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Research review paper
Harmonization of immunoassays for biomarkers in diabetes mellitus
, Peter Achenbach
, Erwin Schleicher
, Andreas Peter
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
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.
1.1. 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
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
0734-9750/ © 2019 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license
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.,
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-
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-
Second, the biomarker is available in pure and stable, i.e. com-
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-
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-
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-
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
- 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
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-
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.,
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
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
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-
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.,
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
= ×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
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
4.5. Does the harmonization of HbA1c improve assay performance and
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.,
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
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
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
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
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
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
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
General characteristics of immunoassays as biomarkers in diabetology.
Formation process – physiological role Clinical utility Measurement methods
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
•long-term glycemic control
•correlation with long-term diabetic
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
•secreted upon stimulation
•evaluation of beta-cell function/insulin reserve
•during a fasting test
•determination of insulin sensitivity and
Immunoassay •JCTLM listed reference material and reference methods
•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
Immunoassay •higher-order reference material and reference
measurement methods listed in the JCTLM database
Autoantibodies 1974 •autoimmune pathogenesis
•promoting the autoimmune response against beta
•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
•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.
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
We thank I. Rettig for critical reading of the manuscript.
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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