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Harmonization of immunoassays for biomarkers in diabetes mellitus

February 2019
Biotechnology Advances 39(4)

February 2019
39(4)

DOI:10.1016/j.biotechadv.2019.02.015

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Authors:

Sebastian Hörber

University Hospital Tuebingen, Tuebingen, Germany

Harmonization of biomarkers is important for the comparability of laboratory results as it allows the definition of universal reference values and clinical decision limits. In diabetology, immunoassays are widely used to determine HbA1c, C-peptide, insulin, and autoantibodies to beta cell proteins, which are essential biomarkers for the diagnosis and classification of diabetes mellitus. Furthermore, as large clinical studies have identified HbA1c as a predictor for the development of diabetic complications, HbA1c has evolved as the general treatment target. For decades, the use of non-harmonized assays caused confusion. After the standardization of HbA1c, the worldwide comparability improved and increased the confidence in this laboratory biomarker. Insulin and C-peptide are not only valuable biomarkers to assess beta-cell function, but may also be used to evaluate insulin resistance, a metabolic feature of type 2 diabetes often occurring before its manifestation. Long-lasting efforts led to substantial improvements in the harmonization process of C-peptide assays, but harmonization of insulin assays is still ongoing. Therefore, C-peptide is now sometimes used as a surrogate biomarker for insulin. Furthermore, autoantibodies against beta cell components are important biomarkers for the accurate differentiation of type 1, type 2, and other special types of diabetes. Owing to the heterogeneity of these autoantibodies against beta cell proteins, harmonization is very difficult to achieve. International efforts are in progress to harmonize the current assays, as the presence of autoantibodies against beta cell proteins predicts the development of type 1 diabetes in early life. In conclusion, clinical studies linking diagnosis, classification, prediction, and treatment to laboratory values of the respective biomarkers need to be harmonized to avoid misdiagnosis and incorrect clinical decisions, thus improving patient care and safety.

Pathological events leading to type 1 and type 2 diabetes mellitus. The sequence of events leading to type 1 and type 2 diabetes mellitus is schematically shown together with relevant biomarkers. Development of type 2 diabetes is caused by constitutional factors and genetic predisposition. These factors favor insulin resistance which is accompanied by elevated insulin and C-peptide concentrations as counter regulatory mechanism in the early stage of disease progression. Consequently, this may lead to a dysregulation of the pancreatic beta cells characterized by an impaired glucose tolerance. Further exacerbation finally ends in the manifestation of type 2 diabetes due to beta cell insufficiency accompanied by inadequately reduced insulin and C-peptide secretion and plasma concentrations. In contrast, the development of type 1 diabetes mellitus is assumed to be associated with genetic and environmental factors. The initial step in the progress of type 1 diabetes is not fully understood. It is presumed that activation of immune cells leads to an autoimmune response accompanied by the formation of high-affinity autoantibodies against antigens of the pancreatic beta cell. Subsequent beta cell destruction leads to insulin and C-peptide deficiency and finally to the manifestation of type 1 diabetes mellitus.

…

Schematic illustration of the formation of glycated hemoglobin (HbA1c). In a first reversible step, glucose is attached to the N-terminal valine of the hemoglobin ß-chain forming a labile Schiff Base, which is rearranged to a stabile ketoamine bond yielding HbA1c. The concentration of HbA1c is proportional to both the patient's erythrocyte life span and the mean glucose concentration during that life span of approximately 120 days.

…

Comparison of HbA1c values obtained by different national harmonization programs. In addition to the U.S., Japan and Sweden set up programs for harmonization of HbA1c comparison of distributed blood samples showed that HbA1c values were lower in Japan and much more so in Sweden, using the highly efficient separation column Mono-S, than US values (Miedema, 2004). DCM, designated comparison method. Reprinted by permission from Springer Customer Service Centre GmbH: Springer, Diabetologia, Towards worldwide standardization of HbA1c determination, Miedema K., c 2004.

…

Reference method for HbA1c. Hemoglobin from lysed human erythrocytes is digested with endoproteinase Glu-C, which specifically splits the peptide bond between two adjacent glutamates liberating N-terminal hexapeptide, regardless of glycation state. The peptides were separated by HPLC and quantified either by electrospray ionization mass spectrometry (ESI-MS) or by capillary electrophoresis (CE) using UV detection at 214 nm. Both methods yielded identical results (Jeppsson et al., 2002).

…

Schematic illustration of insulin synthesis by proinsulin cleavage. After formation of proinsulin in the endoplasmic reticulum, proinsulin is packed in granules and split into insulin and C-peptide by limited proteolysis (arrows). Upon stimulation (e.g. by glucose), both peptides are rapidly secreted into circulation at an equimolar ratio. As insulin is rapidly degraded by the liver, insulin concentrations in the peripheral blood are markedly reduced compared to C-peptide concentrations.

…

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Biotechnology Advances

journal homepage: www.elsevier.com/locate/biotechadv

Research review paper

Harmonization of immunoassays for biomarkers in diabetes mellitus

Sebastian Hörber

a,b,c

, Peter Achenbach

c,d

, Erwin Schleicher

a,b,c,⁎

, Andreas Peter

a,b,c

Institute for Clinical Chemistry and Pathobiochemistry, Department for Diagnostic Laboratory Medicine, University Hospital Tübingen, Germany

Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich, University of Tübingen, Germany

German Center for Diabetes Research (DZD), München-Neuherberg, Germany

Institute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health, München-Neuherberg, Germany

ARTICLE INFO

Keywords:

Autoantibodies

Biomarker

Classiﬁcation

C-peptide

Diabetes mellitus

Glycated hemoglobin

Harmonization

Immunoassay

Insulin

Prediction

Standardization

ABSTRACT

Harmonization of biomarkers is important for the comparability of laboratory results as it allows the deﬁnition

of universal reference values and clinical decision limits. In diabetology, immunoassays are widely used to

determine HbA1c, C-peptide, insulin, and autoantibodies to beta cell proteins, which are essential biomarkers for

the diagnosis and classiﬁcation of diabetes mellitus. Furthermore, as large clinical studies have identiﬁed HbA1c

as a predictor for the development of diabetic complications, HbA1c has evolved as the general treatment target.

For decades, the use of non-harmonized assays caused confusion. After the standardization of HbA1c, the

worldwide comparability improved and increased the conﬁdence in this laboratory biomarker. Insulin and C-

peptide are not only valuable biomarkers to assess beta-cell function, but may also be used to evaluate insulin

resistance, a metabolic feature of type 2 diabetes often occurring before its manifestation. Long-lasting eﬀorts led

to substantial improvements in the harmonization process of C-peptide assays, but harmonization of insulin

assays is still ongoing. Therefore, C-peptide is now sometimes used as a surrogate biomarker for insulin.

Furthermore, autoantibodies against beta cell components are important biomarkers for the accurate diﬀer-

entiation of type 1, type 2, and other special types of diabetes. Owing to the heterogeneity of these auto-

antibodies against beta cell proteins, harmonization is very diﬃcult to achieve. International eﬀorts are in

progress to harmonize the current assays, as the presence of autoantibodies against beta cell proteins predicts the

development of type 1 diabetes in early life. In conclusion, clinical studies linking diagnosis, classiﬁcation,

prediction, and treatment to laboratory values of the respective biomarkers need to be harmonized to avoid

misdiagnosis and incorrect clinical decisions, thus improving patient care and safety.

1. Introduction

1.1. Why do we need harmonization?

Together with clinical examination, laboratory tests provide

important mosaic pieces to establish the diagnosis of a disease and are

useful for prognosis and treatment monitoring. For interpretation in

many cases, ﬁxed reference ranges are used to assess the results of la-

boratory tests and national and international guidelines use ﬁxed la-

boratory test values, e.g. cut-oﬀ values, for treatment decisions. If

https://doi.org/10.1016/j.biotechadv.2019.02.015

Received 29 October 2018; Received in revised form 7 February 2019; Accepted 21 February 2019

Abbreviations: ADA, American Diabetes Association; CAP, College Of American Pathologists; CE, Capillary Electrophoresis; DASP, Diabetes Antibody

Standardization Program; DCCT, Diabetes Control And Complications Trial; DCM, Designated Method Comparison; EASD, European Association For The Study Of

Diabetes; ECBS, Expert Committee On Biological Standardization; ECL, Electrochemiluminescence; ELISA, Enzme-Linked Immunosorbant Assay; GAD, Glutamate

Decarboxylase; GADA, Autoantibodies To GAD; GHb, Total Glycated Hemoglobin; HbA1c, Glycated Hemoglobin; HOMA, Homeostasis Model Assessment; HPLC,

High Pressure Liquid Chromatography; IA-2A, Autoantibodies To IA-2; IAA, insulin autoantibodies; IASP, Islet Autoantibody Standardization Program; ICA, Islet Cell

Antibodies; IDF, International Diabetes Federation; IDS, Immunology Of Diabetes Society; IFCC, International Federation Of Clinical Chemistry; IRR, International

Reference Reagent; JCTLM, Joint Committee For Traceability In Laboratory Medicine; LADA, Late Onset Autoimmune Diabetes In The Adult; LC-MS, Liquid

Chromatography–Tandem Mass Spectrometry; LIPS, Luciferase Immunoprecipitation System; MODY, Maturity Onset Diabetes Of The Young; MS, Mass Spectroscopy;

NGSP, National Glycohemoglobin Standardization Program”; NIBSC, National Institute For Biological Standards And Control; NIDDK, National Institute Of Diabetes

And Digestive And Kidney Diseases; NMIJ, National Metrology Institute Of Japan; PRM, Primary Reference Material; RBA, Radio-binding Assay; RIA,

Radioimmunoassay; RMP, Reference Measurement Procedure; UKPDS, United Kingdom Prospective Diabetes Study; WHO, World Health Organization; ZnT8, Zink

Transporter-8; ZnT8A, Autoantibodies To ZnT8

⁎

Corresponding author at: Otfried-Müller-Str.10, 72076 Tübingen, Germany.

E-mail address: Erwin.Schleicher@med.uni-tuebingen.de (E. Schleicher).

Biotechnology Advances 39 (2020) 107359

Available online 23 February 2019

(http://creativecommons.org/licenses/BY-NC-ND/4.0/).

laboratory results are aﬀected by the analytical procedure, i.e. if they

are not harmonized, wrong conclusions may be drawn for the diagnosis

or the treatment of a patient, although the doctor is adhering to the

guidelines. In these cases, patient safety may be aﬀected (Miller et al.,

2014).

Harmonization of laboratory tests indicates that comparable results

are obtained independent of when and where the analysis is performed.

At best, harmonization can be obtained by standardization of an assay

indicating that, among other requirements, a well-deﬁned reference

standard together with a reference measurement system is available.

The “true” values of biomarkers can be determined only with such la-

borious systems. To achieve solid harmonization or standardization of

laboratory tests, several assumptions and pre-requisites must be con-

sidered:

First, the biomarker is well-deﬁned at the molecular level. This

means only a single molecular form exists that can be precisely and

accurately measured by means of chemical, biochemical, physico-che-

mical, and other methods. This is especially true for low-molecular-

weight biomarkers.

Second, the biomarker is available in pure and stable, i.e. com-

mutable, form.

Third, the biomarker is well-deﬁned on the molecular level, but the

molecular weight is much higher, e.g. peptides or proteins. In this case,

the biomarker may be unstable under physiological conditions and may

not be commutable.

Fourth, the biomarker, e.g. a protein, is well-deﬁned but post-

translationally modiﬁed; thus, the biomarker occurs in diﬀerent mole-

cular entities that are ill-deﬁned and/or the modiﬁcation, but not the

protein, is the clinically relevant biomarker.

Fifth, the biomarker is not well-deﬁned i.e. it exists in several (iso)-

forms or its structure is unknown on the molecular level. Consequently,

no primary reference material is available. In such cases, standardiza-

tion is not possible.

From these considerations, schematically summarized in Fig. 1, it is

obvious that standardization can only be achieved if an appropriate

reference material is available. Otherwise, the assay needs to be har-

monized by deﬁning a “reference material”, which can be commu-

nicated for calibration of an assay to a network of reference laboratories

and manufacturers. In spite of clear diﬀerences between harmonization

and standardization, both are used interchangeably in the literature.

A general model for a “comprehensive, coherent measurement

system” based on establishing a reference material and developing a

reference measurement procedure (RMP) was ﬁrst proposed in 1979

(Tietz, 1979). As schematically outlined in Fig. 2, such a reference

system consists of deﬁned reference material on one side and deﬁnitive

methods on the other. In essence, Tietz described a hierarchical struc-

ture of the reference measurement system including a general proce-

dure on how the system can be implemented via secondary methods

and secondary reference material in peripheral clinical laboratories.

This system is the basis for the harmonization/standardization of la-

boratory tests in clinical chemistry and it has been reﬁned and de-

scribed in ISO 17511 (ISO, 2003). This document speciﬁes how to as-

sure the metrological traceability of values assigned to calibrators and

control materials by establishing or verifying trueness of measurement.

Furthermore, the use of commutability calibrators and control material

for internal and external quality assessment is described. Therefore, the

patients' routine laboratory results can be traced to the secondary re-

ference material provided by the manufacturer. In addition to the

analytical procedures, harmonization/standardization systems also in-

clude pre- and post-analytical steps concerning the sample material,

sample stability, reporting, reference ranges and interpretation, re-

spectively.

2. Immunoassay

Immunoassays are biochemical test systems for determining the

concentrations of proteins or small molecules by using antibodies.

Immunoassays are based on the ability of antibodies to recognize their

Fig. 1. Assumptions and pre-requisites for harmonization and standardization

of biomarkers. If the analyte is well deﬁned on the molecular level, available in

stable, commutable and pure form, the harmonization and standardization is

possible; if these pre-requisites are not fulﬁlled standardization is not possible.

In this case harmonization should be sought.

Fig. 2. The traceability chain of laboratory biomarkers: from primary reference

material to patients' results.

The hierarchical structure of a comprehensive measurement system illustrating

the interrelationship between the reference material (left) and the reference

measurement procedure (right) is shown. Working groups establish primary

reference materials (PRM) and respective reference measurement procedures

(RMP) which are used by manufacturers for calibration of their assays. Via this

traceability chain, the laboratory results of patients are traceable to the primary

reference material based on ISO 17511 (ISO, 2003).

S. Hörber, et al. Biotechnology Advances 39 (2020) 107359

target by binding to speciﬁc epitopes in complex biological solutions.

However, in particular cases it is clinically important to detect the

presence of antibodies to an endogenous antigen and quantify the

concentration of this speciﬁc antibody. Here, the antibody is the bio-

marker rather than the antigen to be determined. The two principles are

schematically shown in Fig. 3.

For quantiﬁcation of biomarkers in clinical chemistry, two general

formats are used: the competitive and the non-competitive im-

munoassay. While the competitive immunoassay is based on competi-

tion between the biomarker and a ﬁxed amount of labeled antigen

binding to a limited amount of the antibody, the non-competitive im-

munoassay uses an excess of labeled speciﬁc antibody recognizing the

biomarker. Numerous formats of immunoassays have been developed.

The assay may be varied by a) the animal source of the antibody b) the

antibody makeup, be it mono- or polyclonal c) the detection system,

including the labeling of the antibody, d) the method by which bound

and unbound antigen are separated or detected without separation, and

e) the assay format, be it homo- or heterogeneous etc.

However, harmonization of immunoassays is a common problem for

all formats, because antibodies are heterogeneous by nature.

Furthermore, their aﬃnity for the antigen of interest may vary over

time, even from batch to batch. While some of the problems can be

avoided by using monoclonal antibodies, establishment of an RMP with

commutable reagents remains a challenge. The speciﬁc problems of

harmonization across immunoassays of speciﬁc biomarkers widely used

in the diagnosis, classiﬁcation, and monitoring of diabetes will be dis-

cussed below.

3. Diagnosis of diabetes mellitus

Diabetes mellitus is increasing worldwide. Since 1980, the pre-

valence rose from 108 to ~ 422 million of the worldwide population

(NCD-RisC, 2016). It is estimated that about 90% of all individuals with

diabetes mellitus have type 2 diabetes (Zheng et al., 2018). Leading

causes of morbidity and mortality in these patients are cardiovascular

events, kidney complications, blindness, stroke, and lower limb am-

putations. The pathogenesis of these vascular complications may lie in

the prediabetic phase before type 2 diabetic patients manifestation i.e.

during the insulin resistant state (Artunc et al., 2016).

By deﬁnition, diabetes is a metabolic disorder characterized by

chronic hyperglycemia. Apart from clinical aspects, laboratory test re-

sults are a major backbone for ﬁrm establishment of the diagnosis.

Detailed cut-oﬀ values have been deﬁned and are reported in national

and international guidelines (ADA, WHO and most European coun-

tries), supporting the diabetes diagnosis if one or more of the following

cut-oﬀ values are exceeded (American Diabetes Association, 2018):

- Fasting plasma glucose ≥126 mg/dL (≥7.0 mmol/L) or

- HbA1c ≥ 6.5% (≥48 mmol/mol) or

- 2 h-plasma glucose during oGTT ≥ 200 mg/dL (≥11.1 mmol/L) or

- Random plasma glucose ≥200 mg/dL (≥11.1 mmol/L)

in a patient with classic symptoms of hyperglycemia or hy-

perglycemic crisis.

Clinical practice and evaluation of the pathogenesis revealed that

diabetes mellitus is a very heterogeneous disease. Therefore, diabetes is

classiﬁed, although the diagnostic criteria from above are valid for all

classes except minor diﬀerences in cut-oﬀ values for gestational dia-

betes mellitus. According to the American Diabetes Association and

most national and international diabetes organizations, diabetes can be

classiﬁed into the following general categories (American Diabetes

Association, 2018):

- Type 1 diabetes (due to autoimmune beta cell destruction, usually

leading to absolute insulin deﬁciency)

- Type 2 diabetes (due to a progressive loss of beta cell insulin se-

cretion usually with a background of insulin resistance)

- Gestational diabetes mellitus

- Speciﬁc types of diabetes due to other causes

In most cases the patient's clinic, together with the laboratory values

of HbA1c and plasma glucose, may support the diagnosis; however,

additional biomarkers are needed to conﬁrm or exclude the diagnosis of

type 1, type 2, or other speciﬁc types of diabetes if the diagnosis is

uncertain. According to an evaluation of the survival analysis using the

data base of UK Bio-Bank, C-peptide is an important and reliable bio-

marker for distinguishing type 1, type 2, and possibly other speciﬁc

types of diabetes (Jones and Hattersley, 2013). Along those same lines,

the determination of autoantibodies may be useful for the diﬀerentia-

tion of type 1 and type 2 diabetes, as well as the proper diagnosis of

speciﬁc diabetes forms such as MODY (Maturity Onset Diabetes of the

Young).

The sequence of pathophysiological events occurring during the

development of type 1 and type 2 diabetes is associated with the oc-

currence of autoantibodies and changes in C-peptide and insulin plasma

concentrations (see Fig. 4).

While a standardization procedure for glucose measurements with

primary reference material has been achieved (Andreis et al., 2014;

Hannestad and Lundblad, 1997;ISO, 2003), the harmonization of other

important biomarkers used in clinical diabetes (e.g. HbA1c, insulin, C-

peptide, and autoantibodies to beta cell proteins) is only partly solved.

Here, we review the way forward for harmonizing the immunoassays of

these biomarkers and reporting on the current status of harmonization

and standardization of these biomarkers.

4. Glycated hemoglobin (HbA1c)

As outlined above, hemoglobin A1c (HbA1c) is one of the most

important laboratory biomarkers for the diagnosis of diabetes and for

monitoring metabolic control in patients with diabetes to reduce com-

plications. However, it took decades until the molecular nature of

HbA1c was deﬁned and the standardization could be initiated. Rahbar

and coworkers described a minor, fast hemoglobin fraction that was

increased in patients with diabetes while they were screening for

Fig. 3. Principles of immunoassays. (A) Biologically

generated antibodies may be used as speciﬁc re-

cognition elements for the determination of bio-

markers (orange). (B) Conversely, the in vivo gen-

erated human antibodies (orange) recognizing

speciﬁc endogenous human proteins (blue) may be

the biomarker of clinical interest. For detection an

anti-human IgG antibody is used (detection anti-

body).

S. Hörber, et al. Biotechnology Advances 39 (2020) 107359

hemoglobinopathies (Rahbar et al., 1969). Although the molecular

nature of this minor hemoglobin fraction was unknown, this ﬁnding

drew the attention of many diabetes centers because no other bio-

marker for assessing glycemia was known, except for acute blood glu-

cose concentration. Using a modiﬁed chromatographic method, Trivelli

et al. reported that 100 patients with diabetes showed an approximate

two-fold increase in fast hemoglobin components (glycohemoglobin)

over values found in 20 normal subjects (Trivelli et al., 1971). From

their chromatographic method it appeared that the “fast” hemoglobin

fraction (HbA1) is more than one fraction indicating heterogeneity.

4.1. Clinical utility

After these promising results, a multicenter, randomized, clinical

study was designed to determine whether an intensive treatment re-

gimen directed at maintaining blood glucose concentrations as close to

normal as possible would aﬀect the appearance or progression of early

vascular complications in type 1 diabetes patients. The results of this

long-term prospective study, “Diabetes Control and Complications

Trial” (DCCT), demonstrated that the risk for development and pro-

gression of diabetic retinopathy is closely related to the degree of gly-

cemic control as assessed by hemoglobin A1c (HbA1c) (Nathan et al.,

1993). In addition, the study provided clear evidence for a relation of

HbA1c values to mean blood glucose values. In this trial, glycated he-

moglobin was analyzed by ion exchange chromatography using “Bio-

Rex 70” as the separation column, yielding a better separation of the

HbA1 fraction into several subfractions termed HbA1a,b,c. As the

HbA1c fraction was associated with glycemia in patients, this fraction

was used to assess glycemia in further studies. The results obtained for

patients with type 1 diabetes in the DCCT were largely supported by the

outcome of the United Kingdom Prospective Diabetes Study (UKPDS)

performed in patients with type 2 diabetes (UKPDS Group, 1998). Both

studies demonstrated that HbA1c is a reliable biomarker of glycemic

control and supported the use of HbA1c values as treatment goals.

However, the widespread use of the HbA1c assay was not possible, as

the assay was not harmonized.

4.2. Deﬁnition of the biomarker

While the clinical studies were running HbA1, HbA1c and total

glycated hemoglobin (GHb) were introduced into clinical practice, al-

though the molecular nature of these hemoglobin fractions was unclear.

Step by step, the molecular identity of glycated hemoglobin was re-

vealed (Bunn et al., 1975;Holmquist and Schroeder, 1966;Koenig

et al., 1977). The formation of glycated hemoglobin was discovered in

1976 (Bunn et al., 1976). After addition of glucose to hemoglobin, a

labile Schiﬀ base is formed (aldimine), which is stabilized by Amadori

rearrangement to a stable ketoamine (Fig. 5). Kinetic analysis of the

reaction indicated that the ﬁrst reversible step was faster than the

second irreversible step (Bunn, 1981). The glycation of hemoglobin

attracted even more attention when it was discovered that other serum

proteins and particularly tissues prone to develop diabetic complica-

tions (e.g. coronary artery, aorta, lung, glomerulus, peripheral nerves)

showed increased glycation in patients with diabetes (Vogt et al.,

1982).

4.3. Harmonization and implementation

The obvious wide-spread usefulness of HbA1c in clinical practice

caused a boost of new HbA1c assays (> 30) developed by diﬀerent

companies using diﬀerent test principles including cation exchange

chromatography, aﬃnity chromatography (which determines total

glycated hemoglobin), enzymatic assays, and immunoassays (Lenters-

Westra et al., 2013;Weykamp, 2013). Not surprisingly, these non-

harmonized, non-standardized assays yielded variable results causing

confusion in the diabetes community. To address this problem the

Fig. 4. Pathological events leading to type 1 and

type 2 diabetes mellitus.

The sequence of events leading to type 1 and type 2

diabetes mellitus is schematically shown together

with relevant biomarkers. Development of type 2

diabetes is caused by constitutional factors and ge-

netic predisposition. These factors favor insulin re-

sistance which is accompanied by elevated insulin

and C-peptide concentrations as counter regulatory

mechanism in the early stage of disease progression.

Consequently, this may lead to a dysregulation of the

pancreatic beta cells characterized by an impaired

glucose tolerance. Further exacerbation ﬁnally ends

in the manifestation of type 2 diabetes due to beta

cell insuﬃciency accompanied by inadequately re-

duced insulin and C-peptide secretion and plasma

concentrations. In contrast, the development of type

1 diabetes mellitus is assumed to be associated with

genetic and environmental factors. The initial step in

the progress of type 1 diabetes is not fully under-

stood. It is presumed that activation of immune cells

leads to an autoimmune response accompanied by

the formation of high-aﬃnity autoantibodies against

antigens of the pancreatic beta cell. Subsequent beta

cell destruction leads to insulin and C-peptide deﬁ-

ciency and ﬁnally to the manifestation of type 1

diabetes mellitus.

S. Hörber, et al. Biotechnology Advances 39 (2020) 107359

“National Glycohemoglobin Standardization Program” (NGSP) was es-

tablished in 1996 (http://www.ngsp.org/). The purpose of this program

was to relate HbA1c results to those of the DCCT and UKPDS, thus

linking clinical outcomes to a laboratory test. Other countries set up

programs accordingly to promote harmonization e.g. in Japan and

Sweden (Mono-S) (Panteghini et al., 2007). However, the data showed

that HbA1c values were lower in Japan and much more so in Sweden,

using the highly eﬃcient separation column Mono-S, than the US values

(Fig. 6). This situation made clear that a worldwide standardization of

HbA1c was necessary (Miedema, 2004).

To achieve a uniform international standardization, the

International Federation of Clinical Chemistry (IFCC) established a

working group in 1995. Based on the deﬁnition of HbA1c as he-

moglobin that is irreversibly glycated at one or both N-terminal valines

of the beta chains, candidate reference methods based on peptide

mapping were suggested (Kobold et al., 1997). On the basis of this

suggestion, a reference standard procedure could be established for

HbA1c (Jeppsson et al., 2002). The principle is schematically outlined

in Fig. 7. In a ﬁrst step hemoglobin obtained from lysed erythrocytes is

speciﬁcally cleaved by the endoproteinase Glu-C, liberating the ﬁrst 6

amino acids of the beta-chain, no matter if glycated or non-glycated. In

a second step the proteolytic peptides are separated by HPLC and

quantiﬁed either by electrospray ionization mass spectrometry or by

capillary electrophoresis. HbA1c is determined as the ratio of HbA1c

and total hemoglobin. For calibration deﬁned mixtures of highly pur-

iﬁed HbA1c and HbAo were used (Finke et al., 1998). Evaluation of the

suggested reference method by an international network of reference

laboratories showed excellent precision with intra- and inter-laboratory

coeﬃcients of variation below 2.0 and 2.3%, respectively (Jeppsson

et al., 2002). These reference methods were approved by the IFCC in

July 2001. With the IFCC-RMP, which is based on the concept of me-

trological traceability, HbA1c values are assigned to whole blood panels

that serve as calibrators for manufacturers. Thus, the complete quality

chain from IFCC-RMP to the patient is created. To implement this re-

ference procedure, an IFCC laboratory network has been established

embedding the IFCC-RMP in a global network of reference laboratories

in Europe, Asia, and the US (Hoelzel et al., 2004).

Comparison of blood samples determined either by IFCC or NGSP

procedures correlated excellently, but IFCC results are consistently

lower (approximately 2% HbA1c) than NGSP based results. Both results

can be interconverted by the formula indicated in the next paragraph.

While IFCC results are accuracy-based, NGSP results are directly related

to clinical outcomes, where the master equation relates accuracy-based

HbA1c values to clinical outcomes.

The ADA, EASD, IDF, and IFCC approved statements for HbA1c

standardization are essentially as follows (Weykamp et al., 2008):

1. HbA1c test results should be standardized worldwide, including the

reference system and results reporting.

2. The IFCC-RMP for HbA1c represents the only valid anchor to im-

plement standardization of the measurement.

Fig. 5. Schematic illustration of the formation of glycated hemoglobin

(HbA1c).

In a ﬁrst reversible step, glucose is attached to the N-terminal valine of the

hemoglobin ß-chain forming a labile Schiﬀ Base, which is rearranged to a

stabile ketoamine bond yielding HbA1c. The concentration of HbA1c is pro-

portional to both the patient's erythrocyte life span and the mean glucose

concentration during that life span of approximately 120 days.

Fig. 6. Comparison of HbA1c values obtained by diﬀerent national harmoni-

zation programs.

In addition to the U.S., Japan and Sweden set up programs for harmonization of

HbA1c comparison of distributed blood samples showed that HbA1c values

were lower in Japan and much more so in Sweden, using the highly eﬃcient

separation column Mono-S, than US values (Miedema, 2004). DCM, designated

comparison method. Reprinted by permission from Springer Customer Service

Centre GmbH: Springer, Diabetologia, Towards worldwide standardization of

HbA1c determination, Miedema K., c 2004.

Fig. 7. Reference method for HbA1c.

Hemoglobin from lysed human erythrocytes is digested with endoproteinase

Glu-C, which speciﬁcally splits the peptide bond between two adjacent gluta-

mates liberating N-terminal hexapeptide, regardless of glycation state. The

peptides were separated by HPLC and quantiﬁed either by electrospray ioni-

zation mass spectrometry (ESI-MS) or by capillary electrophoresis (CE) using

UV detection at 214 nm. Both methods yielded identical results (Jeppsson et al.,

2002).

S. Hörber, et al. Biotechnology Advances 39 (2020) 107359

3. HbA1c results are to be reported worldwide in IFCC units (mmol/

mol) and derived NGSP units (%), using the IFCC-NGSP master

equation:

= ×HbA1c [mmol/mol] (HbA1c [%] 2.15) 10.929

= × +HbA1c [%] HbA1c [mmol/mol] 0.0915 2.15

These statements, acknowledged worldwide, transformed the pre-

viously chaotic situation of HbA1c measurements to a more ordered

state (Gillery, 2013;Little et al., 2011).

Before standardization, most widely used methods for determina-

tion of HbA1c including immunoassays were originally harmonized to

NGSP/DCCT and later calibrated to match the IFCC reference method.

Important to note that the harmonization and standardization is in-

dependent from the diﬀerent assay principles and methods of the

manufacturers; all use secondary reference material to calibrate the

assay. Thus the results should be comparable. Since the standardization

of all HbA1c assay principles have been extensively reviewed, e.g.

(Weykamp, 2013), we will focus on immunoassays of HbA1c in the

following section.

4.4. Immunoassay for HbA1c

Immunoassays for HbA1c were developed using the glycated N-

terminal hexapeptide as the hapten and monospeciﬁc antibodies have

been generated that speciﬁcally recognize the N-terminal glycation of

the hemoglobin beta chain, but not the non-glycated terminus or other

modiﬁcations (e.g. carbamylation) of the N-terminus. Most commer-

cially available immunoassays for HbA1c use antibodies raised against

glycated N-terminal peptides of diﬀerent sizes. Thus, depending on the

manufacturer the antibodies used in the immunoassay recognizes the

ﬁrst four or more amino acids of the glycated N-terminus of the he-

moglobin ß-chain. Several formats of immunoassays have been devel-

oped: a) the antibody reacts with HbA1c yielding soluble immune

complexes. Polyhaptens bind excess antibodies and the resulting ag-

glutinated complexes are measured using immunoturbidimetry at

340 nm (Roche, Basel, Switzerland), b) using the enzyme immune assay

principle with the sample coated to a titer plate (DAKO, Glostrup,

Denmark) and c) a synthetic polymer containing multiple hapten copies

causes agglutination of latex particles coated with an HbA1c mouse

monoclonal antibody. As HbA1c in the patients' samples compete with

the limited number of antibody-latex binding sites, agglutination is

reduced, and light scattering is decreased. This immunoassay format is

used in the point of care device DCA (Siemens Healthineers, Erlangen,

Germany). Various other immunoassays are oﬀered by diﬀerent man-

ufacturers. All assays are calibrated according to the IFCC reference

method.

4.5. Does the harmonization of HbA1c improve assay performance and

patient care/safety?

To assess the eﬀect of harmonization on the variability of glycated

hemoglobin values, the College of American Pathologists (CAP) started

proﬁciency surveys in the mid-1980s. For example in 1993, a CAP

survey revealed that 50% of the participating laboratories reported

their values as HbA1c, 21% as HbA1 and 29% as total glycated he-

moglobin (GHb) (Little et al., 2011). In 1999, 80% of the results were

reported as HbA1c, followed by 100% from 2010 to the present, in-

dicating that all laboratories are determining the same biomarker. In

parallel, the accuracy and precision improved substantially. While in

1993 reported mean values of the circulated HbA1c sample ranged from

3.6–6.5% HbA1c (target value 4.8% HbA1c) with a bias up to 1.8%

HbA1c, these values improved to 5.6–6.4% (target value 5.9% HbA1c)

with a bias up to 0.5% HbA1c in 2010. Numerous national laboratory

organizations also reported an improvement of the accuracy and pre-

cision of HbA1c over time, particularly after the National Glycated

Hemoglobin Standardization Program (NGSP) has been established. A

recent large proﬁciency testing/external quality assessment in Europe

(EurA1c) including 2166 laboratories across 17 countries and 24

manufacturers showed that the majority of the participating countries

and manufacturers met the strong IFCC criterion (European HbA1c

Trial, 2018). Between laboratory variabilities were the main con-

tributors to the overall variability, indicating that more educational

work needs to be done.

The impressive improvements of the comparability of HbA1c values

obtained by the standardization eﬀorts make laboratory values trace-

able to the clinical studies. Therefore, the suggested ﬁxed ranges for

diabetes diagnosis and the HbA1c target values for metabolic control

are valid. Strict standardization enables the deﬁnition of universal re-

ference values and clinical decision limits (Weykamp, 2013). HbA1c is

also an accepted biomarker for assessing the eﬀectiveness of newly

developed antidiabetic drugs.

5. Insulin and C-peptide

Insulin is an endocrine hormone synthesized by the beta cells of the

islets of Langerhans in the pancreas. It is an anabolic hormone com-

posed of 51 amino acids that is stored in vesicles in the beta cells and is

released by elevated glucose concentrations in the blood. It is generated

from its precursor proinsulin by limited proteolysis yielding C-peptide

and the anabolic insulin consisting of an A- and B-chain (Fig. 8

(Rubenstein et al., 1969)). Subsequently, both substrates are released in

equimolar concentrations into circulation. Following secretion, large

amounts of insulin are cleared by the liver, whereas C-peptide passes

the liver almost unaltered. As a consequence, insulin concentrations in

the peripheral blood are signiﬁcantly decreased, in contrast to C-pep-

tide concentrations showing constant blood concentrations. Insulin is

the only hormone capable of reducing blood glucose levels and is

therefore essential to maintaining glucose homeostasis in various con-

ditions. In contrast to the deﬁned biological functions of insulin, the

physiological role of the C-peptide remains elusive. In clinical practice,

C-peptide measurement is mainly used as a surrogate marker of insulin

release. C-peptide levels are more suitable for assessing insulin secre-

tion and insulin resistance because C-peptide has the following ad-

vantages compared to insulin: a) it has a longer plasma half-life in vivo,

b) it is less aﬀected by hemolysis, and c) the standardization eﬀort is

already well advanced (see below).

5.1. Clinical utility

The development and manifestation of diabetes mellitus is asso-

ciated with impairment (type 2) or loss (type 1) of beta cell function. As

outlined above, insulin and C-peptide are directly connected and re-

lated to beta cell function. They are therefore suitable for evaluating the

secretion rate and for monitoring the function of beta cells. In detail,

insulin measurements allow determination of the insulin secretion rate

or the insulin sensitivity and resistance of individuals. Type 2 diabetes

is a heterogeneous disease with diﬀerent causes. Manifestation of the

disease can occur due to decreased beta cell function, accompanied by

reduced insulin secretion, or due to increased insulin resistance, or

both. Beta cell function and insulin resistance can be assessed during an

oral glucose tolerance test measuring insulin and glucose concentra-

tions (Stumvoll et al., 2000). Insulin resistance is a key driver and an

independent risk factor for the development of the metabolic syndrome

and type 2 diabetes (Lillioja et al., 1993;Rewers et al., 2004;Weyer

et al., 2001). Thus, quantiﬁcation of insulin supports the risk assess-

ment of individuals susceptible to the development of type 2 diabetes.

For this purpose, speciﬁed calculations are conducted to quantify in-

sulin resistance, insulin sensitivity, and beta-cell function. For example,

the Homeostasis model assessment (HOMA) score is applied to de-

termine insulin resistance using the concentrations of insulin and glu-

cose (Matthews et al., 1985). The determination of C-peptide

S. Hörber, et al. Biotechnology Advances 39 (2020) 107359

concentration is also important for the diﬀerentiation between type 1

and type 2 diabetes and the classiﬁcation of diabetes subtypes (Jones

and Hattersley, 2013;Oram et al., 2014). The evaluation of hypogly-

cemia in nondiabetic individuals is another important indication for the

determination of insulin and C-peptide. An insulinoma is an uncommon

disease characterized by hyperinsulinemia due to enhanced insulin

secretion by neoplastic cells, mainly localized in the pancreas. The di-

agnosis can be made when a symptomatic patient has signiﬁcantly re-

duced blood glucose concentrations while at the same time the insulin

or C-peptide concentrations are inappropriately high (Cryer et al.,

2009).

In summary, insulin and C-peptide are useful laboratory biomarkers

for clinical and research approaches to diagnose, classify, and monitor

diabetes mellitus. It is therefore essential to use assays that are har-

monized, thereby ensuring the accurate, comparable, and reliable de-

termination of insulin and C-peptide.

5.2. Deﬁnition of the biomarker

As shown in Fig. 8, insulin and C-peptide are well deﬁned on the

molecular level. The ﬁrst insulin immunoassay, a radioimmunoassay

(RIA), was described by Yalow and Berson (Yalow and Berson, 1959)

and used polyclonal guinea-pig anti-bovine insulin antibodies. How-

ever, it could not discriminate between insulin, proinsulin, or diﬀerent

proinsulin variants. This was a particular problem for patients with type

2 diabetes or enhanced insulin resistance, who show increased proin-

sulin levels. For these patients, there was no possibility of correctly

determining insulin secretion using the insulin assays available at this

time (Temple et al., 1992). With the development of monoclonal anti-

insulin antibodies, the sensitivity and speciﬁcity of insulin im-

munoassays improved and automated assays with higher reliability and

reproducibility could be developed (Schroer et al., 1983). Cross-re-

activity of insulin with proinsulin and its variants was reduced, making

it a suitable method to evaluate insulin secretion rates in patients with

diabetes.

C-peptide was ﬁrst described as a “byproduct” of insulin biosynth-

esis (Steiner et al., 1967;Steiner and Oyer, 1967). It consists of 31

amino acids and is secreted in equimolar amounts with insulin in cir-

culation. The ﬁrst antibodies for C-peptide immunoassays were gener-

ated between 1973 and 1976, after C-peptide could be chemically

synthesized (Naithani et al., 1975;Yanaihara et al., 1975). Since then,

these immunoassays have been used in large numbers in numerous

clinical trials and C-peptide determination is now widely accepted as a

surrogate marker of insulin secretion in diabetes. Despite great eﬀorts

in the ﬁeld of immunoassays over the last several decades, comparison

analyses between diﬀerent assay systems (using both insulin and C-

peptide) and between laboratories still showed signiﬁcant diﬀerences at

that time (Wiedmeyer et al., 2007).

5.3. Harmonization and implementation

As described before, the increasing and widespread use of C-peptide

and insulin immunoassays and the continuing discordant comparison

results made it necessary to implement an international standard to

achieve harmonization of these assays. In the following section, we

focus on the eﬀorts to standardize and harmonize C-peptide and insulin

immunoassays.

C-peptide: A WHO international reference reagent (IRR) for human

C-peptide (NIBSC code 84/510), as it is required for a reference mea-

surement system (compare Fig. 1), has been available since 1977.

However, persistent substantial diﬀerences remained and made it ne-

cessary to improve C-peptide immunoassays. In 2002, the National

Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) es-

tablished a C-peptide standardization committee and organized an in-

ternational C-peptide comparison study with focus on the comparability

of C-peptide results between methods and between laboratories

(Wiedmeyer et al., 2007). This report revealed that the C-peptide de-

terminations were not suﬃciently comparable. However in another

study, using for the ﬁrst time a LC-MS based reference method for re-

calibration, signiﬁcant improvements of the coeﬃcients of variation

between methods and between laboratories could be shown (Little

et al., 2008). Furthermore in 2014, the LC-MS reference methods de-

scribed by Kinumi and colleagues (Kinumi et al., 2014) and by

Stoyanov and colleagues (Stoyanov et al., 2013) were successfully listed

in the Joint Committee for Traceability in Laboratory Medicine

(JCTLM) database, which is necessary for the re-calibration of C-pep-

tide assays by the manufacturers. In addition, pooled serum samples

have been established as secondary reference materials. However, the

manufacturers still need to re-calibrate the assays in order to see the full

impact on the harmonization process. In 2017, 30 years after the ﬁrst C-

peptide standard had been established and which is now exhausted, the

ﬁrst international standard was prepared and evaluated (NIBSC code

13/146) (Moore et al., 2017). The WHO Expert Committee on Biolo-

gical Standardization (ECBS) has approved this material for human C-

Fig. 8. Schematic illustration of insulin synthesis by proinsulin cleavage.

After formation of proinsulin in the endoplasmic reticulum, proinsulin is packed in granules and split into insulin and C-peptide by limited proteolysis (arrows). Upon

stimulation (e.g. by glucose), both peptides are rapidly secreted into circulation at an equimolar ratio. As insulin is rapidly degraded by the liver, insulin con-

centrations in the peripheral blood are markedly reduced compared to C-peptide concentrations.

S. Hörber, et al. Biotechnology Advances 39 (2020) 107359

peptide assays. However, the NIBSC material was produced for the

calibration of C-peptide immunoassays and not as primary reference

material in the ID-MS reference measurement system. It is therefore not

appropriate to standardize C-peptide assays. In addition to NIBSC 13/

146, another reference material is available. The National Metrology

Institute of Japan (NMIJ) provides a C-peptide certiﬁed reference ma-

terial (NMIJ CRM 6901-b; (Kinumi et al., 2012)), which is listed in the

JCTLM database and is suitable for the ID-MS reference management

system (Little et al., 2017a;Little et al., 2017b). Therefore, according to

the minutes of the C-peptide standardization committee, the NMIJ

certiﬁed reference material 6901-b should be used as primary reference

material for the traceability chain. This procedure was well described in

a recent report by Little and colleagues proposing a traceability chain,

based on the in vitro diagnostic medical devices ISO 17511:2003 (ISO,

2003), for the implementation of a reference measurement system for

C-peptide (Little et al., 2017b). Despite this tremendous success, there

are competing ongoing eﬀorts in parallel among the participating la-

boratories in diﬀerent countries. Increased cooperation among these

laboratories, together with the outlined scheme, can make this long-

term project a real success.

Insulin: Despite its limited indications in clinical practice, accurate

and reliable determination of insulin concentrations is crucial for re-

search studies and special clinical applications, in particular for the

determination of insulin resistance as part of multicenter studies. The

ﬁrst human insulin IRP (NIBSC code 66/304) was established in 1974.

Prior to that reference, each laboratory prepared their own insulin

standards producing variable assay results due to the diverse im-

munogenic and biologic properties of the applied antibodies. Several

decades later, a task force from the ADA on the standardization of in-

sulin assays investigated the analytical performance of insulin assays

and reported signiﬁcantly diﬀerent values across laboratories and

methods (Robbins et al., 1996). These diﬀerences were also reported in

a later ADA Workgroup study from 2004 to 2006 (Marcovina et al.,

2007). To improve these issues the ADA working group recommended:

a) the preparation of a new reference material, b) the validation of the

preparation and c) the development of a reference method. At that time

there had been no approved reference method for the determination of

insulin. In the following years, an isotope dilution-liquid chromato-

graphy/tandem mass spectrometry (ID-LC/MS) procedure was reported

by Miller and colleagues leading to a slightly improved comparability

between methods (Miller et al., 2009). However, at the present time,

there is no reference material or reference method listed in the JCTLM

database for insulin. These eﬀorts are underway by the IFCC Working

Group on Standardization of Insulin Assays (SWG-IA). In summary,

there is clearly an ongoing need for improvement in standardization

and harmonization of insulin assay results. In contrast to the processes

that have been reached for C-peptide assays, standardization and har-

monization of insulin assays still requires much eﬀort. The proposed

traceability chain by Little and colleagues for the implementation of an

RMP to C-peptide assays can therefore be assumed as a model for in-

sulin standardization (Little et al., 2017b).

Regarding both biomarkers, an external quality assessment is useful

in comparing measurement results between laboratories and in de-

monstrating the success of the harmonization process. Results of C-

peptide measurements included in the German external quality as-

sessment study show high agreement between methods and labora-

tories, suggesting eﬀectiveness of the previous eﬀorts (RfB, 2019). In

contrast, insulin external quality assessment results showed signiﬁcant

and relevant diﬀerences for the same reference material between

methods and laboratories (INSTAND e. V., 2019). It is therefore im-

portant to continue eﬀorts in the harmonization and implementation

process of insulin to guarantee reliable, comparable, and reproducible

measurement results. In 2019, the College of American Pathologists will

begin an accuracy-based program including insulin and C-peptide to

assess the diﬀerences among methods for each analyte. This may help

to evaluate the current progress of the harmonization process.

5.4. Does the harmonization of insulin and C-peptide improve patient care

and safety?

In the past decades substantially improvements have been made in

the standardization of immunoassays for C-peptide and insulin. Fig. 9

shows important steps towards a standardization of these im-

munoassays. However, this process is still ongoing and especially in

case of insulin immunoassays further eﬀorts are still needed. Standar-

dization is crucial to compare results from diﬀerent research studies

and clinical trials. Although insulin is the biological active hormone, its

indications in clinical practice are limited. Determination and inter-

pretation of insulin resistance and sensitivity is still restricted to re-

search studies. Furthermore preanalytical issues for insulin determina-

tion, such as a shorter half-life compared to C-peptide and a higher

aﬀection by hemolysis limits its widespread use. The establishment and

implementation of traceable reference intervals for insulin is also

challenging (Larsen et al., 2017). However, cutoﬀ values of insulin

Fig. 9. Timeline of the standardization and harmonization process of C-peptide and insulin immunoassays. Important landmarks in the history of C-peptide (orange)

and insulin (green), starting with the discovery or ﬁrst description of both parameters and the subsequent steps towards international reference materials and

reference methods. Details of these eﬀorts are described in the text. (For interpretation of the references to colour in this ﬁgure legend, the reader is referred to the

web version of this article.)

S. Hörber, et al. Biotechnology Advances 39 (2020) 107359

concentrations and insulin sensitivity are needed to implement insulin

determination in routine clinical practice (Staten et al., 2010). In con-

trast, C-peptide is recommended and widely used for diabetes classiﬁ-

cation and as a surrogate marker for insulin secretion (Palmer et al.,

2004), especially for insulin-treated patients (Jones and Hattersley,

2013). C-peptide exhibits a longer half-life in vivo and the standardi-

zation and harmonization process is far advanced in comparison to

insulin (Bonser and Garcia-Webb, 1984;Little et al., 2017b). This en-

ables reliable and correct decisions concerning diabetes diagnosis,

distinction between diabetes mellitus type 1 and 2 (Leighton et al.,

2017) and therapy, thereby directly increasing the patient's safety.

Furthermore, reliable comparison of C-peptide is also essential for the

recently introduced novel classiﬁcation of diabetic subgroups suggested

by a Scandinavian consortium (Ahlqvist et al., 2018). This classiﬁcation

is based on both anthropomorphic data and on biomarkers in parti-

cular, including HbA1c, beta cell autoantibody, GAD, and C-peptide to

calculate HOMA indices for assessing insulin secretion and insulin re-

sistance. This novel classiﬁcation leads to more distinct classiﬁcation of

type 2 diabetes indicting e.g. if the diabetic patient is more prone to

diabetic retinopathy or nephropathy. Since this novel classiﬁcation is

mainly based on laboratory biomarkers wrong clinical decisions may be

made if the respective biomarkers are not harmonized or standardized.

6. Autoantibodies to beta cell proteins

Autoantibodies to antigens of the pancreatic islet beta cells are a

hallmark of type 1 diabetes pathogenesis (Ziegler and Nepom, 2010).

They precede diabetes onset in > 95% of children who develop disease

and are frequent in insulin-requiring diabetes in adults. Bottazzo and

colleagues ﬁrst identiﬁed islet cell antibodies (ICA) in sera of type 1

diabetic patients who had polyendocrine autoimmune deﬁciencies as-

sociated with organ-speciﬁc autoimmunity (Bottazzo et al., 1974).

These antibodies were detected by indirect immunoﬂuorescence tested

on sections of fresh frozen human pancreas bound to cytoplasmic an-

tigens. ICA were subsequently found at high frequency in children with

newly diagnosed type 1 diabetes, and it was recognized that these an-

tibodies are often present in the serum from non-diabetic relatives of

individuals with type 1 diabetes indicating a prediabetic period with an

autoimmune serology (Gorsuch et al., 1981). ICA are heterogeneous

between individuals with respect to their molecular targets, thus tests

are diﬃcult to standardize. Today, ICA testing is being superseded by

testing for autoantibodies against biochemically deﬁned islet antigens.

While a variety of molecules have been reported (Lampasona and

Liberati, 2016), only the following have been conﬁrmed as major tar-

gets of autoantibodies in type 1 diabetes.

6.1. Insulin autoantibodies

It had long been recognized that treatment with exogenous forms of

insulin could induce antibodies directed against insulin peptides when

in 1983, Palmer and colleagues ﬁrst described insulin autoantibodies

(IAA) in type 1 diabetic patients before they received insulin therapy

(Palmer et al., 1983). Insulin and proinsulin are early targets of islet

autoimmunity, and IAA are frequent (> 70%) in childhood diabetes

and less prominent markers of type 1 diabetes with clinical onset after

adolescence. The ﬁrst occurrence of IAA is marked at around 1–2 years

of age (Krischer et al., 2015;Parikka et al., 2012;Ziegler et al., 2012),

and there are distinct immunization patterns with respect to the aﬃnity

and epitope speciﬁcities of IAA (Achenbach et al., 2004). In general, the

high-aﬃnity IAA are more predictive for type 1 diabetes and share

certain characteristics, including association with HLA DRB1*04, sub-

sequent progression to autoantibodies against multiple beta cell anti-

gens, binding to human insulin A chain residues 8–13, and binding to

proinsulin. In contrast, children with IAA of lower aﬃnity rarely pro-

gress to type 1 diabetes (Achenbach et al., 2010).

6.2. GAD autoantibodies

In 1990, Baekkeskov and colleagues identiﬁed a 65-kDa isoform of

glutamate decarboxylase (GAD65) as major type 1 diabetes autoantigen

(Baekkeskov et al., 1990). Autoantibodies to GAD (GADA) are frequent

(> 70%) in type 1 diabetes seen at all ages, and the typical marker of

adult-onset type 1 diabetes including the so-called latent autoimmune

diabetes in adults (LADA) (Tuomi et al., 1993). GADA are also detected

in neurological disorders, especially in stiﬀ man syndrome and in

conditions unrelated to diabetes (Baekkeskov et al., 1990). Aﬃnity and

epitope speciﬁcity of GADA can stratify the progression to type 1 dia-

betes (Mayr et al., 2007;Williams et al., 2015) and predict insulin

therapy in individuals with adult-onset diabetes (Achenbach et al.,

2018;Krause et al., 2014).

6.3. IA-2 and IA-2β autoantibodies

In 1994, Rabin and colleagues recognized islet cell antigen 512

(ICA512) as diabetes-speciﬁc autoantigen related to protein tyrosine

phosphatases (Rabin et al., 1994). Before, two tryptic digest fragments

of islet antigens had been characterized from individuals with type 1

diabetes (Christie et al., 1993). A 40-kDa fragment from the in-

tracellular portion of a tyrosine phosphatase-like protein (PTPRN gene)

is now referred to as IA-2ic or ICA512ic (Payton et al., 1995). Auto-

antibodies to IA-2 (IA-2A) are highly speciﬁc and predictive for type 1

diabetes (Decochez et al., 2002), and frequently detected (> 70%) at

clinical onset. They usually occur together with other beta cell auto-

antibodies. The other 37-kDa tryptic fragment was identiﬁed as the IA-

2-related protein IA-2β or phogrin (Hawkes et al., 1996;Lu et al.,

1996). Since almost all individuals with autoantibodies against IA-2β

also have IA-2A, IA-2β autoantibodies are not commonly used as a ﬁrst

line test, although they can identify individuals at high risk of disease

progression (Achenbach et al., 2008;De Grijse et al., 2010).

6.4. ZnT8 autoantibodies

In 2007, Hutton and colleagues identiﬁed zinc transporter-8 (ZnT8)

as type 1 diabetes autoantigen by screening for highly expressed islet

beta cell-speciﬁc molecules (Wenzlau et al., 2007). Autoantibodies to

ZnT8 (ZnT8A) are found in about 70% of patients with type 1 diabetes

and improve prediction of disease. As for IA-2A; they usually occur

together with other beta cell autoantibodies. A principle epitope tar-

geted by ZnT8A is inﬂuenced by the single amino acid at position 325

encoded as arginine, tryptophan, or glutamine by diﬀerent polymorphic

variants of the ZnT8-encoding gene SLC30A8 (Wenzlau et al., 2008).

Autoimmunity against the COOH-terminal region of ZnT8 is highly

prognostic for progression to clinical diabetes (Achenbach et al., 2009;

Andersson et al., 2011;De Grijse et al., 2010).

6.5. Clinical utility

Beta cell autoantibodies circulate in blood, signalling an active and

disease-speciﬁc B lymphocyte response, they can be detected very re-

producibly and are therefore excellent and available immune bio-

markers for type 1 diabetes. In individuals with clinically manifest

diabetes, these autoantibodies are used for disease classiﬁcation, dis-

tinguishing between autoimmune (type 1) and non-autoimmune

(mainly type 2) diabetes, and for prediction of the need for insulin

treatment (Bingley, 2010). Traditionally clinicians have diﬀerentiated

between type 1 and type 2 diabetes based on phenotypic characteristics,

including age at onset, abruptness of onset of hyperglycemia, ketosis-

proneness, degree of obesity, prevalence of other autoimmune disease,

and the need for insulin replacement therapy. The presence or absence

of beta cell autoantibodies in the blood is an important additional cri-

terion if the diagnosis is not clear by clinical symptoms or other la-

boratory biomarkers. In particular, a subset of patients with adult-onset

S. Hörber, et al. Biotechnology Advances 39 (2020) 107359

diabetes present clinically without ketoacidosis and weight loss, require

no insulin therapy initially but develop insulin dependence more ra-

pidly than typical type 2 diabetic patients, and autoantibodies (mainly

GADA) are detectable. This slowly developing form of autoimmune

type 1 diabetes, also called LADA, found in people over 30 years old, is

often misdiagnosed and treated as type 2 diabetes (Leslie et al., 2016).

Thus the diﬀerent etiology of diabetes aﬀects the clinical phenotype of

patients and can be uncovered by autoantibody testing, to the beneﬁt of

therapy.

Moreover, beta cell autoantibodies are excellent biomarkers for

identifying early immunization to beta cell antigens and monitoring

progression of islet autoimmunity in preclinical diabetes. Although beta

cell autoantibodies are not considered eﬀectors of beta cell damage,

they are used for identiﬁcation of individuals at risk for developing type

1 diabetes, and as end-points in observational and intervention studies

(Bonifacio, 2015;Ziegler et al., 2013). Clinical trials are currently in

progress to identify ways to prevent or reverse the autoimmunity of

type 1 diabetes (Battaglia et al., 2017). These trials commonly use

autoantibody positivity as an inclusion criterion for participants. More

recently, beta cell autoantibodies are used for diagnosing asymptomatic

early stage type 1 diabetes (Insel et al., 2015;Raab et al., 2016).

However, particularly single positive autoantibody results require

critical interpretation since 1–7% of individuals without diabetes and

the same number of individuals with type 2 diabetes have false positive

(i.e. not type 1 diabetes-related, mainly low-aﬃnity) autoantibodies

depending on the cut-oﬀ for positivity, and the assay method used

(Thomas et al., 2018). It is therefore obvious that the assays for the

determination of beta cell autoantibodies need to be harmonized and

improved, particularly in their speciﬁcity for type 1 diabetes. The latter

could be achieved by modifying the target antigen to reduce unspeciﬁc

binding sites. For example, the presence of autoantibodies to N-term-

inally truncated GAD65 (consisting of amino acids 96–585) is asso-

ciated with the clinical phenotype of autoimmune type 1 diabetes and

predicts insulin therapy in adult-onset diabetes, whereas restricted

antibody binding to N-terminal GAD65 epitopes is associated with si-

milar clinical phenotype to GADA-negative, type 2 diabetic individuals

(Achenbach et al., 2018).

6.6. Deﬁnition of the biomarker

Unlike other biomarker immunoassays, the assays for detection of

beta cell autoantibodies are not using antibodies for measuring the

biomarker (i.e. the speciﬁc autoantibody) but rather determining the

quantity of autoantibodies against speciﬁc beta cell proteins. Since the

molecular nature of the main target antigens in type 1 diabetes is

known, primary reference material for immunoassays can be deﬁned,

and human insulin, GAD, IA-2, and ZnT8 protein can be prepared by

recombinant procedures. On the other hand, the biomarker auto-

antibodies are less well deﬁned since a) the autoantibodies present in a

person may shift between immunoglobulin isotypes and subtypes and

target epitopes over time and b) the epitope recognition vary sub-

stantially between individuals. This biological variability makes the

molecular deﬁnition and, therefore, standardization of a unique auto-

antibody-immunoglobulin impossible. Another challenge for reducing

the variability of assay results is that most epitopes recognized by beta

cell autoantibodies are conformational epitopes requiring the correct

protein structure. Thus, single epitope assays are hard to achieve.

Today, most research laboratories use various forms of non-com-

mercial ﬂuid phase radio-binding assays (RBAs) for detecting auto-

antibodies. Some commercial ELISAs now perform as well or better

than RBAs in detecting GADA (Torn et al., 2008). While IAA are con-

sidered important autoantibodies for predicting type 1 diabetes in

children, current assays produce highly variable results, and only a few

clinical laboratories consistently perform RBAs with high sensitivity

and speciﬁcity for the disease (Schlosser et al., 2010). Recently, high-

performing and low serum volume-requiring IAA assays have been

developed based on luciferase immunoprecipitation system (LIPS) and

electrochemiluminescence (ECL) technology, These assays are suitable

for large-scale capillary blood screening of young children (Liberati

et al., 2018;Yu et al., 2013).

6.7. Harmonization and implementation

Harmonizing the assays for the detection of beta cell autoantibodies

is challenging but essential in order to obtain results that are compar-

able among laboratories, particularly for multicenter studies. This in

mind, the ﬁrst standardization workshops were established with focus

on cytoplasmic islet cell antibodies (Boitard et al., 1988;Bonifacio

et al., 1990). Later on, the workshop also referred to other beta cell

autoantibodies; the aim was to establish reference materials and to

improve laboratory methods measuring diabetes-associated auto-

antibodies (Verge et al., 1998). The WHO adopted a serum reference

standard for GADA and IA-2A assays, and these standards have assigned

values of 250 units/mL for each autoantibody (Mire-Sluis et al., 2000).

An international reference standard for IAA and ZnT8A does not yet

exist.

Another step forward to harmonization of beta cell autoantibody

assays was promoted by the National Institute of Diabetes and Digestive

and Kidney Diseases (NIDDK). To this end, an Islet Autoantibody

Harmonization Committee was established to enable comparison of

autoantibodies between diﬀerent laboratories included in multicenter

studies (Bonifacio et al., 2010). A NIDDK working calibrator was pre-

pared and introduced, which was made from a mixture of numerous

sera to reduce bias. This is in contrast to the WHO reference material,

which was made out of a single serum preparation. Calibration was

done against the WHO reference material to ensure that units obtained

using the NIDDK calibrator, i.e. NIDDK units, are comparable to WHO

units. The harmonized assays showed higher comparability and dis-

agreements in total values could be reduced.

In 2000, the Immunology of Diabetes Society (IDS) and the U.S.

Centers for Disease Control and Prevention (CDC) established the

Diabetes Antibody Standardization Program (DASP) to improve com-

parability and to act as an outlet mechanism to evaluate new auto-

antigens and test methodologies (Bingley et al., 2003). Since 2012, this

program has been continued as Islet Autoantibody Standardization

Program (IASP), funded by the U.S. National Institutes of Health (NIH),

supervised by the IDS and organized by the TrialNet Islet Cell Auto-

antibody Core Laboratory at the University of Florida. The goal of

DASP/IASP is to improve detection and diagnosis of autoimmune dia-

betes by: a) providing technical support, training, and information

about the best methods; b) providing proﬁciency testing to evaluate

laboratory performance; c) supporting development of highly sensitive

and speciﬁc measurement technologies; and d) developing reference

materials. Since its inception, every 18 months DASP/IASP has con-

ducted international workshops in which laboratories worldwide assay

blinded samples from 50 patients with new-onset type 1 diabetes and

up to 100 controls. This format provides an evaluation of the sensitivity

and speciﬁcity of each test and enables DASP/IASP to assess im-

plementation of assay methods and to document any improvement in

performance. Among the major accomplishments to date, DASP/IASP

has demonstrated that assays in which antibody binding occurs at the

interface of a solid surface coated with antigen, like direct ELISAs, do

not allow for sensitive and speciﬁc detection of beta cell autoantibodies,

in contrast to assay formats in which the interaction of antibodies with

antigen happens completely or partially in ﬂuid phase such as RBA, and

bridge-ELISA (Lampasona and Liberati, 2016). Other DASP/IASP ac-

tivities include the evaluation of the stability of the WHO GADA and IA-

2 autoantibody standard; the evaluation of standard method protocols

for GADA and IA-2A, and the validation of new autoantibody markers

(Achenbach et al., 2007;Bingley et al., 2003;Lampasona et al., 2011;

Williams et al., 2015). As a general recommendation, before using an

autoantibody assay for type 1 diabetes risk assessment and diagnostic

S. Hörber, et al. Biotechnology Advances 39 (2020) 107359

purpose, its performance in the IDS-based international workshops

should be ascertained.

6.8. Does the harmonization of diabetic autoantibodies improve patient care

and safety?

Exact and reproducible autoantibody measurement is a pre-requisite

for accurate prediction of type 1 diabetes and diagnostic autoantibody

testing in patients. The development of autoantibodies against multiple

beta cell antigens has long been recognized as a critical step in patho-

genesis, associated with a signiﬁcantly higher diabetes risk than the

presence of just a single autoantibody (Bingley et al., 1994;Verge et al.,

1996). More recently, it became evident that children who have de-

veloped two or more of the beta cell autoantibody types almost in-

evitably progress to clinically symptomatic diabetes (Ziegler et al.,

2013). These ﬁndings have led to a new staging of type 1 diabetes,

which classiﬁes the presence of advanced beta cell autoimmunity

(multiple autoantibodies) in individuals without diabetic symptoms as

an early stage of disease (Insel et al., 2015). Since 2015, the Fr1da study

in Bavaria, Germany uses capillary blood beta cell autoantibody

screening for identifying asymptomatic early stage type 1 diabetes in a

total of 100,000 children aged 2–5 years (Raab et al., 2016). This study

aims to assess whether early staging of type 1 diabetes: a) is feasible at a

population-based level; b) prevents severe metabolic decompensation

observed at the clinical manifestation of type 1 diabetes; and c) reduces

psychological distress through preventive teaching and care. At a time

when there is an eﬀective treatment available to reintroduce tolerance

in autoimmune diabetes, high-quality, high-throughput, and harmo-

nized autoantibody tests will become essential for identifying in-

dividuals who can beneﬁt from such treatment. Today, the presence of

beta cell autoantibodies is already used as a criterion for recruiting

individuals into prevention studies, or as study end point (Battaglia

et al., 2017;Bonifacio, 2015). Furthermore, a harmonized protocol is

already implemented for measuring autoantibody responses in large

multicenter prospective natural history studies of type 1 diabetes, such

as the The Environmental Determinants of Diabetes in the Young

(TEDDY) study (Krischer et al., 2015).

7. Critique and outlook

The general characteristics of important biomarkers in diabetology

discussed above are summarized in Table 1. After the discovery of

HbA1c in 1969 and the recognition of its potential clinical use as bio-

marker for diagnosis of diabetes and metabolic monitoring, numerous

assays based on various diﬀerent principles have been introduced.

However, the diﬀerent assays yielded variable results causing wide-

spread confusion among the users. It took > 30 years until a worldwide

accepted standardization was achieved. Even worse, although insulin

was discovered in 1921, standardization of insulin immunoassays is still

in process after its ﬁrst description a century ago and recognition of its

central physiological role in metabolism. Accordingly, it took > 50

years following the discovery of C-peptide in 1967 until the standar-

dization procedure for C-peptide immunoassays has been proposed in

2017. The situation concerning autoantibodies (detected in 1974) is

diﬀerent since autoantibodies are highly variable in individual patients

and may also vary over time. Here, after a long initiation period in-

ternational eﬀorts have achieved substantial improvement in harmo-

nization over the last decades. Taken together, the described history of

harmonization of these important biomarkers in diabetology teaches us

to initiate international harmonization eﬀorts immediately after the

clinical use of newly discovered biomarkers has been demonstrated, e.g.

by establishing international working groups.

The importance of proper determination of the discussed bio-

markers in diabetology is obvious considering the classiﬁcation of

diabetes subtypes. As outlined in Fig. 10 plasma concentrations of in-

sulin or C-peptide together with the occurrence of autoantibodies are

Table 1

General characteristics of immunoassays as biomarkers in diabetology.

Biomarker Discovery/ﬁrst

descripton

Formation process – physiological role Clinical utility Measurement methods

(most used)

Status of harmonization and standardization

HbA1c 1969 •metabolic byproduct

•non-enzymatic addition of glucose to N-terminal

valine of the hemoglobin β-chain

•diagnosis of DM

•therapy monitoring

•long-term glycemic control

•correlation with long-term diabetic

complications

Immunoassay

HPLC •higher-order reference material and reference

measurement methods listed in the JCTLM database

Insulin 1921 •endogenous hormone

•synthesized and generated from proinsulin in the

pancreatic beta-cells

•secreted upon stimulation

•evaluation of beta-cell function/insulin reserve

•during a fasting test

•determination of insulin sensitivity and

resistance

Immunoassay •JCTLM listed reference material and reference methods

not available

•Standardization working group established

C-peptide 1967 •byproduct from limited proteolysis of proinsulin

•secreted together with insulin •diﬀerential diagnosis of DM

•during a fasting test

•determination of insulin sensitivity and

resistance

Immunoassay •higher-order reference material and reference

measurement methods listed in the JCTLM database

Autoantibodies 1974 •autoimmune pathogenesis

•promoting the autoimmune response against beta

cell antigens

•antibodies with high biological variability

•diﬀerential diagnosis of DM

•prediction of the need for insulin treatment

•identiﬁcation of individuals at risk for

developing type 1 DM

•diagnosing asymptomatic early type 1 DM

Immunoassay •JCTLM listed reference material and reference methods

not available

•WHO reference material for GADA and IA-2A available

•NIDDK working calibrator for GADA and IA-2A available

HbA1c, Insulin, C-peptide and diabetes associated autoantibodies are laboratory parameters supporting the diagnosis, prognosis and classiﬁcation of diabetes mellitus (DM).

S. Hörber, et al. Biotechnology Advances 39 (2020) 107359

essential for the classiﬁcation of type 1 and type 2 diabetes if the

clinical diagnosis is uncertain. Furthermore, the illustrated clinical al-

gorithm may help to indicate if a speciﬁc, less common type of diabetes

may be present in an individual patient. Following this scheme, la-

boratory biomarkers need to be standardized and harmonized to avoid

misclassiﬁcation and in consequence possibly wrong clinical decisions.

The transfer of these theoretical considerations into routine la-

boratory measurements is not without problems since diﬀerent manu-

facturers use diﬀerent assay principles. This is particularly true for the

measurement of HbA1c. The oﬀered assays may be based on chroma-

tography, electrophoresis, aﬃnity to boronate or on speciﬁc antibodies.

According to the survey 2018b of the College Of American Pathologists

(http://www.ngsp.org/capdata.asp) immunoassays are the most widely

used assays (e.g. Roche, Basel, Switzerland and Siemens Healthineers,

Erlangen, Germany) followed by ion chromatography using HPLC (e.g.

Bio-Rad, Hercules, USA and Tosoh, Tokio, Japan). Many manufacturers

of immunoassays for insulin and C-peptide are on the market which is

quite diverse for these biomarkers and therefore it is not clear which

assay is the most widely used worldwide. For the determination of

autoantibodies to GAD, IA-2 and ZnT8 the solid-phase/liquid-phase

bridge ELISA provided by RSR Ltd. (Cardiﬀ, United Kingdom) is used by

most laboratories. Other manufacturers produce immunoassays based

on the antigens used in these ELISAs. Taken together this diversity

emphasizes the need not only for harmonization of the assays of bio-

markers but also the need for implementation of the whole standardi-

zation procedure worldwide.

8. Conclusions

Harmonization of laboratory tests is a pre-requisite for the com-

parability of biomarkers contributing to the diagnosis, classiﬁcation,

and monitoring of individuals. The increasing use of clinical practice

guideline based on outcome studies requires biomarkers to be harmo-

nized or, if possible, standardized. Besides glucose, HbA1c is the major

laboratory biomarker supporting the diagnosis of diabetes mellitus

while insulin and C-peptide and autoantibodies against beta cell epi-

topes are important biomarkers for the classiﬁcation of diabetes sub-

types. HbA1c has been standardized worldwide and standardization of

C-peptide is close to be ﬁnalized but standardization procedure for in-

sulin is still in process. Most important for the prediction of type 1

diabetes in infants and young individuals worldwide the harmonization

of autoantibodies against beta cell epitopes is well underway. Further

progress in harmonization and standardization will increase the com-

parability of laboratory tests and therefore support the reliability of

biomarkers for clinical decisions, ﬁnally improving patient care and

safety.

Acknowledgements

We thank I. Rettig for critical reading of the manuscript.

Funding

The present study was supported in part by a grant (01GI0925) from

the German Federal Ministry of Education and Research to the German

Center for Diabetes Research (DZD e.V.)

Conﬂict of interest

No conﬂicts of interest were reported by S.H., P.A., E.S. and A.P.

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Apr 2018
DIABETOLOGIA

Aims/hypothesis: Adult-onset type 1 diabetes, in which the 65 kDa isoform of GAD (GAD65) is a major autoantigen, has a broad clinical phenotype encompassing variable need for insulin therapy. This study aimed to evaluate whether autoantibodies against N-terminally truncated GAD65 more closely defined a type 1 diabetes phenotype associated with insulin therapy. Methods: Of 1114 participants with adult-onset diabetes from the Action LADA (latent autoimmune diabetes in adults) study with sufficient sera, we selected those designated type 1 (n = 511) or type 2 diabetes (n = 603) and retested the samples in radiobinding assays for human full-length GAD65 autoantibodies (f-GADA) and N-terminally truncated (amino acids 96-585) GAD65 autoantibodies (t-GADA). Individuals' clinical phenotypes were analysed according to antibody binding patterns. Results: Overall, 478 individuals were f-GADA-positive, 431 were t-GADA-positive and 628 were negative in both assays. Risk of insulin treatment was augmented in t-GADA-positive individuals (OR 4.69 [95% CI 3.57, 6.17]) compared with f-GADA-positive individuals (OR 3.86 [95% CI 2.95, 5.06]), irrespective of diabetes duration. Of 55 individuals who were f-GADA-positive but t-GADA-negative, i.e. with antibody binding restricted to the N-terminus of GAD65, the phenotype was similar to type 2 diabetes with low risk of progression to insulin treatment. Compared with these individuals with N-terminal GAD65-restricted GADA, t-GADA-positive individuals were younger at diagnosis (p = 0.005), leaner (p < 0.0001) and more often had multiple diabetes-associated autoantibodies (28.3% vs 7.3%; p = 0.0005). Conclusions/interpretation: In individuals with adult-onset diabetes, presence of N-terminally truncated GAD65 autoantibodies is associated with the clinical phenotype of autoimmune type 1 diabetes and predicts insulin therapy.

Global aetiology and epidemiology of type 2 diabetes mellitus and its complications

Article

Full-text available

Dec 2017
NAT REV ENDOCRINOL

Globally, the number of people with diabetes mellitus has quadrupled in the past three decades, and diabetes mellitus is the ninth major cause of death. About 1 in 11 adults worldwide now have diabetes mellitus, 90% of whom have type 2 diabetes mellitus (T2DM). Asia is a major area of the rapidly emerging T2DM global epidemic, with China and India the top two epicentres. Although genetic predisposition partly determines individual susceptibility to T2DM, an unhealthy diet and a sedentary lifestyle are important drivers of the current global epidemic; early developmental factors (such as intrauterine exposures) also have a role in susceptibility to T2DM later in life. Many cases of T2DM could be prevented with lifestyle changes, including maintaining a healthy body weight, consuming a healthy diet, staying physically active, not smoking and drinking alcohol in moderation. Most patients with T2DM have at least one complication, and cardiovascular complications are the leading cause of morbidity and mortality in these patients. This Review provides an updated view of the global epidemiology of T2DM, as well as dietary, lifestyle and other risk factors for T2DM and its complications.

Frequency and phenotype of type 1 diabetes in the first six decades of life: A cross-sectional, genetically stratified survival analysis from UK Biobank

Article

Full-text available

Nov 2017

Background: Type 1 diabetes is typically considered a disease of children and young adults. Genetic susceptibility to young-onset type 1 diabetes is well defined and does not predispose to type 2 diabetes. It is not known how frequently genetic susceptibility to type 1 diabetes leads to a diagnosis of diabetes after age 30 years. We aimed to investigate the frequency and phenotype of type 1 diabetes resulting from high genetic susceptibility in the first six decades of life. Methods: In this cross-sectional analysis, we used a type 1 diabetes genetic risk score based on 29 common variants to identify individuals of white European descent in UK Biobank in the half of the population with high or low genetic susceptibility to type 1 diabetes. We used Kaplan-Meier analysis to evaluate the number of cases of diabetes in both groups in the first six decades of life. We genetically defined type 1 diabetes as the additional cases of diabetes that occurred in the high genetic susceptibility group compared with the low genetic susceptibility group. All remaining cases were defined as type 2 diabetes. We assessed the clinical characteristics of the groups with genetically defined type 1 or type 2 diabetes. Findings: 13 250 (3·5%) of 379 511 white European individuals in UK Biobank had developed diabetes in the first six decades of life. 1286 more cases of diabetes were in the half of the population with high genetic susceptibility to type 1 diabetes than in the half of the population with low genetic susceptibility. These genetically defined cases of type 1 diabetes were distributed across all ages of diagnosis; 537 (42%) were in individuals diagnosed when aged 31-60 years, representing 4% (537/12 233) of all diabetes cases diagnosed after age 30 years. The clinical characteristics of the group diagnosed with type 1 diabetes when aged 31-60 years were similar to the clinical characteristics of the group diagnosed with type 1 diabetes when aged 30 years or younger. For individuals diagnosed with diabetes when aged 31-60 years, the clinical characteristics of type 1 diabetes differed from those of type 2 diabetes: they had a lower BMI (27·4 kg/m2 [95% CI 26·7-28·0] vs 32·4 kg/m2 [32·2-32·5]; p<0·0001), were more likely to use insulin in the first year after diagnosis (89% [476/537] vs 6% [648/11 696]; p<0·0001), and were more likely to have diabetic ketoacidosis (11% [61/537] vs 0·3% [30/11 696]; p<0·0001). Interpretation: Genetic susceptibility to type 1 diabetes results in non-obesity-related, insulin-dependent diabetes, which presents throughout the first six decades of life. Our results highlight the difficulty of identifying type 1 diabetes after age 30 years because of the increasing background prevalence of type 2 diabetes. Failure to diagnose late-onset type 1 diabetes can have serious consequences because these patients rapidly develop insulin dependency. Funding: Wellcome Trust and Diabetes UK.

Understanding and preventing type 1 diabetes through the unique working model of TrialNet

Article

Full-text available

Nov 2017
DIABETOLOGIA

Type 1 diabetes is an autoimmune disease arising from the destruction of pancreatic insulin-producing beta cells. The disease represents a continuum, progressing sequentially at variable rates through identifiable stages prior to the onset of symptoms, through diagnosis and into the critical periods that follow, culminating in a variable depth of beta cell depletion. The ability to identify the very earliest of these presymptomatic stages has provided a setting in which prevention strategies can be trialled, as well as furnishing an unprecedented opportunity to study disease evolution, including intrinsic and extrinsic initiators and drivers. This niche opportunity is occupied by Type 1 Diabetes TrialNet, an international consortium of clinical trial centres that leads the field in intervention and prevention studies, accompanied by deep longitudinal bio-sampling. In this review, we focus on discoveries arising from this unique bioresource, comprising more than 70,000 samples, and outline the processes and science that have led to new biomarkers and mechanistic insights, as well as identifying new challenges and opportunities. We conclude that via integration of clinical trials and mechanistic studies, drawing in clinicians and scientists and developing partnership with industry, TrialNet embodies an enviable and unique working model for understanding a disease that to date has no cure and for designing new therapeutic approaches.

Candidate reference methods for hemoglobin A1c based on peptide mapping

Article

Oct 1997

A reference method that specifically measures hemoglobin (Hb) A1c is an essential part of the reference system for the international standardization of Hb A1c/glycohemoglobin. We have developed a new method for quantification, based on the specific N-terminal residue of the hemoglobin β-chains. Enzymatic cleavage of the intact hemoglobin molecule with endoproteinase Glu-C has been optimized to obtain the β-N-terminal hexapeptides of Hb A1c and Hb A0. These peptides have been separated by reversed-phase HPLC and quantitated by electrospray ionization-mass spectrometry (method A) or by capillary electrophoresis (method B). With these peptides and hyphenated separation techniques, it has been possible to overcome the insufficient resolution of currently used protein separation systems for Hb A1c.

EurA1c: The European HbA1c Trial to Investigate the Performance of HbA1c Assays in 2166 Laboratories across 17 Countries and 24 Manufacturers by Use of the IFCC Model for Quality Targets

Article

Jun 2018

BACKGROUND: A major objective of the IFCC Committee on Education and Use of Biomarkers in Diabetes is to generate awareness and improvement of HbA1c assays through evaluation of the performance by countries and manufacturers. METHODS: Fresh whole blood and lyophilized hemolysate specimens manufactured from the same pool were used by 17 external quality assessment organizers to evaluate analytical performance of 2166 laboratories. Results were evaluated per country, per manufacturer, and per manufacturer and country combined according to criteria of the IFCC model for quality targets. RESULTS: At the country level with fresh whole blood specimens, 6 countries met the IFCC criterion, 2 did not, and 2 were borderline. With lyophilized hemolysates, 5 countries met the criterion, 2 did not, and 3 were borderline. At the manufacturer level using fresh whole blood specimens, 13 manufacturers met the criterion, 8 did not, and 3 were borderline. Using lyophilized hemolysates, 7 manufacturers met the criterion, 6 did not, and 3 were borderline. In both country and manufacturer groups, the major contribution to total error derived from between-laboratory variation. There were no substantial differences in performance between groups using fresh whole blood or lyophilized hemolysate samples. CONCLUSIONS: The state of the art is that 1 of 20 laboratories does not meet the IFCC criterion, but there are substantial differences between country and between manufacturer groups. Efforts to further improve quality should focus on reducing between-laboratory variation. With some limitations, fresh whole blood and well-defined lyophilized specimens are suitable for purpose.

Novel subgroups of adult-onset diabetes and their association with outcomes: A data-driven cluster analysis of six variables

Article

Mar 2018

Background: Diabetes is presently classified into two main forms, type 1 and type 2 diabetes, but type 2 diabetes in particular is highly heterogeneous. A refined classification could provide a powerful tool to individualise treatment regimens and identify individuals with increased risk of complications at diagnosis. Methods: We did data-driven cluster analysis (k-means and hierarchical clustering) in patients with newly diagnosed diabetes (n=8980) from the Swedish All New Diabetics in Scania cohort. Clusters were based on six variables (glutamate decarboxylase antibodies, age at diagnosis, BMI, HbA1c, and homoeostatic model assessment 2 estimates of β-cell function and insulin resistance), and were related to prospective data from patient records on development of complications and prescription of medication. Replication was done in three independent cohorts: the Scania Diabetes Registry (n=1466), All New Diabetics in Uppsala (n=844), and Diabetes Registry Vaasa (n=3485). Cox regression and logistic regression were used to compare time to medication, time to reaching the treatment goal, and risk of diabetic complications and genetic associations. Findings: We identified five replicable clusters of patients with diabetes, which had significantly different patient characteristics and risk of diabetic complications. In particular, individuals in cluster 3 (most resistant to insulin) had significantly higher risk of diabetic kidney disease than individuals in clusters 4 and 5, but had been prescribed similar diabetes treatment. Cluster 2 (insulin deficient) had the highest risk of retinopathy. In support of the clustering, genetic associations in the clusters differed from those seen in traditional type 2 diabetes. Interpretation: We stratified patients into five subgroups with differing disease progression and risk of diabetic complications. This new substratification might eventually help to tailor and target early treatment to patients who would benefit most, thereby representing a first step towards precision medicine in diabetes. Funding: Swedish Research Council, European Research Council, Vinnova, Academy of Finland, Novo Nordisk Foundation, Scania University Hospital, Sigrid Juselius Foundation, Innovative Medicines Initiative 2 Joint Undertaking, Vasa Hospital district, Jakobstadsnejden Heart Foundation, Folkhälsan Research Foundation, Ollqvist Foundation, and Swedish Foundation for Strategic Research.

A novel LIPS assay for insulin autoantibodies

Article

Jan 2018

AimsInsulin autoantibodies (IAA) are often the first marker of autoimmunity detected in children in the preclinical phase of type 1 diabetes (T1D). Currently, the vast majority of laboratories adopt the radiobinding micro-assay (RBA) for measuring IAA. Our aim was to replace RBA with a novel non-radioactive IAA Luciferase Immuno Precipitation System (LIPS) assay with improved performance. Methods We developed (pro)insulin antigens with alternative placements of a NanoLuc™ luciferase reporter (NLuc). Performance in LIPS was evaluated by testing sera from new onset T1D (n = 80), blood donors (n = 123), schoolchildren (n = 186), first-degree relatives (FDRs) from the Bart’s Oxford family study (n = 53) and from the Belgian Diabetes Registry (n = 136), coded sera from the Islet Autoantibody Standardization Program (IASP) (T1D n = 50, blood donors n = 90). ResultsIAA LIPS based on B chain-NLuc proinsulin or B chain-NLuc insulin, in which NLuc was fused at the C-terminus of the insulin B chain, required only 2 μL of serum and a short incubation time, showed high concordance with RBA (Spearman r = 0.866 and 0.833, respectively), high assay performance (B chain-NLuc proinsulin ROC-AUC = 0.894 and B chain-NLuc insulin ROC-AUC = 0.916), and an adjusted sensitivity at 95% specificity ranking on par with the best assays submitted to the two most recent IASP workshops. In FDRs, the IAA LIPS showed improved discrimination of progressors to T1D compared to RBA. Conclusions We established a novel high-performance non-radioactive IAA LIPS that might replace the current gold standard RBA and find wide application in the study of the IAA response in T1D.

Implementing a Reference Measurement System for C-Peptide: An Addendum

Article

Oct 2017

Harmonization of immunoassays for biomarkers in diabetes mellitus

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