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Harmonization of immunoassays for biomarkers in diabetes mellitus

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  • University Hospital Tuebingen, Tuebingen, Germany

Abstract and Figures

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.
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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
a
Institute for Clinical Chemistry and Pathobiochemistry, Department for Diagnostic Laboratory Medicine, University Hospital Tübingen, Germany
b
Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich, University of Tübingen, Germany
c
German Center for Diabetes Research (DZD), München-Neuherberg, Germany
d
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
0734-9750/ © 2019 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/BY-NC-ND/4.0/).
T
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
2
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
3
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
4
“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
5
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
6
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
7
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
8
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
9
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
10
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
11
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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... [29]. b auch eine Standardisierung unmöglich [29,33]. Die biologische Variabilität beruht auf verschiedenen Faktoren: ▪ Die Insel-AAK werden von den jeweiligen Menschen individuell produziert und unterscheiden sich damit in ihrer Aminosäuresequenz und somit in der Bindungsregion des Autoantigens. ...
... Beide Peptidhormone sind mit immunologischen Methoden in Heparin-/EDTA-Plasma-Proben oder Serum messbar. Auf Grund der wesentlich längeren in vivo-Halbwertszeit von C-Peptid im Vergleich zu Insulin, der weitgehenden Resistenz von C-Peptid gegenüber Abbau in hämolysierten Blut und der besseren labormedizinischen Standardisierung der Messung von C-Peptid in Immunoassays [33], ist die C-Peptid-Messung als Surrogat-Parameter der β-Zellfunktion der Insulinmessung überlegen. ...
... B. Glucose, HbA1c, C-Peptid und Insulin, die alle molekular genau definiert sind, sind beta-AAK in vieler Hinsicht heterogen. Diese biologische Variabilität macht eine molekulare Definition und deswegen auch eine Standardisierung unmöglich [8]. Eine Vergleichbarkeit der Messwerte muss über eine Harmonisierung angestrebt werden. ...
... Wie aus den obigen Ausführungen zur Problematik bei der Messung von AAK hervorgeht, kann für beta-AAK schon aus biologischen Gründen weder ein definierter Referenzstandard vorhanden sein, noch eine allgemein anerkannte Referenzmethode etabliert werden. Für Testsysteme zur Bestimmung von beta-AAK besteht daher lediglich die Möglichkeit einer Harmonisierung [8]. ...
Article
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... Orally administered drugs employed in the management of diabetes lead to better patient compliance but may cause side effects such as gastric disturbance and poor renal clearance and generally suffer from lower bioavailability due to poor absorption from Fig. 1 Schematic illustration of glycation in hemoglobin (HbA1C). Reprinted with permission from Ref. [6]. Copyright (2020) Elsevier digestive tract and first pass metabolism in liver. ...
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... However, the following observations make this less likely: (i) sex differences; (ii) parallelism between FPG and HbA 1c ; (iii) individuals at the lower ends of the distributions of FPG (in both sexes) and HbA 1c (in women) showed larger increases than individuals at the upper ends, as shown by Cheng and colleagues [13]. Our single-center analysis was robust, because we measured the parameters in all the samples at a single laboratory, which minimizes measurement bias during the identification of small, but significant changes, especially when the standardization and harmonization of the insulin immunoassays are still in progress [23]. According to a study by Ito of 15,191 Japanese individuals, HbA 1c (%) was equal to 0.0334 × FPG (mg/dL) + 2.26 (R 2 = 0.7321, P < 0.0001) [24]. ...
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... Despite the increasing relevance of insulin and C-peptide measurements, studies have reported discordance among results obtained from different laboratories and different measurement systems; thus, substantial effort has been made to improve their harmonization status [5][6][7][8]. In 1996, the American Diabetes Association found that insulin measurements from different laboratories were widely discordant [9]. ...
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... 11,20 Figure 2 presents the results of applying a single conversion factor of 6.00 for the results in The IU unit, namely hormone bioactivity, is commonly adopted in clinical and biological purposes, while the pmol/L unit has priority in metrological measurement systems as it is SI traceable. 8,13,25 The certified values of CRMs are served with SI by assessment of purity and quantification using LC-MS for amino acid analysis via acid hydrolysis, a primary method for protein quantification in terms of metrological hierarchy. 24 The new WHO IS for human insulin (IS 11/212) is also primarily served with an SI-based quantity (mg) with measurement uncertainty, rather than IU. ...
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... T1D is diagnosed by the production of autoantibodies against insulin (especially preproinsulin, GAD65, insulinoma antigen-2 (IA-2) and/or the zinc transporter, ZnT8) (Hörber et al. 2020). These auto antibodies induce oral tolerance but are required in large amounts. ...
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... The authors in [7] form multiple data groups of various individuals and tested each group with K nearest algorithm, SVM, RF, NB, and ANN models and use negative prediction, sensitivity, specificity, and precision for assessing model performance. Authors in [8] studied the harmonization of biomarkers like immunoassays for the prediction of diabetes. Researchers in [9] studied various blood count parameters between healthy pregnant women and pregnant women suffering from Gestational Diabetes Mellitus to find the relation between the various blood count parameters and Gestational Diabetes Mellitus. ...
Chapter
Diabetes mellitus is a deadly disease that affects people all over the globe. An early prediction of diabetes is very beneficial as it can be controlled before the onset of the disease. Various data mining classification techniques have proven fruitful in the early detection and prediction of multiple diseases like heart attack, depression, kidney-related diseases, and many more. This paper discusses and compares various data mining techniques for the prediction of Diabetes Mellitus. Also, three widely used data mining techniques via Artificial Neural Networks (ANN), K-nearest neighbour (KNN), and Support Vector Machine (SVM) have been implemented in Matlab and the results are compared based on accuracy, recall, true negative rate, and precision.
... Insulin und C-Peptid können mittels immunologischer Messungen in Serum oder Heparin-/EDTA-Plasma spezifisch nachgewiesen werden, ohne dass Vorläufermoleküle wie das Proinsulin die Bestimmungen stören. Die Insulinbestimmung ist allerdings nach wie vor nicht standardisiert [14]. Daher zeigt sie erhebliche Unterschiede zwischen verschiedenen Reagenzien und eingesetzten Messverfahren. ...
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The diagnosis of diabetes mellitus is essentially based on the determination of laboratory parameters. Determination of glucose and glycated hemoglobin A (HbA1c) are key parameters for the initial diagnosis, prognosis and treatment control. Diabetes-associated autoantibodies are used for the classification of diabetes and C‑peptide as well as insulin are markers for the endogenous secretion of insulin. Preanalytical and analytical limitations, such as influencing and confounding factors, have to be considered to ensure that laboratory measurements are reliably determined and correctly assessed. The specifications in the guidelines of the Federal Medical Association for the Quality Assurance of Laboratory Medical Investigations (Rili-BÄK) must be observed.
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In this study, a novel core-shell structured magnetic metal-organic framework nanospheres (Fe3O4@[email protected]) were fabricated by in-situ growth of boronic acid-decorated porphyrin-based metal-organic frameworks on polydopamine (PD) functionalized Fe3O4 nanospheres for highly efficient enrichment of cis-diol containing nucleosides by magnetic solid phase extraction (MSPE). PD as a molecular linker promotes the nucleation and crystal growth of boronic acid-decorated porphyrin-based metal-organic framework (BA-Zr-MOF), which was synthesized via a dual-ligand strategy by using Zr⁴⁺ as a metal unit as well as meso-tetra (4-carboxylphenyl) porphyrin (TCPP) and 1, 4-phenylenebisboronic acid (BA) as dual organic ligands. It is worth noting that the nitrogen-rich skeleton of TCPP and abundant boric acid groups in MOF allows for effective and selective enrichment of cis-diol containing compounds by hydrophilic interaction and boron affinity. Also, Zr⁴⁺ well assembled into the MOF is beneficial to extraction via metal oxide affinity interaction due to reversible covalent complex formation/dissociation between Zr and cis-diol compounds. The morphology, structure and saturation magnetization of Fe3O4@[email protected] were systematically characterized. The as-prepared adsorbent coupled with high performance liquid chromatography was used for analysis of four nucleosides including cytidine, uridine, guanosine, and adenosine in urine sample with the detection limits in range of 0.002–0.005 μg mL⁻¹ and the quantitative limits in range of 0.008–0.018 μg mL⁻¹. The as-fabricated Fe3O4@[email protected] nanospheres shows high selectivity, low detection limit, excellent reusability and reproducibility for nucleosides enrichment. The large specific surface area and quick magnetic response performance endow the affinity magnetic nanospheres with outstanding enrichment capability for rapid extraction. The adsorbent of Fe3O4@[email protected] nanospheres has great potential for identification and analysis of trace cis-diol containing nucleosides in biological samples.
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Hemoglobin AIc is a minor component of normal adult erythrocytes whose concentration is elevated approximately 2-fold in patients with diabetes mellitus. Previous work suggested that the unique structural feature of hemoglobin AIc is the presence of a low molecular weight sugar moiety at the NH2-terminal valine of the beta chain. In this study the structure of the carbohydrate moiety and the nature of its linkage of the beta chain were investigated. Enzymatic digestion of borohydride-reduced betaAIc chains followed by ion exchange chromatography led to the isolation of two distinct NH2-terminal glycovalylhistidines. Comparison of these glycodipeptides with synthetic glycovalylhistidines by thin layer chromatography, gas-liquid chromatography, and proton magnetic resonance spectroscopy gave direct evidence that the naturally derived materials correspond to glucitol and mannitol valylhistidines. Model reactions showed that glucose and mannose react with valine under mild conditions to form an adduct which upon sodium borohydride reduction yields in both cases glucitol and mannitol valines. This suggests a common intermediate, 1-deoxy-1-(N-valyl)fructose, for both reactions. From these studies we conclude that hemoglobin AIc has, as the NH2 terminus of the beta chain, 1-deoxy-1-(N-valyl)fructose. The possible biosynthetic pathways of hemoglobin AIc are discussed.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.