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DET FARMACEUTISKE FAKULTET
KØBENHAVNS UNIVERSITET
PhD thesis
Naja Wessel Jacobsen
Disruption of the sex steroid hormone
balance caused by drugs
– Are aromatase enzyme assays sound predictors?
Academic advisor: Bent Halling-Sørensen
Submitted: 00/00/00
PHD THESIS BY NAJA WESSEL JACOBSEN PREFACE The present thesis is submitted as part of the requirements for obtaining a PhD degree at the Faculty of Pharmaceutical Sciences at the University of Copenhagen. The experimental work was conducted at the Section for Toxicology at the Department of Pharmaceutics and Analytical Chemistry, Faculty of Pharmaceutical Sciences, University of Copenhagen, Copenhagen, Denmark and at the Division of Toxicology and Risk Assessment, National Food Institute, Technical University of Denmark, Søborg, Denmark. This thesis offers a short synopsis and discussion of the six papers/manuscripts (I – VI) listed below. Additionally unpublished experiments are incorporated and presented in appropriate subsections. I Jacobsen NW, Halling‐Sørensen B & Birkved FK (2008). Inhibition of human aromatase complex (CYP19) by antiepileptic drugs. Toxicology in vitro. 22 (1), 146‐153. II Jacobsen NW, Yassin S, Nellemann C & Halling‐Sørensen B. Effects of selective serotonin reuptake inhibitors in aromatase supersomes and H295R cells. (Submitted 2011). III Jacobsen NW, Brooks BW & Halling‐Sørensen B. Suggesting a testing strategy for possible endocrine effects of drug metabolites. (Submitted 2011). IV Jacobsen NW, Heegaard AM, Birkved FK, Björklund B, Hansen M & Halling‐
Sørensen B. The effects of valproic acid on the steroid hormone balance in male rats. (Manuscript in preparation). V Nielsen FK, Hansen CH, Fey JA, Hansen M, Jacobsen NW, Halling‐Sørensen B, Björklund E & Styrishave B. H295R cells as a model for steroidogenic disruption: A broader perspective using simultaneous chemical analysis of 7 key steroid hormones. (Submitted 2011). VI Hansen M, Jacobsen NW, Nielsen FK, Björklund E, Styrishave B & Halling‐
Sørensen B (2011). Determination of steroid hormones in blood by GC‐MS/MS. Analytical and Bioanalytical Chemistry. 400 (10), 3409‐3417. i DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? SUPERVISORS Bent Halling‐Sørensen, Professor, PhD Department of Pharmaceutics and Analytical Chemistry Faculty of Pharmaceutical Sciences University of Copenhagen, Denmark Anne Marie Heegaard, Associate professor, PhD Department of Pharmacology and Pharmacotherapy Faculty of Pharmaceutical Sciences University of Copenhagen, Denmark Ole Jannik Bjerrum, Professor, Dr.med. Department of Pharmacology and Pharmacotherapy Faculty of Pharmaceutical Sciences University of Copenhagen, Denmark Franziska Kramer Birkved, PhD Toxicologist Novozymes A/S, Denmark ii PHD THESIS BY NAJA WESSEL JACOBSEN ACKNOWLEDGEMENTS Professor Bent Halling‐Sørensen is gratefully acknowledged for his superb supervision throughout the project; also Anne Marie Heegaard, Ole Jannik Bjerrum and Franziska Kramer Birkved are appreciated for discussions and comments on my plans and manuscripts. Christine Nellemann and Morten Andreasen, thank you for warmly welcoming me to FOOD DTU. And thank you for patiently teaching me how to work in the cell lab. I would like to thank my past and present colleagues at FARMA, KU particularly those at section of Toxicology for creating a great atmosphere both academically and socially. I owe my greatly improved techniques at table football all to you. My fellow PhD office mates Gitte Anskjær and Hannah Runnqvist, I owe you a special thank you, for always being there for a brief or long discussion on aspects of being a PhD student or life in general. Finally, I would like to thank my husband, Morten, for always being supportive and believing in me even when I did not. Thank you. Copenhagen, October 2011 Naja Wessel Jacobsen iii DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? ABSTRACT Over the past decades there has been increasing focus on the effects of endocrine disrupting compounds (EDCs) on humans. However, pharmaceuticals have not received much attention as potential EDCs, even though several classes of drugs e.g. antiepileptic drugs (AEDs), selective serotonin reuptake inhibitors (SSRIs) and fungicides have adverse effects on the reproductive system, and are able to cause a disruption in the sex steroid hormone balance. One target, which may be a causing factor in the occurrence of these adverse effects, is the aromatase enzyme (CYP19). CYP19 catalyses the conversion of androgens to estrogens and is vital for maintaining the sex steroid hormone balance. The aim of this thesis was to evaluate whether aromatase enzyme assays are useful as predictive tools for identifying drugs that can cause a disruption in the sex steroid hormone balance. In order to fulfill this aim, the studies described below were performed. 17 pharmaceuticals from the two drug‐classes AEDs and SSRIs were screened for their ability to interfere with activity of the aromatase enzyme in two aromatase enzyme assays. One of the assays was an already existing method, the other was an optimized method developed during the project. Of the seventeen tested compounds eight compounds (citalopram, ethosuximide, fluoxetine, fluvoxamine, paroxetine, sertraline, valproate, and tiagabine) were found to inhibit the aromatase enzyme in both assays. The effect of metabolites on the aromatase enzyme assay was evaluated using the SSRI sertraline. The evaluation was performed using both “compound by compound” testing and “effect based” testing. Based on the results a testing strategy for including metabolites in in‐vitro screening was drawn up. Three of the compounds identified as inhibitors of aromatase were further evaluated for their effect on the sex steroid hormone balance in more complex test systems. The H295R cell line assay, an established assay developed to identify compounds that can disrupt steroidogenesis was used to evaluate the two SSRIs sertraline and fluvoxamine. Male rats were used to further investigate the effects of the AED valproate. A novel analytical method was developed to analyze the steroid balance in plasma and tissues. The three compounds were all shown to cause a disruption in the sex steroid hormone balance in the more complex test‐systems. A thorough literature search was performed to obtain data on the effects of AEDs and SSRIs on the sex steroid hormone balance both in‐vitro, in‐vivo, and in humans. The literature data combined with the results of the studies performed on the aromatase enzyme assays, the H295R cell line, and on rats were used to evaluate the predictive value of the aromatase enzyme assays. Based on this data the aromatase enzyme assays appeared to be useful as a predictive tool for adverse effects of drugs on the sex steroid hormone balance. iv PHD THESIS BY NAJA WESSEL JACOBSEN RESUMÉ I løbet af de sidste årtier har der været stigende fokus på de effekter, hormonforstyrrende stoffer (EDCer) kan have på mennesker. Der har i den tid ikke været nogen særlig fokus på lægemidler som potentielle EDCer, til trods for at flere lægemidler fra forskellige lægemiddelgrupper har bivirkninger, som er relateret til reproduktionen eller er i stand til at påvirke kønshormonbalancen. Nogle eksempler er epilepsimidler (AEDer), selektive serotonin genoptagelseshæmmere (SSRIer) og fungicider. Et target som kan være vigtigt i forbindelsen med forekomsten af disse bivirkninger er enzymet aromatase (CYP19). CYP19 katalyserer omdannelsen af androgener til østrogener og er nødvendig for opretholdelsen af kønssteroidbalancen. Formålet med arbejdet beskrevet i denne afhandling er at evaluere, om aromataseenzym assays er anvendelige som prædiktive værktøjer til at identificere lægemidler, som potentielt kan påvirke kønshormonbalancen. For at evaluere dette er der udført en række studier, som kort er beskrevet nedenfor. Sytten lægemidler fra grupperne AEDer og SSRIer blev undersøgt i to aromataseenzym assays. Det ene assay var en allerede eksisterende metode. Det andet assay var en optimeret metode, udviklet i forbindelse med projektet. Af de sytten lægemidler var otte (citalopram, ethosuximide, fluoxetine, fluvoxamine, paroxetine, sertraline, valproate og tiagabine) i stand til at hæmme aromataseenzymet i begge assays. Effekten af lægemiddelmetabolitter blev undersøgt for SSRIen sertraline. Effekten af metabolitterne blev undersøgt ved hjælp af to metoder: “et stof af gangen” og “effektbaseret”. På baggrund af de opnåede resultater blev der foreslået en strategi, for hvordan det er muligt at inkludere effekten af metabolitter i in‐vitro screening. Tre lægemidler, som var i stand til at hæmme aromataseenzymet, blev undersøgt videre, for at vurdere, om de i var i stand til at påvirke kønshormonbalancen i mere komplekse testsystemer. Cellelinjen H295R, en etableret cellelinje som er udviklet til at identificere stoffer, der kan påvirke steroidgenesen, blev brugt til at evaluere effekten af de to SSRIer sertralin og fluvoxamin. Hanrotter blev anvendt til at undersøge effekten af AEDen valproat. En ny analysemetode til bestemmelse af kønssteroidniveauer i plasma og væv blev udviklet. De tre stoffer var alle i stand til at påvirke kønshormonbalancen i de mere komplekse testsystemer. Litteraturen blev gennemgået for at finde data vedrørende effekten af AEDer og SSRIer på kønshormonbalancen i in‐vitro studier, in‐vivo studier og i mennesker. Data fra litteraturen blev kombineret med resultaterne fra de udførte forsøg på enzymer, celler og dyr for at vurdere den prædiktive værdi af aromataseenzym assays. Baseret på de kombinerede data synes aromataseenzym assays at være brugbare som et prædiktivt værktøj til identifikation af lægemidler, som potentielt kan have uønskede effekter på kønshormonbalancen. v DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? vi PHD THESIS BY NAJA WESSEL JACOBSEN OUTLINE PREFACE .................................................................................................................................. I SUPERVISORS ........................................................................................................................... II ACKNOWLEDGEMENTS .............................................................................................................. III ABSTRACT .............................................................................................................................. IV RESUMÉ .................................................................................................................................. V 1. INTRODUCTION .................................................................................................................. 2 1.1. ENDOCRINE DISRUPTION ............................................................................................................................... 2 1.2. PREDICTIVE TOXICOLOGY ‐ USING IN‐VITRO MODELS TO PREDICT EFFECTS ON HUMANS AND ENVIRONMENT .................. 3 1.3. STEROIDOGENESIS, ENZYMES, AND STEROIDS ..................................................................................................... 5 1.4. DRUG RESEARCH AND DEVELOPMENT ............................................................................................................. 8 2. HYPOTHESIS, RESEARCH QUESTION AND STUDY DESIGN ............................................................ 12 2.1. HYPOTHESIS ............................................................................................................................................. 12 2.2. OBJECTIVES .............................................................................................................................................. 12 2.3. STUDY DESIGN .......................................................................................................................................... 12 3. THE ISOLATED AROMATASE ENZYME ..................................................................................... 14 3.1. METHODS ................................................................................................................................................ 14 3.2. THE EFFECTS OF SINGLE DRUGS ..................................................................................................................... 14 3.3. DRUG COMBINATIONS ................................................................................................................................ 18 3.4. CHAPTER SUMMARY ................................................................................................................................... 19 4. SCREENING TOOL FOR METABOLITE ASSESSMENT .................................................................... 20 4.1. SERTRALINE METABOLISM ........................................................................................................................... 20 4.2. THE COMPLEX MIXTURE OF UNKNOWNS ‐ EFFECT BASED TESTING ........................................................................ 21 4.3. THE EFFECT OF PURE METABOLITES ‐ COMPOUND BY COMPOUND ....................................................................... 22 4.4. COMBINING THE DATA TO SUGGEST A STRATEGY FOR EVALUATING ENDOCRINE EFFECTS OF METABOLITES .................... 23 4.5. CHAPTER SUMMARY ................................................................................................................................... 23 5. ADDING CELL WALLS AND COMPETING REACTIONS .................................................................. 26 5.1. INHIBITION OF THE AROMATASE ENZYME IN H295R CELLS ................................................................................. 27 5.2. OBTAINING MORE INFORMATION – MULTIPLE STEROID ANALYSIS ........................................................................ 28 5.3. CHAPTER SUMMARY ................................................................................................................................... 30 6. A CELL IN ITS NATURAL SURROUNDINGS ................................................................................ 31 6.1. ANALYTICAL METHODS ................................................................................................................................ 31 6.2. VALPROATE AND THE SYSTEMIC STEROID HORMONE BALANCE IN RATS .................................................................. 32 6.3. VALPROATE AND THE LOCAL STEROID HORMONE BALANCE IN RATS ...................................................................... 33 6.4. CHAPTER SUMMARY ................................................................................................................................... 35 7. COMPARING EFFECTS ACROSS TESTING LEVELS ........................................................................ 36 7.1. ANALYZING THE EFFECTS .............................................................................................................................. 36 7.2. CHAPTER SUMMARY ................................................................................................................................... 40 8. CONCLUSIONS ................................................................................................................. 41 9. EPILOGUE AND PERSPECTIVES ............................................................................................. 43 10. REFERENCES .................................................................................................................... 44 PAPER I ................................................................................................................................ 53 PAPER II ............................................................................................................................... 63 PAPER III .............................................................................................................................. 77 PAPER IV ............................................................................................................................. 95 PAPER V ............................................................................................................................ 107 PAPER VI ........................................................................................................................... 125 APPENDIX A ........................................................................................................................ 137 1 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? 1. INTRODUCTION 1.1. ENDOCRINE DISRUPTION In the late 1980 the American pharmacist Theo Colborn was the first to discover that manmade chemicals were reaching lake water, were taken up by animals, transferred to their offspring and were causing a decrease in the viability of the offspring (1). Around the same time Ana M Soto made the discovery that chemicals might also interfere with the endocrine system of humans as she discovered that leachable compounds from modified polystyrene were able to cause an estrogenic response in the human MCF7 cancer cell line (2). Following these findings Colborn, Soto and co‐workers published a review of the evidence showing a connection between endocrine disruption in both wildlife and humans and exposure to certain chemicals (3). Since these publications in the early nineties, focus on the area of endocrine disrupting compounds (EDCs) has increased vastly. Figure 1 shows the number of peer reviewed articles and reviews published within the field of endocrine disruption per year from 1990 to 2010. The focus of the research has been on identifying EDCs, findings ways to screen chemicals for endocrine effects, and on effects observed in humans and wildlife both in subpopulation being exposed to relatively high levels of chemicals, but also the effects observed in the normal population. 2 2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
1990
Number of publications
per year
EDCs have been defined as 800
“exogenous agents that interfere with the synthesis, secretion, 600
transport, binding, action, or eli‐
mination of natural hormones in 400
the body which are responsible for 200
the maintenance or homeostasis, reproduction, development and or 0
behavior” (4). As indicated in the definition, EDCs may act via a ple‐
Figure 1. The number of articles and reviews published per year thora of mechanisms including with the topic “endocrine disruptor*” OR “”endocrine nuclear hormone receptors, disrupting compound*”. Based on data from ISI web of knowledge February 2011. nonnuclear hormone receptors, nonsteroid receptors, orphan receptors, enzymatic pathways etc. (5). Compounds from very diverse classes of chemicals possess endocrine disrupting properties, and EDCs can be both natural chemicals, such as phytoestrogens and synthetic compounds such as industrial solvents and byproducts (polychlorinated biphenyls), plastics (bisphenol A), plasticizers (phthalates), pesticides (DDT), fungicides (vinclozolin) and drugs (synthetic estrogens such as diethylstilbestrol (DES), several selective serotonin inhibitors (SSRIs), and antiepileptic drugs (AEDs)) (5‐15). PHD THESIS BY NAJA WESSEL JACOBSEN It has been suggested that several disorders of the reproductive system may be linked to exposure to EDCs (5;16;17); an overview of the effects on males and females on different developmental stages is given in Table 1. The effects observed on fetuses include intrauterine growth retardation and malformation of the male genitals. During the prepubertal and pubertal stages EDCs may cause delayed or early puberty in both sexes. Furthermore, in males, small testis and high follicle‐stimulating hormone (FSH) values can be observed, and in females, polycystic ovaries may be observed. In adults, cancer may be caused by EDC exposure as well as disorders in spermatogenesis in males and ovulation disorders and disturbed lactation in females. Table 1. Disorders of the human reproductive system that may be linked to EDCs. Reprinted from the review Endocrine disrupting chemicals: An Endocrine Society Scientific Statement by Diamanti‐Kandaraksi et al (5). Fetal/neonatal Processes Prepubertal
Pubertal
Adult Intrauterine growth Adrenarche retardation Sexual differentiation Gonadarche Spermatogenesis Ovulation Hormonal control of prostate, breast, uterus and lactation Male disorders Intrauterine growth retardation Chryptorchidism Hypospadias Premature puberty Small testis and high FSH Early puberty Delayed puberty Oligospermia Testicular cancer Prostate hyperplasia Female disorders Intrauterine growth retardation Premature the‐
larche Peripheral preco‐
cious puberty Premature pub‐
arche Secondary central precocious pu‐
berty Polycystic ovary syndrome (PCOS) Delayed ovulatory cycles Vaginal adenocarcinoma Disorders of ovulation Benign breast disease Breast cancer Uterine fibroids Disturbed lactation Several of these described effects on the reproductive system have been observed on population level: Declining male reproductive health (16), problems with female reproductive health (17) and a decline in the age at onset of puberty (18). It has been suggested that the cause is unintentional EDC exposure. Furthermore several other severe health challenges such as attention deficit hyperactive disorder (ADHD) and the increasing prevalence of obesity, both unrelated to reproductive health, may be linked to EDC exposure (19;20). 1.2. PREDICTIVE TOXICOLOGY ‐ USING IN‐VITRO MODELS TO PREDICT EFFECTS ON HUMANS AND ENVIRONMENT The increasing awareness of the possible effects of chemicals on both humans and environment has caused the EU to increase the requirements on toxicological knowledge on chemicals used and produced within the union (21). As a consequence of the new regulation it has been estimated that 30,000 chemicals need to be toxicologically evaluated (22). Using the traditional and acknowledged toxicological in‐
3 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? vivo test methods, this will require approximately 5,000 animals per chemical and 12,000 animals if the chemical is a pesticide (22). From an animal welfare point of view this is an extremely large number of animals, and the time and resourced required to perform the studies will not be negligible. In addition, it is acknowledged that these animal models are not necessarily very good at predicting effects in humans (22;23). Consequently there has been a large interest in developing and validating good predictive toxicological models (24). Most predictive models are used to evaluate compounds for very specific effects using either enzymes or cells. If for instance the model is an enzyme based assay, the results can very clearly tell if a given compound is able to reduce or increase the activity of the enzyme, and compounds can be ranked for instance according to potency or maximum effect. The results will not give information about the bioavailability of the test compound, and the result can thus not tell if a test compound will reach the enzyme in its natural setting, and if it does, at what concentrations. There are also other limitations in many in‐vitro models that need to be kept in mind. Some of the most recognized are that in‐vitro systems often lack the ability to produce metabolites (25), three dimensional structures created between cells are challenging to obtain (e.g. tight junctions (26)) and natural interactions between cell types and between organs are not included. It is important that the results obtained using the predictive models can translate into effects observed in whole organisms, without an excess of false positives and false negatives. The false negatives must be very low in order to catch all problematic compounds; however the false positives must also not be too high due to the extra cost of further investigations in a second tier. This can often not be obtained using a single in‐vitro assay and batteries of in‐vitro assays or combinations of in‐vitro and in‐vivo assays are most likely necessary in most areas in order to predict effects (27). The screening batteries are used in a tiered approach, thus if effects are observed in the battery of in‐vitro test, more studies, often in‐vivo, are performed to evaluate the risk associated with the effects observed in‐vitro. If no effects are observed in the first tier no further evaluation is necessary. 1.2.1.
PREDICTING EDCS ‐ IN‐VITRO Determining if a chemical is an EDC is part of the toxicological evaluation, and many assays have been developed to screen for compounds intefering with the numerous targets connected to endocrine disruption (28‐30). However using only in‐vitro screening for detecting endocrine disruption is a challenging goal as a plethora of targets is involved (5). In addition, the endocrine system relies on signaling and feedback mechanisms between several organs e.g. the hypothalamus, the pituitary gland and the gonads/thyroid (the HPG and the HPT axes) (31). 4 PHD THESIS BY NAJA WESSEL JACOBSEN Consequently, at the moment no full screening battery consisting of only in‐vitro assays have been suggested for screening for EDCs. Instead combining the use of in‐vitro assays to screen for interactions with specific targets (e.g. the synthesis of steroid hormones and the interaction with steroid hormone receptors) with in‐vivo studies for determining effects on the signaling axes (HPG and HPT axes), has been suggested by the US Environmental Protection Agency (EPA) (32). The in‐vitro assays, recommended by EPA, used to detect interferences of compounds with steroidogenesis are the recombinant aromatase enzyme assay and the H295R cell assay. The aromatase enzyme assay is an enzymes based assay able to detect compounds that interfere directly with the aromatase enzyme (CYP19), which converts androgens to estrogens (29;33) + (papers I and II). H295R is a cell line which expresses the enzymes of the steroidogenesis pathway, the cell can be used to detect disruptions in the synthesis of all steroid hormones both at enzyme level and at gene expression level (30;34;35) + (papers II and IV). Below a brief overview of the steroid hormones and steroidogenesis is given. 1.3.
STEROIDOGENESIS, ENZYMES, AND STEROIDS Steroid hormones are vital for very diverse functions of the body ranging from maintaining pregnancy, maintaining the salt and water balance, influencing behavior and the development of primary, and secondary sexual characteristics (31;33;36‐39). Steroid hormones are not stored upon synthesis, and the circulation levels are thus primarily determined by the rate of their synthesis (31). An overview of steroidogenesis, the biological pathway for the synthesis of steroid hormones from cholesterol leading to the progestogens, the corticosteroids and the sex steroids including the androgens and estrogens, is given in Figure 2. The figure shows the hormones that are formed and the enzymes involved in their synthesis. Lacking the ability to synthesize one or more of the steroid hormones has severe effects on humans. The symptoms occurring in patients lacking enzymes of steroidogenesis have been described for several enzymes. Below, and in Table 2, a brief overview of symptoms associated with such deficiencies is given. •
•
CYP11A1, also known as cholesterol side‐chain cleavage enzyme converts cholesterol to progesterone, the common precursor for all steroid hormones. CYP11A1 deficiency is associated adrenal insufficiency, hypospadias and chryptorchidisms (40). CYP11B2 is necessary for the formation of aldosterone, lacking this enzyme is associated with salt‐wasting, lowered levels of sodium, elevated levels of potassium and poor growth (41). 5 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? •
CYP19A1 (aromatase) is necessary for the conversion of androgens to estrogens. In females reduced levels of aromatase enzymes causes pseudo‐hermaphrodism at birth. At the time of puberty CYP19 deficiency causes primary amenorrhea, lack of breast development, hypogonadism and cystic ovaries (36). In men, lack of aromatase has been associated with very tall stature, failure of epiphysis closure, severely delayed bone age, infertility, and android obesity (33;36). The effects of increased CYP19 have been studied in mice. Elevated enzyme levels were shown to cause imbalance in the steroid hormone levels with elevated estradiol, and reduced testosterone. Several other effects were observed, including malformation of the male genital, breast development in male mice, disrupted spermatogenesis, infertility and disruption in the bone homeostasis (42‐
44). Figure 2. The steroidogenesis pathway. Via the shown enzymatic processes the steroid hormones are produced from the common precursor cholesterol. In the figure the types of steroid are identified by different background colors: Progestogens (green), the corticosteroids; mineralocorticoids (yellow) and glucocorticoids (orange) and the sex steroid hormones, androgens (blue) and estrogens (red). •
6 A 5α‐reductase deficiency will cause the level of active androgens to decrease and result in feminization of males (31). PHD THESIS BY NAJA WESSEL JACOBSEN Several enzymes are necessary for the formation of cortisol, lacking the ability to form any of these enzymes (CYP21, CYP11B1, CYP17A1 and 3β‐HSD), will cause a lack of cortisol and increased levels of androgens. The symptoms are similar, though they may vary in severity. This group of disorders is called congenital adrenal hyperplasia (CAH). •
•
•
•
CYP21 deficiencies may cause salt waste and an overproduction of androgens in the adrenal glands which causes masculinization of females, both at birth or during puberty and adulthood (31). CYP11B1 deficiency often causes hypertension. Newborn girls have virilized external genitalia, and women may have hirtuism and oligomenorrhea. Both sexes experience precocious pseudopuberty (45). CYP17A1 deficiency has been connected with pseudo‐hermaphrodism and hypertension (31). 3β‐HSD deficiency can cause salt wasting, male pseudo‐hermaphrodism and premature pubarche, hirtuism and menstrual disorder (46) 1.3.1.
DRUGS AS DISRUPTORS OF STEROIDOGENESIS Several marketed pharmaceuticals are known to adversely affect the reproductive system or to cause disruption in the sex steroid hormone balance and are thus classified as EDCs (6‐15) – many of the observed effects are similar to the effects described in connection with EDCs (5) and the enzyme deficiency diseases mentioned above. Some examples are antiepileptic drugs (AEDs), selective serotonin reuptake inhibitors (SSRIs) and fungicides. Table 2 gives an overview of symptoms on the reproductive system observed in patients lacking specific enzymes (CYP17A1, CYP19, or CYP21) of steroidogenesis, or mice having excess enzyme (CYP19); correlated with examples of drugs that cause similar adverse effects during treatment. The table also presents effects of the drugs on specific enzymes of steroidogenesis observed in‐vitro. From Table 2 it can be seen that drugs from the three classes cause adverse effects that are similar to the symptoms in enzyme deficient patients. Furthermore for most of the observed adverse effects of the drugs, there are in‐vitro data indicating an interaction with the specific enzyme available. From the table it can be seen that some drugs particularly the fungicides have been shown to interact with several enzymes of steroidogenesis, and that all three drug classes have adverse effects similar to symptoms that appear in CYP19 deficiency. The combined data indicate that the enzymes of steroidogenesis may be important targets in connection with the occurrence of adverse effects on the reproductive system and the steroid hormone balance. 7 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? Table 2. Selected clinical manifestation of deficient or excessive expression of the enzymes of steroidogenesis coupled with of drugs from three classes with similar effects. The direct effects of pharmaceuticals on enzyme activity/expression are given when available. The pharmaceuticals included in this table are the antiepileptic drugs (AEDs), valproate, carbamazepine and phenytoin, the selective serotonin reuptake inhibitors (SSRIs), citalopram, fluoxetine, paroxetine, and sertraline and the fungicides, ketoconazol, posaconazol, micafungin and intraconazol. The examples of adverse effect of the drugs are solely obtained from publicly available product resumes. Effects on steroid hormones and the reproductive system Examples of drugs with similar adverse effects Observed effect on steroidogenesis of drugs in‐
vitro CYP17 deficiency (31) No production of sex steroid hormones Decreased level of testosterone observed with fungicides (6) Fungicides have been shown to inhibit CYP17 (47), and decrease the of androgen level (paper V) CYP21 deficiency (31) CYP19 deficiency (33;36) Increased CYP19 (mice) (42‐
44) No production of corticosteroids (31) Overproduction of androgens Decreased levels of corticosteroids observed with Fungicides have been shown fungicides (6) to inhibit CYP21 (48) Hyperandrogenism observed with AEDs (11) No production of estrogens Decreased levels of estrogens observed with AEDs (12) Android obesity Weight gain observed with AEDs (11) and SSRIs , (14;15;51) Primary amenorrhea Menstrual disorders is observed with AEDs (11;12), fungicides (6;7;9) and SSRIs (14;52) Cystic ovaries Polycystic ovaries are observed with AEDs (11) Infertility Male fertility may be influenced by fungicides (8) and SSRIs (51) Breast development in male mice Gynecomestia has been observed with fungicides (6), AEDs (14) and SSRIs (52) Disrupted spermatogenesis Lowered semen quality or SSRIs have been shown to sperm count has been increase the level of estradiol observed with fungicides (paper II). (6;8), AEDs (12) and SSRIs (51) Infertility Male fertility may be influenced by fungicides (8) and SSRIs (51) Fungicides have been shown to inhibit CYP19 (49) SSRIs have been shown to interfere with the activity of CYP19 (paper II) AEDs have been shown to interfere with the activity of CYP19 (paper I) (50) 1.4. DRUG RESEARCH AND DEVELOPMENT It is estimated that the average cost of bringing one new pharmaceutical to the market is approximately 800 million US$ and the process takes an average of 13.5 years (53). The vast amount of money is spend on the different phases of research and development included in the processes of making and marketing new effective and safe drugs. However, large amounts of money are also spend on compounds that fail as drug candidates somewhere along the line of drug discovery and development (54). 8 PHD THESIS BY NAJA WESSEL JACOBSEN Drug research and development can be divided into the following overall stages, see also Figure 3: • Discovery, where leads are found and optimized • Nonclinical studies, where drug can‐
didates are tested for efficacy and safety in‐vivo and in‐vitro • Clinical trials, where drug candidates are tested in healthy young males (phase I), in a small group of patients (phase II) and in a large group of patient (phase III) Figure 3. Overview of drug development with focus on safety related studies. On the left of the figure the three overall stages are given in black boxes. To the right of each black box the studies in this category that might identify adverse effects are listed. The background colors shifting from green to red indicate the amount of money invested in the drug. • Post‐marketing where approved drugs are administered to patients out‐
side organized trials. At this stage phar‐
maceutical companies are still required to collect data concerning adverse effects in connection with the drugs (pharmacovigilance). Clinical studies in population subgroups, like children, may be performed on marketed drugs (phase IV). The development of a drug candidate may be stopped due to a number of reasons; two major reasons are lack of effect or the occurrence of unacceptable adverse effects. Drug candidates may fail in any of the above mentioned steps. The later a candidate is discarded the more money has been invested in the compound, consequently discovering unacceptable properties as early as possible is very desirable (53‐55). 1.4.1.
RISK VERSUS BENEFIT When working with drugs a certain amount of adverse effects will almost always be acceptable, as drugs are administered in order to cure, prevent or relieve symptoms of some disease. However which adverse effects that are acceptable are highly dependent on a number of factors: The disease which is treated, the alternative treatments available, and the patient receiving the treatment. Generally the more serious a 9 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? condition is the more adverse effect are acceptable, particularly if the treatment offers significant improvements compared to already registered products. Some groups of patients are considered particularly sensitive and extra caution is necessary when these groups are exposed to drugs (or other xenobiotics). Pregnant women and children are some of the most sensitive groups. In pregnant women exposure to drugs may influence the development of the fetus with severe long term consequences (56;57). History has presented a few cases where exposure during pregnancy had severe consequences for the born children: Thalidomide administered against morning sickness caused severe malformation on the extremities in the children exposed in the womb. Another example is DES, a synthetic non‐steroidal estrogen used to prevent pregnancy losses, however approximately 30 years later a connection between the occurrence of rare vaginal cancers in young women and DES exposure in uterus was made. In addition to these two grave and well known examples, exposure to chemicals during sensitive windows of exposures in fetal life may be the underlying cause for several diseases that occur in adult life (5;56;57). 1.4.2.
NONCLINICAL SAFETY ASSESSMENT OF PHARMACEUTICALS During drug development several toxicological studies are required by the authorities to ensure the safety of the humans being exposed to the drug. The requirements increase during the development stages reflecting the increasing number of humans being exposed in the three clinical phases, the increasing length of exposure and the inclusion of more sensitive groups of patients being exposed e.g. women of childbearing potential and children. A full standard battery of nonclinical safety studies required for a pharmaceutical to gain marketing approval includes pharmacology studies, general toxicity studies, toxicokinetic‐ and pharmacokinetic studies, reproductive toxicity studies and genotoxicity studies. Other studies may be necessary depending on the specific drug. The majority of safety studies are performed in‐vivo (58). Despite the effort put into ensuring patient safety, ninety percent of experimental drugs fail in clinical studies because the used animal studies are not sufficient to predict effects on humans (23). Other drugs reach the market but are the withdrawn due to the discovery of severe adverse effects that was not caught in the limited number of patients exposed during the clinical trials. This is a serious problem, not only for the pharmaceutical companies, but also for the patients being exposed to drugs with possible serious adverse effects. For some very serious effects, such as genotoxicity and delayed ventricular repolarization, steps have been taken to catch drug candidates with the potential to cause such effects. This has been done by including in‐vitro screening batteries in the required pre‐clinical safety evaluation of drug candidates (59;60). 10 PHD THESIS BY NAJA WESSEL JACOBSEN 1.4.3.
PREDICTIVE TOXICOLOGY IN DRUG DISCOVERY AND DEVELOPMENT As mentioned above in‐vitro assays are included in the required safety evaluation of drugs in a few cases (59;60). In the mentioned examples the effects screened for have potential fatal outcomes for the patients. Naturally discovery of such adverse effects in animals or humans is very likely to stop the further development of a given drug candidate, and can even cause withdrawal of marketed drugs. Despite these few inclusions of in‐vitro assays in the regulatory guidelines, the core of the regulatory approach have not changed over the past 40 to 79 years (27). Despite the inclusion of only very few in‐vitro assays in the regulatory guidelines there is an increased focus on using in‐vitro screening before starting the traditional nonclinical in‐vivo studies (61). Several in‐vitro assays are used in the early nonclinical safety studies by some pharmaceutical companies to raise flags about potential adverse effects of drug leads. The focus of this in‐vitro screening is to detect the most serious and the most common adverse effects. Based on the information the most promising candidates are selected for further testing and development (61). The information from in‐vitro assays can also be used to identify potential adverse drug reactions that should be investigated further for the selected candidates. By including batteries of in‐vitro assays able to identify drug leads which have the potential to cause severe or even fatal adverse effects, the risk for the patients included in the clinical trials, patients treated post marketing, and the risk for the pharmaceutical companies can be reduced (61). A battery of in‐vitro assays, able to detect drug leads that act as endocrine disrupting compounds, could be of great value in the early drug discovery phases, as the current knowledge indicates that endocrine disruption may be the underlying cause for several severe diseases, such as some cancers, reduces fertility, PCOS, and obesity (5;16;17). 11 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? 2. HYPOTHESIS, RESEARCH QUESTION AND STUDY DESIGN 2.1. HYPOTHESIS The hypothesis of this study is that in‐vitro aromatase assays are useful tools for predicting adverse effects of drug candidates on the sex steroid hormone balance. 2.2. OBJECTIVES To investigate the hypothesis three objectives were formulated to guide the research: 1.
2.
3.
Investigate the ability of the test compounds to interfere with the aromatase enzyme in enzyme based assays Validate the effect observed directly on the aromatase enzyme in more complex test‐systems Evaluate the predictive value of aromatase enzyme assays 2.3. STUDY DESIGN In Figure 4, an overview of the stages of drug development is given and it is outlined how the papers prepared in connection with this thesis relate to the drug development process. Figure 4 is similar to Figure 3 in chapter 1; however in the present figure, the nonclinical studies consist of an initial screening, used to identify drug candidates with the ability to interfere with selected targets, followed by further evaluation of observed effects in additional specialized studies. This approach is put instead of the standardized set of mainly in‐vivo studies which is used today. It can be seen from the figure that the experimental work described in the papers relates to the nonclinical safety evaluation of drug candidates at two tiers: 1) toxicology screening, and 2) evaluation and further investigation of observed effects in more complex systems. The comparison used to evaluate the overall hypothesis of the thesis is based on the data from the papers, combined with information on the marketed drugs found in the literature. In the following sections the approaches used to reach each of the three objectives are described, with references to the papers prepared in the area. 2.3.1.
INVESTIGATE THE ABILITY OF THE TEST COMPOUNDS TO INTERFERE WITH THE AROMATASE ENZYME IN ENZYME BASED ASSAYS ‐ CHAPTERS 3 AND 4 Two aromatase enzyme assays were used to screen the selected drugs for their ability to directly interfere with the activity of the aromatase enzyme (papers I and II), furthermore relevant combinations of compounds were tested (paper I). 12 PHD THESIS BY NAJA WESSEL JACOBSEN Drug metabolites are formed naturally in humans during therapy; however drug metabolites are not naturally formed in all in‐vitro assays, thus different approaches for including metabolites in screening were tested (paper III). Figure 4. Chronological overview of drug development with increased use of predictive toxicology. On the left of the figure the three overall stages are given in black boxes. To the right of each black box the studies in this stage that might identify adverse effects are identified. On the rightmost part of the figure the sub studies described in this thesis are related to the drug development process. The background color shifting from green to red indicates the amount of money invested in the drug. 2.3.2.
VALIDATE THE EFFECT OBSERVED DIRECTLY ON THE AROMATASE ENZYME IN MORE COMPLEX TEST‐SYSTEMS – CHAPTERS 5 AND 6 Some of the drugs found to interfere with the aromatase enzyme were evaluated in more complex test‐systems to investigate the significance of the inhibition of the aromatase enzyme. Two such systems were used: The H295R cell line (papers II and V) and rats (paper IV); in the studies the sex steroid hormone levels were used to evaluate the effects. A method for simultaneous determination of several steroid hormones was developed (paper VI). 2.3.3.
EVALUATE THE PREDICTIVE VALUE OF AROMATASE ENZYME ASSAYS ‐
CHAPTER 7 Finally results from the 17 drugs studied in papers I‐IV were combined with additional data on the drugs obtained from the literature (appendix A). Based on the combined information the predictive value of the aromatase enzyme assays were evaluated. 13 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? 3. THE ISOLATED AROMATASE ENZYME The most simple test system able to detect effects on the aromatase enzyme (CYP19) consists of the aromatase enzyme (absent of other enzymes, organelles and cell walls); NADPH (a necessary cofactor for the aromatase enzyme); a substrate for the enzyme; the test compound; and a method for detecting either the formation of product or the depletion of substrate. Several methods with these properties have been described (29;62‐69) + (papers I and II). These systems offer information on the ability of a test compound to interfere directly with the enzyme. They are easy to interpret and often fast to perform making them ideal for high throughput screening (29). 3.1. METHODS Two aromatase assays with the above described properties were used in this project to evaluate the direct effects of drugs on the aromatase enzyme (papers I and II). In the first assay (Method A), developed by Stresser and coworkers (29), an artificial substrate for aromatase, dibenzyl fluorescein (DBF) was used. The substrate was incubated with aromatase supersomes, the cofactor NADPH and the test compounds; the formation of product was measured using fluorescence detection (papers I and II). In the second, a by us improved aromatase assay (Method B), the natural substrate for aromatase androstenedione (AN) was used. To determine effects of the pharmaceuticals, test compounds, AN, NADPH and aromatase supersomes were co‐
incubated. The amount of remaining substrate after incubation with aromatase was extracted into heptane using liquid‐liquid extraction and determined using a by us developed GC‐MS/MS method (paper II). All raw data were normalized against controls, and data from different days were pooled to obtain one dataset for each compound. The data was fitted with four pa‐
rameter logistic models (sigmoidal dose response curves) and the concentrations causing 50 % reduction in enzyme activity (EC50) were estimated using the curves. 3.2. THE EFFECTS OF SINGLE DRUGS 17 drugs from the two classes SSRIs and AEDs were investigated in the two aromatase enzyme assays. Figure 5 and Figure 6 shows dose response data for two AEDs and two SSRIs in the two aromatase assays. From the graphs it can be seen that the four pharma‐
ceuticals exhibit dose dependant effects on the enzyme in both assays. The data are nicely described with sigmoidal dose response curves (papers I and II). 14 PHD THESIS BY NAJA WESSEL JACOBSEN substrate: DBF
Ethosuximide
100
50
0
100
substrate: AN
Inhibition of CYP19 (%)
Tiagabine
50
0
The estimated EC50 values toge‐
ther with structu‐
res, physicoche‐
mical properties and pharmacoki‐
netic data are gi‐
ven in Table 3 for AEDs and Table 4 for SSRIs. 10 1
10 2 10 3
Control
10 0
(full inhib)
(no inhib)
Control
10 2
Control
10 1
(full inhib)
(no inhib)
Control
Of the 17 tested compounds eight (ethosuximide, ti‐
Drug concentration (mM)
agabine, valpro‐
ate and the five Figure 5. Concentration response data for two AEDs in two aromatase enzyme inhibition assays using different substrates. The data are fitted to sigmoidal dose SSRIs: Citalopram, response curve (paper I + unpublished data). fluoxetine, fluvo‐
xamine, paroxetine and sertraline) were shown to inhibit CYP19 in both assays, four compounds (phenobarbital, lamotrigine, oxcabazepine and phenytoin) had an effect when DBF was used as substrate, but not when AN was used. The remaining five compounds showed no effect in either assay. All compounds were tested up to their maximum solubility in aqueous solution. 10 -1 10 0
Control
(full inhib)
(no inhib)
Control
Control
(full inhib)
(no inhib)
Control
substrate: AN
Inhibition of CYP19 (%)
substrate: DBF
The eight compounds found to inhibit CYP19 in both assays had very diverse potencies. The most potent inhibitor was flu‐
Fluoxetine
Sertraline
voxamine (a SSRI) 100
with an EC50 va‐
lue [95% CI] of 50
3.08 µM [1.39 ‐ 0
6.80], the least potent inhibitor 100
was valproate (an 50
AED) with an EC50 value of 89.4 mM 0
[63.0 ‐ 127], gi‐
10 0 10 1 10 2 10 3
10 0 10 1 10 2 10 3
ving a span of more than 4 or‐
ders of magnitu‐
Drug concentration (µM)
de in the obser‐
Figure 6. Concentration response data for two SSRIs in two aromatase enzyme ved effect levels. inhibition assays using different substrates. The data are fitted to sigmoidal dose response curves (paper II). 15 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? Table 3. AEDs. Structures, physicochemical properties, pharmacokinetic data, and inhibition of the aromatase enzyme. Steady state plasma conc. in bc µM
Protein binding bd in %
Aromatase inhibition EC50 values in mM 2.45 7.0 236.269 20 ‐ 40 75 NI NI 0.38 9.5 141.168 300 ‐ 600 NA 23.3 [21.1 ‐ 26.7]78.0 [69.1 ‐ 88.0] ‐1.10 3.7; 10.7 171.237 10 ‐ 40 <3 NI NI 0.99 5.7 256.091 10 ‐ 30 55 * 45% (0.39) NI 1.11 NA 252.268 45 ‐ 90 40 * 50% (0.40) NI 1.47 7.4 232.235 65 ‐ 130 45‐60 1.57 [1.34 ‐ 1.80] NI 2.47 8.3 252.268 40 ‐ 80 70 ‐ 95 * 32% (3.3) NI 0.91 NA 218.252 NA NA NI NI 2.04 3.3; 9.4 375.55 40 ‐ 140 96 1.40 [1.28 ‐ 1.53] 2.21 [2.14 ‐ 2.29] ‐1.07 NA 339.363 6 ‐ 30 15 NI NI ‐0.85 4.6 166.20 350 ‐ 700 85 ‐ 95 49.6 [45.1 ‐ 56.6] 89.4 [63.0 ‐ 127] ‐2.16 4.0; 9.7 129.157 NA 0 NI NI a
Compound CAS # Chemical structure Carbamazepine 298‐46‐4
Ethosuximide 77‐67‐8 Gabapentin 60142‐96‐3
Lamotrigine 84057‐84‐1
Oxcarbazepine 28721‐07‐5
Log P b pKa – values
Mw in g/mol e
Method A f Method B
O
Phenobarbital 50‐06‐6 HN
O
NH
O
Phenytoin 57‐41‐0
Primidone 125‐33‐7
Tiagabine 115103‐54‐3 Topiramate 97240 ‐ 79‐4
Valproate 1069‐66‐5 Vigabatrin 60643‐86‐9
NA – not available; NI – no observed inhibition of the aromatase enzyme; * inhibition given as the maximum obtained inhibition and the corresponding concentration. a b
c
d
e
f
Values obtained using EPI SuiteTM v4.0 (70), (71), (72), (73), (paper I), unpublished data. 16 PHD THESIS BY NAJA WESSEL JACOBSEN The EC50 values of the AEDs were in the mM range and the EC50 values of the SSRIs were in the µM range. When comparing the EC50 values obtained in the two assays for the eight compounds found to inhibit in both assays it was apparent that the values were not identical, but similar for most compounds. This is also the trend others have described when comparing inhibition of the aromatase enzyme in different assays (74). The observed differences between the two assays (Method A and B) indicate that either the sensitivities of the two assays are slightly different or that some of the compounds are able to interfere with the detection of product/substrate in either assay. Table 4. SSRIs. Structures, physicochemical properties, pharmacokinetic data, and inhibition of CYP19 Log P pKa ‐ values a Mw in g/mol Steady state plasma conc. in b µM
Protein binding in b %
Aromatase inhibition c EC50 values in µM
3.7 9.1 324.4 0.12 ‐ 0.92 82 610 [591 ‐ 716] 55.8 [21.7 ‐ 144] 4.1 9.2 309.3 0.29 ‐ 0.97 95 246 [201 ‐ 301] 249 [173 ‐ 358] 3.1 8.2 318.3 0.063 ‐ 1.6 77 7.84 [2.56 ‐ 24.1] 3.08 [1.39 ‐ 6.80] 2.9 9.6 329.3 0.027 ‐ 1.6 93 142 [92.9 ‐ 217] 68.5 [28.5 ‐ 165] 5.3 8.9 306.2 0.065 ‐ 0.65 98.5 13.1 [9.54 ‐ 17.9] 90.6 [52.4 ‐ 157] a
Compound CAS # Chemical structure Citalopram 59729‐33‐8 Fluoxetine 54910 ‐ 89‐3 Fluvoxamine 54739‐18‐3 Paroxetine 61869‐08‐7 Sertraline 79617‐96‐2 a
Method A c Method B
b
Values obtained using EPI SuiteTM v4.0 (70), (75) in which Linsay De Vane gives the concentrations in ng/ml. Here the values are given as µM for easy comparison with the EC50 values. The molar concentrations c
have been calculated using the shown molar weights (Mw), (paper II). Tables 3 and 4 give some pharmacokinetic data for the investigated pharmaceuticals. Compared to the effect levels presented in the tables for most compounds, the plasma levels are fairly high. The plasma levels of the AEDs range from 6 µM (topiramate) to 700 µM (valproate). The plasma levels of the SSRIs during steady state treatment are lower, ranging from 26 nM (paroxetine) to 1.6 µM (fluvoxamine and paroxetine). In addition many of the compounds are to a very large extend bound to plasma proteins (percentages are given in Tables 3 and 4). Seven of the twelve AEDs are bound 40 % or 17 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? more to plasma proteins. For the SSRIs the percent protein binding range from 77 to 98 %. Combined, the information on plasma concentration, protein binding, and the by us observed effect levels, indicate that the risk of acute effects of these drugs due to an interference with the aromatase enzyme is unlikely. However, some drugs are found in much higher levels in organs than in circulating plasma, e.g. the organ levels of sertraline are 20 ‐ 50 times higher than the plasma concentration (75;76). In addition to this the aromatase enzyme is placed intracellular in the endoplasmatic reticulum and the exact concentration at this site is at best difficult to estimate. 3.3. DRUG COMBINATIONS It is part of some therapeutic strategies to combine drugs to improve the therapeutic effect, for instance by reaching different targets. In some cases, though not as common, the adverse effects as well as the therapeutic effects are additive or even synergistic (77;78). Two therapeutically relevant binary combinations of AEDs were studied in aromatase enzyme assays (Method A) to investigate if the drugs influenced each other’s ability to interfere with the aromatase enzyme (paper I). To evaluate the effect of mixing the compounds an isobologram was constructed. An isobologram is constructed using a specific (chosen) effect concentration (here EC50 values). The values for the pure compounds are plotted on the axes and between the points a straight line is drawn, confidence intervals can be calculated for the line. The line represents the concentration of each of the two components in a mixture having the specified effect (e.g. EC50). If an EC50 value of a mixture is determined and plotted above or below the line (and its confidence intervals) antagonistic or synergistic effects 2.0
of the compounds in the mixture are indicated, respectively (79). Phenobarbital (mM)
1.5
Terapeutic
mixture
antagonistic
effect
Figure 7 presents an isobologram of the effect of mixing the two aromatase inhibitors 1.0
additive effect
phenobarbital and valproate. Besides the two Equipotent
pure compounds, two mixtures with different mixture
0.5
ratios were tested (a mixture based on the ratios between therapeutically relevant synergistic
effect
0.0
concentration and a mixture based on 0
20
40
60
Valproate (mM)
equipotency) the EC50 values of the mixtures Figure 7.
Isobologram of the effects, measured were determined and plotted together with as EC50 values, of mixtures of phenobarbital and the EC50 values of the pure compounds. The valproate on the aromatase enzyme (paper I). mixtures had EC50 values that very neatly fitted the line for additive effects (paper I). The effect of adding the non‐inhibitor 18 PHD THESIS BY NAJA WESSEL JACOBSEN carbamazepine to the inhibitor valproate was also investigated (paper I). Carbamazepine did not influence the effect valproate had on aromatase. Using polytherapy to treat epilepsy is prevalent as approximately 30% of epileptic patients do not respond well to monotherapy, however combinations should be chosen with care as both effects and adverse effects may be additive or synergistic. One of the commonly used mixtures is valproate and carbamazepine, this combination is advocated due to synergism in efficacy without synergism in adverse effects. The combination of phenobarbital and valproate is advised against as this mixture has both additive effects and additive adverse effects (77;78). 3.4. CHAPTER SUMMARY Pharmaceuticals from the two drug classes AEDs and SSRIs have adverse effects on the reproductive systems, and are able to cause changes in the sex steroid hormone levels in humans and animals. Several of the effects appear to be similar to symptoms observed in CYP19 deficient humans. Drugs from these two classes were thus chosen as test compounds for the evaluation of the value of aromatase enzyme assays as predictive tools. In this chapter, 17 pharmaceuticals from the two drug classes SSRIs and AEDs were tested in two enzymatic aromatase inhibition assays. This was done as a first step in evaluating if the aromatase enzyme might have a role in the occurrence of the observed adverse effects associated with the pharmaceuticals, and could thus be useful as a predictive tool. Eight compounds (ethosuximide, tiagabine, valproate, and all the five tested SSRIs: Citalopram, fluoxetine, fluvoxamine, paroxetine and sertraline) were found to inhibit the activity of the enzyme in the two assays. Five compounds (carbamazepine, gabapentin, primidone, topiramate, and vigabatrine) did not influence the activity of the aromatase enzyme and four compounds (phenobarbital, lamotrigine, oxcabazepine and phenytoin) showed inhibition in one assay but not the other. Two binary mixtures including valproate were tested in aromatase enzyme assay A, both combinations indicated that mixing AEDs caused an additive effect on the aromatase enzyme. The five compounds that did not interfere with the aromatase enzyme in either assay do apparently not have the ability to inhibit the aromatase enzyme; consequently, there is no need to investigate this particular effect further. The eleven compounds shown to have the ability to change the activity of the aromatase enzyme in one or both assays should be investigated in other systems to validate the observed effects and investigate if this compound property (inhibition of aromatase) is relevant in a more complex test system, for instance a cell or an animal. 19 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? 4. SCREENING TOOL FOR METABOLITE ASSESSMENT In the previous chapter direct effects pharmaceuticals were investigated, this is often the case when in‐vitro systems are used to predict effects. However, when the human body is exposed to xenobiotica like pharmaceuticals the body attempts to reduce the exposure to the compound and thus the potential for toxic effects. This is done by metabolizing the compounds, rendering them more hydrophilic and thus more excrete‐
able (80). Pharmaceuticals are often extensively metabolized and often to a large number of different metabolites. In many cases the metabolites formed are safe and readily excreted however in some cases the metabolites have longer half‐lives than their parent compounds, reach higher levels, or have increased effects (81‐86). Including the effects of metabolites is therefore vital when evaluating effects of drugs. A traditional approach to investigate the effects of metabolites is to perform individual concentration response studies on known metabolites. However, the effects of metabolites may be evaluated using at least two different approaches: “Effect based” testing (82;83;86;87) and “Compound by compound” testing (87‐89). In paper III these approaches were compared using the SSRI sertraline as the model compound. Sertraline was chosen due to its potency as an aromatase inhibitor and due to its high degree of metabolization. Based on the results a combined strategy for evaluating the effects of drug metabolites in‐vitro was proposed. The following sections describe the different approaches and the resulting testing strategy. 4.1. SERTRALINE METABOLISM Figure 8. Schematic presentation of selected phase I metabolites of sertraline (paper III). 20 Sertraline is metabolized to a range of phase I and phase II metabolites (90). The primary metabolite desmethylsertraline (DMSer) is pharmacologically active and the plasma concentration of the me‐
tabolite exceeds the level of sertraline du‐
ring treatment. Pharmacologically inactive metabolites are formed from sertraline and DMSer. The five major phase I me‐
tabolites are shown in Figure 8. Several of these phase I metabolites are conjugated to form glucuronides before excretion. The enzymes involved in the metabolism include cytochrome P450 enzymes, mono‐
amine oxidases and uridine diphosphoglu‐
PHD THESIS BY NAJA WESSEL JACOBSEN curonic acid transferases. Each step of the metabolism can be catalyzed by several enzymes (76;90;91). 4.2. THE COMPLEX MIXTURE OF UNKNOWNS ‐ EFFECT BASED TESTING For the effect based testing a mixture of metabolites was produced in‐vitro.The purpose of this was to mimic the complex mixture of metabolites, including minor metabolites, which the body is exposed to during pharmacological treatment. Chromatograms of sertraline before and after metabolism in liver microsomes are shown in Figure 9. OHSer
6
Sertraline
4
2
0
2.5
5.0
7.5
10.0
12.5
15.0
Retention time (min)
Figure 9. Chromatograms of sertraline metabolism. The chromatograms show the conversion of sertraline by liver microsomes in the presence of NADPH at A) the initiation of the incubation, and B) at the end of the incubation (paper III). *
*
*
20
*
*
50
40
*
150+50
100+50
50+50
150
0
100
DMSer
B: 3 hours
Sertraline+
MetabSer
75
0
60
50
10
*
Sertraline
MetabBlank
Absorbance at λ 220nm
20
8
MetabSer
80
Sertraline
A: 0 hours
Inhibition of CYP19 (%)
30
Concentration (µM)
Figure 10. Bar chart of effect of metabolized sertraline (MetabSer) on CYP19. The inhibition is shown as percentage inhibition, the error bars are given in SEM. The white bars show the effect of MetabSer in two concentration levels and the effect of MetabBlank ( buffer treated with metabolizing enzymes) equivalent to a metabolite and sertraline concentration of 0 µM. The black bars give the effect of sertraline alone at three concentration levels. The grey bars give the effect of sertraline at three concentration levels in combination with MetabSer at one level. *: Significant effect on the enzyme activity; p < 0.05 (paper III). The produced mixture of metabolites (MetabSer) was tested alone and in combination with pure sertraline for its effect on CYP19 in aromatase enzyme assay method B (Figure 10). In the bar chart in Figure 10 it is shown how MetabSer was able to inhibit the aromatase enzyme (white bars), though less so than sertraline (black bars). In fact, when sertraline was added to MetabSer (gray bar), no statistical difference was observed between the effect of this mixture and sertraline. These observations lead to the conclusion that the combined sertraline metabolites produced by liver microsomes only had little to no inhibitory effect on CYP19 relative to the parent compound. 21 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? 4.3. THE EFFECT OF PURE METABOLITES ‐ COMPOUND BY COMPOUND Three known phase I metabolites of sertraline, cis‐DMSer, trans‐DMSer, and hydroxyl ketone sertraline (OHSer) were purchased and tested for their ability to interfere with the activity of the aromatase enzyme using the improved aromatase enzyme assay, method B, presented in paper II. Cis‐DMSer and trans‐DMSer were both more potent inhibitors of the aromatase enzyme than the parent compound sertraline, the EC50 values of the three compounds were 14.9 µM [8.94 – 24.7], 13.2 [9.13 – 19.0], and 88.2 µM [52.3 ‐ 149], respectively. The third metabolite OHSer did not inhibit the activity of the aromatase enzyme when tested alone (paper III). Several combination studies of the metabolites and sertraline were designed and tested. Figure 11 shows calculated (dotted lines) and experimental dose response curves (full lines) for the effect of three‐ and four‐compound mixtures of sertraline and its metabolites on CYP19. 100
A
B
C
50
* E≠ T
10 3
Total drug and metabolite concentration (µM)
10 -1
10 0
10 1
10 2
10 3
Control
10 2
(full inhib)
10 1
(no inhib)
10 0
Control
10 -1
Control
10 3
* E≠ T
(full inhib)
10 2
(no inhib)
10 1
Control
10 0
Control
10 -1
(full inhib)
(no inhib)
0
Control
Inhibition of CYP19 (%)
The mixture studies showed that the effect of sertraline and the DMSer metabolites were additive (Figure 11A). However including OHSer in a mixture caused the observed aromatase inhibition to be less than expected based on the inhibitory abilities of the single compounds in the mixture (Figure 11 B and C), this unexplained effect of OHSer was also observed in binary mixtures (paper III) . Figure 11. Calculated and experimental inhibition of CYP19 for mixtures of standardized sertraline and the standardized metabolites cis‐DMSer, trans‐DMSer and OHSer. Experimental data (E) are plotted as mean inhibition in (%) with error bars showing the SEM, against the total concentration (µM) of sertraline and metabolites on a log scale. The data are fitted to sigmoidal concentration response curves, shown with full lines. The dotted lines are the calculated or theoretical effects (T) of combining the compounds calculated by using the ratio between compounds and the inhibitory values for each compound by assuming additive effects. Graph A) An equipotent mixture (EQPT) was composed of the three compounds sertraline, cis‐DMSer and trans‐DMSer and the ratio between the compounds was based on the potencies as EC50 values of the compounds, so each compound theoretically contributed the same to the inhibition. Graph B) An equimolar mixture (EQML) was composed of the four compounds sertraline, cis‐DMSer, trans‐
DMSer and OHSer; the four compounds are mixed in the same molar concentration. Graph C) A simulated liver microsome metabolite mixture composed of the four compounds sertraline, cis‐
DMSer, trans‐DMSer and OHSer. The ratio between the compounds is based on the ratio found in the mixture MetabSer formed in liver microsomes. *: The calculated and experimental dose response curves are different; p<0.05 (paper III). 22 PHD THESIS BY NAJA WESSEL JACOBSEN 4.4. COMBINING THE DATA TO SUGGEST A STRATEGY FOR EVALUATING ENDOCRINE EFFECTS OF METABOLITES Even though some metabolites of sertraline (cis‐DMSer and trans‐DMSer) were shown to inhibit the aromatase enzyme more potently than the parent compound, the combined effect of mixtures of the three metabolites and sertraline (Figure 11) was similar to the magnitude of aromatase inhibition exerted by the parent compound sertraline (Figure 6). Testing the mixture of metabolites formed in liver microsomes showed that this mixture was even less potent, indicating that an aggregate mixture of metabolites formed by liver microsomes (Figure 10) was less potent than a pure mixture of sertraline metabolite standards and the parent compound. Thus, other unknown metabolites appeared to have contributed to the overall observed inhibitory effect of the mixture MetabSer on aromatase. This observation underlines that if only known or major metabolites are included the effect of a compound and its metabolites may be over or underestimated. It is thus important to include all (phase I) metabolites when screening for effects of drugs. Based on our results (paper III), supported by data from the literature (83‐85), and on the criteria that all metabolites should be investigated a five step testing strategy involving both “effect based” testing and “compound by compound” testing was suggested for initial evaluation of metabolites (paper III). A decision tree describing the steps in the test is presented in Figure 12. The strategy is designed to catch compounds that have problematic metabolites, meaning metabolites that are more potent than the parent compound or posseses other effects than the parent compound. If problematic metabolites are indicated in one step of the decision tree, the effect of the metabolites will have to be evaluated according to the next step of the decision tree etc. This strategy makes it possible to include the effects of metabolites when screening compounds for the ability to interfere with the activity of the aromatase enzyme 4.5. CHAPTER SUMMARY One of the most recognized limitations of in‐vitro assays is the limited metabolizing capability of most in‐vitro assay (25). This can in some cases be very problematic as some metabolites are more harmful that their parent compound (81‐86). In such cases the effects determined in in‐vitro assays may underestimate the effect of a compound in an animal or a human where metabolites are formed. This limitation can be reduced by including metabolites when testing compounds in in‐vitro assays. Different approaches for evaluating the effects of metabolites in the aromatase enzyme assays were tested and compared using the model compound sertraline, namely “effect based” testing and “compound by compound” testing. The results showed that the two methods complemented each other. The compound by compound testing approach was 23 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? Figure 12. Proposed procedure for evaluating the potential endocrine effects of drug metabolites. A) Scheme presenting the screening steps in evaluating the effects of metabolites in‐vitro, step 1 to 4 is based on the principles of “effect based” testing; step 5 is based on the procedures of “compound by compound” testing. B) Illustration of the “effect based” testing of metabolites, the numbers in the figure refers to the steps in figure 12A. In the illustration a drug (presented as capsules) is metabolized in‐vitro (step 1), the effect of the mixture is investigated (step 3) and the combined effect of metabolite mixture and pure drug is investigated (step 4). C) Fictive concentration response curves for a drug and three metabolites, the parent drug (gray/white dotted line) has the ability to interfere with a test system, the metabolites II (full gray line) and III (gray/black dotted line) has the same maximum effect on the test system as the parent drug but the effect levels vary. The metabolite III (full black line) influences the test system at lower concentrations than the parent drug, but the maximum effect level is lower. The effects of metabolites of the type III may be not be detected in many test systems as the continuous low effect may be misinterpreted as zero effect. D) Illustration of the “compound by compound” testing, the number in the figure refers to the steps in figure 12A. In the illustration the effect of standardized parent compound and metabolites are investigated one by one and in mixtures (step 5). 24 PHD THESIS BY NAJA WESSEL JACOBSEN able to give specific information about the potencies of single metabolites and simple mixtures of metabolites, whereas the effect based approach could be used for evaluation of very complex mixtures of metabolites formed in‐vitro. By combining data from both approaches a rough estimate of the effect of unknown metabolites could be given. Based on our results a tool for metabolite assessment, consisting of a five step decision tree, was developed to suggest a pragmatic way to assess if metabolites of a drug are more or less harmful than the parent compound, and if metabolites may significantly contribute to any harmful effect of the drug. According to the suggested decision tree, advancement from one level to the next is only necessary when result indicate that metabolites might have unwanted effects. This approach was suggested to ensure the evaluation of all metabolites in‐vitro, without spending an excess of time on unproblematic compounds. 25 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? 5. ADDING CELL WALLS AND COMPETING REACTIONS The test systems used to evaluate the effects of pharmaceuticals in the previous chapters (papers I, II and III), were all enzymatic systems without cell walls. In this chapter the effects of selected compounds shown to interfere with the aromatase enzyme in chapter 3 are investigated in a more complex setting, a cell (paper II). Figure 13. Reprint of figure 2. Overview of the enzymatic processes related to steroidogenesis that occur in H295R cells. Via the shown enzymatic processes the steroid hormones are produced from the common precursor cholesterol. In the figure the types of steroids are identified by different background colors: Progestogens (green), the corticosteroids; mineralocorticoids (yellow) and glucocorticoids (orange) and the sex steroid hormones, androgens (blue) and estrogens (red). Compared to in‐vitro studies with pure enzymes, cells have several properties that make them more realistic test‐systems. Cells have walls separating the intracellular environment, where the aromatase enzyme is present, from the extracellular environment, where the test compounds are added. The test compounds need to be able to pass the cell membrane in order to reach the target; this makes the bioavailability of a cell based assay more similar to the situation in a human or an animal than an enzyme based assay where no part of the natural bioavailability is included. However, when conducting the studies on cells it is only possible to know the test 26 PHD THESIS BY NAJA WESSEL JACOBSEN compound concentration added to the cell medium, and this is not necessarily the same as the concentration that reaches the target. In cells several other processes occur which might influence the observed effects of a test compound. One example is the presence of alternative targets for the same compound; this could be either on the enzyme level or the gene transcription level. Another example is the presence of other enzymes capable of transforming a substrate of interest. 5.1. INHIBITION OF THE AROMATASE ENZYME IN H295R CELLS The cell chosen for this work is the H295R cell line; this particular cell has the ability to express the entire steroidogenesis of which the aromatase enzyme (CYP 19) is one enzyme. Figure 13 shows gives an overview of the enzymatic processes related to steroidogenesis that occurs in the H295R cell. Fluvoxamine and sertraline were investigated in the H295R cell line. Both compounds influenced the hormone balance; however the effects of the compounds were quite different (Figure 14). Fluvoxamine caused significant decrease in the levels of both E2β and TS, the level of E2β was affected by slightly lower concentrations of fluvoxamine compared to TS. The observed difference might be due to an effect on the aromatase enzyme. However the decrease in TS indicates that other cellular processes are interrupted by fluvoxamine as well. % of Control
Testosterone
150
Estradiol
Fluvoxamine
100
Progesterone
Sertraline
*
*
**
50
*
*
**
**
*
*
*
*
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*
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ol
ntr
o
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ol
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Figure 14. The effect of the SSRIs fluvoxamine and sertraline on the steroid hormone production of the H295R cell line. *p < 0.05 compared to control. Sertraline had a general toxic effect on the H295R cells (cell growth inhibition), at the levels found to inhibit the aromatase enzyme in supersomes. However, compound concentrations below the toxic level, significantly increased the E2β concentration and lowered the concentration of TS and (progesterone) PRO. The increase in E2β might be explained by an activation of the aromatase enzyme, but the effects observed on the 27 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? hormone balance might also be due to influences on other cellular processes than the direct conversion of androgens to estrogens. The underlying cause of the unexplained effects on the hormone levels by fluvoxamine and sertraline mentioned above was not investigated. More information could have been obtained by extending the validated use of the H295R cell line (30;34;92), either by analyzing the enzyme levels (35;50;93‐95), or by analyzing the levels of additional steroid hormones expressed by the cells (paper V). Some of the compounds we found to inhibit the aromatase enzyme in the enzyme assays (Method A and B, see chapter 3), have been investigated in the H295R cell line by other research groups. Gracia et al investigated the effects of fluoxetine on the hormone production (TS, PRO and E2β) and on the gene expression (CYP11β2, CYP19, CYP17 and 3βHSD2) of H295R cells. They tested one concentration 1 µg/L (3.2 nM) and found an increase in the CYP11β2 expression; the other measured parameters were not significantly altered (35). The concentration used by Gracia et al, was very low compared to the EC50 values we observed in the aromatase assays (~250 µM). Gustavsen et al investigated the effects of three AEDs (valproate, lamotrigine and carbamazepine) on steroid hormone levels and on gene expression in the H295R cell line. They found that only valproate influenced the hormone secretion (a decrease in E2β, and a concurrent increase in the TS to E2β ratio); all three compounds were observed to influence the expression of genes related to steroidogenesis (50). 5.2. OBTAINING MORE INFORMATION – MULTIPLE STEROID ANALYSIS In the standard protocol for the H295R cells, which was used for evaluation of SSRIs (see above) three steroid hormones are analyzed (TS, E2β and PRO). However many compounds classified as EDCs have several targets within the steroidogenic pathway, this is for instance the case with the three azol fungicides procloraz, ketoconazol and genistein (47‐49;65;67;96‐102). The effects on steroidogenesis enzymes by these compounds are presented in Figure 15. In order to study the effect of compounds with multiple targets within steroidogenesis the H295R cell assay was combined with a novel analytical method develop by us for si‐
multaneous determination of 9 steroid hormones (papers V and VI). Procloraz, ketoconazol, and genistein were investigated using this approach. Even though the three compounds have different effects on the aromatase enzymes according to the literature (see Figure 15), we did not observe any apparent inhibition by procloraz and ketoconazol or any activation by genistein. This may be due to the fact that the three tested compounds all have an inhibitory effect upstream of the aromatase enzyme. In general the results showed that “the first” inhibition in the pathway caused an increase in substrate and a decrease in product. The decrease in product could more or less be followed through the remaining steps of the 28 PHD THESIS BY NAJA WESSEL JACOBSEN steroidogenic pathway, and thus a decrease in the main sex steroid hormones was observed for all three compounds (paper V). For instance, ketoconazol inhibits the formation of pregnenolone (PRE), and a decrease in the level of all steroids downstream (except PRO) was observed. Procloraz inhibits CYP17 and CYP21 and for this compound, an increase in the levels of PRE and PRO was observed as well as a reduction in four of the five measured downstream hormones. Figure 15. The effect of prochloraz (PROC), ketoconazol (KETO) and genisteine (GEN) on the enzymes that are a part of the steroidogenic pathway. The arrows indicate if the compound increase (↑) or decrease (↓) the effect of the enzyme. (47‐49;65;67;96‐102). The steroid hormones in bold are included in our analytical method used in connection with the H295R cell assay (paper V). Our study demonstrates that the effects of these three azol fungicides on steroido‐
genesis are in fact very different from one another since the steroidogenic pathway is disturbed at different stages by prochloraz, ketoconazol and genisteine, and that the 29 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? effects on the sex steroid hormones may actually be a result of effects exerted at other target sites than CYP19 in steroidogenesis. 5.3. CHAPTER SUMMARY In chapter 3 and 4 drugs and metabolites were screened for their ability to inhibit the activity of the aromatase enzyme and several compounds were found to do this. The purpose of testing the compounds in the H295R cell line was to investigate whether the observed inhibition of aromatase was also able to disrupt the sex steroid hormone levels in a more complex system. Two SSRIs shown to inhibit the aromatase enzyme (paper II) were evaluated in the H295R cell line; both compounds were able to disrupt steroidogenesis and caused a significant change in the sex steroid hormone balance of the cells. However the changes caused by the two compounds were not the same and neither of the observed hormone profiles appeared to be caused primarily by an inhibition of the aromatase enzyme. The three fungicides: Ketoconazol, prochloraz and genisteine influence the activity of the aromatase enzyme (paper V); however they also all have other targets within the steroidogenic pathway (47‐49;65;67;96‐102). We investigated these compounds in the H295R cell, however an effect on the androgens and estrogen levels corresponding to the known effect on aromatase was not observed. This lack of effect was probably due to the known inhibitory effects of the fungicides upstream in the steroidogenic pathway, and the corresponding lower levels of the two substrates for aromatase AN and TS. The study showed that the most apparent changes in the steroid secretion of H295R cells caused by compounds, corresponded to the interaction furthest upstream within steroidogenesis. Similarly it could be hypothesized that the SSRIs may have other targets in the steroidogenic pathway that have not yet been identified. Based on the five tested compounds, the H295R cell line does not appear to be very good for detecting direct interactions of compounds with the aromatase enzyme, at least not when alternative interactions with steroidogenesis cannot be excluded. An alternative conclusion to these results could be that the aromatase enzyme is not a relevant target for these compounds as they apparently all have other more significant targets in steroidogenesis. However, contrary to what happens in the H295R cell line, the enzymes of steroidogenesis are not all expressed within the same cell types. Investigating the effects of drugs on the aromatase enzyme in a cell should probably be performed in a different cell type or a modified version of the H295R steroidogenic cell assay. 30 PHD THESIS BY NAJA WESSEL JACOBSEN 6. A CELL IN ITS NATURAL SURROUNDINGS In‐vivo studies have been the golden standard for testing pharmaceuticals for years. Animal studies offer a possibility to test compounds in whole organisms with all the advantages this gives in viewing the total response to a compound. When using animals the distribution of a compound has a large impact on the observed effects as compounds need to be able to reach the target (e.g. the aromatase enzyme) to cause an effect. Animals also posses the ability to metabolize compounds, and thus naturally the effects of the formed metabolites are included; however it should be noted that different species may differ markedly in metabolizing the same compound. Compared to cells, and other in‐vitro systems, an animal (or human) also have a whole range of feedback mechanisms that may either boost the overall effects of an interaction with a specific target or make them negligible. Valproate has been shown to inhibit the aromatase enzyme (paper I) and interfere with steroidogenesis in H295R cells (50). In this chapter the effects of valproate on the systemic steroid hormone levels in plasma and on local steroid hormone levels in three tissues known to express the aromatase enzyme, are described (papers IV + VI). 6.1. ANALYTICAL METHODS The steroid levels in plasma were determined using a newly developed analytical method (paper VI). The method was developed to determine the following steroid hormones: Androsternedione (AN), dehydroepiandrostenedione (DEA), DHT, 17α‐ and 17β-estradiol (E2α and E2β), estrone (E1), progesterone (PRO), pregnenolone (PRE), and TS. The method consisted of a three step serial clean up procedure consisting of two solid phase extractions (SPEs; C‐18 and amino) followed by a silica gel cleanup. Deuterated standards were added to all samples before the cleanup procedure. The steroids were derivatized and the content determined using GC‐MS/MS with selective reaction monitoring (SRM). The detection limits of the GC‐MS/MS method were 0.04 ‐ 0.21 ng injected, depending on the steroid hormone, and the absolute recoveries of the analytes were 53‐112% (paper VI). The tissue samples were extracted using a slightly modified version of a method developed to extract steroids from manure (103) + (paper IV). The tissue samples were dried by grinding with sodium sulphate, and deuterated standards were added. The steroids were extracted using pressurized liquid extraction (PLE). After the extractions the samples were cleaned and analyzed as described above (leaving out the SPE C‐18 clean up). The absolute recoveries of the method were determined using deuterated standards and were: 25 – 53 % from the adrenal glands, 2 ‐ 24 % from the brain and 4 ‐ 16 % from testis. For PRO and AN the recovered deuterated standards from testis and brain were below the instrument detection limit. It was consequently not possible to quantify the content of PRO and AN from these tissues. 31 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? 6.2. VALPROATE AND THE SYSTEMIC STEROID HORMONE BALANCE IN RATS 3
Figure 16 presents the steroid levels determined in rat plasma and tissues (paper IV), using GC‐MS/MS (paper VI) + (103). 3500
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In plasma a significant decrease in the levels of PRE and E2β was observed. In testis a significant increase in the E2β level was observed. No other significant differences in the hormone levels be‐
tween the treated animals and the controls were observed. 0.4
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Figure 16. Concentration of steroid hormones in plasma and organs from treated animals and controls. *: p<0.05, #: p<0.05 when comparing log data, $: E2βis detectable in testis from all treated animals but not in testis from untreated animals (paper IV). The aromatase enzyme converts AN to E1 and TS to E2β, therefore we investi‐
gated whether valproate was able to disrupt the ratios between androgens and estrogens in‐vivo. The following ra‐
tios were investigated: AN/E1; TS/E2β; (AN+TS)/(E1+E2β); E1/AN; E2β/TS; (E1+E2β)/(AN+TS). Figure 17 shows bar charts of the investigated ratios for the plasma samples. 32 S
/T
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gen ratios compared the control animals. The fact Controls
Treated animals
that the ratios between Figure 17. Ratios between androgens and estrogens in plasma from rats male and female sex treated with valproate and control animals. * p<0.05 compared to steroids reach significance controls (paper IV). even though the single steroids do not, indicate that there might in fact be differences in the steroid levels for other steroids than PRE and E2β, but due to the low number of animals we were not able to detect the differences. PHD THESIS BY NAJA WESSEL JACOBSEN 6.3. VALPROATE AND THE LOCAL STEROID HORMONE BALANCE IN RATS Valproate and its metabolites are widely distributed during treatment and the aromatase enzyme is also found in several tissue types, this combination may cause local disruptions in the steroid hormone balance. We thus analyzed the steroid content of plasma as well as organs, brain, adrenal glands, and testis. Table 5 shows the distribution of valproate and metabolites presented by Dickinson et al. (104). The expression of aromatase enzyme in tissues (33;36) combined with our observed differences in the steroid hormones in treated and untreated rats. These organs were chosen based on their vital role as places of steroid production and capability to express aromatase. In plasma no aromatase enzymes are present; however we found a significantly reduced level of E2β, and a reduced E2β to TS ratio (paper IV). A similar effect of valproate on the plasma level of E2β in female rats has been observed by Roste et al, in male rats no effect on the TS level was observed and the E2β level was below the LOD of their method (105). Soliman et al studied the effect of valproate in male rats and reported a decrease in the TS level, E2β was not analyzed (106). Table 5. Distribution of valproate and aromatase and the effect of valproate on the steroid hormone levels in tissues. Note: Valproate is found in several other tissues than mentioned in this table; see paper IV for the full list. Total valproate and Changes in steroid levels in metabolites in selected tissues in rats treated with Presence of organs 90 min after bolus valproate (400 mg/kg/day) aromatase injection of 150 mg compared to controls (paper (33;36) valproate pr kg (µmol/g) IV) (104) Blood 0.88 E2β↓; E2β/T↓; PRE↓ Liver 1.62 + (only fetal) ND Brain 0.17 + No sign. diff. Kidney 1.32 Adrenals ND + No sign. diff. Testis 0.23 + E2β↑ Ovary ND +++ ND Placenta ND +++ ND Fat 0.17 ++ ND Skeletal muscle 0.21 Vascular smooth muscle ND + ND Bone ND + ND Carcass 0.60 ND ND ND +++: Major organ for estrogen formation; ++: Major estrogen source in males and postmenopausal women; +: Organ capable of expressing aromatase; ND: No data; ↓: Decrease; ↑: Increase. In the adrenal glands we found the highest observed levels of both E1 and E2β; however we observed no differences between the treated and untreated animals. In brain tissues we found no changes due to valproate exposure. In testis we found an increased level of 33 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? E2β in the treated animals compared to the controls, this result is opposite of the effect we expected to find based on the fact that valproate is able to inhibit the aromatase enzyme (paper I). One study has described a reduced testicular level of TS due to valproate treatment of male rats, the level of E2β was not investigated (107) similar to our results this effect is contrary to the effect expected of an aromatase inhibitor. The lack of local effect may be due to a number of reasons e.g. the relatively low concentration of valproate in the tissues (Table 5), the relatively low potency of valproate (paper I) or the very high levels of competing substrate for aromatase namely testosterone and androstenedione in the tested tissues (Table 6). Table 6. Steroid concentrations in plasma and tissues of male rats. For concentrations where no significant differences were observed between treated rats (400 mg/kg/day valproate for five days) and controls, the total average level is given. For values where there were significant differences in the levels between the two groups, the values are given in bold text and both values are given (paper IV). Steroid concentration in plasma and tissues (ng/g; 95% CI) Plasma Adrenal glands
Brain
Testis PRE T: 0.17 (0.12‐0.21) C: 0.22 (0.19‐0.25) 80 (39 ‐ 120) 10 (7.3‐13) 15 (12‐18) PRO <LOD 1900 (980 ‐ 2900) <LOD <LOD AN 0.23 (0.19‐0.28) 150 (72‐230) NQ NQ DHT 0.05 (0.04‐0.06) 9.1 (0.35‐18) 1.1 (0.97‐1.2) 116 (63‐170) TS 1.4 (1.1 ‐ 1.7) 13 (9.0 ‐ 17) 17 (9.7‐24) 63 (2.6‐120) E1 0.38 (0.30 ‐ 0.47) 5.7 (3.0 ‐ 8.3) 0.79 (0.57‐1.0) 1.2 (1.0 ‐ 1.4) E2β T: 0.06 (0.02‐0.10) C: 0.23 (0.12‐0.34) 2.1 (0.23‐4.0) 0.09 (0.05‐
0.13) T: 0.12 (0.02‐0.23) C: <LOD NQ: Not quantifiable, T: Treated animals, C: Control animals, LOD: Limit of detection. Table 6 gives the determined steroid levels in plasma and organs. When a significant difference (see above) was found between treated animals and controls, the average for each group is given. The remaining steroid levels are the pooled data for treated and untreated animals. The tissue levels of the analyzed steroids are very diverse, clearly corresponding to the different functions of the organs. The lowest steroid levels were found in plasma, the levels were in the pg/g to low ng/g range. The hormone levels for PRE, DHT, TS and E1 in the brain were significantly higher than the plasma concentration. The highest concentrations of TS and DHT were found in the testis, but the levels of PRE and E1 were also higher in testis than in plasma. The highest hormone levels of PRE, PRO, E1 and E2β were found in the adrenal glands, ranging from the low ng/g to the low µg/g. 34 PHD THESIS BY NAJA WESSEL JACOBSEN Based on our study with its limited sample size it appears that valproate may interfere with the local steroid levels (e.g. the E2β level in testis), but it does not identify the aromatase enzyme as the origin of this disruption. 6.4. CHAPTER SUMMARY In the previous chapters it has been demonstrated that the AED valproate has the ability to interfere with the aromatase enzyme (paper I), and with steroidogenesis in H295R cells (103). These studies give information about the properties of the drug valproate but they cannot clarify if these compound properties will in fact be relevant in a treatment situation. In this chapter the consequences of these abilities of the valproate compound were investigated in a more complex system, the rat. The levels of seven steroid hormones in plasma and tissues were determined in treated rats and in controls (untreated rats). In plasma significantly decreased levels of E2β and PRE as well as decreased estrogen to androgen ratios were observed. These observations indicate that an interference of valproate with the aromatase enzyme could be of significance not only in in‐vitro assays but also in a whole animal. 35 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? 7. COMPARING EFFECTS ACROSS TESTING LEVELS The effects of drugs on the sex steroid hormone balance on several testing levels have been described in the previous chapters. In this chapter the effects observed on the different testing levels are compared, and it is evaluated whether an effect seen in the simplest test systems translates into effects found in systems of increasing complexity, furthermore the usability of the aromatase enzyme as an indicator of general interferences with the sex steroid hormone levels is evaluated. To aid in this comparison a literature search was performed. The search terms and data selection criteria are described in appendix A. The data from the literature and the data presented in this thesis (papers I, II and IV) were combined and categorized into tables (see appendix A) describing the effects of each compound on the aromatase activity and on the sex steroid hormone concentrations in five testing levels: Supersomes (enzymes), cell lines, ex‐vivo, in‐vivo, and human studies. Figure 18 gives a visual presentation of the five testing levels included in the comparison. Figure 18. Flow diagram showing the five testing levels included in comparing effects of compounds on the sex steroid hormone balance. From left the drawing present: Supersomes (enzymes), cell lines, ex‐vivo, in‐vivo and human studies 7.1.
ANALYZING THE EFFECTS Table 7 presents a summary of the data in appendix A. In the table the effects of the 17 drugs are evaluated on six parameters: Amount of data (darker background equals more data), consistency within testing levels, consistency across testing levels, influences sex steroid hormone levels, influences aromatase activity, and is aromatase a good predictor. The last parameter is an indicator of whether there is a correlation between the ability of a compound to interfere with the activity of the aromatase enzyme and the occurrence of disruption in the sex steroid hormone levels (disregarding whether there is a causal connection between the two and whether the effects appear to be opposite). In Table 7 the following terms have been used when grading the data. For the consistency of the data within and between testing levels the terms are (in order of decreasing consistency): Consistent > Almost consistent > Some consistency > Inconsistent. For the effect of a compound on either aromatase or the sex steroid hormone balance the terms are (in order of decreasing effect): Yes > Probably yes > Inconsistent > Probably no > No. Below the results from the six parameters are discussed. 36 Consistency within testing levels Some consistency Almost consistent Some consistency Inconsistent Consistent Some consistency Some consistency Consistent Consistent Consistent Consistent Consistent Consistent Consistent Consistent Consistent Consistent Carbamazepine Valproate Lamotrigine Phenytoin Fluoxetine Oxcarbazepine Phenobarbital Fluvoxamine Gabapentin Topiramate Vigabatrin Citalopram Sertraline Ethosuximide Primidone Tiagabine Paroxetine ? ? ? ? Inconsistent Some consistency Consistent Consistent Consistent Almost Consistent Inconsistent Some consistency Inconsistent Inconsistent Some consistency Some consistency Some consistency Consistency between testing levels ? ? ? ? Yes Yes Yes Yes Yes Yes Inconsistent Inconsistent Yes Yes Probably not Yes Probably yes Influences sex steroid hormones levels Yes Yes No Yes Yes Yes No No No Yes Inconsistent Probably not Yes Inconsistent Probably not Yes Probably not Influences aromatase activity in‐vitro ? ? ? ? Yes Yes No No No Yes ? ? Yes ? Yes Yes Maybe Is aromatase a sound predictor Table 7. Summary of the data in appendix A. In the table the effects of 17 drugs are evaluated on six parameters: Amount of data (darker background equals more data), consistency within testing levels, consistency across testing levels, influences hormone levels , influences aromatase activity in‐vitro, and is aromatase a sound predictor. The last parameter is an indicator of whether there is a correlation between the ability of a compound to interfere with the activity of the aromatase enzyme and the occurrence disruption in the sex steroid hormone balance (disregarding whether there is a causal connection between the two or whether the effects appear to be opposite). PHD THESIS BY NAJA WESSEL JACOBSEN 37 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? 7.1.1.
THE AMOUNT OF DATA The amount of data for the compounds is very varied. For some compounds (carbamazepine and valproate) more than 20 studies describe the effects of the compounds on several parameters resulting in 104 data points for valproate. For other compounds no data were obtained from the literature. For nine of the seventeen compounds one or zero studies were found in addition to the aromatase enzyme assays, resulting in only two to three test systems being included, this means that only the aromatase enzyme assay (Methods A & B) and sometime information from one additional test system was available. 7.1.2.
CONSISTENCY WITHIN TESTING LEVELS The consistency within testing levels was variable, ranging from consistent to inconsistent. Only the data for one compound (phenytoin) was “inconsistent” within testing groups, meaning that within all testing levels the data appeared to be contradicting. For the remaining compounds with more than three data points (seven compounds), there were at least “some consistency” within testing levels. All the compounds with very little data (2‐3 test systems) were “consistent” within groups; this evaluation is however solely based on the results from the two aromatase enzymes assays described in chapter 3. 7.1.3.
CONSISTENCY ACROSS TESTING LEVELS For thirteen compounds data were available on more than one testing level and the consistency between the observed effects between levels could thus be compared. Of those thirteen, four reported such diverse effects that there was “inconsistency” between the testing levels. For three compounds the data were ”consistent”, meaning that the same effects on the sex steroid hormone levels were observed on all the testing levels; however for those three compounds results were only available on two testing levels. For the two compounds with the most research weight (valproate and carbamazepine) the data showed “some consistency”. Overall the consistency between levels were somewhere between “inconsistent” and “some consistency”, indicating that it is very difficult to translate effects directly from one level to the next. 7.1.4.
DO THE COMPOUNDS INFLUENCE THE SEX STEROID HORMONE BALANCE? The majority of the tested compounds seem to influence the steroid hormone levels; results from the aromatase enzyme assays in supersomes are not included. For nine compounds the available research strongly indicates (compared to the amount of data) that the compounds interfere with the levels of some of the investigated sex steroid hormones. 38 PHD THESIS BY NAJA WESSEL JACOBSEN 7.1.5.
DO THE COMPOUNDS INFLUENCE THE ACTIVITY OF AROMATASE? This category consists of data from studies describing the effects of compounds on supersomes (papers I and II), on steroidogenesis of cells, cell fraction or organs. Eight compounds inhibit the aromatase enzyme; four compounds do not inhibit the enzyme. For three compounds it seems unlikely that they inhibit aromatase, however some data have shown some effects. For two compounds no conclusions can be drawn. 7.1.6.
IS THE AROMATASE ENZYME ASSAY A SOUND PREDICTOR OF DISRUPTION OF THE SEX STEROID HORMONE BALANCE BY DRUGS? Based on the available data the most straight forward way to evaluate this parameter is to compare the two previously answered questions regarding the ability of the test compound to: 1) Influence the sex steroid hormone balance, and 2) Interfere with the activity of the aromatase enzyme in‐vitro. For seven compounds this comparison is not possible to make due to lack of data or inconsistencies in the available data. One compound from the top five (with respect to the amount of data available, namely phenytoin) is excluded from the comparison based on these criteria. The following evaluation is based on the remaining ten compounds. For six compounds there is good correlation, and three of these compounds are in the top five regarding the amount of data. The top five also includes a “maybe”, as carbamazepine seems to influence the sex steroid hormone levels, but the effect on aromatase is not consistent though leaning toward no effect. For three compounds the aromatase enzyme does not seem to be a good indicator of effects on the sex steroid hormone balance; however these compounds are all in the group with very little data as only three tests are described – two aromatase inhibition assays and one rodent study. However, keeping the observed inconsistencies within and across testing levels in mind (see above), one rodent study may not contain sufficient data to make a firm conclusion about the effect of a compound on the sex steroid hormone balance. Overall, based on the limited amount of data available on the seventeen selected test compounds, the effect on aromatase appears to have some correlation with interference with the sex steroid hormone levels. This correlation is observed in spite of the fact that the effect levels in the aromatase assays are much higher than the normal concentrations during treatment. The observed correlation may be due to either the direct effect on aromatase, or it could be that these compounds shown to interfere with the aromatase enzyme also have the ability to interfere with other similar targets, for instance other enzymes of steroidogenesis. It should be noted that no group of sound negative controls in the form of drugs that do not influence the sex steroid hormone levels have been included. 39 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? 7.2. CHAPTER SUMMARY In this chapter it was evaluated whether aromatase inhibition or the lack of aromatase inhibition observed in‐vitro (papers I and II) could translate into effects in more complex testing systems and whether aromatase enzyme assays would thus be a sound predictor of disruption in the sex steroid hormone balance. Scrutinizing the literature for data on the 17 compounds has made it clear that for several compounds very little data, if any, is available on their effect on the sex steroid hormone levels. Furthermore it has become very clear that when several studies are available the reported results do not always support each other. The data for the seventeen investigated compounds indicate that for these compounds the effect on aromatase inhibition rarely translates directly from one testing level to the next, however as disruptions of the sex steroid hormone balance are present it indicates that other targets related to the sex steroid hormone levels are also relevant. Furthermore it has become clear that more negative control compounds, in the form of well investigated drugs known not to interfere with the sex steroid hormone levels, should have been included. Despite these shortcomings an evaluation of the available data shows that the aromatase enzyme could be useful as a predictive tool for disruption of the sex steroid hormone balance. However as it appears that multiple targets might be relevant in the disruption of the sex steroid hormone balance for the test compounds reported in the literature, the importance of not using the aromatase enzyme assay as standalone assay must be emphasized. 40 PHD THESIS BY NAJA WESSEL JACOBSEN 8. CONCLUSIONS The overall aim of this study was to evaluate the usability of the aromatase enzyme assays as a predictor of disruption of the sex steroid hormone levels caused by drugs. To guide the research performed in connection with this thesis, three objectives were outlined. The conclusions on each of the three objectives are given below. Investigate the ability of the test compounds to interfere with the aromatase enzyme in enzyme based assays. Seventeen pharmaceuticals from the two classes AEDs and SSRIs were investigated for their ability to interfere with activity of the aromatase enzyme in two aromatase enzyme assays. Of the tested compounds eight were shown to inhibit the activity of aromatase in both assays. Four compounds gave contradictory results in the two assays and five compounds did not interfere with the activity of the aromatase enzyme (papers I and II). The effects of metabolites of sertraline on the aromatase enzyme were evaluated using different approaches. It was found that even though some metabolites had the ability to interfere with the aromatase enzyme the effects of mixtures of metabolites were less than the effect of pure drug. Based on the results a testing strategy for how metabolites can be included in the in‐vitro screening of compounds was drawn up (paper III). Validate the effect observed directly on the aromatase enzyme in more complex test‐
systems Three compounds (sertraline, fluvoxamine, and valproate) able to inhibit the aromatase enzyme were selected for evaluation in more complex testing systems. The ability of sertraline and fluvoxamine to interfere with steroidogenesis and thus the production of sex steroid hormones were investigated in the H295R cell line. Both compounds caused significant changes in the sex steroid hormone levels excreted by the cells. The observed effects however did not support an inhibition of the aromatase enzyme to be the sole underlying cause; this result indicates that these drugs may also interfere with other targets related to steroidogenesis (paper II). An analytical method for the simultaneous determination of nine steroid hormones in plasma and tissue was developed (paper VI), and used in the studies described in papers IV and V. Valproate was investigated for its ability to cause alterations in the sex steroid hormone levels in male rats. Valproate caused a significant decrease in the content of estradiol in plasma, also the ratios between androgens and estrogens were significantly altered, indicating that an inhibition of aromatase could be at least part of the cause. The steroid 41 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? content of brain, testis and adrenal glands were analyzed; the only significant change observed in tissues was an increase in the level of estradiol in testis (paper IV). Evaluate the predictive value of aromatase enzyme assays A literature search was performed to obtain data on the effect of AEDs and SSRIs on the sex steroid hormone balance. The data from the literature as well as the results obtained in the sub studies of this thesis (papers I, II and IV) were combined, sorted into testing levels and compounds, and the effects on the sex steroid hormone balance were extracted. Based on the available data it appears that the aromatase enzyme could be useful as a predictive tool for identifying drug leads able to cause a disruption in the sex steroid hormone balance. For instance valproate caused an inhibition in the two used aromatase assays, and in the majority of studies described in the literature valproate has been shown to cause a disruption in the sex steroid hormone levels in humans, animals, ex‐vivo and in vitro studies. Lamotrigine and oxcarbazepine were shown to have no effect on the aromatase enzyme in one assay and very weak effect on the aromatase enzyme in the other assay, the majority of the data from the literature concerning lamotrigine and oxcarbazepine support that these compounds do not affect the sex steroid hormone balance. However, such an evaluation is only as good as the data it builds on and it is necessary to have good data on several levels, to make a correct evaluation. The information found in the literature regarding the effect of the seventeen compounds on the sex steroid hormone levels was limited for the majority of the compounds and often studies contradicted each other. This can for instance be seen for the studies describing the effect of carbamazepine on the sex steroid hormone balance in humans. Furthermore it was realized that more negative controls in the form of drugs known not to influence the sex steroid hormone balance ought to have been included. Consequently the conclusion that the inhibition of the aromatase enzyme in in‐vitro assays has a fairly good correlation with the occurrence of disruption of the sex steroid hormone balance can only be preliminary. 42 PHD THESIS BY NAJA WESSEL JACOBSEN 9. EPILOGUE AND PERSPECTIVES The drug development process is both time consuming and expensive and very few new chemical entities reach the market as drugs. This is partly due to the fact that drug candidates fail during the clinical trials due to the discovery of unacceptable adverse effects. One way to overcome this problem might be to include a profile of which adverse effects drug leads may have when selecting which candidates should be used for further development. Batteries of predictive in‐vitro assays may have the potential to fulfill this need, and in‐vitro assays are being increasingly used by pharmaceutical companies for this purpose (61). The in‐vitro assays are used to screen drug leads for the ability to interfere with specific targets and thus have the potential to cause related adverse effects in humans. A battery of in‐vitro assay able to detect drug leads that have the potential to cause endocrine disruption could be a valuable part of an in‐vitro screening package. This is due to the very serious long term consequences that exposure to EDCs may have, a few examples being various types of cancers and lowered fertility. The overall finding of this thesis; that aromatase enzyme inhibition might be a good predictor of disruption of the sex steroid hormone balance of pharmaceuticals is thus very useful. The aromatase enzyme assay could be part of a battery of assays composed to catch drug candidates that are endocrine disruptors. A good starting point for selecting which other assays to include in such a battery could be the assays developed and recommended for the screening of chemicals in general (28‐30). These assays would need to be evaluated for their ability to identify drug candidates with the potential to cause unwanted adverse effects. Metabolism of compounds is, as described in chapter four, a natural part of the way humans and animals excrete xenobiotica. 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52 PHD THESIS BY NAJA WESSEL JACOBSEN APPENDIX A Reading across testing levels for effect of pharmaceuticals on aromatase and steroid hormone levels 137 DISRUPTION OF THE SEX STEROID HORMONE BALANCE CAUSED BY DRUGS – ARE AROMATASE ENZYME ASSAYS SOUND PREDICTORS? READING ACROSS TESTING LEVELS In the papers I II and IV it has been (and described in chapters 3, 5, and 6) it has been shown that pharmaceuticals from the drug classes SSRIs and AEDs (known to have adverse effect on the endocrine and reproductive systems) are able to interfere with the aromatase enzyme (papers I and II), with the hormone secretion of H295R cells and with the local and systemic hormone balance in male rats. To compare these results with the findings of others and to investigate whether the effects of specific drug could be followed across testing levels a review of the literature was performed. The search terms and literature selection criteria are given below. SEARCH TERMS A search of the literature was conducted using ISI Web of knowledge. Search 1: To obtain publications with the desired endpoints the following search terms were used: Gonad*, follicle*, sex hormone*, sex steroid*, estradiol*, testosterone*, aromatase*, CYP19. The terms were combined using “OR”. Search 2: Papers describing the effects of AEDs were obtained using the terms: Anticonvulsant*, antiepileptic*. The terms were combined using “OR”. Search 3: Papers describing the effects of SSRIs were obtained using the terms selective serotonin reuptake inhibitor*, SSRI*, citalopram, excitalopram, fluvoxamine, fluoxetine, paroxetine, sertraline. The terms were combined using “OR”. Search 4: Search 1 was combined with Search 2 using “AND” resulting in 465 hits. Search 5: Search 1 was combined with Search 3 using “AND” resulting in 1192 hits. LITERATURE SELECTION CRITERIA The 72 publications used in the table were selected based on the following criteria: Research papers were included (reviews and meting abstracts were excluded), papers in English were included (one Russian, one Spanish, and one Italian paper were excluded). Papers describing the effect of one or more of the twelve AEDs in paper I or of one or more of the five SSRIs in paper II were included. Papers describing the effect of specific compounds were included (papers where effects of different pharmaceuticals were combined were excluded). Papers describing the level of at least one of the sex steroid hormones: TS, AN, E2β or E1 were included (papers not including at least one of these hormones were excluded). 138 PHD THESIS BY NAJA WESSEL JACOBSEN ORGANIZING THE DATA The results were combined into two tables, table 1 for AEDs and table 2 for SSRIs (see below); the tables have the same overall structure. In the tables each of the 17 pharmaceuticals pharmaceutical are described separately, the information on each compound is separated into six main columns and a number of sub‐columns. The purpose of this is to separate the date into the five testing levels shown in figure 1 Column 1 contains general data on the pharmaceutical (name, CAS #, physicochemical properties, and pharmacokinetic data). Column 2 to contain data of the effect of the drug on pure aromatase enzyme (supersomes), the data originate in paper I and II. Column III gives information on the ability of the compounds to interfere with the hormone production in cell lines, the data originate in paper II and literature. Column 4 contains data on effects on steroid levels in organ and the interferences of steroid production of isolated systems (part of organs, cells, sub‐cellular fractions). The data originate in paper IV and literature Column 5. Presents data on steroid levels in plasma and serum of animals exposed to compounds while alive. The data originate in paper IV and literature. Column 6 contains information on the effects of the drugs on the human steroid levels in plasma; the data in this column is from the literature. The sub columns presents the systems, hormones, or ratios that are relevant for the given testing level, e.g. arom (aromatase activity), TS or TS/E2β, for some studies there are also information on the tested drug concentration [drug], the references are given in the last sub‐column of sub‐row. 139 DISRUPTIONOFTHESEXSTEROIDHORMONEBALANCECAUSEDBYDRUGS
–AREAROMATASEENZYMEASSAYSSOUNDPREDICTORS?
Table1.TheeffectofAEDsonaromatase,steroidogenesisandsteroidhormonelevelsinsupersomes,celllines,exvivo(both
hormonelevelsandsteroidogenesis),invivoandinhumans.
SS:Steadystateplasmaconcentration;PB:Proteinbinding;arom:Aromatase;[drug]:Concentrationofdruggivingthementioned
Compound
Supersomes
Cell lines
Ex-vivo
Carbamazepine
Synthetic Substrate
H295R
Rat Testis, Steroidogenesis
CAS # 298-46-4
Log P 2.45
pKa 7.0
Mw 236.269
SS 20 - 40 μM (71)
PB 75% (71)
arom [drug]
~ 3.3 mM
Ethosuximide
Synthetic Substrate
CAS # 77-67-8
Log P 0.38
pKa 9.5
Mw 141.168
SS 0.3-0.6 mM (71)
PB -NA-
arom [drug]
23 mM
Gabapentin
Synthetic Substrate
CAS # 60142-96-3
Log P -1.10
pKa 3.7; 10.7
Mw 171.237
SS 10 - 40 μM (71)
PB <3%
arom [drug]
~ 14 mM
Lamotrigine
Synthetic Substrate
CAS # 84057-84-1
Log P 0.99
pKa 5.7
Mw 256.091
SS 10 - 30 μM
PB 55 %
arom [drug]
0.4 mM
140 ref
PI
PRO TS E2 TS/E2
~ ~ ~
[drug]
8.3 mM
Ref PRO TS AN E2 E1 TS/E2 arom
(50)
Natural Substrate
arom [drug]
~ 3.3 mM
Ref
UP
PRO TS AN E2 E1 TS/E2 arom
Ref
PI
Ref
UP
Ref
PI
Natural Substrate
arom [drug] Ref
~ 14 mM PUP
Ref
PI
Natural Substrate
arom [drug]
~ 0.4 mM
Ref
UP
Ref
(108)
Human Placental Microsomes, Steroidogenesis
Natural Substrate
arom [drug]
78 mM
[drug]
15 μM
H295R
PRO TS E2 TS/E2 [drug]
Ref
~ ~ ~
175 μM (50)
~ ~
*
(133)
*The cells were co treated with forskolin
[drug]
1.5 mM
Ref
(117)
PHDTHESISBY
NAJAWESSELJACOBSEN
effect,whennoeffectisobservedtheconcentrationisthehighesttested;refreference;PRO:Progesterone;TS;
testosterone;E2:17estradiol;AN:Androstenedione;E1:Estrone;:Thelevel/activity/ratioisincreased;:The
level/activity/ratioisdecreased;~:Nosignificantchangeisobserved;P:Paper.
In-vivo
Human studies
Male Rat
PRO TS AN E2 E1 TS/E2
Female
[drug]
Male
Ref PRO TS AN E2 E1 TS/E2 Ref PRO TS AN E2 E1 TS/E2 Ref
~ (111)
(109)
(110)
~ (113)
(106)
(112)
~ ~ ~ ~ ~ (114)
(114)
~ ~ (115) (116)
~ * (118)
(119)
~* ^ (120)
^ ~ (121)
~
(118)
*luteal phase, ^ follicular phase
~ ~ ~ (122)
~ ~ (123)
~ ~ ~ (124)
~ ~ (125)
~ ~ (126)
~ ~ ~ (127)
*TS total, ^TS free
Adolescent Male
PRO TS AN E2 E1 TS/E2 Ref
~ ~ (128)
~ ~ ~ ~ (129)
Male Rat
PRO TS AN E2 E1 TS/E2
[drug]
Ref
100 mg/kg (130)
Male Rat
Female
Male
PRO TS AN E2 E1 TS/E2
[drug]
Ref PRO TS AN E2 E1 TS/E2 Ref PRO TS AN
30mg/kg (130)
~
(131)
~ ~
~
(134) ~ ~ ~
(114)
~ ~ ~
(132)
~ ~
Female Rat
~
(135)
~ ~ ~
(136)
~ PRO TS AN E2 E1 TS/E2
[drug]
Ref
~
(134)
~ E2 E1 TS/E2 Ref
(132)
(135)
(136)
~ ~ (127)
~ (121)
~ (114)
Adolescent males
PRO TS AN E2 E1 TS/E2 Ref
~ ~ (128)
141
DISRUPTIONOFTHESEXSTEROIDHORMONEBALANCECAUSEDBYDRUGS
–AREAROMATASEENZYMEASSAYSSOUNDPREDICTORS?
Compound
Supersomes
Oxcarbazepine
Synthetic Substrate
CAS # 28721-07-5
Log P 1.11
pKa NA
Mw 252.268
SS 45-90 μM
PB 40 %
arom [drug]
0.4 mM
Phenobarbital
Synthetic Substrate
CAS # 50 - 06-6
Log P 1.47
pKa 7.4
Mw 232.235
SS 65-130 μM
PB 45-60 %
arom [drug]
1.6 mM
Phenytoin
Synthetic Substrate
CAS # 57-41-0
Log p 2.47
pKa 8.3
Mw 252.268
SS 40 - 80 μM
PB 70 - 95 %
arom [drug]
3.3 mM
Primidone
Natural Substrate
arom [drug]
~ 0.6 mM
Ref
UP
Ref
PI
Mouse Brain Homogenate, Steroidogenesis
PRO TS AN E2 E1 TS/E2 arom
[drug]
0.9 mM
Ref
(138)
Natural Substrate
arom [drug]
~ 10 mM
Ref
UP
Ref
PI
Natural Substrate
arom [drug]
~ 3.3 mM
Ref
UP
Synthetic Substrate
arom [drug]
~ 0.5 mM
Tiagabine
Synthetic Substrate
CAS # 115103-54-3
Log P 2.04
pKa 3.3; 9.4
Mw 375.55
SS 40 - 140 μM
PB 96 %
arom [drug]
1.4 mM
Topiramate
Synthetic Substrate
CAS # 97240 - 79-4
Log P -1.07
pKa NA
Mw 339.363
SS 6-30 μM
PB 15 %
arom [drug]
~ 0.64mM
142
Ex-vivo
Ref
PI
CAS # 125-33-7
Log P 0.91
pKa NA
Mw 218.252
SS NA
PB NA
Cell lines
Ref
PI
Natural Substrate
arom [drug]
~ 0.1 mM
Ref
UP
Ref
PI
Natural Substrate
arom [drug]
2.2 mM
Ref
UP
Ref
PI
Natural Substrate
arom [drug]
~ 1.4 mM
Ref
UP
Rat Testis, Steroidogenesis
PRO TS AN E2 E1 TS/E2 arom
[drug]
0.18 mM
Ref
(108)
Human Placental Microsomes, Steroidogenesis
PRO TS AN E2 E1 TS/E2 arom
[drug]
0.15 mM
Ref
(117)
PHDTHESISBY
NAJAWESSELJACOBSEN
In-vivo
Human studies
Female
Male
PRO TS AN E2 E1 TS/E2 Ref PRO TS AN E2 E1 TS/E2 Ref
(112)
~ ~ (125)
Children
Adolescent males
PRO TS AN E2 E1 TS/E2 Ref PRO TS AN E2 E1 TS/E2 Ref
~
~
(137)
~ ~ (128)
Neonatal Male Rat
PRO TS AN E2 E1 TS/E2
Female
[drug]
Ref PRO TS AN E2 E1 TS/E2 Ref PRO TS AN E2 E1 TS/E2 Ref
(139)
~*
~ ~ (123)
(120)
^
~ ~ ~ (124)
* luteal phase, ^ follicular phase
Male Rat
PRO TS AN E2 E1 TS/E2
Male
Female
[drug]
Male
Ref PRO TS AN E2 E1 TS/E2 Ref PRO TS AN
(140) ~ *
~
^ (141)
~^
^ * * free; ^ total
* * ~ ~
~ * free; ^ total
E2 E1 TS/E2 Ref
~ (113)
(119)
(123)
~ (121)
(142)
(143)
~ (122)
~ ~ (127)
Male Rat
PRO TS AN E2 E1 TS/E2
[drug]
Ref
0.30 μmol/kg (144)
143
DISRUPTIONOFTHESEXSTEROIDHORMONEBALANCECAUSEDBYDRUGS
–AREAROMATASEENZYMEASSAYSSOUNDPREDICTORS?
Supersomes
Cell lines
Ex-vivo
Valproate
Synthetic Substrate
H295R
Human Placental Microsome, Steroidogenesis
CAS # 1069-66-5
Log P -0.85
pKa 4.6
Mw 166.20
SS 350 - 700 μM
PB 85-95 %
arom [drug]
50 mM
Compound
Ref
PI
Natural Substrate
arom [drug]
89 mM
Ref
UP
PRO TS E2 TS/E2 [drug]
Ref PRO
~ ~ 300 μM (50)
~ ~ (133)
*
*The cells were co treated with forskolin
PRO
TS AN E2 E1 TS/E2 arom
~
[drug]
2 mM
Ref
(117)
Pig Follicles, Steroidogenesis
TS AN E2 E1 TS/E2 arom
[drug]
0.6 mM
0.6 mM
Ref
(150;
(150;
(153)
144)
Human Follicles steroidogenesis
PRO TS AN E2 E1 TS/E2 arom
[drug]
Ref
(155)
0.03-3 mM (156)
Rat Testis
PRO TS AN E2 E1 TS/E2 arom
[drug]
Ref
*
900μM (108)
(107)
~
~
2.4 mmol/kg (P IV)
* steroidogenesis
Rat Brain
PRO TS AN E2 E1 TS/E2 arom
[drug]
Ref
~
~ ~
2.4 mmol/kg (P IV)
Rat Adrenal Glands
PRO TS AN E2 E1 TS/E2 arom
[drug]
Ref
~ ~ ~ ~ ~
2.4 mmol/kg (P IV)
Vigabatrin
Synthetic Substrate
60643-86-9
CAS # -2.16
pKa 4.0; 9.7
Mw 129.157
SS NA
PB 0 %
arom [drug]
~ 5.8 mM
Ref
PI
Natural Substrate
arom [drug]
~ 5.8 mM
Ref
UP
144 PHDTHESISBY
NAJAWESSELJACOBSEN
In-vivo
Female Rat
Human studies
Female
Male
PRO TS AN E2 E1 TS/E2
[drug]
Ref PRO TS AN E2 E1 TS/E2 Ref PRO TS AN E2 E1 TS/E2
~
~
~
(132) ~ 1.8 mmol/kg (145)
~ ~
(146)
~ 3.6 mmol/kg
(105)
2.4 mmol/kg
(147) ~ ~ (131)
1.2 mmol/kg (148)
(118)
~ Female monkey
~
(135)
~ ~ ~ ~
(136)
~ ~ ~ PRO TS AN E2 E1 TS/E2
[drug]
Ref
~ ~
~
(154)
~*
~ (120)
^
~ ~ Male Rat
*lutealphase,^follicularphase
~ ~ PRO TS AN E2 E1 TS/E2
[drug]
Ref
Adolescent Female
Adolescent Male
~ ~ ~ 2.4 mmol/kg (P IV)
(106) PRO TS AN E2 E1 TS/E2 Ref PRO TS AN E2 E1 TS/E2
~
~ ~
(157) ~ ~ ~ ~ 4.8 mmol/kg (105)
(158)
~ Adolescent Male Goat
Children
PRO TS AN E2 E1 TS/E2
[drug]
Ref
0.75 mmol/kg (159) PRO TS AN E2 E1 TS/E2 Ref
~ ~
(160)
Male Rat
PRO TS AN E2 E1 TS/E2
[drug]
Ref
1.5 mmol/kg (130)
Ref
(124)
(125)
(116)
(149)
(118)
(152)
(122)
(135)
(136)
(132)
Ref
(129)
(128)
145
DISRUPTIONOFTHESEXSTEROIDHORMONEBALANCECAUSEDBYDRUGS
–AREAROMATASEENZYMEASSAYSSOUNDPREDICTORS?
Table2.TheeffectofSSRIsonaromatase,steroidogenesisandsteroidhormonelevelsinsupersomes,celllines,exvivo(both
hormonelevelsandsteroidogenesis),invivoandinhumans.
SS:Steadystateplasmaconcentration;PB:Proteinbinding;arom:Aromatase;[drug]:Concentrationofdruggivingthementioned
Compound
Supersomes
Cell lines
Ex-vivo
Male Fish, Gonadal Steroidogenesis
Citalopram
Synthetic Substrate
CAS # 59729-33-8
Log P 3.7
pKa 9.1
Mw 324.4
SS 0.12-0.92 μM
PB 82 %
arom [drug]
56 μM
Fluoxetine
Synthetic Substrate
H295R
CAS # 54910 - 89-3
Log P 4.05
pKa 9.2
Mw 309.3
SS 0.29-0.97 μM
PB 85 %
arom [drug]
ref PRO TS E2
249 μM (P II)
~ ~ ~
TS/E2
Fluvoxamine
Synthetic Substrate
H295R
CAS # 54739-18-3
Log P 3.1
pKa 8.2
Mw 318.3
SS 0.063-1.6 μM
PB 77 %
arom [drug]
ref PRO TS E2
3.1 μM (P II)
Natural Substrate
~
arom [drug]
ref
7.8 μM (P II)
TS/E2
Paroxetine
Synthetic Substrate
CAS # 61869-08-7
Log P2.94
pKa 9.6
Mw 329.3
SS 0.027-1.6 μM
PB 93 %
arom [drug]
68 μM
Sertraline
Synthetic Substrate
H295R
CAS # 79617-96-2
Log P 5.3
pKa 8.9
Mw 306.2
SS 0.065-0.65 μM
PB 98.5 %
arom [drug]
91 μM
TS/E2
146
ref
(P II)
Natural Substrate
arom [drug] Ref
610 μM (P II)
[drug]
1 μM
Ref
(35)
Natural Substrate
TS/E2
arom
[drug] Ref
16 nM (162)
Female Fish, Gonadal Steroidogenesis
arom [drug] Ref
246 μM (P II)
PRO TS AN E2 E1
~
~
[drug]
6.2 μM
3.1 μM
50 μM
Ref
P II
ref
(P II)
Natural Substrate
arom [drug]
ref
142 μM (P II)
ref PRO TS E2
(P II)
Natural Substrate
arom [drug]
ref
13 μM (P II)
PRO TS AN E2 E1
~
~
[drug] Ref
0.93 μM
7.5 μM P II
1.9 μM
TS/E2
arom
[drug] Ref
16 nM (162)
0.1 μM (167)
PHDTHESISBY
NAJAWESSELJACOBSEN
effect,whennoeffectisobservedtheconcentrationisthehighesttested;refreference;PRO:Progesterone;TS;Testosterone;
E2:17estradiol;AN:Androstenedione;E1:Estrone;:Thelevel/activity/ratioisincreased;:Thelevel/activity/ratiois
decreased;~:Nosignificantchangeisobserved;P:Paper.
In-vivo
Human studies
Plasma Concentrations
PRO TS AN E2 E1 TS/E2
~ [drug]
Ref
(161)
Mollusks
PRO TS AN E2 E1 TS/E2
~
Male Fish
[drug]
Ref PRO TS AN E2 E1 TS/E2 [drug]
0.1 μM* (163)
1.7 nM*
170 nM*
Female Fish
~
~
1.6 nM*
PRO TS AN E2 E1 TS/E2 [drug]
Ref
*Concentration of drug in water
~
0.3 nM* (162)
Male Rat
16 ng/g^ (168)
PRO TS AN E2 E1 TS/E2 [drug]
Female Rat
~
PRO TS AN E2 E1 TS/E2 [drug]
Ref
~
32 μg/kg^ (171)
(172)
¤
*Concentration of drug in water, ^injected dose,
¤oviariectomized rats co-treated with fluoxetine and
t
Male Rat
Female
Ref
(164)
(162)
PRO TS AN E2 E1 TS/E2 Ref
(165)
Male
PRO TS AN E2 E1 TS/E2 Ref
~
(166)
Ref
(169)
(170)
PRO TS AN E2 E1 TS/E2 [drug]
Ref
~
31 μg/kg^ (173)
^injected dose
147
Naja Wessel Jacobsen
Naja Wessel Jacobsen
PhD Thesis 2011
ISBN 978-87-82719-15-7
Disruption of the Sex Steroid Hormone Balance Caused by Drugs
– Are Aromatase Enzyme Assays Sound Predictors?
Disruption of the Sex Steroid Hormone Balance Caused by Drugs – Are Aromatase Enzyme Assays Sound Predictors?
Naja Wessel Jacobsen
DEPARTMENT OF PHARMACEUTICS AND ANALYTICAL CHEMISTRY
Disruption of the Sex Steroid
Hormone Balance Caused by Drugs
– Are Aromatase Enzyme Assays
Sound Predictors?