human serum transferrin glycosylation pattern
TRANSCRIPT
From the Division of Alcohol and Drug Dependence Research,
Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
HUMAN SERUM TRANSFERRIN
GLYCOSYLATION PATTERN
– POPULATION DIFFERENCES, ANALYTICAL METHODOLOGY AND APPLICATION AS
BIOMARKER FOR TESTING OF ALCOHOL ABUSE AND CDG
Jonas P Bergström
Stockholm 2007
All previously published papers were reproduced with permission from the publisher. Published by Karolinska Institutet. Printed by US-AB © Jonas P Bergström, 2007 ISBN 978-91-7357-432-7
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- August Strindberg
ABSTRACT Alcohol use and abuse is a major social and economic problem in many societies.
Carbohydrate-deficient transferrin (CDT) is a widely used and highly specific
biochemical alcohol marker of prolonged alcohol abuse. Increased knowledge about the
clinical characteristics of CDT may lead to better possibilities of employing CDT as a
biochemical alcohol marker of risky and heavy alcohol consumption and thus creating
better opportunities for prevention and intervention of alcohol dependence. The aim of
this thesis was to contribute to this knowledge by investigating the properties of CDT in
different populations and evaluating the sensitivity and specificity of different
analytical methodologies for analysis of CDT.
Serum samples (n=1387) from subjects originating from five different countries were
analyzed with a HPLC candidate reference method for CDT. In non-drinkers there were
minimal differences in the serum transferrin glycoform pattern with respect to different
ethnicity, gender, age and BMI. When evaluating disialotransferrin, the primary
glycoform in CDT, with respect to the same categories, no clinically significant
differences were detected. Furthermore the overall test accuracy for identification of
heavy drinkers (>210 g ethanol/week for men and >140 g ethanol/week for women)
showed no gender difference.
Serum samples (n=178) were analyzed from subjects with clinical or pharmacological
factors previously reported to cause false-positive CDT levels. Only ~5% showed a
relative disialotransferrin level exceeding the upper limit for the reference interval,
leading to a conclusion that earlier reports on reasons for false positive CDT values are
linked with the methodology used rather than with true physiological influences.
When compared with a HPLC candidate reference method, the Bio-Rad %CDT HPLC
test and the CEofix™ CDT assay proved to be appropriate for confirmatory and routine
%CDT testing, showing an overall good correlation and agreement.
The HPLC candidate reference method could readily be used for preliminary diagnosis
of CDG and for assignment of cases to either CDG-I or CDG-II.
LIST OF PUBLICATIONS I. Bergström JP, Helander A.
Influence of alcohol use, ethnicity, age, gender, BMI and smoking on the serum transferrin glycoform pattern: implications for the use of carbohydrate-deficient transferrin (CDT) as alcohol biomarker. Clin Chim Acta 2007;In press.
II. Bergström JP, Helander A. Clinical characteristics of carbohydrate-deficient transferrin (CDT) measured by HPLC: sensitivity, specificity, gender differences and relationship with other markers of prolonged alcohol abuse. Submitted 2007.
III. Bergström JP, Helander A. HPLC evaluation of clinical and pharmacological factors reported to cause false-positive carbohydrate-deficient transferrin (CDT) levels. Submitted 2007.
IV. Helander A, Bergström JP. Determination of carbohydrate-deficient transferrin in human serum using the Bio-Rad %CDT by HPLC test. Clin Chim Acta 2006;371:187-190.
V. Helander A, Wielders JPM, te Stroet R, Bergström JP. Comparison of HPLC and capillary electrophoresis for confirmatory testing of the alcohol misuse marker carbohydrate-deficient transferrin. Clin Chem 2005;51:1528-1531.
VI. Helander A, Bergström JP, Freeze H. Testing for congenital disorders of glycosylation by HPLC measurement of serum transferrin glycoforms. Clin Chem 2004;50:954-958.
The original articles (I, IV, V and VI) have been printed with permission from the publishers.
CONTENTS 1 Introduction .................................................................................................. 1
1.1 Biochemical alcohol markers............................................................. 1 1.1.1 Markers of acute alcohol consumption ................................. 1 1.1.2 Markers of chronic alcohol consumption.............................. 2
1.2 Carbohydrate-deficient transferrin (CDT)......................................... 3 1.2.1 Transferrin structure............................................................... 4 1.2.2 CDT pathomechanisms.......................................................... 5 1.2.3 CDT sensitivity ...................................................................... 6 1.2.4 CDT specificity ...................................................................... 6 1.2.5 Congenital disorders of glycosylation (CDG)....................... 7 1.2.6 Analysis of CDT .................................................................... 7
2 General aims of the thesis ............................................................................ 9 3 Materials and methods ............................................................................... 10
3.1 Study Populations............................................................................. 10 3.1.1 The WHO/ISBRA Collaborative Project (Paper I-II)......... 10 3.1.2 Clinical samples (Paper III-V)............................................. 12 3.1.3 CDG samples (Paper VI) ..................................................... 12
3.2 HPLC candidate reference method (Paper I-VI) ............................. 12 3.3 Other methods for CDT analysis ..................................................... 14
3.3.1 Bio-Rad %CDT by HPLC Reagent Kit (Paper IV) ............ 14 3.3.2 CEofix™, CE, (Paper V) ..................................................... 15 3.3.3 %CDT immunoassay (Paper V) .......................................... 15 3.3.4 CDTect™ (Paper II)............................................................. 15
3.4 Analysis of GGT and AST (Paper II) .............................................. 16 3.5 Statistics ............................................................................................ 16
4 Results ........................................................................................................ 17 4.1 Paper I ............................................................................................... 17 4.2 Paper II.............................................................................................. 20 4.3 Paper III ............................................................................................ 23 4.4 Paper IV............................................................................................ 24 4.5 Paper V ............................................................................................. 25 4.6 Paper VI ............................................................................................ 26
5 Discussion................................................................................................... 28 6 Conclusions ................................................................................................ 30 7 Acknowledgements .................................................................................... 31 8 References .................................................................................................. 33
LIST OF ABBREVIATIONS 5-HIAA 5-Hydroxyindole-3-Acetic Acid 5-HTOL 5-Hydroxytryptophol AED Antiepileptic Drug ALT Alanine Aminotransferase AST Aspartate Aminotransferase AUC Area Under the Curve BMI Body Mass Index CDG Congenital Disorders of Glycosylation CDT Carbohydrate-Deficient Transferrin CE Capillary Electrophoresis CRP C-Reactive Protein CV Coefficient of Variation CF Cystic Fibrosis DST Disialotransferrin EtG Ethyl Glucuronide EtS Ethyl Sulfate GC-MS Gas Chromatography-Mass Spectrometry GGT Gamma Glutamyltransferase HPLC High-Performance Liquid Chromatography FeNTA Ferric Nitrilotriacetic Acid ID Inner Diameter IFCC International Federation of Clinical Chemistry and Laboratory
Medicine IEF Isoelectric Focusing ISBRA International Society for Biomedical Research on Alcoholism LC-MS Liquid Chromatography-Mass Spectrometry LC-MS/MS Liquid Chromatography-Mass Spectrometry/Mass Spectrometry LOD Limit of Detection LOQ Limit of Quantification NIAAA National Institute on Alcohol Abuse and Alcoholism PEth Phosphatidylethanol RIA Radioimmunoassay ROC Receiver-Operating Characteristic U/L Units/Liter WHO World Health Organization
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1 INTRODUCTION
1.1 BIOCHEMICAL ALCOHOL MARKERS Alcoholic beverages, and the pleasures and problems they cause, have been known to
mankind since the beginning of recorded history. The use and abuse of alcohol is the
cause of immense costs in most of the western societies, with a rather big proportion of
its citizens being alcohol dependent or consuming harmful amounts of alcohol (1).
Therefore, screening for alcohol-related problems is an important task to detect alcohol
dependence or risky alcohol consumption behavior, and is usually accomplished by
structured interviews and/or laboratory tests. The most widely employed alcohol
questionnaires over the last years are the Alcohol Use Disorder Identification Test
(AUDIT) (2-4) and CAGE (5, 6), both of them relying on the patient’s self-reported
alcohol consumption and the associated problems. The self-reported amount of alcohol
consumed is however known to be frequently underreported, therefore leading to
possible under-diagnosis of alcohol related problems (7). Laboratory tests, or
biochemical markers of alcohol use and abuse, offers more objective methods to
monitor or detect excessive alcohol consumption.
1.1.1 Markers of acute alcohol consumption The biochemical markers of acute alcohol consumption are laboratory tests developed
in order to detect single intakes of alcohol, typically in the last 0-48 hours prior to
sampling, depending on the sensitivity of the test and the amount of alcohol consumed.
These markers provide a powerful tool within areas such as forensic medicine, criminal
applications, occupational medicine, and can also be used for confirmation of
abstinence in outpatient treatment (8-10).
1.1.1.1 Ethanol
After alcohol consumption, ethanol can be determined in breath or body fluids (11).
The major drawback with ethanol as a biochemical marker is that the human body
rapidly metabolizes even large amounts of ethanol in typically <12 hours, making the
time range for detection very small (12). Another drawback is that the ethanol
concentration does not provide information about hazardous drinking patterns and
eventual alcohol problems.
2
1.1.1.2 EtG and EtS
Ethyl glucuronide (EtG) and ethyl sulfate (EtS) are water-soluble, stable, conjugated
direct metabolites of ethanol (13, 14). EtG is formed from a minor part of the ingested
ethanol (<0.1%) via reaction with uridine-5-diphospho-β-glucuronic acid (15). EtS is
also formed from a minor part of the ingested ethanol (<0.1%) after reaction between
ethanol and sulfate by sulfotransferase (16). Both EtG and EtS are excreted in the urine
and, sharing approximately the same elimination profiles, are washed out from the
body at a much slower rate than ethanol itself, and can often be detected days after
alcohol consumption (17, 18). Therefore EtG and EtS offer an extended window for
assessment of single ethanol intake. Urinary EtG and EtS can today be determined with
a range of analytical methodology (14, 19-21).
1.1.1.3 5-HTOL/5-HIAA
During normal conditions, the major part of all serotonin is metabolized to 5-
hydroxyindole-3-acetic acid (5-HIAA) with only a smaller part (<1%) forming into 5-
hydroxytryptophol (5-HTOL). However, alcohol consumption results in a shift towards
an increased formation of 5-HTOL, and consequently an elevated ratio of 5-HTOL/5-
HIAA can be detected in urine for several hours after all ethanol is cleared from the
body. This makes it possible to detect a single alcohol intake for a much longer period
of time (22-24). 5-HTOL and 5-HIAA have traditionally been analyzed by gas
chromatography-mass spectrometry (GC-MS) and high-performance liquid
chromatography (HPLC), respectively (25, 26), but lately there has been suggestions to
replace 5-HTOL as target analyte and instead analyze 5-HTOL glucuronide (GTOL)
together with 5-HIAA with a highly sensitive and specific LC-MS/MS method (27).
1.1.2 Markers of chronic alcohol consumption Biochemical markers of chronic alcohol consumption are laboratory tests that can be
used for identification of a chronic, sustained consumption that has been going on for
typically over a week (28). These markers are currently in use in areas such as traffic
medicine, occupational medicine and in various clinical settings as indicators of a
chronic alcohol misuse (29). The marker in focus in this thesis, CDT, is presented in
detail in section 1.2.
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1.1.2.1 GGT
Gamma-glutamyltransferase is an intracellular liver enzyme that in response to acute
hepatocellular damage, e.g. following prolonged alcohol abuse, can leak into the blood.
The reported alcohol consumption needed for an elevated serum level of GGT have
shown great variations. Still, it is today maybe the most used laboratory marker for
chronic alcohol consumption (30, 31). The specificity of GGT for chronic alcohol
abuse is very poor. Some of the reported factors that cause an elevated GGT level are
smoking, male gender, obesity, age, non-alcoholic liver diseases, medication and
diabetes (28, 32, 33). The half-life of GGT is between 2-3 weeks (34).
1.1.2.2 AST and ALT
Elevated serum concentrations of the liver enzymes aspartate aminotransferase (AST)
and alanine aminotransferase (ALT) are indicators of non-specific liver dysfunction,
and concentrations are frequently heightened also in alcoholic patients (35, 36). These
liver enzymes leaks into the blood following hepatocellular damage in the same way as
GGT. The sensitivity and specificity for identification of alcohol misuse are in most
cases reported low or moderate for both AST and ALT (37). An elevated AST level can
also arise from non-hepatic sites (e.g., heart and muscles), and from conditions such as
non-alcoholic liver disease, myocardial infarction and skeletal muscle trauma (38). The
half-life of AST and ALT is reported to be 2-3 weeks (37).
1.1.2.3 PEth
Phosphatidylethanol (PEth) is an abnormal phospholipid formed exclusively by the
action of phospholipase D in the presence of ethanol and is considered a promising new
biochemical marker of chronic alcohol misuse (39, 40). PEth has a half-life of ~4 days,
making it possible to detect PEth in blood of chronic alcohol users up to 3 weeks after
alcohol withdrawal. The amount of PEth in blood is reported to be highly correlated
with the past alcohol intake in alcohol abusers (41). The sensitivities and specificities
that are reported so far are high, but this biomarker is in need of further evaluation
within different clinical settings. The current methods for analysis of PEth include
HPLC with evaporative light scattering detection (42, 43) and LC-MS (44).
1.2 CARBOHYDRATE-DEFICIENT TRANSFERRIN (CDT) Transferrin is a glycoprotein mainly synthesized in the hepatocytes(45). It is the major
Fe3+-transport protein in the body, with a normal serum concentration range of 1.9-3.3
4
g/L (46). Under prolonged heavy alcohol consumption, the microheterogeneity of the
glycoform pattern of transferrin changes towards a higher proportion of so called
carbohydrate-deficient transferrin (CDT), making it useful as a laboratory marker of
sustained alcohol abuse (47, 48). This discovery was first reported in 1976 by Stibler
and Kjellin, after studies on the transferrin glycoform pattern in cerebrospinal fluid
from alcoholics (49).
1.2.1 Transferrin structure Transferrin consists of three different sub-structural domains: a single polypeptide
chain with 679 amino acids, two Fe3+ ion-binding sites, one within the N-terminal
domain and one within the C-terminal domain, and two N-linked complex
oligosaccharide chains (Figure 1) (45). There are many different polypeptide chain
variants reported (~40) (50). The most common polypeptide chain is the homozygous
transferrin C variant, with the subtype transferrin C1 being the most frequent occurring
in Caucasians (>95%). Heterozygous transferrin BC, CD and other variants seldom
show a prevalence over 1% of the population. Another microheterogeneity is the
varying iron load of transferrin in blood. With a normal iron saturation of transferrin in
blood (~30%) there are transferrin molecules with none, one or two Fe3+ ions present
simultaneously. The microheterogeneity between the oligosaccharide chains is
complex: the chains can be biantennary, triantennary or even tetraantennary, each
antennary usually terminating in a sialic acid residue, the total number of residues
traditionally giving name to the glycoform (51).
N-Acetylglucosamine
Mannose
Galactose
Sialic Acid
Fe3+ Fe3+N C
N-Acetylglucosamine
Mannose
Galactose
Sialic Acid
Fe3+ Fe3+N C
Figure 1. Detailed structure of the main transferrin glycoform tetrasialotransferrin that normally represents ~80% of the total serum transferrin in healthy adults. The line between N and C represents the single polypeptide chain.
5
For example, the most common transferrin glycoform in healthy adults,
tetrasialotransferrin (~80%; Figure 1), consists of two disialylated N-linked glycans,
e.g. a total of four terminal sialic acid residues, hence its structural name. Other
normally occurring transferrin glycoforms in healthy adults are disialotransferrin
(<2%), trisialotransferrin (~4%), pentasialotransferrin (~14%) and hexasialotransferrin
(~1%) (52-54).
Fe3+ Fe3+N C
Fe3+ Fe3+N C
Fe3+ Fe3+N C
Fe3+ Fe3+N C
Fe3+ Fe3+N C
Fe3+ Fe3+N C
Trisialotransferrin ~4% Pentasialotransferrin ~14% Hexasialotransferrin ~1%
Asialotransferrin
( alcohol)
Monosialotransferrin
( with high trisialotransferrin)Disialotransferrin ~1%
( alcohol)
Fe3+ Fe3+N C
Fe3+ Fe3+N C
Fe3+ Fe3+N C
Fe3+ Fe3+N C
Fe3+ Fe3+N C
Fe3+ Fe3+N C
Trisialotransferrin ~4% Pentasialotransferrin ~14% Hexasialotransferrin ~1%
Asialotransferrin
( alcohol)
Monosialotransferrin
( with high trisialotransferrin)Disialotransferrin ~1%
( alcohol)
Figure 2. Detailed structure of the most common minor transferrin glycoforms and their relative occurrence in serum from healthy adults. Prolonged alcohol abuse elevates the relative level of disialotransferrin. In subjects with high levels of disialotransferrin, sometimes asialotransferrin can be detected. Monosialotransferrin can often be seen in individuals with a genetically high trisialotransferrin level.
Under prolonged alcohol abuse, the glycoform disialotransferrin increases relatively to
the total transferrin, and in subjects with high levels of disialotransferrin, sometimes
asialotransferrin can be detected (Figure 2) (55-57). Monosialotransferrin can
sometimes be detected in subjects with genetically very high levels of trisialotransferrin
(57).
1.2.2 CDT pathomechanisms The detailed pathomechanisms behind the increase of CDT during prolonged alcohol
consumption are not fully evaluated yet. There is however some evidence that ethanol
or its metabolite acetaldehyde interferes in the transferrin N-glycan chain synthesis in
the Golgi apparatus. The activities of the glycoprotein glycosyltransferases
galactosyltransferase and N-acetylglucosaminyltransferase were lower in serum from
alcoholics than in subjects from a healthy control group (58). In alcohol fed rats,
6
ethanol lowers the levels of sialyltransferase mRNA, and consequently lowers the
sialyltransferase activity (59). In another study on alcohol fed rats, an increase of
sialidase activity in liver plasma was seen (60). Accordingly with these studies, ethanol
or maybe more likely acetaldehyde seems to hamper glycoprotein glycosyltransferase
activity in general, which in combination with an increased sialidase activity give rise
to increased levels of CDT .
1.2.3 CDT sensitivity The sensitivity of CDT as a marker of chronic alcohol abuse is reported with great
variation depending on factors such as study population, mean daily alcohol intake and
drinking patterns (47, 61-63). When reviewed, a sensitivity of 30-50% for women and
50-70% for men seemed to be of average (48). The amounts of alcohol reported to
increase the CDT value over the reference interval for social drinkers have been
debated, but it seems that at least 50-80 grams of ethanol per day for 2 weeks or longer
is necessary to produce elevated CDT concentrations (64-66). Factors that have been
reported to affect the sensitivity of CDT include age, gender, drinking patterns, body
mass, hypertension and smoking, to name a few (67-70). It is however unclear how
much the often aged and less specific analysis methodology (e.g., CDTect™) used in
many reports on this issue have influenced the reliability of the results (71-74). The
half-life of CDT is reported to be 1.5-2 weeks, and following alcohol abstinence a
normalization of the CDT level occurs within approximately 4 weeks (47).
1.2.4 CDT specificity The single biggest advantage of using CDT as a marker of chronic alcohol abuse is that
of all laboratory tests available CDT is the most specific (48). That said, there have
over the years been numerous reports published on clinical conditions or other factors
that could produce false-positive (i.e., non alcohol related) CDT results (70). These
reports identify, among other things, genetic transferrin variants, congenital disorders of
glycosylation (CDG), different liver diseases, iron deficiency, haemochromatosis,
hypertension, cystic fibrosis (CF), various medication and sepsis to be factors that
elevate CDT values (75-83). However, these findings are often based on very small
subject groups or with a methodology for CDT analysis that is now out of date (e.g.,
CDTect), making it hard to estimate the true impact of the different clinical factors
investigated on CDT levels.
7
1.2.5 Congenital disorders of glycosylation (CDG) Congenital disorders of glycosylation (CDG) are a group of rare hereditary diseases
characterized by defects in the synthesis of the glycan moieties of glycoproteins or
other glycoconjugates caused by mutations in the genes coding for enzymes involved in
the glycoprotein synthesis (84, 85). The two main types of protein glycosylation are N-
glycosylation and O-glycosylation, where the latter will not be further discussed here.
In general, N-glycosylation consists of an assembly pathway (in cytosol and
endoplasmatic reticulum) followed by a processing pathway (in endoplasmatic
reticulum and Golgi). The two main types of N-glycosylation CDG are defects in
glycoprotein synthesis during the assembly pathway (CDG-I) or during the processing
pathway (CDG-II). These two main groups are further sub-categorized, so that each
defective gene correspond to one specific CDG (e.g. CDG-Ia, CDG-Ib, CDG-IIa etc.),
and today there are ~10 CDG-I and ~5 CDG-II categorized (86). N-Glycosylation
defects affects primarily the nervous system with the clinical expression including
psychomotor, growth and mental retardation, and the effect varies between being
extremely severe to very mild. Since the clinical symptoms often are unspecific, CDG
are probably under-diagnosed. The main laboratory tool used to identify and categorize
N-glycosylation CDG has traditionally been isoelectric focusing (IEF) of the transferrin
glycoform pattern (87), but mass spectrometry techniques for identification of CDG are
also available (88).
1.2.6 Analysis of CDT CDT was originally defined as the three transferrin glycoforms with a pI > 5.7 after
IEF, i.e. asialo-, monosialo- and disialotransferrin (47). IEF was the first reference
method for serum transferrin glycoform analysis, and is still used today as a reference
method for identification of genetic transferrin variants and CDG, much because of its
high selectivity. The major drawback with IEF is difficulties with quantitative CDT
analysis (89).
Jeppsson et al. developed the first HPLC method for identification and quantification of
transferrin glycoforms in 1993 (100), and it has later been followed by commercial
HPLC kits (101). Some of the general advantages with HPLC methods for CDT
analysis is the ability to identify genetic transferrin variants, the specificity (i.e., only
disialotransferrin is measured) and that HPLC is a well known methodology in many
8
clinical laboratories. Later Helander et al. developed an improved HPLC method that is
now a suggested candidate reference method for CDT analysis (102).
Over the years there have been several capillary electrophoresis (CE) and capillary
zone electrophoresis methods available for analysis of CDT, with gradually increasing
sensitivity and selectivity, and lately some methods have been commercially available
for routine use (90-92).
The immunoassay CDTect RIA (Pharmacia & Upjohn, Uppsala, Sweden) was the first
commercial test kit for CDT analysis and was launched 1993 (93, 94). This method,
and later its follower the %CDT immunoassay (Axis-Shield ASA, Oslo, Norway) have
both been available in a number of different variants for different applications (details
on methodology in section 3.3.3 and 3.3.4) (95-98). Notably, both are measuring the
sum of asialo-, monosialo-, disialo- and sometimes a fraction of trisialotransferrin
making them unspecific and not capable of identifying genetic transferrin variants that
are known to produce false-high or false-low CDT values (99).
Recently the first direct immunoassay for CDT, N Latex CDT (Dade Behring,
Marburg, Germany), became available. Measurement with N Latex CDT is based on a
monoclonal antibody that recognizes transferrin glycoforms that lack one or both of the
complete N-glycans (i.e., asialo-, monosialo- and disialotransferrin) (103). The
difference compared with other methods that measures the sum of asialo-, monosialo-
and disialotransferrin is that the monoclonal antibody used in N Latex CDT does not
discriminate between different genetic transferrin variants, and thus genetic variants do
not interfere with measurements, making it a more specific method.
During the last years, reports on analysis of transferrin with mass spectrometry have
begun to be published, providing valuable information on the structural
microheterogeneity of the transferrin glycans (104-106).
9
2 GENERAL AIMS OF THE THESIS
• To evaluate any baseline differences in the transferrin glycoform pattern in
relation to ethnicity, age, gender, body mass index and smoking in a large study
population from five different countries.
• Within the same study population evaluate the sensitivity and specificity of
serum disialotransferrin as a biochemical marker for chronic alcohol abuse in
relation to ethnicity, gender, age and body mass index, and to compare the
performance of disialotransferrin with the traditional alcohol biomarkers GGT
and AST.
• Evaluate clinical and pharmacological factors previously reported to cause
false-positive CDT levels.
• Evaluate two potential confirmatory and routine methods for CDT testing, the
Bio-Rad %CDT by HPLC test and the CEofix™ CDT assay.
• To study the usefulness of a HPLC candidate reference method for the detection
and preliminary diagnosis of CDG.
10
3 MATERIALS AND METHODS
3.1 STUDY POPULATIONS The serum samples analyzed in Paper I and II were all from subjects participating in the
WHO/ISBRA Study on State and Trait Markers of Alcohol Use and Dependence, an
international multicenter study (107). The serum samples analyzed in Paper III, IV and
V were anonymous leftover volumes from the Karolinska University Hospital or (in
Paper V) also from Meander Medical Center, Amersfoort, The Netherlands. In Paper
VI, the serum samples from subjects with different CDG types were from The
Burnham Institute, La Jolla, California, USA, all other serum samples were de-
identified leftover volumes from the Karolinska University Hospital.
3.1.1 The WHO/ISBRA Collaborative Project (Paper I-II)
The WHO/ISBRA Study on State and Trait Markers of Alcohol Use and Dependence
was established in 1988. The aim with the study was to assess and compare markers of
recent alcohol use and also of the trait of alcohol dependence in a multicenter trial
(107). The study group consisted of representatives from the World Health
Organization (WHO), the International Society for Biomedical Research on
Alcoholism (ISBRA) and the National Institute on Alcohol Abuse and Alcoholism
(NIAAA). The samples used within this study were collected from both the community
and from alcohol treatment services in 5 countries: Australia (Sydney), Brazil (São
Paolo), Canada (Montreal), Finland (Helsinki) and Japan (Sapporo). A total of 1863
subjects aged over 18 were recruited, 67% of the subjects men and 33% women. In
Australia and Finland, only men were recruited. All participants were extensively
characterized for socio-demographic, health and lifestyle factors, and thoroughly
interviewed about their drinking habits by trained researched staff using the structured
WHO/ISBRA Interview Schedule (108). Based on this information, each subject was
classified as either “non-drinker” = totally abstinent, or one who drinks alcohol on no
more 6 special occasions per year (e.g., birthdays), and no more than 15 g ethanol on
each occasion; “light/moderate drinker” = drinks at least once per month but <210 g
ethanol/week for men and < 140 g ethanol/week for women, but no past treatment for
alcohol-related problems; “heavy drinker” = drinks > 210 g ethanol/week for men and
> 140 g ethanol/week for women, but no past treatment for alcohol-related problems; or
“under alcohol treatment” = a person currently receiving treatment for alcohol
11
Table 1. Demographic data on the country of origin, gender, age, ethnicity and drinking status of the WHO/ISBRA collaborative project study population used in Paper I and II.
Australia Brazil Canada Finland Japan Total
Serum samples, n 239 385 432 200 131 1387
Gender, n (%)
Male 239 (100%) 211 (54.8%) 231 (53.5%) 200 (100%) 65 (49.6%) 946 (68.2%)
Female 0 174 (45.2%) 201 (46.5%) 0 66 (50.4%) 441 (31.8%)
Age, years
Mean ± SD 37.0 ± 13.1 35.5 ± 11.7 36.8 ± 12.0 39.2 ± 11.4 37.5 ± 11.3 36.9 ± 12.0
Median 36 33 36 38 35 35
Range 18-65 18-60 18-60 18-60 21-59 18-65
Age <31 (%) 87 (36.4%) 161 (41.8%) 156 (36.1%) 57 (28.5%) 45 (34.4%) 506 (36.5%)
Age 31-40 51 (21.3%) 95 (24.7%) 95 (22.0%) 53 (26.5%) 34 (26.0%) 328 (23.6%)
Age 41-50 51 (21.3%) 73 (19.0%) 110 (25.5%) 52 (26.0%) 30 (22.9%) 316 (22.8%)
Age >50 50 (20.9%) 56 (14.5%) 71 (16.4%) 38 (19.0%) 22 (16.8%) 237 (17.1%)
Ethnicity, n (%)
White 206 (86.2%) 268 (69.6%) 382 (88.4%) 198 (99.0%) 1 (0.8%) 1055 (76.0%)
Asian/Indian 24 (10.0%) 12 (3.1%) 23 (5.3%) 0 129 (98.5%) 188 (13.6%)
Black 5 (2.1%) 58 (15.1%) 9 (2.1%) 0 0 72 (5.2%)
Pacific 1 (0.4%) 0 2 (0.5%) 0 0 3 (0.2%)
American Indian 0 1 (0.3%) 2 (0.5%) 0 1 (0.8%) 4 (0.3%)
Other/Unknown 3 (1.3%) 46 (11.9%) 14 (3.2%) 2 (1.0%) 0 65 (4.7%)
Drinking status, n (%)
Non-drinker 65 (27.2%) 90 (23.4%) 132 (30.6%) 61 (30.5%) 12 (9.2%) 360 (25.9%)
Light drinker 97 (40.6%) 180 (46.8%) 189 (43.8%) 117 (58.5%) 106 (80.9%) 689 (49.7%)
Heavy drinker 77 (32.2%) 115 (29.9%) 111 (25.7%) 22 (11.0%) 13 (9.9%) 338 (24.4%)
dependence. However, in Paper I and II, the samples from the category with subjects
undergoing alcohol treatment were excluded from determination of CDT with the
HPLC candidate reference method, since these samples did not meet the criteria of the
aims of the studies. In the remaining three drinking categories some serum samples
were excluded because of too small sample volumes. In the end, serum samples from a
total of 1387 subjects were analyzed with the HPLC candidate reference method for
CDT (102, 109). Detailed information about the study population concerning gender,
age, ethnicity and drinking status is shown in Table 1. Based on the HPLC transferrin
pattern, 1362 (98%) subjects were indicated to be of transferrin C phenotype (a further
sub-classification into C1, C2 and C3 was not performed). The other 25 samples were
of different genetic variants and were excluded from the calculations, due to
overlapping peaks causing unreliable quantification of individual glycoforms (57).
12
3.1.2 Clinical samples (Paper III-V) The serum samples in these studies were all anonymous leftover volumes from
different departments at the Karolinska University Hospital, with the exception of 37
serum samples in Paper V that were collected at the Meander Medical Center,
Amersfoort, The Netherlands. In Paper III serum samples were collected from subjects
with various clinical conditions or undergoing medication with drugs previously
reported to cause non-alcohol related elevations of CDT. The samples were from
subjects with end-stage liver disease (n=50), diabetes mellitus type 2 (n=46), an
elevated C-reactive protein (CRP) level (n=15), medication with enzyme or non-
enzyme inducing antiepileptic drugs (AED; n=43), and cystic fibrosis (CF; n=24). In
Paper IV the serum samples used were two human serum pools (containing ~1.3% and
~2.6% disialotransferrin, respectively, by HPLC), 150 surplus clinical sera selected
from routine samples pool in order to cover the entire measurement range from
low/normal to highly elevated disialotransferrin values (0.7-22% by HPLC), as well as
18 serum samples with genetic transferrin variants. In Paper V, 42 anonymous surplus
sera were collected from the routine samples pool to cover the measuring range from
low/normal to highly elevated %CDT levels (1.3-24.2% by %CDT immunoassay), as
well as some genetic transferrin variants. In addition, 37 serum samples for this study
were collected at the Meander Medical Center, Amersfoort, The Netherlands, as
mentioned above.
3.1.3 CDG samples (Paper VI) In this study, serum samples from 9 patients with biochemically and/or genetically
confirmed CDG type I (a, b and g subtypes) and 4 with undefined CDG type IIx defects
were obtained from The Burnham Institute, La Jolla, California, USA. Serum samples
used for comparison from 42 children and adolescents (0-3 weeks, n=13; 1-9 months,
n=11; 1-18 years, n=18), 132 adult social drinkers and 74 chronic alcohol misusers
were all randomly selected leftover volumes from routine samples at the Karolinska
University Hospital (110).
3.2 HPLC CANDIDATE REFERENCE METHOD (PAPER I-VI) The HPLC candidate reference method is an improved HPLC method for measurement
of CDT in serum based on anion-exchange chromatographic separation of the different
transferrin glycoforms followed by photometric detection (Figure 3) (102). The method
13
Time (min) 5 10 15 20 25
0.2
0.4
0.6
0.8
Abs
orba
ncy
(mA
U)
1.0
0.0
d
Time (min) 5 10 15 20 25
0.2
0.4
0.6
0.8
Dis
ialo
trans
ferr
in
Tris
ialo
trans
ferr
in
Tetra
sial
otra
nsfe
rrin
Pen
tasi
alot
rans
ferr
in
Hex
asia
lotra
nsfe
rrin
Abs
o rba
ncy
(mA
U)
1.0
0.0
a
Time (min) 5 10 15 20 25
0.2
0.4
0.6
0.8
Abs
orb a
ncy
(mA
U)
1.0
0.0
Dis
ialo
trans
ferr
in
Tris
ialo
trans
ferri
n
Tetra
sial
otra
nsfe
rrin
Pen
tasi
alot
rans
ferri
n
Hex
asia
lotra
nsfe
rrin
Asi
alot
rans
ferr
in
b
Time (min) 5 10 15 20 25
0.2
0.4
0.6
0.8
Abs
orba
ncy
(mA
U)
1.0
0.0
Dis
ialo
trans
ferri
n
Tris
ialo
trans
ferri
n
Tetra
sial
otra
nsfe
rrin
Pen
tasi
alot
rans
ferr
in
Hex
asia
lotra
nsfe
rrin
Mon
osia
lotra
nsfe
rrin
c
Time (min) 5 10 15 20 25
0.2
0.4
0.6
0.8
Abs
orba
ncy
(mA
U)
1.0
0.0
d
Time (min) 5 10 15 20 25
0.2
0.4
0.6
0.8
Dis
ialo
trans
ferr
in
Tris
ialo
trans
ferr
in
Tetra
sial
otra
nsfe
rrin
Pen
tasi
alot
rans
ferr
in
Hex
asia
lotra
nsfe
rrin
Abs
o rba
ncy
(mA
U)
1.0
0.0
a
Time (min) 5 10 15 20 25
0.2
0.4
0.6
0.8
Abs
orb a
ncy
(mA
U)
1.0
0.0
Dis
ialo
trans
ferr
in
Tris
ialo
trans
ferri
n
Tetra
sial
otra
nsfe
rrin
Pen
tasi
alot
rans
ferri
n
Hex
asia
lotra
nsfe
rrin
Asi
alot
rans
ferr
in
b
Time (min) 5 10 15 20 25
0.2
0.4
0.6
0.8
Abs
orba
ncy
(mA
U)
1.0
0.0
Dis
ialo
trans
ferri
n
Tris
ialo
trans
ferri
n
Tetra
sial
otra
nsfe
rrin
Pen
tasi
alot
rans
ferr
in
Hex
asia
lotra
nsfe
rrin
Mon
osia
lotra
nsfe
rrin
c
Figure 3. Shown in (a) is a control serum sample from a light drinker with the predominant transferrin C homozygote variant; (b), transferrin C serum from a heavy drinker with increased disialotransferrin (3.2% of total AUC for transferrin) and detectable (~0.4%) asialotransferrin; (c), transferrin C serum from a person with high trisialotransferrin (8.4%) and a measurable (~0.5%) monosialotransferrin; (d), transferrin BC heterozygote, a genetic transferrin variant. Figure edited from (102).
is based on earlier HPLC methodology developed by Jeppson et al. (100). The primary
target molecule for this method is disialotransferrin, as recommended by the IFCC
working group on CDT standardization (111). Transferrin was first iron-saturated by
mixing 10-100 µL (depending on the available volume) of serum at a volume ratio of
5:1 with FeNTA (final concentration, 1.7 mmol/L), a well-known transferrin iron donor
(112). Lipoproteins were precipitated by mixing the iron-saturated sample 6:1 (by
volume) with dextran sulfate and CaCl2 (1.4 mg/L and 70 mmol/L, respectively). The
samples were mixed gently and left in the cold (~5 ºC) 30-60 minutes, and then
centrifuged at 3500g for 10 minutes. The clear supernatant was diluted fivefold with
water and then transferred to glass HPLC vials. If available, the injection volume was
200 µL. The HPLC system consisted of an Agilent 1100 Series Liquid Chromatograph,
equipped with a quarternary pump and degasser, thermostated autosampler (4 ºC) and
column compartment (25 ºC), a G1365B multiple wavelength detector and
ChemStation software. The transferrin glycoforms were separated by use of a
SOURCE® 15Q PE 4.6/100 anion-exchange chromatography column (Amersham
Biosciences, Uppsala, Sweden) with a linear salt gradient elution at a flow rate of 1
14
mL/min. Quantification of the different transferrin glycoforms relied on the selective
absorbance of the iron-transferrin complex at 470 nm. Baseline integration was used for
all transferrin peaks, typically from monosialotransferrin (if visible) or
disialotransferrin to hexasialotransferrin, with asialotransferrin (if visible) integrated
separately. With this method, the relative amount of any single glycoform (e.g.,
disialotransferrin) or combination of glycoforms to total transferrin (all quantified
glycoforms) are measured in terms of the relative area under the curve (%AUC). The
typical LOD and LOQ for the transferrin glycoforms were ~0.05% and 0.10%,
respectively, of total serum transferrin in the normal transferrin concentration range
(reference interval 1.9-3.3 g/L) (46). The intra- and inter-assay imprecision (CV)
determined for serum samples containing normal and elevated disialotransferrin (range
1.0-5.6%) are below 5% (102).
3.3 OTHER METHODS FOR CDT ANALYSIS Apart from the HPLC candidate reference method described above, which served as the
principal analysis method during the work with this thesis, other methods for analysis
of CDT were also used; Bio-Rad %CDT by HPLC Reagent Kit (Paper IV) (101), the
CEofix™ CDT Assay for CE analysis (Paper V) (113), the %CDT immunoassay
(Paper V) (114) and the CDTect™ radioimmunoassay (RIA) (94) method (Paper II).
3.3.1 Bio-Rad %CDT by HPLC Reagent Kit (Paper IV) Bio-Rad %CDT by HPLC Reagent Kit (Bio-Rad, Munich, Germany) is a new
commercial application for HPLC that allows separation of asialo-, disialo-, trisialo,
tetrasialo- and pentasialotransferrin in serum within ~6 min (total analysis time for 1
sample is ~10 min) (101). The method measures individual glycoforms in proportion to
total transferrin using baseline integration. The samples were prepared following the
manufacturers instructions for the reagent kit. The transferrin glycoforms were
separated on a gradient HPLC system with anion-exchange cartridge (guard, 5*4.6 mm
ID; analytical, 30*4 mm ID), followed by specific measurement of the iron-transferrin
complex at 460 nm. With this HPLC method monosialo- and disialotransferrin are co-
eluating, thus CDT is defined as the sum of asialo-, monosialo- and disialotransferrin,
and according to the manufacturer’s instructions the upper 95% confidence limit (mean
+ 2 SD) for this kit is 1.7%.
15
3.3.2 CEofix™, CE, (Paper V) The CEofix™ CDT Assay (Analis, Namur, Belgium) is a commercial CE method for
separation of individual transferrin glycoforms and for determination of CDT (92, 115,
116). The serum samples were first iron saturated. The fused capillary had an ID of 50
µm with a total length of 50 cm and had 40 cm to the detector. Before separation, the
capillary is dynamically coated by rinsing the capillary with an initiator buffer
containing a polycation and with the separation buffer containing a polyanion, creating
a dynamic double coating. Electrophoresis was carried out with an overall separation
time of ~6 min with ultraviolet detection at 214 nm on a Beckman Coulter P/ACE
5000, according to the manufacturer’s instructions. The relative amounts of single
transferrin glycoforms were calculated from peak areas by valley-to-valley integration.
All analysis with CEofix™ was performed at the Department of Clinical Chemistry,
Meander Medical Center, Amersfoort, The Netherlands (117).
3.3.3 %CDT immunoassay (Paper V) The %CDT immunoassay (Axis-Shield ASA, Oslo, Norway) is a heterogeneous
immunoassay with column separation followed by turbidimetric measurement that
measures CDT, i.e. the sum of asialo-, monosialo-, disialo-, and a portion (~50%) of
trisialotransferrin as the relative amount to the total transferrin (114) . The serum
transferrin in the sample was saturated with Fe3+ and applied to an ion-exchange
column where the different glycoforms are separated due to differences in charge. The
CDT glycoforms (as defined above) were eluted and determined by turbidimetric
measurement after formation of an immune complex with anti-transferrin antibodies.
The total transferrin content in the sample was determined separately using the same
anti-transferrin antibodies, and the %CDT concentration could then be calculated as the
ratio between CDT and total transferrin. According to the manufacturer the cut-off is
2.6%.
3.3.4 CDTect™ (Paper II) The CDTect RIA method (Pharmacia & Upjohn, Uppsala, Sweden) is based on column
separation followed by a double antibody RIA procedure measuring CDT (94), i.e. the
sum of asialo-, monosialo, part of disialo-, and traces of trisialotransferrin (71). The
serum transferrin in the sample was iron saturated with ferric citrate solution, and
elution buffer was added. An aliquot of the sample-buffer mixture was applied to the
anion-exchange microcolumns, and the CDT glycoforms (as defined above) were after
16
separation obtained in the column effluxes. Finally, the CDT from the eluate was
quantified with a double antibody RIA procedure and expressed as an absolute value in
units/liter (U/L). According to the manufacturer the cut-off value is 20 U/L for men and
26 U/L for women. Analysis with CDTect™ of the serum samples in this study was
already performed at an earlier point at the Alcohol Laboratory, Karolinska University
Hospital, Stockholm, Sweden, when the work with Paper II began.
3.4 ANALYSIS OF GGT AND AST (PAPER II) Gamma glutamyltransferase (GGT) and Aspartate Aminotransferase (AST) were
assayed by reflectance spectrophotometry using a Vitros 250 Analyser (Ortho Clinical
Diagnostics, Rochester, NY). Analysis of plasma samples for GGT and AST was
already performed at an earlier point at the laboratories of ALKO and KTL, Helsinki,
Finland, when the work with Paper II began (118).
3.5 STATISTICS
Statistical calculations were performed using the Student-Newman-Keuls test for
pairwise comparisons, a T-test (parametric) when the examined groups showed a
Gaussian distribution or Wilcoxon (non-parametric) if not. For statistical analysis of
correlations, Pearson´s correlation coefficient (parametric) or Spearman´s coefficient
of rank correlation (nonparametric) were used. All statistical analysis was performed
with MedCalc statistical software.
17
4 RESULTS
4.1 PAPER I The relative amounts of serum transferrin glycoforms in non-drinkers (n=358),
light/moderate drinkers (n=677) and heavy drinkers (n=327) within the WHO/ISBRA
Study on State and Trait Markers of Alcohol Use and Dependence are found in Table 2.
The major differences in the transferrin glycoform pattern between the three drinking
categories were the higher levels of disialo- (P<0.0001) and trisialotransferrin
(P<0.001) in light/moderate drinkers and heavy drinkers compared with non-drinkers.
Also, there were no detectable amounts of asialotransferrin in non-drinkers, but in 2.2%
of the light/moderate drinkers and in 18.3% of the heavy drinkers.
Table 2. Distribution of serum transferrin glycoforms in different drinking categories.
Non-drinkers Light/Moderate drinkers Heavy drinkers
Serum samples, n 358 677 327
Transferrin glycoform
Unknown peak 0.63 ± 0.65 (n = 36) 0.39 ± 0.32 (n = 39) 0.65 ± 0.47 (n = 13)
0.47, 0.11-3.26* 0.22, 0.10-1.16 0.46, 0.11-1.53
Asialotransferrin (n = 0) 0.40 ± 0.23 (n = 15) 0.53 ± 0.48 (n = 60)
0.30, 0.16-0.90 0.39, 0.10-2.43
Monosialotransferrin 0.17 ± 0.06 (n = 200) 0.18 ± 0.09 (n = 323) 0.22 ± 0.12 (n = 197)
0.16, 0.10-0-58 0.16, 0.10-0.69 0.19, 0.10-0.90
Disialotransferrin 1.14 ± 0.19 1.34 ± 0.55 2.25 ± 1.57
1.14, 0.54-1.87 1.22, 0.50-5.87 1.72, 0.86-10.6
Trisialotransferrin 4.02 ± 1.10 4.38 ± 1.35 4.89 ± 1.46
3.89, 1.78-10.0 4.16, 1.45-10.4 4.64, 2.05-12.7
Tetrasialotransferrin 79.9 ± 1.75 79.7 ± 2.04 78.1 ± 3.23
80.1, 74.0-85.5 80.0, 68.3-84.7 78.7, 61.1-84.4
Pentasialotransferrin 14.0 ± 1.48 13.8 ± 1.64 13.8 ± 1.99
13.9, 9.52-19.4 13.7, 9.27-26.7 13.7, 9.37-22.2
Hexasialotransferrin 0.73 ± 0.36 (n = 348) 0.64 ± 0.35 (n = 646) 0.75 ± 0.45 (n = 311)
0.67, 0.11-2.72 0.59, 0.10-3.15 0.68, 0.11-2.80
*Mean ± SD, median, range.
18
When comparing the correlations between the serum transferrin glycoforms for all
samples, the strongest positive correlation (r=0.80) was obtained between disialo- and
asialotransferrin, whereas disialo- and asialotansferrin were negatively associated with
tetrasialotransferrin. These associations were dependent on the alcohol consumption
level. The level of trisialotransferrin was positively correlated with
monosialotransferrin but this association was indicated to be unrelated to the alcohol
consumption level.
When the relative amounts of serum transferrin glycoforms in non-drinkers from the
five different countries in the WHO/ISBRA project were compared, it could be seen
that the general differences were very small (Table 3). The only statistically significant
differences (P<0.05) observed were the higher mean levels of trisialotransferrin in the
Finnish and Japanese subjects compared with Australians, Brazilians and Canadians.
When the relative amounts of serum transferrin glycoforms for the non-drinkers of
different ethnic origin were compared, the general differences between the transferrin
glycoform levels were also found to be very small. In this case, the only statistically
significant difference observed was a lower trisialotransferrin level in Asian/Indians
compared with whites (P<0.05).
Compared with female non-drinkers (n=117), male non-drinkers (n=241) showed small
but statistically significant higher levels of tetrasialotransferrin (mean 79.5% vs. 80.2%
respectively) and lower levels of pentasilaotransferrin (mean 14.4% vs. 13.9%). Most
important for CDT testing was that there were no gender associated statistically
significant difference between the relative amounts of disialotransferrin (mean 1.16%
vs. 1.13%). When all non-drinkers were divided into four age groups (<31, 31-40, 41-
50, and >50 years; n=66-128/group) the only statistically significant difference between
the levels of transferrin glycoforms were the slightly lower tetrasialotransferrin level in
those aged 41-50 years compared with those <31 years. When all non-drinkers were
subdivided based on their BMI (<20, 20-24.9, 25-30 or >30). Those with a BMI >30
(obese individuals) showed a significantly (P<0.05) higher mean value for
disialotransferrin (mean 1.22%) compared with the other subgroups (range 1.11-
1.12%). Other small but statistically significant differences were the higher levels of
monosialotransferrin (mean 0.20% vs. 0.14-0.17%), trisialotransferrin (4.53% vs. 3.39-
4.07%) and lower levels of hexasialotransferrin (0.57% vs. 0.74-0.77%) for those with
a BMI <20 compared with the other BMI subgroups.
19
Tabl
e 3.
Dis
tribu
tion
of s
erum
tran
sfer
rin g
lyco
form
s in
non
-drin
kers
from
diff
eren
t stu
dy s
ites.
20
Significantly (P<0.05) higher disialotransferrin levels were found in smokers compared
with non-smokers for all 3 drinking categories. In non-drinkers, the disialotransferrin
mean value was 1.13% compared with 1.20% for smokers, but between the other
drinking categories the differences were higher. However, in the light/moderate and
heavy drinkers, the higher disialotransferrin levels in smokers could largely be
explained by a higher alcohol consumption level compared with non-smokers.
4.2 PAPER II The relative levels of different serum transferrin glycoforms in samples from the
WHO/ISBRA Study on State and Trait Markers of Alcohol Use and Dependence were
determined. There was a statistically significant difference between the relative
amounts of disialotransferrin (%DST) in men and women in both light/moderate
drinkers (mean 1.40% vs. 1.23%) and heavy drinkers (2.40% vs. 1.75%). When the
whole sample instead was divided into four age groups (<31, 31-40, 41-50 and >50
years), the only significant (P<0.05) difference in %DST was that heavy drinkers aged
41-50 years showed higher levels (mean 2.80%) compared with those aged <31 years
(2.08%) and >50 years (2.02%). Notably, the self reported average alcohol
consumption level during the last month was similar for all age subgroups (range for
means 74-95 g/day). When the whole sample was grouped based on body mass index
(BMI <20, 20-25, >25-30, >30), the only statistically significant (P<0.05) difference
was that heavy drinkers with a normal BMI of 20-25 showed higher %DST values
(mean 2.66%) compared with the other groups (range for means 1.53-2.05%), and
again this was with rather similar alcohol consumption levels for all BMI subgroups
(range for means 60-95 g/day).
Correlations of %DST, CDTect, GGT and AST with self-reported mean daily alcohol
consumption in the month prior to blood sampling are given in Table 4. For all drinkers
combined, and for light/moderate drinkers of both genders, and also for male heavy
drinkers, the strongest correlation with the self-reported alcohol intake was found for
%DST. In female heavy drinkers GGT was the strongest correlate with mean alcohol
intake.
21
Table 4. Correlations between self-reported mean daily alcohol consumption and serum levels of %disialotransferrin (%DST), CDT by CDTect, gamma-glutamyltransferase (GGT) and aspartate aminotransferase (AST).
Self-reported mean daily alcohol consumption
Light/Moderate drinkers Heavy drinkers All drinkers
Men Women Men Women
%DST
0.47***
(n = 436)
0.27***
(n = 241)
0.30***
(n = 250)
0.24*
(n = 77)
0.59***
(n = 1004)
CDTect
0.32***
(n = 444)
0.18**
(n = 245)
0.22***
(n = 259)
0.22
(n = 79)
0.31***
(n = 1027)
GGT
0.16*
(n = 442)
0.06
(n = 243)
0.13*
(n = 258)
0.31***
(n = 78)
0.34***
(n = 1021)
AST
0.14**
(n = 442)
0.00
(n = 243)
0.20*
(n = 258)
0.26*
(n = 78)
0.25***
(n = 1021)
*** P<0.0001, **P<0.01, *P<0.05
Figure 4. Receiver-operating characteristic (ROC) analysis was used to distinguish female and male heavy drinkers from the combination of non-drinkers and light/moderate drinkers by measurement of serum %disialotransferrin. ROC analysis was also used analysing the CDTect and GGT values for non-drinkers and light/moderate drinkers compared with heavy drinkers.
0 20 40 60 80 100
80
60
40
20
0
Sens
itivi
ty (%
)
%DST Men
%DST Women
GGT
CDTect
100-Specificity (%)
22
For evaluation of the overall test accuracy of %DST as an alcohol biomarker and for
comparision with CDTect, GGT and AST, receiver-operating characteristics (ROC)
analysis was performed (Figure 4). The area under the ROC curves (AUC) for the
combination of the non-drinkers and light/moderate drinkers in comparison with heavy
drinkers was not significantly different between men (AUC 0.83) and women (0.82).
The AUC for %DST was significantly (P<0.001) higher than for CDTect (0.68) and
GGT (0.69). The sensitivities and specificities of serum %DST for “heavy drinking”,
according to the WHO/ISBRA Interview Schedule classification, at different threshold
limits are shown in Table 5 for all subjects combined and for men and women
separately. At any potential cut-off, women showed lower sensitivity but higher
specificity compared with men.
Table 5. Comparisons of sensitivities and specificities of serum %disialotransferrin (%DST) for “heavy drinking” at different cut-off limits for all subjects combined and for men and women separately.
Non-drinkers + Light/Moderate drinkers vs. Heavy drinkers
All subjects Men Women
%DST cut-off Sensitivity Specificity Sensitivity Specificity Sensitivity Specificity
1.5 66.1 87.0 68.8 84.5 57.1 91.6
1.6 59.6 90.7 63.2 88.5 48.1 95.0
1.7 51.1 92.8 55.6 90.7 35.1 96.6
1.8 44.6 94.4 48.8 92.9 31.2 97.5
1.9 38.2 95.2 42.8 93.6 23.4 98.0
2.0 36.1 95.9 40.8 94.4 20.8 98.9
23
4.3 PAPER III The relative disialotransferrin level as determined by HPLC in samples collected from
subjects with various clinical conditions or undergoing medication with drugs
previously reported to cause non-alcohol related elevations of CDT (end-stage liver
disease, diabetes mellitus type 2, enzyme or non-enzyme inducing AEDs, CRP > 100
mg/L and CF) are given in Table 6. None of the groups showed a statistically
significant higher %disialotransferrin level in comparison with the average level for the
whole sample.
Table 6. Relative amount of disialotransferrin to total transferrin in samples originating from subjects with clinical conditions or under medications previously reported to cause false-positive CDT levels.
Clinical condition or medication Disialotransferrin
(% of total transferrin)
End-stage liver diseases (n = 50)
Primary biliary cirrhosis (n=17)
Haemochromatosis (n=8)
Hepatitis C (n=10)
Others (n=15)
1.42, 3.22, 1.27, 0.90 - 5.07*
1.22, 1.72, 1.20, 1.01 - 1.72
2.03, 5.07, 1.53, 1.14 - 5.07
1.35, 2.16, 1.15, 1.07 - 2.16
1.40, 2.60, 1.31, 0.90 - 2.60 Diabetes Type 2 (n = 46) 1.18, 1.64, 1.17, 0.78 - 1.81
Antiepileptic drugs
Enzyme inducing (n = 31)
(carbamazepine, phenytoin)
1.41, 4.91, 1.22, 0.81 - 5.50
Non-enzyme inducing (n=12)
(valproate, lamotrigine)
1.22, 1.48, 1.18, 1.06 - 1.48
CRP > 100 mg/L (n=15) 1.15, 1.50, 1.16, 0.62 - 1.50
Cystic fibrosis (n=24) 1.21, 1.73, 1.20, 0.90 - 1.76
*Mean, 97.5th percentile, median and range
Of the 178 samples, only 9 (5%) had a %disialotransferrin level at or above 1.8% and
were thus considered “positive”. Of the positive samples, 6 originated from patients
with end-stage liver disease, 1 from a patient with type 2 diabetes and 2 from patients
taking enzyme-inducing AED. The samples collected from subjects with end-stage
liver diseases were further categorized into the four subgroups primary biliary cirrhosis
(n = 17), haemochromatosis (n = 8), hepatitis C (n = 10), and “others” (including
autoimmune hepatitis, toxic liver damage, non-alcoholic steatohepatitis and primary
24
sclerosing cholangitis; n = 14) (Table 6). The highest frequency of positive results was
found in subjects with haemochromatosis with 3 of 8 (38%) samples showing
%disialotransferrin levels ≥ 1.8%.
4.4 PAPER IV The Bio-Rad %CDT by HPLC test allowed for reproducible separation of the asialo-,
disialo-, trisialo-, tetrasialo-, and pentasialotransferrin glycoforms within ~6 min and
the total analysis time for one sample was ~10 min. Genetic transferrin variants and
glycoform types known to cause falsely high or low results with the ion-exchange
minicolumn–immunoassay combination for %CDT, such as the transferrin CD and
BC heterozygotes, produced similar unique peak patterns, and were readily identified,
by either HPLC method. The disialotransferrin values obtained for the 150 clinical
sera by the Bio-Rad %CDT by HPLC test (mean 3.61%, range 0.6–21.4%) and the
HPLC candidate reference method (mean 3.87%, range 0.7–22.4%) were highly
correlated (r2=0.998, p<0.0001), and no outliers were noted (Figure 5). The HPLC
candidate reference method produced slightly higher disialotransferrin values (+0.20–
0.25% on average) over the entire measuring range.
Figure 5. Correlation between relative disialotransferrin values obtained using the Bio-Rad %CDT by HPLC test and the HPLC candidate reference method. The dashed line is x=y.
0 5 10 15 20 25
25
20
15
10
5
0
Rel
ativ
e di
sial
otra
nsfe
rrin
valu
es
by th
e Bi
o-R
ad %
CD
T te
st (%
)
Relative disialotransferrin values by the HPLC candidate reference method (%)
25
4.5 PAPER V The HPLC and CE methods allowed for reproducible separation and quantification of
single transferrin glycoforms with similar peak patterns. Rare genetic transferrin
variants and glycoform types, including transferrin B homozygotes and BC and CD
heterozygotes, another variant tentatively identified as “C2C3”, and serum samples
containing high relative amounts of monosialo- and trisialotransferrin, all identified
as actual or potential causes of falsely high or low %CDT results with the
minicolumn immunoassays, were readily identified by both methods. The relative
amounts of disialotransferrin to total transferrin obtained by HPLC and CE were
highly correlated (r2=0.972; P<0.0001; Figure 6). However, the HPLC method
constantly yielded higher results, the values being 1.36% higher, on average (range,
0.15%–4.20%; P<0.0001), than the CE values.
25
Figure 6. Passing and bablok regression line (solid line) with 95% confidence interval (dashed lines) for relative disialotransferrin values (in percentage to total transferrin) obtained by HPLC and CE.
0 5 10 15 20 25 Disialotransferrin by HPLC (%)
20
15 10
5
0
Dis
ialo
trans
ferri
n by
CE
(%)
26
4.6 PAPER VI Sera from CDG-I patients showed increased relative amounts of disialo- and
asialotransferrin and concomitant reductions in tetrasialotransferrin (Figure 7).
Patients with the CDG-Ia subtype had the highest amounts of disialo- (range, 19–
42%) and asialotransferrin (3.4–26%), whereas the patients with type Ib and Ig CDG
had less asialotransferrin (<3%). This compares with disialotransferrin concentrations
<2% and undetectable asialotransferrin in the controls. In heavy drinkers, disialo- and
asialotransferrin concentrations were 0.8–16% and 0–4.0% of total transferrin,
respectively. After the CDG-Ib patient was treated with low-dose mannose, the
abnormal transferrin pattern improved, as indicated by marked reductions in disialo-
(from 18% to 6%) and asialotransferrin (from 2.6% to 0.7%).
Time (min) 5 10 15 20 25
0.3
0.6
0.9
1.2
Abs
orba
nce
(mA
U)
1.5
0.0
Dis
ialo
trans
ferri
n
Tris
ialo
trans
ferr
in
Tetra
sial
o-tra
nsfe
rrin
Pen
tasi
alot
rans
ferri
n
Hex
asia
lotra
nsfe
rrin
Asi
alot
rans
ferr
in
b
Mon
osia
lotra
nsfe
rrin
CDG-Ia
Time (min) 5 10 15 20 25
0.3
0.6
0.9
1.2
Dis
ialo
trans
ferri
n
Tris
ialo
trans
ferr
in
Tetra
sial
otra
nsfe
rrin
Pent
asia
lotra
nsfe
rrin
Hex
asia
lotra
nsfe
rrin
Abs
orba
nce
(mA
U)
1.5
0.0
a
Asi
alot
rans
ferr
in
Mon
osia
lotra
nsfe
rrin
Control Alcohol
Time (min) 5 10 15 20 25
0.3
0.6
0.9
1.2
Abs
orba
nce
(mA
U)
1.5
0.0
cCDG-Ib
Asi
alot
rans
ferri
n
Dis
ialo
trans
ferri
n
Tetra
sial
otra
nsfe
rrin
Before mannoseAfter mannose
Time (min) 5 10 15 20 25
0.3
0.6
0.9
1.2
Abs
orba
nce
(mA
U)
1.5
0.0
Dis
ialo
trans
ferri
n
Tris
ialo
trans
ferr
in
Tetra
sial
o-tra
nsfe
rrin
Pen
tasi
alot
rans
ferri
n
Hex
asia
lotra
nsfe
rrin
Asi
alot
rans
ferr
in
d
Mon
osia
lotra
nsfe
rrin
CDG-II
BA
Time (min) 5 10 15 20 25
0.3
0.6
0.9
1.2
Abs
orba
nce
(mA
U)
1.5
0.0
Dis
ialo
trans
ferri
n
Tris
ialo
trans
ferr
in
Tetra
sial
o-tra
nsfe
rrin
Pen
tasi
alot
rans
ferri
n
Hex
asia
lotra
nsfe
rrin
Asi
alot
rans
ferr
in
b
Mon
osia
lotra
nsfe
rrin
CDG-Ia
Time (min) 5 10 15 20 25
0.3
0.6
0.9
1.2
Abs
orba
nce
(mA
U)
1.5
0.0
Dis
ialo
trans
ferri
n
Tris
ialo
trans
ferr
in
Tetra
sial
o-tra
nsfe
rrin
Pen
tasi
alot
rans
ferri
n
Hex
asia
lotra
nsfe
rrin
Asi
alot
rans
ferr
in
b
Mon
osia
lotra
nsfe
rrin
CDG-Ia
Time (min) 5 10 15 20 25
0.3
0.6
0.9
1.2
Dis
ialo
trans
ferri
n
Tris
ialo
trans
ferr
in
Tetra
sial
otra
nsfe
rrin
Pent
asia
lotra
nsfe
rrin
Hex
asia
lotra
nsfe
rrin
Abs
orba
nce
(mA
U)
1.5
0.0
a
Asi
alot
rans
ferr
in
Mon
osia
lotra
nsfe
rrin
Control Alcohol
Time (min) 5 10 15 20 25
0.3
0.6
0.9
1.2
Dis
ialo
trans
ferri
n
Tris
ialo
trans
ferr
in
Tetra
sial
otra
nsfe
rrin
Pent
asia
lotra
nsfe
rrin
Hex
asia
lotra
nsfe
rrin
Abs
orba
nce
(mA
U)
1.5
0.0
a
Asi
alot
rans
ferr
in
Mon
osia
lotra
nsfe
rrin
Control AlcoholControl Alcohol
Time (min) 5 10 15 20 25
0.3
0.6
0.9
1.2
Abs
orba
nce
(mA
U)
1.5
0.0
cCDG-Ib
Asi
alot
rans
ferri
n
Dis
ialo
trans
ferri
n
Tetra
sial
otra
nsfe
rrin
Before mannoseAfter mannose
Time (min) 5 10 15 20 25
0.3
0.6
0.9
1.2
Abs
orba
nce
(mA
U)
1.5
0.0
cCDG-Ib
Asi
alot
rans
ferri
n
Dis
ialo
trans
ferri
n
Tetra
sial
otra
nsfe
rrin
Before mannoseAfter mannoseBefore mannoseAfter mannose
Time (min) 5 10 15 20 25
0.3
0.6
0.9
1.2
Abs
orba
nce
(mA
U)
1.5
0.0
Dis
ialo
trans
ferri
n
Tris
ialo
trans
ferr
in
Tetra
sial
o-tra
nsfe
rrin
Pen
tasi
alot
rans
ferri
n
Hex
asia
lotra
nsfe
rrin
Asi
alot
rans
ferr
in
d
Mon
osia
lotra
nsfe
rrin
CDG-II
BA
Time (min) 5 10 15 20 25
0.3
0.6
0.9
1.2
Abs
orba
nce
(mA
U)
1.5
0.0
Dis
ialo
trans
ferri
n
Tris
ialo
trans
ferr
in
Tetra
sial
o-tra
nsfe
rrin
Pen
tasi
alot
rans
ferri
n
Hex
asia
lotra
nsfe
rrin
Asi
alot
rans
ferr
in
d
Mon
osia
lotra
nsfe
rrin
CDG-II
BA
Figure 7. Shown in (a) are HPLC chromatograms for a control serum from a light drinker, showing the predominant transferrin C homozygous variant (solid line), and for serum from a heavy drinker with increased asialo- and disialotransferrin (dashed line). (b), serum from a CDG-Ia patient showing markedly increased asialo- and disialotransferrin and reduced tetrasialotransferrin. (c), serum from a CDG-Ib patient showing increased asialo- and disialotransferrin (solid line) and another sample from the same patient after mannose therapy (dashed line). (d), serum from a CDG-II patient with uncharacterized defects (type IIx) showing increased mono- and trisialotransferrin and reduced tetrasialotransferrin, as well as two unknown peaks (A and B).
27
Sera from patients with undefined CDG-IIx defects had the type II pattern with
typical increases in trisialo- (range, 7.1–32%) and monosialotransferrin (5.7–15%),
indicating the presence of truncated glycans. This compares with trisialotransferrin
values typically <8% in controls and heavy drinkers, and monosialotransferrin was
measurable only in individuals with high trisialotransferrin. In all four CDG-II sera,
two unidentified peaks were also observed (Figure 7). In the control group, children
up to 3 weeks of age, 6 of 13 (46%) showed a disialotransferrin concentration below
the range in older children, adolescents, and adults. Trisialotransferrin concentrations
were below the adult range in 9 of 11 (82%) children 1–9 months of age and 7 of 18
(39%) of those 1–18 years of age, and penta- + hexasialotransferrin concentrations
were above the adult range in ~50% of the children in both age groups. Otherwise,
there were no marked age-related differences in the relative amounts of transferrin
glycoforms, and no gender differences were observed in children and adolescents.
Our results demonstrate that measurement of serum transferrin glycoforms by HPLC
can be used for preliminary diagnosis of CDG and for assignment of cases to either
type I or type II.
28
5 DISCUSSION The original definition of CDT as the sum of asialo-, monosialo- and disialotransferrin
was closely related to the analytical methods that were available for CDT analysis at
the time, methods that only could measure those added fractions (47). Later scientific
work with more specific methods for transferrin glycoform analysis, further confirmed
in this thesis, has proven that the only transferrin glycoforms clearly related to chronic
heavy drinking in a dose-dependent manner are asialo- and disialotransferrin (57, 109).
With that background, disialotransferrin was recommended to be the primary target
molecule for CDT analysis by an IFCC working group on CDT standardization (111).
Over the years there have been numerous reports on non-alcohol related reasons for
differences in the transferrin glycoform pattern (4, 48, 70). This thesis shows that there
on the contrary are minimal differences in the serum transferrin glycoform pattern
between non-drinkers from different countries and of different ethnicity, gender, age
and BMI. When it comes to disialotransferrin, the primary glycoform in CDT, some
small differences could be seen between groups with different ethnic origin, BMI, age
and gender. Although sometimes reaching statistical significance, these differences in
relative amounts of disialotransferrin in non-drinkers were never big enough to even
hypothetically cause any systematical misinterpretations with respect to CDT testing,
i.e. clinical false positive samples. A question that has been discussed in many reports
on CDT is the potential difference in CDT sensitivity between men and women. Based
on the drinking limits for men and women for each drinking category within the
WHO/ISBRA project, the ROC curve analysis did not reveal any statistically
significant gender difference in the detection of heavy drinkers. That said, male
light/moderate and heavy drinkers in general showed slightly higher relative mean
levels of disialotransferin compared with women, and showed higher correlations
between the different biomarkers of alcohol analyzed. It should be remembered that
most of the early reports on CDT were performed with CDTect, a method using
different reference values for men and women. It seems highly plausible that many of
the reports on non-alcohol related differences in the transferrin glycoform pattern due
to different physiological or clinical factors instead were linked to the analysis
methodology used. In general, disialotransferrin performed much better as a laboratory
biomarker for prolonged alcohol abuse than AST and GGT, much because of its higher
29
specificity, but disialotansferrin also showed superior sensitivity in most subgroups
examined compared with the other laboratory markers.
When samples from subjects belonging to different groups with previously reported
clinical risk factors for non-alcohol induced elevated CDT were analyzed, only ~5%
had a relative disialotransferrin level over the upper limit for the reference interval of
the HPLC method used. Notably, all samples within the study came from subjects with
an unclear drinking history, meaning that heavy drinking could not be excluded. As
already mentioned above, there are reasons to believe that most of the reports on non-
alcohol related differences in the transferrin glycoform pattern are linked to the non-
specific methodology used for CDT analysis, rather than representing true
physiological or pharmacological influences. An interesting exception was the relative
disialotransferrin levels in samples from subjects with haemochromatosis, where 3 of 8
were elevated. This clinical condition needs further investigation.
Asialotransferrin is a potential laboratory marker of prolonged alcohol abuse, its main
advantage being the very high specificity, theoretically 100%, or close. When
compared with disialotransferrin in Paper II and IV in this thesis, asialotransferrin in
general showed a much lower sensitivity for identification of heavy drinking. Perhaps
with development of new and much more sensitive analytical methods for identification
of very low concentrations of asialotransferrin in serum, this might be a promising
candidate marker for identification of chronic heavy drinking.
Immunoassays that do not identify different genetic transferrin variants, and thus are
likely to produce false positive and false negative results, should always be used
together with a reference method that do (119). The HPLC and CE methods evaluated
in this thesis all showed high correlation and allowed for reproducible separation and
quantification of single transferrin glycoforms with similar peak patterns. Different
genetic transferrin variants were readily identified with all evaluated methods.
Paper VI shows that CDG testing could be combined with CDT testing by HPLC.
This could enable testing for the preliminary diagnosis of CDG to be carried out in
many more clinical laboratories. This could counteract the underdiagnosis of CDG
that probably exists due to a combination of unspecific clinical symptoms and a lack
of reference methods for CDG testing in most clinical laboratories.
30
6 CONCLUSIONS CDT, defined as the relative amount of disialotransferrin to total transferrin
(%disialotransferrin), is a biomarker of chronic alcohol abuse with very high specificity
and medium sensitivity.
With respect to CDT testing, the results in this thesis indicate that adjustment of
reference intervals for %disialotransferrin in relation to ethnicity, age, gender, BMI and
smoking is not required.
In a study population with 1387 subjects from five different countries, the relative
concentration of serum disialotransferrin in general performed better than GGT and
AST, two traditional biomarkers of alcohol abuse.
It is most likely that reports on clinical and pharmacological factors reported to cause
false-positive CDT levels performed with methods for CDT analysis that don’t have the
ability to measure single glycorforms separately or don’t identify genetic transferrin
variants needs re-evaluation. Many of these findings are probably linked to the
methodologies used for CDT analysis, rather than representing true physiological or
pharmacological influences on the transferrin glycosylation pattern.
Asialotransferrin might in the future be a potential biomarker of prolonged alcohol
abuse, its main advantage being a superior specificity. But with the analytical
methodology available today the sensitivity in general is too low compared with the
relative level of disialotransferrin.
The Bio-Rad %CDT HPLC test and the CEofix™ CDT assay are appropriate for
confirmatory and routine %CDT testing. They showed an overall good correlation and
agreement with the corresponding results of a HPLC candidate reference method.
The HPLC candidate reference method could readily be used for preliminary diagnosis
of CDG and for assignment of cases to either CDG-I or CDG-II.
31
7 ACKNOWLEDGEMENTS This work was carried out at the Karolinska Institutet, Stockholm, Sweden. Many persons have contributed to and supported this work in different ways. Very often have I been inspired and impressed by all your knowledge and skills. I would like to express my sincere gratitude to all of you and especially to: Anders Helander, my supervisor, for excellent guidance, invaluable support and encouragement and for always being full of ideas and ready for discussion. Hudson Freeze, Jos Wielders and Riekie te Stroet, my co-authors, for great scientific knowledge and fruitful co-operation. Helen Dahl, for great collaboration, support, and for looking after me ever since my first day at the Alcohol Laboratory. Kristian Björnstad, for support, friendship and endless movie discussions. Good luck with finishing you Ph.D. studies! So many drugs, so little time... Naama Kenan, for finally having someone to discuss all my memories from my time in Israel with, and for being a great friend. Toda! Yufang Zheng, for always putting me in a good mood. Take good care of the baby! Thomas Gustafsson, Eva Lindmark and the rest of the CDT laboratory at the Karolinska University Hospital. You’ve always been kind and helpful to me, and I truly appreciate your assistance over the years. Jan-Olov Jeppsson, Anna Arnetorp and the rest of the CDT laboratory at the Malmö University Hospital. For great co-operation, enthusiasm and professionalism. Wayne Jones, my co-supervisor during my master’s thesis work. For all good advices on science and writing. Olof Beck, for being a scientific role model in every way and for kindly sharing your knowledge about ducks. Bim Linderholm, Andreas Almlén, Marie Hegerstrand-Björkman and Guido Stichtenoth at the Surphactant Laboratory for friendship, encouragement and many laughs. Past Alcohol Laboratory and Surphactant Laboratory employees for good company, interest and support. Stefan Borg and Hans Bergman, for financial support and for allowing me to launch my Ph.D. project to begin with. Eva Severinsson and Camilla Ahlqvist, from the Stockholm Graduate School of Biomedical Research for giving me the opportunity to start exploring the wonderful world of biomedical sciences. Mats Fjellner, for via MSN Messenger, live and direct from various parts of Spain, keeping me company during thousands of hours in the lab. And for over the last years keeping me company during ~1500 kilometres of trekking in Spain, Nepal and Catalunya. Malin Roiha, for many discussions on philosophy, vegan food, music and Catalan beer brands, and for reminding me to visit Barcelona as often as possible.
32
Katja Kozian, for always making me smile and simply just being a fantastic person. Mattias Bergman and Amanda Derwinger, friends, neighbours and baby-sitters. With more neighbours like you, I would never leave my neighbourhood. Gunnar Ljungqvist, for tons of encouragement, being a great company during numerous cultural activities, and for teaching me a lot about wine, not only in theory but also in practice. Erik Södersten, fellow Ph.D. student and long time friend. For fantastic discussions and adventures over the years. Erik Andersson, fellow Ph.D. student, for excellent lunch company and for being not only the tallest guy I know, but also the friendliest. Fredrik Lundberg, for always being worse off than I am, and for great company at the Camp Nou during el Clásico. Robert Lindberg, for great friendship and spiritual guidance. Joakim Bergström and Malin Norman, for always being interested and supportive, with many questions and great curiosity. With persons like you around, living is easy. Göran and Gun-Inger Bergström, my parents, for always being there. Dante Wahlund, who arrived three days before I was supposed to hold my half-time seminar. Thank you for being the best child one could ever possibly imagine and for always encouraging me to wake up early. Katarina Wahlund, for endless support and encouragement during all those years, but above all, for being exactly who you are. Puss!
“Ett stort tack till er alla!” / J B
33
8 REFERENCES 1. Room R, Babor T, Rehm J. Alcohol and public health. Lancet 2005;365:519-
30. 2. Saunders JB, Aasland OG, Babor TF, de la Fuente JR, Grant M. Development
of the Alcohol Use Disorders Identification Test (AUDIT): WHO Collaborative Project on Early Detection of Persons with Harmful Alcohol Consumption--II. Addiction 1993;88:791-804.
3. Allen JP, Litten RZ, Fertig JB, Babor T. A review of research on the Alcohol Use Disorders Identification Test (AUDIT). Alcohol Clin Exp Res 1997;21:613-9.
4. Bortolotti F, De Paoli G, Tagliaro F. Carbohydrate-deficient transferrin (CDT) as a marker of alcohol abuse: a critical review of the literature 2001-2005. J Chromatogr B Analyt Technol Biomed Life Sci 2006;841:96-109.
5. Mayfield D, McLeod G, Hall P. The CAGE questionnaire: validation of a new alcoholism screening instrument. Am J Psychiatry 1974;131:1121-3.
6. Ewing JA. Detecting alcoholism. The CAGE questionnaire. Jama 1984;252:1905-7.
7. Feunekes GI, van 't Veer P, van Staveren WA, Kok FJ. Alcohol intake assessment: the sober facts. Am J Epidemiol 1999;150:105-12.
8. Helander A. Biological markers in alcoholism. J Neural Transm Suppl 2003:15-32.
9. Hannuksela ML, Liisanantti MK, Nissinen AE, Savolainen MJ. Biochemical markers of alcoholism. Clin Chem Lab Med 2007;45:953-61.
10. Wurst FM, Alling C, Aradottir S, Pragst F, Allen JP, Weinmann W, et al. Emerging biomarkers: new directions and clinical applications. Alcohol Clin Exp Res 2005;29:465-73.
11. Swift R. Direct measurement of alcohol and its metabolites. Addiction 2003;98 Suppl 2:73-80.
12. Jones AW. Excretion of alcohol in urine and diuresis in healthy men in relation to their age, the dose administered and the time after drinking. Forensic Sci Int 1990;45:217-24.
13. Schmitt G, Aderjan R, Keller T, Wu M. Ethyl glucuronide: an unusual ethanol metabolite in humans. Synthesis, analytical data, and determination in serum and urine. J Anal Toxicol 1995;19:91-4.
14. Helander A, Beck O. Mass spectrometric identification of ethyl sulfate as an ethanol metabolite in humans. Clin Chem 2004;50:936-7.
15. Wurst FM, Kempter C, Seidl S, Alt A. Ethyl glucuronide--a marker of alcohol consumption and a relapse marker with clinical and forensic implications. Alcohol Alcohol 1999;34:71-7.
16. Wurst FM, Dresen S, Allen JP, Wiesbeck G, Graf M, Weinmann W. Ethyl sulphate: a direct ethanol metabolite reflecting recent alcohol consumption. Addiction 2006;101:204-11.
17. Dahl H, Stephanson N, Beck O, Helander A. Comparison of urinary excretion characteristics of ethanol and ethyl glucuronide. J Anal Toxicol 2002;26:201-4.
18. Helander A, Beck O. Ethyl sulfate: a metabolite of ethanol in humans and a potential biomarker of acute alcohol intake. J Anal Toxicol 2005;29:270-4.
19. Stephanson N, Dahl H, Helander A, Beck O. Direct quantification of ethyl glucuronide in clinical urine samples by liquid chromatography-mass spectrometry. Ther Drug Monit 2002;24:645-51.
20. Bottcher M, Beck O, Helander A. Evaluation of a New Immunoassay for Urinary Ethyl Glucuronide Testing. Alcohol Alcohol 2007.
21. Esteve-Turrillas FA, Bicker W, Lammerhofer M, Keller T, Lindner W. Determination of ethyl sulfate--a marker for recent ethanol consumption--in human urine by CE with indirect UV detection. Electrophoresis 2006;27:4763-71.
22. Voltaire A, Beck O, Borg S. Urinary 5-hydroxytryptophol: a possible marker of recent alcohol consumption. Alcohol Clin Exp Res 1992;16:281-5.
34
23. Helander A, Beck O, Jacobsson G, Lowenmo C, Wikstrom T. Time course of ethanol-induced changes in serotonin metabolism. Life Sci 1993;53:847-55.
24. Helander A, Beck O, Borg S. The use of 5-hydroxytryptophol as an alcohol intake marker. Alcohol Alcohol Suppl 1994;2:497-502.
25. Beck O, Borg S, Eriksson L, Lundman A. 5-hydroxytryptophol in the cerebrospinal fluid and urine of alcoholics and healthy subjects. Naunyn Schmiedebergs Arch Pharmacol 1982;321:293-7.
26. Helander A, Beck O, Wennberg M, Wikstrom T, Jacobsson G. Determination of urinary 5-hydroxyindole-3-acetic acid by high-performance liquid chromatography with electrochemical detection and direct sample injection. Anal Biochem 1991;196:170-3.
27. Stephanson N, Helander A, Beck O. Alcohol biomarker analysis: simultaneous determination of 5-hydroxytryptophol glucuronide and 5-hydroxyindoleacetic acid by direct injection of urine using ultra-performance liquid chromatography-tandem mass spectrometry. J Mass Spectrom 2007;42:940-9.
28. Niemela O. Biomarkers in alcoholism. Clin Chim Acta 2007;377:39-49. 29. Neumann T, Spies C. Use of biomarkers for alcohol use disorders in clinical
practice. Addiction 2003;98 Suppl 2:81-91. 30. Hietala J, Puukka K, Koivisto H, Anttila P, Niemela O. Serum gamma-glutamyl
transferase in alcoholics, moderate drinkers and abstainers: effect on gt reference intervals at population level. Alcohol Alcohol 2005;40:511-4.
31. Conigrave KM, Davies P, Haber P, Whitfield JB. Traditional markers of excessive alcohol use. Addiction 2003;98 Suppl 2:31-43.
32. Puukka K, Hietala J, Koivisto H, Anttila P, Bloigu R, Niemela O. Age-related changes on serum ggt activity and the assessment of ethanol intake. Alcohol Alcohol 2006;41:522-7.
33. Puukka K, Hietala J, Koivisto H, Anttila P, Bloigu R, Niemela O. Obesity and the clinical use of serum GGT activity as a marker of heavy drinking. Scand J Clin Lab Invest 2007;67:480-8.
34. Hietala J, Koivisto H, Anttila P, Niemela O. Comparison of the combined marker GGT-CDT and the conventional laboratory markers of alcohol abuse in heavy drinkers, moderate drinkers and abstainers. Alcohol Alcohol 2006;41:528-33.
35. Rosman AS, Lieber CS. Diagnostic utility of laboratory tests in alcoholic liver disease. Clin Chem 1994;40:1641-51.
36. Allen JP, Litten RZ. The role of laboratory tests in alcoholism treatment. J Subst Abuse Treat 2001;20:81-5.
37. Sillanaukee P. Laboratory markers of alcohol abuse. Alcohol Alcohol 1996;31:613-6.
38. Conigrave KM, Saunders JB, Whitfield JB. Diagnostic tests for alcohol consumption. Alcohol Alcohol 1995;30:13-26.
39. Hansson P, Caron M, Johnson G, Gustavsson L, Alling C. Blood phosphatidylethanol as a marker of alcohol abuse: levels in alcoholic males during withdrawal. Alcohol Clin Exp Res 1997;21:108-10.
40. Hartmann S, Aradottir S, Graf M, Wiesbeck G, Lesch O, Ramskogler K, et al. Phosphatidylethanol as a sensitive and specific biomarker: comparison with gamma-glutamyl transpeptidase, mean corpuscular volume and carbohydrate-deficient transferrin. Addict Biol 2007;12:81-4.
41. Aradottir S, Asanovska G, Gjerss S, Hansson P, Alling C. PHosphatidylethanol (PEth) concentrations in blood are correlated to reported alcohol intake in alcohol-dependent patients. Alcohol Alcohol 2006;41:431-7.
42. Varga A, Hansson P, Johnson G, Alling C. Normalization rate and cellular localization of phosphatidylethanol in whole blood from chronic alcoholics. Clin Chim Acta 2000;299:141-50.
43. Aradottir S, Olsson BL. Methodological modifications on quantification of phosphatidylethanol in blood from humans abusing alcohol, using high-performance liquid chromatography and evaporative light scattering detection. BMC Biochem 2005;6:18.
35
44. Tolonen A, Lehto TM, Hannuksela ML, Savolainen MJ. A method for determination of phosphatidylethanol from high density lipoproteins by reversed-phase HPLC with TOF-MS detection. Anal Biochem 2005;341:83-8.
45. de Jong G, van Dijk JP, van Eijk HG. The biology of transferrin. Clin Chim Acta 1990;190:1-46.
46. Rustad P, Felding P, Franzson L, Kairisto V, Lahti A, Martensson A, et al. The Nordic Reference Interval Project 2000: recommended reference intervals for 25 common biochemical properties. Scand J Clin Lab Invest 2004;64:271-84.
47. Stibler H. Carbohydrate-deficient transferrin in serum: a new marker of potentially harmful alcohol consumption reviewed. Clin Chem 1991;37:2029-37.
48. Arndt T. Carbohydrate-deficient transferrin as a marker of chronic alcohol abuse: a critical review of preanalysis, analysis, and interpretation. Clin Chem 2001;47:13-27.
49. Stibler H, Kjellin KG. Isoelectric focusing and electrophoresis of the CSF proteins in tremor of different origins. J Neurol Sci 1976;30:269-85.
50. Kamboh MI, Ferrell RE. Human transferrin polymorphism. Hum Hered 1987;37:65-81.
51. van Noort WL, de Jong G, van Eijk HG. Purification of isotransferrins by concanavalin A sepharose chromatography and preparative isoelectric focusing. Eur J Clin Chem Clin Biochem 1994;32:885-92.
52. van Eijk HG, van Noort WL, de Jong G, Koster JF. Human serum sialo transferrins in diseases. Clin Chim Acta 1987;165:141-5.
53. van Eijk HG, van Noort WL. The analysis of human serum transferrins with the PhastSystem: quantitation of microheterogeneity. Electrophoresis 1992;13:354-8.
54. Martensson O, Harlin A, Brandt R, Seppa K, Sillanaukee P. Transferrin isoform distribution: gender and alcohol consumption. Alcohol Clin Exp Res 1997;21:1710-5.
55. Stibler H, Allgulander C, Borg S, Kjellin KG. Abnormal microheterogeneity of transferrin in serum and cerebrospinal fluid in alcoholism. Acta Med Scand 1978;204:49-56.
56. Stibler H, Borg S, Allgulander C. Clinical significance of abnormal heterogeneity of transferrin in relation to alcohol consumption. Acta Med Scand 1979;206:275-81.
57. Helander A, Eriksson G, Stibler H, Jeppsson JO. Interference of transferrin isoform types with carbohydrate-deficient transferrin quantification in the identification of alcohol abuse. Clin Chem 2001;47:1225-33.
58. Stibler H, Borg S. Glycoprotein glycosyltransferase activities in serum in alcohol-abusing patients and healthy controls. Scand J Clin Lab Invest 1991;51:43-51.
59. Lakshman MR, Rao MN, Marmillot P. Alcohol and molecular regulation of protein glycosylation and function. Alcohol 1999;19:239-47.
60. Xin Y, Lasker JM, Lieber CS. Serum carbohydrate-deficient transferrin: mechanism of increase after chronic alcohol intake. Hepatology 1995;22:1462-8.
61. Helander A, Tabakoff B. Biochemical markers of alcohol use and abuse: experiences from the Pilot Study of the WHO/ISBRA Collaborative Project on state and trait markers of alcohol. International Society for Biomedical Research on Alcoholism. Alcohol Alcohol 1997;32:133-44.
62. Stowell LI, Fawcett JP, Brooke M, Robinson GM, Stanton WR. Comparison of two commercial test kits for quantification of serum carbohydrate-deficient transferrin. Alcohol Alcohol 1997;32:507-16.
63. Legros FJ, Nuyens V, Baudoux M, Zouaoui Boudjeltia K, Ruelle JL, Colicis J, et al. Use of capillary zone electrophoresis for differentiating excessive from moderate alcohol consumption. Clin Chem 2003;49:440-9.
64. Landberg E, Pahlsson P, Lundblad A, Arnetorp A, Jeppsson JO. Carbohydrate composition of serum transferrin isoforms from patients with high alcohol consumption. Biochem Biophys Res Commun 1995;210:267-74.
36
65. Henry H, Froehlich F, Perret R, Tissot JD, Eilers-Messerli B, Lavanchy D, et al. Microheterogeneity of serum glycoproteins in patients with chronic alcohol abuse compared with carbohydrate-deficient glycoprotein syndrome type I. Clin Chem 1999;45:1408-13.
66. Randell E, Diamandis EP, Goldberg DM. Changes in serum carbohydrate-deficient transferrin and gammaglutamyl transferase after moderate wine consumption in healthy males. J Clin Lab Anal 1998;12:92-7.
67. Whitfield JB, Fletcher LM, Murphy TL, Powell LW, Halliday J, Heath AC, Martin NG. Smoking, obesity, and hypertension alter the dose-response curve and test sensitivity of carbohydrate-deficient transferrin as a marker of alcohol intake. Clin Chem 1998;44:2480-9.
68. Lesch OM, Walter H, Antal J, Heggli DE, Kovacz A, Leitner A, et al. Carbohydrate-deficient transferrin as a marker of alcohol intake: a study with healthy subjects. Alcohol Alcohol 1996;31:265-71.
69. van Pelt J, Leusink GL, van Nierop PW, Keyzer JJ. Test characteristics of carbohydrate-deficient transferrin and gamma-glutamyltransferase in alcohol-using perimenopausal women. Alcohol Clin Exp Res 2000;24:176-9.
70. Fleming MF, Anton RF, Spies CD. A review of genetic, biological, pharmacological, and clinical factors that affect carbohydrate-deficient transferrin levels. Alcohol Clin Exp Res 2004;28:1347-55.
71. Arndt T, Hackler R, Kleine TO, Gressner AM. Validation by isoelectric focusing of the anion-exchange isotransferrin fractionation step involved in determination of carbohydrate-deficient transferrin by the CDTect assay. Clin Chem 1998;44:27-34.
72. Sorvajarvi K, Blake JE, Israel Y, Niemela O. Sensitivity and specificity of carbohydrate-deficient transferrin as a marker of alcohol abuse are significantly influenced by alterations in serum transferrin: comparison of two methods. Alcohol Clin Exp Res 1996;20:449-54.
73. Helander A. Absolute or relative measurement of carbohydrate-deficient transferrin in serum? Experiences with three immunological assays. Clin Chem 1999;45:131-5.
74. Alden A, Ohlson S, Pahlsson P, Ryden I. HPLC analysis of carbohydrate deficient transferrin isoforms isolated by the Axis-Shield %CDT method. Clin Chim Acta 2005;356:143-6.
75. Jaeken J, Carchon H. The carbohydrate-deficient glycoprotein syndromes: an overview. J Inherit Metab Dis 1993;16:813-20.
76. DiMartini A, Day N, Lane T, Beisler AT, Dew MA, Anton R. Carbohydrate deficient transferrin in abstaining patients with end-stage liver disease. Alcohol Clin Exp Res 2001;25:1729-33.
77. Berlakovich GA, Soliman T, Freundorfer E, Windhager T, Bodingbauer M, Wamser P, et al. Pretransplant screening of sobriety with carbohydrate-deficient transferrin in patients suffering from alcoholic cirrhosis. Transpl Int 2004;17:617-21.
78. De Feo TM, Fargion S, Duca L, Mattioli M, Cappellini MD, Sampietro M, et al. Carbohydrate-deficient transferrin, a sensitive marker of chronic alcohol abuse, is highly influenced by body iron. Hepatology 1999;29:658-63.
79. Jensen PD, Peterslund NA, Poulsen JH, Jensen FT, Christensen T, Ellegaard J. The effect of iron overload and iron reductive treatment on the serum concentration of carbohydrate-deficient transferrin. Br J Haematol 1994;88:56-63.
80. Fagerberg B, Agewall S, Berglund A, Wysocki M, Lundberg PA, Lindstedt G. Is carbohydrate-deficient transferrin in serum useful for detecting excessive alcohol consumption in hypertensive patients? Clin Chem 1994;40:2057-63.
81. Larsson A, Flodin M, Kollberg H. Increased serum concentrations of carbohydrate-deficient transferrin (CDT) in patients with cystic fibrosis. Ups J Med Sci 1998;103:231-6.
82. Brathen G, Bjerve KS, Brodtkorb E, Bovim G. Validity of carbohydrate deficient transferrin and other markers as diagnostic aids in the detection of alcohol related seizures. J Neurol Neurosurg Psychiatry 2000;68:342-8.
37
83. Piagnerelli M, Boudjeltia KZ, Nuyens V, De Backer D, Su F, Wang Z, et al. Rapid alterations in transferrin sialylation during sepsis. Shock 2005;24:48-52.
84. Freeze HH. Congenital Disorders of Glycosylation: CDG-I, CDG-II, and beyond. Curr Mol Med 2007;7:389-96.
85. Jaeken J, Matthijs G. Congenital disorders of glycosylation: a rapidly expanding disease family. Annu Rev Genomics Hum Genet 2007;8:261-78.
86. Jaeken J. Komrower Lecture. Congenital disorders of glycosylation (CDG): it's all in it! J Inherit Metab Dis 2003;26:99-118.
87. Marklova E, Albahri Z. Screening and diagnosis of congenital disorders of glycosylation. Clin Chim Acta 2007;385:6-20.
88. Wada Y. Mass spectrometry for congenital disorders of glycosylation, CDG. J Chromatogr B Analyt Technol Biomed Life Sci 2006;838:3-8.
89. Hackler R, Arndt T, Kleine TO, Gressner AM. Effect of separation conditions on automated isoelectric focusing of carbohydrate-deficient transferrin and other human isotransferrins using the PhastSystem. Anal Biochem 1995;230:281-9.
90. Trout AL, Prasad R, Coffin D, DiMartini A, Lane T, Blessum C, et al. Direct capillary electrophoretic detection of carbohydrate-deficient transferrin in neat serum. Electrophoresis 2000;21:2376-83.
91. Crivellente F, Fracasso G, Valentini R, Manetto G, Riviera AP, Tagliaro F. Improved method for carbohydrate-deficient transferrin determination in human serum by capillary zone electrophoresis. J Chromatogr B Biomed Sci Appl 2000;739:81-93.
92. Wuyts B, Delanghe JR, Kasvosve I, Wauters A, Neels H, Janssens J. Determination of carbohydrate-deficient transferrin using capillary zone electrophoresis. Clin Chem 2001;47:247-55.
93. Stibler H, Borg S, Joustra M. Micro anion exchange chromatography of carbohydrate-deficient transferrin in serum in relation to alcohol consumption (Swedish Patent 8400587-5). Alcohol Clin Exp Res 1986;10:535-44.
94. Stibler H, Borg S, Joustra M. A modified method for the assay of carbohydrate-deficient transferrin (CDT) in serum. Alcohol Alcohol Suppl 1991;1:451-4.
95. Arndt T, Kropf J, Brandt R, Gressner AM, Hackler R, Herold M, et al. CDTect-RIA and CDTect-EIA for determination of serum carbohydrate-deficient transferrin compared. Alcohol Alcohol 1998;33:639-45.
96. Schwarz MJ, Domke I, Helander A, Janssens PM, Van Pelt J, Springer B, et al. Multicentre evaluation of a new assay for determination of carbohydrate-deficient transferrin. Alcohol Alcohol 2003;38:270-5.
97. Helander A. Multicentre validation study of instrument applications for %CDT, an immunoassay for quantification of carbohydrate-deficient transferrin in serum. Alcohol Alcohol 2002;37:209-12.
98. Bell H, Tallaksen CC, Haug E, Try K. A comparison between two commercial methods for determining carbohydrate deficient transferrin (CDT). Scand J Clin Lab Invest 1994;54:453-7.
99. Simonsson P, Lindberg S, Alling C. Carbohydrate-deficient transferrin measured by high-performance liquid chromatography and CDTect immunoassay. Alcohol Alcohol 1996;31:397-402.
100. Jeppsson JO, Kristensson H, Fimiani C. Carbohydrate-deficient transferrin quantified by HPLC to determine heavy consumption of alcohol. Clin Chem 1993;39:2115-20.
101. Helander A, Bergstrom JP. Determination of carbohydrate-deficient transferrin in human serum using the Bio-Rad %CDT by HPLC test. Clin Chim Acta 2006;371:187-90.
102. Helander A, Husa A, Jeppsson JO. Improved HPLC method for carbohydrate-deficient transferrin in serum. Clin Chem 2003;49:1881-90.
103. Delanghe JR, Helander A, Wielders JP, Pekelharing JM, Roth HJ, Schellenberg F, et al. Development and multicenter evaluation of the N latex CDT direct immunonephelometric assay for serum carbohydrate-deficient transferrin. Clin Chem 2007;53:1115-21.
38
104. Busto ME, Montes-Bayon M, Sanz-Medel A. Accurate determination of human serum transferrin isoforms: Exploring metal-specific isotope dilution analysis as a quantitative proteomic tool. Anal Chem 2006;78:8218-26.
105. Flahaut C, Michalski JC, Danel T, Humbert MH, Klein A. The effects of ethanol on the glycosylation of human transferrin. Glycobiology 2003;13:191-8.
106. Kleinert P, Kuster T, Durka S, Ballhausen D, Bosshard NU, Steinmann B, et al. Mass spectrometric analysis of human transferrin in different body fluids. Clin Chem Lab Med 2003;41:1580-8.
107. Tabakoff B, Helander A, Conigrave KM, Martinez L, Hoffman PL, Whitfield J, et al. WHO/ISBRA study on state and trait markers in alcoholism. Alcohol Clin Exp Res 2001;25:99S-103S.
108. Glanz J, Grant B, Monteiro M, Tabakoff B. WHO/ISBRA Study on State and Trait Markers of Alcohol Use and Dependence: analysis of demographic, behavioral, physiologic, and drinking variables that contribute to dependence and seeking treatment. International Society on Biomedical Research on Alcoholism. Alcohol Clin Exp Res 2002;26:1047-61.
109. Bergstrom JP, Helander A. Influence of alcohol use, ethnicity, age, gender, BMI and smoking on the serum transferrin glycoform pattern: Implications for use of carbohydrate-deficient transferrin (CDT) as alcohol biomarker. Clin Chim Acta 2007.
110. Helander A, Bergstrom J, Freeze HH. Testing for congenital disorders of glycosylation by HPLC measurement of serum transferrin glycoforms. Clin Chem 2004;50:954-8.
111. Jeppsson JO, Arndt T, Schellenberg F, Wielders JP, Anton RF, Whitfield JB, Helander A. Toward standardization of carbohydrate-deficient transferrin (CDT) measurements: I. Analyte definition and proposal of a candidate reference method. Clin Chem Lab Med 2007;45:558-62.
112. van Eijk HG, van Noort WL, Kroos MJ, van der Heul C. Analysis of the iron-binding sites of transferrin by isoelectric focussing. J Clin Chem Clin Biochem 1978;16:557-60.
113. Legros FJ, Nuyens V, Minet E, Emonts P, Boudjeltia KZ, Courbe A, et al. Carbohydrate-deficient transferrin isoforms measured by capillary zone electrophoresis for detection of alcohol abuse. Clin Chem 2002;48:2177-86.
114. Helander A, Fors M, Zakrisson B. Study of Axis-Shield new %CDT immunoassay for quantification of carbohydrate-deficient transferrin (CDT) in serum. Alcohol Alcohol 2001;36:406-12.
115. Martello S, Trettene M, Cittadini F, Bortolotti F, De Giorgio F, Chiarotti M, Tagliaro F. Determination of carbohydrate deficient transferrin (CDT) with capillary electrophoresis: an inter laboratory comparison. Forensic Sci Int 2004;141:153-7.
116. Lanz C, Kuhn M, Deiss V, Thormann W. Improved capillary electrophoresis method for the determination of carbohydrate-deficient transferrin in patient sera. Electrophoresis 2004;25:2309-18.
117. Helander A, Wielders JP, Te Stroet R, Bergstrom JP. Comparison of HPLC and capillary electrophoresis for confirmatory testing of the alcohol misuse marker carbohydrate-deficient transferrin. Clin Chem 2005;51:1528-31.
118. Conigrave KM, Degenhardt LJ, Whitfield JB, Saunders JB, Helander A, Tabakoff B. CDT, GGT, and AST as markers of alcohol use: the WHO/ISBRA collaborative project. Alcohol Clin Exp Res 2002;26:332-9.
119. Arndt T, Kropf J. Alcohol abuse and carbohydrate-deficient transferrin analysis: are screening and confirmatory analysis required? Clin Chem 2002;48:2072-4.