INTERPRETATION OF POSTMORTEM
TOXICOLOGY RESULTS
Pharmacogenetics and Drug-Alcohol Interaction
Anna Koski
Department of Forensic Medicine
University of Helsinki
Finland
ACADEMIC DISSERTATION
To be publicly discussed, with the permission of the Medical Faculty of the
University of Helsinki, in the auditorium of the
Department of Forensic Medicine on September 23rd 2005, at 12 noon.
Helsinki 2005
SUPERVISORS
Professor Antti Sajantila
Department of Forensic Medicine
University of Helsinki
Helsinki, Finland
Docent Ilkka Ojanperä
Department of Forensic Medicine
University of Helsinki
Helsinki, Finland
REVIEWERS
Docent Eero Mervaala
Institute of Biomedicine
University of Helsinki
Helsinki, Finland
Docent Kari Poikolainen
Finnish Foundation for Alcohol Studies
National Research and Development Centre for Welfare and Health
Helsinki, Finland
OPPONENT
Professor Jørg Mørland
Division of Forensic Toxicology and Drug Abuse
Norwegian Institute of Public Health
Oslo, Norway
ISBN 952-91-9214-2 (paperback)
ISBN 952-10-2662-6 (pdf)
http://ethesis.helsinki.fi
Helsinki University Printing House
Helsinki 2005
Obtaining a quantitative result is not the endpoint of the analytical process.
Irving Sunshine
CONTENTS
ABBREVIATIONS ......................................................................................................................... 6
LIST OF ORIGINAL PUBLICATIONS .............................................................................................. 7
ABSTRACT .................................................................................................................................. 8
INTRODUCTION ........................................................................................................................... 9
REVIEW OF THE LITERATURE ................................................................................................... 10
1 Interpretation of Postmortem Forensic Toxicology Results................................................ 10
1.1 Blood Samples .............................................................................................................. 10
1.1.1 Toxicological Tables ............................................................................................ 11
1.2 Other Matrices .............................................................................................................. 12
1.3 Postmortem Changes .................................................................................................... 12
1.4 Metabolites.................................................................................................................... 13
1.5 Alcohol Toxicity ........................................................................................................... 13
1.6 Drug Toxicity................................................................................................................ 13
1.6.1 Fatal Toxicity Index ............................................................................................. 14
1.6.2 Other Measures of Toxicity.................................................................................. 15
1.6.3 Sources of Bias in Toxicity Indices...................................................................... 15
2 Pharmacogenetics ................................................................................................................ 16
2.1 Drug-Metabolizing Enzymes........................................................................................ 16
2.1.1 Cytochrome P450 System .................................................................................... 16
CYP2D6 ............................................................................................................... 17
CYP2C19 ............................................................................................................. 19
2.2 Studies on Drug Metabolism ........................................................................................ 19
2.2.1 Tramadol Metabolism .......................................................................................... 19
2.2.2 Amitriptyline Metabolism .................................................................................... 20
2.3 Clinical Pharmacogenetics............................................................................................ 21
2.4 Postmortem Pharmacogenetics ..................................................................................... 22
3 Drug-Alcohol Interaction .................................................................................................... 23
3.1 Alcohol Effects and Anesthetic Action ........................................................................ 23
3.1.1 γ-Aminobutyric Acid Receptor Type A ............................................................... 24
3.2 Animal Studies.............................................................................................................. 24
3.3 Postmortem Studies ...................................................................................................... 25
AIMS OF THE STUDY ................................................................................................................. 26
4
CONTENTS
MATERIALS AND METHODS ...................................................................................................... 27
1 Autopsy cases ...................................................................................................................... 27
1.1 Blood Samples .............................................................................................................. 27
1.2 Database ........................................................................................................................ 27
2 Analysis of Drug Concentrations ........................................................................................ 27
2.1 Screening....................................................................................................................... 27
2.2 Metabolite Analysis ...................................................................................................... 28
3 Genotyping .......................................................................................................................... 28
3.1 Long Polymerase Chain Reaction................................................................................. 29
3.2 Restriction Fragment Length Polymorphism Analysis................................................. 29
3.3 Multiplex Single-Base Extension Reaction..................................................................... 29
4 Case Selection Criteria ........................................................................................................ 29
5 Statistical Methods .............................................................................................................. 30
RESULTS ................................................................................................................................... 31
1 Pharmacogenetics ................................................................................................................ 31
1.1 CYP2D6 and Tramadol (I) ............................................................................................ 31
1.2 CYP2D6 and Amitriptyline (II)..................................................................................... 31
1.3 CYP2C19 and Amitriptyline (II)................................................................................... 32
1.4 Allele and Genotype Frequencies (I, II)........................................................................ 33
2 Fatal Toxicity Indices (IV, V) ............................................................................................. 33
3 Drug-Alcohol Interaction..................................................................................................... 34
3.1 Alcohol and Benzodiazepines (III) ............................................................................... 34
3.2 Alcohol and Other Common Drugs (IV-VI)..................................................................... 34
DISCUSSION .............................................................................................................................. 38
1 Methodological Considerations ........................................................................................... 38
2 Pharmacogenetics ................................................................................................................ 39
3 Drug-Alcohol Interaction..................................................................................................... 41
3.1 Alcohol and Benzodiazepines....................................................................................... 41
3.2 Alcohol and Other Common Drugs .............................................................................. 41
4 Drug Safety.......................................................................................................................... 42
4.1 Newer Antidepressants ................................................................................................. 42
5 Implications for Interpretation............................................................................................. 43
CONCLUSIONS .......................................................................................................................... 45
ACKNOWLEDGMENTS ............................................................................................................... 46
REFERENCES............................................................................................................................. 47
CONTENTS
5
ABBREVIATIONS
ADR
BAC
BDZ
bp
CI
CNS
CYP
CYP2C19
CYP2C19
CYP2D6
CYP2D6
DDD
DME
EHAT
EHNT
EM
FTI
GC
gEM
gPM
gUM
ICD-10
IM
kb
LC/MS-MS
LD50
LIMS
M1
M2
M3
M4
M5
MR
MRM
MS
NNT
p
OPLC
PCR
PM
RFLP
SSRI
TCA
TLC
UM
ZHAT
ZHNT
6
adverse drug reaction
blood alcohol concentration
benzodiazepine
base pair
confidence interval
central nervous system
cytochrome P450
cytochrome P450 enzyme 2C19
gene encoding CYP2C19
cytochrome P450 enzyme 2D6
gene encoding CYP2D6
defined daily dose
drug-metabolizing enzyme
(E)-10-hydroxyamitriptyline
(E)-10-hydroxynortriptyline
extensive metabolizer (phenotype)
fatal toxicity index
gas chromatography
genetically extensive metabolizer
genetically poor metabolizer
genetically ultra-rapid metabolizer
International Classification of Diseases, 10th Revision
intermediate metabolizer (phenotype)
thousand base pairs
liquid chromatography – tandem mass spectrometry
median lethal dose, the dose required to kill 50% of the given population
laboratory information management system
O-demethyltramadol
N-demethyltramadol, nortramadol
N,N-didemethyltramadol
O,N,N-tridemethyltramadol
O,N-didemethyltramadol
metabolite ratio
multiple reaction monitoring
mass spectrometry
N-demethylnortriptyline
significance level
overpressured layer chromatography
polymerase chain reaction
poor metabolizer (phenotype)
restriction fragment length polymorphism
selective serotonin reuptake inhibitor
tricyclic antidepressant
thin layer chromatography
ultra-rapid metabolizer (phenotype)
(Z)-10-hydroxyamitriptyline
(Z)-10-hydroxynortriptyline
ABBREVIATIONS
LIST OF ORIGINAL PUBLICATIONS
This thesis is based on the following articles, which are referred to as I-VI in the text:
I
Levo A, Koski A, Ojanperä I, Vuori E, Sajantila A (2003) Post-mortem SNP analysis of
CYP2D6 gene reveals correlation between genotype and opioid drug (tramadol) metabolite
ratios in blood. Forensic Sci Int 135(1):9-15.
II
Koski A, Sistonen J, Ojanperä I, Gergov M, Vuori E, Sajantila A (2005) CYP2D6 and
CYP2C19 genotypes and amitriptyline metabolite ratios in a series of medicolegal autopsies.
Forensic Sci Int (in press, published online July 14, DOI: 10.1016/j.forsciint.2005.05.032).
III
Koski A, Ojanperä I, Vuori E (2002) Alcohol and benzodiazepines in fatal poisonings. Alcohol
Clin Exp Res 26(7):956-9.
IV
Koski A, Ojanperä I, Vuori E (2003) Interaction of alcohol and drugs in fatal poisonings. Hum
Exp Toxicol 22(5):281-7.
V
Koski A, Vuori E, Ojanperä I (2005) Newer antidepressants: evaluation of fatal toxicity index
and interaction with alcohol based on Finnish postmortem data. Int J Legal Med (in press,
published online March 1, DOI: 10.1007/s00414-005-0528-x).
VI
Koski A, Vuori E, Ojanperä I (2005) Relation of postmortem blood alcohol and drug
concentrations in fatal poisonings involving amitriptyline, propoxyphene and promazine. Hum
Exp Toxicol 24(8):389-96.
The original publications are reproduced with the permission of the copyright holders.
LIST OF ORIGINAL PUBLICATIONS
7
ABSTRACT
Postmortem forensic toxicology annually reveals more than a thousand fatal poisonings in Finland.
Both alcohol and drugs are found in the vast majority of cases, with certain drugs more often
involved than others. Some of the drugs commonly causing fatal poisonings are polymorphically
metabolized.
In this thesis, a retrospective, statistical approach was taken to elucidate the role of pharmacogenetics
and drug-alcohol interaction in fatal poisonings. More specifically, the objective was to investigate
whether certain genetic variants associated with abnormal drug metabolism can be correlated with
metabolite ratios in postmortem material, and whether an interaction between alcohol and common
toxic drugs is perceptible in fatal poisonings. Methods included genotyping and metabolite analysis
using autopsy blood, as well as statistical analysis of the obtained metabolite ratios. Drug safety was
evaluated as a function of alcohol and drug concentrations determined in postmortem blood and of
fatality rates in relation to the sales of drugs.
Correlations between the CYP2D6 gene dose and the tramadol metabolite ratios were observed in 33
cases involving tramadol. In 195 cases involving amitriptyline, similar correlations were found
between the CYP2D6 gene dose and the metabolite ratios related to stereospecific ring hydroxylation
and between CYP2C19 gene dose and the metabolite ratios related to N-demethylation. Most
importantly, the nonfunctional genotypes were significantly different from the corresponding fully
functional genotypes with respect to several of the investigated metabolite ratios. However, no fatal
poisonings with accidental or undetermined cause of death were associated with nonfunctional
genotypes.
Regarding fatal poisonings involving two common benzodiazepines, blood alcohol concentrations
were on average lower in cases involving temazepam than in those involving diazepam or alcohol
alone. Diazepam therefore appeared safer in combination with alcohol than temazepam. Among the
drugs most commonly causing fatal poisonings, promazine, doxepin, amitriptyline, and
propoxyphene were the least safe in combination with alcohol, whereas zopiclone, diltiazem, and the
newer antidepressants proved relatively safe. The selective serotonin reuptake inhibitors appeared the
safest among the newer antidepressants. Interestingly, the least safe drugs in combination with
alcohol were also found to cause more fatal poisonings with respect to their sales than the other drugs
included in the study. A similar correlation was also observed within the group of newer
antidepressants.
In conclusion, genetic factors seem to play a more dominant role in metabolite ratios than age,
gender, or environmental factors, and postmortem genotyping may therefore provide useful
information in poisoning cases where the manner of death is unclear. When determining the cause of
death, the possibility of a fatal poisoning due to an interaction between alcohol and drugs should be
considered seriously, especially when certain toxic drugs are involved. These results have
implications not only for the interpretation of postmortem toxicology results but for drug safety in
general.
8
ABSTRACT
INTRODUCTION
Approximately 50 000 Finns die each year.
Twenty percent of these deaths are investigated
in a medicolegal autopsy, and in about half of
the autopsy cases samples are taken for
toxicological analysis. Forensic toxicology, i.e.
the use of toxicology for legal purposes, today
employs a wide variety of analytical methods
producing a wealth of data. In postmortem
investigation, the main purpose of these data is
to help the forensic pathologist to determine the
cause of death, but the eventual significance of
the results can vary greatly. Besides confirming,
revealing, or excluding fatal poisonings, the
findings may yield important information on the
contributing factors and general circumstances
of the death.
According to Act 169/1948, all postmortem
forensic toxicology in Finland is centralized to
the Laboratory of Toxicology, Department of
Forensic Medicine, at the University of
Helsinki. Blood, urine, and liver are routinely
screened for drugs, alcohols, and drugs of abuse.
Upon request, samples are also analyzed for
carbon monoxide, cyanide, and other suspected
poisons. Analytical methods include chromatography, spectrometry, and immunological
assays. DNA analysis may also be employed for
further investigations. Broad drug screens and
dedicated analyses are focused on reliable
detection, identification, and quantitation of
potentially toxic compounds. Quality control is
extensively applied to ascertain the integrity of
results. The laboratory was accredited by
the Finnish Accreditation Service (FINAS) in
1997.
Advances in pharmacology, resulting in
new drugs and combinations of drugs, as well as
in novel indications for existing drugs, pose a
challenge to forensic toxicology. The discipline
is further complicated by illegal drugs, designer
drugs, and changing local and global trends in
drug abuse. To keep current on what is
happening ‛on the street’, the analytical methods
in the laboratory must be continuously
developed. Modern-day forensic toxicology
produces a wealth of data, demanding
automation in analysis, reporting, and data
management. Forensic toxicology findings are
therefore stored in a database such as the
Laboratory Information Management System
(LIMS) in the Laboratory of Toxicology.
Interpretation of postmortem toxicology
results is based on a forensic pathologist’s
experience and on previously reported findings
regarding toxicity of drugs, alcohols, and other
common poisons. In Finland, it is the forensic
pathologist who determines the cause of death,
although the forensic toxicologist may be
consulted on analytical findings. A strength of
Finnish forensic medicine is the practice of the
investigating pathologist to send a copy of the
completed death certificate to the Laboratory of
Toxicology. Integrating the information on
cause and manner of death to the LIMS creates a
nation-wide databank enabling complex
research and acquisition of detailed statistics on
Finnish fatalities.
There are several confounding factors in
the interpretation of postmortem toxicology
results. Besides the background information,
important issues to be taken into consideration
include postmortem redistribution, individual
variation,
and
concomitant
findings.
Theoretically, any two compounds that share a
mechanism of action or produce a similar
response may cause unwanted or pronounced
adverse effects. In practice, the most common
agent to interact with a drug is alcohol. Alcohol
is a frequent finding in forensic toxicology, and
being a central nervous system (CNS)
depressant, is often deemed to have played a
part in causing death. A study was therefore
undertaken to elucidate the role of alcohol in
fatal poisonings. In addition, the role of genetic
factors in drug-related deaths was investigated.
The general purpose of this thesis was to
assess the importance of pharmacodynamic
drug-alcohol interactions and pharmacogenetic
variation affecting drug metabolism in a
postmortem context. The findings can be
expected to support the interpretation of
postmortem toxicology results.
INTRODUCTION
9
REVIEW OF THE LITERATURE
1 Interpretation of Postmortem Forensic
Toxicology Results
A forensic toxicological investigation consists of
three main steps: obtaining the case history and
suitable specimens, performing toxicological
analyses, and interpreting the findings. In a postmortem case, toxicological specimens are
collected at autopsy or external examination and
subjected to chemical analysis, which is a
process of extraction, detection, identification,
and quantitation of the analytes [1,2].
Comprehensive treatises on interpretation
of forensic toxicology results have most recently
appeared by Jones [3], Richardson [4], and
Holmgren [5], but throughout the years the
subject has inspired numerous reviews, essays,
and book chapters [6-15]. Although the
principles are globally applicable, some of the
discussion reflects professional experience,
personal opinions, and local medicolegal
systems of the authors. In the Finnish system,
interpretation of postmortem toxicology results
involves both the forensic toxicologist, who
estimates the relevance of the findings and the
need for further analysis, and the forensic pathologist, who eventually assesses the contribution
of the findings to the cause of death.
Several aspects are considered in the
interpretation. First of all, the numerical results
obtained in the laboratory are meaningful only
in context with the individual case and such
background information as acute/chronic
exposure, emergency treatment, and length of
survival [6,8,15]. Besides individual variation,
thought should be given to the site of specimen
collection, the methods of collection and
analysis, findings in the other matrices
investigated, autopsy findings, and possible
postmortem changes [8,10].
Multiple substances are commonly
involved in overdoses, hence the difficulty of
attributing the fatality to any single one.
Whenever several drugs are found, the
possibility of additive effects, synergism, or
antagonism ought to be considered [6].
Especially benzodiazepines (BDZs) and alcohol
10
REVIEW OF THE LITERATURE
are often present in overdoses of other drugs
[16,17]. Moreover, tolerance (and crosstolerance) to drugs or alcohol may have
developed prior to death. Since the extent and
duration of exposure are seldom precisely or
reliably known, concentrations of certain
analytes, e.g. lead, barbiturates, BDZs, and
several drugs of abuse, are not necessarily very
meaningful [6,10,14]. In addition to appreciating
the pharmacodynamic properties of drugs,
knowledge of pharmacokinetics, of drug biotransformation in particular, is essential in
interpreting the results, especially when the
parent compound is either rapidly or polymorphically metabolized or is not readily
detected. Yet another phenomenon to be
considered is idiosyncrasy: although most
people react to a drug predictably, a few will
react differently [6].
What is not found also influences the
assessment. Negative findings allow exclusion
of many relevant poisons [2], but require
comprehension of the limitations of analytical
methods. Even the most modern equipment is
able to detect only a part of the vast array of
pharmacological agents in use today. Due to the
great number of possible toxicants, general
unknown screening [18] and substance
identification [19] are currently key problems in
state-of-the-art forensic toxicology. Moreover,
once a chemical entity has been detected and
identified, quantitation may prove impossible
because certified reference materials are
unavailable or difficult to obtain [20].
1.1 Blood Samples
Of the matrices available at autopsy, blood is
essential for evaluating whether the deceased
was under the influence of a drug at the time of
death. The specimen of choice for quantitative
purposes is femoral venous blood because it is
the least susceptible to postmortem changes
[3,15,21]. The recommended method of
collection is to draw blood from a ligated or
severed femoral vein into a plastic tube. A
supplementary sample of central blood is often
collected, especially when femoral blood is
unavailable or scant, but should be reserved for
qualitative purposes only [15]. The drug
concentrations in cardiac blood are often higher
than in femoral blood [11,22], which may
facilitate detection. When time has elapsed
between trauma and eventual death, analysis of
subdural and epidural blood clots may provide
information pertaining to the time of injury.
In toxicological case work, blood drug
concentrations are today reliably determined
using mass spectrometry (MS) [19], although
older tools, such as gas chromatography (GC)
coupled with flame ionization detection or with
a nitrogen-phosphorus selective detector remain
valuable in the analysis of alcohols [23] and
nitrogen-containing drugs [24], respectively. To
ensure the quality of analytical results and their
validity in courts of law, method validation,
internal quality assurance, and external
proficiency testing are widely employed in
forensic toxicology laboratories [25-28].
1.1.1 Toxicological Tables
To aid interpretation of the results, therapeutic,
toxic, and lethal concentrations of drugs in
human blood, plasma, and serum have been
compiled into various handbooks [22,29,30],
reviews, and original articles [31-44].
Providing a useful addition to the
traditional handbooks and other printed
references, the internet can be employed to
access many toxicology-related resources,
recently reviewed by Goldberger and Polettini
[45]. These resources include two extensive
compilations of therapeutic and toxic levels of
drugs in biological specimens [46,47].
A major problem with using such reference
values in postmortem toxicology is that postmortem drug concentrations are determined in
hemolyzed whole blood, whereas clinical
studies usually provide information on plasma
or serum concentrations [11]. To extrapolate
postmortem results to the antemortem state,
whole blood/plasma concentration ratios [15]
and whether they stay the same in a
decomposing body [3] should be known. The
compilations most relevant to forensic
toxicology, as discussed by Druid and Holmgren
[48], are therefore those in which the lethal
concentrations in postmortem material are cited
[33,34,37]. Some of these tables also include
statistical
information
on
concentration
distributions in different types of fatalities
[34,37].
However, how concentrations measured
postmortem relate to those measured in life
[10,13,15]
remains
obscure.
Drawing
correlations between these two situations is
therefore not straightforward. Firstly, postmortem blood is not the same as circulating
blood in a living person [13]. Secondly, in a
living body the pharmacodynamic response to a
drug is dictated by the concentration of a free
drug, whereas a postmortem result represents the
sum of the free and protein-bound drug. Thirdly,
peak concentrations of the drug are likely to
have been higher than what is seen postmortem,
since the peak concentration may cause
irreversible damage but not immediate death
[49]. It may take hours for the intoxicated
person to succumb, with the drug being
metabolized in the meanwhile. Blood alcohol
concentration (BAC), for instance, decreases
0.10-0.25‰/h in moderate drinkers and even
faster in alcoholics [50]. There are also instances
where peak drug concentrations have been
reported to be higher postmortem; in two cases
in which intoxication had led to hospitalization
prior to death, higher amitriptyline and
propoxyphene concentrations in blood were
found postmortem than antemortem [20].
Finally, when a drug has one or more chiral
centers, the pharmacodynamic and pharmacokinetic behavior usually differs between the isomers. In the hopes of minimizing the expensive
production of ineffective isomers, avoiding the
side-effects caused by harmful isomers (e.g. (–)thalidomide), and splitting the drug load on an
individual in general, drug development is now
aimed at enantiospecific drugs [51]. When a
drug may be present in toxicological samples
either as a racemate or as an enantiomer, as in
the cases of citalopram and amphetamine,
interpretation of blood concentrations can be
considered confounded by yet another factor,
unless enantioselective analysis has been applied
to the forensic samples.
REVIEW OF THE LITERATURE
11
1.2 Other Matrices
Other common matrices of interest in
postmortem toxicology include urine, liver,
gastric contents, bile, blood clots, and vitreous
humor [15,52]. Muscle tissue, bone marrow, and
hair can be used in severely putrefied cases, and
even larvae feeding on the corpse may be
examined [8,52,53]. In all, alternative matrices
can constitute valuable specimens for
postmortem toxicology, as recently reviewed by
Drummer and Gerostamoulos [52] and Skopp
[15].
Due to site and temporal dependence of
drug concentrations [54,55], the toxicological
results obtained in other matrices differ in
significance from those determined in femoral
blood. A positive finding in urine, for instance,
shows that the detected substance was present in
the body some time before death, but the
physiological effects exerted by the compound
on the body may not be readily deduced from
the concentration in urine [8,15].
Liver is a highly valuable specimen since
many substances are present in higher
concentrations in the liver and are thus more
easily detected than in femoral blood [11,22].
Utilization of hair samples has been recently
recapitulated by Kintz [53]. Hair is of
exceptional value in exhumed bodies, but can
also be used to detect exposure to drugs over a
period of several months prior to death [15].
Detection of a compound in gastric contents
does not necessarily indicate recent uptake, for
drugs can be re-excreted into gastric juices [3].
Vitreous humor is another valuable
specimen in postmortem toxicology. It is a
relatively well-isolated, sterile compartment
protected from trauma and putrefaction, with
drug concentrations typically following the
concentrations in blood with a certain delay
[15]. Glucose, lactate, and potassium are
conveniently determined in vitreous humor [56].
Alcohol concentrations in vitreous humor
closely follow BACs, when the difference in
water content is taken into account [57]. Thus
vitreous humor provides the only other matrix,
besides peripheral blood, capable of yielding a
meaningful quantitative result [11]. Its use as an
alternative specimen is, however, limited by the
small sample size of only 3-6 ml [3].
12
REVIEW OF THE LITERATURE
1.3 Postmortem Changes
The quality of a postmortem specimen is often
poor; it can be watery, putrefied, degraded, or
burned. The stability of drugs in postmortem
samples is another concern [15,52,58]. Changes
in concentration are generally not sufficiently
large to affect interpretation, especially when
femoral blood is used [58], but such drugs as
nitrobenzodiazepines and cocaine may disappear
gradually due to bacterial action [59] and
hydrolysis [60], respectively. It has also been
suggested that, due to reformation of the parent
drug from metabolites [58], e.g. by hydrolysis
of conjugated entities [15], parent drug
concentrations may even increase.
Another type of postmortem change is the
production of ethanol from carbohydrates by
certain microorganisms in a putrefying body or
during storage [61]. To prevent further
conversion in the autopsy sample, refrigeration
and addition of potassium or sodium fluoride to
a final concentration of 1-5% are generally
recommended. Microbial activity may produce
significant ethanol concentrations, in some cases
in excess of 1‰, and a positive BAC should
therefore be verified by analysis of urine or
vitreous humor whenever possible [62].
The most relevant alteration occurring
between death and autopsy is, however, postmortem redistribution, i.e. the migration of
drugs between tissues and blood in a cadaver
[63,64]. Literature on postmortem redistribution
has recently been summarized in a brief review
by Leikin and Watson [11], and the mechanisms
involved have been the subject of a more
extensive review by Pélissier-Alicot et al. [65].
Drugs that undergo postmortem redistribution
are typically lipophilic, weakly basic
compounds with a relatively large volume of
distribution or preferential binding to the
myocardium [21,65,66].
The most important mechanism of
redistribution has been estimated to be drug
diffusion from the gastrointestinal tract, lungs,
and other drug-rich tissues, such as the
myocardium, into surrounding tissues and blood
[67]. Recent ingestion of a large amount of
drugs may result in postmortem diffusion of the
unabsorbed drug from the gastric contents to the
surrounding organs and vessels [65]. The extent
of redistribution depends on the drug
concentration and possible resuscitation
attempts, probably shifting cardiac blood
towards the periphery [55,65], but also on the
length of the delay between death and autopsy
and the conditions during the delay [68].
1.4 Metabolites
In intoxications, a large part of the toxic action
may derive from the metabolites of the
consumed substances. When the metabolite is
pharmacologically active (e.g. amitriptyline/
nortriptyline,
codeine/morphine/morphine-6glucuronide, methanol/formic acid), it may
contribute to death to the same or even to a
greater extent than the parent drug. Knowledge
of metabolite levels is therefore of great
interpretative value in postmortem toxicology.
Quantitative determination of known
metabolites along with the parent drug may
further help to determine the time of intake and
the type of poisoning (acute vs. chronic or
therapeutic exposure [69]), and possibly arouse
suspicions of metabolic anomalies [70].
Qualitative identification of metabolites is often
used to corroborate the finding of a parent drug.
Furthermore, certain metabolites are present in
the body in higher concentrations, thus being
easier to detect than the parent drug. Screening
for metabolites is particularly important when
the suspected parent compound is metabolized
extremely fast (e.g. cocaine or heroin [14]),
is not excreted in urine, or is not readily
detected. Unfortunately, few metabolites are
commercially available [71].
1.5 Alcohol Toxicity
Alcohol (ethyl alcohol, ethanol) is a frequent
finding in postmortem toxicology, with
approximately 400 fatal poisonings attributed to
it annually in Finland [72]. Alcohol was
detected in 47.7% of Swedish fatal poisonings in
1992-2002 [73], and BACs of 0.50‰ or higher
were detected in 50.4% of Finnish fatal drug
poisonings in 2000-2001 [72]. Of all of the
Finnish postmortem cases analyzed for alcohol
in 2000-2004, BACs of 0.20‰ or higher were
detected in 45.5% (Vuori et al., unpublished
results). The frequent involvement of alcohol in
poisonings in general is illustrated by a Finnish
study in which alcohol was found in two-thirds
of patients presenting with acute poisoning to an
emergency department [74].
The BAC level causing death is often cited
as >3.5‰ [42] or ≥4‰ (92mM) [31,33,38], but
lower estimates have also been presented
[34,75]. Depending on the source, the given
value may refer to either a BAC determined
postmortem or a peak BAC estimated to have
caused an irreversible event leading to death.
However, death may ensue already from lower
BACs, especially in alcoholics with a weakened
physiological status (heart disease, malnutrition,
liver cirrhosis, ketoacidosis), as well as when
aspiration of stomach content, postural asphyxia,
or hypothermia is involved [75,76]. Old age and
concurrent CNS depression from other causes
are further factors that may lower the lethal
BAC [76]. Tolerance, however, is also an
important aspect of alcohol toxicity. People have
survived – even driven motor vehicles [77] – at
concentrations much higher than 4‰, with a
BAC of 15‰ (340mM) probably being the
highest reported in a living person [78].
Reported mean and median BACs found in
fatal alcohol poisonings usually range from 3‰
to 4‰ [34,49,79-81]. Cumulative frequency
distributions have also been published [79-81].
The curves in Figure 1 show the cumulative
proportion of fatal alcohol poisonings in which a
certain BAC was found.
1.6 Drug Toxicity
Drugs exert their therapeutic effects by various
mechanisms. Each drug usually has a specific
mechanism of action, which may also mediate
the toxic effects produced by higher
concentrations, but no single mechanism can be
pointed out as the cause of drug toxicity in
general. Toxicity is therefore thoroughly
investigated in the process of drug development,
with each new drug having to pass an extensive
series of preclinical and clinical tests before
being approved for sale. Even so, virtually all
drugs on the market have some degree of
toxicity. Postmarketing research on drug toxicity
is therefore conducted as well, with the purpose
of further improving drug safety. Identification
of particularly toxic drugs can lead to
restrictions or recommendations intended to
REVIEW OF THE LITERATURE
13
Figure 1. Cumulative frequency distribution of blood alcohol concentrations in fatal alcohol
poisonings in Finland in 1983-1985. Modified from a report by Vuori et al. [80].
prevent future adverse events. Restricted
prescription of barbiturates since the late
1960s, for instance, was a successful measure
in reducing barbiturate poisonings [82],
and similarly, dispensing regulations for
propoxyphene were tightened in the 1980s, after
many reports of propoxyphene-related fatalities
[83-85]. The conventional method of assessing
acute lethal toxicity, i.e. determining the amount
of drug required to kill 50% of a given
population (LD50), is obviously not appropriate
for people. Various methods have thus been
developed for assessing acute drug toxicity in
humans in overdose situations, usually by taking
an epidemiological approach.
1.6.1 Fatal Toxicity Index
The frequency of poisonings caused by a drug
depends to a large extent on its availability and
inherent toxicity [86,87]. Controlling for drug
availability should thus enable us to compare the
degree of inherent drug toxicity for man. From a
forensic toxicologist’s point of view, a practical
measure of relative drug toxicity is the fatal
toxicity index (FTI). It is calculated by relating
the number of fatalities attributed to a drug over
14
REVIEW OF THE LITERATURE
a certain time period and area to the
consumption of the drug over the same period
and area. Consumption can be measured either
by number of prescriptions, kilograms, or
defined daily doses (DDDs) dispensed, with
DDD being the assumed average maintenance
dose per day for a drug used for its main
indication in adults [88]. This approach has been
used to compare both individual drugs and
classes of drugs, often in the UK [86,87,89-97].
It must be noted, however, that the FTIs
calculated using prescription data are valid for
prescription medications only and cannot be
applied to over-the-counter drugs such as
aspirin, paracetamol (acetaminophen), and
ibuprofen. This limitation is not an issue when
consumption data in DDDs or kilograms is
available.
Death rate per millions of prescriptions was
used to demonstrate that nitrazepam is a safer
hypnotic than barbiturates [89,91]. By
estimating BDZ death rates per diazepam
equivalents, temazepam and flurazepam
appeared more toxic than average hypnotics, and
diazepam more toxic than average anxiolytics
[98]. The latter finding, however, was attributed
to the concurrent use of alcohol. Tricyclic drugs
as a group had a FTI (expressed as deaths per
million prescriptions) higher than the average
for all the drugs studied [86,92].
Among antidepressants, tricyclic antidepressants (TCAs) were associated with a
higher FTI and antidepressants introduced after
1973 with a lower FTI than the average for all
antidepressants [86,93]. Mianserin, on the other
hand, was found early on to have a lower FTI
than the TCAs [86,87,94,99], and the selective
serotonin reuptake inhibitors (SSRIs) were later
shown to cause significantly less fatal
intoxications than the TCAs in proportion to
their consumption [17,100-102]. Moreover,
most SSRI fatalities appear to involve coingestion of other substances [16]. Among the
TCAs, amitriptyline, desipramine, doxepin, and
dothiepin have been estimated to be the most
toxic in several FTI studies [17,92,93,99].
Among the newer antidepressants, a higher FTI
has been reported for venlafaxine than for the
other serotoninergic agents [96].
1.6.2 Other Measures of Toxicity
Toxicity indices may also be calculated for
ranking purposes by substituting the number of
mentions on death certificates for the number of
deaths attributed to the drug [103]. Drug toxicity
has also been estimated by comparing attempted
and completed suicides [104]. Besides fatalities,
overdose-related hospital admissions, clinical
representation, and outcome have been
compared, as have seriousness of side-effects
and possibility of drug interactions [105-107].
Yet another measure is related to the therapeutic
index; de Jonghe and Swinkels classified
antidepressants as ‛safe’ or ‛less safe’ according
to whether the amount of drug prescribed for
two weeks’ therapy can prove fatal. They
considered an antidepressant safe when a twoweek supply was not life-threatening in
overdose [105,106]. TCAs would therefore be
considered ‛less safe’ since significant
symptoms can result from ingestion of three to
four times the therapeutic daily dose, with a
lethal dose only eight to ten times greater
[16,108].
Although depressed patients should be
allowed only limited access to antidepressant
drugs, as pointed out on several occasions
[16,109,110], a reported fatal poisoning caused
by citalopram alone involved ingestion of a dose
equal to more than a six-month therapeutic
supply [111]. In this case, the citalopram
concentration determined in femoral blood was
approximately 40 times greater than the highest
concentration considered therapeutic [37].
In a British study, median fatal
concentrations of certain drugs, namely antidepressants, hypnotics, and volatile anesthetics,
were shown to correlate with their aqueous
solubility [112]. Inversely, drugs with high FTIs
were reported to show more lipophilic character
than the least toxic drugs. These drugs were
thought to act via a nonspecific mechanism
disrupting physiological processes in the lipoprotein membranes of the brain [112]. However,
this approach was not applicable to nonnarcotic
poisons which exert their lethal effects by very
specific mechanisms. Nonspecific membranestabilizing activity, also termed a quinidine-like
effect, was nevertheless offered as a cause of
fatal poisoning and a mechanism of additive
interactions [113]. Correlations were also been
reported between antidepressant rank orders by
FTI and LD50 in mice [95,100,114].
1.6.3 Sources of Bias in Toxicity Indices
Toxicity index measures do not necessarily
directly represent the inherent toxicity of a drug
but can also be related to the indications and
manner of use. Antidepressants, for instance, are
consumed by people who have suicidal
tendencies and who are thus at an elevated risk
of death compared with nondepressed
individuals [115]. It has also been suggested that
prescribing practices may result in biased
perceptions of toxicity differences between antidepressants since dual-action antidepressants,
such as venlafaxine, are prescribed to patients
already at a relatively high risk of suicide, i.e.
patients whose depression has been resistant to
narrow-spectrum serotonergic agents or whose
initial symptoms suggest use of something other
than a SSRI as a first-line drug [116,117].
Furthermore, some antidepressants may have
several indications besides depression, e.g.
obsessive-compulsive behavior, bulimia, and
nocturnal enuresis, conditions which generally
REVIEW OF THE LITERATURE
15
are associated with lower risk of drug abuse or
self-harm than depression. Yet another
consideration is that TCAs may actually be
prescribed in subtherapeutic doses because in
therapeutic doses, side-effects are common and
may lead to noncompliance. For these reasons,
TCAs may be ineffective in treating depression,
whereas SSRIs, due to their mild side-effect
profiles, can be taken in therapeutic amounts
and with good compliance, resulting in
improvement of the condition, and thus, a lower
risk of suicide [109,118].
On the other hand, fatal drug poisonings
are not always suicides, but may also occur by
accident, and even an intentional overdose can
lead to an unintentional death. A Finnish study
reported 26% of unintentional deaths among
fatal drug poisonings, with 76% of fatal
antidepressant poisonings being suicides [102].
Similarly, the proportion of suicides did not
exceed 80% in a Danish study on lethal
antidepressant intoxications [119]. Another
behavioral characteristic affecting poisoning
statistics is that some prescription drugs,
especially those with euphorigenic or anxiolytic
properties, are abused more often than others,
while some of the prescribed and acquired
medications are never ingested. Fast-acting
drugs with short-term effects have been
estimated to have a higher abuse potential [120].
These aspects must be kept in mind when
compiling and interpreting toxicity index data.
2 Pharmacogenetics
Drug response as well as absorption, disposition,
metabolism, and excretion are affected by
individual variation. Pharmacogenetics, the
study of the heritable component of this
variation, is a rapidly expanding field of science;
in the 2000s, hundreds of review articles have
appeared on the subject [for recent reviews, see
121-128]. The increasing research interest is
explained by the powerful new tools available
for DNA analysis and by the observations that
even a single nucleotide change in a gene may,
due to altered dose-response relationships, lead
to clinically significant differences between
individuals. More specifically, expression of a
functionally altered protein product or an altered
16
REVIEW OF THE LITERATURE
amount of a normal product can be expected to
increase the likelihood of adverse drug reactions
(ADRs) or of inadequate therapeutic outcome at
normal drug dosages. When two or more
variants of the same gene locus occur at a
frequency of 1% or higher in a population, the
gene is termed polymorphic [129]. Polymorphisms may affect pharmacodynamics, e.g.
the structure of receptors, ion channels, and
carrier proteins [121,130], but most of the
currently available information concerns
pharmacokinetics, especially enzymes involved
in drug metabolism.
2.1 Drug-Metabolizing Enzymes
Drug-metabolizing enzymes (DMEs) act as a
defense mechanism against foreign compounds.
These enzymes have evolved in animals during
the course of interaction with plants [131]. Most
exogenous substances enter the body via the
gastrointestinal tract, where they are absorbed
into the portal circulation, which transports them
to the liver. DMEs are predominantly located in
the liver, enabling efficient first-pass
metabolism of foreign entities and thus
constituting an important factor in the
bioavailability of ingested drugs. Their bodyprotecting function comprises rendering a
compound more easily excretable; in Phase 1
reactions, DMEs unmask or incorporate a polar,
often oxygen-containing function in the
compound, thereby creating a site for a Phase 2
reaction, which conjugates the compound with a
highly polar agent. Genetic variation in DMEs
makes it difficult to predict dosage, efficacy, or
safety of a drug. Patients with an abnormal
enzymatic status are prone to be predisposed to
ADRs (Table 1) [132].
An individual’s response is also affected by
several other factors, including age, gender, diet,
concurrent medication, general health, lifestyle,
and even education and socioeconomic status
[133]. In pursuit of personalized medicine,
phenotyping panels have been devised for the
most common polymorphic DMEs [134-137].
2.1.1 Cytochrome P450 System
The superfamily of cytochrome P450 (CYP)
enzymes is the most important metabolic system
in Phase 1 [138]. These enzymes are heme-
Table 1. Possible consequences of abnormal enzymatic status depending on the properties of
substrate drugs and expected metabolites involved in the reaction.
Enzymatic
Substrate
Expected product
Consequence
status
Normal
+ Normal dose of
Æ Normal metabolite
Æ Expected response
enzyme in
drug
(toxic effects rare)
normal
quantities
Lack of
functional
enzyme,
inhibited
enzyme
Excess of
enzyme
+ Active parent drug
Æ Inactive metabolite
+ Toxic parent drug
Æ Detoxified metabolite Æ Toxic effects
+ (Pro)drug
Æ Active metabolite
Æ Lack of response,
undertreatment
+ Active parent drug
Æ Inactive metabolite
Æ Lack of response,
undertreatment
+ Active parent drug
Æ Toxic metabolite
Æ Toxic effects
+ (Pro)drug
Æ Active metabolite
Æ Excessive response
containing proteins that show a characteristic
absorption maximum at 450 nm in reduced
microsomes treated with carbon monoxide. CYP
enzymes are located in the endoplasmic
reticulum and expressed mainly in the liver, but
also in extra-hepatic tissues such as the intestine,
brain, and lung [128,139]. There are 57
sequenced human CYP genes and 58 pseudogenes, the latter having mutated to such an
extent that all variants have lost the ability to
produce functional enzymes [140].
Human CYP forms are divided into
families and subfamilies on the basis of
similarities in amino acid sequence. The
individual isozymes are very versatile and are
often capable of catalyzing several types of
oxidative reactions [138]. There is increasing
evidence that CYPs are involved in chemical
carcinogenesis and chemical-induced toxicity
through metabolic activation, i.e. formation of
reactive metabolites [139]. Families CYP1,
CYP2, and CYP3 participate extensively in drug
metabolism, with three of the major isozymes
(CYP2C9, CYP2C19, and CYP2D6) being polymorphic to a clinically significant degree [125].
The following sections focus on research
involving the hepatic enzymes CYP2D6 and
CYP2C19 and the polymorphic genes CYP2D6
and CYP2C19 encoding them.
Æ Excessive response
CYP2D6
The CYP2D6 enzyme was originally called
sparteine
hydroxylase
or
debrisoquine
hydroxylase due to two separate clinical trials
where some of the subjects experienced ADRs
because they were unable to hydroxylate these
compounds [141,142]. CYP2D6 has been
estimated to participate in the metabolism of
more than 70 common drugs and 20-25% of all
drugs in clinical use [125,128,138]. Most
importantly, CYP2D6 metabolizes many
psychoactive substances such as several
antidepressants (TCAs, SSRIs, mianserin,
mirtazapine,
venlafaxine)
and
various
antipsychotics
(haloperidol,
perphenazine,
risperidone, thioridazine). CYP2D6 substrates
also include opioids (codeine, dextromethorphan,
ethylmorphine,
methadone,
oxycodone, tramadol), β-blockers (metoprolol,
propranolol, timolol), type 1 antiarrhythmics
(flecainide, mexiletine, propafenone), and
methylenedioxymethamphetamine (MDMA, i.e.
‛ecstasy’) [138]. The major reaction types
catalyzed by CYP2D6 appear to be ring
oxidation and O-demethylation. Substrates of
CYP2D6 tend to be basic in character, with a
protonatable nitrogen atom at a distance of
5-7 Å from the site of the oxidative reaction
[143].
REVIEW OF THE LITERATURE
17
Figure 2. Chromosome 22, gene CYP2D6, and the sequence positions of the major CYP2D6
polymorphisms in the nine exons, with adjacent pseudogenes CYP2D7P and CYP2D8P shown.
According to current knowledge, CYP2D6
is the most polymorphic CYP gene [144], with
more than 80 allelic variants documented to date
[145,146]. In humans, the 4.2-kb region
containing the CYP2D6 gene (MIM*124030)
resides on the long arm of chromosome 22
(22q13.1), with two pseudogenes, CYP2D7P
and CYP2D8P, in close proximity upstream
(Figure 2).
In addition to interindividual variation, the
CYP genes show interethnic variation.
Approximately 7% of the Caucasian population
and 1% of Orientals carry a homozygously
defective CYP2D6 genotype (gPM). They
produce no active CYP2D6 enzyme, and thus,
regarding CYP2D6 substrates, exhibit a poor
metabolizer phenotype (PM). The major
nonfunctional (null) alleles *3 (frame shift), *4
(splicing defect), and *5 (deletion of the entire
gene) are responsible for approximately 90% of
gPMs in Europeans [123]. Of the alleles
associated with decreased CYP2D6 activity, *9,
*10, and *17 do not contribute significantly to
drug metabolism in Caucasians [147], whereas
the frequency of newly described allele *41 is
approximately 8% [148]. The functional alleles
*1 and *2 are common in European, African,
and Asian populations, with a combined allele
frequency of ~71%, ~68%, and ~52%,
respectively. Allele *4 is relatively frequent in
Europeans (20%), while alleles *10 and *17 are
18
REVIEW OF THE LITERATURE
common in East Asian (38-70%) and Black
African (24%) populations [147].
Individuals carrying two functional copies
of CYP2D6, i.e. genotypically extensive
metabolizers (gEMs), are predicted to have an
extensive metabolizer phenotype (EM). Since
the range of metabolic ratios (MRs) associated
with one functional gene generally overlaps with
that observed for gEMs [149,150], the carriers
of one functional gene are typically also
considered EMs [127,128]. A nonfunctional
CYP2D6 allele in combination with a
functionally deficient allele [128,151,152] is
currently considered to predict an intermediate
metabolizer phenotype (IM). Furthermore,
inhibitors or high-affinity substrates of
CYP2D6, such as quinidine, paroxetine, or
fluoxetine, may temporarily convert gEMs to
IMs or PMs, thus constituting a source of
clinically significant drug interactions [128].
Expression of CYP2D6, unlike many other
CYP genes, is noninducible, but during human
evolution its metabolic capacity has been upmodulated by duplication and multiduplication
of the entire gene. Some individuals may
therefore carry extra copies of CYP2D6. Three
or more copies of CYP2D6, constituting an
ultra-rapid metabolizer genotype (gUM), is
considered to lead to ultra-extensive production
of CYP2D6 protein, thus predicting an ultrarapid metabolizer (UM) phenotype [153].
However, the sensitivity of genotyping to
predict the UM phenotype is low; common
estimates of the frequency of duplication in
European UMs range from 10% to 30%
[128,132]. For instance, a duplicated copy of
CYP2D6 has been found in 4 of 18 UMs (22%)
phenotyped with sparteine [150] and in 14 of 64
UMs (23%) phenotyped with debrisoquine
[154]. Moreover, the phenotypes exhibited by
gUMs and gEMs overlap [128,152].
Probe drugs used in CYP2D6 phenotyping
include debrisoquine, sparteine, and dextromethorphan [124]. In genotyping, the polymorphic positions of the CYP2D6 gene are not
detected directly in one step because of high
sequence homology with neighboring pseudogenes [155]. Therefore, a CYP2D6-specific
fragment is first amplified by polymerase chain
reaction (PCR) in parallel with two other
possible fragments identifying a deleted
CYP2D6 gene (*5) and a (multi)duplicated one
(*1xN, *2xN, *4xN, *10xN, *35xN). The polymorphic positions are then identified using such
techniques as restriction fragment length polymorphism (RFLP) analysis [155], multiplex
single-base extension reaction (e.g. SNaPshotTM)
[156], real-time fluorometric melting point
analysis [157], pyrosequencing [158], and oligonucleotide microarray technology (‛gene chips’)
[151,159].
CYP2C19
The CYP2C19 polymorphism was originally
discovered as a deficiency in (S)-mephenytoin
4'-hydroxylation [160]. In addition to
mephenytoin, omeprazole has been used as a
probe drug in CYP2C19 phenotyping [161].
Other CYP2C19 substrates include antidepressants
(TCAs,
SSRIs,
mianserin,
moclobemide, venlafaxine), antipsychotics
(clozapine, perphenazine), BDZs (diazepam,
flunitrazepam,
temazepam),
β-blockers
(metoprolol, propranolol), several proton pump
inhibitors, dextromethorphan, phenytoin, and
(S)-warfarin [138]. Substrates of CYP2C19 are
often weakly basic in character and have two
hydrogen bond donor/acceptor atoms. There are
typically seven or eight chain atoms between the
site of metabolism and the site forming a
hydrogen bond. The major reactions catalyzed
by CYP2C19 include dealkylation and ring
hydroxylation [143].
CYP2C19 is a large gene of more than 90
kb, including nine exons, on chromosome
10q24.1-q24.3 (MIM*124020). Approximately
2-3% of the Caucasian population [162] and
14-21% of East Asians [161] are CYP2C19
gPMs. Allele *2 (splicing defect) is the only
common defective mutation in Caucasians
(15%) and Blacks (17%). In addition to a high
frequency (30%) of allele *2 (splicing defect),
allele *3 (premature stop codon) is present in the
Chinese at a frequency of 5% [161]. The
mutations corresponding to these alleles are
681G>A in exon 5 [163] and 636G>A in exon 4
[164], respectively. They are readily detected by
first amplifying a fragment covering exons 4 and
5 and then applying one of the various
techniques mentioned above (section CYP2D6).
Of the CYP2C19 genotypes commonly observed
in Caucasians, *1/*1 is considered to predict an
EM, *1/*2 an IM, and *2/*2 a PM of CYP2C19
substrates [126,165].
2.2 Studies on Drug Metabolism
Human liver microsomes have been used
extensively in studying metabolic polymorphisms, but the ‛well-characterized’ human
liver microsomes used in in vitro studies may
contain enzyme variants that metabolize well the
probe drug but not the drug being investigated
[166]. Therefore, in vitro studies are not
reviewed in detail in the following sections,
focusing instead on the role of CYP enzymes in
the metabolism of the opioid drug tramadol and
TCAs, especially amitriptyline.
2.2.1 Tramadol Metabolism
Tramadol is administered as a racemic mixture
of (+)- and (–)-trans-tramadol, i.e. (R,R)- and
(S,S)-tramadol, respectively. CYP2D6 has been
shown to convert tramadol to O-demethyltramadol (M1) in vitro [167,168] and in vivo
[169]. The formation of (+)-M1 is important for
the hypoalgesic effect because it has a higher
affinity for opioid receptors than the parent drug
[170]. Demethylation of tramadol in vitro is
stereoselective, with (+)-tramadol being
preferentially O-demethylated by CYP2D6 and
(–)-tramadol N-demethylated by CYP3A4 [167].
REVIEW OF THE LITERATURE
19
HO
HO
HO
CYP3A4
CYP3A4?
NHMe
NMe2
OMe
OMe tramadol
CYP2D6
M2
CYP2D6?
HO
CYP3A4?
CYP3A4?
NHMe
NMe2
M1
M3
CYP2D6?
HO
HO
OH
NH2
OMe
OH
M5
NH2
OH
M4
Figure 3. Outline of main pathways of tramadol metabolism in Phase 1, starting from (R,R)tramadol, i.e. (+)-trans-tramadol, the isomer with the highest affinity for the µ-opioid receptor.
Cyclohexyl oxidation is not shown.
Apparently, the N-demethylation product
N-demethyltramadol (M2, nortramadol) is
further N-demethylated to N,N-didemethyltramadol (M3) by CYP3A4 and O-demethylated
to O,N-didemethyltramadol (M5) by CYP2D6,
possibly followed by formation of O,N,N-tridemethyltramadol (M4) from M3 via CYP2D6
as well as from M5 via CYP3A4 (Figure 3)
[171]. At low tramadol concentrations, in vitro
M1 formation predominates, while M2 is the
major metabolite at higher concentrations [168].
2.2.2 Amitriptyline Metabolism
Metabolism of TCAs is well known [for
reviews, see 123,172], for it was the subject of
intensive research even before the discovery of
CYP genes. In early studies, aliphatic ring
hydroxylation of both amitriptyline [173,174]
and nortriptyline [175-177] in vivo correlated
with
polymorphic
4-hydroxylation
of
debrisoquine, whereas N-demethylation of
amitriptyline did not [178]. The 2-hydroxylation
reactions of imipramine [179] and desipramine
[180] have also been suggested to be under the
same genetic control as sparteine hydroxylation.
In parallel with amitriptyline metabolism,
N-demethylation of imipramine to desipramine
does
not
cosegregate
with
sparteine
polymorphism [179].
20
REVIEW OF THE LITERATURE
Nortriptyline is the N-demethylated
metabolite of amitriptyline, but also a drug on its
own. Studies on nortriptyline metabolism are of
great relevance here because nortriptyline
formation is quantitatively the most important
pathway in amitriptyline metabolism [173], with
(E)-10-hydroxyamitriptyline (EHAT) formed to
a lesser extent.
The major metabolite of nortriptyline is
(E)-10-hydroxynortriptyline (EHNT) [176], or
more precisely, the (–)-enantiomer of EHNT
[181]. The enzymes mediating (Z)-10-hydroxymetabolite formation are not known, but
(Z)-10-hydroxyamitriptyline
(ZHAT)
and
(Z)-10-hydroxynortriptyline (ZHNT) have been
detected in vitro [182] and in vivo [181].
Nortriptyline is further demethylated to
N-demethylnortriptyline (NNT) (Figure 4).
In vivo, the stereoselective formation of
(–)-EHAT and (–)-EHNT in particular has been
shown to depend on the activity of CYP2D6
[181]. In amitriptyline demethylation to
nortriptyline, several enzymes have been
implicated, namely CYP2C19, CYP3A4,
CYP1A2, and CYP2D6 [183,184]. The results
suggest a dominant role of CYP2C19 at
therapeutic concentrations and involvement of
CYP3A4 at higher concentrations.
NHMe
NMe2
CYP2C19
CYP2C19
H HH H
amitriptyline
NH2
H HH H
CYP2D6
nortriptyline
H HH H
NNT
CYP2D6
NMe2
NHMe
CYP2C19
HO
EHAT
HO
EHNT
Figure 4. Outline of amitriptyline metabolism in Phase 1, with formation of (E)-hydroxymetabolites shown. The major pathway is indicated with bold arrows. N-oxide formation is not
shown.
2.3 Clinical Pharmacogenetics
The discipline of clinical pharmacogenetics is
aimed at individualized drug therapy, primarily
by identifying patients at risk prior to initiating
treatment (improved risk prediction). When the
drug to be prescribed is exceptionally toxic
or expensive, diagnostic phenotyping or
genotyping, in addition to therapeutic drug
monitoring, may help to improve safety and
efficacy, i.e. to avoid ADRs and therapeutic
failure. This will maximize medical and
financial benefits and minimize the burden of
medication both on the individual and on public
health. Furthermore, in nonresponsive patients,
phenotyping or genotyping may allow
differentiation between ultra-rapid metabolism
and noncompliance [185,186].
Phenotyping
typically
involves
measurements in plasma or urine. After giving
the patient a single oral dose of a probe drug, the
concentrations of the unchanged drug and a
relevant metabolite are analyzed, and the
obtained MR is compared with a reference value
or distribution determined in a large population.
The metabolism of a probe drug cannot,
however, accurately represent the metabolism of
another drug because several enzymes are
typically involved in the metabolism of a
drug, and the probe drug and the drug to be
prescribed may eventually behave differently
[166].
Genotyping offers several advantages over
phenotyping: the patient is not exposed to probe
drugs; drawing one blood sample takes little
time; genotyping can also be carried out postmortem, when clinical phenotyping is no longer
an option; and genotyping is very specific, with
no interference from comedication. On the other
hand, the latter is also a disadvantage since
interactions arising from comedications are not
taken into account.
In evaluating the concordance between
tramadol metabolism, dextromethorphan phenotype, and CYP2D6 genotype, only a modest
correlation was found between the tramadol/M1
plasma ratio and the urinary dextromethorphan/
dextrorphan ratio in general, but when the
subjects were segregated according to the
number of functional CYP2D6 genes, a much
stronger relationship was observed in gEMs
[187]. The impact of the CYP2D6 genotype on
10-hydroxylation of nortriptyline [188-191] and
amitriptyline [192], and the effect of the
CYP2C19 genotype on N-demethylation of
amitriptyline [192,193] have also been
examined in volunteers and psychiatric patients.
The nortriptyline/10-hydroxynortriptyline ratio
was shown to be influenced by CYP2D6 geno-
REVIEW OF THE LITERATURE
21
type and gender in one study [188], whereas in
another, age and gender as factors did not reach
statistical significance, with only the number of
mutated CYP2D6 alleles being significant [191].
Theoretically, PMs are at an elevated risk
of developing excessive plasma concentrations
of certain drugs, for instance, of nortriptyline or
desipramine, when these are given as such or are
formed from amitriptyline or imipramine,
respectively. Such instances have in fact been
documented in several case reports [185,194196]. Furthermore, a German study recently
found that gPMs were overrepresented among
28 patients reported to suffer from ADRs after
taking CYP2D6-dependent antidepressant drugs,
with an observed frequency of 29% compared
with a frequency of 7% in a random German
population. The same study also genotyped 16
nonresponders and found that duplication of
CYP2D6 was overrepresented, with an allele
frequency of 12.5% vs. 1.8% in a general
German population [132].
ADRs are, however, relatively rare,
probably because most drugs can be
metabolized by several enzymes, so that when
one is not fully active, complementary pathways
may compensate, thus preventing harmful
accumulation [187,192]. For instance, no
evidence of an increased ADR rate was found in
gPMs treated with fluoxetine or nortriptyline
[197]. Nevertheless, on the basis of advanced
study settings and calculations, preliminary
genotype-based dose recommendations for
certain antidepressants have been published
[126,165,198]. Furthermore, since CYP2D6inhibiting comedication may convert EMs to
PMs, e.g. when paroxetine is combined with
desipramine [199], it may also constitute a
favorable interaction by converting an
unresponsive UM to a responsive patient.
2.4 Postmortem Pharmacogenetics
Even before the advent of postmortem genotyping, the possibility of a defective CYP2D6
genotype leading to death was discussed in a
case report presenting two fatal poisonings
involving imipramine and desipramine. Chronic
accumulation of imipramine and desipramine,
particularly of desipramine, was suspected since
very low imipramine/desipramine ratios were
22
REVIEW OF THE LITERATURE
found. The patients had been comedicated with
thioridazine and chlorpromazine, both of which
inhibit the CYP2D6 enzyme responsible for
desipramine metabolism [138]. However,
CYP2D6 is also involved in the metabolism of
thioridazine and chlorpromazine, and high
concentrations of imipramine and desipramine
can competitively inhibit CYP2D6. The
possibility of a drug interaction was therefore
also considered [200].
In 1999, CYP2D6 genotyping was
demonstrated to be feasible using autopsy blood,
with 22 suspected overdose fatalities and 24
controls successfully genotyped for CYP2D6
alleles *1, *3, and *4. No gPMs were found
among the overdose cases, but CYP2D6
inhibitors were present in eight cases. However,
the cases were not preselected according to
known CYP2D6-catalyzed reactions, and the
relevance of the investigated metabolic reactions
to CYP2D6 was not discussed. Furthermore, no
MRs allowing comparison between genotypes
were calculated [201].
A case report of a toddler, deceased at the
age of two years and genotyped for CYP2D6
postmortem, was published in 2000. The cause
of death was determined as dextromethorphan
poisoning following a therapeutic ingestion of
cough medicine. Although the dextromethorphan/dextrorphan ratio of 2.5 suggested
slow O-demethylation, a reaction catalyzed by
CYP2D6, the CYP2D6 genotype was that of an
EM. No concurrent analytes were found in
general drug screening [202].
In another case reported in 2000, the death
of a child was investigated in depth when high
blood concentrations of both fluoxetine and
norfluoxetine were found in postmortem
toxicology. The parents were first accused of
homicide, but were vindicated by the results of
genotyping, with DNA analysis revealing a
homozygously defective CYP2D6 genotype. The
interpretation of the results was therefore
chronic accumulation of fluoxetine and
norfluoxetine. In fact, the nine-year-old boy had
been prescribed fluoxetine at 100 mg/day, a
dose five times the DDD, and his medical
history indicated several hospitalizations due to
seizure episodes. The parents eventually filed a
malpractice suit against the neurologist who had
prescribed fluoxetine at an exceptionally high
dosage and yet failed to recognize the symptoms
of toxicity in the patient [79,203].
In a Swedish series of 242 fatal drug
intoxications, both CYP2D6 and CYP2C19
genotypes were determined and the genotype
distributions compared with those in 281
controls (blood donors). The CYP2C19 genotyping results in the autopsy cases were similar
to those in the blood donors, but the prevalence
of CYP2D6 gPMs in fatal intoxications was
found to be lower (4.7%) than expected from the
frequencies of these genotypes in the blood
donors (8.5%), leading the authors to suggest
that intoxication victims might exhibit a lower
frequency of CYP2D6 gPMs than the general
population [204]. No explanation has been
offered for this observation.
In 15 fatalities involving oxycodone [205]
and in 21 involving methadone [206], CYP2D6
genotyping has been used to aid interpretation of
postmortem toxicology results, although without
calculating the relevant MRs.
In 53 Swedish autopsy cases involving
citalopram, genotyping of CYP2D6 and
CYP2C19 was combined with enantioselective
analysis of citalopram enantiomers by chiral
liquid chromatography. No gPMs were found
for CYP2C19 and only 2 gPMs (3.8%) for
CYP2D6. The authors suggested that
pharmacokinetic interactions are likely to play a
more important role than pharmacogenetic
deficiencies in drug metabolism [207].
In summary, postmortem pharmacogenetics is a relatively new area of research; the
extent to which it will contribute to medicolegal
investigations remains to be seen.
3 Drug-Alcohol Interaction
Drug-alcohol interactions have been widely
investigated in animals and in clinical settings,
especially with regard to psychomotor
performance, but studies on human postmortem
material are scarce. Alcohol is, however, a
frequent finding in fatal poisonings. For
instance, alcohol was detected in 47.7% of
Swedish fatal poisonings in 1992-2002 [73], and
BACs of 0.50‰ or more were detected in 50.4%
of Finnish fatal drug poisonings in 2000-2001
[72]. An overview of the current knowledge of
the mechanisms of drug-alcohol interactions will
be provided below and research on postmortem
material summarized. Although most studies on
drug-alcohol interactions relate to animals or
living persons, clinical studies pertaining to
psychomotor skills are beyond the scope of this
review.
3.1 Alcohol Effects and Anesthetic Action
A pharmacologically active drug typically has
one or more known mechanisms and sites of
action, e.g. binding directly to a specific
proteinaceous receptor or enzyme. With regard
to alcohol, while its effects are well known, the
mechanism is less clear. Knowledge of this
mechanism is, however, crucial in elucidating
the interaction between drugs and alcohol. Many
aspects of ethanol, recently reviewed by Jones
[208], differ from medicinal drugs. Ethanol is
often ingested in large quantities, has nutritional
value, and is evenly distributed throughout the
body. The molecular structure of ethanol is
small and simple, with several potential
physiological targets. In alcohol-related
fatalities, anesthesia and CNS depression
leading to respiratory failure are considered the
mechanisms of major importance [208].
General anesthesia can be produced by a
wide variety of chemical entities, including
alcohols, alkanes, ketones, ethers, and inert
gases, but the mechanism of action remains
largely unresolved. An early effort to explain it,
the Meyer-Overton hypothesis, based on the
independent but similar findings of Meyer in
1899 and Overton in 1901, states that there is a
correlation between anesthetic potency and oil
solubility (i.e. hydrophobicity) of a compound
[209]. Anesthesia was then proposed to occur
when a critical drug concentration is achieved in
the cell membrane, but the intramembrane
volume was later found to be a better parameter
than the intramembrane concentration for equal
degrees of narcosis produced by different agents
[210]. In the 1970s, the anesthetic site of action
was concluded to be located within the neuronal
membranes [211], and the physiological site of
action of general anesthetics was thought to
involve proteins rather than the lipid region of
the membrane [212]. This proposition was based
REVIEW OF THE LITERATURE
23
on the observed correlation of anesthetic
potency and the n-octanol/water partition
coefficient [212].
The potency of structurally diverse
anesthetic agents was thereafter shown to
correlate with their ability to partition into the
phospholipid bilayer (instead of oil) [213].
Furthermore, the membrane-disordering potency
of various aliphatic alcohols was found to be
closely related to their oil/water partition
coefficients and thus to their membrane
solubilities [214]. Aqueous solubility was also
offered as a theoretical basis for the synergism
observed in barbiturate-ethanol poisonings
[79,215]. Nevertheless, the protein theory
eventually gained ground when the activity of a
pure soluble protein (firefly luciferase) was
shown to be inhibited by general anesthetics at
concentrations which induce anesthesia [216].
Disordering or fluidization of the lipid
membrane is therefore no longer considered to
explain the commonly observed effects and
toxicity of alcohol [217,218]. However, the
membrane-related effects of alcohols and
anesthetics are still being researched to explain
the Meyer-Overton correlation [209,219].
In current research into the mechanism of
general anesthesia, and therefore also into the
mechanism of alcohol effects, proteins –
membrane-embedded receptors, in particular –
are favored over the lipid bilayer as probable
anesthetic targets in the CNS. Members of the
ligand-gated superfamily of ion channels, for
instance, seem sensitive to general anesthetics
[217,218]. This superfamily includes the
receptors for the inhibitory neurotransmitters
glycine and γ-aminobutyric acid (GABA).
Within these receptors, putative sites of alcohol
and volatile anesthetic action have been
discovered, as reviewed by Mihic and Harris
[220] and Harris et al. [221].
3.1.1 γ-Aminobutyric Acid Receptor Type A
GABA is the major inhibitory messenger in the
vertebrate CNS, and the GABA type A receptor
(GABAA) has been established as a prime
anesthetic target [217]. General anesthetics,
including alcohol, potentiate the GABAmediated inhibition of neuronal transmission by
binding to a specific modulatory site in the
24
REVIEW OF THE LITERATURE
GABAA receptor, prolonging the channel open
time and thereby enhancing the flow of chloride
ions into the cell [217,220,222]. As a result, the
neuronal excitability is reduced more than by
GABA alone, which may lead to incoordination,
sedation, and even anesthesia, typical of mild to
moderate or severe alcohol intoxication [220]. In
moderate drinkers, BACs above 2.0‰ cause
hypnotic and anesthetic effects [222]. Lower
concentrations of alcohol cause sedative and
motor-incoordinating effects, which seem to
involve the GABAA system. Anesthetic
concentrations also seem to potentiate GABAA
receptor responses, but possibly with a different
mechanism [223].
The GABAA receptor (Figure 5) is a large
protein consisting of five subunits with different
specificities and sensitivities to modulatory
agents such as BDZs, barbiturates, alcohols,
neurosteroids,
and
volatile
anesthetics
[220,221]. This is currently believed to
constitute the physiological basis of interaction
between alcohol and BDZs or barbiturates,
although alcohol is known to affect the function
of several brain receptors and enzymes, e.g.
acutely
inhibiting
N-methyl-D-aspartate
(NMDA) receptors of glutamate [221].
Development of tolerance is typical of GABAA
substrates, and evaluating concentrationresponse relationships, including acute toxicity,
and interactions with other CNS-affecting agents
is therefore difficult. Fatal poisonings by BDZs
are, however, known to predominantly occur in
combination with other CNS depressants,
usually alcohol [22,98,225].
3.2 Animal Studies
The interaction of ethanol with other CNSdepressing substances has been investigated in
animals in terms of psychomotor performance,
sleep time, and lethality, with the latter being the
most relevant to this study. The effects of
ethanol on drug lethality have been examined in
mice and rats. In one study, oral ethanol up to
4.0 g/kg had no effect on the lethality caused by
chlordiazepoxide in mice, whereas 2 g/kg
reduced the LD50 of pentobarbital by 13%
and 4 g/kg by 41% [226]. In rats, ethanol in
sedative doses was not – contrary to the study
hypothesis – observed to increase lethality after
Figure 5. Schematic illustration showing the pentameric structure of a GABAA receptor
with suggested binding sites for γ-amino butyric acid (GABA), ethanol, barbiturates,
benzodiazepines, and neurosteroids. Modified from reviews by Mihic and Harris [220] and
McKernan and Whiting [224].
propoxyphene overdoses [227]. However, as
doses are often reported instead of BACs and as
the pharmacokinetics of alcohol in animals may
differ from that in people, the results of animal
studies are not directly generalizable to humans
and will not be discussed in more detail here.
3.3 Postmortem Studies
Alcohol is often found in drug-related fatalities
[72], especially in accidental antidepressant
poisonings [119]. In Frey et al. [17], for
instance, fatal citalopram intoxications occurred
only in combination with alcohol. Although the
role of drug-alcohol interaction in fatal
poisonings has often been discussed, empiric
evaluation using quantitative measures on
postmortem material has been carried out on
only a few occasions. The material consisted of
toxicologically examined cases in which a drug
was found in postmortem blood either alone or
together with alcohol, and the methods involved
comparing the average (mean or median)
concentrations and the cumulative frequencies
between different types of cases [79,228-230].
The major findings were that when alcohol was
present the concentrations of propoxyphene
[228-230], amitriptyline [229], and barbiturates
[79,229] were lower. The greatest differences
were found in amitriptyline poisonings with and
without alcohol, leading to the interpretation
that amitriptyline potentiates the toxic effects of
alcohol to a relatively large extent [229]. Major
shortcomings in these studies were small sample
size, unknown site and method of blood sample
collection, and lack of statistical analysis, but
these studies, nevertheless, provide useful
examples for modern research of drug-alcohol
interactions in postmortem material.
REVIEW OF THE LITERATURE
25
AIMS OF THE STUDY
Previous observations suggest that fatal poisonings involving both drugs and alcohol may exhibit
analyte concentrations lower than those found in single-substance poisonings. Moreover, clinical
studies have shown the genetic regulation of some DMEs, producing variable drug response.
In this thesis, a retrospective, statistical approach was undertaken to investigate drug-alcohol
interactions and pharmacogenetics in postmortem material in a medicolegal setting. In addition, the
safety of newer antidepressants, especially in combination with alcohol, was evaluated based on
postmortem material.
Specifically, the studies sought to answer the following questions:
Are there correlations between the CYP2D6 gene dose and tramadol metabolite ratios (MRs) in a
postmortem sample population? Can accidental or undetermined tramadol poisonings be attributed to
a genetic inability to produce functional CYP2D6 enzyme? (I)
Do CYP2D6 and/or CYP2C19 gene doses correlate with amitriptyline MRs in a large postmortem
sample population? Can accidental or undetermined amitriptyline poisonings be attributed to a
genetic inability to produce functional CYP2D6 or CYP2C19 enzyme? (II)
Do BACs in fatal poisonings involving certain BDZs differ from those found in cases involving
alcohol alone? Does the amount of the difference depend on the identity of the BDZ? (III)
Do BACs in fatal poisonings involving certain common drugs – i.e. those most often found in fatal
poisonings – differ from those found in cases involving alcohol alone? What are the fatal toxicity
indices of the drugs in question? Do these two measures correlate? (IV)
Do BACs in fatal poisonings involving newer antidepressants differ from those found in cases
involving alcohol alone? What are the fatal toxicity indices for the newer antidepressants? Do these
measures correlate? (V)
Do blood concentrations of common toxic drugs in fatal poisonings involving alcohol differ from
those found in cases involving the drug alone? (VI)
26
AIMS OF THE STUDY
MATERIALS AND METHODS
1 Autopsy cases
All of the cases were autopsied in Finland
during 1995-2003. The cases included in Study I
were autopsied at the Department of Forensic
Medicine, University of Helsinki. All autopsy
samples taken for forensic toxicology were
analyzed at the Laboratory of Toxicology,
Department of Forensic Medicine, University of
Helsinki. The results of chemical analyses and
the eventual death certificate information were
coded into the laboratory database.
1.1 Blood Samples
All concentration data used in these studies were
acquired from femoral venous blood taken at
autopsy into plastic tubes containing a small
amount of sodium fluoride to prevent microbial
degradation. The samples were stored at 4°C
(except during transport) until analysis, after
which they were preserved at –20°C.
1.2 Database
For storing pertinent information on the forensic
toxicology cases, the Laboratory of Toxicology
utilized dBase (Microsoft Corp., Redmond, WA,
USA) until the end of the year 1999. At the
beginning of 2000, Access 2000 (Microsoft
Corp., Redmond, WA, USA) was inaugurated as
the new Laboratory Information Management
System (LIMS). Descriptive information stored
in the database includes name, age, gender, site
of residence, and known occupation. Analytical
entries identify the analyte, the matrix, and the
qualitative (positive/negative) or quantitative
(concentration) result, among others. The codes
denoting the cause of death and the manner of
death are later entered into the database from a
copy of the completed death certificate provided
by the pathologist. In fatal poisonings, the most
important toxicological finding is indicated on
the death certificate by a code stating the
underlying cause of death. The 10th revision of
the International Classification of Diseases
(WHO, Geneva, Switzerland), ICD-10, has been
used for this purpose since 1996. The manner of
death in poisoning cases is generally accidental,
suicide, or undetermined.
Table 2. Therapeutic ranges of selected drugs in
whole blood.
Drug
Therapeutic Reference
range (mg/l)
Amitriptyline
0.04-0.2
[34]
Citalopram
0.01-0.4
[37]
Diazepam
0.1-2.5
[33]
Diltiazem
0.05-0.3
[36]
Doxepin
0.03-0.15
[33]
Levomepromazine 0.05-0.14
[34]
Promazine
0.1-0.4
[36]
Propoxyphene
0.1-0.75
[36]
Temazepam
0.4-0.9
[34]
Tramadol
0.1-0.6
[42]
Zopiclone
0.01-0.1
[36]
2 Analysis of Drug Concentrations
The Laboratory of Toxicology received official
accreditation from the Finnish Accreditation
Service (FINAS) in 1997. A vast array of
validated, stable methods, covering a broad
range of analytes and producing a wealth of
reliable and commensurate data, is used.
Screening and dedicated methods are performed
according to pathologists' request or when
otherwise deemed.
The drug concentrations considered in this
study to indicate therapeutic use when found in
postmortem blood are listed in Table 2.
2.1 Screening
Each postmortem case was submitted to a broad
drug screen. The major screening methods used
to detect toxicologically significant analytes
included gas chromatography (GC), thin-layer
chromatography (TLC), overpressured layer
chromatography (OPLC), and immunological
assays, such as EMIT. Screening was always
carried out in blood (GC, GC-MS) and urine or
liver (TLC, OPLC, GC). Separate GC screens
were used for acidic and basic drugs, which
were also quantitated directly in the screening
analysis. Alcohol screening by head-space GC
was performed in practically all cases in blood
MATERIALS AND METHODS
27
and urine. The BACs were reported in mass per
mass units as parts per thousand (‰). The limit
of quantitation for ethanol was 0.20‰.
Tramadol
and
amitriptyline
were
determined in 1 ml of blood submitted to routine
drug screening. After extraction into ethyl
acetate at pH 9, the samples were injected into a
gaschromatograph equipped with a nitrogenphosphorus-selective detector [24]. For both
tramadol and amitriptyline, the method was
linear up to 10 mg/l, with a limit of quantitation
of 0.1 mg/l.
2.2 Metabolite Analysis
The major metabolites of tramadol (I) and
amitriptyline (II) were analyzed by liquid
chromatography coupled with tandem mass
spectrometry (LC-MS/MS).
The tramadol metabolites O-demethyltramadol (M1) and N-demethyltramadol (M2)
were obtained from Grünenthal GmbH (Aachen,
Germany) and determined in blood samples to
a limit of quantitation of 0.01 mg/l. MR1 and
MR2 were calculated as concentration of
tramadol per concentration of metabolite. The
analytes were extracted into a mixture of
dichloromethane and 2-propanol, followed by
liquid chromatographic separation on a
C18 column and detection by tandem MS using
multiple reaction monitoring (MRM). Linear
calibration was used from 0.0025 mg/l to
0.3 mg/l and quadratic calibration above
0.3 mg/l.
The amitriptyline metabolites nortriptyline,
NNT, EHAT, ZHAT, EHNT, and ZHNT were
obtained from H. Lundbeck A/S (Copenhagen,
Denmark). Imipramine was used as an internal
standard.
The analytes were extracted into a
mixture of ethyl acetate and 2-propanol (97:3).
A sufficient separation was achieved with
gradient elution on a C18 column, and the
analytes were detected by MS using MRM. For
amitriptyline metabolites, the limit of
quantitation was 0.001 mg/l; quadratic
calibration was used from 0.001 mg/l to 5 mg/l,
and concentrations above 5 mg/l were
quantitated in 1:10 dilutions.
28
MATERIALS AND METHODS
3 Genotyping
DNA was isolated from an autopsy bloodstain
(I) dried on dedicated paper (FTA® GeneCard,
Invitrogen Life Technologies, Carlsbad, CA,
USA) or from blood (II). The stains on FTA®
paper
were
processed
according
to
manufacturer’s recommendations, whereas
liquid blood samples were subjected to the
following standard procedure: 0.5-3 ml of blood
was mixed with 10-12.5 ml of lysis buffer
(10mM Tris-HCl, pH 7.5, 5mM MgCl2,
0.32M sucrose, 1% Triton X-100) in a screwcap plastic tube. After centrifugation, the
supernatant was decanted and 4 ml of lysis
buffer was added to the precipitate. After
mixing, centrifugation, and decantation, the
leukocyte pellets were digested in 2 ml of
digestion buffer (10mM Tris-HCl, pH 8.0,
10mM EDTA, 100mM NaCl, 2% sodium
dodecyl sulfate) and 20 µl of proteinase K
(20 mg/ml) at 56°C overnight. The incubated
sample was then transferred to a Phase Lock Gel
Light™ tube (Eppendorf AG, Hamburg,
Germany). The next step consisted of adding 1
ml of phenol and 1 ml of chloroform/3-methyl1-butanol (96:4), mixing, and centrifugation.
This step was repeated first with a similar
addition and then with 2 ml of chloroform/
3-methyl-1-butanol. In the end, the supernatant
was decanted into another screw-cap plastic tube
containing 10 ml of cold (-20°C) ethanol and
400 µl of 3M sodium acetate (pH 7.0). After
mixing and centrifugation at 4°C, ethanol was
decanted and the precipitate was washed with
5 ml of 70% cold ethanol. After mixing and
centrifugation (4°C), ethanol was decanted and
the precipitate was dried at room temperature
overnight. In the morning, the precipitate was
dissolved in 100 µl of 1xTE buffer
(10mM Tris-HCl, pH 7.5, 10mM EDTA). The
DNA stocks were stored frozen (-20°C) in
buffer solution.
The regions of interest were amplified
using PCR and the relevant polymorphic
positions were detected with an RFLP (I) or
SNaPshotTM (II) method (see Figure 2 on p. 18).
For primer specifications, see the Materials and
Methods section in Studies I and II. CYP2D6
allele nomenclature and nucleotide numbering
are according to the CYP Allele Nomenclature
Committee [146]. The genotyping methods used
take into account all of the common CYP2D6
and CYP2C19 mutations in Caucasians
[147,161].
3.1 Long Polymerase Chain Reaction
For CYP2D6 genotyping (I, II), three parallel
long PCRs were performed including 1) a
fragment covering the whole CYP2D6 gene
(4.7 kb in I, 5.1 kb in II), 2) a duplicationspecific fragment (3.6 kb in I, 3.2 kb in II) and
an internal control fragment (5.2 kb in I, 3,8 kb
in II), and 3) a deletion-specific fragment
(3.5 kb) identifying allele *5 and an internal
control fragment (3.0 kb). For CYP2C19
genotyping (II), a 1.9-kb fragment covering
exons 4 and 5 was amplified.
3.2 Restriction
Fragment
Length
Polymorphism Analysis
In Study I, 18 selected positions with known
mutations (100C>T, 124G>A, 138insT,
843T>G,
883G>C,
974C>A,
984A>G,
997C>G, 1023C>T, 1661G>C, 1707delT,
1758G>T/A, 1846G>A, 2549delA, 2613–
15delAGA, 2850C>T, 2935A>C, 4180G>C;
Table 3) were detected by reamplifying eight
separate fragments of 186–471 bp from the
4.7-kb amplificate and digesting them with a set
of 15 restriction enzymes (HphI, MspI, BspMI,
PstI, BsmAI, BstNI, BsaAI, MboII, HinP1I,
FokI, BanII, BstEII, HaeII, SacII, EagI). The
RFLP panel allowed identification of alleles *2*4, *6-*12, *14, *15, *17, and *39. For details,
see Study I, Table 1. Alleles not carrying any of
the above mutations were classified as *1.
3.3 Multiplex Single-Base Extension Reaction
In Study II, nine selected polymorphic positions
(100C>T, 1023C>T, 1661G>C, 1707delT,
1846G>A,
2549delA,
2613-5delAGA,
2850C>T, 4180G>C; Table 3) in CYP2D6 were
detected using a multiplex single-base extension
reaction with nine detection primers and an ABI
PRISM SNaPshot™ Multiplex Kit (Applied
Biosystems, Foster City, CA, USA). The
SNaPshot method allowed the identification of
CYP2D6 alleles *3, *4, *6, *9, *10, and *17
[156]. Alleles with 1661G>C, 2850C>T, and
4180G>C were classified as *2.
Table 3. CYP2D6 positions genotyped in Studies I
and II (highlighted) and their known occurrence in
various alleles [146]. See also Figure 2 on p. 18.
Mutation
Allele
100C>T
*4, *10, *14
124G>A
*12
138insT
*15
843T>G
*2, *4
883G>C
*11
974C>A
*4
984A>G
*4
997C>G
*4
1023C>T
*17
1661G>C
*2, *4, *8, *10-*12, *14, *39
1707delT
*6
1758G>T/A
*8, *14
1846G>A
*4
2549delA
*3
2613–5delAGA
*9
2850C>T
*2, *8, *11, *12, *14, *17
2935A>C
*7
4180G>C
*2, *4, *8, *10-*12, *14, *17, *39
An application of this method was used to detect
the positions 636G>A and 681G>A in
CYP2C19, allowing identification of CYP2C19
alleles *3 and *2, respectively. Alleles not
carrying these mutations were classified as *1.
4 Case Selection Criteria
The cases investigated in Study I were autopsy
cases from June 1998 to June 2000 in which
tramadol was found, a bloodstain on FTA®
paper was available, and a sufficient amount of
blood remained for metabolite analysis.
The cases investigated in Study II included
a consecutive series of autopsy cases from 1999
to 2001 in which amitriptyline was found at
concentrations ≥0.2 mg/l in blood and a
sufficient amount of blood was available.
The cases investigated in Study III
included fatal poisonings from 1995 to 2000
involving alcohol alone or in combination with
the BDZ anxiolytic diazepam or the BDZ
hypnotic temazepam.
The cases investigated in Study IV
included fatal poisonings from 1995 to 2000
RESULTS
29
involving alcohol alone or in combination with a
drug commonly causing fatal poisonings in
Finland, i.e. the phenothiazine antipsychotic
promazine or levomepromazine (methotrimeprazine), the TCA doxepin or amitriptyline,
the opioid analgesic propoxyphene (dextropropoxyphene), the BDZ hypnotic temazepam,
the non-BDZ hypnotic zopiclone, the SSRI
citalopram, or the calcium channel inhibitor
diltiazem.
The cases investigated in Study V included
fatal poisonings from 1995 to 2002 involving
newer antidepressants available in Finland
during this period, i.e. mianserin, mirtazapine,
venlafaxine,
milnacipran,
reboxetine,
nefazodone, trazodone, the SSRIs citalopram,
fluoxetine, fluvoxamine, paroxetine, and
sertraline, and the monoamineoxidase type A
inhibitor moclobemide.
The cases investigated in Study VI
included fatal poisonings from 1995 to 2002
involving amitriptyline, propoxyphene, or
promazine either alone or in combination with
alcohol.
In addition to the selection findings,
allowed coincidental findings were caffeine and
nicotine (III-VI), acetone and 2-propanol in
30
MATERIALS AND METHODS
ethanol-positive cases (III-VI), diazepam
metabolites nordiazepam and chlordiazepoxide
(III), and therapeutic concentrations of BDZs
(IV-VI).
5 Statistical Methods
Statistical analysis was performed using
MINITAB 13 (Minitab Inc., State College, PA,
USA) and SPSS 10 (SPSS Inc., Chicago, IL,
USA) software for calculation of confidence
intervals (CIs) for means and medians and for
performing univariate analysis of variance, test
of two proportions, Student’s t-test, and MannWhitney test. A p-value of <0.05 was
considered to indicate a statistically significant
difference. The 95% CIs for the number of
observed deaths were taken from the Poisson
distribution.
When average drug concentrations were
compared between groups, medians were used
instead of means. Drug concentrations are not
normally distributed because pharmacological
response generally exhibits a logarithmic
relation to a substance concentration. Medians
are therefore more appropriate for describing
these distributions.
RESULTS
1 Pharmacogenetics
Genotyping of postmortem samples was
generally successful despite the often poor
quality of cadaveric blood specimens and the
large fragments required for CYP2D6 analysis.
1.1 CYP2D6 and Tramadol (I)
All of the 33 tramadol cases were successfully
genotyped. A positive correlation was found
between the CYP2D6 gene dose and the rate of
Number of functional CYP2D6 genes
tramadol O-demethylation, and a negative
correlation between the CYP2D6 gene dose and
the rate of tramadol N-demethylation (Figure 6).
More specifically, the median metabolite ratio
MR1 was significantly higher and the median
MR2 significantly lower in the cases with no
functional genes than in those with two or more.
No fatal poisonings coincided with a
homozygous nonfunctional genotype.
Number of functional CYP2D6 genes
Figure 6. Metabolite ratios MR1 (O-demethylation) and MR2 (N-demethylation) of tramadol
plotted against the number of functional CYP2D6 genes. Logarithmic transformations of
median MRs are shown with 95% confidence intervals. See also Figure 3 on p. 20. = p<0.05,
= p<0.01.
1.2 CYP2D6 and Amitriptyline (II)
Of the amitriptyline-related cases, 195
individuals of 202 were successfully genotyped.
Gene dose correlated with several MRs, with
expected correlations found between the number
of functional CYP2D6 genes and the MRs
related to the rate of trans-hydroxylation, i.e.
EHNT/ZHNT, EHAT/ZHAT, nortriptyline/
EHNT, amitriptyline/EHAT, and nortriptyline/
EHAT (Figure 7). Several of the MRs were
significantly different between the genotype
groups with zero, one, or two functional genes.
Only one of the fatal poisonings included
in the material coincided with a homozygous
nonfunctional genotype (*4/*4). The case was a
suicide: a 56-year old female had ingested a
large amount of her husband’s medication.
Amitriptyline was found in postmortem blood at
a concentration of 60 mg/l, when the upper limit
of the therapeutic range is 0.2 mg/l [36].
RESULTS
31
log(AT/NT)
log(EHNT/ZHNT)
1.3
0.6
0.4
0.2
1.1
0.9
0
0.7
-0.2
0.5
log(EHAT/EHNT)
log(EHAT/ZHAT)
0.7
0.5
0.3
0.1
log(ZHAT/ZHNT)
0.6
0.3
0
-0.4
-0.1
-0.3
-0.5
-0.3
-0.7
2
0.6
1.7
1.4
1.1
0.4
0.2
0.8
0
1.6
1.1
log(NT/ZHAT)
log(NT/EHAT)
-0.2
-0.6
0.1
log(NT/EHAT)
log(AT/EHAT)
log(NT/EHNT)
-0.1
0.9
0
1.2
0.8
0.4
0.9
0.7
0.5
0.3
0
0
1
2
3
Number of functional CYP2D6 genes
0
1
2
Number of functional CYP2C19 genes
Figure 7. Relevant metabolite ratios in amitriptyline metabolism plotted against the number of
functional CYP2D6 and CYP2C19 genes. Logarithmic transformations of median metabolite
ratios are shown with 95% confidence intervals. AT = amitriptyline, NT= nortriptyline. See also
Figure 4 on p. 21. = p<0.05, = p<0.01, = p<0.001.
1.3 CYP2C19 and Amitriptyline (II)
Regarding CYP2C19, 177 individuals of 195
were successfully genotyped. The CYP2C19
gene dose correlated with several MRs, with
expected correlations found between the number
32
RESULTS
of functional CYP2C19 genes and MRs related
to the rate of N-demethylation (amitriptyline/
nortriptyline, EHAT/EHNT, ZHAT/ZHNT,
nortriptyline/EHAT, and nortriptyline/ZHAT;
Figure 7). Several of the MRs were significantly
different between the genotype groups with
zero, one, or two functional genes, but none of
the fatal poisonings coincided with a
homozygous nonfunctional genotype.
1.4 Allele and Genotype Frequencies (I, II)
In Studies I and II, altogether 228 individuals
were successfully genotyped for CYP2D6. The
allele frequencies in this population are shown
in Table 4.
Most of this population, i.e. 124
individuals (54.4%), had two functional
CYP2D6 genes, but 69 (30.3%) had only one
and 17 (7.5%) none. Three or more functional
CYP2D6 genes were found in 18 cases (7.9%).
Overall, the frequency of duplicated alleles in
the Finnish population appears to be 5% and that
of null alleles (*3-*6) 23.4%. According to the
Hardy-Weinberg
principle,
this
would
correspond to approximately 5% of CYP2D6
gPMs and 7% of CYP2D6 gUMs in the Finnish
population.
In the population of 177 cases successfully
genotyped for CYP2C19, the observed
CYP2C19 allele frequencies were 0.836 for
*1 and 0.164 for *2. Allele *3 was not found.
The majority, i.e. 130 cases (73.4%),
revealed two functional CYP2C19 genes, but
36 (20.3%) carried only one and 11 (6.2%)
none.
Table 4. CYP2D6 allele frequencies in the 228
successfully genotyped cases.
Allele
n
%
*1
151
33.1
*2
165
36.2
17
3.7
*3
*4
64
14.0
*5
12
2.6
*6
14
3.1
*9
3
0.7
*10
8
1.8
9
2.0
*1xN
13
2.9
*2xN
Total
456
100
2 Fatal Toxicity Indices (IV, V)
FTIs were calculated for nine newer antidepressants (V) and eight other common drugs
(IV), with citalopram included in both FTI
studies. Furthermore, the number of fatal
poisonings caused by each of the newer antidepressants was compared with the number of
expected poisonings (V), revealing that venlafaxine, mianserin, and mirtazapine caused more
and fluoxetine, sertraline, and moclobemide less
fatal poisonings than expected from the sales of
newer antidepressants in 1995-2002 (Table 5).
FTIs were highest for the phenothiazine
antipsychotics promazine and levomepromazine,
Table 5. Sales and observed and expected deaths due to newer antidepressants.
Drug
Citalopram (SSRI)
Fluoxetine (SSRI)
Sertraline (SSRI)
Mirtazapine
Paroxetine (SSRI)
Mianserin
Moclobemide
Venlafaxine
Fluvoxamine (SSRI)
Othersd
Total
Salesa
84.0
48.9
15.7
14.5
11.2
10.9
10.9
6.80
5.26
1.12
209.1
Fatal poisonings
Observed
104
16
6
37
16
33
29
30
8
5
284
Expectedb
114
66
21
20
15
15
15
9
7
2
p-valuec
>0.05
<0.001
0.003
0.017
>0.05
0.006
0.027
<0.001
>0.05
>0.05
a) In DDD/1000 inhabitants/day (National Agency for Medicines)
b) Calculated for each drug by dividing the total number of poisonings by the corresponding
proportion of total sales
c) p-value for the difference between the proportions of observed and expected deaths
d) Includes trazodone, nefazodone, milnacipran, and reboxetine
RESULTS
33
the opioid analgesic propoxyphene, and the
TCAs doxepin and amitriptyline (Table 6).
3 Drug-Alcohol Interaction
Striking differences were observed in median
BACs between fatal poisonings involving
different drugs.
3.1 Alcohol and Benzodiazepines (III)
Median BAC in fatal accidental alcohol
poisonings where no other analytes were
detected was 3.3‰ (n=615). In fatal poisonings
involving diazepam it was 3.5‰ (n=161), but in
those involving temazepam it was only 2.45‰
(n=32) (III).
The major difference between the
characteristics of these two groups was that
manner of death was accidental in 99.8% and
98.8% of ethanol- and diazepam-related
fatalities, respectively, but in only 62.5% of
temazepam-related poisonings. In the latter, the
median BAC was lower in suicides than in
accidental poisonings (2.55‰ (n=20) vs. 2.1‰
(n=7)), with a point estimate of difference of
0.6‰ (p=0.02). A difference was also observed
in temazepam concentrations, with a median of
2.6 mg/l in suicides and 0.3 mg/l in accidental
poisonings (p<0.001).
3.2 Alcohol and Other Common Drugs (IV-VI)
In addition to diazepam and temazepam, median
BACs in fatal drug-alcohol poisonings were
calculated for six newer antidepressants (V) and
seven other common drugs (IV). The median
BACs (Table 6) were lower than that in pure
alcohol poisonings (3.3‰), with the exception
of poisonings involving fluoxetine. In drugalcohol poisonings involving moclobemide
(n=9), the difference did not reach statistical
significance. However, the drugs associated with
low median BACs (IV) were also the ones more
often associated with suicides and less often
with accidental manner of death (Figure 9).
Table 6. Fatal toxicity indices (FTIs) and median blood alcohol concentrations (BACs) in
fatal drug-alcohol poisonings.
Median BAC (95% CI)
n
BDZ+
Drug
FTI (95% CI)a
(deaths/DDD/1000
inhabitants/year)
Fluoxetine*
Citalopram*
Diltiazem
Zopiclone
Moclobemide*
Mirtazapine°
Levomepromazine
Temazepam
Mianserin*
Venlafaxine°
Propoxyphene
Doxepin
Amitriptyline
Promazine
Fluvoxamine*
Sertraline*
Paroxetine*
0.33
1.2
1.4
0.96
2.7
2.6
48
0.90
3.0
4.4
33
21
12
120
1.5
0.38
1.4
(0.19-0.53)
(1.0-1.5)
(1.1-1.8)
(0.8-1.1)
(1.8-3.8)
(1.8-3.5)
(42-53)
(0.7-1.1)
(2.1-4.3)
(3.0-6.3)
(29-37)
(18-24)
(11-14)
(110-140)
(0.66-3.0)
(0.14-0.83)
(0.82-2.3)
(‰)
3.4
2.9
2.8
2.7
2.7
2.7
2.6
2.5
2.4
2.4
1.7
1.6
1.6
1.3
nd
nd
nd
(3.0-3.9)
(2.5-3.2)
(2.0-3.3)
(2.2-3.1)
(1.1-3.9)
(2.3-3.2)
(2.0-2.9)
(2.2-2.7)
(1.7-2.9)
(0.4-2.7)
(1.5-1.8)
(1.2-1.9)
(1.4-1.9)
(1.1-1.6)
-
(%)
21
80
23
38
9
16
64
57
16
8
67
27
50
31
-
62
63
30
24
56
88
45
(100)
63
75
25
33
46
29
-
nd = not determined; BDZ+ = proportion of benzodiazepine-positive cases in drug-alcohol poisonings
a) Data from 1997 to 2002 for venlafaxine and mirtazapine (°), from 1995 to 2002 for the other newer
antidepressants (*), and from 1995 to 2000 for the other common drugs. Confidence intervals (CI)
calculated using the Poisson distribution.
34
RESULTS
3.2
3.2
6
7
2.4
8
2.0
3
1.6
1
4
2
20%
5
6
8
2.4
7
2.0
4
1.6
1
3
2
1.2
1.2
0%
R2 = 0.70
2.8
5
2.8
Median BAC [‰]
Median BAC [‰]
9
9
R2 = 0.70
40%
60%
80%
Manner of death accidental
0%
20%
40%
60%
Manner of death suicide
Figure 9. The correlation of median blood alcohol concentration (BAC) with the manner of
death in drug-alcohol poisonings. The drugs involved are propoxyphene (1), promazine (2),
doxepin (3), amitriptyline (4), diltiazem (5), zopiclone (6), levomepromazine (7), temazepam
(8), and citalopram (9).
Therapeutic concentrations of some common
BDZs were present in 45% of drug-alcohol
poisonings included in Studies IV and V
(excluding citalopram and temazepam cases
from Study IV) (Table 6).
The combined results of FTI and median
BAC analyses are shown in Figure 10. The
drugs appearing the safest are located in the
lower left-hand corner (fluoxetine, etc.), and the
ones appearing the least safe in the upper righthand corner (promazine, etc.).
Median drug concentrations in fatal
poisonings were calculated for amitriptyline,
propoxyphene, and promazine (VI). Median
amitriptyline and propoxyphene concentrations
were lower in drug-alcohol poisonings than in
pure
drug
poisonings.
Amitriptyline
concentrations were on average lower also when
BDZs were present.
BAC distributions in fatal poisonings
involving alcohol alone and alcohol in
combination with amitriptyline, propoxyphene,
and promazine from Study VI are shown in
Figure 11. In the cumulative distributions, a
notable shift occurs towards lower BACs in all
of the combinations. The most prominent shift is
observed in promazine-related cases, with
almost no overlap with the curve for fatal
poisonings by alcohol alone.
Combined drug-alcohol concentration
curves (isobolograms) were constructed in Study
VI (Figure 12). They illustrate the concentration
distributions seen in fatal poisonings involving
alcohol alone (y-axis), drug alone (x-axis), and
their combination (connecting lines). The lines
connect concentration pairs equally effective in
causing 10%, 30%, 50%, 70%, and 90% of the
fatalities. The drug concentrations generally
increase as alcohol concentrations decrease,
with the exception of promazine concentrations
being relatively low in fatal poisonings by
promazine alone.
RESULTS
35
Figure 10. Fatal toxicity index (FTI) plotted against the deviation of median blood alcohol
concentration (BAC) in drug-alcohol poisonings from that found in pure alcohol poisonings (IV,
V). The bars represent the 95% confidence intervals for the difference in BAC. * = n<10.
90 %
Cumulative Deaths
80 %
70 %
60 %
50 %
40 %
30 %
20 %
10 %
0%
0.5 ‰
1‰
2‰
3‰
4‰
BAC
Figure 11. Concentration-response curves in cases of fatal poisoning involving alcohol alone (—)
and alcohol in combination with amitriptyline (–z–), propoxyphene (–▲–), and promazine (–■–).
36
RESULTS
4
BAC [‰]
3
2
1
0
0
2
0
5
10
15
20
25
30
Propoxyphene concentration [mg/l]
35
40
0
3
6
9
12
15
18
Promazine concentration [mg/l]
21
24
a
4
6
8
10
12
Amitriptyline concentration [mg/l]
14
4
BAC [‰]
3
2
1
0
b
4
BAC [‰]
3
2
1
0
c
Figure 12. Concentration-concentration curves illustrating the concentration distributions seen in
fatal poisonings involving alcohol and a drug. The lines connect concentration pairs which would
account for 10% (––), 30% (–■–), 50% (—), 70% (–z–), and 90% (–▲–) of cases.
RESULTS
37
DISCUSSION
1 Methodological Considerations
Finland is an excellent site for research on
forensically interesting postmortem material
because the medicolegal autopsy rate is high,
recently 20% of all annual deaths, with forensic
toxicology involved in approximately one-half
of cases [94,231]. A high autopsy rate (or a large
population) is essential for achieving sufficient
sample sizes for statistical studies, such as the
ones presented here. A small number of cases
would result in low statistical power and hence
in low interpretative value in any study.
Furthermore, with postmortem blood collection
from the femoral vein being the standard
procedure throughout the country from 1995
onwards and with validated methodologies
employed in the Laboratory of Forensic
Toxicology, the blood concentrations obtained
in Finnish postmortem toxicology constitute
reliable, commensurate data.
Although the relevance of proper collection
and preservation of autopsy samples was not
assessed in the experimental part of this thesis, it
must be noted that they are the basis for all of
the research presented here, as well as for all
results reported by any laboratory of
postmortem forensic toxicology. If sample
collection is in some way compromised, it
cannot be compensated for at a later stage.
Therefore, the origin of the sample should
always be known to the forensic toxicologist and
should also be stated in the methods section of a
publication, especially if the reported value is to
be used as a reference in interpretation.
As discussed by King more than 20 years
ago [229], most studies on drug-alcohol
interactions are conducted on animals or living
persons, with little data available on human
postmortem investigations. This is a problem
because drug concentrations can be markedly
higher in fatal poisonings than concentrations
produced in a clinical study. In fact, a massive
overdose can result in such concentrations that
they are no longer in proportion with the end
result, i.e. death would have resulted from a
concentration many times lower than that found
in the samples.
38
DISCUSSION
In fatal poisonings due to alcohol alone and
without complicating factors, the maximum
antemortem alcohol concentrations can be
assumed to have been much higher, with an
estimated mean of 4.63 g/l (4.4‰), and a
subsequent decrease during survival time [76].
However, this does not preclude statistical
analysis based on postmortem concentrations.
On the contrary, a statistical approach may be
assumed to compensate for possible postmortem
changes – such as redistribution of alcohol (or
drugs) in the body or alcohol formation by
microbial activity – in individual cases.
The drugs investigated in Studies III and
IV were chosen because they were among the
most common causes of fatal poisonings
investigated in Finland during 1995-2000. In
addition, they are the most common drugs in
Finnish hospitalizations due to intoxication,
two-thirds of which also involve alcohol [74].
However, a problem with retrospective research
in forensic toxicology is that the poisoning
panorama is ever-changing and only a part of
the results is applicable to the present situation.
For instance, since 1995, the use of
propoxyphene has diminished in Finland, most
likely due to published warnings on its abuse
potential and to the introduction of tramadol.
Alcohol-propoxyphene poisonings are therefore
less common today than during the study period.
Despite
the
introduction
of
newer
antidepressants, amitriptyline and doxepin
remain on the market and are frequently
encountered in fatal poisonings [94]. Likewise,
promazine, predominantly prescribed to alcohol
abusers to relieve withdrawal symptoms, still
constitutes a serious problem, reflected in the
number of fatal poisonings involving this
neuroleptic agent [94]. Therefore, in spite of the
retrospective approach the results presented here
can be considered relevant in forensic medicine
today.
In a department of forensic medicine,
identification of unknown dead bodies using
genetic profiling is common practice. The
detection methods used for genotyping in this
study were originally chosen according to the
existing equipment, which was the one in place
for genetic profiling. An alternative genotyping
approach could also be applied to postmortem
CYP genotyping [204]. However, the techniques
employed here worked relatively well, as
discussed below, and significant progress was
made in CYP genotyping by replacing the
laborious RFLP method with the moderate
throughput SNaPshot method [156].
2 Pharmacogenetics
Postmortem determinations are inevitably
limited to one-time sampling at a random timepoint after an unknown intake instead of timed
sampling after controlled ingestion, followed by
calculation of the area under the curve, as in
clinical settings. This is one of the most
important factors complicating interpretation of
postmortem toxicology results.
Drug pharmacokinetics may be affected by
several other factors besides genetic variation,
especially by metabolic drug interactions, age,
and renal or liver malfunction. This is of
particular interest in a medicolegal context,
where polypharmacy and various pathophysiological conditions are common findings. In our
case series, gender was not observed to affect
the MRs, whereas age, due to age-associated
physiological status, may have played a role
[133]. However, due to the large number of
known inhibitors of CYP2C19 or CYP2D6, the
varying degree of inhibition, and the wide range
of inhibitor concentrations present in the
material, taking these factors into account in a
reasonable manner was not possible.
Another limitation of the study was the
quality of the autopsy samples. Postmortem
DNA can be difficult to amplify because of
extensive degradation. The process of
decomposition may also give rise to impurities,
such as free metal cations, which may inhibit the
enzymes used in PCR. Thus, analysis of
degraded samples will not always yield an
unequivocally interpretable result. Problems
were encountered here both with CYP2D6
genotyping (II), unsuccessful in 7 of 202 cases,
and with CYP2C19 genotyping, unsuccessful in
18 of 195 cases (II). Probable reasons for the
lack of result in these cases may have been the
extent of DNA degradation, precluding
amplification of the large CYP2D6 fragments,
and the presence of impurities that probably
inhibited the enzyme used for the amplification
of CYP2C19 fragments.
Despite these limitations, postmortem
pharmacogenetics may provide important
information in individual cases and shed light on
the cause and mode of death in otherwise
unclear forensic cases. Postmortem samples are
routinely taken for toxicological analysis in
cases where the autopsy findings or background
information indicate poisoning. In Finland, these
samples are stored for one year after analysis,
making them available for later re-examination,
if necessary. Genetic factors could explain those
cases where intentional overdose can reasonably
be ruled out but toxicological analysis reveals
either an unexpectedly high concentration of the
parent drug or an exceptional parent drug/
metabolite ratio. This is best exemplified by a
case report of an incident where parents were
absolved from homicide charges as a result of a
homozygously defective CYP2D6 gene being
detected in the postmortem investigation of a
fluoxetine-related death [70].
We examined the possibility of a fatal
poisoning occurring due to a combination of
drug treatment and a defective genotype.
Amitriptyline and tramadol are toxic drugs
known to cause fatal intoxications, and they
were therefore selected as candidate drugs in
this study. Among the tramadol cases, there was
one fatal drug poisoning due to tramadol alone
(9 mg/l), but the CYP2D6 genotype was fully
functional (*1/*2) and MR1 and MR2 were in
the ranges typical of cases with two functional
genes. Among the amitriptyline cases, none of
the accidental fatal poisonings was associated
with either a homozygously defective
CYP2D6 genotype or a homozygously defective
CYP2C19 genotype. Even though Studies I and
II did not reveal fatal poisonings which could be
attributed to genetic defects, we have recently
identified a case of fatal doxepin poisoning
where the manner of death is accidental and the
CYP2D6 genotype is completely nonfunctional
(Koski et al., unpublished results).
With tramadol, however, it was evident
that when the number of functional genes
DISCUSSION
39
increased, the median MR1 decreased. The
median MR2 also correlated with the number of
functional genes, but in the reverse direction, as
was expected based on the complementary
nature of O- and N- demethylation pathways,
respectively. A clinical study on children found
that the CYP2D6-mediated metabolite (M1) was
formed to a lesser extent, and the formation of
the non-CYP2D6 product (M2) was more
extensive in subjects carrying one functional
CYP2D6 gene than in those carrying two
functional genes [187]. This would implicate
that when one metabolic pathway is absent or
blocked, the metabolism is shunted towards an
alternative route.
Even a single metabolic reaction may be
catalyzed by different enzymes, thus having
several complementary pathways. Other
enzymes besides CYP2C19 have been suggested
to
participate
in
N-demethylation
of
amitriptyline, especially at high amitriptyline
concentrations [184]. Therefore, less correlation
can be expected between amitriptyline MRs and
CYP2C19 genotypes than between amitriptyline
metabolites and CYP2D6 genotypes. Judging
from the correlations between the observed amitriptyline metabolite patterns and the determined
CYP2D6 and CYP2C19 genotypes, amitriptyline
metabolism appeared more dependent on
CYP2D6 than on CYP2C19.
The total allele frequency of the CYP2D6
null alleles (*3-*6) observed here, 23.4%, is
somewhat lower than previously reported in
Caucasians, e.g. 25.2% in Germans [149] and
27% in the Swiss/French [232]. Moreover,
frequencies of 31.0% and 23.1% have been
reported in Swedish blood donors and in fatal
intoxications, respectively [204]. The allele
frequency of CYP2C19*2 in this study, 16.4%,
agrees well with those reported in the Swedish
study, i.e. 14.3% in blood donors and 15.5% in
fatal intoxications [204], and the frequency
estimated by Wedlund, 14.7% [161].
No distinction was made between alleles
associated with normal CYP2D6 enzyme
activity (*1 and *2) and those associated with
decreased activity (*9 and *10). By making this
distinction, a category corresponding to an
approximately 0.5 functional gene predicting the
IM phenotype could have been established
40
DISCUSSION
[128]. It was recently suggested that allele
CYP2D6*41, also associated with decreased
expression of a functional protein product [233],
might be differentiated from CYP2D6*2 by
genotyping the position 2988G>A (*41:2988A,
*2:2988G) [148]. In this study, allele *41 was
not included in the genotyping methods. With an
estimated allele frequency of 8.4% [148], *41 is
more common in Caucasian population than the
other known alleles associated with lower
CYP2D6 expression, but its importance is
unclear [152]. Alleles *9 and *10 have a total
allele frequency of 3-4% in Europeans
[149,232], with our result of 2.5% agreeing well
with earlier reports. Subjects homozygous for
*10 have been found to show a doubled
nortriptyline plasma half-life compared with
subjects homozygous for *1 [190], and thus
carrying two alleles associated with decreased
activity might be considered equal to carrying
one functional gene. Having only one functional
gene has been suggested to constitute a risk
factor for CYP2D6 substrate toxicity [206]. Any
CYP2D6 alleles associated with diminished
activity and present in a relevant frequency in a
population should therefore be taken into
account in future work.
Finally, it is highly unlikely that the
metabolism and excretion of a drug would
depend on only one type of enzyme. Of the
extensive field of pharmacogenetics, only two
metabolic enzymes and two substrates were
targeted here, and although differences in
metabolite ratios were observed between
genotype groups, they were relatively small and
often overlapping. However, the finding of
differences in this material, unadjusted for age,
gender, or dosage, suggests that in the context
studied the genes play a dominant role over
other factors. The effects of a drug obviously
also depend on the genes associated with
transporter proteins and receptors, but the
polymorphic metabolic enzymes are today
considered of such importance that the
pharmaceutical
companies
abandon
a
polymorphically metabolized candidate drug
molecule fairly early on in the development if a
pharmacologically equipotent alternative exists
[125]. This can be a change for the better also
from the Finnish point of view, since altogether
12% of the individuals genotyped in this study
were either CYP2D6 gPMs or gUMs, and thus,
at least one in eight Finns taking CYP2D6
substrates could be expected to experience
ADRs due to genetically altered metabolism.
Moreover, 6.2% of the cases investigated here
revealed a nonfunctional CYP2C19 genotype.
3 Drug-Alcohol Interaction
Clinical studies often focus on the pharmacokinetic interactions and psychomotor effects of
drug-alcohol combinations, whereas in fatal
poisonings, the pharmacodynamic interactions
are more important. In drug-related fatalities,
the relevant questions are which findings
have contributed and by what mechanism. It is
also important to consider whether certain
combinations of drugs and alcohol have
greater effects than others in a manner
reflected in concentrations found in postmortem
investigation.
3.1 Alcohol and Benzodiazepines
A striking difference is apparent in the outcome
of ethanol poisonings depending on the nature of
concomitant drugs. With regard to the common
BDZs, lower ethanol concentrations appear to
result in fatal poisonings when temazepam is
involved than when diazepam or no other drug
is involved. Interestingly, no cases combining
high concentrations of alcohol and diazepam
were found in any of these studies, and thus, no
conclusions about such combinations should be
inferred. The relatively frequent occurrence of
high
temazepam
concentrations
further
accentuates the absence of high diazepam
concentrations, which may reflect differences in
tissue distribution of temazepam and diazepam.
The proportion of suicides is, however,
relatively high in the temazepam group and
nonexistent in the fairly large diazepam group. It
therefore seems that those who have
attained high blood concentrations of both
alcohol and diazepam simultaneously have
recovered, with or without supportive treatment.
The general public may also perceive the
hypnotic temazepam as a toxic substance, but
diazepam as a relatively mild and harmless
anxiolytic.
3.2 Alcohol and Other Common Drugs
For the other drugs commonly found in fatal
poisonings, marked differences were present
in alcohol concentration distributions. The
median BACs in cases involving amitriptyline,
doxepin, propoxyphene, and promazine were
conspicuously low compared with those in
other cases. They might therefore be considered
to interact with alcohol in a fatal manner,
although the mechanism of interaction cannot be
deduced from this data. Whereas alcohol and
BDZs are considered to exert their effects at
least in part via the GABAA receptor and thus
have a rational basis for interaction, this
mechanism is not likely to apply to the other
drugs. All of them, however, exert their
therapeutic effects via the CNS, a fact that
renders the idea of interaction with alcohol
plausible.
The analgesic propoxyphene acts via
opioid receptors. Stimulation of opioid receptors
has several specific effects, including depression
of the respiratory center. Propoxyphene can
therefore be expected to show additive or
synergistic effects with alcohol [234]. The
toxicity of amitriptyline has been attributed to
the quinidine-like action by which it causes
cardiac depression. The interactions of
propoxyphene and amitriptyline with alcohol
have therefore been hypothesized to involve
membrane-stabilizing activity [113,234]. The
phenothiazines promazine and levomepromazine
exert their antipsychotic effects by acting on the
dopamine system, especially by blocking
dopamine receptors, but they are also known to
cause nonspecific sedation. Mianserin and
venlafaxine were associated with the lowest
BAC levels among cases of fatal poisonings
involving newer antidepressants, although the
number of cases was relatively small (Table 6).
These drugs also act via the CNS, their
mechanism of action being based on inhibition
of monoamine reuptake. This does not, however,
explain why they would interact more strongly
with alcohol than the other newer
antidepressants.
Another line of reasoning which may
explain the relatively low BACs found in
combination with amitriptyline, doxepin,
propoxyphene, and promazine is that these four
DISCUSSION
41
drugs are the ones most often involved in
suicides (Figure 9). Whereas the relatively low
BACs might be considered to result from
additive or synergistic interactions with these
drugs, they might, alternatively, be considered to
indicate intentional but moderate use of alcohol
during the suicide attempt, for instance, for the
purpose of flushing down the pills or giving the
attempter more courage to complete the act. It is
also conceivable that impaired judgment and
dysphoric states provoked by alcohol may give
rise to impulsive and aggressive acts, even to
suicide, with less serious intent [235].
In addition to the lower BAC distributions
in fatal poisonings involving drugs, lower blood
drug concentrations were found in fatal
poisonings in which amitriptyline or propoxyphene was present in combination with alcohol
than in cases not involving alcohol (VI). This
would support the hypothesis of interaction.
However, the median promazine concentrations
were similar in alcohol-positive and alcoholnegative cases, although the median BAC (IV)
was the lowest in promazine cases, and the
isobologram constructed in Study VI did not
differ significantly from those constructed for
amitriptyline and propoxyphene. Interestingly,
none of the isobolograms were convex towards
the origin, as were the alcohol-barbiturate curves
created by Stead and Moffat [79]. The potential
interaction can therefore be considered additive
at most and not synergistic. Amitriptyline
concentrations were also lower in BDZ-positive
than in BDZ-negative cases, in parallel with the
results of an earlier study [236].
4 Drug Safety
The BAC in drug-alcohol poisonings can be
considered a reliable parameter for assessing
drug-alcohol interaction since the distribution of
postmortem alcohol concentrations in poisoning
caused by alcohol alone is essentially similar
independent of the sample, as illustrated earlier
by Vuori et al. (see also Figure 1) [80] and
Study VI (Figure 11). By considering the
median BAC as a relative measure of drug
toxicity similar to FTI, these two measures can
be compared. Among the 18 drugs studied in the
context of FTIs and median BACs (IV, V), the
FTI rank order largely agreed with the
42
DISCUSSION
magnitude of median BAC deviation in pure
alcohol
poisonings,
with
promazine,
amitriptyline, doxepin, and propoxyphene
appearing the least safe (Figure 10).
This division obviously reflects not only
the acute toxicity but also the manner of use of
these drugs. Judging from the varying
proportions of suicides and blood concentrations
exceeding therapeutic ranges, it is evident that
certain drugs are deliberately taken in overdoses
for intoxication purposes or with suicidal intent.
However, Buckley and McManus [97] have
concluded that the FTIs that they obtained for
anxiolytic and sedative drugs largely reflect the
inherent toxicity of these drugs. Also Henry
[101] and Farmer and Pinder [87] considered the
inherent toxicity of the compound the crucial
factor in the fatal toxicity of antidepressants and
the prescribing practices and the popular
perception of toxicity of secondary importance.
Even if the ingested dose and the acute toxicity
of a drug are deemed the determining factors for
outcome, reaching hospital care certainly is
another; most overdose fatalities occur outside
hospitals, with very low overall mortality of
hospitalized overdose patients [74,237,238].
The drugs investigated in Studies IV and V
are to a large extent newer than those covered in
the 1980s. Amitriptyline and propoxyphene are
striking exceptions, although since the study
period, the use of propoxyphene has decreased.
Promazine is an older drug and its use is
not very common worldwide. The results
concerning promazine might, however, be
generalizable to chlorpromazine, a close relative
of promazine and in more widespread use. The
absence of high alcohol concentrations among
the promazine cases is especially remarkable,
with the maximum BAC in the promazinealcohol poisonings equaling the median BAC in
pure alcohol poisonings. Furthermore, the FTIs
of promazine, and to a lesser extent levomepromazine, are markedly higher than those of
the other common drugs included here.
4.1 Newer Antidepressants
The newer antidepressants in general appeared
safer in combination with alcohol than
amitriptyline and doxepin. Among the common
newer antidepressants, fluoxetine and sertraline
had caused significantly less and the non-SSRI
agents significantly more deaths than expected.
The rare drugs caused almost no deaths: in
1995-2002, trazodone caused three, nefazodone
one, milnacipran one, and reboxetine none. Both
the FTIs and the median BAC differences
indicate that among the newer antidepressants,
the SSRIs, especially fluoxetine, are relatively
safe and venlafaxine relatively unsafe, with
mianserin, mirtazapine, and moclobemide
somewhere in between (V).
Mianserin, which was released to the UK
market in 1976, was relatively early on
associated with a lower FTI than those of TCAs
[93,94,99]. For mirtazapine and venlafaxine,
however, the FTIs obtained in this study yielded
novel information since these drugs were
introduced in Finland after the study period
covered by Öhberg et al. [102] and since
mirtazapine was represented by only a single
fatality in the study of Buckley and McManus
[96]. The relatively high toxicity of venlafaxine
and the relative safety of SSRIs have already
been established by several studies [e.g. 96,107].
An important factor here might be the suggested
differences in prescribing practices, with
venlafaxine allegedly prescribed to people
already at a relatively high risk of suicide
(recurrent or treatment-resistant depression)
[116,117]. A Swedish study recently found that
the SSRIs were underrepresented and other
modern antidepressants overrepresented in
suicides compared with a control group
consisting of accidental and natural deaths, with
TCAs occurring equally in both groups [239].
The low mortality associated with SSRIs may in
part arise from their also being prescribed for
conditions other than depression. Moreover, the
SSRIs are generally tolerated at effective doses,
resulting in good compliance and eventual
improvement of the condition.
Besides inherent toxicity, perception of
toxicity, and prescription practices, the manner
of use is an important factor in postmortem drug
toxicity evaluations. In drug-alcohol poisonings
involving newer antidepressants (V), the manner
of death, indicating the putative manner of drug
use, was associated with the cause of death; of
cases with a newer antidepressant noted as the
most important finding, 46% were suicides and
42% accidental, whereas of cases with alcohol
noted as the most important finding, 96% were
accidental, with no suicides. Furthermore, the
median BAC in accidental deaths was
significantly higher than the median in suicides
(3.1‰ vs. 2.0‰), but similar to the median
found in a series of accidental alcohol
poisonings caused by ethanol alone (3.3‰).
Another confounding factor was that normal or
therapeutic concentrations of BDZs were present
in 65% of cases included in the drug-alcohol
part of Study V, which is more than the 40%
average for all BDZ findings in postmortem
cases undergoing drug screening [240].
In all, the newer antidepressants
investigated here, starting with mianserin
introduced in 1976, appear safer than the older
ones, indicating both successful drug
development and a shift from older to newer
drugs in prescription practices. This progress is
very welcome since antidepressants have
become increasingly important in the Western
world. In Finland, the consumption of
antidepressants has increased 600% in the past
14 years (Figure 13), with SSRIs accounting for
68% of current antidepressant consumption.
Citalopram surpassed the TCAs amitriptyline
and doxepin in 1992 and is today the most
common antidepressant in Finland, with the
second most common being fluoxetine. It is not
surprising therefore that citalopram-related
fatalities have also increased, although not to a
level comparable to the TCAs. In Austria, the
increasing use of newer antidepressants was
found not to result in an increase in suicidal
poisonings by these drugs [17]. In England, by
contrast, although a decrease in the number of
deaths involving antidepressants has been
observed since 1996, an 8% rise was seen from
2002 to 2003, with the biggest proportional
increase in SSRI-related deaths [241].
5 Implications for Interpretation
The forensic relevance of postmortem
toxicology results is most expediently
exemplified by cases of suspected homicide or
in traffic accident fatalities, but the results may
also reveal unsuspected drug abuse, erroneous
medication, or noncompliance. A special case
DISCUSSION
43
50
Other antidepressants
Sales (DDD/1000 inhabitants/day)
45
40
35
Monoamine oxidase type A inhibitors
Selective serotonin reuptake inhibitors
Nonselective monoamine reuptake inhibitors
30
25
20
15
10
5
0
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Figure 13. Sales of antidepressants in Finland in 1990-2004 (National Agency for Medicines).
relevant to this study is one where the forensic
toxicology results indicate fatal poisoning, but
where it is not clear, judging from the
circumstances, whether the manner of death is
accidental or suicide [242]. Most fatal
antidepressant poisonings are indeed suicides, as
discussed above. In Finland, the proportion of
suicides in fatal antidepressant poisonings has in
recent years ranged from 63% to 67% (Vuori
et al., unpublished data), but as many as 80% of
antidepressant poisonings were found to be
suicides in a Danish study [119]. On the other
hand, abuse of alcohol is often indicated in
antidepressant poisonings, e.g. in 38% of the
cases in the Danish study [119]. Deciding
between alcohol and antidepressants as a cause
of death and between accident and suicide as a
manner of death might therefore be difficult, and
thus, the manner of death in fatal poisonings
44
DISCUSSION
involving antidepressant poisonings may remain
undetermined [242].
Nevertheless, the results presented here
indicate that the possibility of accidental
poisoning should be considered seriously when
alcohol is present or when the drug considered
responsible for the poisoning is polymorphically
metabolized and the MR is inconsistent with
acute poisoning. The presence of any interacting
substances should also be taken into account.
Finally, it must be kept in mind that the
forensic pathologist may more readily attribute
fatalities to drugs generally perceived as
dangerous, resulting in drugs considered safer
not being implicated as cause of death even
when found in high concentrations in blood.
These perceptions are likely to affect the
proportion of deaths attributed to a drug, and,
consequently, the perceptions themselves.
CONCLUSIONS
These results on tramadol and amitriptyline are
among the first to demonstrate that analysis of
genetic variation of DMEs using postmortem
blood is possible. Although genetic factors in
drug metabolism were observed to have a
dominant role over various pathological
conditions, interacting substances, and other
confounding factors, the study did not reveal
any fatal poisonings to be associated with nonfunctional CYP2D6 or CYP2C19 genotypes.
Furthermore, alternative metabolic pathways
appear to compensate for a defective route thus
preventing accumulation of the parent drug in
gPMs. While genotyping does not seem
worthwhile in routine case work, it comprises a
valuable tool in elucidating the manner of death
in suspicious fatal poisoning cases, where
background information does not suggest
suicidal intent.
Our findings on common toxic drugs offer
a new viewpoint on fatal drug-alcohol
interactions with implications for drug safety.
Fatal drug poisonings often involve alcohol,
BDZs, or both, and an additive or synergistic
interaction may occur between some of the
components. An interaction appears to exist
between temazepam and alcohol, with
pronounced effects at high temazepam
concentrations. Diazepam, chlordiazepoxide,
and nordiazepam do not seem to affect ethanol
lethality in the range of BDZ concentrations
present in the data. In combination with alcohol,
diazepam and chlordiazepoxide therefore appear
safer than temazepam, although combining any
BDZs with alcohol should be avoided. Of the
most common drugs in the recent Finnish
poisoning panorama, amitriptyline, propoxyphene, and promazine appear to be especially
dangerous in combination with alcohol.
Although the newer antidepressants are
increasingly common findings in postmortem
investigations, they cause fewer deaths than
expected from the sales of antidepressants, and
they can also be considered safer in combination
with alcohol than TCAs and other common toxic
drugs. All in all, our results confirm that the
newer antidepressants are significantly safer
than other common drugs involved in fatal
intoxications. Furthermore, the differences in
toxicity between the newer antidepressants are
small.
In the future, more attention should be
given to the contention that some drug-alcohol
combinations are less safe than others. A safer
alternative could be chosen already at the
prescription stage, especially when indications
of alcohol abuse or suicide risk are present. In
interpretation of postmortem forensic toxicology
results, even a moderate concentration of
alcohol should be considered seriously.
However, in addition to the inherent drug
toxicity, behavioral aspects, prescribing
practices, and the popular perception of toxicity
should be considered in evaluating the combined
effect of alcohol and drugs in postmortem
forensic toxicology.
CONCLUSIONS
45
ACKNOWLEDGMENTS
This study was carried out at the Department of Forensic Medicine, University of Helsinki, in
2001-2004. Financial support from the Finnish Foundation for Alcohol Studies is gratefully
acknowledged.
I am indebted to Professor Erkki Vuori, Head of the Department and of the Forensic Toxicology
Division, for giving me the opportunity to prepare a doctoral thesis in Forensic Toxicology. I
sincerely thank him for providing excellent working facilities and for creating an enthusiastic
working atmosphere; he has always shown a genuine interest in the well-being of his personnel.
I am deeply grateful to my supervisors, Professor Antti Sajantila and Docent Ilkka Ojanperä, for
novel ideas and expert scientific advice. Their patience and positive attitude never failed me.
The pre-examiners of this thesis, Docent Kari Poikolainen and Docent Eero Mervaala, are thanked
for constructive and insightful comments. I also thank Carol Ann Pelli, HonBSc, for editing the
language of the manuscript.
I sincerely thank Dr. Merja Gergov and Johanna Sistonen, MSc, for their collaboration and expertise,
as well as Juhani Vartiovaara, MSc, and Jari Nokua, MSc, for everything related to data, computers,
and other electronic media. Special thanks go to Helena Liuha for her kind help in numerous
practical matters. I also wish to thank all of the personnel at the Forensic Toxicology Division for
bearing with me. I especially enjoyed working in the GC-MS group.
I am also grateful to my friends and colleagues at the Departments of Chemistry and Applied
Chemistry and Microbiology; they got me started in my graduate education and introduced me to the
world of science, and their companionship and encouragement have followed me ever since. My
friends from the world outside of work receive my heartfelt thanks for providing plenty of fun times
and enough shoulders to cry on. My warmest thanks go to Jukka for believing in me and keeping me
sane.
Finally, I would like to express my deepest gratitude to my mother for more than three decades of
love, encouragement, and support.
Helsinki, August 2005
Anna Koski
46
ACKNOWLEDGMENTS
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