100

blood donor controls

DASP2010 Workshop:



IASP2012 GADA substudy:



42 laboratories with 56 GADA assays 39 laboratories with 53 GADA assays

10 laboratories assayed samples with 35S-labeled

GAD65(1-585) and GAD65(96-585)

3 laboratories assayed DASP2010

samples with 35S-labeled GAD65(1-585),

GAD65(46-585) 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.


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c d

Supplemental figure 2. Binding of 35S-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.


70

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95

AS95 (%)

GAD65 construct

GAD(1-585) GAD(46-585) GAD(96-585)

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.


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,


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


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


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


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.


Documents

Detection of antibodies directed to the N-terminal region ... · However GADA are also found in many individuals at low risk of diabetes progression. To identify the sources of diabetes