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JOHANNA HIETALA

Novel Use of Biomarkers and Their Combinations
for Detecting Excessive Drinking

ACADEMIC DISSERTATION
To be presented, with the permission of
the Faculty of Medicine of the University of Tampere,
for public discussion in the auditorium of
Mediwest Health Technology Center, Koskenalantie 16, Seinäjoki,
on February 23rd, 2007, at 12 o’clock.
(Simultaneous video conference connection
in the small auditorium of Building K,
Medical School of the University of Tampere,
Teiskontie 35, Tampere)

U N I V E R S I T Y O F TA M P E R E

ACADEMIC DISSERTATION
University of Tampere, Medical School
Seinäjoki Central Hospital, Department of Laboratory Medicine and Medical Research Unit
Finland

Supervised by
Professor Onni Niemelä
University of Tampere

Reviewed by
Docent Kari Pulkki
University of Turku
Professor Kaija Seppä
University of Tampere

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Printed dissertation
Acta Universitatis Tamperensis 1210
ISBN 978-951-44-6856-8 (print)
ISSN 1455-1616

Tampereen Yliopistopaino Oy – Juvenes Print
Tampere 2007

Electronic dissertation
Acta Electronica Universitatis Tamperensis 594
ISBN 978-951-44-6857-5 (pdf )
ISSN 1456-954X
http://acta.uta.fi

To my family

3

4

Abstract

Excessive alcohol consumption and consequent medical disorders create a major burden for modern
health care. In addition to medical and social problems, excessive drinking causes considerable
strains on the national economy. In order to improve the diagnosis and treatment of patients suffering from ethanol-related health problems, reliable and accurate methods for recognizing excessive
alcohol consumption in its early phase need to be developed. Currently, excessive drinkers tend to
escape detection, which may lead to delays in intervention.
The present study was set out to develop new approaches for detecting excessive drinking based
on conventional and new laboratory tests and their combinations and to address the relationships
between such markers and alcoholic liver disease. Conventional laboratory markers of excessive
drinking (GGT, CDT, MCV, AST, ALT), a mathematically formulated combination of GGT and
CDT, and autoimmune responses to proteins modified with acetaldehyde, the first metabolite of
ethanol, were measured in alcoholics with or without liver disease, moderate drinkers and abstainers. Cytokine profiles of subjects were also studied in order to clarify the associations between alcohol intake and pathogenesis of alcoholic liver disease.
The results show that even moderate drinking may increase levels of gamma-glutamyl transferase (GGT). When GGT was combined logarithmically with carbohydrate-deficient transferrin
(CDT), the diagnostic performance of the combination GGT-CDT was found to markedly exceed
that of the traditional markers, reaching a sensitivity of 90 % whereas the sensitivities of its parent
components remained at 63 % (CDT) and 58 % (GGT).
Alcohol consumption was also found to induce alterations in the immune system. An association
between cytokine levels and alcohol use was observed, with most evident alterations in alcoholics
with liver disease. Pro-inflammatory cytokines (IL-2, IL-6, IL-8, TNF-α) were found to increase in
alcoholic liver disease whereas the levels of anti-inflammatory cytokines, particularly TGF-β1
showed a slight decrease.
Acetaldehyde adducts are formed when acetaldehyde reacts with proteins and cellular constituents. Antibodies directed against acetaldehyde-modified proteins were found in the circulation of
alcoholic patients. The highest anti-adduct IgA and IgG titres occurred in patients with alcoholic
liver disease, while specific class IgM antibodies were most abundant in alcoholics without liver
disease. The possible usefulness of anti-adduct IgA as a marker of excessive drinking was subsequently studied in alcoholics without liver disease, and the mean anti-adduct IgA levels were significantly higher than those in the moderate drinkers or abstainers (p < 0.001), while the difference
between the moderate drinkers and abstainers was also significant (p < 0.05). Mean daily ethanol
consumption during the previous month was found to correlate significantly with anti-adduct IgA
levels. Based on these findings, anti-adduct IgA antibodies could serve as markers of alcohol con-

5

sumption. A combination of the anti-adduct IgA and CDT results showed improved diagnostic performance for this marker (IgA-CDT) as compared to traditional ones.
In the light of these results, it may be suggested that GGT, CDT and IgAs against acetaldehydederived epitopes either alone or combined by means of mathematical equations can serve as useful
markers of alcohol consumption. The elevation of GGT in moderate drinkers as compared with abstainers may affect its reference ranges, since they are usually calculated from general population in
which the proportion of abstainers is decreasing. The results also indicate that the antibody responses and alterations in cytokine balance may contribute to the pathogenesis and progression of
alcoholic liver disease in humans.

6

Contents

ABSTRACT .................................................................................................................5
CONTENTS .................................................................................................................7
ABBREVIATIONS....................................................................................................10
LIST OF ORIGINAL PUBLICATIONS ...................................................................13
1. INTRODUCTION..................................................................................................15
2. REVIEW OF THE LITERATURE........................................................................16
2.1. Ethanol: past and present................................................................................................. 16
2.2. Main features of ethanol metabolism .............................................................................. 16
2.3. Effects of ethanol on health ............................................................................................. 17
2.3.1. Ethanol and the liver ........................................................................................... 18
2.3.2. Ethanol and extrahepatic tissues ......................................................................... 19
2.3.3. Ethanol and the immune system ......................................................................... 20
2.3.4. Ethanol, psychiatric disorders and accidents ...................................................... 20
2.3.5. Suggested positive effects of ethanol.................................................................. 21
2.4. Assessing alcohol consumption....................................................................................... 22
2.4.1. Amount and pattern of drinking.......................................................................... 22
2.4.2. Self-reported alcohol consumption ..................................................................... 22
2.4.3. Laboratory markers of alcohol consumption ...................................................... 23
2.4.4. Laboratory markers of ethanol-induced tissue injury ......................................... 25
2.4.5. Gender issues ...................................................................................................... 25
2.5. Routinely used biomarkers of ethanol consumption ....................................................... 25
2.5.1. Ethanol concentration in blood, breath or urine.................................................. 25
2.5.2. Gamma-glutamyl transferase .............................................................................. 25
2.5.3. Carbohydrate-deficient transferrin ...................................................................... 26
2.5.4. Mean corpuscular volume ................................................................................... 27
2.5.5. Aminotransferases............................................................................................... 27

7

2.6. New biomarkers of ethanol consumption........................................................................ 27
2.6.1. Acetaldehyde adducts and anti-adduct antibodies .............................................. 27
2.6.2. 5-Hydroxytryptophol .......................................................................................... 28
2.6.3. Ethyl glucuronide ................................................................................................ 28
2.6.4. Fatty acid ethyl esters.......................................................................................... 28
2.6.5. Phosphatidylethanol ............................................................................................ 29
2.6.6. Sialic acid ............................................................................................................ 29
2.6.7. Other postulated markers .................................................................................... 29
2.7. Marker combinations....................................................................................................... 30
2.8. Laboratory markers for the follow-up of alcoholics........................................................ 31
2.9. Immune responses related to alcohol consumption......................................................... 31
2.9.1. Immune responses to ethanol metabolites........................................................... 31
2.9.2. Alcohol-induced cytokine responses................................................................... 33

3. AIMS OF THE PRESENT RESEARCH...............................................................34
4. MATERIALS AND METHODS ...........................................................................35
4.1. Subjects............................................................................................................................ 35
4.2. Measurements of laboratory markers (I-II, IV) ............................................................... 36
4.3. Determination of marker combinations (II, IV) .............................................................. 37
4.3.1. GGT-CDT (II)..................................................................................................... 37
4.3.2. IgA-CDT ............................................................................................................. 37
4.4. Measurement of antibodies against acetaldehyde adducts (III-IV) ................................. 37
4.5. Serum cytokines .............................................................................................................. 38
4.6. Statistical methods........................................................................................................... 38

5. RESULTS...............................................................................................................39
5.1. Influence of drinking levels on markers (I, II, IV) .......................................................... 39
5.2. Clinical characteristics of marker combinations (II, IV)................................................. 39
5.2.1. GGT-CDT (II)..................................................................................................... 39
5.2.2. IgA-CDT (IV) ..................................................................................................... 40
5.3. Antibody and cytokine responses in alcoholics (III–IV)................................................. 41
5.3.1. Alcohol-related changes in cytokine and antibody production (III-IV).............. 41
5.3.2. Anti-adduct IgAs as a marker of alcohol consumption (IV)............................... 41

8

5.4. Markers in the follow-up of alcoholics (II-IV)................................................................ 42

6. DISCUSSION.........................................................................................................43
6.1. Influence of moderate drinking on marker levels (I-IV) ................................................. 43
6.2. Marker combinations (II, IV) .......................................................................................... 44
6.3. Antibody and cytokine responses in alcohol abusers (III-IV)......................................... 45
6.3.1. Changes in antibody and cytokine production attributable to alcohol and liver
disease (III-IV) .............................................................................................................. 45
6.3.2. Anti-adduct IgAs as a marker of alcohol consumption....................................... 47
6.4. Follow-up studies ............................................................................................................ 47
6.5. Possible limitations of this study..................................................................................... 48
6.6. Future considerations....................................................................................................... 48

7. CONCLUSIONS ....................................................................................................49
ACKNOWLEDGEMENTS .......................................................................................50
REFERENCES ...........................................................................................................51

9

Abbreviations

ADH
ALDH
ALT
Apo J
AST
AUC
AUDIT
BMI
CAGE
CCLI
CDT
%CDT
CHD
CMI
CYP2E1
DSM-IV
EOA
EtG
EtS
FAE
FAEEs
FAS
GGT
HA
HDL
HIAA
HTOL
IFN
IgA, IgG, IgM
IL
LOA
LPS
MAST
MCV
MEOS
NPV
PBS
PEth

Alcohol dehydrogenase
Aldehyde dehydrogenase
Alanine aminotransferase
Apolipoprotein J
Aspartate aminotransferase
Area under the curve
Alcohol Use Disorders Identification Test
Body mass index
Cut down, Annoyed, Guilty, Eye-opener (acronym)
Combined clinical and laboratory index
Carbohydrate-deficient transferrin
CDT as a percentage of total transferrin
Coronary heart disease
Combined morphological index
Cytochrome P450 IIE1
Diagnostic and Statistical Manual of Mental Disorders. Fourth Edition.
Early onset alcoholics
Ethyl glucuronide
Ethyl sulphate
Fetal alcohol effects
Fatty acid ethyl esters
Fetal alcohol syndrome
Gamma-glutamyl transferase
Hyaluronic acid
High density lipoprotein -cholesterol
Hydroxyindole-acetic acid
Hydroxytryptophol
Interferon
Immunoglobulin A, G, M
Interleukin
Late onset alcoholics
Lipopolysaccharide
Michigan Alcoholism Screening Test
Mean corpuscular volume
Microsomal ethanol oxidizing system
Negative predictive value
Phosphate-buffered saline
Phosphatidylethanol

10

PINP
PIIINP
PPV
ROC
SA
SD
SIJ
TGF-β1
TLFB
TNF-α

Aminoterminal propeptide of type I collagen
Aminoterminal propeptide of type III collagen
Positive predictive value
Receiver-operating characteristic
Sialic acid
Standard deviation
Sialic acid index of apolipoprotein J
Transforming growth factor-β1
Timeline follow-back -method
Tumor necrosis factor-α

11

12

List of original publications

I

Hietala J, Puukka K, Koivisto H, Anttila P, Niemelä O (2005) Serum gamma-glutamyl
transferase in alcoholics, moderate drinkers and abstainers: effect on GT reference intervals at population level. Alcohol Alcohol 40: 511–514.

II

Hietala J, Koivisto H, Anttila P, Niemelä O (2006) Comparison of the combined
marker GGT-CDT and the conventional laboratory markers of alcohol abuse in heavy
drinkers, moderate drinkers and abstainers. Alcohol Alcohol 41: 528–533.

III

Latvala J, Hietala J, Koivisto H, Järvi K, Anttila P, Niemelä O (2005) Immune responses to ethanol metabolites and cytokine profiles differentiate alcoholics with or
without liver disease. Am J Gastroenterol 100: 1303–1310.

IV

Hietala J, Koivisto H, Latvala J, Anttila P, Niemelä O (2006) IgAs against acetaldehyde-modified red cell protein as a marker of ethanol consumption in male alcoholic
subjects, moderate drinkers, and abstainers. Alcohol Clin Exp Res 30: 1693–1698.

The original articles are referred to in the text with the above Roman numerals.

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14

1. Introduction

Excessive alcohol consumption and consequent medical disorders are considerable problems in
many Western countries (Österberg 2006, Blocker, Jr. 2006). In addition to medical and social
problems at the individual level, excessive drinking causes significant problems for the national
economy. Resources should therefore be focused on reducing the prevalence of alcoholism through
more effective diagnosis and early intervention (Anderson 1993, Sharpe 2001, Fleming et al. 2002,
Latt and Saunders 2002, Niemelä 2002, Rehm et al. 2006). It has been estimated that only 20–50 %
of patients with alcoholism are actually identified in health care and thus more reliable and accurate
methods of recognizing excessive alcohol consumption in clinical work are urgently needed (Reid
et al. 1986, Moore et al. 1989, Sharpe 2001).
The diagnosis of excessive alcohol consumption is often based on patients' own reports and answers to questionnaires. This approach suffers from a lack of reliability, because patients are usually
unwilling to admit excessive drinking (Rosman and Lieber 1994, Sharpe 2001, Niemelä 2002).
Laboratory markers have been integrated into the diagnostics and may lead to a considerable improvement in detecting excessive drinking (Lieber 1995, Niemelä 2002). The main advantage of
laboratory markers is their objective nature. The results of laboratory tests revealing excessive alcohol consumption and possible tissue injury could motivate patients more than a verbal report by a
clinician (Allen et al. 1992, Rosman and Lieber 1994). It has also been suggested that a better understanding of the physiological effects of ethanol and the mechanisms by which alcohol exerts its
effects on different tissues would lead to improved diagnostics and treatment of alcohol use disorders.
This work was aimed at investigating the usefulness of various laboratory markers and their
combinations for detecting excessive drinking. The effect of abstaining and moderate drinking on
levels of these markers was studied. The aims were also to clarify the effects of alcohol on specific
antibody and cytokine responses and to investigate the possibility of using such responses as markers of alcohol consumption and tissue injury.

15

2. Review of the literature

2.1. Ethanol: past and present
Alcohol has been used in human societies from the beginning of recorded history. The earliest alcoholic beverages were fermented drinks, and distilled alcohol products emerged about 3000 years
ago. Alcohol has been used over the centuries for both medicinal and refreshment purposes (Millikan 1999), and the production of alcoholic beverages has gradually become industrialized and has
turned into a worldwide business (Walsh 1997, Room 1997). After the temperance movements of
late 19th and early 20th centuries, alcohol consumption has become more accepted and is no longer
viewed as a threat to all individuals (Blocker, Jr. 2006). Consequently, consumption volumes have
grown continuously in many industrialized countries since World War II, with the exception of certain Mediterranean countries, which have shown a slow downward trend during recent decades
(Pyörälä 1990, Medical Research Council 1998, Stakes 2005, Blocker, Jr. 2006, IAS 2006). Alcohol consumption by women and young people in particular has increased considerably since the
war, and attention has also been focused more recently on the increasing use of alcohol among the
elderly.
It has been known for centuries that alcohol consumption is somehow associated with increased
illness and death, and the scientific study of alcohol-related mortality that started in the 1920s has
continued with the establishment of a connection between alcohol and liver disease (Mann et al.
2003). Over the past few decades, alcohol and alcoholism have been studied intensively in order to
achieve more effective diagnosis, treatment and prevention.
Alcoholism and alcohol-related disorders place a considerable burden on society nowadays, and
alcohol strategies should therefore be focused on the prevention and early detection of alcoholism
(Wilson 1995, Room et al. 2005, Rehm et al. 2006). The simultaneous use of alcohol and drugs has
also become more common, posing a new challenge to health care. The price and availability of
alcoholic beverages are among the major factors that have contributed to alcohol consumption, and
these should be controlled in order to reduce consumption at the population level (Chaloupka et al.
1998, Room et al. 2005).

2.2. Main features of ethanol metabolism
Ethanol is a simple molecule, which can affect cell membranes and signaling pathways throughout
the body. Ethanol in itself is not very toxic, but its first metabolite, acetaldehyde, is highly toxic and
may cause various adverse effects in cells and tissues (Niemelä 2001, Eriksson 2001). Acetaldehyde
is carcinogenic, mutagenic and can interfere with DNA synthesis and repair. It can also react with
16

proteins and cellular constituents, forming stable or unstable acetaldehyde adducts. The process of
ethanol metabolism also generates free oxygen radicals, which are extremely reactive and may
thereby cause major damage to cells (Molina et al. 2003, Caro and Cederbaum 2004).
After ingestion, ethanol is absorbed in the gastrointestinal tract, mainly in the small intestine.
Approximately 2–10 % of the ethanol absorbed will be removed unaltered in the respiration and
urine (Lieber 2005), while the rest will be metabolized. The oxidation of ethanol to acetaldehyde
begins in gastric wall through the action of the alcohol dehydrogenase enzyme (ADH), in a process
referred to as gastric first-pass metabolism (Julkunen et al. 1985, Frezza et al. 1990, Seitz and
Pöschl 1997). The microbes in the alimentary tract are also capable of metabolizing ethanol. The
resulting acetaldehyde may accumulate in the colon because of insufficient aldehyde dehydrogenase
(ALDH) activity and may cause adverse effects there (Salaspuro 1996, Koivisto and Salaspuro
1996).
Ethanol is rapidly distributed among the various tissues of the body. Its metabolism takes place
primarily in the liver, where it is oxidized to acetaldehyde, mainly via the ADH pathway. The minor
metabolic pathways are the microsomal ethanol oxidizing system (MEOS) and the catalase pathway. The MEOS pathway, in which hepatic P450 cytochromes (mainly CYP2E1) are responsible
for ethanol oxidation, is induced by high blood ethanol concentrations and chronic ethanol consumption (Lieber and DeCarli 1968, Salaspuro and Lieber 1978, Asai et al. 1996, Lieber 2004). The
catalase pathway requires hydrogen peroxide, which is produced only in small amounts under normal circumstances (Thurman and McKenna 1975, Thurman and Handler 1989, Molina et al. 2003).
More recently, however, Bradford and co-workers (1999) have reported that the catalase pathway
appears to be ethanol- and methanol-inducible and that the Kupffer cells in the liver participate in
the regulation of the hydrogen peroxide supply. It has also been suggested that the catalase pathway
may account for most of the ethanol oxidation occurring in brain (Aragon et al. 1991, McBride et al.
2002). This is of importance because acetaldehyde, unlike intact ethanol, cannot readily pass from
the blood to the brain because of the abundance of ALDH in the blood-brain barrier (Zimatkin and
Deitrich 1997).
Acetaldehyde is further oxidized to acetate in liver by hepatic ALDH. The resulting acetate is
transported to the muscles and heart and finally converted to carbon dioxide and water and eliminated from body.

2.3. Effects of ethanol on health
The health hazards associated with excessive alcohol consumption are numerous and well known.
Almost all tissues in the body are affected by ethanol and it is related to more than 60 medical conditions (Rehm et al. 2003). The adverse health effects of excessive or even moderate ethanol consumption include both physiological and mental problems (Lieber 1995, Damström Thakker 1998,
Adrian and Barry 2003, Corrao et al. 2004). Some beneficial effects of moderate drinking have also
been suggested recently. The adverse and beneficial effects of alcohol consumption habits on health
are summarized in Table 1.

17

When evaluating the health effects of ethanol, attention should be paid both to the actual amount
consumed and to drinking patterns, as some adverse effects are related to occasional heavy drinking
and intoxication and some to chronic consumption (Niemelä 2002, Rehm et al. 2003). Social harm
and the possible health benefits seem to be more closely linked to drinking patterns than are the
adverse health effects (Damström Thakker 1998). There are also several factors that affect individual susceptibility to the effects of alcohol, such as age, gender, race, body mass and genetic factors
(Lieber 1995, Damström Thakker 1998).
Table 1. Possible effects of various levels of ethanol intake on health.
Abstaining

Moderate
drinking

Excessive
drinking

Liver disease

0





Cancer

0





Nervous system

0





Fetal effects

0





Immune system

0

0 or +



Psychiatric disorders

0

0 or +



Accidents and injuries

0





Coronary heart disease



+



Alcohol-related disorder

+ protective effects

– harmful effects

0 no effects

(Medical Research Council 1998, Damström Thakker 1998, Cook 1998, Eckardt
et al. 1998, Rodgers et al. 2000, Diaz et al. 2002, Sareen et al. 2004, Watzl et al.
2004, Meyerhoff et al. 2005, Borges et al. 2006, Heng et al. 2006)

2.3.1. Ethanol and the liver
Since the liver accounts almost exclusively of ethanol metabolism, it is also the main target for
ethanol toxicity (Lieber 1977, Jaeschke et al. 2002, Niemelä 2002). Many studies have reported a
dose-response relationship between alcohol consumption and various types of liver damage (Coates
et al. 1986, Norton et al. 1987, Corrao et al. 1999, White et al. 2002). Some of the adverse effects of
ethanol on the liver are likely to be caused by acetaldehyde and free radical production rather than
the ethanol itself (Eriksson 2001, Molina et al. 2003, Chase et al. 2005, Dey and Cederbaum 2006),
and it has also become evident that the immune system plays a key role in the pathology of liver
diseases (Leevy and Elbeshbeshy 2005).
The earliest abnormality to appear in the liver due to excessive alcohol consumption is the accumulation of lipids, which may lead to steatosis (fatty liver). This condition is transient and usually
reversible if the alcohol intake ceases. Upon continuing ethanol intake, steatosis may develop into
an inflammation process, hepatitis, which involves cell death and massive migration of immune
cells into the liver. This is a potentially lethal condition and may easily recur in patients who re18

cover and resume drinking. Alcoholic cirrhosis is a condition in which the normal liver structure has
gradually become fibrotic as a consequence of persistent inflammation and abnormal connective
tissue metabolism. The normal functions of liver become impaired as fibrogenesis proceeds and
eventually this process may lead to liver failure and death. It has been estimated that 10–15 % of all
chronic alcoholics will eventually develop cirrhosis (Niemelä 2002, Mann et al. 2003).
Advanced liver disease may also contribute to brain function. When the venous blood flow to
the liver is obstructed due to extensive cirrhosis, toxic substances and metabolic by-products may
leak into the systemic circulation and pass to the brain, interfering in the actions of neurotransmitters (Oscar-Berman et al. 1997).

2.3.2. Ethanol and extrahepatic tissues
Even a moderate level of ethanol intake has been found to be associated with several types of cancer, including cancers of the upper aerodigestive tract, colorectal area and liver, and breast cancer in
women. There seems to be a dose-response relationship between ethanol intake and the related cancer risk (Corrao et al. 1999, Boffetta and Hashibe 2006). Genetic factors have also been found to
affect individual susceptibility to development of alcohol-related cancer, mainly via polymorphisms
of enzymes associated with ethanol metabolism, folate metabolism and DNA repair (Boffetta and
Hashibe 2006). The exact mechanisms by which ethanol induces cancer have not been fully defined
but several possibilities have been discussed (Wight and Ogden 1998, Molina et al. 2003, Dumitrescu and Shields 2005, Boffetta and Hashibe 2006). Alcohol has been estimated to cause 3 % of
all cancers worldwide (Medical Research Council 1998).
Continuous ethanol consumption is known to have adverse effects on the nervous system, particularly in the brain, including brain shrinkage, emotional and personality changes and learning and
memory defects. It is also known to affect sleep patterns, muscular coordination and the regulation
of body temperature (Oscar-Berman et al. 1997). The mechanisms by which ethanol affects the
nervous system are complex and not yet fully understood, and there appear to be additional factors
such as age, gender, family history, coexisting health problems and nutritional deficiencies that play
a role in the development of neurological defects (Oscar-Berman et al. 1997). It is well established
that ethanol can activate the dopamine system in the brain, which contributes to its rewarding effects (Di Chiara 1997, Tupala and Tiihonen 2004) and it also interferes with the actions of various
other neurotransmitters (Oscar-Berman et al. 1997, Eckardt et al. 1998). Unlike other addictive
drugs, however, it does not have specific receptors on cell surfaces.
Ethanol is known to penetrate the placental barrier and cause adverse effects on the growing fetus but the exact mechanisms are still unclear. Fetal alcohol syndrome (FAS), or its milder form,
fetal alcohol effects (FAE), may result from alcohol consumption during pregnancy and is associated with growth and mental retardation and certain facial features and also with abnormalities in
various organs (Jones and Smith 1973, Chaudhuri 2000, Jacobson and Jacobson 2002). FAS seems
to be related to relatively high levels of ethanol consumption but milder symptoms such as reduced
birth weight and learning problems have already been observed at moderate levels of ethanol intake
(Ogston and Parry 1992, Allebeck and Olsen 1998, Eckardt et al. 1998, Sood et al. 2001). Fetal
damage has been shown to be dose-dependent (Allebeck and Olsen 1998, Sood et al. 2001), al-

19

though high occasional blood alcohol levels have been reported to be a greater risk for the fetus
than lower continuous consumption (Maier and West 2001). However, not all heavy-drinking mothers give birth to a FAS/FAE child, so that additional risk factors have been suggested to exist (Jacobson et al. 1996, Maier and West 2001). The number of children born with FAS/FAE has been
increasing with the growing percentage of alcohol-consuming pregnant women and this problem
needs special attention in current health care (Chaudhuri 2000, Warren and Foudin 2001, Eustace et
al. 2003).
Excessive drinking may also lead to disorders in the gastrointestinal, cardiovascular, respiratory,
reproductive and endocrine systems (Medical Research Council 1998, Damström Thakker 1998,
Adrian and Barry 2003). High alcohol intake has been reported to cause damage to heart muscle
and to increase the risk of arrhythmias (Piano and Schwertz 1994), and also to elevate blood pressure, which is a risk factor for brain infarction, for instance (Hillbom and Kaste 1990, Puddey and
Beilin 2006). Excessive alcohol consumption is a major cause of acute and chronic pancreatitis, its
relationship to the risk and severity of pancreatitis being dose-dependent (Durbec and Sarles 1978,
Jaakkola et al. 1994, Corrao et al. 1999, 2004). Alcohol is also known to cause various adverse effects in the gastrointestinal tract, such as disruptions in the gastric mucosal barrier, which may lead
to deficient absorption of many nutrients and vitamins (Bujanda 2000, Bode and Bode 2003).

2.3.3. Ethanol and the immune system
It is well known that the immune system is greatly influenced by excessive drinking (Cook 1998). It
was found in the early 20th century that alcoholics are more susceptible to pneumonia than nonalcoholics, and it was later observed that alcoholics are also more susceptible to other types of infection, such as septicaemia and tuberculosis. More recent studies on immunity and alcohol have
focused mostly on immune mechanisms in liver pathology although these mechanisms may also
play a part in alcohol-related cardiac, endocrine and neurological damage. Ethanol is known to interfere with the functioning of cells in the immune system such as B and T cells, macrophages,
monocytes and dendritic cells and may thus contribute to an increased susceptibility to infection
(Cook 1998, Saeed et al. 2004, Szabo et al. 2004, Chase et al. 2005). An imbalance in the T cell
subsets TH1 and TH2 has been suggested as a factor contributing to immunological disturbances in
alcoholics (Cook 1998). Decreased B-cell numbers have been reported in alcoholics with liver disease, but they often show elevated immunoglobulin levels, particularly IgA levels, and increased
IgA deposition in the kidneys, skin and liver (Swerdlow et al. 1983, van de Wiel et al. 1988, Amore
et al. 1994, Cook 1998). Excessive alcohol consumption may lead to the specific production of antibodies against ethanol-induced antigens (Israel et al. 1986, Koskinas et al. 1992, Tuma and Klassen 1992), and also to alterations in the cytokine balance, which both may contribute to the pathogenesis of tissue damage (McClain et al. 1993, Crews et al. 2006).

2.3.4. Ethanol, psychiatric disorders and accidents
The association between excessive drinking and psychiatric disorders has been studied since the
1950s. It has been reported that mental problems tend to emerge before the onset of excessive
drinking but may also follow excessive drinking or the two may coincide in onset (Kessler et al.

20

1997, Berglund and Öjehagen 1998). Alcohol abuse or dependence can worsen the prognosis for
psychiatric disorders (Berglund and Öjehagen 1998), and alcohol dependence is also a significant
risk factor for suicide, particularly if associated with mental disorders (Berglund and Öjehagen
1998, Pirkola et al. 2004, Preuss et al. 2006). Alcohol has been found in the blood of 20–55 % of
patients who have committed suicide (Öhberg et al. 1996, Crombie et al. 1998, Bedford et al. 2006).
At the population level, suicide rates are usually high in countries with a high alcohol consumption
and a rise in suicide rates is observed when total alcohol consumption increases (Berglund and Öjehagen 1998).
In addition to diseases, excessive alcohol consumption accounts for numerous cases of trauma,
violence and motor vehicle accidents (Brismar and Bergman 1998, Cunningham et al. 2002, Savola
et al. 2005). Alcohol-related accidents are common: it has been estimated that over 50 % of injured
emergency unit patients have alcohol in their blood (Savola et al. 2005). In connection with alcoholrelated violent behaviour, it has been speculated that alcohol may either weaken the normal inhibitory impulses or stimulate aggressive behaviour, but the theories are not conclusive (Källmén and
Gustafson 1998, Badawy 2003). Either way, the amount of alcohol consumed is clearly associated
with the number of reported cases of violence. Alcohol is also involved in significant proportions of
traffic accidents and the risk is known to increase with increasing blood alcohol levels (Hingson and
Winter 2003, Bedford et al. 2006, Heng et al. 2006). A recent report has also stated that even moderate drinking (blood alcohol concentration within the legal limits) may significantly increase the
risk of motor vehicle accidents (Heng et al. 2006).

2.3.5. Suggested positive effects of ethanol
Although the positive effects of ethanol consumption are usually thought to lie in psychological
benefits such as mood elevation, stress relief and more social behaviour, reports concerning the
beneficial effects of moderate drinking on somatic health have also been published recently. Studies
on coronary heart disease (CHD) have suggested that people drinking approximately 20 g of ethanol
per day have the lowest relative risk of CHD, although there is a rapidly increasing risk at higher
consumption levels (Doll 1997, Corrao et al. 2000, Agarwal 2002). It has been suggested that red
wine may confer a greater protective effect than other types of alcoholic beverage (Grønbæk 2006).
Ethanol is known to elevate high-density lipoprotein (HDL) levels and this, along with other possible factors, has been suggested to contribute to a reduction in the CHD risk (De Oliveira e Silva et
al. 2000, Agarwal 2002). Moderate drinking may also be associated with a decreased risk of diabetes (Howard et al. 2004). The thresholds for "healthy" drinking are not definitive, however, as there
is wide variation in individual susceptibility to the harmful effects of alcohol (Damström Thakker
1998, Enoch 2003, Fromme et al. 2004). Whether clinicians should advise patients with a high risk
of cardiovascular disease, for example, to have one drink per day remains a controversial issue
(Ellison 2002, Fisher Wilson 2003), especially as the same beneficial effects could in most cases be
achieved with regular exercise and a low-fat diet, without the risks associated with alcohol (Damström Thakker 1998, Goldberg 2003). The benefits of moderate drinking with respect to cardiovascular disease, for instance, may quickly be outweighed by increases in liver disease and cancer, and
the net effect is likely to be negative (Friedman and Klatsky 1993, Damström Thakker 1998, Goldberg 2003).

21

2.4. Assessing alcohol consumption
2.4.1. Amount and pattern of drinking
The limits for moderate ethanol intake and the definition of a standard drink show variation depending on the source and country. The upper limits quoted here for moderate drinking, 280 g of ethanol
per week for men and 190 g for women, are those defined for Finland (Sillanaukee et al. 1992a),
while in the United Kingdom, for instance, the weekly limits are set at 168 g for men and 112 g for
women (Sharpe 2001). One unit or drink is defined as containing ethanol in amounts ranging from 8
g to as much as 20 g, so that ethanol consumption should preferably be assessed in grams in order
to avoid confusion (Turner 1990, Dufour 1999, Brick 2006).
The methods for identifying excessive drinking include verbal reports, questionnaires and laboratory tests. In clinical practice, interviews and questionnaires form the basis for detecting excessive
drinking in its early phase, whereas laboratory tests are most useful for monitoring the treatment of
alcoholism, although they can also be integrated into the detection of excessive drinking (Treatment
of alcohol abuse. Current Care Guideline 2005).
On the basis of their drinking habits, individuals can be divided into five groups based on limits that
are currently used in Finland.
1. Abstainers, who do not drink any alcohol,
2. Moderate drinkers, who have a weekly ethanol consumption below 280 g (men) and 190 g
(women) and do not drink over 80 g (men) and 60 g (women) on any single occasion,
3. Hazardous drinkers, who consume alcohol in amounts exceeding the limits of moderate drinking,
but do not show any obvious immediate disorders,
4. Alcohol abusers, who consume ethanol in large amounts and have various medical, social and
financial problems due to their drinking, although they do not fulfill the criteria for alcoholism, and
5. Alcoholics, alcohol abusers who meet the criteria for alcohol dependence including pathological
alcohol consumption, social impairment, and the presence of tolerance and withdrawal symptoms.
Alcoholic individuals may further be classified into two subtypes according to the onset of their
drinking (Buydens-Branchey et al. 1989, Johnson et al. 2000, Enoch 2003). If excessive drinking
has started before the age of 20, the drinker is classified as an early onset alcoholic (EOA), also
called type II alcoholism. It is often associated with antisocial behaviour and a high familial or genetic loading towards alcoholism. Late onset alcoholics (LOA) or type I alcoholics usually start
drinking later in life, often as a consequence of psychosocial stress.

2.4.2. Self-reported alcohol consumption
Since there are no exact symptoms of early-phase alcohol problems, clinicians have limited means
of assessing patients' drinking based on external evaluations (MacKenzie et al. 1996, Sharpe 2001).

22

Patients with alcohol problems often tend to deny having any, and it may be difficult to make a
clinical diagnosis when based solely on an interview.
Structured questionnaires can be of assistance in identifying alcohol abusers and are well suited
for screening purposes (Seppä et al. 1995, Ryb et al. 1999, Aertgeerts et al. 2001). The best-known
questionnaires are AUDIT, CAGE and MAST. AUDIT (Alcohol Use Disorders Identification Test)
is a quite recently developed questionnaire, which consists of 10 questions and focuses mainly on
the level and frequency of consumption and the adverse consequences of drinking (Saunders et al.
1993). It has been reported that AUDIT is the most sensitive among the current questionnaires for
detecting hazardous and harmful drinking (Seppä et al. 1995, MacKenzie et al. 1996, Reid et al.
1999). Shorter forms of this questionnaire (three to five questions) have also been developed and
tested in clinical populations more recently, and the results have so far been quite promising (Piccinelli et al. 1997, Aertgeerts et al. 2001, Gual et al. 2002, Hodgson et al. 2002). The CAGE questionnaire includes four questions concerning drinking habits and alcohol-related problems (Ewing
1984), its name being an acronym for the key words in the questions (Cut down, Annoyed, Guilty,
Eye-opener). The most extensive questionnaire is the Michigan Alcoholism Screening Test
(MAST), which consists of 25 questions directed at the recognition of drinking problems, helpseeking behaviour and alcohol-related disabilities (Selzer 1971). Both CAGE and MAST have been
found to perform well in detecting alcohol dependence but to be less effective in identifying hazardous drinkers (MacKenzie et al. 1996, Reid et al. 1999). Combinations of these questionnaires
and novel variations have also been introduced, with efficacies comparable or superior to the older
ones (Seppä et al. 1998, Merikallio-Pajunen et al. 2004, Patton et al. 2004).
A commonly used means of assessing the amounts of ethanol consumed is the timeline followback (TLFB) method, in which the patient is not asked to estimate the mean consumption of alcohol
but to fill in a calendar and report how many drinks he or she has consumed during a specified period of time (Allen et al. 1992). This method is used mostly for research purposes and to a lesser
extent in clinical interviews.

2.4.3. Laboratory markers of alcohol consumption
The introduction of laboratory tests for detecting excessive alcohol intake has improved the assessment of ethanol consumption. Laboratory tests and structured questionnaires may be used in combination in order to achieve the most efficient detection of excessive alcohol use (Sharpe 2001, Dolman and Hawkes 2005, Berner et al. 2006).
An ideal biomarker for detecting excessive drinking should be
1. Specific to ethanol, in order to avoid false positives
2. Sensitive enough to provide a useful screening tool for identifying excessive drinking also in its
early phases
3. Related to the amount of alcohol consumed.
4. Suitable for monitoring abstinence (e.g. decreasing consistently after cessation of drinking) and
5. Easy and cost-effective in routine use.

23

None of the existing biomarkers fulfills all these criteria. The most frequently used markers today
are carbohydrate-deficient transferrin, gamma-glutamyltransferase and the mean corpuscular volume of erythrocytes.
The development of a new marker usually begins by contrasting alcoholics with abstainers,
which shows whether the method gives any differences between these two groups in the first place.
The process continues with studies in clinical populations, since the ultimate purpose of a marker is
to identify excessive drinkers in a general population, where various sources of unspecificity may
occur. If the marker appears to be of value in these studies, its use may be considered in routine
clinical contexts.
Basically, biomarkers can be divided into markers of acute and chronic alcohol consumption
(Rosman and Lieber 1992). The former, which remain elevated for a few days, may be used for
detecting relapses in alcoholic patients undergoing treatment, for example. The latter, which are
usually elevated after a longer period of drinking or several shorter periods of binge drinking, are
useful for identifying alcohol abuse and to some extent for screening purposes. Some of these longterm markers can also be useful for detecting relapses during treatment.
Among the measures used to describe the diagnostic performance of a marker (Boyd 1997), sensitivity is the percentage of positive test results of all the positive patients and specificity is the percentage of negative test results from all the negative patients. Thus, if an alcohol marker has a sensitivity of 60 % and a specificity of 90 %, it means that 60 % of the alcoholics will have abnormal test
results and 90 % of the control population will have normal test results. An ideal assay should provide both a specificity and a sensitivity close to 100 %. The other commonly used measures are
predictive values. The positive predictive value (PPV) is the percentage of true positive results of all
positive results (including true and false positives), and the negative predictive value (NPV) is the
percentage of true negative results of all negative results (including true and false negatives). The
closer these values are to 100 %, the better the predictive value of the marker.
The cut-off values, sensitivities and specificities of markers can be assessed with the receiveroperating characteristic (ROC) curves (Robertson and Zweig 1981, Zweig and Campbell 1993,
Boyd 1997). A cut-off value is what separates a normal from an abnormal (usually elevated) result.
ROC analysis gives sensitivity and specificity values for all possible cut-offs, and a measure called
the area under the curve (AUC), which describes the accuracy of the test. With ROC analysis, it is
easy to compare the performance of different markers and cut-off values.
One important aspect of the use of laboratory markers is the definition of "normal" values and
reference limits. Reference intervals are defined based on values for apparently healthy individuals.
This reference population should be carefully selected and the effects of age, gender, race, nutritional status and preferably alcohol drinking habits must be considered in order to avoid misleading
reference limits and future misinterpretation of laboratory results. The most common methods for
determining reference intervals are the mean ± 2SD for populations following a Gaussian distribution (or a Gaussian distribution is obtained by transformation of the data) and the non-parametric
method, which does not require Gaussian distributions but uses 2.5 and 97.5 percentiles as the limits (for a review, see Horn and Pesce (2003)).

24

2.4.4. Laboratory markers of ethanol-induced tissue injury
Alcohol-induced tissue injury may be examined with blood tests, although a tissue biopsy is the
only confirmative test (Niemelä 2002, Phillips et al. 2003). The liver enzymes commonly used for
measuring alcohol consumption (GGT, AST, ALT, see next section) reflect the status of the liver
and may also be used to assess liver damage. Serum albumin, bilirubin and alkaline phosphatase
may also be used for this purpose. Markers of the progression of liver disease are usually associated
with collagen and connective tissue metabolism, the most commonly used being the aminoterminal
propeptide of type III procollagen (PIIINP). Other postulated fibrosis markers include the aminoterminal propeptide of type I procollagen (PINP) and hyaluronic acid (HA).

2.4.5. Gender issues
Gender has been reported to influence both the effects of alcohol consumption on health and the
detection of alcohol abuse. Women are known to be more susceptible to the effects of alcohol than
men, particularly to liver disease, for several physiological and metabolic reasons (Lieber 1995,
Schenker 1997, Damström Thakker 1998). Immune responses have also been observed to vary
greatly between the genders, probably due to hormonal factors (Kovacs and Messingham 2002).
When assessing individuals' alcohol consumption, questionnaires appear to be more effective for
men than for women, with AUDIT being the most accurate (Seppä et al. 1995, Aertgeerts et al.
2001). Laboratory tests seem in general to be more accurate for detecting alcohol abuse in men than
in women, and significant gender-dependent differences in the diagnostic usefulness of markers
have been observed (Chalmers et al. 1980, Anton and Moak 1994, Löf et al. 1994, Allen et al. 2000,
Sillanaukee et al. 2001, Neumann and Spies 2003).

2.5. Routinely used biomarkers of ethanol consumption
2.5.1. Ethanol concentration in blood, breath or urine
Measurement of the ethanol concentration in the blood, breath or urine is suitable for acute health
care purposes and provides a specific marker for alcohol intake. It can also give information on the
patient's drinking habits, as blood ethanol levels exceeding 150 mg/l (1.5 ‰ or 33 mM) without
obvious signs of intoxication or 300 mg/l (3.0 ‰ or 65 mM) on any occasion indicate significant
tolerance, which is typically associated with alcohol dependence (Niemelä 2002). The blood alcohol
concentration at the time of admission has been reported to be the best indicator of hazardous drinking practices and alcohol dependence in trauma patients (Ryb et al. 1999, Savola et al. 2004).

2.5.2. Gamma-glutamyl transferase
The liver enzyme gamma-glutamyl transferase (GGT) is one of the most commonly used laboratory
tests for detecting excessive alcohol intake, although it may also be elevated by other causes of liver
damage, e.g. drugs or non-alcoholic liver diseases. Coffee, smoking, obesity and age have also been
25

found to influence GGT values (Cushman 1992, Aubin et al. 1998, Daeppen et al. 1998, Puukka et
al. 2006a, 2006b). There have been several reports of a positive correlation between the amount of
ethanol ingested and serum GGT levels, but the sensitivity of GGT has varied greatly between
populations, from 15 to 85 %, being lower in samples from the general practice (Bagrel et al. 1979,
Chick et al. 1981, Papoz et al. 1981, Anton and Moak 1994, Yersin et al. 1995, Sillanaukee et al.
1998, Hock et al. 2005, Berner et al. 2006). GGT tends to have a relatively low specificity as compared with carbohydrate-deficient transferrin (CDT), for example, because of many sources of unspecificity (Reynaud et al. 2000, Niemelä 2002, Miller and Anton 2004, Hock et al. 2005).
The ethanol consumption needed for an elevation in GGT has been estimated to be over 40 g per
day (Sharpe 2001, Miller and Anton 2004) although no clear threshold has been observed (Schellenberg et al. 2005). GGT values have been estimated to normalize in 2–5 weeks in alcoholics, depending on the original level and the presence or absence of liver pathology (Orrego et al. 1985,
Cushman 1992, Conigrave et al. 2003).

2.5.3. Carbohydrate-deficient transferrin
The first reports on the existence of carbohydrate-deficient transferrin (CDT) in alcoholics were
published almost 30 years ago (Stibler and Kjellin 1976, Stibler et al. 1978, 1979), since when CDT
has emerged as a highly useful marker of excessive ethanol consumption (Stibler 1991, Allen et al.
1994, Golka and Wiese 2004, Bortolotti et al. 2006, Niemelä 2007). Its sensitivity has varied from
20 to 90 %, depending on the population, being higher for men than for women in most studies, and
lower in detecting hazardous drinking than in identifying alcoholism (Bell et al. 1994, Anton and
Moak 1994, Anton and Bean 1994, Litten et al. 1995, Lesch et al. 1996b, Sillanaukee et al. 1998,
Allen et al. 2000, Anton et al. 2001, Berner et al. 2006). The advantage of CDT over other markers
is its high specificity (Stibler 1991). False positives have been reported to occur in rare cases of
genetic transferrin variants (Stibler et al. 1988, Helander et al. 2001) and in certain other conditions
(Sillanaukee et al. 2001, Fleming et al. 2004). Some variation in the results was also observed with
earlier methods that measure the absolute amounts of CDT (U/l) due to variations in total transferrin
levels (Sorvajärvi et al. 1996, Keating et al. 1998, Viitala et al. 1998, Anton et al. 2001). More recently developed methods, which express the CDT results as a percentage of total transferrin, have
improved the performance of this marker (Keating et al. 1998, Helander 1999, Anton et al. 2001,
Helander et al. 2005).
CDT includes isoforms that have fewer carbohydrate (sialic acid) moieties than normal transferrin (Stibler 1991). The predominant isoform in a healthy individual is tetrasialotransferrin, with four
sialic acid moieties, and excessive alcohol consumption has been shown to increase the proportion
of the asialotransferrin and disialotransferrin isoforms, which are generally considered to constitute
CDT. The trisialo fraction is not usually included in CDT measurements and has actually been
found to reduce the diagnostic accuracy of CDT (Mårtensson et al. 1997, Helander et al. 2001,
Arndt et al. 2002, Legros et al. 2002). It is not yet clear how ethanol induces the elevation of CDT,
but it has been suggested that acetaldehyde might either inhibit the enzymes that participate in
transferrin sialylation or activate the deglycosylating enzymes, or both (Stibler and Borg 1991, Xin
et al. 1995, Arndt 2001, Sillanaukee et al. 2001). CDT has been reported to become elevated at
daily ethanol consumptions ranging from 40 to 80 g, with duration of 2 to 3 weeks (Stibler 1991,

26

Schellenberg et al. 2005) although it has been suggested that even higher consumption may be
needed to increase CDT in the general population (Lesch et al. 1996a). The half-life of CDT has
been estimated to be approximately two weeks (Behrens et al. 1988, Stibler 1991, Allen et al.
1994).

2.5.4. Mean corpuscular volume
An increase in the mean corpuscular volume of erythrocytes (E-MCV), or macrocytosis, is typical
of people with chronic excessive ethanol intake, having sensitivities ranging from 20 to 90 %
(Cushman 1992, Bell et al. 1994, Yersin et al. 1995, Reynaud et al. 2000, Mundle et al. 2000).
MCV has proved to be diagnostically more sensitive among women, in whom it may even be superior to other markers (Chalmers et al. 1980, Morgan et al. 1981, Seppä and Sillanaukee 1994, Sillanaukee et al. 1998, Mundle et al. 2000). Several haematological diseases, hypothyroidism, reticulocytosis and vitamin B12 or folic acid deficiency (often related to excessive drinking) and smoking
have been shown to elevate MCV and thus reduce its specificity as an alcohol marker (Sharpe 2001,
Niemelä 2002). Alcohol abuse is frequently the underlying cause of elevated MCV in hospital patients with non-anaemic macrocytosis (Seppä et al. 1991).
The normalization time for MCV is longer than that for any other commonly employed marker,
2 to 4 months, which places limitations on its use for the short-term monitoring of abstinence but
offers a possibility for supervising abstinence over longer periods (Morgan et al. 1981, Mundle et
al. 1999, Niemelä 2002).

2.5.5. Aminotransferases
Other liver enzymes commonly used for detecting excessive drinking are the aminotransferases
(aspartate aminotransferase, AST and alanine aminotransferase, ALT). Although these are frequently elevated in patients with excessive alcohol consumption, they are more directly related to
liver status, so that increased AST and ALT values can be found in other conditions where the liver
is damaged, e.g. due to viral hepatitis or medications (Pratt and Kaplan 2000, Niemelä 2002, Conigrave et al. 2003). It has been suggested that the ratio of AST to ALT may indicate the aetiology of
liver disease: a ratio over 2 often being seen in alcohol-related liver disease, particularly in advanced states (Rosman and Lieber 1994, Nyblom et al. 2004). Aminotransferase levels have been
reported to normalize in 2 to 3 weeks after cessation of drinking, depending on the original level
(Niemelä 2002, Chrostek et al. 2006).

2.6. New biomarkers of ethanol consumption
2.6.1. Acetaldehyde adducts and anti-adduct antibodies
Acetaldehyde adducts are formed when acetaldehyde, the first metabolite of ethanol, reacts with
proteins and cellular constituents (Gaines et al. 1977, Stevens et al. 1981, Niemelä 2001) and may
27

persist in the blood for 1 to 3 weeks after the last dose of ethanol (Niemelä and Israel 1992). The
measuring of these adducts in either erythrocytes or plasma proteins could be of use for determining
recent alcohol consumption (Niemelä and Israel 1992, Sillanaukee et al. 1992b, Lin et al. 1993,
Niemelä 2002). Elevated levels have been reported in moderate drinkers as compared with abstainers (Niemelä and Israel 1992). The specificity of this approach may nevertheless be reduced to
some extent by endogenous acetaldehyde production (Rosman and Lieber 1992).
Acetaldehyde adducts have been shown to induce an immune response, and circulating IgA, IgG
and IgM antibodies, which recognize sequential and conformational epitopes in adducts, have been
found in alcohol-consuming populations (Israel et al. 1986, Koskinas et al. 1992, Tuma and Klassen
1992). Of these, anti-adduct IgAs have emerged as a possible indicator of excessive drinking (Worrall et al. 1994, 1996, 1998, Niemelä 2007).

2.6.2. 5-Hydroxytryptophol
The ratio of two serotonin metabolites, 5-hydroxytryptophol (5HTOL) and 5-hydroxyindole-3acetic acid (5HIAA), has been reported to increase in the urine after heavy drinking (Helander et al.
1992, Voltaire et al. 1992) and to remain elevated for 6–20 h after the disappearance of ethanol (Helander et al. 1993, Carlsson et al. 1993, Helander et al. 1996a). This marker has been suggested as
being of use for assessing recent ethanol ingestion e.g. for monitoring treatment or in forensic investigations, and also for verifying subjects' self-reports in alcohol studies (Helander et al. 1996a,
Helander and Eriksson 2002, Beck and Helander 2003).

2.6.3. Ethyl glucuronide
Ethyl glucuronide (EtG) is a direct non-oxidative metabolite of ethanol that has been reported to
increase in amount in the urine after ethanol ingestion (Dahl et al. 2002, Sarkola et al. 2003). Levels
of EtG may remain detectable for up to 5 days (Wurst et al. 2003) and as an intermediary marker it
could fill up the gap between the known short-term and long-term markers of alcohol consumption
(Wurst et al. 1999, Wurst and Metzger 2002, Wurst et al. 2003). Use of the EtG to creatinine ratio
in the urine has also been suggested, because drinking large volumes of water can lower the EtG
concentration but does not affect the EtG/creatinine ratio (Dahl et al. 2002, Bergström et al. 2003).
EtG has been found in serum, urine, tissues and even hair and may have significant applications in
both clinical and forensic medicine (Wurst et al. 1999, 2003, Bergström et al. 2003).

2.6.4. Fatty acid ethyl esters
Fatty acid ethyl esters (FAEEs), which are formed when ethanol reacts with fatty acids, were first
found in organs damaged by ethanol and also suggested as mediators of organ damage (Laposata
and Lange 1986, Laposata 1997). Later, their presence in serum and hair after ethanol intake was
also confirmed (Doyle et al. 1994, Pragst et al. 2001). FAEEs have been proposed as markers of
alcohol consumption, both in short term (measurements in serum) and long term (hair analysis)
(Doyle et al. 1996, Laposata 1997, Auwärter et al. 2001). They have been reported to remain de-

28

tectable in serum for up to 24 h after ethanol ingestion (Doyle et al. 1994), and for even longer periods in heavy drinkers (Borucki et al. 2004).

2.6.5. Phosphatidylethanol
Phosphatidylethanol (PEth) is formed from phospholipides when ethanol is present, in a reaction
catalyzed by phospholipase D (Gustavsson 1995). Blood PEth has been reported to correlate closely
with ethanol consumption, but detectable PEth levels may not occur until ethanol consumption is
relatively high (Hansson et al. 1997, Varga et al. 1998, Aradottir et al. 2006). PEth may be detected
for more than two weeks after last dose of ethanol (Hansson et al. 1997, Gunnarsson et al. 1998) so
that it has been suggested as a possible marker of excessive drinking (Varga et al. 1998, Aradottir et
al. 2006).

2.6.6. Sialic acid
Studies have suggested that concentrations of sialic acid (SA), a carbohydrate predominantly found
in the oligosaccharide chains on the surface of cell membranes and macromolecules (Traving and
Schauer 1998), are often elevated in serum and saliva of alcoholics and might serve as an alcohol
marker (Pönniö et al. 1999a, Sillanaukee et al. 1999b, Romppanen et al. 2002). However, SA concentrations seem to increase in a number of other conditions as well, e.g. in inflammatory and cardiovascular diseases, diabetes and cancer, which limits its use as a marker of excessive drinking
(Stefenelli et al. 1985, Sillanaukee et al. 1999a). In addition, body mass index (BMI), blood pressure, ageing, hormonal factors and smoking may cause variations in SA levels (Pönniö et al.
1999b). The presence of SA in the saliva of alcoholics could be of use when considering noninvasive methods of assessing alcohol intake (Pönniö et al. 1999a). SA concentrations also appear
to decrease during abstinence with a time range of several weeks (Pönniö et al. 1999a, Sillanaukee
et al. 1999b, Anttila et al. 2005).
Another application involving sialic acid is the plasma sialic acid index (SIJ) of apolipoprotein J
(ApoJ), referring to the number of sialic acid moieties of ApoJ. This index has been found to decrease as a consequence of chronic ethanol intake and could possibly serve as a marker of excessive
drinking (Ghosh et al. 2001).

2.6.7. Other postulated markers
In addition to other direct ethanol metabolites (EtG, FAEEs, PEth), ethyl sulphate (EtS) in the urine
has been introduced as a potential marker of alcohol consumption. It appears to have quite similar
characteristics to EtG (Wurst et al. 2006).
Other suggested markers of alcohol intake include hepatic lysosomal enzyme β-hexosaminidase,
which has been shown to increase in alcoholics (Isaksson et al. 1985, Kärkkäinen et al. 1990, Hultberg et al. 1991), but also in non-alcoholic liver disease and in some other conditions, which limits
its usefulness (Rosman and Lieber 1992, Javors and Johnson 2003).

29

Urinary dolichols are polyprenol compounds, which have been reported to increase in chronic
alcoholics (Pullarkat and Raguthu 1985, Roine et al. 1987). Their use as a marker, however, suffers
from a lack of both sensitivity (Stetter et al. 1991) and specificity (Roine et al. 1989, 1991).
In addition, mitochondrial AST (mAST) (Nalpas et al. 1986), erythrocyte ALDH (Agarwal et al.
1983), urinary salsolinol (Collins et al. 1979, Haber et al. 1995) and urinary alanine aminopeptidase
(Taracha et al. 2004) have also been proposed as indicators of excessive drinking. More research
into these postulated markers is needed in order to establish their clinical value and usefulness.

2.7. Marker combinations
Despite the abundance of potential markers, none of them has so far achieved perfect diagnostic
accuracy. Some researchers during the past 20 years have suggested that a diagnostic improvement
could be achieved by combining two or more alcohol markers (Monteiro and Masur 1985,
Salaspuro 1987, Niemelä and Israel 1992, Yersin et al. 1995, Anton et al. 2001, Sillanaukee and
Olsson 2001, Hock et al. 2005). An ideal combination would consist of markers which are affected
in different ways by alcohol intake. GGT and CDT, for example, do not correlate in the alcoholic
population and seem to be elevated in partially different populations, possibly reflecting independent mechanisms by which ethanol induces their elevation (Anton and Moak 1994, Helander et al.
1996b, Huseby et al. 1997, Anton et al. 2001, Conigrave et al. 2002).
The first researchers who studied the use of test results in combination integrated a large panel
of laboratory tests into a single score by mathematical methods (Beresford et al. 1982, Hillers et al.
1986, Hartz et al. 1997, Harasymiw et al. 2000, Harasymiw and Bean 2001). The use of large test
panels with dozens of assays would not, however, be either rational or cost-effective, and thus more
interest has been shown in combining two or three markers of alcohol consumption. The conventional manner of combining markers is to see whether either is elevated. This approach has been
found to give improved assay sensitivity but is frequently associated with a decrease in specificity
(Rosman and Lieber 1992, Anton and Moak 1994, Helander et al. 1996b, Huseby et al. 1997, Anton
et al. 2001, Schwan et al. 2004). Researchers have also introduced the idea of combining markers
by means of mathematical equations (Sillanaukee 1992, Sillanaukee and Olsson 2001), whereupon
the sensitivities appear to increase without significant loss of specificity (Sillanaukee and Olsson
2001, Anttila et al. 2003, Chen et al. 2003). The most frequently used components of such combinations are CDT and GGT, and some researchers have also included MCV as a third component (Sillanaukee et al. 1998, Sillanaukee and Olsson 2001, Anttila et al. 2003, Hock et al. 2005). A promising approach was introduced by Sillanaukee and Olsson (2001), who combined GGT and CDT by
means of the equation 0.8 x ln(GGT) + 1.3 x ln(CDT) and reported sensitivities of 79 % (men) and
72 % (women) for this marker. A further improvement in this combination was achieved by replacing absolute CDT values with %CDT (Anttila et al. 2003). The marker has been reported to be more
sensitive for detecting excessive drinking in men than in women (Sillanaukee and Olsson 2001,
Anttila et al. 2003, Chen et al. 2003). Chen and co-workers (2003) also found that integrating clinical information with the combined marker would be useful for the accuracy of detection.

30

More research into combinations of markers is needed in order to establish their usefulness in
screening for excessive drinking. Their cost-effectiveness would also need to be evaluated in order
to assess whether the improvement in detection is worth the increase in assay costs. The long-term
effects of any improvement in early detection and treatment should also be taken into consideration
in cost-effectiveness analyses.

2.8. Laboratory markers for the follow-up of alcoholics
Laboratory markers play an important role in the monitoring of abstinence in treatment units and in
health care, and they are also used for legal purposes, e.g. for the supervision of drunken drivers. A
suitable marker for follow-up purposes should normalize at a steady rate with as little interindividual variation as possible and should also react to relapses of drinking during follow-up.
For the moment, CDT is the most favoured marker for follow-up purposes, as it has been observed to decrease steadily during abstinence and to be suitable for detecting relapses (Schmidt et
al. 1997, Allen et al. 2001, Sharpe 2001, Anton et al. 2002). Determination of the patient's CDT
baseline could be of use in the monitoring process, as a 30 % elevation from the baseline may indicate a relapse (Borg et al. 1995, Anton et al. 2002). CDT appears to be especially suitable for follow-up in the case of men and of patients with liver disease (Bell et al. 1993, Anton et al. 1996, Allen et al. 1999, Anton et al. 2002), since the use of GGT and other liver enzymes in follow-up may
be complicated by the fact that they are affected by liver status (Rosman and Lieber 1994). Thus
they have usually not performed as well as CDT in follow-up studies (Bell et al. 1993, Salaspuro
1999, Anttila et al. 2004).
Markers of recent alcohol consumption (particularly the direct metabolites of ethanol) may
prove to be of significant value for follow-up purposes (Hansson et al. 1997, Wurst et al. 1999, Helander and Eriksson 2002, Bisaga et al. 2005, Wurst et al. 2005), and as these markers have different time frames with respect to detection (from hours to weeks) it might be possible to select suitable markers for different situations.
Combinations of markers have also been proposed for the follow-up of treatment. CDT together
with the 5HTOL/5-HIAA ratio in urine could serve as an accurate marker for detecting a recent
relapse (Carlsson et al. 1993), and another useful combination for this purpose could be GGT and
CDT (Allen et al. 1999, Anton et al. 2002).

2.9. Immune responses related to alcohol consumption
2.9.1. Immune responses to ethanol metabolites
Acetaldehyde is a highly reactive molecule and can form stable condensates with various proteins
and cellular constituents (Gaines et al. 1977, Stevens et al. 1981, Wehr et al. 1993, Svegliati-Baroni
et al. 1994, Braun et al. 1997, Niemelä 2001), and other ethanol metabolites such as malondialde31

hyde and 4-hydroxynonenal are also capable of generating protein adducts (Niemelä 2001). Acetaldehyde adducts may result in altered protein function and play a part in the stimulation of fibrogenesis and the induction of immune responses (Tuma and Sorrell 1987, Niemelä 1999). They have
been found in both the circulation and tissues of alcoholics in increased amounts as compared with
control populations (Stevens et al. 1981, Peterson and Polizzi 1987, Niemelä and Israel 1992, Sillanaukee et al. 1992b, Niemelä 2001). Haemoglobin-acetaldehyde adduct levels seem to correlate
with self-reported ethanol consumption (Sillanaukee et al. 1991a, 1991b, Hazelett et al. 1998) and
have thus been suggested as markers of alcohol intake (Niemelä et al. 1990, Sillanaukee et al.
1991b, Gross et al. 1992, Niemelä and Israel 1992, Sillanaukee et al. 1992b, Lin et al. 1993, Hazelett et al. 1998). They have been found to persist in the blood for 1 to 3 weeks (Niemelä and Israel
1992). The earliest methods for measuring haemoglobin-acetaldehyde adducts were based on chromatography and isoelectric focusing (Stevens et al. 1981, Huisman et al. 1983, Nguyen and Peterson 1984, Gordis and Herschkopf 1986, Sillanaukee and Koivula 1990), and antibody-based assays
have been developed more recently (Lin et al. 1990, Niemelä et al. 1990, Niemelä and Israel 1992).
Of the adducts localized in tissues, liver adducts have been the most intensively studied, and
their association with alcohol-induced liver damage has been well established (Niemelä et al. 1991,
Holstege et al. 1994, Paradis et al. 1996, Li et al. 1997, Niemelä 2001). There is only limited information on adducts in other tissues, but other potential sites of adduct formation are the alimentary
tract and pancreas (Iimuro et al. 1996, Salmela et al. 1997, Biewald et al. 1998, Niemelä 2001). Adducts have also been localized in the muscles and brain (Rintala et al. 2000, Worrall et al. 2000,
Niemelä 2001, Worrall et al. 2001) and in erythrocyte cell membranes (Niemelä and Parkkila
2004).
Acetaldehyde adducts are immunogenic and may trigger antibody responses that appear to be
specific to acetaldehyde-modified epitopes and not to depend on the carrier protein (Niemelä et al.
1987). Class IgG, A and M antibodies against acetaldehyde adducts have been found in the
circulation of alcohol consumers (Israel et al. 1986, Niemelä et al. 1987, Hoerner et al. 1988, Israel
et al. 1988, Izumi et al. 1989, Worrall et al. 1991, Koskinas et al. 1992, Tuma and Klassen 1992,
Worrall et al. 1994, Viitala et al. 1997). Class IgA antibodies against acetaldehyde adducts have
proved to be the most promising for differentiating between excessive drinkers and control individuals, the highest anti-adduct IgA values being observed in alcoholics with liver disease (Hoerner
et al. 1988, Izumi et al. 1989, Worrall et al. 1991, Koskinas et al. 1992, Viitala et al. 1997), although those without liver disease also show elevated values as compared with non-drinkers (Worrall et al. 1994, 1996, Viitala et al. 1997, Worrall et al. 1998). IgG and IgM responses also show
changes after ethanol ingestion, but not as distinctly as IgA (Worrall et al. 1991, 1994, Viitala et al.
1997).
It is still unclear whether the antibody responses to acetaldehyde adducts reflect protective or
harmful effects. It has been suggested that the generation of these responses may contribute to the
pathogenesis of alcoholic liver disease (Niemelä et al. 1987, Israel et al. 1988, Izumi et al. 1989),
but it is also possible that the antibodies may serve as neutralizing factors by binding and removing
acetaldehyde adducts from the circulation (Israel et al. 1988). It has been speculated that immunological damage to tissues may develop in the presence of both high antibody levels and continuous adduct formation i.e. continuous alcohol intake (Israel et al. 1988).

32

2.9.2. Alcohol-induced cytokine responses
The involvement of cytokine responses in alcohol-related liver injury has been widely studied in
recent years (Khoruts et al. 1991, Deviere et al. 1992, McClain et al. 1993, Border and Noble 1994,
Peters 1996, Yin et al. 1999, Neuman 2003, Bode and Bode 2005). Cytokines are a group of proteins that modulate immune responses and participate in cell growth and differentiation and they
can be classified as either pro-inflammatory or anti-inflammatory, although they may have overlapping or multiple functions depending on the cell type. An important function of cytokines is to recruit the cells of the immune system to a site of inflammation (McClain et al. 1997). Cytokines include several classes of molecules: interleukins (IL), tumor necrosis factor (TNF), transforming
growth factor (TGF) and interferons (IFN). The currently known family of cytokines has over 100
members altogether, working in concert to produce either anti-inflammatory or pro-inflammatory
effects depending on the target cells and organs.
Under normal circumstances the liver tissue produces only minimal levels of cytokines (Neuman 2003), but when the liver suffers damage, e.g. due to excessive alcohol consumption, their production increases and the resulting cytokines mediate the regeneration of liver tissue (Peters 1996).
This process includes an inflammatory response, which is required for normal tissue healing, and
the cytokine levels return to baseline levels when the inflammation is under control (Neuman 2003).
It appears that acute moderate alcohol intake leads to inhibition of this inflammatory process
(through increases in anti-inflammatory and decreases in pro-inflammatory cytokine production),
while chronic alcohol consumption shifts the cytokine balance towards persistent inflammation
(Crews et al. 2006). Patients with alcoholic liver disease appear to have elevated pro-inflammatory
(e.g. IL-1, IL-6, TNF-α, and IL-8) and lowered anti-inflammatory (IL-10, IL-4) cytokine levels
(McClain et al. 1997, Cook 1998, Crews et al. 2006). The continuous presence of pro-inflammatory
cytokines and inflammation in the liver (alcoholic hepatitis) may ultimately lead to scar tissue formation (fibrosis) and cirrhosis (Neuman 2003). Apoptosis has also been shown to contribute to the
tissue damage that occurs in alcoholic liver disease and this process may be induced by ethanol (Casey et al. 2001, Neuman 2003).
The increased intestinal permeability observed in alcoholics has been shown to lead to elevated
bacterial lipopolysaccharide (LPS) concentrations in the circulation, whereupon the resulting endotoxaemia may lead to the activation of liver macrophages and induces them to produce proinflammatory cytokines. This cascade leads to inflammation in the liver and may initiate or promote
the pathogenesis of alcoholic liver disease (Wheeler 2003, Bode and Bode 2005). The LPS pathway
may in fact represent a significant contributor to the onset of alcoholic liver disease (Bode and Bode
2005).

33

3. Aims of the present research

Despite advances in methods of detecting excessive alcohol consumption, the incidence of alcoholism and its associated medical, social and economic problems continue to increase in many Western
societies. Accurate screening tools and a better understanding of the primary mechanisms involved
in the adverse health effects of alcohol are clearly needed.

The aims of the present work were as follows:
1.
2.
3.
4.

To study the influence of the reference population on the reference intervals of gammaglutamyltransferase and other markers of excessive alcohol consumption.
To study the clinical behaviour of the marker combination GGT-CDT in assessing alcohol
consumption.
To examine the association between immune responses to acetaldehyde adducts, alcoholinduced liver disease and alcohol consumption.
To develop a new marker for excessive drinking based on a specific immune response to acetaldehyde adducts.

34

4. Materials and methods

4.1. Subjects
The excessive drinkers included in these studies were alcoholics who were recruited from a detoxification and alcoholism treatment unit. They had all been classified for alcohol dependence by reference to the DSM-IV criteria and had a well-documented history of excessive drinking. Detailed
interviews on their alcohol consumption were carried out using a timeline follow-back method, according to which the patients were asked how many drinks of alcohol (standard drink = 12 g of
ethanol) they had consumed during the past 24 h, the past week and the past 4 weeks before admission. The mean duration of abstinence prior to sampling was 2 ± 2 days. The patients with alcoholic
liver disease had all had a history of continuous ethanol consumption for at least five years (> 80
g/day) and the liver disease had been assessed by a previously established combined morphological
index (CMI) or a combined clinical and laboratory index (CCLI) (Orrego et al. 1983, Blake and
Orrego 1991). All the excessive drinkers were negative for hepatitis B antigen or hepatitis C serology. The reference population consisted of apparently healthy abstainers and moderate drinkers
who had mostly been recruited from hospital personnel and who had no previous social or medical
history of excessive drinking. The mean daily alcohol consumption of the moderate drinkers, as
assessed with questionnaires, was 1–40 g. Blood sampling was performed by trained laboratory
personnel. The analyses of liver enzymes and blood cell counts were performed immediately and
the serum samples separated by centrifugation were then stored at –70 °C until used for additional
analyses. The participants gave their informed consent and the research was carried out in accordance with the provisions of the Declaration of Helsinki.
The subjects in paper I included 195 individuals, comprising 103 alcoholics (90 men, 13
women) and 92 reference individuals (54 men, 38 women). The population of alcoholics had no
signs of liver damage and their mean consumption of ethanol had been 40–539 g per day during the
past 4 weeks. The reference population included 30 abstainers and 62 moderate drinkers with a
mean daily ethanol consumption of 1–40 g. For the comparisons between moderate drinkers and
abstainers, additional data were included from a survey on 2485 apparently healthy individuals
(1174 men, 1311 women) collected for the Nordic Reference Interval Project, as kindly provided by
the project coordinator, Professor Pål Rustad, Fürst Medical Laboratory, Oslo, Norway. These subjects were either abstainers (n = 1156: 471 men, 685 women) or moderate drinkers (n = 1329: 703
men, 626 women), the maximum alcohol consumption during the twenty-four hours prior to sampling having been 24 g (two standard drinks). Weekly alcohol consumption was assessed by means
of questionnaires employing categories of a) 0 drinks, b) 1–21 drinks and c) over 21 drinks, and
category c was excluded from the analyses. The survey also excluded individuals who had clinical
or laboratory evidence of current or recent illnesses or infections, were pregnant, had donated blood
during the past five months or had taken any prescription drugs during the preceding week. Smoking had not been allowed for one hour prior to sampling.
35

Paper II reports on a sample of 165 alcoholics (140 men, 25 women) with a mean daily ethanol
consumption of 40–540 g during the past month. They were further classified according to liver
status, with 51 patients (38 men, 13 women) designated as having liver disease. In order to assess
marker normalization rates, follow-up tests with supervised abstinence periods of 11 ± 4 days (confirmed with repeated breath analyses) were carried out on 44 alcoholics (39 men, 5 women). The
reference population comprised 86 healthy volunteers (49 men, 37 women), including 35 abstainers
and 51 moderate drinkers.
Paper III consisted of 86 male alcoholic patients (mean age 48 ± 12 years), of whom 54 had biopsy-proven liver disease and 32 had no clinical or laboratory evidence of significant liver disease.
A follow-up with supervised abstinence for 8 ± 2 days, controlled by means of hospitalization and
repeated breath analyses was carried out on 17 patients. The reference population consisted of 20
apparently healthy male volunteers who were either abstainers (n = 6) or moderate drinkers (n = 14)
with a mean daily ethanol consumption of 20 g (a maximum of 60 grams on any one occasion).
The subjects in paper IV consisted of 40 male alcoholics who had no clinical or laboratory signs
of liver disease, but had a history of continuous ethanol consumption or binge drinking, the mean
recent consumption having been 40–540 g/day for a period of 4 weeks prior to sampling. 19 alcoholics (mean age 42 ± 12 years) volunteered for a follow-up, which was carried out with supervised
abstinence over a period of 8 ± 3 days. In addition, there were 41 male reference individuals who
were either abstainers (n = 16) or moderate drinkers (n = 25), none of whom had any history or
clinical evidence of alcohol abuse, recent illnesses or immunological disorders.

4.2. Measurements of laboratory markers (I-II, IV)
CDT concentrations were measured using a turbidimetric immunoassay (TIA) after ion exchange
chromatography (%CDT, Axis-Shield, Oslo, Norway). This assay detects primarily asialo-,
monosialo- and disialotransferrin, although there may be some reactivity to the trisialo fraction of
CDT, as recently reported by Aldén and co-workers (2005). The %CDT results are expressed as
percentages of total transferrin. The measurements were carried out on a Behring Nephelometer II
(Dade Behring, Behring Diagnostics GmbH, Marburg, Germany). The within-run precision of the
assay was 4.7 %, day-to-day variation 6.0 % and accuracy 12.7 %.
Serum gamma glutamyl transferase (GGT), serum aspartate aminotransferase (AST), serum
alanine aminotransferase (ALT), alkaline phosphatase, albumin, bilirubin and mean corpuscular
volume (MCV) of erythrocytes were measured by standard clinical chemical methods in an accredited (SFS-EN ISO/IEC 17025) laboratory at Seinäjoki Central Hospital, Finland. The assay characteristics for these were as follows (assay; within-run variation, day-to-day variation, accuracy):
GGT; 0.85 %, 0.54 %, 5.0 %, AST; 0.90 %, 1.5 %, 10.6 %, ALT; 0.87 %, 1.1 %, 12.1 %, alkaline
phosphatase; 2.0 %, 1.9 %, 10.1 %, albumin; 2.3 %, 2.0 %, 11.2 %, bilirubin; 2.2 %, 2.4 %, 13.4 %
and MCV; 0.41 %, 0.37 %, 3.7 %. The cut-offs for these parameters were as follows: GGT < 80 U/l
(men), < 50 U/l (women); AST and ALT < 50 U/l (men), < 35 U/l (women); alkaline phosphatase
60–275 U/l; albumin 36–50 g/l; bilirubin 2–20 µmol/l; MCV 76–96 fl.

36

4.3. Determination of marker combinations (II, IV)
4.3.1. GGT-CDT (II)
The original equation for combining GGT and CDT in the present manner was suggested by Sillanaukee and Olsson (2001), who used absolute CDT values (U/l). These were later replaced with
%CDT results (Anttila et al. 2003). In the present work the combined GGT-CDT marker was calculated in the latter manner (Anttila et al. 2003): GGT-CDT = 0.8 x ln(GGT) + 1.3 x ln(%CDT). The
assay cut-off values were determined with ROC analyses using Analyse-It for Microsoft Excel
software, which yielded a GGT-CDT cut-off of 4.18 for men and 3.81 for women.

4.3.2. IgA-CDT
Several equations for combining %CDT and anti-adduct IgA results were tested for differentiating
between alcoholics and the control population. The IgA-CDT marker was eventually calculated
according to an equation logCDT + (IgA/103), which appeared to be superior to the others tested.
The cut-off value was 0.412, as determined by ROC analysis.

4.4. Measurement of antibodies against acetaldehyde adducts (III-IV)
The test antigen was prepared by purifying a human erythrocyte fraction from the EDTA-blood of
an abstainer. The cells were separated by centrifugation and washed three times with phosphatebuffered saline (PBS: 7.9 mM Na2HPO4, 1.5 mM KH2PO4, 137 mM NaCl, 2.7 mM KCl, pH 7.4).
They were then haemolyzed with polyoxyethylene ether, 0.1 % V/V in borate buffer (Hemolysis
Reagent, DIAMATTM Analyzer system, Bio-Rad) and incubated for 35 min at 37 °C to remove unstable Schiff bases. The haemolyzate was diluted with PBS to contain 12 mg/ml of protein, dialysed
twice against PBS and then mixed with acetaldehyde (in PBS) so that the final concentration of the
latter in the reaction mixture was 10 mM. The mixture was allowed to react overnight (18 h) at 4 °C
in a tightly sealed container and the adducts generated were reduced by the addition of sodium
cyanoborohydride (10 mM) and mixed for 5 h at 4 °C. The reduced protein solutions were then dialysed twice against PBS at 4 ºC and stored in aliquots for single use at –70 ºC. The unmodified
proteins were prepared and treated similarly to the modified proteins except for the addition of acetaldehyde.
For the measurement of antibody titres, microtitre plates (Nunc-Immuno Plate, MaxisorpTM, InterMed, Denmark) were coated with acetaldehyde-modified red cell protein or corresponding unmodified protein in PBS (3 µg protein in 100 µl/well) and incubated for 1½ h at +37 °C. Nonspecific binding was blocked by incubation with 0.2 % gelatin in PBS (150 µl/well) for 1 h at +37
°C. The samples were diluted (1:40) in PBS containing 0.04 % Tween 20 (PBS-Tween) and 50 µl
of the diluted serum was allowed to react with the coated proteins (1 h, +37 °C). The plates were
then washed extensively with PBS-Tween. Alkaline phosphatase -linked goat anti-human immunoglobulins IgA, IgG, or IgM (Jackson ImmunoResearch Laboratories, Inc., West Grove) were

37

used to detect antibody-antigen complexes. The immunoglobulins (50 µl/well) were diluted in PBSTween containing 8 mM MgCl2 and a small amount of dithiothreitol (DTT). The plates were incubated overnight at +4 °C and washed with PBS-Tween. After washing, 100 µl of pnitrophenylphosphate solution was added as a colour reaction substrate (Alkaline Phosphatase Substrate Kit, Bio-Rad Laboratories, Hercules, CA). This reaction was stopped by adding 100 µl NaOH
(0.4 M) and the optical densities (ODs) were read at 405 nm with an Anthos HTII microplate reader
(Anthos Labtec Instruments, Salzburg, Austria). The anti-adduct IgA results are expressed as
units/litre (U/l), corresponding to OD405 nm x 103.

4.5. Serum cytokines
The concentrations of serum cytokines (IL-2, IL-6, IL-8, IL-10, TNF-α and TGF-β1) were determined using Quantikine high sensitivity ELISA kits (R&D Systems Inc., Minneapolis, USA). The
results are presented in U/l units, which correspond to OD(450 nm–540 nm) x 103. The analytical characteristics, as given by the assay manufacturer, were as follows (assay; average within-run variation,
average day-to-day variation, detection limit): IL-2; 3.1 %, 4.6 %, 7 pg/ml, IL-6; 2.6 %, 4.5 %, 0.70
pg/ml, IL-8; 5.8 %, 7.7 %, 3.5 pg/ml, IL-10; 3.7 %, 6.9 %, 3.9 pg/ml, TNF-α; 4.7 %, 5.8 %, 1.6
pg/ml, TGF-β1; 5.3 %, 11.0 %, 7 pg/ml. All the assays were linear within their dynamic range.

4.6. Statistical methods
The statistical analyses were carried out using GraphPad Prism (GraphPad Software Inc., San
Diego, CA, USA) and SPSS 13.0 (SPSS Inc., Chicago, IL, USA) and the ROC analyses with Analyse-it software (Analyse-it Software Ltd, Leeds, U.K.).
The t-test was used for comparisons between two groups following a Gaussian distribution, and
the Mann-Whitney test was used for non-Gaussian populations. For comparisons of three or more
groups, a one-way analysis of variance (ANOVA) with Bonferroni’s post hoc test was employed
when the data followed Gaussian distribution and passed the homogeneity of variance test, while
the Kruskal-Wallis test with an appropriate post hoc test was used if a Gaussian distribution or
equal variances in the groups could not be obtained from the original data or from the logarithmically transformed data.
Correlations were calculated using Pearson product-moment correlation coefficients for continuous non-skewed parameters or Spearman’s rank correlations for non-continuous or skewed parameters, as required. A p-value of less than 0.05 was considered statistically significant.
Cut-off values for new markers were either determined with ROC-analyses or calculated as
mean + 2 SD of the control group.

38

5. Results

5.1. Influence of drinking levels on markers (I, II, IV)
In paper I, GGT was measured in a large population of alcoholics, moderate drinkers and abstainers.
The concentration in alcoholics consuming 40–80 g (68 ± 54 U/l) or > 80 g (167 ± 254 U/l) of ethanol per day significantly exceeded those in both the abstainers (p < 0.001) and the moderate drinkers (p < 0.001) consuming ethanol in amounts ranging from 1 to 40 g per day. GGT activities were
also found to be significantly higher in the moderate drinkers (28 ± 23 U/l) than in the abstainers
(24 ± 17 U/l) (p < 0.001). When experimental reference intervals were calculated from these populations, the upper limits were found to be on average 43 % higher when the moderate drinkers were
taken as the source than when calculated for the abstainers. Gender and age were also found to have
an effect on the reference intervals; the limits for men were higher than for women and the age
group > 40 years had higher levels than the age group 18–39 years in both genders. The fluctuation
in reference intervals due to the choice of reference population was found to have a significant effect on the sensitivity of GGT, so that 69 % of the heavy drinkers were identified when contrasted
with the abstainers, as opposed to 56 % with the moderate drinkers.
The inclusion of moderate drinkers in the reference population was also found to lead to decreases in the sensitivity of MCV and AST whereas GGT-CDT and CDT were not affected. The
anti-adduct IgA responses studied in paper IV were also found to be affected by moderate drinking,
as these values were significantly higher in the moderate drinkers than in the abstainers (p < 0.05).

5.2. Clinical characteristics of marker combinations (II, IV)
5.2.1. GGT-CDT (II)
The performance of a mathematical combination of GGT and CDT, assessed in paper II, was found
to be superior to that of the conventional laboratory markers in detecting excessive drinking. GGTCDT reached a sensitivity of 90 % (for a specificity of 98 %), whereas the sensitivity of CDT alone
remained at 63 % and that of GGT at 58 %. The sensitivities and specificities of GGT-CDT were
high for both men and women. Combining GGT and CDT in a manner which gave a positive result
when either of the markers was positive obviously yielded a higher sensitivity (85 %) than either
assay alone, but did not reach the sensitivity of the mathematically formulated combination. Liver
status was not found to complicate the assessment of alcohol consumption with GGT-CDT, the sensitivities being quite similar for both alcoholics with (93 %) and without (88 %) liver disease, while
the performance of GGT, MCV, AST and ALT was clearly dependent on liver status. Elevation of

39

the GGT-CDT marker was estimated to require a threshold ethanol consumption of 40 g per day,
and GGT-CDT was found to correlate more closely with self-reported ethanol consumption (r =
0.76, p < 0.001) than either GGT (r = 0.71, p < 0.001) or CDT (r = 0.59, p < 0.001) alone or any of
the other markers.

5.2.2. IgA-CDT (IV)
When the possibility of using anti-adduct IgA results in marker combinations was examined in paper IV, the highest sensitivities and specificities were obtained by combining these with CDT in a
mathematical equation. This approach yielded a sensitivity of 90 %, a specificity of 98 % and an
AUC of 0.966. Preliminary analyses suggest that IgA-CDT may to be comparable or even superior
to GGT-CDT (Figure 1).

100

90 %
83 %

Sensitivity, %

80

65 %

63 %

60

43 %

41 %

38 %

40
20
0
IgA-CDT

GGT-CDT

IgAs

CDT

GGT

MCV

AST

Figure 1. Sensitivity of laboratory markers and their combinations in detecting excessive drinking.
IgA-CDT, a combination derived from the equation logCDT + (IgA/103); GGT-CDT, a combination
derived from the equation 0.8 x ln(GGT) + 1.3 x ln(%CDT); IgAs, immunoglobulin A against acetaldehyde adducts; CDT, carbohydrate-deficient transferrin; GGT, gamma-glutamyl transferase;
MCV, mean corpuscular volume of erythrocytes; AST, aspartate aminotransferase.

40

5.3. Antibody and cytokine responses in alcoholics (III–IV)

5.3.1. Alcohol-related changes in cytokine and antibody production (III-IV)
Alterations in anti-adduct immunoglobulin levels were found in alcoholics, particularly in those
with liver disease. The anti-adduct titres were measured for immunoglobulin classes IgA, IgG and
IgM in paper III, while paper IV focused on the characteristics of anti-adduct IgA as a marker of
excessive drinking. The highest anti-adduct IgA and IgG titres were found in the patients with alcoholic liver disease (paper III), the differences relative to the moderate drinkers and the abstainers
being significant (p < 0.001), while the alcoholics without any apparent liver disease also showed
elevated IgA levels as compared with both control groups (p < 0.01). IgM titres were highest in the
alcoholics without liver disease, and the values for the moderate drinkers were also higher than for
the abstainers (p < 0.05), as was also the case for class IgA antibodies. There were no significant
differences in total serum immunoglobulin levels between the groups.
Cytokine profiles were measured in paper III in order to assess the effects of alcohol intake and
liver disease on the regulation of inflammation. The alcoholics with liver disease showed markedly
increased levels of pro-inflammatory cytokines IL-2, IL-6, IL-8 and TNF-α, and decreased TGF-β1,
while those without liver disease had normal or slightly elevated pro-inflammatory cytokine levels,
except for IL-6, which was high in both alcoholic groups as compared with the control groups (p <
0.001). IL-10 levels were higher in all the alcohol-consuming groups than in the abstainers.
Anti-adduct IgA values were found to correlate significantly (p < 0.001) with recent ethanol
consumption (r = 0.77), as also were IL-6 levels (r = 0.83, p < 0.001).

5.3.2. Anti-adduct IgAs as a marker of alcohol consumption (IV)
When anti-adduct IgAs and various traditional alcohol markers were measured in a population
comprising alcoholics, moderate drinkers and abstainers, the alcoholics showed elevated levels as
compared with either the moderate drinkers (p < 0.001) or the abstainers (p < 0.001). The diagnostic
characteristics of anti-adduct IgAs for detecting excessive drinking were compared with those of the
conventional markers CDT, GGT, MCV and AST by contrasting the data obtained for the alcoholics with those obtained for the abstainers and/or moderate drinkers. The sensitivity of anti-adduct
IgAs using abstainers as the reference population was 73 % for a specificity of 94 %, which exceeded the corresponding figures obtained for CDT, GGT, MCV and AST. When moderate drinkers
were also included in the reference population, the sensitivity of the anti-adduct IgA assay was 65
% for a specificity of 88 %, showing essentially similar characteristics to CDT while remaining
superior to GGT, MCV or AST. The sensitivity of anti-adduct IgAs can be further improved by
combining it with CDT (see section 5.2.2.).
The anti-adduct IgA values showed significant correlations with all the conventional markers of
alcohol consumption and also with actual recent consumption. Anti-adduct IgAs were found to cor-

41

relate significantly with serum IL-6 (r = 0.33, p < 0.05) and TNF-α (r = 0.31, p < 0.05), but not with
IL-2, IL-8, IL-10 or TGF-β1.

5.4. Markers in the follow-up of alcoholics (II-IV)
Marker normalization was examined in papers II and IV, and changes in cytokine levels were also
addressed in paper III. GGT-CDT was found to decrease in 93 % of alcoholics during 11 ± 4 days
of supervised abstinence, and the normalization rate was estimated to be 18 ± 9 days, depending on
the initial value. GGT-CDT and CDT showed more consistent declines during abstinence than did
GGT, MCV, AST or ALT.
Anti-adduct IgG ad IgM values in the alcoholics did not show any significant changes upon abstinence, but a significant decrease was observed in anti-adduct IgA levels (papers III and IV),
which also remained higher in the alcoholics after abstinence than in the moderate drinkers or the
abstainers. Assessment of the normalization rate of anti-adduct IgAs in paper IV showed it to be
about 3 % per day, with a mean normalization time of about four weeks, depending on the original
level.
Significant changes were also noted in the levels of cytokines during abstinence, the changes in
IL-6 (–47 %), IL-10 (–82 %) and TNF-α (–41 %) being significant, whereas IL-2 (± 0 %), IL-8 (–26
%) and TGF-β1 (+3 %) remained relatively stable. IL-6 levels still remained higher after abstinence
than those in the control groups (p < 0.05 for moderate drinkers; p < 0.001 for abstainers).

42

6. Discussion

6.1. Influence of moderate drinking on marker levels (I-IV)
The present data indicate that moderate drinking has an influence on several biomarkers of alcohol
consumption, which could lead at the population level to changes in reference intervals and subsequently to problems in recognizing excessive alcohol consumption in its early phase. It would therefore be essential to define reference intervals on the basis of abstainers rather than moderate drinkers. In order to obtain universally comparable policies, the concept of moderate drinker should also
be defined more accurately in terms of both drinking pattern and alcohol intake.
Serum GGT concentrations were observed to be significantly elevated in alcoholics and also in
moderate drinkers as compared with the abstainers (paper I), and the estimated upper normal limits
for GGT would be approximately 40 % higher if moderate drinkers were used as the reference
population instead of abstainers. This situation was also reflected in a recent NORIP survey produced in the Nordic countries, which showed markedly increased GGT reference values as compared with the limits used previously (Stromme et al. 2004). Such a change in GGT limits would
obviously lead to decreased sensitivity in the detection of alcoholics, as the present data suggest that
13 % of them would escape detection if moderate drinkers were taken as the reference population
instead of abstainers. At the same time, it can be argued that with lower GGT limits the specificity
of the assay would decrease, leading to false positive values, as approximately 11 % of the moderate drinkers studied here would have been labelled as having elevated values with lower limits. This
aspect may also be viewed, of course, as a possibility for detecting excessive drinking in an earlier
phase, for these reference individuals with slightly elevated GGT may report moderate drinking but
actually represent drinkers who are on the edge of excessive alcohol consumption or have other
confounding factors such as obesity and diabetes, which can both cause elevated GGT values
(Kornhuber et al. 1989, Cushman 1992, Aubin et al. 1998, Daeppen et al. 1998, Puukka et al.
2006a).
The differences between moderate drinkers and abstainers were also investigated in the case of
the GGT-CDT, CDT, MCV, AST and ALT (paper II), and the inclusion of moderate drinkers in the
reference population was found to affect the diagnostic performance of GGT, AST and MCV but
not GGT-CDT. This may be an important consideration when screening for excessive alcohol consumption.
Papers III and IV focused on the immunological responses to alcohol and its metabolites. These
responses were also found to show variation as a result of moderate drinking. Anti-adduct IgA values were found to be significantly elevated in moderate drinkers by comparison with abstainers, and
the other anti-adduct immunoglobulins, IgG and IgM, were also found to show variation between
moderate drinkers and abstainers, the difference in IgM being significant. For cytokines, anti43

inflammatory IL-10 values appeared to be slightly elevated in moderate drinkers. It could be speculated that both the IgM response and IL-10 elevation indicate an early response against the adverse
effects of alcohol.

6.2. Marker combinations (II, IV)
Although various markers for detecting excessive alcohol consumption have emerged during past
decades, clinicians continue to lack a sensitive tool for the identification of excessive drinking, especially in its early phase. Since the passage of a new marker molecule from its discovery to routine
use can take years or even decades, increasing interest has been shown in the idea of combining
existing markers. Various marker combinations have been introduced during the past two decades
(Salaspuro 1987, Anton et al. 2001, Sillanaukee and Olsson 2001, Anttila et al. 2003, Hock et al.
2005). Traditionally, combinations have included CDT, GGT and/or MCV, usually combined in a
manner in which a case is deemed positive when either of the markers is positive. The combining of
GGT and CDT in this way, for instance, has been shown to yield a sensitivity of 90 % for a specificity of 81 % in men and a sensitivity of 75 % for a specificity of 87 % in women (Anton et al.
2001). More recently, Schwan and co-workers (2004) have shown that combining GGT and CDT as
independent parameters provides a sensitivity of 90 % in alcohol abusers and 99 % in alcoholdependent subjects, whereas the specificity remains at a level of only 63 %. A further improvement
in marker combinations has been achieved by using mathematical equations, the most promising
combination of this kind so far being GGT and CDT with an equation of 0.8 x ln(GGT) + 1.3 x
ln(%CDT) (Sillanaukee and Olsson 2001, Anttila et al. 2003). In line with this view, Hock and coworkers (2005) recently reported a sensitivity of 83 % with a specificity of 95 % using a simple
combination of log GGT and CDT. When MCV was included as a third component in these analyses, the sensitivity was reported to increase to 88 %.
The data presented in papers II and IV clearly support the idea of using marker combinations for
detecting hazardous drinking. The mathematically formulated equation based on serum GGT and
CDT results, referred to in paper II as GGT-CDT was first introduced by Sillanaukee and Olsson
(2001), who used absolute CDT values (U/l) in their equation. The replacement of these with
%CDT results has proved to improve the performance of this approach still further (Anttila et al.
2003). The present comparison of the diagnostic characteristics of GGT-CDT with those of various
other biochemical markers used in the diagnosis of excessive drinking (II) showed this combination
to be superior to all the conventional markers. One remarkable thing is that this improvement in
sensitivity was achieved without sacrificing the specificity. The use of MCV or any other parameter
as a third component in the combination was not found to lead to any additional improvement over
GGT-CDT alone. GGT-CDT also appears to be relatively independent of liver status, despite having GGT as one of its components. Earlier observations suggest that using %CDT in the equation
instead of absolute CDT further improves this property (Anttila et al. 2003). On the other hand, the
presence of liver pathology was found to affect the performance of GGT, AST, ALT and MCV in
the assessment of excessive drinking.
Paper IV introduces briefly a marker combination consisting of anti-adduct IgAs and %CDT,
combined by means of a mathematical equation logCDT + (IgA/103). The resulting marker, IgA-

44

CDT, was found to provide improved sensitivity as compared with its parent components or other
alcohol markers, without any loss in assay specificity. The diagnostic performance of IgA-CDT also
seems to be similar to or even better than that of GGT-CDT.
Ideal markers for combinations should have different mechanisms of induction, so that the combination will gain the diagnostic benefits of both components. GGT and CDT, for instance, frequently increase in different individuals and may represent different types of ethanol-induced
pathophysiological processes (Anton et al. 2002, Anttila et al. 2003, Neumann and Spies 2003).
This combination of different diagnostic windows could partly explain the distinct improvement
that can be obtained with marker combinations. Taken together, this work supports the idea of employing marker combinations to achieve a more sensitive diagnosis of excessive drinking. Antiadduct IgA measurements are not currently available for clinical use, but since GGT and CDT already belong to the set of routine assays, GGT-CDT would be cost-effective and easy to manage in
hospital laboratories.

6.3. Antibody and cytokine responses in alcohol abusers (III-IV)
An understanding of the pathophysiological processes related to alcohol is equally as important as
the discovery of a reliable laboratory marker. If the mechanisms of tissue pathology could be clarified, it might provide new tools for effective treatment and enable the use of immune parameters as
biomarkers of alcohol consumption and alcoholic liver disease. Alcohol affects almost every tissue
in the body, and our knowledge of the mechanisms of these actions is limited. The present study of
the antibody and cytokine responses related to alcohol intake (III) and the possibility of using antibodies as markers of alcoholism (IV) was focused on male subjects because the immunological responses in vivo may show significant gender dependence, possibly due to differences in sex hormones (Kovacs and Messingham 2002). Women generally show stronger immune responses, and
thus further studies with female populations are clearly warranted.

6.3.1. Changes in antibody and cytokine production attributable to alcohol and liver
disease (III-IV)
Some of the adverse consequences of alcohol consumption are clearly mediated by immunological
mechanisms. The antibody and cytokine responses studied here seem to be associated with inflammatory processes in tissues, particularly in the liver. The generation of immune responses to acetaldehyde-modified epitopes appears to occur early in the sequence of events leading from excessive
alcohol consumption to clinical signs of alcoholic liver injury. Both anti-adduct IgA and IgM already showed an elevation in alcoholics without liver disease, and IgG antibodies also parallelled
the evolution of liver injury. These findings, together with the observation that cytokine levels also
respond to ethanol intake, suggest that the balance in the immune regulation of tissues may be disturbed by ethanol.
Previous studies focusing on alcoholic liver disease have reported an increase in circulating total
IgA concentrations together with increased deposition of IgA in tissues (Swerdlow et al. 1983, van

45

de Wiel et al. 1987, 1988, Tuma and Klassen 1992, Amore et al. 1994). It has been suggested that
this may result from either decreased IgA catabolism or excretion or increased IgA production (van
de Wiel et al. 1987, Koskinas et al. 1992, Tuma and Klassen 1992, Viitala et al. 1997). The present
findings support the theory that the increase in total IgA is due to antigen-driven antibody production, because the levels of specific antibodies become elevated before any generalized increase in
serum total IgA levels.
The specific IgAs against ethanol metabolites may be derived from intestinal B-cells, because
IgA is the predominant antibody in the gastrointestinal tract, and gastric immunity may readily respond to environmental and dietary antigens (Kerr 1990, Amore et al. 1994). The epithelial tissues,
which are rich in enzymes capable of metabolizing ethanol to acetaldehyde, are continuously exposed to ethanol in excessive drinkers, thus enabling the formation of acetaldehyde adducts and
antibodies against them (Seitz et al. 1994, Salaspuro 1996, Salmela et al. 1997, Visapää et al. 1998).
This is also supported by the present observations that there is a close correlation between antiadduct IgA levels and recent ethanol intake, and also by the presence of anti-adduct IgAs in individuals reporting moderate drinking. Excessive ethanol intake has previously been found to increase
intestinal permeability and disrupt mucosal barriers (Bode and Bode 2003). This could further enhance the antibody responses to various gut-derived antigens and also increase the absorption of
IgA. Alcoholics with liver disease often have high endotoxin levels and they have been reported to
produce IgA antibodies to endotoxin (Nolan et al. 1986, Parlesak et al. 2002, Wheeler 2003) and
also to human gut luminal aspirates (Douds et al. 1998). Anti-endotoxin antibodies as well as antiadduct antibodies may contribute to the formation of alcoholic liver disease (Klassen et al. 1995,
Parlesak et al. 2002, Leevy and Elbeshbeshy 2005).
The involvement of cytokine signalling in the progression of alcoholic liver disease has become
more and more evident in the past decades, and the present studies also show a distinctly different
cytokine profiles for alcoholics and for healthy controls. It is not known, however, whether the immune responses in excessive drinkers represent protective or harmful mechanisms for the liver. The
positive correlation found between anti-adduct IgAs and the pro-inflammatory cytokines TNF-α and
IL-6 may be an indication of early-phase inflammatory response to ethanol-derived antigens, as IL6 has been reported to participate in the acute phase hepatic response (Khoruts et al. 1991) and also
in the control of immunoglobulin production (Deviere et al. 1992). The increased amount of antiadduct IgM and IL-10 in moderate drinkers and in alcoholics without liver disease may represent an
early-phase immune response and the regulation of protective immune mechanisms. IgA antibodies
may also contribute to immune protection by excluding and neutralizing the altered protein structures resulting from acetaldehyde modification (Israel et al. 1988). When excessive drinking continues, the anti-adduct IgA increases and the pro-inflammatory cytokines become even more elevated,
while anti-inflammatory cytokines show a decline. When antigenic stimulation is excessive, IgA
immune complexes may be damaging, since these can cause monocytes to release mediators of tissue damage (Deviere et al. 1991). IgG antibodies are known as mediators of several immunopathogenic consequences, including complement activation and the induction of cytotoxic reactions.
These immune responses are likely to play an important role in the progression of liver pathology.
Alcoholics with liver disease clearly have a skewed balance in cytokine levels, with distinct elevations in IL-2, IL-6, IL-8 and TNF-α, while TGF-β1 levels are actually decreased, although TGF-β1
has previously been associated with the progression of fibrosis in alcoholics (Chen et al. 2002). An
excessive release of pro-inflammatory cytokines can induce the activation of inflammatory cells,

46

increase the production of reactive oxygen species from hepatocytes and induce apoptosis (Neuman
2003). According to several studies, increased TNF-α production and Kupffer cell activation may
play key roles in hepatic inflammation (Iimuro et al. 1997, Yin et al. 1999).

6.3.2. Anti-adduct IgAs as a marker of alcohol consumption
It is shown in paper IV that the specific IgA response to acetaldehyde adducts may serve as a clinically useful tool for diagnosing excessive ethanol consumption. A high sensitivity and specificity
was observed for the adduct-specific IgA measurements in differentiating between alcoholics and
non-alcoholics, and a close correlation between alcohol intake and anti-adduct IgA levels was also
found. The diagnostic usefulness of IgA antibodies has previously been studied with a different test
antigen (acetaldehyde-modified bovine serum albumin) and these investigations also gave a significant correlation (r = 0.44) between anti-adduct IgAs and alcohol intake (Worrall et al. 1996, 1998).
Although the anti-acetaldehyde antibody responses are generated independently of the carrier protein, there may be differences in the characteristics of the test antigen and in the efficiency of the
assay in differentiating alcoholics from the control population. The red cell protein (mainly consisting of haemoglobin) appears to suit well for anti-adduct antibody measurements, which may be due
to an efficient modification of the carrier protein, perhaps leading to an adduct resembling the naturally occurring ones.
It should be noted that moderate drinkers show elevated IgA values as compared with abstainers. This has to be taken into consideration when defining normal values for such measurements.
The diagnostic sensitivity of anti-adduct IgAs exceeds that of the conventional markers if abstainers
are used as the reference individuals, but the inclusion of moderate drinkers elevates the reference
limit and causes a slight decrease in assay sensitivity. Nevertheless, measurements of specific IgAs
against acetaldehyde-modified epitopes in proteins could be used as a sensitive tool for detecting
excessive drinking.

6.4. Follow-up studies
Of the markers studied here, GGT-CDT was found to be most suitable for the follow-up of alcoholics during treatment, since it was observed to decrease in 93 % of the subjects and the mean normalization rate was estimated to be 2–3 weeks. The time required for the normalization of GGTCDT was slightly longer than for either of its components separately, suggesting that this mathematical combination follows a slightly different kinetics in its normalization. In line with previous
studies, CDT performed well in the follow-up, while the normalization of GGT, AST and ALT was
not as consistent as that of either GGT-CDT or CDT alone (Bell et al. 1993, Salaspuro 1999, Anttila
et al. 2004). This is perhaps due to the induction of liver pathology, which may be reflected in
marker levels even after the cessation of drinking.
Anti-adduct IgA antibodies and IL-6 levels were found to decrease significantly in the follow-up
of abstaining alcoholics, and they still remained elevated by comparison with those in healthy controls. Significant changes during abstinence were also observed for IL-10 and TNF-α. The follow-

47

up studies showed that anti-adduct IgA levels normalize at an average rate of 3 % per day, the mean
time required for normalization being 29 days. Since the average half-life of a single IgA molecule
is 5–6 days, the longer appearance of anti-adduct IgAs in serum may be explained by the fact that
acetaldehyde adducts in the erythrocytes of alcoholics persist in the circulation for 1 to 3 weeks
after the last dose of ethanol (Niemelä and Israel 1992). This consistent decrease in anti-adduct
IgAs during abstinence suggests, however, that this marker could also be used for follow-up purposes.

6.5. Possible limitations of this study
It should be noted that this study contrasted apparently healthy controls with alcoholics, while in
clinical practice the hospital population may comprise patients with various medical conditions and
drinking habits, which may complicate the assessment of alcohol consumption by means of laboratory markers. Data on possible refusers among alcoholics were not collected, but it can be assumed
that the significance of this factor is relatively small in large populations. The control individuals
used here also entail some limitations. The permitted alcohol intake for women was similar to that
for men, which may have led to the inclusion of some female individuals who were in fact on the
edge of excessive consumption rather than true moderate drinkers. Also, as the alcohol consumption
data are based on individuals' own reports, the possibility of having some excessive drinkers among
the male control population as well cannot be excluded.
Most of the methods used in these studies are already in routine use and thus quite well characterized in terms of variation and accuracy as well as clinical usefulness. The anti-adduct IgA assay
has so far been used for research purposes only and corresponding figures for its precision have not
yet been established. We cannot exclude some additional variation in results due to this unstandardized assay method, and this work should therefore be continued by standardization of the assay.

6.6. Future considerations
The markers and combinations presented here appear to provide some improvements in the diagnosis of excessive alcohol consumption. Since the prevalence of excessive drinking continues to increase and frequently still remains undetected in health care, there is an obvious need for new objective tools. The markers that are already in routine use could also be used in combinations for
clinical purposes. In the case of new markers, assay methods need to be standardized both within
and between laboratories, and further studies are needed in clinical settings in order to establish
their diagnostic value.

48

7. Conclusions
These findings indicate that the assessment of alcohol consumption in clinical practice could be
improved by using laboratory markers and their combinations in a carefully standardized manner.
Moderate drinking at the population level may induce changes in some of the commonly used
biomarkers of alcohol consumption, such as GGT. This should be taken into consideration in the
clinical use of such markers and when selecting individuals for reference populations. Any ethanolrelated deviation in GGT reference intervals will obviously reduce the sensitivity of this marker in
detecting excessive drinking.
The diagnosis of excessive drinking can be improved by using combinations of markers. The
present data suggest that the diagnostic characteristics of the combined marker GGT-CDT appear to
exceed those of the traditional markers and both of its components separately.
Immune responses to alcohol-induced antigens, together with disturbances in cytokine balance,
may contribute to the development of tissue injury in alcoholics. Changes in ethanol-induced immune responses may already occur in alcoholics without liver disease, however, and even in moderate drinkers. Anti-acetaldehyde adduct IgAs may be suitable for assessing alcohol consumption,
particularly when combined with CDT.

49

Acknowledgements
This research was carried out at the Department of Clinical Chemistry and Medical Research Unit,
Seinäjoki Central Hospital, during the years 2004–2007.
I would like to express my sincere gratitude to my supervisor, Professor Onni Niemelä, M.D.,
Ph.D., for the opportunity to work in his research group and for his encouragement during these
years. This thesis would not have come into existence without his wide knowledge of alcohol research and his guidance throughout the work.
Professor Kaija Seppä and Docent Kari Pulkki, the reviewers appointed by the Medical Faculty,
are gratefully acknowledged for their valuable comments and constructive criticism on the thesis. It
was a great honour for me to hear that Docent Arja Rautio had agreed to be the official opponent for
the discussion of the thesis. I also wish to thank Mr. Malcolm Hicks for his revision of the English
language of the manuscript.
I thank Dr. Matti Rekiaro and Docent Hannu Puolijoki for their interest in my thesis and in our
research group, and Jaakko Pihlajamäki, Head of the Hospital District, for his positive attitude towards the research at our department.
I would like to express my sincere thanks to my closest co-workers, Heidi Koivisto and Taana
Sandman, who, in addition to professional collaboration, have supported me with their friendship
during these years. I also wish to express my warmest thanks to my other co-workers and coauthors, Katri Puukka, Jaana Latvala, Petra Anttila, Katja Viitala and Kimmo Järvi, and to all the
members of the staff of Seinäjoki Central Hospital laboratory. Especially I would like to thank my
colleagues Aira Sorto, Kristina Eichholz and Markku Latva-Nevala for their support to a young
specializing hospital chemist.
I owe my deepest gratitude to my parents, who have always believed in me and supported me in
every way throughout my life. I am sincerely thankful to my beloved fiancé, Pekka, for his love and
understanding and for reminding me that there is life outside the academic world. I would also like
to thank all my friends and relatives for their support and for the interest they have shown in my
thesis and in alcohol research in general.
Parts of this research were supported financially by the Finnish Foundation for Alcohol Studies
and the Foundation for the Promotion of Laboratory Medicine.
Seinäjoki, January 2007

Johanna Hietala

50

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Alcohol and Alcoholism Advance Access published August 30, 2005
Alcohol & Alcoholism Page 1 of 4
doi:10.1093/alcalc/agh201, available online at www.alcalc.oxfordjournals.org

SERUM GAMMA-GLUTAMYL TRANSFERASE IN ALCOHOLICS, MODERATE DRINKERS
AND ABSTAINERS: EFFECT ON GT REFERENCE INTERVALS AT POPULATION LEVEL
JOHANNA HIETALA, KATRI PUUKKA, HEIDI KOIVISTO, PETRA ANTTILA
and ONNI NIEMELÄ*
Department of Laboratory Medicine and Medical Research Unit, Seinäjoki Central Hospital, and University of Tampere,
FIN-60220 Seinäjoki, Finland
(Received 2 June 2005; first review notified 15 July 2005; accepted in final revised form 8 August 2005)
Abstract — Aims: To clarify in the association between amount of ethanol consumption and serum gamma-glutamyl transferase (GT)
levels. Methods: GT values were measured from 195 individuals with a wide variety of well-documented ethanol consumption assessed
by detailed personal interviews using a time-line follow-back technique. These included 103 heavy drinkers (90 men, 13 women) and 92
healthy volunteers (54 men, 38 women) who were either abstainers (n = 30) or moderate drinkers (n = 62). For comparisons, data were
collected from GT measurements for establishing GT reference intervals from 2485 healthy volunteers including 1156 abstainers and
1329 moderate drinkers. Results: GT values in the individuals whose mean ethanol consumption exceeded 40 g of ethanol per day
were significantly higher than those in the moderate drinkers with a mean consumption of 1–40 g/day (P < 0.001) or in abstainers
(P < 0.001). The GT values in the group of moderate drinkers also exceeded those of the abstainers (P < 0.001). The upper normal
GT limits obtained from the data from abstainers were markedly lower (men 45 U/l, women 35 U/l) than those obtained from the population of moderate drinkers (men 66 U/l, women 40 U/l). Conclusions: Serum GT concentrations may respond to relatively low levels of
ethanol consumption, which should be considered when defining GT reference intervals. The continuous increase in alcohol consumption at population level may lead to increased GT cut-off limits and hamper the detection of alcohol problems and liver affection in their
early phase.

INTRODUCTION

or abstainers: 54 men, mean age 41 ± 16 years; 38 women,
mean age 44 ± 19 years) who underwent detailed personal
interviews using a time-line follow-back technique (interview
sample). The heavy drinkers had a history of continuous ethanol consumption or binge drinking, the mean consumption
being in the range of 40–539 g/day during the period of
4 weeks prior to sampling. In addition, this interview sample
included 30 abstainers and 62 moderate drinkers with a
mean daily ethanol consumption between 1 and 40 g/day.
Measurements of GT levels were carried out using standard
clinical chemical methods in an accreditated (SFS-EN
45001, ISO/IEC Guide 25) laboratory of Seinäjoki Central
Hospital, Finland. For comparisons, data from a survey on
2485 apparently healthy individuals (1174 men, age 47 ±
18 years; 1311 women, age 47 ± 18 years) collected for establishing reference intervals in Nordic countries were also
used as kindly provided by the project coordinator, Professor
Pål Rustad, Fürst Medical Laboratory, Oslo, Norway. These
subjects were classified as either abstainers (n = 1156:
471 men, age 49 ± 19 years; 685 women, age 49 ± 19 years)
or moderate drinkers (n = 1329: 703 men, age 46 ± 17 years;
626 women, age 45 ± 16 years). In these subjects, the maximum amount of alcohol consumption during the 24 h period
prior to sampling had been 24 g (two standard drinks). The
survey excluded individuals who had clinical or laboratory
evidence of current or recent illnesses or infections, who
were pregnant, had donated blood during the past 5 months,
or had used any prescription drugs during the preceding
1 week. Smoking was not allowed for 1 h prior to sampling.
All GT measurements were carried out with homogeneous
International Federation of Clinical Chemistry (IFCC)
compatible measuring systems.

Gamma-glutamyl transferase (GT) is a commonly used laboratory parameter for detecting excessive alcohol consumption
(Zein and Discombe, 1970; Reyes and Miller, 1980). Although
several studies have reported a positive correlation between
the amount of alcohol consumed and serum GT levels, the
reported sensitivities of this marker in previous literature
have varied greatly, from 15 to 85% (Bagrel et al., 1979;
Chick et al., 1981; Papoz et al., 1981; Persson et al., 1990;
Leino et al., 1995; Anttila et al., 2004).
Over the past decades, both the total ethanol consumption
per capita and associated medical disorders have continued
to increase. Simultaneously, the percentage of individuals
fully abstaining from ethanol has decreased. In previous studies and in routine health care, reference intervals for GT determinations have been based on values obtained from mixed
populations of apparently healthy moderate drinkers and
abstainers, whereas only limited attention has been paid on the
exact amounts of ethanol consumption in these individuals.
In this work we explored the relationship between ethanol
consumption and GT values in individuals with a wide variety
of ethanol consumption. Our data indicate distinct effects of
mild to moderate ethanol consumption on serum GT levels,
which should be considered in the clinical use of GT measurements as a marker of ethanol abuse and liver status.
METHODS
Study protocol
Serum GT was first measured from a sample of 195 individuals (103 heavy drinkers: 90 men, mean age 42 ± 10 years;
13 women, mean age 40 ± 7 years, and 92 moderate drinkers

Ethical considerations
The procedure was approved by the institutional review board.
Informed consent was obtained from the participants and the

*Author to whom correspondence should be addressed at: Tel.: +358 6 415
4719; Fax: +358 6 415 4924; E-mail: onni.niemela@epshp.fi
1

Ó The Author 2005. Published by Oxford University Press on behalf of the Medical Council on Alcohol. All rights reserved

2

J. HIETALA et al.

study was carried out according to the provisions of the
Declaration of Helsinki.
Statistical methods
Values are expressed as mean ± SD. Comparisons were made
with Kruskal-Wallis test and Dunn’s Multiple Comparison
Test or Mann–Whitney test when comparing two groups.
Correlations were calculated with Pearson product–moment
correlation coefficients. Reference intervals were calculated
after logarithmic transformation as previously described
(Horn and Pesce, 2003). A P-value <0.05 was considered
statistically significant.
RESULTS
In the total population, serum GT concentrations (mean ± SD)
in the groups of heavy drinkers drinking 40–80 g (68 ± 54 U/l)
or >80 g (167 ± 254 U/l) of ethanol per day significantly
exceeded the levels of both abstainers (P < 0.001) and moderate drinkers (P < 0.001) (Fig. 1). Male alcoholics had slightly
higher GT values (166 ± 267 U/l) than female alcoholics
(130 ± 163 U/l), although the difference between genders did
not reach significance. Interestingly, GT values in the group of
moderate drinkers with a daily consumption of 1–40 g
(28 ± 23 U/l) also exceeded the values obtained from the
P<0.001
P<0.001
P<0.001

250

DISCUSSION

P<0.001
P<0.001
200

GT U/l

group of abstainers (24 ± 17 U/l) (P < 0.001). The correlation
between ethanol consumption and GT values, as calculated
from the individuals interviewed with the time-line followback method, was significant (r = 0.35, P < 0.001).
Figure 2 demonstrates the previously established changes in
national GT reference intervals in Finland in comparison with
the yearly changes in ethanol consumption at population level.
The data on GT reference intervals, as calculated from the
individuals classified according to ethanol consumption data
in the detailed personal interviews, are summarized in
Table 1. The upper normal limits were found to be on average
43% higher, when the individuals with moderate drinking are
contrasted with the population of abstainers. The upper normal
limits for men were higher than those for women and the age
group >40 years had higher levels than the age group 18–
39 years in both genders. However, the correlation between
GT levels and age per se did not reach significance (r = 0.097).
The effect of the choice of the reference population on the
estimated diagnostic sensitivity of GT as a marker of excessive ethanol consumption is demonstrated in Fig. 3. When
the heavy drinkers are contrasted with abstainers, 69% of
heavy drinkers become correctly classified. If the reference
interval and definition of normal values would be based on
moderate drinkers, the sensitivity remains at a level of 56%.
In separate analyses of men and women, the corresponding
percentages were 68 and 54% for men and 77 and 69% for
women, showing essentially similar changes.

150

100

50

0

>80 g
EtOH/day

40–80 g
EtOH/day

1–40 g
EtOH/day

0g
EtOH/day

Fig. 1. GT values in individuals with different levels of ethanol consumption.
The values in the groups with ethanol consumption over 80 g (167 ± 254 U/l)
or 40–80 g (68 ± 54 U/l) are significantly higher than those in the abstainers
(24 ± 17 U/l) or moderate drinkers consuming a mean of 1–40 g/day
(28 ± 23 U/l). The difference between the group of moderate drinkers and
abstainers was also significant (P < 0.001).

Alcohol abuse and alcoholism rank as one of the most serious
health problems in most Western countries (Room et al.,
2005). Therefore, a high priority should be given to reduction
in the prevalence of alcoholism through more effective diagnosis and early intervention. Objective methods for detecting
excessive ethanol consumption in health care are necessary
for a majority of heavy drinkers who have not self-identified
as having alcohol problems.
Studies in the past have shown that a number of biochemical
parameters are altered in alcoholics, of which serum GT has
emerged as one of the most efficient tests (Bagrel et al.,
1979; Chick et al., 1981; Papoz et al., 1981; Bernadt et al.,
1982; Leino et al., 1995; Anttila et al., 2004). The present
study indicates that even moderate amounts of ethanol consumption influence serum GT concentrations at population
level and this phenomenon may significantly affect the interpretation and the establishment of common reference intervals
for GT measurements in health care. The data support the view
that in order to improve the diagnostic potential of laboratory
markers of excessive ethanol consumption and liver status, the
reference intervals of each test should be based on healthy

Table 1. GT reference intervals based on the data from the groups of individuals classified according to ethanol intake in the interview sample

Moderate drinkers
Alcohol consumption (1–40 g/day)
Moderate drinkers and abstainers
Alcohol consumption (0–40 g/day)
Abstainers
Alcohol consumption (0 g/day)

All men

Men 18–39

Men >40

All women

Women 18–39

Women >40

8–66

7–63

11–66

6–40

6–31

6–64

9–61

8–57

12–62

7–39

7–30

8–44

10–45

9–37

11–52

8–35

7–30

9–37

GT AND ALCOHOL CONSUMPTION

Liters of 100 % ethanol per capita / year

A

3

Yearly ethanol consumption (Finland)
9
8.1
8
7.4
7

6.7

6.5

6.7

6.9

7.0

1997

1998

7.1

7.6

7.7

2002

2003

7.0

6.2
6

5
1975

1985

B

1995 1996

1999 2000

2001

2004

Recommendations for national reference intervals for
GT measurements (Finland)
120

GT U/l

100

80

60

40

20

Men

Women

Men

–1991

Women

1992–1998

Men

Men

Women

18–39 yrs

1999–

Women

≥ 40 yrs

Percentages of alcoholics correctly
classified

Fig. 2. (A) Mean ethanol consumption in Finland over the years 1975–2004. (B) The changes in recommended reference intervals for GT measurements based on
surveys on apparently healthy individuals.
80
69
70
60

56

50
40
30
20
10
0
alcohol consumption 1–40 g/day

alcohol consumption 0 g/day

Source of reference interval

Fig. 3. Effect of the source of reference intervals on the sensitivity of detecting problem drinking with GT measurements. When reference intervals are
based on values from abstainers, 69% of the heavy drinkers are detected.
When the reference population consists of moderate drinkers, only 56% of
the heavy drinkers become correctly identified.

individuals who abstain from ethanol. Since a gold standard
for a bona fide social drinker currently does not exist, the concepts of moderate drinking and social drinking should also be
defined more accurately and the proportions of abstainers and

moderate drinkers considered separately when selecting reference individuals in future studies.
The present data indicate that the estimated upper normal
limits for GT measurements would be 40% higher if the
data based on moderate drinkers would be used as the basis
of the reference population instead of abstainers. In accordance with this view, a recent NORIP survey from the Nordic
countries showed markedly increased GT reference values
(Stromme et al., 2004). The diagnostic sensitivity of GT measurements as a marker of excessive ethanol consumption
would obviously improve if reference intervals would be
based on the data from abstainers. This work indicates that
13% of alcoholics would escape detection if moderate drinkers
are used as the reference population, instead of abstainers.
Thus, there may be a need for revising the reference range
downwards. It may, however, be argued that setting a lower
limit could worsen the specificity of GT assays and lead to a
high number of false positive values. According to this work,
11% of the moderate drinkers would have shown increased
values. However, there may be individuals who are in the
upper range of the limits of social drinking. Since the data
are based on self-reports, we cannot rule out occult alcohol
abuse in these subjects. It should be noted, however, that
future studies are clearly warranted to explore the independent
effect of various possible sources of unspecificity on GT

4

J. HIETALA et al.

values, such as obesity or diabetes in individuals reporting
either moderate drinking or no drinking. Our preliminary
analyses on moderate drinkers with different degrees of
obesity have indicated potentiation of GT activities in individuals with significant obesity (data not shown). The associations between GT, moderate drinking, and obesity have
previously been examined by Kornhuber et al. (1989) who
also concluded that the definition of GT normal values may
need to be readdressed. The correlation (r = 0.35) between
alcohol consumption per se and GT values in this study is consistent with previous observations (Bagrel et al., 1979; Chick
et al., 1981; Papoz et al., 1981; Leino et al., 1995; Anttila
et al., 2004). The correlation was, however, essentially similar
in women (r = 0.36) and men (r = 0.32), though some earlier
studies have reported higher correlations in populations consisting of men only (Papoz et al., 1981; Anton and Moak,
1994; Sillanaukee et al., 1998). The diagnostic sensitivity of
GT has usually been shown to be lower for women than for
men (Anton and Moak, 1994; Yersin et al., 1995; Mundle
et al., 2000). Based on the present data, these findings may
in part be explained by the definition of reference intervals.
Furthermore, GT values in women may increase at lower
levels of alcohol consumption as a result of women’s
increased vulnerability to the toxic effects of alcohol (Anton
et al., 1998).
The advent of carbohydrate-deficient transferrin (CDT)
testing has recently imposed a new challenge to the use of
GT measurements because CDT has shown higher specificities than GT in several trials. Although CDT has become
an increasingly important tool for assessing excessive ethanol
consumption, it appears that CDT and GT frequently increase
in different individuals (Anton et al., 2002; Anttila et al.,
2003; Neumann and Spies, 2003). Some studies have concluded that GT is more efficient in identifying female alcoholics than CDT (Anton and Moak, 1994, Anton et al.,
2002). Therefore, it seems at this time that CDT alone does
not cover all the needs for an alcohol marker in routine clinical
practice, and other markers, especially GT are needed as well.
Taken together, the present data indicate that the changes in
drinking behaviour at population level may parallel increases
in recommended GT cut-offs, which may subsequently lead
to problems in recognizing excessive alcohol consumption in
its early phase. Therefore, a critical re-evaluation of reference
intervals even in the use of the well-established biochemical
markers of alcohol consumption may be necessary in order
to improve the assessment and treatment of patients with
early-stage alcohol problems.
Acknowledgements — The help of professor Pål Rustad, Fürst Medical Laboratory, Oslo, Norway, for providing data on GT measurements in the Nordic
NORIP Survey for establishing reference intervals is gratefully acknowledged.
The studies were supported in part by a grant from the Finnish Foundation for
Alcohol Studies.

REFERENCES
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consumption: gender differences. Alcoholism: Clinical and
Experimental Research 18, 747–754.
Anton, R. F., Stout, R. L., Roberts, J. S. et al. (1998) The
effect of drinking intensity and frequency on serum

carbohydrate-deficient transferrin and gamma-glutamyl transferase levels in outpatient alcoholics. Alcoholism: Clinical and
Experimental Research 22, 1456–1462.
Anton, R. F., Lieber, C. and Tabakoff, B. (2002) Carbohydratedeficient transferrin and gamma-glutamyltransferase for the
detection and monitoring of alcohol use: results from a multisite
study. Alcoholism: Clinical and Experimental Research 26,
1215–1222.
Anttila, P., Järvi, K., Latvala, J. et al. (2003) A new modified
gamma-%CDT method improves the detection of problem
drinking: studies in alcoholics with or without liver disease.
Clinica Chimica Acta 338, 45–51.
Anttila, P., Järvi, K., Latvala, J. et al. (2004) Method-dependent characteristics of carbohydrate-deficient transferrin measurements in
the follow-up of alcoholics. Alcohol and Alcoholism 39, 59–63.
Bagrel, A., d’Houtaud, A., Gueguen, R. et al. (1979) Relations
between reported alcohol consumption and certain biological
variables in an ‘‘unselected’’ population. Clinical Chemistry 25,
1242–1246.
Bernadt, M. W., Mumford, J., Taylor, C. et al. (1982) Comparison of
questionnaire and laboratory tests in the detection of excessive
drinking and alcoholism. The Lancet 1, 325–328.
Chick, J., Kreitman, N. and Plant, M. (1981) Mean cell volume and
gamma-glutamyl-transpeptidase as markers of drinking in
working men. The Lancet 1, 1249–1251.
Horn, P. S. and Pesce, A. J. (2003) Reference intervals: an update.
Clinica Chimica Acta 334, 5–23.
Kornhuber, J., Kornhuber, H. H., Backhaus, B. et al. (1989) The
normal values of gamma-glutamyltransferase are falsely defined
up to now: on the diagnosis of hypertension, obesity and diabetes
with reference to ‘‘normal’’ consumption of alcohol.
Versicherungsmedizin 41, 78–81.
Leino, A., Impivaara, O., Irjala, K. et al. (1995) Health-based reference intervals for ALAT, ASAT and GT in serum, measured
according to the recommendations of the European Committee
for Clinical Laboratory Standards (ECCLS). The Scandinavian
Journal of Clinical and Laboratory Investigation 55, 243–250.
Mundle, G., Munkes, J., Ackermann, K. et al. (2000) Sex
differences of carbohydrate-deficient transferrin, gammaglutamyltransferase, and mean corpuscular volume in alcoholdependent patients. Alcoholism: Clinical and Experimental
Research 24, 1400–1405.
Neumann, T. and Spies, C. (2003) Use of biomarkers for alcohol use
disorders in clinical practice. Addiction 98 (Suppl. 2), 81–91.
Papoz, L., Warnet, J. M., Pequignot, G. et al. (1981) Alcohol
consumption in a healthy population. Relationship to gammaglutamyl transferase activity and mean corpuscular volume. The
Journal of the American Medical Association 245, 1748–1751.
Persson, J., Magnusson, P. H. and Borg, S. (1990) Serum gammaglutamyl transferase (GGT) in a group of organized teetotallers.
Alcohol 7, 87–89.
Reyes, E. and Miller, W. R. (1980) Serum gamma-glutamyl transpeptidase as a diagnostic aid in problem drinkers. Addictive Behaviors
5, 59–65.
Room, R., Babor, T. and Rehm, J. (2005) Alcohol and public health.
The Lancet 365, 519–530.
Sillanaukee, P., Aalto, M. and Seppä, K. (1998) Carbohydratedeficient transferrin and conventional alcohol markers as indicators for brief intervention among heavy drinkers in primary health
care. Alcoholism: Clinical and Experimental Research 22,
892–896.
Stromme, J. H., Rustad, P., Steensland, H. et al. (2004) Reference
intervals for eight enzymes in blood of adult females and males
measured in accordance with the International Federation of
Clinical Chemistry reference system at 37 C: part of the Nordic
Reference Interval Project. The Scandinavian Journal of Clinical
and Laboratory Investigation 64, 371–384.
Yersin, B., Nicolet, J. F., Dercrey, H. et al. (1995) Screening for
excessive alcohol drinking. Comparative value of carbohydratedeficient transferrin, gamma-glutamyltransferase, and mean
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Alcohol & Alcoholism Vol. 41, No. 5, pp. 528–533, 2006
Advance Access publication 23 June 2006

doi:10.1093/alcalc/agl050

COMPARISON OF THE COMBINED MARKER GGT–CDT AND THE CONVENTIONAL
LABORATORY MARKERS OF ALCOHOL ABUSE IN HEAVY DRINKERS, MODERATE
DRINKERS AND ABSTAINERS
JOHANNA HIETALA, HEIDI KOIVISTO, PETRA ANTTILA and ONNI NIEMELÄ*
Department of Laboratory Medicine and Medical Research Unit, Seinäjoki Central Hospital and University of Tampere,
FIN-60220 Seinäjoki, Finland
(Received 6 January 2006; first review notified 19 April 2006; in revised form 5 May 2006; accepted 19 May 2006;
advance access publication 23 June 2006)
Abstract — Aims: A combined index based on g-glutamyltransferase (GGT) and carbohydrate-deficient transferrin (CDT) measurements (GGT–CDT) has been recently suggested to improve the detection of excessive ethanol consumption. The aim of this work
was to compare GGT–CDT with the conventional markers of alcohol abuse in individuals with a wide variety of alcohol consumption.
Methods: A cross-sectional and follow-up analysis was conducted in a sample of 165 heavy drinkers, consuming 40–540 g of ethanol
per day, and 86 reference individuals who were either moderate drinkers (n = 51) or abstainers (n = 35). Results: GGT–CDT
(5.35 ± 1.08) in the heavy drinkers was significantly higher than in the reference individuals (3.30 ± 0.37). The sensitivity of GGT–
CDT (90%) in correctly classifying heavy drinkers exceeded that of CDT (63%), GGT (58%), mean corpuscular volume (MCV)
(45%), aspartate aminotransferase (AST) (47%), and alanine aminotransferase (ALT) (50%), being also essentially similar for
alcoholics with (93%) or without (88%) liver disease. When comparing the data using either moderate drinkers or abstainers as
reference population, the sensitivity of GGT–CDT, CDT, and ALT remained unchanged whereas the sensitivity of GGT, MCV, and
AST was found to show variation. Conclusions: GGT–CDT improves the sensitivity of detecting excessive ethanol consumption as
compared with the traditional markers of ethanol consumption. These findings should be considered in the assessment of patients
with alcohol use disorders.

INTRODUCTION

the CDTect assay. However, as yet, only limited information
has been available on the clinical performance of the new
GGT–CDT method and its comparisons with other markers
of ethanol intake.
This study was aimed at comparing the diagnostic value of
GGT–CDT with several other biomarkers of alcohol abuse in
a well-characterized population of heavy drinkers, moderate
drinkers, and abstainers.

Although the prevalence of alcoholism and associated medical
disorders are continuously growing in most Western countries,
patients with hazardous drinking practices continue to escape
detection in clinical work (Lieber, 1995; Conigrave et al.,
2002; Niemelä, 2002; Room et al., 2005). Therefore, the
need for objective laboratory tests, which respond to excessive
ethanol intake in a sensitive and specific manner, has been
widely recognized. In spite of the fact that a wide variety of
biochemical parameters in circulation are altered in alcoholics, none of them has so far provided enough diagnostic accuracy to meet the demands of clinicians in routine use for
differentiating between alcoholics and non-alcoholics (Allen
et al., 1994; Salaspuro, 1999; Scouller et al., 2000; Arndt,
2001; Conigrave et al., 2002; Niemelä, 2002).
Recent studies have suggested the possibility of using marker combinations, which could improve assay sensitivities
without sacrificing specificity (Sillanaukee and Olsson,
2001; Anttila et al., 2003a). A mathematically formulated
equation derived from the data of g-glutamyltransferase
(GGT) and carbohydrate-deficient transferrin (CDT) measurements appears to be elevated in a higher percentage of
alcoholics than either GGT or CDT alone. This approach,
when the latter component of the equation is replaced by the
results from %CDT assay, which expresses CDT data as
percentage of total transferrin, was recently found to further
improve this method as compared with the previous
CDTect-based equation (Anttila et al., 2003a). The main
advantage achieved by the %CDT method in this context
is its ability to avoid the interference of unexpected variation
in serum transferrin levels, which complicated the use of

METHODS
Patients
The sample of alcohol abusers consisted of 165 heavy drinkers
(140 men, 25 women), age (mean ± SD) 46 ± 10 years (range
19–73 years). All patients showed a well-documented history
of excessive ethanol consumption, as assessed by detailed personal interviews using a time-line follow-back technique and
medical and social records. They had consumed ethanol in
amounts ranging from 40 to 540 g/day during the past 1 month
either continuously or during repeated episodes of binge
drinking. The patients also met the DSM-IV criteria of alcohol
dependence including pathological alcohol use, social impairment, presence of tolerance, and withdrawal symptoms. There
were 51 patients, (38 men, 13 women) age 49 ± 10 years,
range 30–67 years, who also showed evidence of liver disease,
as assessed by previously established combined morphological index (CMI) or a combined clinical and laboratory index
(CCLI) (Orrego et al., 1983; Blake and Orrego, 1991).
The mean duration of abstinence prior to sampling was
2 ± 2 days, range 0–6 days. All patients were negative for hepatitis B antigen or hepatitis C serology. Follow-up studies with
supervised abstinence for assessing marker normalization
rates were carried out in 44 alcoholics, age 42 ± 11 years
(range 19–59 years), who were monitored for a period of
11 ± 4 days, range 3–19 days.

*Author to whom correspondence should be addressed. Tel: +358 6 415 4719;
Fax: +358 6 415 4924; E-mail: onni.niemela@epshp.fi
528

 The Author 2006. Published by Oxford University Press on behalf of the Medical Council on Alcohol. All rights reserved

BIOMARKERS OF ALCOHOL CONSUMPTION

Reference individuals were 86 healthy volunteers (49 men,
37 women), age 48 ± 17 years (range 19–84 years) who were
either abstainers (n = 35, age 54 ± 18 years, range 22–
84 years) or moderate drinkers (n = 51, age 43 ± 14 years,
range 19–77 years) whose mean ethanol consumption per
day, as also assessed from the past one month by questionnaires, was between 1 and 40 g. All of them were without
any previous social or medical history of alcohol abuse. The
weekly ethanol consumption in these individuals did not
exceed 280 g of alcohol (men) and 160 g (women) or 6 drinks
(men) and 4 drinks (women) on any single occasion.
All serum samples were stored at –70 C until analysis. All
participants gave their informed consent and the study was
carried out according to the provisions of the Declaration of
Helsinki. The study was approved by the hospital ethical
committee.

529

Microsoft Excel software, which yielded a cut-off of 4.18 for
men and 3.81 for women.
Statistical methods
The values are expressed as means ± SD. The comparisons
between groups were carried out using the Kruskal–Wallis
test with the Dunn’s test for multiple comparisons. Correlations were calculated using the Pearson product-moment correlation coefficients for continuous non-skewed parameters
or the Spearman’s rank correlations for non-continuous
variables, as required. Statistical analyses were carried out
using GraphPad Prism, version 3.03 (GraphPad Software,
San Diego, CA) and Analyse-It for Microsoft Excel software
(version 1.68), Leeds, UK. A P-value < 0.05 was considered
statistically significant.
RESULTS

Laboratory methods
The concentration of CDT was measured by a turbidimetric
immunoassay (TIA) after ion exchange chromatography
(%CDT, Axis-Shield, Oslo, Norway). The assay detects
primarily a-, mono- and disialotransferrin, although there
may be some reactivity towards the trisialofraction of CDT,
as recently reported by Aldén et al. (2005). The measurements
were carried out on Behring Nephelometer II (Dade Behring,
Behring Diagnostics GmbH, Marburg, Germany). The
within-run precision was 4.7%, day-to-day variation was
6.0%, and accuracy 12.7%. Serum GGT was measured using
enzymatic colorimetric assay, as standardized against IFCC
(International Federation of Clinical Chemistry and Laboratory Medicine). The imprecision within run was 0.85% and
the day-to-day variation was 0.54%. The accuracy of the
GGT method was found to be 5.0%. Serum aspartate aminotransferase (AST) and serum alanine aminotransferase (ALT)
were analysed using pyridoxal phosphate methods according
to IFCC. For AST, the within-run precision was 0.90%, the
day-to-day precision was 1.5%, and accuracy of the method
was 10.6%. For ALT, the corresponding values were: within
run 0.87%, day-to-day 1.1%, and accuracy 12.1%. The analyses of GGT, AST, and ALT were carried out with Cobas
Integra 800 analyser (Roche Diagnostics, Basel, Switzerland).
Mean corpuscular volume (MCV) of erythrocytes was
measured using the Sysmex XE-2100 hematology analyser
(Sysmex Corporation, Kobe, Japan). The imprecision within
run was 0.41% and the day-to-day variation was 0.37%. The
accuracy of the method was 3.7%. All assays were carried
out in an accredited (SFS-EN ISO/IEC 17025) laboratory of
the Seinäjoki Central Hospital, Finland. The cut-offs in the
above assays were as follows: GGT, men 80 U/l, women
50 U/l; CDT, 2.6%; MCV, 96 fl; AST, men 50 U/l, women
35 U/l; ALT, men 50 U/l, women 35 U/l.

Counting the combined marker
GGT–CDT was counted using an equation based on the data
derived from GGT and CDT measurements as follows:
GGT–CDT = 0.8 · ln(GT) + 1.3 · ln(%CDT) (Anttila et al.,
2003a). Analyses for assay cut-offs from the present reference
population were made with ROC analyses using Analyse-It for

The mean values for GGT–CDT, GGT, CDT, MCV, AST, and
ALT were all significantly higher in the heavy drinkers
than those in the moderate drinkers or abstainers (Fig. 1,
P < 0.001 for all comparisons). The sensitivities and specificities of the various markers in differentiating between the
heavy drinkers and the reference individuals are summarized
in Table 1. GGT–CDT reached a sensitivity of 90% for a specificity of 98%, which clearly exceeded the sensitivities
achieved by all the other markers in these comparisons. The
sensitivities and specificities of GGT–CDT were high for
both men and women (Table 1). Combining GGT and CDT
in a manner where either marker is positive obviously yielded
a higher sensitivity (85%) than the assays alone, but even this
approach did not reach the sensitivity of the mathematically
formulated combination (Table 1). When the alcoholic
patients were further classified according to the presence
or absence of liver disease, GGT–CDT showed essentially
similar diagnostic accuracies for both groups, whereas the
diagnostic characteristics of GGT, MCV, AST and ALT
were found to change as a function of liver status (Table 1).
The degree of liver disease severity, as assessed by the combined morphological index (CMI), was not found to correlate
significantly with GGT–CDT (r = 0.19).
When the marker data obtained from the heavy drinkers
were contrasted alternatively with either moderate drinkers
or abstainers, the sensitivity percentages of GGT (+4%),
MCV (+17%), and AST (+20%) all increased when abstainers
were used as the only control population. In contrast, GGT–
CDT and CDT sensitivities were not affected. The threshold
ethanol consumption for elevation of GGT–CDT values
when plotting daily ethanol consumption and GGT–CDT
was found to be 40 g of ethanol (Figure 2). GGT–CDT
also correlated more strongly with self-reported ethanol consumption (r = 0.76, P < 0.001) than either GGT (r = 0.71,
P < 0.001) or CDT (r = 0.59, P < 0.001) alone or any of the
other markers (Table 2).
In the follow-up of 44 alcoholic patients, GGT–CDT was
found to decrease in 93% of these individuals during
11 ± 4 days (range 3–19 days) of supervised abstinence
(Table 3). The estimated time for normalization for GGT–
CDT, depending on the initial value, was 18 ± 9 days, the
mean rate of decay being 1.5% of the initial value per day,

530

J. HIETALA et al.
P<0.001

P<0.001

P<0.001

P<0.001

110

8
7

100

5

MCV fl

GGT-CDT

6

4

90

3
2

80

1
0

70

Heavy drinkers Moderate drinkers

Heavy drinkers Moderate drinkers

Abstainers

Abstainers

P<0.001
P<0.001

P<0.001
400

P<0.001
2000

350
300

AST U/l

GGT U/l

1500

1000

250
200
150
100

500

50
0

0

Heavy drinkers Moderate drinkers

Heavy drinkers Moderate drinkers

Abstainers

P<0.001

P<0.001
14

Abstainers

300

P<0.001

P<0.001

250
12

200

ALT U/l

CDT

10
8

150

6

100
4

50
2

0

0

Heavy drinkers Moderate drinkers

Abstainers

Heavy drinkers Moderate drinkers

Abstainers

Fig. 1. Box plots of various laboratory markers of alcohol consumption in heavy drinkers, moderate drinkers, and abstainers. Alcohol abusers show
significantly higher values than moderate drinkers or abstainers in all comparisons (P < 0.001). GGT–CDT, combined marker based on the data from GGT
and CDT measurements; GGT, g-glutamyltransferase; CDT, carbohydrate-deficient transferrin; MCV, mean corpuscular volume; AST, aspartate aminotransferase; ALT, alanine aminotransferase.

as compared with 3.4% for GGT and 3.7% for CDT. Nevertheless, the changes towards normalization were found to be more
consistent for GGT–CDT and CDT than those for the other
markers (Table 3).

DISCUSSION
In the diagnostics of alcohol use disorders, it is crucial that the
laboratory analyses are accurate. Such analyses are needed

BIOMARKERS OF ALCOHOL CONSUMPTION

531

Table 1. Sensitivities of laboratory markers of alcohol consumption in heavy drinkers, as also divided by gender and liver status, and the specificities, as
obtained from the current reference population
Heavy drinkers with
liver disease

Heavy drinkers
All
n = 165

Men
n = 140

Women
n = 25

All
n = 51

Men
n = 38

Women
n = 13

All
n = 114

Men
n = 102

Women
n = 12

Sensitivity
Specificity
Sensitivity
Specificity
Sensitivity
Specificity
Sensitivity

90
98
58
99
63
98
85

89
98
56
98
65
100
86

96
97
68
100
52
94
83

93
98
76
99
67
98
89

91
98
79
98
71
100
91

100
97
69
100
58
94
83

88
98
50
99
60
98
84

88
98
48
98
62
100
84

91
97
67
100
45
94
82

Specificity
Sensitivity

96
37

98
38

94
35

96
54

98
59

94
42

96
28

98
28

94
27

Specificity
Sensitivity
Specificity
Sensitivity
Specificity
Sensitivity
Specificity

100
45
94
47
95
50
87

100
46
94
43
94
49
88

100
36
95
68
97
57
86

100
69
94
59
95
92
87

100
70
94
53
94
100
88

100
67
95
77
97
67
86

100
42
94
42
95
44
87

100
44
94
40
94
43
88

100
27
95
58
97
55
86

Cut-off
GGT–CDT
GGT U/l
CDT %

Men 4.18
Women 3.81
Men 80
Women 50
2.60

GGT or CDT
elevated
GGT and CDT
elevated
MCV fl

96

AST U/l

Men 50
Women 35
Men 50
Women 35

ALT U/l

Heavy drinkers without
liver disease

both for detecting excessive ethanol consumption and for
monitoring abstinence. An ideal assay should provide
both specificity and sensitivity near 100%. However, to
date such assays have not emerged, although marker combinations have been suggested to open new possibilities for
improving the situation (Salaspuro, 1987; Anton et al., 2001;
Sillanaukee and Olsson, 2001; Anttila et al., 2003a; Hock
et al., 2005).
The present work compares a recently developed marker
combination, defined here as GGT–CDT, with several other
biochemical markers in the diagnosis of alcohol abuse. The
data show that the sensitivity of GGT–CDT, which relies on
a mathematically formulated equation based on serum GGT
and CDT results, exceeds the diagnostic sensitivity of all the
conventional markers of alcohol abuse. Interestingly, this
advantage is achieved without sacrificing assay specificity.
When using standardized methods for the GGT and CDT
measurements, the combination can well be standardized for
multi-laboratory use, too.
It appears that weighing GGT and CDT in the present manner is important for optimizing assay sensitivity. Previously,
combining independent measurements of GGT and CDT
(when either of the markers is positive) has been shown to
yield a sensitivity of 90% for a specificity of 81% in men
and a sensitivity of 75% for a specificity of 87% in women
(Anton et al., 2001). Schwan et al. (2004) recently showed
that combining GGT and CDT as independent parameters provides a sensitivity of 90% in alcohol abusers and 99% in the
alcohol-dependent group, whereas the specificity remains at
a level of only 63%. Hock et al. (2005) recently combined
log GGT and CDT and obtained a sensitivity of 83% with a
specificity of 95%. The sensitivity increased to 88% when
MCV was included as a third component in the analyses.
The use of MCV or any other parameter as a third component
in the present material was, however, not found to lead to any
additional improvement as compared with GGT–CDT alone
(data not shown).

The first studies employing the combination of GGT and
CDT used similar cut-offs for men and women (Sillanaukee
and Olsson, 2001; Anttila et al., 2003a). The present work
shows, however, that different cut-offs for men and women
may be necessary also for this marker. Previously, genderdependent analytical variation has been observed especially
in CDT assays with the CDTect method, which has been later
abolished by the use of %CDT assays (Anton and Moak, 1994;
Tsutsumi et al., 1994; Niemelä et al., 1995; Viitala et al.,
1998; Conigrave et al., 2003). Women are known to be more
sensitive to the hepatotoxic effects of alcohol, and it is possible that the activities of serum GGT may also respond to
alcohol consumption in a gender-dependent manner, which
could explain in part the need for separate cut-offs for men
and women. In this material, the presence of liver pathology
was found to also affect the interpretation of GGT, AST,
ALT, and MCV in the assessment of heavy drinking, whereas
GGT–CDT appears to be more resistant towards the variation
induced by liver pathology per se. The association between
GGT–CDT combination and liver disease may, however,
also depend on the method used for analysing the CDT component of the assay (Viitala et al., 1998; Anttila et al.,
2003b; Fleming et al., 2004).
The diagnostic potential of GGT–CDT is also supported by
its strong correlation with the actual amounts of ethanol consumption from the past 1 month prior to sampling. The values
appear to increase after the daily ethanol consumption exceeds
40 g. Previously, CDT has been reported to elevate with daily
ethanol consumption ranging from 40 to 80 g, possibly also
depending on the method used (Stibler, 1991; Schellenberg
et al., 2005). While GGT has also been suggested to increase
with a threshold consumption of over 40 g of ethanol per day
(Sharpe, 2001), even moderate drinkers may, however, show
increased GGT values more often than abstainers (Hietala
et al., 2005). Interestingly, recent data have suggested that
GGT could actually be considered a marker of oxidative stress
(Lim et al., 2004). It is, thus, possible that combining GGT and

532

J. HIETALA et al.
Table 2. Correlations between biochemical markers of ethanol
consumption, and markers and self-reported ethanol consumption

8

GGT-CDT

7

GGT–CDT
GGT
CDT
MCV
AST
ALT
EtOH g/
previous day
EtOH g/
previous month

6
5
4
3
2
0

20

40

60

80

100

120

140

160

180

200

GGT–CDT

GGT

CDT

MCV

AST

ALT

1
0.90***
0.78***
0.56***
0.72***
0.66***
0.45***

1
0.47***
0.58***
0.66***
0.68***
0.42***

1
0.33***
0.55***
0.40***
0.40***

0.76***

0.71*** 0.59*** 0.52*** 0.59*** 0.50***

1
0.43*** 1
0.33*** 0.85*** 1
0.37*** 0.38*** 0.33***

***P < 0.001.

EtOH g/day during previous month
Table 3. Normalization rates for alcohol markers based on follow-ups of
44 alcoholic patients with supervised abstinence for a period 11 ± 4 days

200

Marker

GGT U/l

160

GGT–CDT
GGT
CDT
AST
ALT
MCV

120

80

Normalization time
(days), mean ± SD

93
84
93
68
57
20

18 ± 9
16 ± 8
16 ± 11
13 ± 20
16 ± 19
N.D.

N.D. not determined.
The sensitivities and specificities are expressed as percentages.
GGT–CDT, combined marker based on the data from GGT and
CDT measurements.

40

0
0

20

40

60

80

100

120

140

160

180

200

EtOH g/day during previous month
10

8

CDT

Percentages of
declining values

6

4

2

0
0

20

40

60

80

100

120

140

160

180

200

EtOH g/day during previous month
Fig. 2. Correlations of GGT–CDT, GGT, and CDT with daily ethanol consumption from the past 1 month prior to sampling. Marker values showed an
increase after a threshold consumption of 40 g/day, GGT–CDT showing
the strongest correlation with the amount of ethanol consumption.

CDT could provide new diagnostic windows with synergistic
benefits for the assessment of hazardous drinking practices.
GGT–CDT seems to recognize ethanol overconsumption
in a similar manner whether or not heavy drinkers are
contrasted with abstainers or moderate drinkers, which may
be a useful characteristic for instance in screening
programmes for excessive alcohol consumption. It should
be noted that in routine health care reference populations in
trials examining diagnostic tests have usually consisted of

combined populations of moderate drinkers and abstainers.
Here inclusion of moderate drinkers into the reference population was found to affect the diagnostic performance of GGT,
AST, and MCV although not GGT–CDT. The combined
marker was also found to be suitable for the follow-up of
abstinence, showing a rather consistent decline during supervised abstinence, with mean normalization rate of 2–3 weeks.
Interestingly, the time required for normalization for GGT–
CDT appeared slightly longer than for each marker separately,
suggesting that the mathematically formulated combination
also follows a slightly different kinetics in its decay.
Taken together, this work supports the idea of using GGT–
CDT for achieving a more sensitive diagnosis of alcohol
abuse. Since this approach is also cost effective and easy to
manage in hospital laboratories, it should be suitable for
routine clinical work.

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ALCOHOLISM: CLINICAL AND EXPERIMENTAL RESEARCH

Vol. 30, No. 10
October 2006

IgAs Against Acetaldehyde-Modified Red Cell Protein as a
Marker of Ethanol Consumption in Male Alcoholic
Subjects, Moderate Drinkers, and Abstainers
Johanna Hietala, Heidi Koivisto, Jaana Latvala, Petra Anttila, and Onni Niemelä

Background: Alcohol abuse has been shown to result in the production of antibodies against
acetaldehyde-modified epitopes in proteins. However, as yet, only limited information has been available on the clinical usefulness of such responses as markers of hazardous drinking.
Methods: We developed an ELISA to measure specific IgAs against acetaldehyde-protein
adducts. This method was evaluated in cross-sectional and follow-up studies on male heavy drinkers
with a current ethanol consumption of 40 to 540 g/d (n 5 40), moderate drinkers consuming 1 to
40 g/d (n 5 25), and abstainers (n 5 16). The clinical assessments included detailed interviews on the
amounts and patterns of ethanol consumption and various biochemical markers of alcohol abuse and
liver function.
Results: The mean antiadduct IgAs (198  28 U/L) in the alcohol abusers were significantly
higher than those in the moderate drinkers (58  11 U/L, po0.001) or abstainers (28  8 U/L,
po0.001). The values of moderate drinkers were also higher than those in abstainers (po0.05). The
amount of ethanol consumed during the period of 1 month preceding blood sampling correlated
strongly with antiadduct IgAs (r 5 0.67, po0.001). The sensitivity (73%) and specificity (94%) of this
marker were found to exceed those of the conventional laboratory markers of alcohol abuse in comparisons contrasting heavy drinkers with abstainers although not in comparisons contrasting heavy
drinkers with moderate drinkers. During abstinence, antiadduct IgAs disappeared with a mean rate
of 3% per day. In additional analyses of possible marker combinations, antiadduct IgAs, together
with CDT, were found to provide the highest sensitivity and specificity.
Conclusions: Measurements of antiadduct IgAs may provide a new clinically useful marker of
alcohol abuse, providing a close relationship between marker levels and the actual amounts of recent
ethanol ingestion.
Key Words: Ethanol, Marker, Acetaldehyde, Immune Responses.

E

XCESSIVE ALCOHOL CONSUMPTION has been
shown to induce the production of circulating antibodies, which recognize sequential and conformational
epitopes generated in covalent binding reactions between
proteins and ethanol metabolites (Israel et al., 1986;
Koskinas et al., 1992; Niemelä, 2001; Viitala et al., 1997;
Worrall et al., 1991; Xu et al., 1998). Previously, studies in
alcoholic patients with liver disease have indicated that in
such patients, there is often an increase in serum total IgAs
coinciding with abnormal IgA tissue deposition (Amore
et al 1994; van de Wiel et al 1988). Other studies have
From the Department of Laboratory Medicine and Medical Research
Unit, Seinäjoki Central Hospital, and University of Tampere, Tampere,
Finland.
Received for publication March 21, 2006; accepted May 30, 2006.
Supported in part by a grant from the Finnish Foundation for Alcohol
Studies (ON).
Reprint requests: Prof. Onni Niemelä, Seinäjoki Central Hospital,
Laboratory, Seinäjoki, FIN-60220, Finland; Fax:1358-6-415-4924;
E-mail: onni.niemela@epshp.fi
Copyright r 2006 by the Research Society on Alcoholism.
DOI: 10.1111/j.1530-0277.2006.00204.x
Alcohol Clin Exp Res, Vol 30, No 10, 2006: pp 1693–1698

further shown high levels of IgA antibodies directed against
acetaldehyde-derived neoantigens in alcoholic subjects,
suggesting antigen-driven IgA responses (Latvala et al.,
2005; Viitala et al., 1997; Worrall et al., 1991). Worrall
et al. (1996, 1998) have previously suggested the possibility of
using antiadduct IgAs also as markers of ethanol consumption. However, as yet, only a few studies have been
available on clinical evaluations of this approach.
The present study was set out to gain further insight on
the diagnostic utility of measuring antiadduct IgAs by
comparing the IgA marker with several traditional markers of ethanol consumption in male subjects with a wide
range of alcohol consumption.
MATERIALS AND METHODS
Patients and Control Subjects
The study population included 40 male heavy drinkers (mean age
45  11 years), who showed a well-documented history of excessive
ethanol consumption. All of these patients had been admitted for
detoxification, but were devoid of clinical and laboratory signs of
significant liver disease. They showed a history of continuous
ethanol consumption or binge drinking, the mean recent consumption
1693

HIETALA ET AL.

1694

being 40 to 540 g/d from the period of 4 weeks before sampling. The
documentation of alcohol abuse was based on detailed personal
interviews using a time-line follow-back technique. The mean duration
of abstinence before sampling was 2  2 days. Nineteen alcoholic
subjects (mean age 42  12 years) volunteered for a follow-up, which
was carried out with supervised abstinence and repeated sampling
during hospitalization over a period of 8  3 days. Blood alcohol
concentrations during this time were controlled by repeated ethanol
analyses from breath air.
Reference individuals were healthy male volunteers who were
either abstainers (n 5 16, age 54  15 years) or moderate drinkers
(n 5 25, age 45  12 years), whose daily ethanol consumption did
not exceed 40 g. All of these subjects were devoid of any history or
clinical evidence of alcohol abuse, recent illnesses, or immunological
disorders.
All serum samples were stored at 70 1C until analysis. All participants of the study gave their informed consent, and the study was
carried out according to the provisions of the Declaration of Helsinki.
Antiadduct IgA Analyses
Preparation of Acetaldehyde-Modified Red Cell Protein. For preparation of the test antigen, human erythrocyte protein fraction was
first purified from EDTA blood of an abstainer (Latvala et al., 2005).
The cells were separated by centrifugation and washed 3 times with
phosphate-buffered saline (PBS, 7.9 mM Na2HPO4, 1.5 mM
KH2PO4, 137 mM NaCl, 2.7 mM KCl, pH 7.4). The washed cells
were lysed with polyoxyethylene ether, 0.1% v/v in borate buffer
(Hemolysis Reagent, DIAMATTM Analyzer system, Bio-Rad Laboratories, Hercules, CA), and incubated for 35 minutes at 37 1C to
remove unstable Schiff bases. The hemolyzate containing 12 mg of
red cell protein/mL (in PBS) was stored frozen in aliquots at 70 1C.
For acetaldehyde labeling, the hemolyzate was mixed with acetaldehyde (in PBS) to obtain a final acetaldehyde concentration of
10 mM. After incubation for 18 hours at 4 1C in tightly sealed containers, the protein adducts generated were reduced by addition of
sodium cyanoborohydride (10 mM) and gentle mixing for 5 hours
at 4 1C. Protein solutions were then dialyzed exhaustively against
PBS at 4 1C and stored in aliquots for single use at 70 1C. The
unmodified proteins were obtained by hemolyzing and treating
EDTA blood of an abstainer without acetaldehyde.
Measurements of the Antibody Titers. Microtiter plates (NuncImmuno Plate, MaxisorbTM, InterMed, Denmark) were coated with
acetaldehyde-modified red cell protein, or corresponding unmodified
proteins in PBS (3 mg protein in 100 mL/well) and incubated for
112 hours at 137 1C. Nonspecific binding was blocked by incubation
(1 hour, 137 1C) with 0.2% gelatin in PBS (150 mL/well). The samples were diluted (1:40) in PBS, which contained 0.04% Tween-20.
The serum dilutions were allowed to react with the coated proteins
(1 hour, 137 1C), followed by extensive washing with PBS-Tween.
Antibody–antigen complexes were detected using alkaline
phosphatase–linked goat anti-human immunoglobulin IgA (Jackson
ImmunoResearch Laboratories Inc., West Grove, PA). The
immunoglobulins were diluted in PBS-Tween, containing 8 mM
MgCl2 and a small amount of dithiothreitol (DTT). The plates were
incubated overnight at 14 1C and washed with PBS-Tween and 100
mL of p-nitrophenylphosphate solution was added as a color reaction
substrate (alkaline phosphatase substrate kit, Bio-Rad). This reaction was stopped by adding 100 mL NaOH (0.4 M), and the optical
densities were read at 405 nm by an Anthos HTII microplate reader
(Anthos Labtec Instruments, Salzburg, Austria).
Other Measurements
Serum carbohydrate-deficient transferrin (CDT) was measured
by a turbidimetric immunoassay (TIA) after ion-exchange
chromatography (Axis-Shield, Oslo, Norway), which separates

transferrin variants with 0 to 2 sialic acid residues. The measurements were carried out on a Behring Nephelometer II (Dade
Behring, Behring Diagnostics GmbH, Marburg, Germany)
according to the instructions of the manufacturer. Serum g-glutamyl
transferase (GGT), aspartate aminotransferase (AST), and mean
corpuscular volume (MCV) of erythrocytes were measured by standard clinical chemical methods in an accredited (SFS-EN 45001,
ISO/IEC Guide 25) laboratory of EP Central Hospital, Seinäjoki,
Finland. Cytokines IL-2, IL-6, IL-8, IL-10, TNF-a, and TGF-b1
were measured using Quantikine high-sensitivity ELISA kits (R&D
Systems, Abington Science Park, UK).
Calculations and Statistical Methods
The data for the study variables are expressed as mean  SEM. In
the assays for the antiadduct IgAs, the values (OD405) obtained in a
reaction with the sample and the unconjugated protein (background)
were subtracted from the corresponding values measured
from the reaction between the sample and the acetaldehydeprotein conjugate. The antiadduct IgA values are expressed as U/L,
corresponding to OD405103. The combination marker IgA-CDT
was calculated with an equation logCDT1(IgA/103). The combination of GGT and CDT (GGT-CDT) was counted using a previously
established equation GGT-CDT 5 0.8ln(GGT)11.3ln(%CDT)
(Anttila et al., 2003). The differences between the groups of heavy
drinkers, moderate drinkers, and abstainers were analyzed with an
ANOVA or a Kruskal–Wallis test, as required. A paired t-test was
used for comparing alcoholic subjects before and after abstinence,
and the difference between moderate drinkers and abstainers was
further examined with an unpaired t-test or a Mann–Whitney test, as
required. Correlations were calculated using the Pearson product–
moment correlation coefficients for continuous nonskewed parameters or Spearman’s rank-correlations for noncontinuous or skewed
variables. A p-value o0.05 was considered statistically significant.

RESULTS

The mean antiadduct IgA levels (198  28 U/L) in the
alcohol abusers were significantly higher than those in the
moderate drinkers (58  11 U/L, po0.001) or abstainers
(28  8 U/L, po0.001) (Fig. 1). When comparing only
moderate drinkers and abstainers with each other, the values of moderate drinkers were also significantly higher
than those in abstainers (po0.05).
The diagnostic sensitivity and specificity of antiadduct
IgA measurements were subsequently compared with
those of the traditional markers of alcohol abuse by contrasting the data obtained from the heavy drinkers with
the data obtained from the abstainers and/or moderate
drinkers (Table 1). In comparison with the abstainers only,
the sensitivity of antiadduct IgAs was 73% for a specificity
of 94%, which exceeded the corresponding figures found
for CDT, GGT, MCV, and AST. When both moderate
drinkers and abstainers were included in the reference
population, the sensitivity of antiadduct IgA assay was
65% for a specificity of 88%, showing essentially similar
analytical characteristics to those of CDT although
remaining higher than those of GGT, MCV, or AST
(Table 1). The antiadduct IgAs correlated significantly to
all the conventional markers of alcohol abuse (Table 2)
and also highly significantly to the actual amount of recent
ethanol consumption (r 5 0.67, po0.001). In comparison

ANTIADDUCT IgAs AND ALCOHOL

1695

P < 0.001***
P < 0.001***

P < 0.001***

800

15.0
12.5

600
10.0

500
P < 0.05*

400

%CDT

Anti-adduct IgA (U /l)

700

P < 0.001***

300

7.5
5.0

200
2.5

100
0

0.0
Alcoholics

Moderate drinkers

Abstainers

Alcoholics

P < 0.001***
400

Moderate drinkers

Abstainers

P < 0.001***

P < 0.001***

110
P < 0.01***

105
300
MCV (fl)

GGT (U/l)

100
200

95
90

100
85
0

80
Alcoholics

Moderate drinkers

Abstainers

Alcoholics

Moderate drinkers

Abstainers

P < 0.05*
200

AST (U/l)

150

100

50

0
Alcoholics

Moderate drinkers

Abstainers

Fig. 1. Markers of ethanol consumption in heavy drinkers, moderate drinkers, and abstainers. Antiadduct IgA, carbohydrate-deficient transferrin, and
g-glutamyl transferase values in heavy drinkers are all significantly higher than those in both moderate drinkers and abstainers (po0.001 for all comparisons).
Mean corpuscular volume (MCV) was significantly higher (po0.001) in alcoholic subjects than in abstainers, and aspartate aminotransferase was significantly
higher (po0.05) in alcoholic subjects than in moderate drinkers. Significant differences between moderate drinkers and abstainers were found in antiadduct IgA
and in MCV values (dotted lines).

with the major cytokines, antiadduct IgAs were found to
correlate significantly with serum IL-6 (r 5 0.33, po0.05)
and TNF-a (r 5 0.31, po0.05) levels, whereas not with
IL-2, IL-8, IL-10, or TGF-b1.
Figure 2 demonstrates the results of the follow-up of
heavy drinkers. The values at the initiation (160  31 U/L)
decreased significantly to 131  26 U/L (po0.01) during a
period of 8  3 days of supervised abstinence. After this

time, the levels were still higher than those of moderate
drinkers or abstainers, the difference to the latter group
remaining statistically significant (po0.001). The rate of
antiadduct IgA disappearance was estimated to be about
3% per day, and the mean normalization time to be about
4 weeks.
In the analyses for possible marker combinations, the
highest sensitivities and specificities were obtained by

HIETALA ET AL.

1696

Table 1. Sensitivity and Specificity Characteristics of Various Markers of
Ethanol Consumption When Either Abstainers or Moderate Drinkers Are
Used as the Control Population
Source of cutoff
Antiadduct IgA
Abstainers
Abstainers and moderate
drinkers
Moderate drinkers
CDT
Abstainers
Abstainers and moderate
drinkers
Moderate drinkers
GGT
Abstainers
Abstainers and moderate
drinkers
Moderate drinkers
MCV
Abstainers
Abstainers and moderate
drinkers
Moderate drinkers
AST
Abstainers
Abstainers and moderate
drinkers
Moderate drinkers

CutoffSensitivity %Specificity %

AUC (SE)

74
93

73
65

94
88

0.902 (0.0401)
0.843 (0.0436)

99

65

88

0.806 (0.0545)

2.67
2.54

63
65

100
98

0.889 (0.0432)
0.897 (0.0343)

2.46

65

96

0.902 (0.0366)

50
55

63
60

100
98

0.846 (0.0508)
0.850 (0.0433)

59

58

96

0.852 (0.0465)

95
98

47
41

100
98

0.822 (0.0591)
0.738 (0.0623)

100

19

96

0.684 (0.0713)

45
46

43
43

100
95

0.688 (0.0715)
0.689 (0.0604)

47

43

92

0.690 (0.0656)

Cut-offs were determined as mean12SD.
AUC, area under curve; SE, standard error of AUC; IgA, immunoglobulin A; CDT, carbohydrate-deficient transferrin; GGT, g-glutamyl
transferase; MCV, mean corpuscular volume of erythrocytes; AST,
aspartate aminotransferase.

combining IgAs with CDT, which yielded a sensitivity of
90%, a specificity of 98%, and an area under the curve of
0.966 (Table 3).
DISCUSSION

The present data indicate that the assessment of IgA
antibodies to acetaldehyde-modified protein epitopes may
provide a clinically useful tool for diagnosing excessive
ethanol consumption. As IgAs already among moderate
drinkers may exceed the levels observed in teetotallers, it
appears that the generation of such immune responses is
an early event in the physiological consequences induced
by ethanol ingestion, which should also be considered in
Table 2. Correlations Between the Different Markers of Ethanol Intake

Antiadduct IgA
CDT
GGT
MCV
AST

Antiadduct IgA

CDT

GGT

MCV

AST

1
0.39
0.35
0.51
0.23

1
0.43
0.28
0.46

1
0.48
0.46

1
0.32

1

po0.05; po0.01; po0.001.

CDT, carbohydrate-deficient transferrin; GGT,g-glutamyl transferase;
MCV, mean corpuscular volume of erythrocytes; AST, aspartate aminotransferase.

studies on the mechanisms of ethanol-induced tissue
effects.
Previous studies in patients with alcoholic liver disease
have demonstrated an increase in serum total IgAs and the
appearance of IgA deposits in liver and kidney tissue
(Amore et al., 1994; Tuma and Klassen, 1992; van de Wiel
et al., 1988). More recent evidence has suggested that the
generation of excess IgAs in such patients could in fact be
antigen-driven (Koskinas et al., 1992; Latvala et al., 2005;
Viitala et al., 1997; Worrall et al., 1991). Such specific
antibodies could originate from intestinally induced B-cells
under conditions where the gastrointestinal tract, which is
rich in enzymes capable of metabolizing ethanol to acetaldehyde, is repeatedly exposed to ethanol (Latvala et al.,
2005; Salaspuro, 1996; Seitz et al., 1994; Visapää et al.,
1998). This view is also consistent with the strong correlation between the specific IgA antibody levels and the
amounts of recent ethanol ingestion as well as with the
presence of antiadduct IgAs in individuals reporting
moderate drinking. As alcohol is also known to increase
intestinal permeability, this could further enhance the
immune responses toward the intestinal antigens. The positive correlation found between antiadduct IgAs and the
proinflammatory cytokines TNF-a and IL-6 indicates that
there is also an early-phase inflammatory response to
ethanol-derived neoantigens. Upon continuing heavy
drinking, the induction of the immune responses and the
cytokine cascades may also play an important role in the
sequence of events leading to liver pathology. Acetaldehyde modification of proteins and cellular constituents has
been previously shown to disturb protein function in vivo,
and the generation of IgAs toward ethanol metabolites
could also promote the destruction of such protein modifications.
The present data indicate a high sensitivity and
specificity for the adduct-specific IgA measurements in
differentiating between alcoholic subjects and nonalcoholic subjects. Worrall et al. (1996, 1998) have previously
investigated antiadduct IgA responses as markers of alcohol
abuse using acetaldehyde-modified bovine serum albumin
as a test antigen. Despite the difference in the method and
the nature of protein adducts in these and the present studies, it should be noted that Worrall and coworkers also
found a significant correlation (r 5 0.44) between ethanol
intake and antiadduct IgAs among social drinkers and
alcoholic subjects. Previously, the control populations in
biomarker studies have usually consisted primarily of
social drinkers, and the possible differences occurring
between moderate drinkers and teetotallers have received
less attention. The present data show that the diagnostic
sensitivity of antiadduct IgAs exceeds that of the conventional markers especially when abstainers are used as the
reference individuals. Conversely, inclusion of moderate
drinkers in the reference population decreases the diagnostic sensitivity, indicating that future reference limits for
alcohol markers should perhaps preferably be based on

ANTIADDUCT IgAs AND ALCOHOL

1697

14
p = 0.0028**

p = 0.0002***

12

400

10
300

%CDT

Anti-adduct IgA (U/l)

500

200

8
6
4

100
2
0

0

A

B

A

300

110
p = 0.13

p = 0.024*

250

105

200

100

MCV (fl)

GGT (U/l)

B

150

95

100

90

50

85

0

80

A

B

A

B

250
p = 0.24

AST (U/l)

200
150
100
50
0

A

B

Fig. 2. Laboratory parameters of alcoholic subjects before and after 8  3 days of abstinence. The decreases in antiadduct IgA (p 5 0.0028) and carbohydrate-deficient transferrin values (p 5 0.0002) were statistically significant. Mean corpuscular volume values showed a significant increase during abstinence
(p 5 0.024). (A) Alcoholic subjects before abstinence and (B) after abstinence.

abstainers. This approach would obviously lead to some
positive values in individuals with moderate drinking habits, but provide us with a new tool for raising the issue of
possible hazardous drinking practices in an earlier phase.
Current follow-up studies indicate that serum antiadduct IgA levels normalize at an average rate of 3% per
day, the mean time required for normalization being
29 days. As the average half-life of a single IgA molecule is
5 to 6 days, the relatively long appearance of antiadduct
IgAs in the serum may be explained by the fact that acetaldehyde adducts in erythrocytes of alcoholic subjects may
Table 3. Sensitivities and Specificities of Marker Combinations

IgA-CDT
GGT-CDT

Cutoff

Sensitivity %

Specificity %

0.412
4.20

90
83

98
98

CDT, carbohydrate-deficient transferrin.

persist in circulation for 1 to 3 weeks after the last dose of
ethanol (Niemelä and Israel, 1992). The consistent
decrease in the antiadduct IgAs upon abstinence indicates,
however, that IgA titers could also be used for monitoring
treatment in recovering alcoholic subjects.
Recent evidence has suggested that further improvement
in the clinical accuracy of alcohol markers may be
obtained through the development of ideal marker combinations. Such combinations have usually consisted of
CDT, GGT, and MCV. Recent studies have indicated the
highest diagnostic accuracy for a mathematically formulated combination of GGT and CDT (Anttila et al., 2003;
Sillanaukee and Olsson, 2001). The present work shows
that the combination of antiadduct IgAs and CDT also
provides improved sensitivity compared with its parent
components without sacrificing assay specificity. The
diagnostic performance also seems to exceed that found
for the combination of GGT and CDT. It should be noted,
however, that before adopting the IgA-based assay into

HIETALA ET AL.

1698

routine clinical and multilaboratory use, a careful standardization of the method will be needed. This could be
achieved by using internationally standardized antigen
preparations and test protocols including standard color
reaction times and the expression of the assay results using
international reference samples.
In this study, we chose to study men only, because sex
may be a significant confounding factor in studies on
immunological responses in vivo (Kovacs and Messingham,
2002; Makkonen et al., 2001). Although the specific mechanisms underlying these phenomena have remained
unclear, sex hormones appear to play a key role in the
regulation of immune responses. As women generally also
show stronger immune responses and higher serum
immunoglobulin levels, future studies in populations consisting of women only also appear warranted to evaluate
the diagnostic potential and pathogenic significance of the
IgA responses.
Taken together, this work shows that measurements of
specific IgAs against acetaldehyde-modified epitopes in
proteins could be used as a sensitive tool for detecting
heavy drinking. Assays for such immune responses could
also be important in studies on the pathogenesis of
ethanol-induced tissue injury.
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