interpretation of postmortem toxicology results...

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 adverse drug reaction BAC blood alcohol concentration BDZ benzodiazepine bp base pair CI confidence interval CNS central nervous system CYP cytochrome P450 CYP2C19 cytochrome P450 enzyme 2C19 CYP2C19 gene encoding CYP2C19 CYP2D6 cytochrome P450 enzyme 2D6 CYP2D6 gene encoding CYP2D6 DDD defined daily dose DME drug-metabolizing enzyme EHAT (E)-10-hydroxyamitriptyline EHNT (E)-10-hydroxynortriptyline EM extensive metabolizer (phenotype) FTI fatal toxicity index GC gas chromatography gEM genetically extensive metabolizer gPM genetically poor metabolizer gUM genetically ultra-rapid metabolizer ICD-10 International Classification of Diseases, 10th Revision IM intermediate metabolizer (phenotype) kb thousand base pairs LC/MS-MS liquid chromatography – tandem mass spectrometry LD50 median lethal dose, the dose required to kill 50% of the given population LIMS laboratory information management system M1 O-demethyltramadol M2 N-demethyltramadol, nortramadol M3 N,N-didemethyltramadol M4 O,N,N-tridemethyltramadol M5 O,N-didemethyltramadol MR metabolite ratio MRM multiple reaction monitoring MS mass spectrometry NNT N-demethylnortriptyline p significance level OPLC overpressured layer chromatography PCR polymerase chain reaction PM poor metabolizer (phenotype) RFLP restriction fragment length polymorphism SSRI selective serotonin reuptake inhibitor TCA tricyclic antidepressant TLC thin layer chromatography UM ultra-rapid metabolizer (phenotype) ZHAT (Z)-10-hydroxyamitriptyline ZHNT (Z)-10-hydroxynortriptyline

6 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 chromato-graphy, 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 post-mortem 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 patho-logist, 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

are often present in overdoses of other drugs [16,17]. Moreover, tolerance (and cross-tolerance) 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 bio-transformation in particular, is essential in interpreting the results, especially when the parent compound is either rapidly or poly-morphically 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

10 REVIEW OF THE LITERATURE

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 post-mortem 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, post-mortem 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 pharmaco-kinetic behavior usually differs between the iso-mers. 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].

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, post-mortem 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-6-glucuronide, 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


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

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 anti-depressants (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 co-ingestion 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 two-week 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 anti-depressants, 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 lipo-protein membranes of the brain [112]. However, this approach was not applicable to nonnarcotic poisons which exert their lethal effects by very specific mechanisms. Nonspecific membrane-stabilizing 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 anti-depressants 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


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

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]. Poly-morphisms 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 body-protecting 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 status

Substrate Expected product Consequence

Normal enzyme in normal quantities

+ Normal dose of drug

Normal metabolite Expected response (toxic effects rare)

+ Active parent drug Inactive metabolite Excessive response

+ Toxic parent drug Detoxified metabolite Toxic effects

Lack of functional enzyme, inhibited enzyme + (Pro)drug Active metabolite Lack of response,

undertreatment

+ Active parent drug Inactive metabolite Lack of response, undertreatment

+ Active parent drug Toxic metabolite Toxic effects

Excess of enzyme

+ (Pro)drug Active metabolite 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 pseudo-genes, 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 poly-morphic 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.

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, dextro-methorphan, 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].


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

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 up-modulated 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 ultra-rapid 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 dextro-methorphan [124]. In genotyping, the poly-morphic positions of the CYP2D6 gene are not detected directly in one step because of high sequence homology with neighboring pseudo-genes [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 poly-morphic positions are then identified using such techniques as restriction fragment length poly-morphism (RFLP) analysis [155], multiplex single-base extension reaction (e.g. SNaPshotTM) [156], real-time fluorometric melting point analysis [157], pyrosequencing [158], and oligo-nucleotide 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 anti-depressants (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 poly-morphisms, 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-demethyl-tramadol (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].


NMe2

OH

OMeNHMe

OH

OMe

NHMe

OH

OHNMe2

OH

OH

NH2

OH

OMe

NH2

OH

OH

CYP3A4 CYP3A4?

tramadol M2 M3

CYP2D6 CYP2D6? CYP2D6?

CYP3A4? CYP3A4?

M1 M5 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-didemethyl-tramadol (M3) by CYP3A4 and O-demethylated to O,N-didemethyltramadol (M5) by CYP2D6, possibly followed by formation of O,N,N-tri-demethyltramadol (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].

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-hydroxy-metabolite 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.


HHHH

NMe2

HHHH

NHMe

NMe2

OH

NHMe

OH

HHHH

NH2

CYP2C19 CYP2C19

amitriptyline nortriptyline NNT

CYP2D6 CYP2D6

CYP2C19

EHAT EHNT

Figure 4. Outline of amitriptyline metabolism in Phase 1, with formation of (E)-hydroxy-metabolites 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 post-mortem, 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 pheno-type, 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-


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 [185,194-196]. 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 CYP2D6-inhibiting 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 geno-typing, 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

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 dextro-methorphan/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 geno-typing 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 pharmaco-genetics 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


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 GABA-mediated inhibition of neuronal transmission by binding to a specific modulatory site in the

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 concentration-response 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 CNS-depressing 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.


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

range (mg/l) Reference

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 nitrogen-phosphorus-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-demethyl-tramadol (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.

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 screw-cap 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-methyl-1-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

28 MATERIALS AND METHODS

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 duplication-specific 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 (methotri-meprazine), the TCA doxepin or amitriptyline, the opioid analgesic propoxyphene (dextro-propoxyphene), 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

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 Mann-Whitney 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.

30 MATERIALS AND METHODS

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

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 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

-0.2

0

0.2

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0.6lo

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HN

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ZHA

T)

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

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

32 RESULTS

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*3 17 3.7 *4 64 14.0*5 12 2.6 *6 14 3.1 *9 3 0.7 *10 8 1.8 *1xN 9 2.0 *2xN 13 2.9 Total 456 100

2 Fatal Toxicity Indices (IV, V) FTIs were calculated for nine newer anti-depressants (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 anti-depressants was compared with the number of expected poisonings (V), revealing that venla-faxine, 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 Salesa Fatal poisonings p-valuec

Observed Expectedb Citalopram (SSRI) 84.0 104 114 >0.05 Fluoxetine (SSRI) 48.9 16 66 <0.001 Sertraline (SSRI) 15.7 6 21 0.003 Mirtazapine 14.5 37 20 0.017 Paroxetine (SSRI) 11.2 16 15 >0.05 Mianserin 10.9 33 15 0.006 Moclobemide 10.9 29 15 0.027 Venlafaxine 6.80 30 9 <0.001 Fluvoxamine (SSRI) 5.26 8 7 >0.05 Othersd 1.12 5 2 >0.05 Total 209.1 284 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 drug-alcohol 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. Drug FTI (95% CI)a Median BAC (95% CI) n BDZ+

(deaths/DDD/1000 inhabitants/year) (‰) (%)

Fluoxetine* 0.33 (0.19-0.53) 3.4 (3.0-3.9) 21 62 Citalopram* 1.2 (1.0-1.5) 2.9 (2.5-3.2) 80 63 Diltiazem 1.4 (1.1-1.8) 2.8 (2.0-3.3) 23 30 Zopiclone 0.96 (0.8-1.1) 2.7 (2.2-3.1) 38 24 Moclobemide* 2.7 (1.8-3.8) 2.7 (1.1-3.9) 9 56 Mirtazapine° 2.6 (1.8-3.5) 2.7 (2.3-3.2) 16 88 Levomepromazine 48 (42-53) 2.6 (2.0-2.9) 64 45 Temazepam 0.90 (0.7-1.1) 2.5 (2.2-2.7) 57 (100) Mianserin* 3.0 (2.1-4.3) 2.4 (1.7-2.9) 16 63 Venlafaxine° 4.4 (3.0-6.3) 2.4 (0.4-2.7) 8 75 Propoxyphene 33 (29-37) 1.7 (1.5-1.8) 67 25 Doxepin 21 (18-24) 1.6 (1.2-1.9) 27 33 Amitriptyline 12 (11-14) 1.6 (1.4-1.9) 50 46 Promazine 120 (110-140) 1.3 (1.1-1.6) 31 29 Fluvoxamine* 1.5 (0.66-3.0) nd - - - Sertraline* 0.38 (0.14-0.83) nd - - - Paroxetine* 1.4 (0.82-2.3) nd - - - 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

R2 = 0.70

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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 right-hand 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.

0 %

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Figure 11. Concentration-response curves in cases of fatal poisoning involving alcohol alone (—) and alcohol in combination with amitriptyline (– –), propoxyphene (–▲–), and promazine (–■–).

36 RESULTS

0

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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% (– –), 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.

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

38 DISCUSSION

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 time- point 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 pathophysio-logical 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 ami-triptyline 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

[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

40 DISCUSSION

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 pharmaco-kinetic 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 propoxy-phene 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 alcohol-negative 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

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 promazine-alcohol poisonings equaling the median BAC in pure alcohol poisonings. Furthermore, the FTIs of promazine, and to a lesser extent levome-promazine, 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

42 DISCUSSION

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

0

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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

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.

44 DISCUSSION

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 non-functional 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, propoxy-phene, 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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