Why Does Risk-Taking Peak During Adolescence?: Contribution of Neurochemical and
Circuit-Level Function to Lower Serotonin-Mediated Behavioral Inhibition in
Adolescents
by
Andrew Emmett Arrant
Department of Pharmacology and Cancer Biology Duke University
Date:______Approved:
______Cynthia M. Kuhn, Supervisor
______Edward D. Levin
______J. Victor Nadler
______Theodore A. Slotkin
______Redford B. Williams
______Wilkie A. Wilson
Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Pharmacology and Cancer Biology in the Graduate School of Duke University
2012
i
v
ABSTRACT
Why Does Risk-Taking Peak During Adolescence?: Contribution of Neurochemical and
Circuit-Level Function to Lower Serotonin-Mediated Behavioral Inhibition in
Adolescents
by
Andrew Emmett Arrant
Department of Pharmacology and Cancer Biology Duke University
Date:______Approved:
______Cynthia M. Kuhn, Supervisor
______Edward D. Levin
______J. Victor Nadler
______Theodore A. Slotkin
______Redford B. Williams
______Wilkie A. Wilson
An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Pharmacology and Cancer Biology in the Graduate School of Duke University
2012
Copyright by Andrew Emmett Arrant 2012
Abstract
Adolescence is the period of transition between childhood and adulthood, and is characterized across mammalian species by changes in behavior that include increases in risk taking, novelty/sensation seeking, and social behavior. While it is a part of normal development, this increase in risk taking behavior contributes to the leading causes of adolescent injury and mortality. Earlier maturation of limbic brain regions relative to the cortex is thought to contribute to this increase in risk taking in adolescents, but not younger individuals. Immaturity of the central serotonergic system during adolescence could contribute to risk taking behavior by resulting in lower avoidance of aversive stimuli in adolescents than adults. The purpose of this dissertation was to investigate whether immature serotonergic function could contribute to adolescent risk taking. We studied pre- and postsynaptic serotonergic function and circuit-level mechanisms relevant to risk taking behavior using behavioral and neurochemical approaches.
Serotonergic modulation of behavior was assessed in adult (67-74 day old) and adolescent (28-34 day old) male rats in the novelty induced hypophagia (NIH), elevated plus maze, (EPM), and light/dark (LD) tests for anxiety-like behavior. Serotonin depletion with the synthesis inhibitor p-chlorophenylalanine (PCPA) produced anxiolytic effects only in adult rats in the NIH test and in both age groups in the EPM.
These data showed that some serotonin-mediated behavioral inhibition is present
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during adolescence. However, adolescent rats were less sensitive than adults to the anxiogenic effects of the serotonin releasing drugs fenfluramine and methylenedioxymethamphetamine (MDMA) and the serotonin uptake inhibitor fluoxetine in the LD test, suggesting that serotonergic circuits are not as effective at inhibiting behavior in adolescents as in adults.
Microdialysis conducted in medial prefrontal cortex (mPFC) showed that adolescent rats exhibited smaller increases in extracellular serotonin after treatment with the releasing drug fenfluramine, but not the uptake inhibitor fluoxetine. Further investigation of presynaptic serotonergic function in adults and adolescents revealed that adolescent rats have lower tissue serotonin content than adults in several forebrain regions, but similar rates of serotonin synthesis, density of serotonin transporter (SERT)- immunoreactive innervation, and SERT radioligand binding. These data suggest that adolescents may have a smaller increase in extracellular serotonin than adults after administration of a releasing drug, but not an uptake inhibitor, due to lower tissue serotonin stores. Lower serotonin stores may limit the ability of a releasing drug to increase extracellular serotonin, but are unlikely to affect response to an uptake inhibitor. These findings also indicate that extracellular serotonin does not completely account for the lower adolescent behavioral response to indirect serotonin agonists.
Since presynaptic serotonergic function did not explain age differences in the anxiogenic effects of indirect serotonin agonists, we investigated postsynaptic serotonin
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signaling by testing the behavioral effects of serotonin receptor agonists in the LD test.
Adolescent rats were less sensitive than adults to the anxiogenic effects of the 5-HT1A agonist 8-hydroxy-2-(dipropylamino)tetralin (8-OH DPAT) in the LD test, but not to the
5-HT2 agonist meta-chlorophenylpiperazine (mCPP). No age differences were observed in 3H-8-OH DPAT binding in prefrontal cortex, amygdala, or hippocampus between adolescents and adults, and infusion of 8-OH DPAT into mPFC (prelimbic cortex), ventral hippocampus, or basolateral amygdala was unable to replicate the systemic effects of 8-OH DPAT. These data suggest that lower adolescent sensitivity to the anxiogenic effects of 8-OH DPAT is not due to age differences in receptor expression in the mPFC, ventral hippocampus, and basolateral amygdala, and show that 5-HT1A stimulation in these areas alone is not sufficient to mimic the effects of systemic 8-OH
DPAT.
We then tested the circuit-level effects of fluoxetine and 8-OH DPAT, since stimulating 5-HT1A receptors in single brain regions failed to reproduce age differences in systemic 8-OH DPAT administration. Fluoxetine produced greater expression of the immediate early gene c-Fos in regions of the extended amygdala in adult rats, and 8-OH
DPAT produced greater activation of the lateral orbital cortex and central amygdala in adult rats. Lower activation of cortical and amygdala brain regions could underlie the more modest behavioral effects of these drugs in adolescents, as these brain regions are important in mediating behavioral inhibition and anxiety-like behavior. These data are
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also consistent with human studies showing immature cortical and amygdala function during adolescence.
This dissertation shows that adolescents are less sensitive than adults to serotonin mediated behavioral inhibition, and that this may be due to immature activation of neural circuits modulated by the 5-HT1A receptor between the prefrontal cortex and amygdala. There is evidence that neural circuits mediating pursuit of rewarding stimuli are hyperactive in adolescents relative to juveniles or adults.
Immature serotonergic behavioral inhibition in adolescents may be unable to effectively counteract this hyperactive rewarding system, and so contribute to adolescent risk taking and drug abuse. Immature serotonin-mediated behavioral inhibition could also contribute to increased risk for suicidality during SSRI therapy for depression and mood disorders in both adolescents and children.
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Contents
Abstract ...... iv
Contents ...... viii
List of Tables ...... xv
List of Figures ...... xvi
1. Introduction ...... 1
1.1 Adolescence ...... 1
1.1.1 Puberty and the Growth Spurt ...... 1
1.1.2 Behavioral & Cognitive Maturation ...... 4
1.1.2.1 Social Behavior ...... 5
1.1.2.2 Sensation Seeking ...... 6
1.1.2.3 Impulsivity ...... 6
1.1.2.4 Cognitive Maturation ...... 8
1.1.3 Downsides of Adolescent Development: Risk Taking and the Onset of Affective Disorders ...... 10
1.1.3.1 Risk Taking Behavior and Drug Abuse ...... 10
1.1.3.2 Affective Disorders, Suicide, and the Response to Antidepressants ...... 14
1.1.4 Brain Maturation ...... 17
1.1.4.1 General Brain Maturation ...... 17
1.1.4.2 Differential Maturation of Cortical and Limbic Brain Systems ...... 19
1.1.4.3 Dopamine and Serotonin ...... 22
1.2 Serotonin ...... 25
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1.2.1 Serotonergic Physiology ...... 26
1.2.1.1 Anatomy ...... 26
1.2.1.2 Electrophysiology ...... 27
1.2.1.3 Biochemistry ...... 28
1.2.1.4 Serotonin Release and Regulation of Extracellular Serotonin ...... 29
1.2.1.5 Serotonin Receptors ...... 31
1.2.2 Ontogeny ...... 37
1.2.2.1 Humans and Non-human Primates ...... 37
1.2.2.2 Non-human Primates ...... 39
1.2.2.3 Rodents ...... 40
1.2.3 Modulation of Behavior ...... 44
1.2.3.1 Impulsivity ...... 46
1.2.3.2 Anxiety and Anxiety-Like Behavior ...... 47
1.2.3.3 Aggression ...... 54
1.2.3.4 Drug Reward and Self-Administration ...... 55
1.2.3.5 Summary ...... 56
1.3 Specific Aims ...... 57
2. Methods ...... 61
2.1 General Methods ...... 61
2.1.1 Animals ...... 61
2.1.2 Drugs and Injections ...... 62
2.2 Behavior Testing ...... 63
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2.2.1 Light/Dark Test ...... 64
2.2.2 Elevated Plus Maze ...... 65
2.2.3 Novelty Induced Hypophagia ...... 66
2.3 Confirmation of Serotonin Depletion with PCPA ...... 67
2.4 Tissue Serotonin Content and Synthesis ...... 68
2.5 Serotonin Transporter Immunostaining ...... 69
2.6 3H-Paroxetine Binding ...... 70
2.7 3H-8-OH DPAT Binding ...... 71
2.8 Microdialysis ...... 72
2.8.1 Guide Cannula Implantation ...... 72
2.8.2 Set up and Collection of Baseline Samples ...... 73
2.8.3 Zero Net Flux ...... 74
2.8.4 Fenfluramine Dose Response ...... 75
2.8.5 Potassium Infusion ...... 75
2.8.6 Fluoxetine Dose Response ...... 76
2.8.7 Fluoxetine Infusion ...... 76
2.8.8 Verification of Probe Placement ...... 76
2.8.9 HPLC-EC Detection for Microdialysis ...... 77
2.9 Site Specific Injections ...... 77
2.9.1 Implantation of Guide Cannulae ...... 78
2.9.2 Habituation to Handling and Infusion ...... 79
2.9.3 Site Specific Injection and Behavior Testing ...... 80
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2.9.4 Confirmation of Cannula Placement ...... 81
2.10 c-Fos Immunostaining ...... 81
2.10.1 Determination of Maximal c-Fos Response ...... 82
2.10.3 Response to Fluoxetine, 8-OH DPAT, and mCPP ...... 82
2.10.4 Perfusions and Brain Collection ...... 83
2.10.5 Immunostaining ...... 83
2.10.6 Cell Counting ...... 83
2.11 Data Analysis and Statistics ...... 84
2.11.1 Behavior Tests ...... 84
2.11.1.1 Baseline Behavior ...... 84
2.11.1.2 Baseline Behavior: Systemic vs. Site-Specific Control Animals ...... 85
2.11.1.3 Drug Effects in Each Age Group ...... 85
2.11.2 Confirmation of Serotonin Depletion, Tissue Serotonin Content, and Synthesis ...... 86
2.11.3 Radioligand Binding and Serotonin Transporter Immunostaining ...... 86
2.11.4 Microdialysis ...... 87
2.11.5 c-Fos Immunostaining ...... 88
3. Age Differences in the Behavioral Effects of Pharmacologic Manipulation of Extracellular Serotonin ...... 90
3.1 Baseline Behavior in Anxiety Tests ...... 91
3.2 Reducing Extracellular Serotonin with PCPA ...... 94
3.2.1 Novelty Induced Hypophagia ...... 95
3.2.2 Light/Dark Test ...... 97
xi
3.2.3 Elevated Plus Maze ...... 99
3.2.4 Confirmation of Serotonin Depletion ...... 100
3.3 Increasing Extracellular Serotonin with Indirect Agonists...... 102
3.3.1 Serotonin Releasing Drugs ...... 103
3.3.1.1 Fenfluramine Light/Dark Test ...... 103
3.3.1.2 Fenfluramine Elevated Plus Maze ...... 104
3.3.1.3 MDMA Light/Dark Test ...... 106
3.3.2 Serotonin Uptake Inhibitor ...... 108
3.3.2.1 Fluoxetine Light/Dark Test ...... 108
4. The Effects of Indirect Serotonin Agonists on Extracellular Serotonin ...... 110
4.1 Indices of Serotonergic Innervation and Function...... 110
4.1.1 Tissue Serotonin Content, Turnover, and Synthesis ...... 110
4.1.2 Density of Serotonin Transporter Immunostaining ...... 111
4.1.3 3H-Paroxetine Serotonin Transporter Binding ...... 114
4.2 Comparison of Probe Recovery and Baseline Extracellular Serotonin Using the Zero Net Flux Method of Quantitative Microdialysis ...... 115
4.3 Fenfluramine ...... 116
4.4 Potassium Evoked Release ...... 117
4.5 Fluoxetine ...... 118
4.6 Local Fluoxetine Infusion ...... 119
4.7 Confirmation of Probe Placements ...... 120
5. Comparison of the Post-synaptic Response to Serotonergic Signaling ...... 122
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5.1 Behavioral Effects of Serotonin Receptor Agonists ...... 122
5.1.1 8-OH DPAT Light/Dark Test ...... 122
5.1.2 mCPP Light/Dark Test ...... 124
5.1.3 3H-8-OH DPAT Binding ...... 125
5.1.4 Site Specific Injection of 8-OH DPAT ...... 126
5.1.4.1 Control Animal Behavior ...... 126
5.1.4.2 Prelimbic Cortex ...... 128
5.1.4.3 Ventral Hippocampus ...... 130
5.1.4.4 Basolateral and Central Amygdala ...... 131
5.2 Measuring c-Fos Activation After Treatment with Fluoxetine, 8-OH DPAT, and mCPP ...... 133
5.2.1 Determining Maximal c-Fos Expression ...... 133
5.2.3 c-Fos Expression Following Fluoxetine or 8-OH DPAT Treatment ...... 135
5.2.4 c-Fos Expression Following mCPP Treatment ...... 140
6. Discussion ...... 142
6.1 Age Differences in Baseline Behavior ...... 146
6.2 Behavioral Response to Serotonin Depletion ...... 147
6.3 Behavioral Response to Indirect Serotonin Agonists ...... 150
6.4 Age Differences in Presynaptic Serotonergic Function ...... 152
6.5 Neurochemical Effects of Indirect Serotonin Agonists ...... 156
6.6 Behavioral Effects of 5-HT1A and 5-HT2 Receptor Agonists ...... 159
6.7 Circuit-Level Effects of Fluoxetine, 8-OH DPAT, and mCPP ...... 162
xiii
6.8 Conclusions ...... 169
6.9 Significance ...... 175
6.10 Future Directions ...... 180
References ...... 186
Biography ...... 254
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List of Tables
Table 1: Coordinates for Sterotaxic Implantation of Injection Guide Cannulae ...... 79
Table 2: PCPA Effects on Tissue Serotonin and 5-HIAA ...... 102
Table 3: 3H-Paroxetine Saturation Binding Results ...... 115
Table 4: c-Fos Immunoreactive Nuclei After Medial Forebrain Bundle Stimulation ...... 134
Table 5: Numbers of c-Fos-IR Cells in Adult and Adolescent Rats Treated With Fluoxetine or 8-OH DPAT ...... 138
Table 6: Number of c-Fos-IR Cells in Adult and Adolescent Rats Treated With mCPP. 140
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List of Figures
Figure 1: Neurobiology of Adolescent Risk Taking ...... 21
Figure 2: Serotonergic Terminals, Release, and Metabolism ...... 31
Figure 3: Timeline for Microdialysis Experiments ...... 72
Figure 4: Example Zero Net Flux Experiment ...... 75
Figure 5: Timeline for Site Specific Injection Experiments ...... 78
Figure 6: Behavior of Saline Treated Animals in the NIH Test ...... 92
Figure 7: Behavior of Saline Treated Animals in the LD Test ...... 93
Figure 8: Behavior of Saline Treated Animals in the EPM ...... 94
Figure 9: PCPA Novelty Induced Hypophagia Test ...... 97
Figure 10: PCPA Light/Dark Test ...... 98
Figure 11: PCPA Elevated Plus Maze...... 99
Figure 12: Fenfluramine Light/Dark Test ...... 104
Figure 13: Fenfluramine Elevated Plus Maze ...... 106
Figure 14: MDMA Light/Dark Test ...... 107
Figure 15: Fluoxetine Light/Dark Test ...... 109
Figure 16: Tissue Serotonin Content, 5-HIAA Levels, and Serotonin Synthesis ...... 111
Figure 17: Density of SERT-Immunoreactive Axons ...... 112
Figure 18: Example SERT Immunostaining ...... 113
Figure 19: 3H-Paroxetine Single Point Binding ...... 114
Figure 20: Zero Net Flux Results and Baseline Extracellular Serotonin ...... 116
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Figure 21: Fenfluramine Microdialysis ...... 117
Figure 22: Potassium-Evoked Serotonin Release ...... 118
Figure 23: Fluoxetine Microdialysis ...... 119
Figure 24: Local Fluoxetine Administration in Medial Prefrontal Cortex ...... 120
Figure 25: Microdialysis Probe Placement ...... 121
Figure 26: Effects of 8-OH DPAT in the LD Test ...... 123
Figure 27: Effects of mCPP in the LD Test ...... 125
Figure 28: 3H-8-OH DPAT Binding in Tissue Homogenates ...... 126
Figure 29: Comparison of Light/Dark Test Behavior of Controls from Systemic and Site Specific Experiments ...... 128
Figure 30: Behavior in LD Test After Infusion of 8-OH DPAT into Prelimbic Cortex .... 129
Figure 31: Behavior in LD Test After Infusion of 8-OH DPAT into Ventral Hippocampus ...... 131
Figure 32: Behavior in LD Test After Infusion of 8-OH DPAT into Basolateral Amygdala ...... 133
Figure 33: c-Fos Staining in Lateral Orbital Cortex ...... 135
Figure 34: Percent Increase in c-Fos Immunoreactive Nuclei After Fluoxetine or 8-OH DPAT ...... 139
Figure 35: Percent Increase in c-Fos Immunoreactive Nuclei After mCPP ...... 141
Figure 36: Neural Circuits Involved in Serotonergic Modulation of Anxiety-like Behavior ...... 170
Figure 37: Immature Prefrontal Cortical Circuits in Adolescents and Consequences for Behavior ...... 173
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1. Introduction
1.1 Adolescence
Adolescence is the period of transition from childhood to adulthood. This developmental period is common to many mammalian species, and is characterized by a series of events that mark the final maturation into adulthood. Conservative estimates for the ages spanned by adolescence are 12 to 18 years of age in humans and 28 to 42 days old in rodents; though developmental changes continue to occur until age 25 in humans and 60 days old in rodents (reviewed in McCutcheon and Marinelli, 2009;
Spear, 2000). A number of events occur across species during adolescence that play a role in maturation of adult physiology and behavior. These include puberty, rapid growth, hyperphagia, changes in sleep patterns, brain maturation, and the emergence of behavioral patterns that are unique to adolescence (reviewed in Spear, 2000).
1.1.1 Puberty and the Growth Spurt
Puberty, which entails reproductive maturation and changes mediated by gonadal steroid hormones, is one of the major processes that occurs during adolescence
(reviewed in Sisk and Foster, 2004). While the terms are sometimes used interchangeably, adolescence and puberty are not synonymous. Adolescence includes puberty, as well as social, cognitive, and psychological maturation reviewed in Ernst et al., 2006; Sisk and Foster, 2004; Spear, 2000). Not all of the changes that occur during adolescence are mediated by the pubertal rise in gonadal steroid hormones, but gonadal
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steroid hormones are important in some of the changes in social and risk taking behavior during adolescence (Primus and Kellogg, 1989; reviewed in Nelson et al., 2005;
Sisk and Foster, 2004). The onset of puberty is not tied strictly to a certain age, but is influenced by a variety of factors, including body weight/nutritional status, stress, and social factors (reviewed in Ebling, 2005; Frisch, 1984; Graber et al., 1995).
One of the factors making rodents a useful model of adolescence is the generally similar hormonal changes that occur during puberty across mammalian species. Onset of puberty begins with increased frequency of pulses of gonadotropin releasing hormone (GnRH) release from the hypothalamus that stimulate release of luteinizing hormone (LH) and follicle stimulating hormone (FSH) from the anterior pituitary
(reviewed in Grumbach, 2002; Plant and Barker-Gibb, 2004). GnRH pulses and the subsequent increases in LH and FSH are relatively silent during childhood in humans and other primates, but this period of reduced activity does not occur in juvenile rats
(reviewed in Grumbach, 2002; Plant, 1985; Plant and Barker-Gibb, 2004). However, rats exhibit increases in LH at the onset of puberty as is seen in humans and primates (Lee et al., 1975; Meijs-Roelofs et al., 1983). LH and FSH act on the testes or ovaries to stimulate production of the gonadal steroids testosterone, estrogen, and progesterone which are responsible for development of secondary sex characteristics and maturation of reproductive function and behavior (reviewed in Grumbach, 2002; Sisk and Foster,
2004). The process of activation of GnRH neurons leading to increased circulating levels
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of gonadal steroids is referred to as gonadarche. In humans, gonadarche is preceded by adrenarche, in which the adrenal glands begin to produce the androgens androstenedione, dehydroepiandrosterone, and dehydroepiandrosterone sulfate
(reviewed in Havelock et al., 2004). Aside from humans, adrenarche has only been observed in certain species of primate such as chimpanzees and rhesus macaques
(reviewed in Abbott and Bird, 2009; Conley et al., 2011; Cutler et al., 1978). Adrenarche and gonadarche are considered to be independent processes, so the absence of adrenarche in rodents does not preclude their usefulness as a model of puberty and adolescence (reviewed in Plant and Barker-Gibb, 2004; Spear, 2000)
Adolescence is a period of rapid growth, and the growth spurt begins during puberty (reviewed in Rogol et al., 2002; Spear, 2000). In addition to increases in gonadal steroid hormones, levels of growth hormone increase during puberty (reviewed in
Albertsson-Wikland et al., 1994; Gabriel et al., 1992). The increase in growth hormone occurs in earlier pubertal stages in females than in males, resulting in earlier growth spurts in females (reviewed in Albertsson-Wikland et al., 1994). Increased growth hormone and gonadal steroids also change distribution of fat, muscle mass, and bone density in a sexually dimorphic pattern (reviewed in Rogol et al., 2002). Growth slows during later adolescence and young adulthood as growth hormone levels fall and the epiphyseal plates on bones close, ending the potential for further growth (reviewed in
Albertsson-Wikland et al., 1994; Emons et al., 2011).
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In addition to sexual maturation and physical growth, adolescence entails behavioral, cognitive and social maturation. These processes are closely tied with development of key brain regions and neural pathways, which involves increasing organization and efficiency at the cellular and circuit levels. This period of development is crucial to attaining adult function, but is also vulnerable to disruption by genetic, environmental, and pharmacologic factors that can contribute to a variety of disorders such as depression, anxiety disorders, schizophrenia, and drug addiction. Additionally, adolescent-typical risk taking behavior leads to many of the primary causes of injury and death in this age group. Understanding the vulnerabilities and opportunities of adolescent brain development could lead to improved health outcomes for this age group.
1.1.2 Behavioral & Cognitive Maturation
Behavior and cognitive function mature during adolescence. This involves both monotonic changes from childhood to adulthood and transient increases in certain behaviors during adolescence. Many of these changes have been observed in both humans and animal models. Adolescents exhibit changes in social behavior and are more sensation-seeking, and impulsive than adults. These behavioral patterns are important in social and psychological development, but in some individuals may also produce risk taking behaviors that lead to adverse outcomes (reviewed in Casey et al.,
2008; Spear, 2000). Numerous aspects of cognitive function also mature during
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adolescence. These include improvements in reasoning, abstract thought, attention, and the ability to regulate behavior and emotions (reviewed in Klaczynski, 2004; Steinberg,
2005). Improvement of decision making during adolescence does not prevent negative risk taking, in part because adolescents are more vulnerable than adults to the effects of peers and emotions on decision making (Chein et al., 2011; Figner et al., 2009; Gardner and Steinberg, 2005).
1.1.2.1 Social Behavior
Social behavior changes during adolescence as individuals begin to spend less time with family members and more time with peers (Csikszentmihalyi, 1977; Larson and Richards, 1991). This period of “social re-orientation” is important for attaining normal adult social and affective behavior (reviewed in Nelson et al., 2005). Social behavior also changes in adolescent rodents. Play behavior peaks during early adolescence (around PN32) in rats, and adolescent rats find social interaction more rewarding than adults (Douglas et al., 2004; Panksepp, 1981). Adolescent rats also exhibit more social interaction than adult rats with peers in a familiar environment
(Primus and Kellogg, 1989). Early adolescent male rats (PN28) are insensitive to environmentally mediated changes in social interaction with peers, though this matures by PN35 with the onset of puberty (Primus and Kellogg, 1989). Gonadal steroid hormones are known to be important for adolescent social development in both humans and animal models (reviewed in Nelson et al., 2005; Sisk and Foster, 2004).
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1.1.2.2 Sensation Seeking
In addition to increases in social behavior, adolescents exhibit more sensation seeking and novelty seeking. Sensation seeking or novelty seeking is a personality trait that involves the desire for new and exciting experiences that may involve risk
(reviewed in Zuckerman, 1986, 1964). Sensation seeking is at its peak during adolescence in humans (Steinberg et al., 2008; Zuckerman et al., 1978). Novelty-seeking can be assessed in rodents using the locomotor response to a novel environment, interaction with novel objects, and preference for a novel versus a familiar compartment
(reviewed in Bardo et al., 1996). Adolescent rodents are more novelty seeking than adults in these paradigms, as they have greater locomotion in a novel open field, interact more with novel objects, and spend more time in a novel rather than a familiar compartment (Adriani et al., 1998; Douglas et al., 2003; Stansfield and Kirstein, 2006).
1.1.2.3 Impulsivity
Impulsivity is the tendency to act without foresight or thinking about consequences. In contrast to sensation seeking and social behavior, which peak in the early adolescent years, impulsivity steadily declines from childhood to adulthood
(Steinberg et al., 2008; Steinberg et al., 2009). Questionnaire-based methods are often used to assess impulsivity in humans. These studies show a decline in impulsivity with age, with several studies showing that adolescents are more impulsive than adults
(Galvan et al., 2007; Leshem, 2007; Steinberg et al., 2008; Steinberg et al., 2009). There are
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many experimental approaches to measuring impulsivity in both humans and animal models. For the purposes of this discussion these will be broadly classified as measuring either delay discounting or behavioral inhibition (reviewed in Evenden,
1999). Human and animal studies collectively show that early adolescents are more impulsive than adults on both types of task.
Delay discounting refers to the decreasing subjective value of a reward with longer delays to the receipt of the reward, resulting in a preference for a small immediate reward over a larger delayed reward (reviewed in Evenden, 1999). Delay discounting declines from childhood to adulthood, and a detailed study of delay discounting across adolescence found that discount rates mature around age 16 (Green,
1994; Olson et al., 2007; Prencipe et al., 2011; Scheres et al., 2006; Steinberg et al., 2009).
Adolescent rodents are more impulsive than adults in delay discounting paradigms, though some strains of mice do not show this age difference (Adriani and Laviola, 2003;
Doremus-Fitzwater et al., 2012; Pinkston and Lamb, 2011). The lack of developmental differences in some strains of mice is due to high impulsivity in the adult mice, making developmental changes in impulsivity more difficult to detect (Pinkston and Lamb,
2011). These strains may model individuals with impulsive behavior throughout the life span rather than the more typical developmental pattern of reductions of impulsivity from early adolescence to adulthood (Pinkston and Lamb, 2011).
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Behavioral inhibition describes the ability to regulate behavior by refraining from action at inappropriate times or in inappropriate contexts (reviewed in Evenden, 1999).
A wide variety of tasks are used to assess behavioral inhibition in humans and animals, most of which test the ability to refrain from performing a response (such as pressing a button or lever or performing a saccade) based on presentation of cues (reviewed in
Chamberlain and Sahakian, 2007; Evenden, 1999). Behavioral inhibition in humans improves steadily from childhood to adulthood with a similar time course as delay discounting (Asato et al., 2006; Luna and Sweeney, 2004; Steinberg, 2008; Tamm et al.,
2002; Williams et al., 1999). In human studies, early adolescents perform worse than adults on some behavioral inhibition tasks, and behavioral inhibition matures by around age 16 (Asato et al., 2006; Luna and Sweeney, 2004; Steinberg et al., 2008; Tamm et al.,
2002). Direct comparisons of adult and adolescent rodent performance on behavioral inhibition tasks are not available due to the long training time required for these paradigms coupled with the relatively short duration of adolescence in these species.
1.1.2.4 Cognitive Maturation
A variety of aspects of cognitive function improve during adolescence, most of which are attributed to maturation of the cortex and its connections with the striatum and limbic brain regions (reviewed in Casey et al., 2008; Tau and Peterson, 2010).
Reasoning, logical decision making, and abstract thought improve over the course of adolescence (reviewed in Klaczynski, 2004; Steinberg, 2005). Social aspects of cognition
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also improve during this period, as adolescents improve at interpreting the emotional states of others and considering others’ perspective (reviewed in Burnett et al., 2011;
Crone and Dahl, 2012). A major component of cognitive development during adolescence is the maturation of cognitive control. Cognitive control refers to the ability to remain focused on goals by inhibiting irrelevant attentional, behavioral, or emotional processes, and is sometimes used synonymously with executive function (reviewed in
Casey et al., 2002; Crone and Dahl, 2012; Luna, 2009; Tottenham et al., 2011). Cognitive control includes behavioral inhibition as assessed in impulsivity tests such as the go/no- go task, but also involves tests for attention that assess the ability to filter out distracting information (reviewed in Casey et al., 2002; Luna, 2009). Like impulsivity, cognitive control improves steadily from childhood to adulthood (reviewed in Casey et al., 2002;
Luna, 2009). Adolescents are better at inhibiting inappropriate behavioral or emotional responses than children, but have not yet attained adult function (reviewed in Casey et al., 2002; Luna, 2009; Tottenham et al., 2011). Adolescents are also more vulnerable than adults to disruption of cognitive control and working memory by distracting stimuli or emotionally charged cues (Ridderinkhof and van der Stelt, 2000; Spronk et al., 2012;
Tottenham et al., 2011).
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1.1.3 Downsides of Adolescent Development: Risk Taking and the Onset of Affective Disorders
1.1.3.1 Risk Taking Behavior and Drug Abuse
The data discussed above shows that adolescents are more sensation seeking and impulsive than adults and engage in more social behavior. These adolescent-typical behaviors are helpful for humans or animals as they leave the family group or nest and establish a place as a mature adult (reviewed in Spear, 2000). These characteristics are also thought to play a role in normal social and psychological development (reviewed in
Casey et al., 2008; Fairbanks et al., 2004; Spear, 2000). However, they can lead to negative risk taking behaviors that are leading causes of adolescent injury and death
(Eaton et al., 2012). Adolescents engage in elevated levels of reckless and drunk driving, unsafe sexual behavior, experimentation with drugs, and minor crimes (reviewed in
Arnett, 1992; Steinberg, 2008). These negative risk taking behaviors are considered a normal part of development, though they result in injury or death in some individuals
(reviewed in Casey et al., 2008; Eaton et al., 2012; Fairbanks et al., 2004; Maggs, 1995;
Spear, 2000).
Adolescent risk taking behaviors such as reckless driving present an acute health risk, but others such as experimenting with drugs of abuse may create risk for the onset of chronic disorders. Experimentation with drugs during adolescence is associated with greater risk for future drug addiction, with individuals who use drugs earlier more likely to become addicted (SAMHSA, 2011; reviewed in Schramm-Sapyta et al., 2009).
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Adolescence is an important period for the onset of drug abuse and most people who use drugs at any point during their life will have initiated use during their teenage years or early twenties (Chen and Kandel, 1995; SAMHSA, 2011). Adolescent behavior appears to set the stage for experimentation with drugs, and individuals with genetic or environmental vulnerabilities are most likely to begin using drugs earlier and eventually become addicted (reviewed in Schramm-Sapyta et al., 2009). Animal data on adolescent drug self-administration vary by drug, but adolescents generally engage in greater self- administration of nicotine and ethanol than adults (reviewed in Schramm-Sapyta et al.,
2009).
The previously discussed changes in social behavior, sensation seeking, impulsivity, and cognition all contribute to increased risk taking behavior during adolescence. The influence of peers is known to increase adolescent risk taking
(reviewed in Arnett, 1992; Steinberg, 2008). A laboratory study of risk taking behavior found that adolescents, but not adults, took more risks when accompanied by peers than when alone (Gardner and Steinberg, 2005). Given that adolescents spend more time with peers and less with family members, the facilitation of risk taking by peers may be a significant factor in adolescent risk taking (Csikszentmihalyi, 1977; Larson and
Richards, 1991).
Increased sensation seeking in adolescence is also thought to be a major factor underlying risk taking behavior (reviewed in Arnett, 1992). Adolescent sensation
11
seeking may have particular relevance for experimenting with drugs of abuse, as greater sensation seeking has been associated with greater risk for drug use in both adults and adolescents (Kreek et al., 2005; Maggs, 1995; Wills, 1994; Zuckerman, 1986). Greater locomotor response to novelty in rodents has also been associated with greater sensitivity to the locomotor effects of drugs of abuse and greater psychostimulant self- administration (Bardo et al., 1996; Deroche et al., 1993; Hooks et al., 1991; Klebaur et al.,
2001; Piazza et al., 1989; Schramm-Sapyta et al., 2011; Walker et al., 2009). Animal studies generally show greater sensitivity to the rewarding effects of all drugs of abuse during adolescents, but studies of locomotor effects and self administration of psychostimulants in adult and adolescent rodents are less clear (reviewed in Schramm-
Sapyta et al., 2009). It may therefore be the case that adolescents who exhibit the greatest increases in sensation seeking are the individuals at greatest risk for drug abuse and addiction (Maggs, 1995; Wills, 1994).
There is a strong link between impulsivity and the leading causes of adolescent injury and mortality such as risk taking behavior, drug abuse, and suicide (Eaton et al.,
2012; reviewed in Mann, 2003; Perry and Carroll, 2008). Numerous human and animal studies show that increased impulsivity on delay discounting or behavioral inhibition tasks is associated with drug abuse and drug self-administration (Bechara, 2005; Jentsch and Taylor, 1999; Perry et al., 2008). It is difficult to determine whether impulsivity increases risk for drug abuse or occurs as a result of drug abuse using human studies,
12
but animal studies suggest that both possibilities are likely. Animals with above average impulsivity on delay discounting or behavioral inhibition tasks self-administer more cocaine, nicotine, and ethanol (Anker et al., 2009; Belin et al., 2008; Dalley et al., 2007;
Diergaarde et al., 2008; Diergaarde et al., 2012; Perry et al., 2005; Perry et al., 2008;
Poulos, 1995). Animals with chronic exposure to drugs of abuse given by the experimenter also have increased impulsivity (Blondel et al., 2000; Logue et al., 1992;
Paine et al., 2003; Richards et al., 1999; Simon et al., 2007). Impulsivity data from animals with self-administration experience is mixed and may be affected by the self- administration paradigm and how long the animal has been in withdrawal (Bird and
Schenk, 2012; Dalley et al., 2005a; Dalley et al., 2005b; Gipson and Bardo, 2009;
Winstanley et al., 2009). Though impulsivity plays an important role in adolescent risk taking, it is unlikely to be the sole factor. As noted above, adolescents are less impulsive than children, but engage in more risk taking behavior. The immature ability to inhibit impulses may work in conjunction with increased sensation seeking during adolescence to contribute to risk taking behavior (reviewed in Casey et al., 2008; Steinberg, 2010).
The increased vulnerability of adolescents to emotional or peer influence on cognition may also feed into risk taking behavior. When tested in an emotionally neutral situation, adolescents performed similarly to adults in a laboratory risk taking task (Figner et al., 2009). However, adolescents made more risky choices than adults when the test was reconfigured to trigger emotional responses (Figner et al., 2009).
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Adolescents are also more susceptible than adults to enhancement of risk taking by peers (Chein et al., 2011; Gardner and Steinberg, 2005). These data are consistent with observational studies showing that adolescents are most vulnerable to negative risk taking behaviors in emotionally charged situations, such as when engaged in activities perceived as fun and in the presence of peers (Maggs, 1995; reviewed in Casey et al.,
2008; Steinberg, 2008).
1.1.3.2 Affective Disorders, Suicide, and the Response to Antidepressants
Adolescence is an important period for onset of affective disorders (reviewed in
Costello et al., 2002; Kessler et al., 2005). The majority of people with anxiety disorders or depression will experience onset of the disease prior to age 24 (reviewed in Kessler et al., 2005). The increase in gonadal steroid hormones during puberty may play a role in onset of mood disorders during adolescence. Females develop a higher incidence of these disorders than males during this age period, and this increase in depressive symptoms is associated with pubertal stage (Angold et al., 1998; Zahn-Waxler et al.,
2008). Adolescence may also be a vulnerable period for disruption of neural circuit development by stressors that could contribute to affective disorders during adulthood
(reviewed in Steinberg, 2005). The cortical and limbic circuits mediating social cognition, emotional regulation, and executive function mature during adolescence, and abnormal development of these circuits could contribute to onset of anxiety disorders and depression (reviewed in Casey et al., 2010; Casey et al., 2008; Crone and Dahl, 2012;
14
Ernst et al., 2006; Tau and Peterson, 2010). The influence of serotonergic and other genetic differences on affective disorders emerges during later adolescence (around age
15), supporting the hypothesis that critical developmental changes in neural circuits mediating affective behavior continue to occur throughout adolescence (Petersen et al.,
2012; Zavos et al., 2012).
Adolescent affective disorders contribute to an increase in suicide rates between childhood and adolescence (Bertolote and Fleischmann, 2002; Evans et al., 2004; Patton et al., 2009). Suicide is very rare in childhood, but begins to occur during adolescence and rates increase into adulthood (Bertolote and Fleischmann, 2002; Patton et al., 2009).
Suicide is a significant adolescent health problem. It was one of the four leading causes of death in adolescents in the United States in 2008, accounting for 13% of all adolescent deaths, and is also a major cause of adolescent death worldwide (Bertolote and
Fleischmann, 2002; Eaton et al., 2012; Patton et al., 2009).
A complicating factor in the treatment of adolescent affective disorders is potentially increased suicidality in adolescents treated with SSRI antidepressants, the primary pharmacotherapy for these disorders (Barbui et al., 2009; Brent et al., 2009;
Dubicka et al., 2006; Hammad et al., 2006; Schneeweiss et al., 2010). Several meta- analyses of clinical trials suggested an increase in suicidality in adolescents, leading to a black-box warning from the FDA (Hammad et al., 2006; Newman, 2004). More recent analyses have supported this finding (Barbui et al., 2009; Brent et al., 2009; Dubicka et
15
al., 2006; Schneeweiss et al., 2010). Suicidality is a risk during early antidepressant treatment for all age groups, as the motor symptoms of depression are alleviated before mood improves (Hall, 2006). It is possible that developmental differences in motivated behavior and impulsivity could contribute to the increased vulnerability of adolescents to suicidality during SSRI therapy. The risks and benefits of SSRIs in adolescents have been debated, as SSRIs are effective at reducing symptoms of depression in adolescents, and not all studies find increased risk of suicide in adolescents (Correll et al., 2011;
Gibbons et al., 2012; Gibbons et al., 2007). Animal models are concordant with antidepressant efficacy in humans, as single doses of SSRIs are effective in adolescent rodents in antidepressant behavioral screens (Reed et al., 2009; Reed et al., 2008).
However, there is no animal model for suicidality and the neurobiological underpinnings of potentially increased suicidality in adolescents treated with SSRIs remain unknown.
In addition to increased suicidality, there is also concern that SSRI exposure during adolescence or earlier could alter development of neural circuits regulating sensory and affective function in the brain (Andersen and Navalta, 2004; Homberg et al.,
2010). Animal studies of chronic SSRI treatment that mimic human usage patterns reveal potential negative effects in young rodents. Several weeks of SSRI treatment during the juvenile period in rodents can result in long-lasting increases in anxiety-like behavior, but this likely models gestational or early postnatal exposure in humans
16
(Ansorge et al., 2004; reviewed in Oberlander et al., 2009). Chronic SSRI treatment initiated during adolescence may also cause long-term changes in rodent models of anxiety-like behavior, stress responsivity, memory, and sexual behavior (de Jong et al.,
2006; Homberg et al., 2011; Iniguez et al., 2010; Norcross et al., 2008; Oh et al., 2009; Sass and Wortwein, 2012; Vorhees et al., 2011). These data suggest that SSRIs may also alter development of neural circuits in children and adolescents, resulting in long-lasting changes in brain function and behavior.
1.1.4 Brain Maturation
1.1.4.1 General Brain Maturation
The final stages of brain maturation occur during adolescence and underlie the maturation of behavioral and cognitive function (reviewed in Casey et al., 2008; Luna and Sweeney, 2004). Studies of humans and animals have revealed large scale structural changes in the brain across adolescence. Development of the human brain during adolescent has been studied with both post-mortem analyses and live imaging studies, many of which have focused on the cortex. These studies collectively indicate that adolescent brain development involves increasing organization of cortical neuroanatomy and subsequent increased signaling efficiency. Cortical gray matter volume decreases across adolescence, which may reflect pruning of dendrites and axons
(Giedd, 2004; Giedd et al., 1999; Gogtay et al., 2004; Sowell et al., 2003). In keeping with this hypothesis, synaptic density decreases across adolescence in the cortex
17
(Huttenlocher, 1979). Animal studies also show declines across adolescence in the number of cortical synapses, neurons in basolateral amygdala and prefrontal cortex, and dendrites of neurons in the medial amygdala (Bourgeois et al., 1994; Markham et al.,
2007; Rubinow and Juraska, 2009; Zehr et al., 2006). Cortical thickness decreases across adolescence, reflecting large scale reorganization of the tissue (Shaw et al., 2008; Tamnes et al., 2010). Increased myelination of axons could also contribute to loss of gray matter. This hypothesis is supported by the fact that white matter volume increases linearly across adolescence and into adulthood (Barnea-Goraly et al., 2005; Giedd, 2004;
Giedd et al., 1999; Paus et al., 1999; Tamnes et al., 2010). Myelinated axons may become increasingly well organized based on data from diffusion tensor imaging (DTI). This method tracks the diffusion of water molecules to infer the level of organization of tissue. The measure “fractional anisotropy” is used to assess the diffusion of water in tissue, with a higher value signifying more restricted diffusion and thus greater tissue organization. Fractional anisotropy increases across adolescence, which suggests increasing organization of the cortical neural pathways (Barnea-Goraly et al., 2005; Lebel et al., 2008; Tamnes et al., 2010). The prefrontal cortex, an area important for decision making and behavioral inhibition, is one of the last areas to mature by all of these measures. Imaging studies of brain activity during tasks requiring focused attention or behavioral inhibition show a transition from a diffuse pattern of brain activation in children that matures across adolescence into a more focused, efficient pattern in adults
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(reviewed in Casey et al., 2008; Luna and Sweeney, 2004). The developmental changes discussed above may therefore be important for the cognitive and behavioral maturation that occurs during adolescence.
1.1.4.2 Differential Maturation of Cortical and Limbic Brain Systems
Several hypotheses have been proposed to explain how incomplete development of the brain during adolescence results in sensation-seeking, risk taking behavior (Fig.1).
Human and animal studies suggest a role for immaturity of neural circuits in the brain, as well as neuromodulatory systems projecting to these circuits. Based on human fMRI data, Casey et al proposed that earlier maturation of limbic brain systems relative to the prefrontal cortex could contribute to adolescent risk taking and vulnerability to affective disorders (reviewed in Casey et al., 2008). Casey suggests that mature limbic function during adolescence produces powerful emotional drives and incentive to pursue rewarding stimuli, but immature prefrontal cortical function results in reduced ability to regulate these behaviors (Fig.1a) (reviewed in Casey et al., 2008). Several human imaging studies show increased nucleus accumbens and striatal activation in adolescents in response to rewarding stimuli (Cohen et al., 2010; Ernst et al., 2005;
Galvan et al., 2006; Van Leijenhorst et al., 2010). Many other studies have found increased amygdala activation in adolescents in response to fearful faces, perhaps indicating increased emotionality (Guyer et al., 2008; Hare et al., 2008; Monk et al., 2003).
Adolescents also exhibit immature patterns of diffuse prefrontal cortical activity similar
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to those seen in children rather than more focused adult-typical activation (Galvan et al.,
2006; Rubia et al., 2006; Tamm et al., 2002). These data are consistent with Casey, et al’s hypothesis of increased limbic activity in adolescents due to immature prefrontal cortical regulation.
Ernst et al have proposed a similar hypothesis that differentiates limbic brain regions into a reward system with the nucleus accumbens as a key brain region, and a harm avoidance system centered around the amygdala (reviewed in Ernst and Fudge,
2009; Ernst et al., 2006). In the “triadic model” (Fig.1b) Ernst proposes that adolescents have a hyperactive reward approach system, a hypoactive harm avoidance system, and an immature prefrontal cortex to regulate this imbalanced system (reviewed in Ernst and Fudge, 2009; Ernst et al., 2006). Many of the same imaging studies of the nucleus accumbens and prefrontal cortex were used to support the hypothesis of a hyperactive reward system and immature prefrontal cortical function (Cohen et al., 2010; Ernst et al.,
2005; Galvan et al., 2006; Rubia et al., 2006; Tamm et al., 2002; Van Leijenhorst et al.,
2010). A key difference between Ernst’s and Casey’s hypothesis lies in interpretation of fMRI studies of the amygdala. While Casey interpreted greater adolescent amygdala activation in response to fearful faces as indicative of greater adolescent emotionality,
Ernst used an imaging study in which adolescents exhibited less amygdala activation in response to losing money in a gambling task to suggest a hypoactive avoidance/aversive system ( Ernst et al., 2005; reviewed in Casey et al., 2008; Ernst et al., 2006). The nature
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of the stimuli used in amygdala imaging studies may explain the apparent inconsistency of the data. Fearful faces are a social cue, and processing of faces continues to develop across adolescence (reviewed in Burnett et al., 2011). Greater amygdala reactivity in response to fearful faces in adolescents may therefore be influenced by the social nature of the stimulus. In contrast, the lower amygdala reactivity to reward omission in a gambling task could be influenced by age differences in the subjective value of money
(reviewed in Ernst et al., 2005; Ernst et al., 2006). Further study is therefore needed to clarify the ontogeny of amygdala responsivity to aversive stimuli.
Figure 1: Neurobiology of Adolescent Risk Taking Two current hypotheses of the neurobiology underlying adolescent risk taking. A.) Casey et al suggest that maturation of limbic brain regions prior to the prefrontal cortex results in strong emotional drives that adolescents are unable to properly regulate (Casey et al., 2008). Adapted from (Somerville et al., 2010). B.) Ernst et al hypothesize that adolescents have a hyperactive approach system and a hypoactive avoidant system, and that this imbalance is further exacerbated by immature prefrontal cortical regulation of these subcortical drives. Adapted from (Ernst et al., 2006).
Animal studies of adolescent brain development show a similar pattern as human studies, with the efficiency of neural pathways and connections between the
21
cortex and limbic brain regions increasing across adolescence. Dendritic and axonal pruning has been observed in the cortex and limbic brain regions such as the amygdala in rodents and primates (Bourgeois et al., 1994; Cressman et al., 2010; Zehr et al., 2006).
Other pathways continue to grow across adolescence such as projections between the amygdala and cortex (Cunningham et al., 2002). Similar to human fMRI data, analysis of cortical activity using electrode arrays has shown less organized activity in the adolescent cortex when animals perform a goal directed task (Sturman and
Moghaddam, 2011b). These studies show that similar changes occur in rodent brains and human brains during adolescence, making rodents a valid animal model to study brain development during this age period.
1.1.4.3 Dopamine and Serotonin
Neuromodulatory systems are also included in Ernst’s triadic model (Fig.1b), with a hyperactive dopaminergic system feeding into the reward system, and potentially lower serotonergic function contributing to the hypoactive avoidance system
(reviewed in Ernst et al., 2006). Others have also proposed a role for lower serotonergic function in adolescent risk taking (reviewed in Chambers et al., 2003; Crews et al., 2007).
The dopaminergic and serotonergic systems work together to modulate approach and avoidance behavior (reviewed in Boureau and Dayan, 2011; Cools et al., 2011; Daw et al.,
2002; Dayan and Huys, 2009). Dopamine mediates the reinforcing effects of rewarding stimuli and approach to these stimuli, while serotonin is important for behavioral
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inhibition in response to aversive stimuli (Crockett et al., 2009; Crockett et al., 2012; reviewed in Schultz, 2010; Soubrie, 1986). A skewed balance between dopaminergic and serotonergic signaling during adolescence could therefore contribute to increased risk taking behavior and alter the response to drugs of abuse, contributing to addiction vulnerability. This possibility is supported by a primate study that found that the ratio of the dopamine metabolite HVA to the serotonin metabolite 5-HIAA in cerebrospinal fluid was at its lowest during adolescence, indicating a greater ratio of dopaminergic to serotonergic activity (Fairbanks et al., 2004). Peaks in dopaminergic neuron firing rate and dopamine receptor expression suggest dopaminergic hyperactivity during adolescence (Andersen et al., 2000; Brenhouse et al., 2008; Gelbard et al., 1989; Giorgi et al., 1987; McCutcheon and Marinelli, 2009; Teicher et al., 1995). Developmentally lower serotonergic function during adolescence could further contribute to this imbalance, but little is known about development of the serotonergic system across adolescence.
Given that adolescent behavior is characterized by increased approach type behaviors, the ontogeny of the dopaminergic system across adolescence has been well studied. In humans, most markers of dopaminergic innervation to the striatum such as dopamine transporter and tyrosine hydroxylase expression fall across adolescence to adult levels, though dopamine content in the striatum increases during adolescence
(Haycock et al., 2003; Meng et al., 1999). Dopamine receptors are overexpressed in early childhood, and expression decreases during childhood and adolescence, with a slower
23
steady decline throughout adult life (Meng et al., 1999; Rinne et al., 1990; Seeman et al.,
1987). In contrast to humans, markers of dopaminergic innervation increase in adolescent rodents (Cao et al., 2007; Coulter et al., 1996; Kalsbeek et al., 1988; Kirksey and Slotkin, 1979; Porcher and Heller, 1972; Tarazi et al., 1998). Adolescent rats also have lower baseline and electrically stimulated extracellular dopamine in several brain regions (Andersen and Gazzara, 1993; Gazzara et al., 1986; Laviola et al., 2001; Stamford,
1989; Walker and Kuhn, 2008). However, adolescent rodents exhibit a transient peak in dopamine receptor expression in the prefrontal cortex and striatum that is later pruned to adult levels (Andersen et al., 2000; Brenhouse et al., 2008; Gelbard et al., 1989; Giorgi et al., 1987; Teicher et al., 1995). This transient overexpression of dopamine receptors is more pronounced in male adolescent rats than in females (Andersen et al., 1997). The firing rate of dopaminergic neurons also peaks during adolescence in rodents
(McCutcheon and Marinelli, 2009). These studies show that the dopaminergic system is still developing during adolescence and that immaturity of the dopaminergic system could contribute to adolescent-typical behavior changes and altered responses to drugs of abuse (reviewed in Chambers et al., 2003; Crews et al., 2007; Ernst et al., 2006).
Several authors suggest that immaturity of the serotonergic system could contribute to adolescent risk taking behavior and the emergence of mood disorders, but few studies have directly tested this hypothesis (reviewed in Chambers et al., 2003;
Crews et al., 2007; Ernst et al., 2006). Serotonin is important for behavioral inhibition,
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and deficits in central serotonergic function are associated with impulsivity and aggression (Crockett et al., 2009; Crockett et al., 2012; Higley and Linnoila, 1997; Higley et al., 1996; Mehlman et al., 1994; Soubrie, 1986; Virkkunen et al., 1995). Studies of the ontogeny of the serotonergic system during adolescence suggest that presynaptic serotonergic function may be immature during adolescence (Dao et al., 2011; Kirksey and Slotkin, 1979; Loizou and Salt, 1970; Mercugliano et al., 1996; Moll et al., 2000).
However, no study has directly compared serotonergic modulation of behavior in adults and adolescents, and only one study has investigated drug effects on extracellular serotonin in adolescents (Staiti et al., 2011). The goal of this project was to test the hypothesis that lower forebrain serotonergic function during adolescence contributes to risk taking behavior and alters the response to drugs targeting the serotonin system.
The following section provides background on serotonergic neurotransmission and serotonergic modulation of behavior.
1.2 Serotonin
Serotonin was initially isolated from serum and was noted as causing vasoconstriction in multiple preparations (Rapport et al., 1948). These scientists named it serotonin because it was found in serum and increased the tone of blood vessels
(Rapport et al., 1948). Another early study termed the substance “thrombocytin” (Rand and Reid, 1951). Serotonin was also isolated from the enterochromaffin cells of the gastric mucosa and called “enteramine” as it was not initially recognized to be the same
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compound as the serotonin isolated from serum (Erspamer and Asero, 1952). Shortly after these discoveries, serotonin was found in the brain (Amin et al., 1954; Twarog and
Page, 1953). In mammals, serotonin is found throughout the body, with high levels in the gut, platelets, and the brain (Berger et al., 2009). Serotonin is involved in a vast range of functions throughout the body, but this review will focus on the actions of serotonin in the brain. The actions of serotonin in the forebrain to modulate behavior will be of particular interest, as these are likely the most relevant to adolescent risk taking behavior and the behavioral effects of serotonergic drugs.
1.2.1 Serotonergic Physiology
1.2.1.1 Anatomy
Serotonergic neuroanatomy is generally similar across mammalian species, including rats, cats, non-human primates, and humans (Baker et al., 1991a; Baker et al.,
1991b; Dahlstrom, 1964; Felten and Sladek, 1983; Jacobs et al., 1984; Steinbusch, 1981).
Initial studies of serotonergic neurons in rodents discovered a number of cell groups in the brainstem that were termed B1-B9 (Dahlstrom, 1964). Some of these cell groups send their projections into the brain and others send projections down the spinal cord. These cell groups are mostly located in the raphe nuclei, though there are some serotonergic neurons that lie outside of the raphe (Dahlstrom, 1964). The nuclei sending their projections into the brain are located in the midbrain and pons, and consist of the dorsal raphe nucleus (DRN) (B6 and B7), the median raphe nucleus (MRN) (B5 and B8), and the
26
caudal linear nucleus (B8) (Dahlstrom, 1964; Jacobs and Azmitia, 1992; Tork, 1990). The nuclei projecting down the spinal cord are located in the medulla and include the raphe obscurus (B2), the raphe pallidus (B1, B4), and the raphe magnus (B3) (Dahlstrom, 1964;
Jacobs and Azmitia, 1992; Tork, 1990). The DRN and MRN send axons to almost every structure in the brain (Steinbusch, 1981). The nuclei have separate, but overlapping patterns of projections, with the striatum, amygdala, and basal ganglia preferentially innervated by the DRN, and the dorsal hippocampus and septum receiving more innervation from the MRN (Azmitia and Segal, 1978; Molliver, 1987; Vertes, 1991; Vertes and Martin, 1988; Wallman et al., 2011). Both nuclei innervate the cortex, with regional differences in the ratio of dorsal/median raphe innervation (Kosofsky and Molliver,
1987). In addition to different terminal fields, projections of neurons of the DRN and
MRN have different morphology. DRN neurons have thin axons with small, irregularly shaped varicosities, while axons of MRN neurons are thicker with larger round varicosities (Kohler et al., 1980; Kosofsky and Molliver, 1987).
1.2.1.2 Electrophysiology
Serotonergic neurons have a slow, rhythmic firing rate that averages around 1-3
Hz at baseline (Aghajanian et al., 1968; Jacobs and Fornal, 1991; McGinty and Harper,
1976; Mosko and Jacobs, 1974; Trulson and Jacobs, 1979). Many of the early studies on serotonergic activity in awake animals were conducted in cats and recorded from the midline region of the dorsal raphe nucleus. These studies found that the regular
27
baseline firing of serotonergic neurons increased during periods of active behavior and decreased during sleep (Jacobs and Fornal, 1991; McGinty and Harper, 1976; Trulson and Jacobs, 1979). Neurons in the dorsal raphe also showed increased activity when cats were engaged in oral movements such as chewing or grooming (Fornal et al., 1996).
However, serotonergic neurons did not respond to either pulses of light or changes in the light/dark cycle (Mosko and Jacobs, 1974; Trulson and Jacobs, 1983). Serotonergic neuron firing increased in response to stressful stimuli, but not beyond the range found by generally activating stimuli (Wilkinson and Jacobs, 1988). These studies lead to the hypothesis that serotonergic function primarily regulates arousal and motor activity
(reviewed in Jacobs and Fornal, 1999). More recent electrophysiological studies of the dorsal raphe have focused on transient changes in firing and have recorded from the lateral regions of the dorsal raphe nucleus. These studies show that subsets of DRN neurons increase firing in response to a variety of sensory stimuli and motor activities
(Ranade and Mainen, 2009; Waterhouse et al., 2004).
1.2.1.3 Biochemistry
The basic synthetic and metabolic pathway of serotonin was worked out soon after its discovery in the brain (reviewed in Udenfriend et al., 1956). Serotonin is synthesized from the amino acid tryptophan (reviewed in Udenfriend et al., 1956).
Tryptophan is hydroxylated by tryptophan hydroxylase 2 (TPH2), the brain-specific isoform of tryptophan hydroxylase, to form 5-hydroxytryptophan (5-HTP) (Gal et al.,
28
1963; Grahame-Smith, 1964; Walther et al., 2003). Tryptophan hydroxylase is not saturated under normal conditions and is the rate limiting step in serotonin synthesis, so serotonin synthesis is dependent upon available concentrations of tryptophan (Carlsson and Lindqvist, 1978; Fernstrom and Wurtman, 1971; Jequier et al., 1967). 5-HTP is then decarboxylated by l-amino acid decarboxylase (l-AADC) to form 5-hydroxytryptamine
(5-HT), or serotonin (Lovenberg et al., 1962). Serotonin is metabolized into 5- hydroxyindole acetic acid (5-HIAA) by the mitochondrial enzyme monoamine oxidase
(MAO) (Sjoerdsma et al., 1955). Serotonin is primarily metabolized by the MAO isoform
MAO A, though metabolism by MAO B is also possible (Cases et al., 1995; Kinemuchi et al., 1980; Mitra and Guha, 1980).
1.2.1.4 Serotonin Release and Regulation of Extracellular Serotonin
Serotonin is accumulated in vesicles by the vesicular monoamine transporter 2
(VMAT2), and is released when action potentials arrive at the terminal (reviewed in
Henry et al., 1998; Travis et al., 2000; Veenstra-VanderWeele et al., 2000). Serotonergic signaling in the brain consists of both synaptic signaling and volume transmission, with volume transmission thought to be the primary mode of signaling (Descarries et al.,
1975; Fuxe et al., 2010; Hensler, 2006; Seguela et al., 1989). Levels of extracellular serotonin are regulated by the serotonin transporter (SERT) and 5-HT1A and 5-HT1B autoreceptors. SERT removes serotonin from the extracellular space by transporting it back into the neuron (reviewed in Blakely and Edwards, 2012; Rudnick, 2006). The 5-
29
HT1A and 5-HT1B receptors provide feedback inhibition of serotonin signaling. Both receptors are inhibitory G-protein coupled receptors that couple to Gi (reviewed in
Barnes and Sharp, 1999). 5-HT1A autoreceptors are expressed on cell bodies and dendrites in the raphe nuclei, while 5-HT1B autoreceptors are expressed on serotonergic axons and terminals (Riad et al., 2000; Sari et al., 1999). 5-HT1A receptors suppress serotonergic neuron firing by activating a G-protein coupled potassium channel, and 5-
HT1B receptors suppress serotonin release in serotonergic terminal fields (Aghajanian et al., 1990; Engel et al., 1986; Trillat et al., 1997). 5-HT1B receptors are capable of activating
G-protein coupled potassium channel when tranfected into cardiac cells, but there is a lack of evidence that 5-HT1B autoreceptors act via potassium channels in vivo (Ghavami et al., 1997). Activation of both receptor subtypes reduces serotonin synthesis, and there is evidence that the 5-HT1B activation enhances SERT activity to further reduce extracellular serotonin levels (Hagan et al., 2012; Hjorth et al., 1995).
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Figure 2: Serotonergic Terminals, Release, and Metabolism
An illustration of serotonergic terminals (A.) and serotonin release and uptake (B.). A.) Serotonin is packaged in vesicles in the axon terminals of serotonergic neurons. These vesicles fuse with the cell membrane and release serotonin in response to action potential firing and subsequent calcium influx. The serotonin transporter and autoreceptors (5-HT1A and 5-HT1B) are expressed on serotonergic neurons and regulate extracellular levels of serotonin. The effects of serotonin are mediated by a large family of receptors (5-HT1-7 families) expressed on postsynaptic neurons. B.) After its release into the extracellular space, serotonin is taken back into the neuron by the serotonin transporter. Free intracellular serotonin is either packaged back into vesicles by the transporter VMAT2 or metabolized to 5-HIAA by MAO.
1.2.1.5 Serotonin Receptors
The effects of serotonin are mediated by a large family of serotonin receptors expressed on postsynaptic neurons. There are at least 14 different serotonin receptor subtypes that are classified into 7 families termed 5-HT1 through 5-HT7 (reviewed in
Barnes and Sharp, 1999; Hannon and Hoyer, 2008; Hoyer et al., 2002; Nichols and
31
Nichols, 2008). The majority of serotonin receptors are G-protein coupled receptors, with the exception of the 5-HT3 receptor, which is a ligand-gated ion channel (reviewed in Barnes and Sharp, 1999; Hannon and Hoyer, 2008; Hoyer et al., 2002; Nichols and
Nichols, 2008). Most, but not all of these receptors are expressed in the brain. The 5-
HT1, 5-HT2, and 5-HT3 receptors are the best understood, though the 5-HT4, 5-HT5, 5-
HT6, and 5-HT7 receptors are also expressed in the brain and likely contribute to serotonin’s effects on physiology and behavior.
The 5-HT1 receptor family includes the 5-HT1A, 5-HT1B, 5-HT1D, 5-HT1E, and 5-
HT1F receptors, all of which negatively regulate adenylyl cyclase activity and couple to
Gi (reviewed in Barnes and Sharp, 1999; Hannon and Hoyer, 2008; Hoyer et al., 2002;
Nichols and Nichols, 2008). The 5-HT1A and 5-HT1B receptors are the best characterized of this family. In addition to their role as autoreceptors, both subtypes are expressed on non-serotonergic postsynaptic neurons throughout the forebrain (Boschert et al., 1994;
Miquel et al., 1992; Sari et al., 1999). The 5-HT1A receptor is widely expressed in the brain, especially in the cortex and hippocampus, with very low expression in the striatum and cerebellum (Hall et al., 1997; Khawaja, 1995; Kung et al., 1995; Miquel et al.,
1992; Radja et al., 1991; Wright et al., 1995). The 5-HT1A receptor is expressed in pyramidal neurons and interneurons of the cortex, and plays an important role in regulating neuronal excitability (Amargos-Bosch et al., 2004; de Almeida and Mengod,
2008; Llado-Pelfort et al., 2012; Santana et al., 2004). 5-HT1A receptors are primarily
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expressed on the axon hillock of cortical pyramidal neurons and may function to regulate output of these cells (Andrade, 2011; Azmitia et al., 1996). The 5-HT1B receptor is highly expressed in the striatum, basal ganglia, and cerebellum (Maroteaux et al.,
1992; Radja et al., 1991; Varnas et al., 2001). In addition to being serotonin autoreceptors,
5-HT1B receptors are expressed on terminals of other neurons and regulate release of other neurotransmitters (Sari, 2004; Tanaka and North, 1993). There are minor species differences in the sequence of the 5-HT1B receptor between rodents and humans, and human 5-HT1B was initially named 5-HT1D (reviewed in Hoyer et al., 2002; Nichols and
Nichols, 2008). There were two human 5-HT1D genes, which were named 5-HT1Dα and 5-
HT1Dβ (Weinshank et al., 1992). The human 5-HT1Dβ receptor was renamed 5-HT1B when it was determined that the two were analogous receptors (Adham et al., 1992; Hartig et al., 1996). The 5-HT1Dα receptor was renamed 5-HT1D (Hartig et al., 1996). The 5-HT1D, 5-
HT1E and 5-HT1F receptors are expressed throughout the brain, though their function is less well understood (reviewed in Hannon and Hoyer, 2008; Nichols and Nichols, 2008).
5-HT1D and 5-HT1F receptors are targets of drugs used to treat migraine, which act on the trigeminovascular system in the brain (Villalon et al., 2003). The 5-HT1E receptor is expressed in humans and some other mammalian species, but has not been found in rodents (Bai et al., 2004).
The 5-HT2 family of receptors couples to Gq subunits, and activation of the receptors activates phospholipase C, resulting in production of diacylglycerol and
33
inositol triphosphate (reviewed in Barnes and Sharp, 1999; Hannon and Hoyer, 2008;
Hoyer et al., 2002; Nichols and Nichols, 2008). There are three 5-HT2 receptors, the 5-
HT2A, 5-HT2B, and 5-HT2C receptors (reviewed in Barnes and Sharp, 1999; Hannon and
Hoyer, 2008; Hoyer et al., 2002; Nichols and Nichols, 2008). The 5-HT2A receptor is expressed throughout the brain, with particularly heavy expression in the cortex (Burnet et al., 1995; Mengod et al., 1990; Pazos et al., 1985; Pazos et al., 1987; Pompeiano et al.,
1994; Wright et al., 1995). 5-HT2A is expressed in pyramidal neurons and interneurons in the cortex and functions along with 5-HT1A receptors to regulate excitability of cortical pyramidal neurons (Amargos-Bosch et al., 2004; Andrade, 2011; Araneda and Andrade,
1991; Burnet et al., 1995; de Almeida and Mengod, 2007; Morilak et al., 1994; Santana et al., 2004). 5-HT2A receptors are primarily expressed on the apical dendrites of pyramidal neurons, and stimulation of these receptors depolarizes the cells (Aghajanian and
Marek, 1997; Araneda and Andrade, 1991; Cornea-Hebert et al., 1999; Davies et al., 1987;
Hamada et al., 1998; Tanaka and North, 1993; Willins et al., 1997). This effect is associated with increased glutamatergic signaling to pyramidal neurons and is thought to be caused by activation of local cortical neuronal networks (Beique et al., 2007). The
5-HT2B receptor is only expressed in low levels in the brain, but is more highly expressed in the periphery (Bonhaus et al., 1995; Duxon et al., 1997; Pompeiano et al., 1994). In contrast to 5-HT2B, 5-HT2C receptors are primarily expressed in the central nervous system (reviewed in Barnes and Sharp, 1999). 5-HT2C receptors were originally called 5-
34
HT1C, but they were reclassified into the 5-HT2 family based on their genetic sequence and activation of phospholipase C rather than inhibition of adenylyl cyclase (Hoyer et al., 1994). They are found in many brain regions, including the cortex, striatum, basal ganglia, hippocampus, and amygdala (Clemett et al., 2000; Pasqualetti et al., 1999;
Pompeiano et al., 1994; Wright et al., 1995). 5-HT2C receptors also excite neurons, but do not play a major role in regulating cortical excitability like 5-HT2A receptors (Andrade,
2011; reviewed in Barnes and Sharp, 1999). However, 5-HT2C signaling in limbic brain regions is important for serotonergic effects on behavioral inhibition (Bagdy et al., 2001;
Campbell and Merchant, 2003; Christianson et al., 2010; Dekeyne et al., 2000; Gibson et al., 1994; Vicente and Zangrossi, 2011).
The 5-HT3 receptor is the only serotonin receptor that is a ligand-gated ion channel (reviewed in Barnes and Sharp, 1999; Hannon and Hoyer, 2008; Hoyer et al.,
2002; Nichols and Nichols, 2008). The receptor has two subunits with known function,
5-HT3A and 5-HT3B (reviewed in Barnes et al., 2009; Nichols and Nichols, 2008). Human genes for 5-HT3C, 5-HT3D, and 5-HT3E subunits have been found, but their function remains unclear (reviewed in Barnes et al., 2009). The functional receptor is composed of five subunits, which consist either of entirely 5-HT3A subunits or a combination of 5-
HT3A and 5-HT3B subunits (Barrera et al., 2005; Maricq et al., 1991; reviewed in Barnes et al., 2009). The 5-HT3 receptor is a non-selective cation channel that depolarizes neurons, and its highest expression levels in the brain are found in the brain stem in the area
35
postrema and nucleus of the solitary tract, where the receptors induce vomiting (Brown et al., 1998; Kilpatrick et al., 1989; Nichols and Nichols, 2008; Tecott et al., 1993; Waeber et al., 1989; reviewed in Barnes et al., 2009). 5-HT3 receptors are also found in the forebrain in the cortex, hippocampus, amygdala, and striatum, though expression levels are lower than in the brain stem (Kilpatrick et al., 1989; Tecott et al., 1993; Waeber et al.,
1989).
The 5-HT4, 5-HT6, and 5-HT7 receptors couple to Gs subunits and stimulate production of cyclic AMP (reviewed in Barnes and Sharp, 1999; Hannon and Hoyer,
2008; Hoyer et al., 2002; Nichols and Nichols, 2008). These receptors have splice variants, but only one unique gene per family (reviewed in Barnes and Sharp, 1999;
Hannon and Hoyer, 2008; Hoyer et al., 2002; Nichols and Nichols, 2008). All three receptors are expressed in the brain, with the 5-HT4 and 5-HT6 receptors having somewhat overlapping expression patterns. 5-HT4 and 5-HT6 receptors are expressed in many brain regions, with highest levels in the cortex, hippocampus, striatum, and basal ganglia for 5-HT4, and in the cortex, hippocampus and striatum for 5-HT6 (Bonaventure et al., 2000; Gerard et al., 1997; Jakeman et al., 1994; Ruat et al., 1993a; Ward et al., 1995).
The 5-HT7 receptor is also expressed in cortex and hippocampus, but is more highly expressed in the thalamus and hypothalamus (Gustafson et al., 1996; Neumaier et al.,
2001; Ruat et al., 1993b). While their function is not as well understood as the 5-HT1 and
5-HT2 receptors, the 5-HT4, 5-HT6, and 5-HT7 receptors are thought to contribute to
36
serotonin’s effects on affective behavior, cognition, and memory, as well as other physiological processes such as feeding and circadian rhythms (reviewed in Barnes and
Sharp, 1999; Bockaert et al., 2011; Carr and Lucki, 2010; Matthys et al., 2011; Nichols and
Nichols, 2008).
The 5-HT5 family includes two receptors, 5-HT5A and 5-HT5B (reviewed in Barnes and Sharp, 1999; Hannon and Hoyer, 2008; Hoyer et al., 2002; Nichols and Nichols,
2008). These receptors couple to Gi and inhibit the activity of adenylate cyclase
(reviewed in Nichols and Nichols, 2008). 5-HT5A receptor mRNA is expressed throughout the brain, including the cortex, hippocampus, striatum, thalamus, hypothalamus, amygdala, and cerebellum (Erlander et al., 1993; Pasqualetti et al., 1998;
Plassat et al., 1992; Rees et al., 1994). 5-HT5B mRNA is found in the hippocampus and habenula (Erlander et al., 1993; Matthes et al., 1993; Wisden et al., 1993). The function of these receptors is largely unknown, and it is thought that humans do not express a functional 5-HT5B receptor (Grailhe et al., 2001; reviewed in Nichols and Nichols, 2008).
1.2.2 Ontogeny
1.2.2.1 Humans and Non-human Primates
Serotonergic neurons differentiate as early as the fifth gestational week, and are grouped into the raphe nuclei by the fifteenth week of gestation (Sundstrom et al., 1993;
Takahashi et al., 1986). These neurons proliferate and send axons to the forebrain and down the spinal cord throughout gestation, reaching the cortical plate around week 13
37
of gestation (Olson et al., 1973; Verney et al., 2002). The serotonin transporter is temporarily expressed in thalamocortical projecting neurons for around two weeks during gestation, suggesting that serotonin may play a trophic role in development of neural circuits (Verney et al., 2002). Similar findings have been published in rodents and it appears that interfering with serotonergic function early in development can lead to life-long alterations in affective behavior (Ansorge et al., 2004; reviewed in Oberlander et al., 2009). The postnatal development of serotonergic projections to the forebrain has not been well described in humans, but other measures of central serotonergic function have been studied. Levels of serotonin and 5-HIAA in cerebrospinal fluid (CSF) are elevated at birth and fall to adult levels by 3-5 years of age (Hedner et al., 1986; Seifert et al.,
1980). Serotonin transporter function in platelets can serve as an indicator of central
SERT function, and 3H-imipramine binding and serotonin uptake in platelets is similar between adolescents and adults (Weizman et al., 1986). Data on the ontogeny of serotonin receptors in humans is also limited. At birth, levels of 5-HT1A mRNA are similar to adult levels in the frontal cortex, dorsal raphe, and parts of the hippocampus, but are higher compared to adults in the cerebellum and the molecular layer of the dentate gyrus (del Olmo et al., 1998). This study only included neonates, young children, and adults, so it is unclear when 5-HT1A levels mature. A 5-HT1A autoradiography study found decreases in 5-HT1A binding with age in the cortex and raphe nuclei between individuals in their mid- to late teens and early twenties compared
38
to middle-aged adults (Dillon et al., 1991). These studies show that crude measures of central serotonergic function mature quite early in humans, but expression of 5-HT1A receptors may still be slightly higher than adults during adolescence.
1.2.2.2 Non-human Primates
Many studies of the ontogeny of the serotonin system in non-human primates have been conducted in rhesus monkeys. Serotonergic neurons develop earlier in rhesus monkeys than in humans, with the peak of serotonergic neurogenesis in the dorsal raphe occurring around day 30 of gestation (Levitt and Rakic, 1982). Several measures of central serotonergic function reach adult levels during the juvenile period in rhesus monkeys, with adult levels of serotonergic inputs to the cortex achieved by the second postnatal week, and mature cortical serotonin content reached second to fifth postnatal months (Goldman-Rakic, 1982; Lambe et al., 2000). However, transient changes in serotonergic function occur later in development. Prefrontal cortical serotonin content is similar to adult levels at 5 months of age, but decreases by the eighth postnatal month and remains lower than in adults until around 2 to 3 years of age
(Goldman-Rakic, 1982). A study of grivet monkeys showed that the ratio of 5-HIAA to
HVA in cerebrospinal fluid across development follows a u-shaped pattern and is at its lowest during adolescence (Fairbanks et al., 1999). Data from non-human primates therefore show transient changes in serotonergic function during the juvenile and adolescent periods that could be relevant for risk taking behavior.
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1.2.2.3 Rodents
Cells staining positive for serotonin first appear during days 12 to 14 of gestation
(E12-E14) (Aitken and Tork, 1988; Lauder and Bloom, 1975; Lidov and Molliver, 1982;
Wallace and Lauder, 1983). The transcription factors Pet1 and Lmx1b are required for the development of serotonergic neurons and for maintaining serotonergic phenotype throughout the life of the animal (Ding et al., 2003; Hendricks et al., 2003; Liu et al., 2010;
Zhao et al., 2006). Other transciption factors required for development of serotonergic neurons include Gata-2, Gata-3, Nkx2.2, Nkx6.1, Ascl1, Foxa2, and Insm-1, but these genes are not necessary for maintaining serotonergic phenotype throughout postnatal life (reviewed in Deneris and Wyler, 2012). Serotonergic neurons send out projections that reach the telencephalon by E17, and axons have reached all target regions by E21
(Aitken and Tork, 1988; Lidov and Molliver, 1982; Wallace and Lauder, 1983). Axon arborization continues postnatally, with the adult pattern of serotonergic innervation achieved by PN21 (Lidov and Molliver, 1982). Mature innervation density has been reported at this age in the cortex and hippocampus, but may be lower in the striatum
(Lidov and Molliver, 1982; Loizou, 1972). The basal firing pattern of serotonergic neurons appears to mature early, as animals from PN4 to PN24 have similar basal firing rates as adults (Lanfumey and Jacobs, 1982). Neuronal input into the raphe nuclei increases throughout development, with synaptogenesis continuing across adolescence, as PN30 rats have fewer synaptic profiles in dorsal and median raphe than adults
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(Lauder and Bloom, 1975). The whole brain 5HIAA/5HT ratio (serotonin turnover), an indirect measure of serotonin release, matures around PN20 (Herregodts et al., 1990).
However, certain brain regions do not have mature serotonin content during adolescence. Most studies find that adolescent rats have lower serotonin content in hippocampus, cortex, and striatum (Loizou and Salt, 1970; Mercugliano et al., 1996;
Nomura et al., 1976). The rate of serotonin synthesis is likely to mature during early adolescence, as tryptophan hydroxylase activity reaches adult levels by PN30 in the forebrain (Deguchi and Barchas, 1972; Park et al., 1986; Schmidt and Sanders-Bush,
1971). SERT autoradiography studies have found lower radioligand binding in the adolescent cortex, though results from subcortical structures have been mixed (Dao et al., 2011; Galineau et al., 2004; Moll et al., 2000; Tarazi et al., 1998). Lower SERT binding by autoradiography is consistent with lower synaptosomal uptake of serotonin observed in homogenates of striatum and cortex (Kirksey and Slotkin, 1979). Early adolescents may also have fewer serotonergic synapses in several forebrain regions. Studies of forebrain serotonergic synapse development in rats have revealed a transient decrease in the percentage of serotonergic axons forming synapses around PN21 that returned to mature levels by mid-adolescence (PN35) in the lateral geniculate nucleus, visual cortex, basal forebrain nuclei, and superior colliculus (Dinopoulos et al., 1995, 1997; Dori et al.,
1996; Dori et al., 1998). This transient dip in serotonergic synapses occurred in sensory, but not motor areas (Dori et al., 1996; Dori et al., 1998).
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Many studies of the ontogeny of serotonin receptor expression show attainment of adult levels of expression during the juvenile period (Basura et al., 2008; Daval et al.,
1987; Garcia-Alcocer et al., 2006; Li et al., 2004; Morilak and Ciaranello, 1993; Pranzatelli and Galvan, 1994; Vizuete et al., 1997; Waeber et al., 1996; Waeber et al., 1994).
However, a common pitfall of these studies is that they do not include adolescents, but skip from the late juvenile period (around PN21) to adulthood. This could result in failure to detect transient changes in expression during adolescence similar to those seen with dopamine receptors. The ontogenetic pattern of serotonin receptor expression varies by brain region, and several patterns of expression have been observed. In some instances, levels of serotonin receptors are at their peak at birth and decline to adult levels. This has been observed for 5-HT1A receptors in cerebellum, 5-HT2C expression in regions of the hippocampus, and 5-HT7 receptors in the striatum and thalamus (Daval et al., 1987; Garcia-Alcocer et al., 2006; Vizuete et al., 1997). Another common pattern is overexpression and pruning of serotonin receptors. This is similar to dopamine overexpression and pruning during adolescence, though most studies show that receptors are pruned to mature levels prior to adolescence. This pattern has been observed for 5-HT1A expression in the thalamus and brain stem, 5-HT2A and 5-HT2C in regions of the cortex, and 5-HT4 in the basal ganglia (Basura et al., 2008; Daval et al.,
1987; Li et al., 2004; Morilak and Ciaranello, 1993; Waeber et al., 1996). In other brain regions there is a steady increase in receptor expression that plateaus at adult levels.
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This has been reported for 5-HT1A expression in the cortex and hippocampus, 5-HT1B expression in the cortex, striatum, and hippocampus, and 5-HT4 receptors in the striatum and hippocampus (Daval et al., 1987; Pranzatelli and Galvan, 1994; Waeber et al., 1996). This has also been shown for 5-HT2A and 5-HT2C in whole cortex and hippocampus, despite overexpression and pruning in specific regions of these structures
(Li et al., 2004). Some studies have investigated functional changes in serotonin receptors across development. Serotonin has a net inhibitory effect on cortical neuron firing in mid-adolescent (PN35) rats, while it has a net excitatory effect in younger animals (Beique et al., 2004). This was shown to be due to a decrease in 5-HT7 receptor mediate excitation and an increase in 5-HT1A mediated inhibition (Beique et al., 2004).
Unfortunately, this study did not investigate adult rats, so it remains uncertain whether further changes occur across adolescent development. A study that directly compared adolescents and adults found a change in 5-HT1A modulation of adenylyl cyclase activity
(Xu et al., 2002). Treatment with 8-OH DPAT stimulated cyclase activity in adolescent
(PN45) cortex and brainstem, but inhibited activity in adults (PN75) (Xu et al., 2002).
This and another study also found decreases between adolescence and adulthood in 5-
HT1A binding in forebrain, midbrain, and brainstem, and decreases in 5-HT2 binding in cortex (Slotkin et al., 2008; Xu et al., 2002). It may therefore be the case that there are transient changes in serotonin receptor function during adolescence that have been missed by studies that excluded adolescent animals.
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The findings discussed above show that the ontogeny of the serotonergic system has been well characterized in early postnatal development in humans, non-human primates, and rodents. However, serotonergic function during adolescence remains poorly understood. Data from primates and rodents suggest that serotonergic function may be immature during adolescence. Studies that have assessed serotonergic function during adolescence show either ongoing maturation or transient changes during this age period. Other studies show maturation between the juvenile period and adulthood, but fail to characterize changes in serotonergic function in between these ages. Immaturity of serotonergic function during adolescence could contribute to risk taking behavior based on what is known about serotonergic modulation of behavior. The following section discusses serotonergic modulation of behavior, with a focus on behavior relevant to adolescent risk taking.
1.2.3 Modulation of Behavior
From the standpoint of adolescent risk taking behavior, perhaps the most interesting function of serotonin is the regulation of motivated behavior. The serotonergic system falls into the hypoactive avoidant system of Ernst’s triadic model of adolescent neurobiology, and it has been proposed to modulate behavioral inhibition and/or processing of aversive stimuli (reviewed in Deakin, 1991; Ernst et al., 2006;
Soubrie, 1986). Recent work with serotonin depletion in humans suggests that serotonin mediates both functions, such that serotonin mediates behavioral inhibition specifically
44
under the possibility of aversive outcomes (Crockett et al., 2009). This function of serotonin is thought to work in opposition to the dopaminergic system, which mediates approach to reward and behavioral activation (reviewed in Boureau and Dayan, 2011;
Cools et al., 2011). Developmentally lower serotonergic function during adolescence has been proposed to contribute to risk taking behavior and experimentation with drugs, especially in the context of a hyperactive adolescent dopaminergic system (reviewed in
Chambers et al., 2003; Crews et al., 2007; Ernst et al., 2006). Deficits in central serotonergic function are associated with aggression, impulsivity, risk taking, and suicide, which seems consistent with top causes of adolescent injury and death such as auto accidents, drug abuse, homicide, suicide, and unsafe sexual behavior (Caspi et al.,
2003; Eaton et al., 2012; Goodwin and Post, 1983; Higley and Linnoila, 1997; Higley et al.,
1996; Karg et al., 2011; Lucki, 1998; Mann, 2003; Mehlman et al., 1994; Petersen et al.,
2012; Virkkunen et al., 1995). The following section reviews serotonergic modulation of impulsivity, anxiety-like behavior, aggression, and drug reward/self-administration.
Serotonin modulates these diverse behaviors with similar directionality. Based on current thought on serotonergic modulation of behavior, these behavioral effects of serotonin may reflect its global role in mediating behavioral inhibition and processing of aversive stimuli.
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1.2.3.1 Impulsivity
In keeping with its role in promoting behavioral inhibition, serotonergic signaling functions to reduce impulsive behavior. In observational studies, low central serotonergic function is associated with impulsive behavior in humans and non-human primates (Higley and Linnoila, 1997; Virkkunen et al., 1995). Depletion of central serotonin either by lesion of serotonergic axons or inhibition of synthesis increases impulsivity on tasks assessing behavioral inhibition (Harrison et al., 1997, 1999;
Walderhaug et al., 2002). Serotonin depletion only seems to cause disinhibition in tasks in which failure to inhibit responding is met with punishment, as behavioral inhibition tasks with no punishment component do not respond to serotonin depletion (Clark et al., 2005; Crockett et al., 2009; Eagle et al., 2009). Serotonin depletion has also been found to increase impulsivity in delay discounting tasks, though not all studies have confirmed this effect (Bizot et al., 1999; Mobini et al., 2000; Winstanley et al., 2004; Wogar et al., 1993). Recent electrophysiological studies of the DRN may support a role for serotonin in delay discounting. Putative serotonergic neurons in the DRN encode reward size, and may be critical in waiting for reward receipt (Bromberg-Martin et al.,
2010; Miyazaki et al., 2011; Nakamura et al., 2008; Ranade and Mainen, 2009).
Studies of the effects of enhancing serotonin signaling support results from experiments with serotonin depletion. Genetic and pharmacologic manipulations that increase extracellular serotonin reduce impulsivity (Bizot et al., 1999; Homberg et al.,
46
2007). Studies with agonists and antagonists for serotonin receptors have primarily focused on the 5-HT1A, 5-HT2A, and 5-HT2C receptors and reveal complex subtype and brain-region specific regulation of impulsivity. Systemic treatment with low doses of the 5-HT1A agonist 8-OH DPAT increase impulsivity in a behavioral inhibition task (Carli and Samanin, 2000). This effect was likely due to activation of 5-HT1A autoreceptors, as infusion of the 5-HT1A antagonist WAY 100635 into DRN blocked the effects of 8-OH
DPAT (Carli and Samanin, 2000). In agreement with these data, infusion of 8-OH DPAT into the mPFC did not affect impulsivity, but only affected attention (Winstanley et al.,
2003). Pharmacology studies show that the 5-HT2A and 5-HT2C receptors exert opposite influences on impulsive behavior in behavioral inhibition tasks. 5-HT2A signaling increases impulsive behavior and 5-HT2C signaling reduces it (Fletcher et al., 2007;
Koskinen et al., 2000; Passetti et al., 2003; Winstanley et al., 2004). Infusions of 5-HT2A and 5-HT2C antagonists into specific brain regions show that both receptor subtypes modulate impulsivity through signaling in the nucleus accumbens, and 5-HT2A signaling in the cortex also plays a role (Robinson et al., 2008; Winstanley et al., 2003).
1.2.3.2 Anxiety and Anxiety-Like Behavior
Scientists have been investigating the role of serotonin in anxiety for decades using a variety of behavioral approaches. While the literature has been described as contradictory, patterns have emerged that are consistent with the model of serotonergic signaling as mediating behavioral inhibition and aversive processing. Generally
47
speaking, manipulations that acutely increase extracellular serotonin have anxiogenic effects and decreases in extracellular serotonin are anxiolytic (reviewed in Griebel, 1995;
Millan, 2003). The time course of these changes is important, as acute treatment with
SSRIs is often anxiogenic in animal models, while chronic treatment is anxiolytic
(Bodnoff et al., 1989; Burghardt et al., 2004; Griebel et al., 1994; Silva and Brandao, 2000).
This is consistent with the fact that the therapeutic effects of SSRIs for anxiety disorders and depression in humans do not emerge until after several weeks of treatment
(reviewed in Carr and Lucki, 2010; Kent et al., 1998). Another important consideration in serotonergic modulation of anxiety-like behavior is the type of test used to assess behavior. For the purpose of this discussion, tests for anxiety-like behavior will be grouped into three broad categories: tests of punished responding, unconditioned anxiety tests, and conditioned fear.
Some of the earliest studies of the effects of serotonin on anxiety-like behavior measured the effects of serotonin depletion on punished responding. These studies provided some of the initial evidence that serotonin mediates behavioral inhibition
(Soubrie, 1986). Punished responding tasks generate an approach-avoidance conflict by providing access to food or water to a food- or water-deprived animal, then initiating periods in which the animal occasionally receives a weak electric shock when consuming the food or water (reviewed in File et al., 2004). Serotonin depletion and the non-specific serotonin antagonist methysergide increase responding under these
48
conditions, suggesting that serotonin functions to inhibit behavior in response to shock
(Geller and Blum, 1970; Graeff and Schoenfeld, 1970; Robichaud and Sledge, 1969; Tye et al., 1977). Numerous studies show that 5-HT1A agonists increase responding as well, and this effect is believed to be primarily due to stimulation of 5-HT1A autoreceptors and the subsequent reduction in serotonergic neuron firing (reviewed in Millan, 2003).
The behavioral tests classified as unconditioned anxiety tests may be grouped into two sub-categories. Some tests set up an approach-avoidance conflict based on rodents’ drive to explore new areas versus fear or brightly lit, open spaces. These types of test include the open field (OF), elevated plus maze (EPM), elevated zero maze
(EZM), and light/dark test (LD) (reviewed in File et al., 2004). Other tests produce conflict between fear of novel, brightly lit spaces and the drive to approach reinforcers such as palatable food (novelty suppression of feeding or novelty induced hypophagia tests) or interaction with social partners (social interaction test) (Merali et al., 2003; reviewed in File et al., 2004). In all of these tests the level of approach behavior
(exploring aversive area, eating food, interacting with partners) is a key measure of anxiety, and many studies show that serotonin suppresses approach behavior across all of these tests (reviewed in Griebel, 1995). Serotonin depletion increases exploration of aversive areas of the EPM or LD box and prevents suppression of feeding or social interaction by a novel environment (Bechtholt et al., 2007; Briley et al., 1990; File et al.,
1979; Gibson et al., 1994; Koprowska et al., 1999; Kshama et al., 1990). Inhibition of the
49
raphe nuclei by site-specific injection of 5-HT1A agonists also produces anxiolytic effects in these tasks (Cheeta et al., 2000; File and Gonzalez, 1996; File et al., 1996; Graeff et al.,
1996b; Hogg et al., 1994; reviewed in Engin and Treit, 2008). In contrast, serotonin releasing drugs or serotonin uptake inhibitors reduce exploration of aversive areas and enhance the suppression of feeding or social interaction by a novel environment (Bagdy et al., 2001; Bodnoff et al., 1989; Dekeyne et al., 2000; Graeff et al., 1996b; Griebel et al.,
1994; Morley and McGregor, 2000; Pinheiro et al., 2008; Silva and Brandao, 2000).
Studies of the modulation of unconditioned anxiety-like behavior by serotonin receptor subtypes have often produced conflicting results, but several consistent patterns have emerged (Griebel, 1995; Millan, 2003). Numerous studies point to a role for the 5-HT2C receptor in mediating anxiety-like behavior. 5-HT2C, but not 5-HT2A antagonists, block the anxiogenic effects of acute treatment with serotonin reuptake inhibitors and the non-selective 5-HT2 agonist mCPP (Bagdy et al., 2001; Dekeyne et al.,
2000; Gibson et al., 1994). Site specific injection studies show that 5-HT2C receptors in the basolateral amygdala may mediate the anxiogenic effects of mCPP, indirect serotonin agonists, and exposure to stress (Campbell and Merchant, 2003; Christianson et al., 2010;
Vicente and Zangrossi, 2011). Hippocampal 5-HT2C receptors may also be important in mediating anxiety-like behavior (Alves et al., 2004; Whitton and Curzon, 1990). In keeping with a role for 5-HT2C signaling in behavioral inhibition and anxiety-like behavior, 5-HT2C knockout mice display less anxiety-like behavior, while overexpression
50
of forebrain 5-HT2C receptors results in increased anxiety-like behavior (Heisler et al.,
2007; Kimura et al., 2009). Many pharmacologic studies do not show a role for the 5-
HT2A receptor in the anxiogenic effects of acute indirect serotonin agonists, but 5-HT2A knockout mice display an anxiolytic phenotype that can be reversed by expressing 5-
HT2A receptors in the cortex (Weisstaub et al., 2006). While stimulation of 5-HT1A autoreceptors is anxiolytic, site-specific injection studies suggest that post-synaptic 5-
HT1A signaling in the hippocampus, amygdala, and possibly medial prefrontal cortex can produce anxiogenic effects (File et al., 1996; Gonzalez et al., 1996; Overstreet et al.,
2006; Solati et al., 2011). These effects are particularly robust in the social interaction test, but exploration based tests such as the EPM reveal less consistent results (File et al.,
1996; Gonzalez et al., 1996; Solati et al., 2011). Similarly, low doses of the 5-HT1A agonist
8-OH DPAT or partial agonists that preferentially activate autoreceptors are anxiolytic, while higher doses that activate both receptor populations are often anxiogenic
(Blanchard et al., 1992; Critchley and Handley, 1987; Kshama et al., 1990; Millan, 2003;
Soderpalm et al., 1989). 5-HT1A receptor knockout mice display an increase in anxiety- like behavior, but this is due to 5-HT1A effects on development of hippocampal circuits rather than an acute loss of 5-HT1A signaling (Heisler et al., 1998; Parks et al., 1998;
Ramboz et al., 1998; Silveira et al., 2001; Tsetsenis et al., 2007). Numerous studies also show a role for the 5-HT3 receptor in anxiety-like behavior. 5-HT3 antagonists are often anxiolytic, and 5-HT3 antagonists injected into the amygdala consistently produce
51
anxiolytic effects (Menard and Treit, 1999; Rex et al., 1998; reviewed in Engin and Treit,
2008; Millan, 2003). As with the 5-HT2A and 5-HT2C receptors, 5-HT3A subunit knockout mice exhibit less anxiety-like behavior than wildtypes (Kelley et al., 2003). The role of the remaining 5-HT receptor subtypes is less clear, though some studies do show modulation of anxiety by these receptors as well (Millan, 2003). Taken together, these data indicate that the behaviorally inhibiting effects of serotonin in tests for anxiety-like behavior are mediated by the 5-HT1A, 5-HT2C, and 5-HT3 receptors, with some variation between tests as to the receptor subtypes and brain regions most important for behavior.
Across anxiety tests, 5-HT2C signaling in the basolateral amygdala seems to be a key mechanism mediating behavioral inhibition in response to indirect serotonin agonists.
Conditioned fear is another type of anxiety test in which serotonin modulates behavior. These types of tests pair either an auditory cue or a particular area with a footshock, and rodents later exposed to either the auditory or contextual cue exhibit increased freezing behavior (reviewed in LeDoux, 2000). Treatments which increase freezing relative to control are interpreted as anxiogenic, while reductions in freezing are considered anxiolytic. The neural circuits involved in both types of conditioned fear are well characterized. Both auditory and contextual conditioned fear rely on signaling in the amygdala, but auditory conditioned fear also relies on input to the amygdala from the auditory cortex, while contextual paradigms involve signaling in the hippocampus
(reviewed in Gross and Canteras, 2012; LeDoux, 2000). Serotonin appears to
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differentially modulate the two paradigms of conditioned fear. In keeping with their effects in unconditioned anxiety tests, acute treatment with serotonin reuptake inhibitors either increases freezing in auditory conditioned fear paradigms, an effect which is blocked by pretreatment with a 5-HT2C antagonist (Burghardt et al., 2007; Burghardt et al., 2004). Citalopram treatment either before conditioning to footshock or before testing for conditioned freezing increases freezing behavior, suggesting that serotonin modulates both formation of the aversive memory and expression of behavior induced by conditioning (Burghardt et al., 2007; Burghardt et al., 2004). Chronic treatment with an SSRI is anxiolytic in this paradigm, mimicking the response pattern seen in humans and other animal models (Burghardt et al., 2004). Acute treatment with SSRIs has the opposite effect in contextual conditioned fear paradigms. Acute treatment with SSRIs either before conditioning or before testing reduces freezing in contextual fear paradigms (Hashimoto et al., 1996; Inoue et al., 1996; Inoue et al., 2011; Muraki et al.,
2008). This effect may be due to postsynaptic 5-HT1A signaling in the hippocampus
(reviewed in Inoue et al., 2011). The discrepancy between the two types of conditioned fear paradigms and unconditioned anxiety tests may be partially due to the different nature of the behavior in conditioned versus unconditioned anxiety tests. Tests of punished responding and unconditioned anxiety tests are designed around approach- avoidance conflicts, while conditioned fear entails behavioral inhibition in response to an aversive memory. Conditioned fear testing may therefore be more relevant to
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affective disorders and the response to stress, while unconditioned tests may involve risk taking and impulsive behavior.
1.2.3.3 Aggression
Central serotonergic signaling acts to inhibit aggression. Observational studies of humans and non-human primates consistently show an association between low 5-
HIAA levels in CSF and increased aggression (Brown et al., 1979; Higley and Linnoila,
1997; Higley et al., 1996; Linnoila et al., 1983; Mehlman et al., 1994; Virkkunen et al.,
1995). A variety of serotonin depletion paradigms increase aggressive behavior in humans and animals (Marsh et al., 2002; Miczek et al., 1975; Vergnes et al., 1986; Young and Leyton, 2002). Mouse models of serotonin deficiency such as Tph2 and Pet1 knockout mice also show increased aggression (Angoa-Perez et al., 2012; Hendricks et al., 2003). More recent studies reveal complex region-specific effects of serotonin, such as increases in medial prefrontal cortical serotonin associated with increased aggression
(Takahashi et al., 2011; Takahashi et al., 2010). Aggression is modulated by signaling through 5-HT1 and 5-HT2 receptors (Takahashi et al., 2011). 5-HT1B receptor knockout mice display increased aggressive behavior, and infusion of 5-HT1A agonists into the raphe nuclei to activate autoreceptors reduces aggression (Saudou et al., 1994; Takahashi et al., 2011). Acute treatment with 5-HT2 receptor agonists suppresses aggression, similar to the effects of suppression of impulsivity and behavioral inhibition in anxiety
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tests mediated by 5-HT2 receptors (Takahashi et al., 2011). However, it is unclear whether these effects are mediated by 5-HT2A or 5-HT2C receptors.
1.2.3.4 Drug Reward and Self-Administration
All drugs of abuse increase extracellular dopamine, which is critical for their reinforcing effects (Chen et al., 2006; Di Chiara and Imperato, 1988; Pierce and
Kumaresan, 2006; Thomsen et al., 2009a; Thomsen et al., 2009b). However, many drugs of abuse also increase extracellular serotonin levels in the brain (Bradberry et al., 1993;
Hernandez et al., 1987; Portas et al., 1994; Ribeiro et al., 1993; Tao and Auerbach, 1994;
Yoshimoto et al., 1992; Yoshimoto et al., 2000). Psychostimulants such as amphetamine, methamphetamine, MDMA, and cocaine increase extracellular serotonin by direct actions at the serotonin transporter, but ethanol, morphine, and nicotine increase extracellular serotonin by indirect methods such as disinhibition of serotonergic neuron firing (Pierce and Kumaresan, 2006; Tao and Auerbach, 2002; reviewed in Sulzer et al.,
2005). There is little evidence that serotonin mediates rewarding effects of drugs of abuse, but serotonin appears to limit intake of some drugs and may contribute to the aversive effects of psychostimulants. Acute treatment with SSRIs or increases in dietary tryptophan reduces self-administration of psychostimulants and ethanol (Carroll et al.,
1990a, b; Porrino et al., 1989; Vengeliene et al., 2008). Conversely, depletion of serotonin or administration of serotonin antagonists increases self-administration of psychostimulants (Leccese and Lyness, 1984; Lyness et al., 1980). The 5-HT2C receptor
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may mediate the intake-limiting effects of serotonin on psychostimulant self- administration, as 5-HT2C knockout mice self-administer more cocaine than wild-types
(Rocha et al., 2002). Infusion of a 5-HT2C agonist into the medial prefrontal cortex also reduces reinstatement of cocaine self-administration in a cocaine-induced reinstatement paradigm (Pentkowski et al., 2010). Serotonin depletion or administration of buspirone reduces the anxiogenic and aversive effects of cocaine in the runway model of self- administration and conditioned place aversion paradigms in rodents (Ettenberg and
Bernardi, 2006, 2007; Ettenberg et al., 2011). The actions of buspirone in these studies were attributed to activation of 5-HT1A autoreceptors, which would suppress serotonergic neuron activity (Ettenberg and Bernardi, 2006, 2007). In the conditioned taste aversion (CTA) model of drug aversion, SERT knockout mice are less sensitive to cocaine-induced CTA than wild types (Jones et al., 2010). Drug pairing studies with this model show that fluoxetine pretreatment can partially attenuate cocaine CTA, and vice versa, indicating that the two drugs share some aversive mechanisms, presumably increases in extracellular serotonin (Jones et al., 2009; Serafine and Riley, 2010).
1.2.3.5 Summary
This review of serotonergic modulation of behavior reveals similarities in the effects of serotonin on a variety of behaviors that is consistent with the hypothesis that serotonin mediates processing of aversive stimuli and behavioral inhibition (Crockett et al., 2009). Acute increases in extracellular serotonin reduce impulsivity, increase
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anxiety-like behavior, and reduce aggression. Depletion of serotonin has the opposite effect and may reduce the aversive effects of drugs of abuse and increase psychostimulant self-administration. Of the many serotonin receptor subtypes, the 5-
HT2C and postsynaptic 5-HT1A receptors are repeatedly implicated in mediating these effects of serotonin. Given the impact of risk taking behavior on adolescent health and the overlap between behaviors associated with reduced central serotonergic function and adolescent risk taking behavior, we propose that central serotonergic function and serotonergic modulation of behavior in adolescents is an important and understudied topic.
1.3 Specific Aims
This review of the literature shows that adolescence is a developmental period in which a variety of behavioral changes serve to make individuals prone to pursuing rewarding stimuli with little regard for negative consequences, especially in emotionally salient situations. While this is evolutionarily advantageous and a part of normal development, it can also lead to problem behaviors that are chief causes of adolescent injury and death such as reckless driving, drug abuse, and suicide. This study was designed to test the hypothesis that immature serotonergic function in adolescence contributes to the disinhibited, risk taking behavior observed during this age period, and can alter responses to drugs targeting the serotonergic system. This could contribute to the reduced aversive effects of drugs of abuse during adolescence, as well
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as increased suicidality during the early phases of antidepressant therapy. Immature serotonergic function in adolescents could entail lower presynaptic serotonin function, lower postsynaptic receptor function, or immaturity of the circuits modulated by serotonin. This study was designed to test all three possibilities with the following specific aims.
Aim 1 – Compare the behavioral effects of pharmacologic manipulation of serotonin function in adult and adolescent rats. We assessed the behavioral effects of treatments to increase or decrease serotonin function in adult and adolescent male rats in tests for anxiety-like behavior. We used the novelty-induced hypophagia test (NIH), the light/dark test (LD), and the elevated plus maze (EPM), as they are unconditioned tests built around an approach avoidance conflict (reviewed in File et al., 2004). This approach avoidance conflict has been proposed to model risk taking behavior or impulsivity, and provides a method to screen animals during the short adolescent period (Harro, 2002; Macri, 2002; Olausson et al., 1999). We assessed the behavioral effects of serotonin depletion with the serotonin synthesis inhibitor p- chlorophenylalanine (PCPA) in all three tests. In order to tests the effects of acute increases in extracellular serotonin, we treated animals with vehicle or indirect serotonin agonists and assessed behavior in the LD test. The serotonin releasing drugs fenfluramine or MDMA, and the serotonin uptake inhibitor fluoxetine were used as
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representative indirect agonists. The effects of fenfluramine were further tested in the
EPM.
Aim 2 – Compare presynaptic serotonin function in adult and adolescent rats.
We assessed the density of serotonergic innervation to the prefrontal cortex, amygdala, and hippocampus using immunostaining for the serotonin transporter (SERT). Tissue levels of SERT were measured by radioligand binding with 3H-paroxetine. Tissue serotonin and 5-HIAA content were assessed by HPLC, and serotonin synthesis was investigated by measuring accumulation of 5-hydroxytryptophan after treatment with the l-AADC inhibitor NSD-1015. Finally, the increase in extracellular serotonin following systemic treatment with fenfluramine or fluoxetine was assessed by microdialysis. The effects of local infusion of potassium chloride or fluoxetine were measured to confirm that age differences in drug metabolism did not influence the effects of systemic fenfluramine and fluoxetine. In vivo probe recovery in each age group was determined using the zero net flux method of quantitative microdialysis.
Aim 3 – Compare age differences in postsynaptic serotonin responses. The behavioral effects of activation of specific serotonin receptor subtypes were assessed in the LD test following treatment with the 5-HT2 agonist meta-chlorophenyl piperazine
(mCPP) and the 5-HT1A agonist 8-hydroxy-2-(dipropylamino)tetralin (8-OH DPAT). We followed systemic 8-OH DPAT LD testing with site specific injection of 8-OH DPAT into the medial prefrontal cortex and basolateral amygdala. Expression of 5-HT1A receptors
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were further investigated by 3H-8-OH DPAT radioligand binding. The effects of fluoxetine, 8-OH DPAT, and mCPP on activation of neural circuits were assessed by immunostaining for the immediate early gene c-Fos.
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2. Methods
2.1 General Methods
2.1.1 Animals
Young adult (PN60-63) and juvenile (PN21) male Sprague-Dawley (Hagan et al.) rats were purchased from Charles River Laboratories (Raleigh, NC). The rats were housed in ventilated plastic cages (Techniplast USA, Exton, PA) or standard rat cages
(Allentown Caging, Allentown, NJ) with corn cob bedding on a 12:12 hour light/dark cycle with lights on at 06:00 and lights off at 18:00. All rats were allowed to acclimate to our AALAC accredited facility for at least 7 days before using for experiments.
Experiments were carried out when adult rats were aged PN67-74 and adolescent rats were aged PN28-32. All experiments were approved by the Duke University
Institutional Animal Care and Use Committee (IACUC), and were described on existing
IACUC protocols.
The ages used for adult and adolescent rats were chosen to provide a comparison of early adolescents with young adults. The age range of PN28-32 used for adolescent rats is during the early stages of adolescence (Spear, 2000). Male rats at PN67-74 have recently attained mature levels of testosterone and completed development into adulthood, which is considered to begin around PN63 (Lee et al., 1975; McCutcheon and
Marinelli, 2009). Early adolescent humans and animals can be quite different from late adolescents, who often behave more like adults (Casey et al., 2008; Spear, 2000; Steinberg
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et al., 2008; Steinberg et al., 2009). Steinberg et al have shown in humans that early adolescents (aged 10-15) are significantly different from late adolescents and adults in several laboratory measures of impulsivity (Steinberg et al., 2008; Steinberg et al., 2009).
In our own laboratory, early adolescent rats (PN28) exhibit greater cocaine-stimulated locomotion than late adolescent (PN42) and adult (PN65) rats (Caster et al., 2005, 2007;
Parylak et al., 2008).
Only male rats were used in this study to allow for a tighter focus on the role of serotonin in adolescent risk taking. Males engage in more risk taking than females during adolescence (Byrnes et al., 1999; Gardner and Steinberg, 2005; Harris, 2006).
There are sex differences in both the serotonergic system and behavior in rodent models of anxiety-like behavior that would require the addition of female adult and adolescent rats and complicate experimental design (Bebbington et al., 2003; Bethea et al., 2009;
Blanchard et al., 1991; Hayward and Sanborn, 2002; Johnston and File, 1991; Palanza,
2001). Sex differences in development of the serotonergic system and anxiety-like behavior were beyond the scope of this project.
2.1.2 Drugs and Injections
Fenfluramine hydrochloride, 3-hydroxybenzylhydrazine dihydrochloride (NSD-
1015), 8-hydroxy-2-(dipropylamino)tetralin (8-OH DPAT), and potassium chloride were purchased from Sigma-Aldrich (St. Louis, MO). 3,4-methylenedioxymethamphetamine
(MDMA) was obtained from the National Institute on Drug Abuse. Fluoxetine
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hydrochloride was purchased from Spectrum Chemicals (New Brunswick, NJ). Meta- chlorophenylpiperazine (mCPP) was purchased from Tocris Bioscience (Bristol, UK).
Fenfluramine, MDMA, 8-OH DPAT, NSD-1015, and mCPP were dissolved in 0.9% saline, and fluoxetine was dissolved in distilled water. NSD-1015 was injected i.p. in a volume of 2 mL/kg and all other drugs were injected i.p. in a volume of 1 mL/kg.
Ketamine (Ketaset) was purchased from Fort Dodge Animal Health (Fort Dodge, IA) and xylazine (Anased) was purchased from Lloyd Inc. (Shenandoah, IA). Ketamine and xylazine were administered i.m. at a volume of 1 mL/kg.
2.2 Behavior Testing
For all behavior tests, drug effects were determined by comparing drug treated adult and adolescent rats to age matched vehicle treated controls. Most experiments had a 2 x 2 design with adult and adolescent rats treated with drug or vehicle. The only exceptions to this design were when multiple drug doses were used. Each experiment involved two or more cohorts of animals run on different days. Each cohort included adult and adolescent rats from each treatment group that arrived in our animal facilities on the same day and had the same acclimation period prior to testing. This was done to minimize any confounding effects of shipping stress or other environmental variables that could affect anxiety-like behavior.
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2.2.1 Light/Dark Test
Rats were tested in Kinder locomotor boxes (Kinder Scientific, Inc. Poway, CA)
(40 cm x 40 cm x 40 cm) with black plastic inserts (20 cm x 40 cm x 40 cm) that occupied half of the locomotor box. Each insert had a sliding door that restricted access to one part of the box. The room was lit by two incandescent lamps so that the lighting in each box was 65 lux on average. Rats were placed in the dark half of the box and testing began as the door to the light side of the box was raised. Time and distance traveled in each compartment were measured for 15 minutes with infrared photobeams and software from the manufacturer. The latency to emerge into the light compartment was determined by dividing the session into 5 second bins and determining the bin of first light entry. The time spent in the light compartment and the latency to emerge into the light were used as measures of anxiety-like behavior, and the total distance traveled was used to assess locomotion (Morley et al., 2005; Schramm-Sapyta et al., 2007). PCPA or saline was given in two 150 mg/kg (i.p.) doses the two days prior to testing.
Fenfluramine (2 mg/kg i.p.), MDMA (5 mg/kg i.p.), and fluoxetine (10 mg/kg i.p.) were administered 30 minutes prior to testing. 8-OH DPAT (0.25 and 0.5 mg/kg i.p.) and mCPP (0.5 and 1 mg/kg i.p.) were administered 10 and 20 minutes before testing, respectively. Each of these experiments included vehicle treated groups for each age with the same delay between injection and testing. The number of rats used for each experiment is as follows: PCPA 44 rats (11 per treatment group), fenfluramine 48 rats (12
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per treatment group), MDMA 48 rats (12 per treatment group), fluoxetine 72 rats (18 per treatment group), 8-OH DPAT 32 rats (each rat was tested twice, once with vehicle and once with a dose of 8-OH DPAT resulting in 16 vehicle per age, 8 0.25 mg/kg per age, and 8 0.5 mg/kg per age), mCPP 72 rats (18 vehicle per age, 8 0.5 mg/kg per age, 10 1 mg/kg per age).
2.2.2 Elevated Plus Maze
The elevated plus maze was made of black painted, sealed wood and consisted of two open arms and two closed arms arranged in a “plus” shape elevated 60 cm from the floor. The arms were 60 cm x 9 cm. The closed arms were enclosed by a 50 cm wall and the open arms had a 1 cm ledge. Rats were placed in an open field for 5 minutes immediately prior to testing to enhance the ability to measure anxiogenic drug effects
(Pellow and File, 1986). Rats were placed in the center square (9 x 9 cm) facing an open arm and allowed to explore the maze for 5 minutes. White sheets were hung around the maze to create a neutral visual field. Average lighting was 8 lux for open arms and 2 lux for closed arms. All sessions were recorded with a video camera and scored for time in each area of the maze, entries into arms, and the latency to first open arm entry. The percent time spent in the open and closed arms of the maze, the number of entries into the open arms, and the latency to emerge into an open arm were used as measures of anxiety-like behavior, while the number of entries into closed arms was used as an index of locomotion (Cruz et al., 1994; File et al., 2004; File et al., 1993; Rogerio and Takahashi,
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1992). PCPA (150 mg/kg i.p.) or saline was given once daily on the two days prior to testing. Fenfluramine (2 mg/kg i.p.) or saline was administered 30 minutes prior to the pre-EPM open field test. The number of animals used for each experiment was as follows: PCPA 32 rats (8 per treatment group), fenfluramine 60 rats (15 each treatment group).
2.2.3 Novelty Induced Hypophagia
We conducted the NIH test using the methods established by Merali et al and modified by Bechtholt et al (Bechtholt et al., 2007; Merali et al., 2003). Rats were housed two per cage and began training two days after arriving. Training consisted of 15 minute sessions in the home cage in which the rats were separated by a plexiglass divider and a bowl of cereal (Kellogg’s Froot Loops) was placed on each side. Dividers were inserted into the cages 90 minutes prior to the training session. Training sessions were videotaped and the amount of cereal eaten and the latency to begin eating were monitored. All rats went through five days of training with one session per day. Rats that were still not eating after the third training day had a few pieces of cereal placed in their cage following the session. One adult rat did not eat by the end of training and was excluded from the study. On the day following training, rats were injected with 150 mg/kg PCPA once per day for two days, with the last injection given 24 hours before the home test session. The home test day was identical to the training sessions and was used to assess the effects of PCPA on baseline food consumption. The following day,
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the rats were placed one per cage in a novel cage of the same dimensions as the home cage. The cages were in a different room and had laboratory bench paper instead of corn cob bedding. The paper was changed between animals. The rats were left in the cage for 15 minutes, and eating and latency to eat were recorded. A total of 48 rats were used for this experiment (12 per treatment group).
2.3 Confirmation of Serotonin Depletion with PCPA
Serotonin depletion by PCPA was confirmed by performing HPLC with electrochemical detection (HPLC-EC) on homogenates of frontal cortex, amygdala, and hippocampus. Frontal cortex, amygdala, and hippocampus were dissected using a brain block (Heffner et al., 1980). Frontal cortex was defined as cortex overlying the dorsal striatum and nucleus accumbens. This includes regions of frontal, cingulate, motor, and parietal cortex. The samples were weighed, frozen on dry ice, and stored at -80ºC until
HPLC analysis. Tissue samples were homogenized by sonication in mobile phase, filtered through a 0.45 µm centrifugal filter, and injected onto a 4.6 x 100 mm reversed phase C18 column (Phenomenex, Torrance, CA). Serotonin, 5-HIAA, dopamine,
DOPAC, and HVA were measured using electrochemical detection at 0.75V (BAS, West
Lafayette, IN) at a flow rate of 1 mL/min. The mobile phase consisted of 0.05 M sodium phosphate, 0.05 M citric acid, 0.22 mM sodium octyl sulfate , 0.1 mM EDTA, and 15% methanol adjusted to pH 4.50 (Kilts et al., 1981). Samples were quantitated relative to an
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external standard curve run each day and data were corrected for tissue weight collected for each sample.
2.4 Tissue Serotonin Content and Synthesis
Adult and adolescent rats were injected with saline or 100 mg/kg NSD-1015 to inhibit L-amino acid decarboxylase and decapitated 30 minutes later. Levels of 5- hydroxytryptophan (5-HTP) after treatment with NSD-1015 were used to determine the rate of serotonin synthesis (Carlsson et al., 1972). Serotonin and 5-HIAA were also compared in saline treated adults and adolescents. Prefrontal cortex, amygdala, and hippocampus were dissected using a brain block (Heffner et al., 1980). Prefrontal cortex was defined as cortex from sections anterior of the dorsal striatum and nucleus accumbens, and includes regions of cingulate, infralimbic, prelimbic, motor, insular and orbital cortex. The samples were weighed, frozen on dry ice, and stored at -80ºC until
HPLC analysis. Tissue samples were homogenized by sonication in 0.2 N perchloric acid and injected onto a 4.6 x 100 mm reversed phase C18 column (Phenomenex,
Torrance, CA). Serotonin, 5-HIAA, dopamine, DOPAC, HVA, and 5-HTP were measured using electrochemical detection at 0.70V (BAS, West Lafayette, IN) at a flow rate of 0.7 mL/min. The mobile phase consisted of 0.1 M sodium phosphate, 0.8 mM octanesulfonic acid , 0.1 mM EDTA, and 18% methanol adjusted to pH 3.10 (Miguez et al., 1995). Samples were quantitated relative to an external standard curve run each day
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and data were corrected for tissue weight collected for each sample. A total of 32 rats were used for this experiment (8 per treatment group).
2.5 Serotonin Transporter Immunostaining
Adult and adolescent rats were anesthetized with 250 mg/kg pentobarbital and transcardially perfused with PBS followed by 10% formalin. Brains were postfixed in
10% formalin overnight at 4ºC, then cryoprotected in 30% sucrose until sectioning. The brains were cut into 30 µm sections and mounted onto slides prior to immunostaining.
After heat mediated antigen retrieval in citric acid buffer (10 mM citrate, pH 6.0), the sections were stained with an anti-SERT primary antibody (Immunostar, Hudson, WI) followed by an anti-rabbit secondary antibody conjugated to AlexFluor 594 (Invitrogen,
Carlsbad, CA) and counterstained with DAPI (Invitrogen). The sections were imaged on a widefield fluorescent microscope with a motorized stage (DeltaVision Elite, Applied
Precision, Issaquah, WA). Panels of images were taken of the prefrontal cortex, amygdala, and dorsal hippocampus using a 20X objective, with 7 z-stacks per panel.
The images were deconvoluted, projections were made of the z-stacks, and the panels were stitched together to create a single high-resolution image. For analysis, the amygdala was subdivided into central and basolateral amygdala, and the hippocampus was subdivided into CA1, CA3, and dentate gyrus. ImageJ software was used for analysis. The images were thresholded to exclude background, and the percent of the total image area occupied by thresholded structures was used to quantitate the density
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of SERT-immunoreactive innervation. A total of 24 rats were used for this experiment
(12 per age group).
2.6 3H-Paroxetine Binding
Samples of prefrontal cortex, amygdala, and hippocampus were collected from adult and adolescent rats using the same procedure as for HPLC analysis. The samples were immediately frozen on dry ice and stored at -80ºC until analysis. Samples were thawed and homogenized by sonication in 20 volumes of phosphate buffer (8 mM sodium phosphate dibasic, 2 mM sodium phosphate monobasic, 118 mM NaCl, 5 mM
KCl, pH 7.4). The samples (10 µg of protein per tube) were incubated with 3H- paroxetine (Perkin Elmer, Waltham, MA) for 90 minutes at room temperature.
Fluoxetine (10 µM) was used for determination of nonspecific binding. The reactions were terminated by the addition of 3 mL of ice cold buffer, and then filtered onto glass fiber filters (Cambridge Technology, Watertown, MA) presoaked in 0.05% polyethylenimine to reduce nonspecific binding.
A single point binding analysis was performed for each sample and saturation binding analysis was run on pooled adult and adolescent samples from each brain region. For single point analysis, samples were incubated with 50 pM 3H-paroxetine so that age differences in either the affinity or total number of binding sites could be detected. The samples were then pooled for saturation analysis, with one pool per age group for each region. Pooled samples were run with a range of 3H-paroxetine
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concentrations from 10 pM to 2000 pM. Nonlinear fits of saturation binding curves were performed with GraphPad Prism 5.0 (Graphpad, La Jolla, CA). Sixteen rats were used for this experiment (8 per age group).
2.7 3H-8-OH DPAT Binding
Samples of prefrontal cortex, amygdala, and hippocampus were collected from adult and adolescent rats using the same procedure as for HPLC analysis. The samples were immediately frozen on dry ice and stored at -80ºC until analysis. Samples were thawed and homogenized by sonication in 20 volumes of Tris buffer (50 mM Tris, 2 mM
MgCl2, 2 mM Sodium Ascorbate, pH 8.0). The samples (25 µg of protein per tube) were incubated with 3H-8-OH DPAT (Perkin Elmer, Waltham, MA) for 1 hour at room temperature. Serotonin (400 µM) was used for determination of nonspecific binding.
The reactions were terminated by the addition of 3 mL of ice cold buffer, and then filtered onto glass fiber filters (Cambridge Technology, Watertown, MA) presoaked in
0.05% polyethylenimine to reduce nonspecific binding.
A single point binding analysis was performed for each sample. Samples were incubated with 1 nM 3H-8-OH DPAT so that age differences in either the affinity or total number of binding sites could be detected. No age differences were detected in single point binding, so these experiments were not followed by saturation binding. Sixteen rats were used for this experiment (8 per age group).
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2.8 Microdialysis
Adult and adolescent rats underwent surgery to implant a guide cannula for microdialysis typically within four to five days of arrival in our animal facility. Animals were allowed to recover from the surgery for two to four days before implantation of the microdialysis probe and collection of samples the following day. The following figure depicts the timeline of experiments.
Figure 3: Timeline for Microdialysis Experiments
2.8.1 Guide Cannula Implantation
Animals were anesthetized with ketamine (100 mg/kg i.m.) and xylazine (20 mg/kg i.m.) and placed in a stereotaxic frame (Kopf Instruments, Tujunga, CA). Body temperature was maintained with a Deltaphase isothermal heating pad (Braintree
Scientific, Braintree, MA). Guide cannulae (BAS, inc. West Lafayette, IN) were implanted 2 mm over the medial prefrontal cortex, and placed at +3.2 mm anterior and
+0.8 mm lateral from bregma and -3.0 mm from the surface of the brain based on a rat brain atlas (Paxinos and Watson, 1986). Coordinates for adolescent rats were adjusted to 72
+2.8 mm anterior and +0.8 mm lateral from bregma and -2.5 mm from the surface of the brain. The cannula was secured to the skull using three anchor screws and dental cement. Animals were allowed to recover for a minimum of 48 hours before insertion of the microdialysis probe. Ibuprofen (20 mg/kg/day) was administered through the drinking water from three days prior to surgery until the night before microdialysis experiments in accordance with Duke University IACUC standards.
2.8.2 Set up and Collection of Baseline Samples
The evening prior to all experiments, animals were briefly anesthetized with isoflurane and a 2 mm microdialysis probe (BAS, Inc. West Lafayette, IN) was inserted into the cannula. Animals were placed in a clear plastic microdialysis chamber (BAS,
Inc. West Lafayette, IN) and the probe was perfused overnight with artificial cerebrospinal fluid (aCSF, 147 mM NaCl, 2.7 mM KCl, 1.2 mM CaCl2, 0.85 mM MgCl2,
CMA Microdialysis, Solna, Sweden) at 0.5 µL/min using a syringe pump (Harvard
Apparatus, Holliston, MA). The microdialysis cages were bowl-shaped and had a diameter of approximately 36 cm at the bottom of the cage, and a depth of approximately 30 cm with bedding. The same size cages were used for each age group.
The inlet and outlet lines for the microdialysis probe were run through a liquid swivel
(BAS, Inc, West Lafayette, IN), and animals were tethered to the swivel by plastic collars.
Food and water were freely available throughout the overnight equilibration and subsequent experiments. The following morning the flow rate was increased to 1
7 3
µL/min for one hour before collection of baseline samples. Baseline samples were then collected for 2 hours prior to experimental manipulations. Samples were collected on ice, then immediately frozen on dry ice for later analysis by HPLC with electrochemical detection. One adult and one adolescent rat were run simultaneously each day.
2.8.3 Zero Net Flux
The zero net flux method of microdialysis was used to estimate extracellular serotonin levels and in vivo probe recovery (Lonnroth et al., 1987). After collection of baseline samples, the aCSF in the syringe was switched to aCSF containing 0.5, 1, or 2.5 nM serotonin. The new solution was allowed to equilibrate for 40 minutes and then four
20 minute samples were collected. The aCSF was then switched to another concentration and the process was repeated until all three concentrations had been tested. The order of serotonin concentrations was changed from day to day. To obtain estimates of extracellular serotonin and probe recovery, a plot was generated with the concentration of serotonin perfused into the probe (5-HTin) on the x axis and the difference between 5-HTin and serotonin measured in the dialysate on the y axis (5-HTin -
5-HTout). The slope of this plot provides probe recovery, and the x intercept provides an estimate of extracellular serotonin concentration (Justice, 1993). The following figure
(Fig.4) shows an example experiment. The syringe contents were analyzed each day to obtain the actual “5-HT in” when constructing the zero net flux plot. Collection of
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baseline samples began at 7-8 AM and the experiment concluded from 3-4 PM. A total of 16 animals were used for this experiment (8 adults and 8 adolescents).
Figure 4: Example Zero Net Flux Experiment
2.8.4 Fenfluramine Dose Response
Animals were sequentially injected with 1, 2.5, and 10 mg/kg fenfluramine i.p. with three hours between each dose. Samples were collected at 30 minute intervals.
Collection of baseline samples began at 7 AM and the experiments concluded around 6
PM to ensure that all samples were collected during the light phase. A total of 17 animals were used for this experiment (9 adults and 8 adolescents).
2.8.5 Potassium Infusion
After collection of baseline samples, the aCSF in the syringes was replaced with aCSF containing 100 mM potassium chloride. The high potassium aCSF was perfused for 20 minutes before the syringes were switched back to normal aCSF. Samples were collected for another 4 hours with normal aCSF. All samples were collected in 20 minute
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intervals. A total of 22 animals were used for this experiment (12 adults and 10 adolescents).
2.8.6 Fluoxetine Dose Response
After collection of baseline samples, animals were sequentially injected with 2.5,
5, and 10 mg/kg fluoxetine i.p. with two hours between each dose. Samples were collected at 20 minute intervals. Collection of baseline samples began at 7-8 AM and the experiments concluded around 3-4 PM. A total of 26 animals were used for this experiment (13 per age group).
2.8.7 Fluoxetine Infusion
After collection of baseline samples, the aCSF in the syringe was replaced with aCSF containing 30 µM fluoxetine. This concentration was chosen because it has been shown to be a half-maximal dose for increasing extracellular serotonin in the prefrontal cortex (Hervas and Artigas, 1998). Samples were collected at 20 minute intervals for four hours during fluoxetine infusion. Collection of baseline samples began at 7-8 AM and the experiments concluded from 1-2 PM. A total of 17 animals were used for this experiment (10 adults and 7 adolescents).
2.8.8 Verification of Probe Placement
After conclusion of microdialysis experiments, animals were anesthetized with isoflurane and decapitated. Brains were postfixed in 10% formalin, cut into 30 µm sections, and stained with cresyl violet to confirm probe placement (Supplemental Fig.
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1). Animals with probes placed greater than ± 0.5 mm anterior or posterior from the target region were excluded from further analysis (3 out of 55 total adults and 6 out of 52 total adolescents). These animals are not included in the sample sizes given for each experiment.
2.8.9 HPLC-EC Detection for Microdialysis
Dialysates were directly injected onto a 2.1 x 100 mm reversed phase C18 column
(Phenomenex, Torrance, CA). The mobile phase consisted of 150 mM sodium phosphate,
4.8 mM citric acid, 3 mM sodium dodecyl sulfate, 50 µM EDTA, with 11% methanol and
17% acetonitrile, pH=5.6 and was run at a flow rate of 0.2 mL/min. Serotonin was measured using an electrochemical detector set to 0.55V (BAS, Inc. West Lafayette, IN).
The sensitivity of the assay was 1 fmol of serotonin in a 15 µL injection. Samples were quantitated relative to an external standard curve run each day.
2.9 Site Specific Injections
Site specific injections of 8-OH DPAT were used to investigate the behavioral effects of stimulating 5-HT1A receptors within specific brain regions. We investigated the effects of 8-OH DPAT infusion into the prelimbic region of the medial prefrontal cortex, the ventral hippocampus, and the basolateral and central nuclei of the amygdala.
Behavioral experiments with site specific injection require several steps that must be timed carefully to allow behavioral testing during early adolescence. The timeline for these experiments is shown in the following figure.
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Figure 5: Timeline for Site Specific Injection Experiments
2.9.1 Implantation of Guide Cannulae
Adult and adolescent rats underwent surgery to implant guide cannulae within 3 to 5 days of arriving in our animal facility. Animals were anesthetized with ketamine
(100 mg/kg i.m.) and xylazine (20 mg/kg i.m.) and placed in a stereotaxic frame (Kopf
Instruments, Tujunga, CA). Body temperature was maintained with a Deltaphase isothermal heating pad (Braintree Scientific, Braintree, MA). Guide cannulae were purchased from Plastics One, Inc. (Roanoke, VA). The guide cannulae used for each brain region were as follows: prelimbic cortex bilateral 26 gauge, ventral hippocampus
22 gauge, basolateral and central amygdala 26 gauge. Cannulae were implanted bilaterally at the coordinates listed in the following table. All cannulae were placed 1 mm over the target region, and each was paired with an injection cannula extending 1 mm beyond the tip of the guide. The cannulae were secured using three anchor screws and dental cement. Dummy cannulae that did not extend beyond the guide were inserted after surgery to ensure patency of the guide cannulae. Animals were allowed to 78
recover for a minimum of 7 days before behavior testing. All animals were solo housed following surgery to prevent damage to cannulae. Ibuprofen (20 mg/kg/day) was administered through the drinking water for three days after surgery in accordance with
Duke University IACUC standards.
Table 1: Coordinates for Sterotaxic Implantation of Injection Guide Cannulae
Brain Region Age Group Coordinates from Bregma Anterior(+)/Posterior(-) Medial/Lateral Ventral (from Brain Surface) Prelimbic Adolescents +2.7 ±0.6 -2.6 Cortex Adults +3.0 ±0.7 -3.0 Ventral Adolescents -4.3 ±4.5 -5.4 Hippocampus Adults -4.8 ±5.0 -6.0 Basolateral Adolescents -2.5 ±4.5 -6.6 Amygdala Adults -2.8 ±5.0 -7.3 Central Adolescents -2.1, -2.5, -2.5 ±3.6, ±3.6, ±3.8 -6.3, -6.3, -6.5 Amygdala Adults -2.3, -2.8, -2.8 ±4.0, ±4.0, ±4.0 -7.0, -7.0, -7.3
Coordinates used for implantation of guide cannulae for site specific injections. Coordinates are shown in mm from bregma for anterior/posterior and medial/lateral coordinates. Ventral coordinates were calculated from the surface of the brain. For anterior/posterior coordinates, + = mm anterior to bregma, - = mm posterior to bregma. Three sets of coordinates are listed for the central amygdala because three sets coordinates were used without achieving consistent hits of this brain region.
2.9.2 Habituation to Handling and Infusion
All animals were habituated to handling and infusion on the three days prior to behavior testing. On the first two days animals were gently handled and the dummy cannulae were removed and reinserted into the guides. On the third day animals underwent an infusion of artificial cerebrospinal fluid (aCSF, 147 mM NaCl, 2.7 mM 79
KCl, 1.2 mM CaCl2, 0.85 mM MgCl2, CMA Microdialysis, Solna, Sweden). The procedure for infusion was the same as that performed prior to behavior testing.
Infusion cannulae were inserted into the guides and attached by screwing onto the guide cannula pedestal. For the prelimbic cortex and amygdala nuclei 33 gauge infusion cannulae were used, and 28 gauge cannulae were used for ventral hippocampus.
Animals were placed in a standard size cage with bedding and allowed to move freely during infusion. A volume of 1 µL (cortex and hippocampus) or 0.5 µL (amygdala nuclei) was infused over two minutes using a syringe pump (Harvard Apparatus,
Holliston, MA) and 10 µL syringes (Hamilton, Reno, NV), and infusion cannulae were left in place for one minute following infusion. The infusion cannulae were then removed and animals were returned to the home cage.
2.9.3 Site Specific Injection and Behavior Testing
The day following aCSF infusions, adult and adolescent rats were infused with either aCSF or 8-OH DPAT dissolved in aCSF as described above, and immediately placed in the light/dark box for behavior testing. Doses of 50, 100, and 200 ng of 8-OH
DPAT were infused into prelimbic cortex, and 100 ng of 8-OH DPAT was tested in all other brain regions. Behavior of 8-OH DPAT treated animals was compared to aCSF treated animals to determine drug effects on behavior. The total number of animals used for each experiment is as follows: prelimbic cortex 68 rats (aCSF 14-15 per age, 50 ng 2-3 per age, 100 ng 8-9 per age, 200 ng 8-9 per age), ventral hippocampus 12 rats (3
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per treatment group), basolateral amygdala 21 rats with confirmed placement (6-7 aCSF per age, 3-5 100 ng per age), central amygdala 5 rats with confirmed placement (0-2 aCSF, 1-2 100 ng per age).
2.9.4 Confirmation of Cannula Placement
After conclusion of behavior experiments, animals were anesthetized with 2 g/kg urethane. Cresyl violet dye was infused using the same procedure as with aCSF and 8-
OH DPAT to aid in determination of bilateral cannula placement and diffusion distance through brain tissue. Brains were postfixed in 10% formalin, cut into 30 µm sections, and stained with cresyl violet to confirm cannula placement. Cannula placement was checked for basolateral and central amygdala. Of these animals, 21 out of 31 animals had correct placement for basolateral amygdala and 5 out of 33 had correct placement for central amygdala.
2.10 c-Fos Immunostaining
The immediate early gene c-Fos is expressed when neurons are strongly activated and has become widely used to investigate neural circuits involved in behavior or drug responses (Curran and Morgan, 1995; Farivar et al., 2004; Kovacs,
2008). We used expression of c-Fos to investigate age differences in circuit-level effects of treatment with fluoxetine, 8-OH DPAT, or mCPP.
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2.10.1 Determination of Maximal c-Fos Response
Electrical stimulation of the medial forebrain bundle (MFB) was performed to determine the maximal c-Fos response in each age group. Electrical stimulation of the
MFB should cause release of dopamine, serotonin, and norepinephrine and subsequently activate postsynaptic neurons. Adult and adolescent rats were anesthetized with urethane (2.0 g/kg i.p.) and placed in a stereotaxic apparatus. A bipolar stimulating electrode was placed at 4.6 mm posterior and 1.4 mm lateral relative to bregma. Only one side of the brain was stimulated so that the unstimulated hemisphere could serve as an internal control. The electrode was lowered 7.0 mm from the surface of the brain, and a 300 µA biphasic stimulation was applied, with 2 ms per phase. Each stimulation lasted 10 seconds at a frequency of 60 Hz. Five more identical stimulations were applied at -7.4, -7.7, -8.0, -8.3, and -8.6 mm from the surface of the brain to ensure adequate stimulation of the MFB. The animals were then removed from the stereotaxic frame and perfused two hours later for c-Fos immunostaining. Animals remained under anesthesia during the two hour waiting period. A total of 8 animals were used for this experiment (n=4 per age group).
2.10.3 Response to Fluoxetine, 8-OH DPAT, and mCPP
Adult and adolescent rats were treated with vehicle, 10 mg/kg fluoxetine, 0.5 mg/kg 8-OH DPAT, or 1 mg/kg mCPP (i.p.) and perfused for immunostaining two hours after injection. The two hour delay between injection and perfusion was determined in
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preliminary western blot experiments. The fluoxetine and 8-OH DPAT experiments were run in parallel with animals from both groups run on the same days. The vehicle for fluoxetine was distilled water and the vehicle for 8-OH DPAT was saline. Half of the vehicle group for this experiment received water and half received saline. The mCPP experiment was run on separate days, and the vehicle for this experiment was saline.
2.10.4 Perfusions and Brain Collection
Rats were anesthetized with and transcardially perfused by phosphate buffered saline (PBS) followed by 10% formalin. Brains were postfixed in 10% formalin overnight at 4°C, then cryoprotected in 30% sucrose prior to cutting into 30 µm sections on a cryostat. The sections were stored in PBS at 4°C until staining.
2.10.5 Immunostaining
Three sections per rat from each brain region were stained. The sections were incubated in an anti-c-Fos primary antibody (1:20 000, EMD Millipore, Billerica, MA) in
5% normal goat serum (Invitrogen, Carlsbad, CA) with 0.4% Triton X-100 (Sigma
Aldrich, St. Louis, MO), followed by a biotinylated goat anti-rabbit secondary antibody
(1:250, Vector Laboratories, Burlingame, CA). Immunostaining was visualized using the
ABC-NiDAB method (Vector Laboratories, Burlingame, CA).
2.10.6 Cell Counting
Brain regions chosen for quantitation of c-Fos immunoreactivity were the prefrontal cortex (prelimbic and lateral orbital regions), bed nucleus of the stria
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terminalis (lateral and ventral subdivisions), amygdala (central and medial amygdala nuclei), and the paraventricular nucleus of the hypothalamus. A 20X image was taken of the region of interest from both hemispheres of each section. Images were thresholded, and ImageJ software was used to count c-Fos immunoreactive cells. The values from each hemisphere were added to give a value for each section and the section values were averaged to provide the final count for each rat. All imaging and quantitation was performed by an investigator blinded to the age and treatment of each animal.
2.11 Data Analysis and Statistics
Unless otherwise noted, all statistical tests were carried out using NCSS 2004 software (Number Crunchers Statistical Systems, Kayesville, UT). For all analyses, significant three way interactions in ANOVA were followed by lower order two way
ANOVA, and significant two way interactions were followed by Newman-Keuls post- hoc testing.
2.11.1 Behavior Tests
2.11.1.1 Baseline Behavior
Baseline behavior of each age group in the NIH, LD, and EPM tests was compared by pooling data from all saline-treated animals, including animals from pilot experiments. All animals were in their first trial for each test, and were run under identical conditions across experiments. Baseline behavior in each age group was
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analyzed by two-tailed t-test using Graphpad Prism 5.0, with the exception of latency measures from all three tests (NIH % change in latency to eat, LD latency to emerge into the light compartment, and EPM latency to emerge into an open arm). These measures were analyzed by Mann-Whitney test using Graphpad Prism 5.0 due to non-Gaussian distribution of the data. Eating and latency to eat in home and novel cages during the
NIH test were analyzed by two-way repeated measures ANOVA with age as a between factor and cage (home/novel) as a within factor using NCSS.
2.11.1.2 Baseline Behavior: Systemic vs. Site-Specific Control Animals
Behavior of control animals from systemic and site-specific LD experiments were compared by two way ANOVA with age and experiment as factors. The control animal data from systemic LD experiments was compiled as described above. All aCSF control animals from site specific injection experiments were used regardless of correct probe placement, as the intent of this analysis was to test whether the surgery and handling procedures used for site specific injection affect LD behavior. As with systemic control animals, all site-specific control animals had no prior LD test experience.
2.11.1.3 Drug Effects in Each Age Group
The effects of age and drug treatment in the LD and EPM were analyzed by
ANOVA with age and treatment as factors. The anxiety measures of the EPM test (% time in open arms, open entries, latency to enter an open arm, and % time in closed arms) were analyzed by MANOVA to determine effects of age and drug treatment. The
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number of EPM closed entries was analyzed by ANOVA, as this measure reflects locomotor activity rather than anxiety-like behavior. Eating and latency to eat in the home and novel cages of the NIH test were analyzed by repeated measures ANOVA with age, treatment, and cage as factors. The percent change in these measures between the home and novel cages was analyzed by ANOVA with age and treatment as factors.
2.11.2 Confirmation of Serotonin Depletion, Tissue Serotonin Content, and Synthesis
HPLC data confirming serotonin depletion with PCPA or assessing serotonin synthesis using NSD-1015 were analyzed by similar strategies. The effects of PCPA or
NSD-1015 treatment across age groups in multiple brain regions were analyzed by repeated measures ANOVA with age and treatment as between factors and brain region as a within factor. In the serotonin synthesis experiment, global ANOVA revealed an effect of NSD-1015 treatment on 5-HIAA levels [F(1,28)=38.99, p<0.001] and 5-HIAA/5-
HT levels [F(1,28)=75.87, p<0.001], so only saline-treated animals were used for age comparisons in 5-HT, 5-HIAA, and 5-HIAA/5-HT. The effect of age on these measures across brain regions was analyzed by repeated measures ANOVA with age as a between factor and brain region as a within factor.
2.11.3 Radioligand Binding and Serotonin Transporter Immunostaining
3H-paroxetine and 3H-8-OH DPAT single point binding data and serotonin transporter immunostaining in prefrontal cortex, amygdala, and hippocampus were
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analyzed using the same strategy. The effect of age on these measures across all three brain regions was analyzed by repeated measures ANOVA with age as a between factor and brain region as a within factor.
2.11.4 Microdialysis
Probe recovery and extracellular serotonin concentrations determined by zero net flux were compared between age groups by paired t-test using Graphpad Prism
(Graphpad, La Jolla, CA). Adult and adolescent rats were paired by experimentation day for this analysis. For the fenfluramine and fluoxetine dose response experiments, the effect of drug treatment in each age group was analyzed by three-way repeated measures ANOVA with age as a between factor and time and dose as within factors.
Data for both dose response experiments were log transformed to normalize the wide range of values between doses. A significant age x time x dose interaction was followed by a two way repeated measures ANOVA for each dose with age and time as factors.
Doses with a significant age x time interaction were subjected to Newman-Keuls posthoc testing to determine at which time points adults and adolescents had different extracellular serotonin levels. The potassium and fluoxetine infusion experiments were analyzed by two-way repeated measures ANOVA with age as a between factor and time as a within factor.
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2.11.5 c-Fos Immunostaining
The effects of fluoxetine and 8-OH DPAT on c-Fos expression across brain regions were analyzed by repeated measures ANOVA with age and treatment as between factors and brain region as a within factor. Saline or water-treated rats were combined to form a common control group and all three treatments (vehicle, fluoxetine,
8-OH DPAT) were analyzed by the same global analysis. Adolescent and adult rats often had different levels of c-Fos expression after treatment with vehicle, so the percent increase from vehicle in fluoxetine and 8-OH DPAT treated animals was also analyzed.
Percent increase in c-Fos relative to vehicle was analyzed in fluoxetine and 8-OH DPAT treated animals using three-way repeated measures ANOVA with age, treatment, and brain region as factors. Vehicle treated animals were not included in this ANOVA, as the purpose was to analyze change relative to vehicle. Global ANOVA for cell counts was followed by individual ANOVAs for each brain region with age and treatment as factors. Percent increase values were further analyzed by a repeated measures ANOVA for each drug with age and region as factors. For these analyses, brain regions were grouped into extended amygdala (central and medial amygdala and the lateral and ventral subdivisions of the bed nucleus of the stria terminalis), prefrontal cortex
(prelimbic and lateral orbital cortices) and the hypothalamus (paraventricular nucleus).
The effects of mCPP on c-Fos expression were analyzed using the same strategy, but
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were not included in the same analysis as fluoxetine and 8-OH DPAT because these animals were treated and perfused on different days.
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3. Age Differences in the Behavioral Effects of Pharmacologic Manipulation of Extracellular Serotonin
The goal of this project was to investigate the hypothesis that immature serotonergic function during adolescence contributes to risk taking behavior and alters the behavioral and neurochemical responses to drugs targeting the serotonin system.
We further hypothesized that less behavioral inhibition induced by serotonergic drugs in adolescents could contribute to vulnerabillty to drug abuse and the increased suicidality observed in adolescents during the early phases of SSRI therapy. We began our investigation by testing the behavioral effects of pharmacologic manipulation of extracellular serotonin levels in each age group. We employed two strategies for manipulating extracellular serotonin. We used the serotonin synthesis inhibitor PCPA to deplete extracellular serotonin in each age group, and increased extracellular serotonin with the serotonin releasing drugs fenfluramine and MDMA and the uptake inhibitor fluoxetine. The effects of these drugs relative to vehicle were assessed in adult and adolescent rats in rodent anxiety tests. We used rodent anxiety tests designed around an approach/avoidance conflict with the goal of probing the proposed skewed approach/avoidance drive in adolescence (Ernst and Fudge, 2009; Ernst et al., 2006). The effects of PCPA were assessed in the novelty induced hypophagia (NIH), light/dark
(LD), and elevated plus maze (EPM) tests for anxiety. The indirect serotonin agonists could not be tested in the NIH test due to their anorectic effects, but were tested in LD
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and EPM. We predicted that each of these drugs would have greater behavioral effects in adults than adolescents.
3.1 Baseline Behavior in Anxiety Tests
Baseline behavior for each age group in the NIH, LD, and EPM tests was compared by pooling data from all available saline-treated animals. The two age groups behaved similarly for most measures of anxiety-like behavior, which facilitated comparison of drug effects between age groups. The only measure of anxiety-like behavior that had an age difference at baseline was the latency to emerge into the light compartment in the LD test (Fig.7d). This may reflect age differences in behavioral inhibition.
When eating was corrected for body weight, adolescent rats ate more than adults in the NIH test (Fig.6a) [main effect of age F(1,45)=9.81, p<0.01]. The analysis yielded a main effect of cage (home/novel) [F(1,45)=198.45, p<0.001], showing that the novel environment affected eating in both age groups, but also an age x cage interaction
[F(1,45)=5.30, p<0.05]. Post-hoc testing revealed that adolescents ate more than adults in both cages. The percent change in eating was not different between age groups, suggesting that both age groups exhibited similar suppression of feeding by the novel environment. Analysis of latency to eat produced only a main effect of cage (Fig.6b)
[F(1,44)=138.45, p<0.001], showing that the novel environment slowed the latency to begin eating in both age groups, and that there were no overall age differences in latency
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to eat. There was no age difference in the percent change in eating (Fig. 6c) or latency to eat (Fig. 6d) between cages.
Figure 6: Behavior of Saline Treated Animals in the NIH Test Baseline behavior in NIH test in adult and adolescent rats. A.) Eating corrected for body weight in home and novel cages, B.) Latency to eat in home and novel cages, the percent change from home to novel cage in (C.) eating and (D.) latency to eat. n= 23 adults and 24 adolescents.
Adult and adolescent rats behaved similarly in the LD test with the exception of latency to emerge into the light for the first time (Fig.7b) (p<0.001). The magnitude of the age difference varied across cohorts of animals, but adolescent rats consistently
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emerged more quickly than adults. This was the only measure of anxiety-like behavior that exhibited an age difference in saline-treated animals across all three anxiety tests.
Figure 7: Behavior of Saline Treated Animals in the LD Test Baseline behavior in LD test in adult and adolescent rats. A.) Time spent in the light compartment, B.) latency to eat emerge into the light compartment, C.) the number of entries into the light compartment, (D.) total distance traveled. * = significant age difference (p<0.001). n = 81 adults and 84 adolescents
Adult and adolescent rats also behaved similarly in the EPM. No age difference was observed in any of the measures of anxiety-like behavior. Adolescent rats made more entries into the closed arms of the maze than adults (Fig.8e) (p<0.05), indicating greater locomotor activity in this age group.
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Figure 8: Behavior of Saline Treated Animals in the EPM Baseline behavior in EPM in adult and adolescent rats. A.) the percent of total time spent on the open arms, B.) the number of entries into open arms, C.) latency to emerge into an open arm, (D.) the percent of total time spent on the closed arms, and E.) the number of entries into closed arms * = significant age difference (p<0.05), n = 26 adults and 26 adolescents.
3.2 Reducing Extracellular Serotonin with PCPA
We used the tryptophan hydroxylase inhibitor PCPA to deplete tissue serotonin and reduce extracellular serotonin levels (Koe and Weissman, 1966). The conversion of tryptophan to 5-hydroxytryptophan by tryptophan hydroxylase is the rate limiting step in serotonin synthesis, and inhibition of this enzyme for even a few hours will begin to deplete tissue serotonin (Best et al., 2010; Koe and Weissman, 1966). Large doses of
PCPA administered over two to three days induce dramatic depletion (~90%) of tissue
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serotonin, and produce anxiolytic effects in the NIH, LD, and EPM tests (Bechtholt et al.,
2007; Gibson et al., 1994; Koprowska et al., 1999; Kshama et al., 1990; Treit et al., 1993).
3.2.1 Novelty Induced Hypophagia
Serotonin depletion with PCPA induced anxiolytic effects in adults but not adolescents on both the amount eaten and the latency to eat in the novel cage. Body weight corrected eating in home and novel cages was analyzed by three way repeated measures ANOVA with factors of age, treatment, and cage (home/novel). The analysis yielded a significant age x treatment x cage interaction (Fig.9a) [F(1,40)=8.37, p<0.01], so the effects of PCPA were further examined in each age group by two way repeated measures ANOVA with treatment and cage as factors. Analysis of adult eating produced a significant treatment x cage interaction [F(1,19)=5.83, p<0.05], and post-hoc testing showed that PCPA-treated adults ate significantly more in the novel cage than did saline-treated adults. PCPA did not significantly change home cage eating in adults based on the post-hoc test. In adolescents, this analysis produced a main effect of treatment [F(1,22)=8.96, p<0.01], indicating general PCPA effects on eating across environment. There was also a main effect of cage [F(1,21)=147.15, p<0.001], showing that the novel environment suppressed eating in adolescents regardless of treatment.
There was no treatment x cage interaction in adolescents. A similar strategy was used to analyze latency to eat (Fig. 9b). After global repeated measures ANOVA produced a significant age x treatment x cage interaction [F(1,40)=5.77, p<0.05], each age group was
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split up for individual two way ANOVAs. The ANOVA for adult rats again revealed a treatment x cage interaction [F(1,19) 15.76, p<0.001], and post hoc testing showed that
PCPA-treated adults began to eat more quickly in the novel cage than controls. The adolescent analysis produced a main effect of cage [F(1,21)=81.54, p<0.001], but no effect of treatment or treatment x cage interaction.
As an alternative way of analyzing the data, the percent change in eating and latency to eat between the home and novel cages was calculated for each animal. These data were analyzed by two way ANOVA with age and treatment as factors. Analysis of the percent change in eating revealed an age x treatment interaction (Fig.9c)
[F(1,40)=5.96, p<0.05], showing that PCPA affected the age groups differently. Post-hoc testing showed that PCPA-treated adults had less novelty suppression of eating than both control adults and PCPA-treated adolescents. Analysis of latency to eat also produced an age x treatment interaction (Fig.9d) [F(1,38)=9.33, p<0.01], and post-hoc analysis showed that PCPA treated adults had lower increases in latency than adult controls. These data show that PCPA was anxiolytic in adults, but not adolescents in the
NIH test.
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Figure 9: PCPA Novelty Induced Hypophagia Test The effects of serotonin depletion with PCPA on behavior in the novelty induced hypophagia test. A.) Eating (corrected for body weight) in home and novel cages, B.) Latency to eat in home and novel cages, C.) The percent change in eating between home and novel cages, D.) The percent change in latency to eat between home and novel cages, * = significantly different from age-matched controls (p<0.05), # = significantly different from PCPA-treated adolescents (p<0.05). n=12 per treatment group.
3.2.2 Light/Dark Test
PCPA did not produce significant anxiolytic effects in either age group.
Adolescents emerged into the light more quickly than adults (Fig.10b) [main effect of age F(1,38)=25.33, p<0.001], so it is possible a floor effect prevented the detection of a
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further reduction in latency by PCPA treatment. The number of entries into the light compartment was reduced by PCPA (Fig.10c) [main effect of treatment F(1,40)=5.33, p<0.01]. PCPA did not affect the total distance traveled, although there was a significant main effect of age driven by higher locomotion in adults (Fig.10d) [F(1,40)=4.3, p<0.05].
Figure 10: PCPA Light/Dark Test The effects of serotonin depletion with PCPA on behavior in the light dark test. A.) Time spent in the light compartment. B.) Latency to emerge into the light compartment. C.) Number of entries into the light compartment. D.) Total distance traveled. n = 11 per treatment group.
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3.2.3 Elevated Plus Maze
Treatment with PCPA produced anxiolytic effects in both age groups in the EPM.
MANOVA of the percent time spent in open arms (Fig. 11a) and closed arms (Fig.11d), the number of open entries (Fig.11b), and the latency to enter an open arm (Fig.11c) revealed a main effect of treatment [F(4,23)=3.52, p<0.05], but no effect of age or interaction of age with treatment. There was no significant effect of PCPA on the number of entries into closed arms (Fig.11e), but there was a main effect of age
[F(1,26)=4.69, p<0.05] as adolescents generally made more closed entries than adult rats.
Figure 11: PCPA Elevated Plus Maze The effects of serotonin depletion with PCPA on behavior in the elevated plus maze. A.) The percent of total time spent in the open arms. B.) The number of entries into open arms. C.) Latency to enter an open arm for the first time. D.) The percent of total time spent in closed arms. E.) The number of entries into closed arms. n = 8 per treatment group.
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3.2.4 Confirmation of Serotonin Depletion
Serotonin depletion with PCPA was confirmed by measuring tissue serotonin and 5-HIAA content by HPLC-EC (Table 2). PCPA depleted both tissue serotonin content and 5-HIAA levels similarly in each age group. PCPA treatment dramatically lowered tissue serotonin content in both age groups as shown by a main effect of treatment in global ANOVA [F(1,122)=1754.60, p<0.001]. There were also age and regional differences in serotonin content [main effects of age F(1,122)=35.97, p<0.001 and region F(2,242)=629.64, p<0.001]. The global ANOVA revealed an age x treatment x region interaction [F(2,242)=10.11, p<0.001], so each region was analyzed by two way
ANOVA with age and treatment as factors. Two way analyses yielded age x treatment interactions in the frontal cortex [F(1,122)=22.2, p<0.001], amygdala [F(1,121)=34.87, p<0.001], and hippocampus [F(1,121)=14.86, p<0.001]. Post-hoc testing showed that saline-treated adult rats had higher serotonin content than adolescents in all brain regions, but that there were no age differences between PCPA-treated animals. The significant interaction terms in two- and three way ANOVA were therefore driven by baseline differences in serotonin content, and PCPA reduced serotonin content to similar levels in each age group.
Results from the analysis of tissue 5-HIAA levels were similar to those with serotonin content. PCPA significantly depleted 5-HIAA as shown by a main effect of treatment [F(1,122)=1506.54, p<0.001]. There were regional differences in 5-HIAA levels
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[main effect of region F(2,237)=10.09, p<0.001], but no significant effect of age. Analysis of 5-HIAA levels produced an age x treatment x region interaction [F(2,237)=10.77, p<0.001], so each brain region was further analyzed by two way ANOVA with age and treatment as factors. Two way analysis of each brain region revealed main effects of treatment in frontal cortex [F(1,122)=803.43, p<0.001] and amygdala [F91,113)=1320.85, p<0.001], but no effect of age or age x treatment interaction, indicating similar PCPA effects in each age group. Analysis of 5-HIAA levels in hippocampus revealed an age x treatment interaction [F(1,122)=4.54, p<0.05], but post hoc testing revealed age differences between saline, but not PCPA treated animals.
PCPA also altered serotonin turnover [main effect of treatment F(1,122)=4.36, p<0.05]. There were regional differences in 5-HIAA/5-HT [main effect of region
F(2,236)=119.35, p<0.001] and overall age differences in turnover [main effect of age
F(1,122)=20.46, p<0.001]. There was no significant age x treatment or age x treatment x region interaction for serotonin turnover, indicating no significant differences in PCPA effects in each age group.
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Table 2: PCPA Effects on Tissue Serotonin and 5-HIAA The effects of PCPA upon serotonin, 5-HIAA, and 5-HIAA/5-HT in frontal cortex (FC), amygdala (AMG), and hippocampus (HPC). 5-HT and 5-HIAA are shown as pg/mg tissue. All data are shown as mean SEM. * = significantly different from saline treated adolescents (p<0.05). n = 31 per treatment group.
Analyte Adolescents Adults Saline PCPA % Change Saline PCPA % Change F 5-HT 1016 192 -82% 1568 * 243 -84% C 5-HIAA 1667 322 -81% 1777 272 -85% 5-HIAA/ 1.70.07 2.23.26 +31% 1.20.07 1.5.19 +26% 5-HT A 5-HT 3059 515 -83% 40013 * 484 -88% M 5-HIAA 2438 214 -91% 2528 173 -93% G 5-HIAA/ .81.03 .38.06 -53% .64.02 .33.05 -49% 5-HT H 5-HT 1966 323 -84% 2236 * .022.002 -90% P 5-HIAA 2798 252 -91% 23911 * 152 -94% C 5-HIAA/ 1.46.06 .84.08 -42% 1.08.04 .70.07 -34% 5-HT
3.3 Increasing Extracellular Serotonin with Indirect Agonists
We tested the effects of indirect serotonin agonists upon anxiety-like behavior in adult and adolescent rats. The serotonin-releasing drugs fenfluramine and MDMA, and the serotonin uptake inhibitor fluoxetine were used as representative indirect serotonin agonists. Fenfluramine and MDMA are amphetamine derivatives that enter serotonergic neurons via SERT and release vesicular serotonin that is then reverse transported into the extracellular space by SERT (Sulzer et al., 2005). Fenfluramine was used due to its greater affinity for SERT relative to other monoamine transporters, and
MDMA was used because it is a drug of abuse that potently releases serotonin (Rothman
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et al., 2001). Fluoxetine was used as a representative uptake inhibitor because it is widely used in treated depression and anxiety disorders in children and adolescents
(Kodish et al., 2011; Vasa et al., 2006).
3.3.1 Serotonin Releasing Drugs
3.3.1.1 Fenfluramine Light/Dark Test
Fenfluramine increased anxiety-like behavior in both ages as shown by a reduction in time spent in the light compartment (Fig.12a) [main effect of treatment,
F(1,39)=77.92, p<0.001]. This effect was significantly greater in adult rats, as indicated by a significant age x treatment interaction [F(1,39)=7.75, p<0.01]. Post-hoc testing showed that fenfluramine reduced the time spent in the light compartment more in adults than in adolescents. Fenfluramine produced similar age-dependent anxiogenic effects on latency to emerge (Fig.12b) [age x treatment interaction F(1,40)=5.91, p<0.05]. Post-hoc testing confirmed that fenfluramine increased latency to emerge in adult, but not adolescent, rats relative to controls. Fenfluramine reduced the number of entries into the light compartment (Fig.12c) [main effect of treatment F(1,39)=28.83, p<0.001] and total distance (Fig.12d) [ main effect of treatment F(1,39)=50.30, p<0.001] similarly in both ages.
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Figure 12: Fenfluramine Light/Dark Test The effects of 2 mg/kg fenfluramine on behavior in the light dark test. A.) Time spent in the light compartment. B.) Latency to emerge into the light compartment. C.) Number of entries into the light compartment. D.) Total distance traveled. * = different from age matched saline (p<0.05), # = different from fenfluramine treated adolescents (p<0.05). n=12 per treatment group.
3.3.1.2 Fenfluramine Elevated Plus Maze
Fenfluramine was also more anxiogenic to adult rats than adolescents in the EPM as shown by an age x treatment interaction [F(4,52)=2.62, p<0.05] in MANOVA of the percent time in open (Fig.13a) and closed arms (Fig.13d), the number of open entries
(Fig.13b), and the latency to enter an open arm (Fig.13c). This analysis also revealed a main effect of age [F(4,52)=10.02, p<0.001]. The age x treatment interaction in MANOVA
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was further analyzed by individual ANOVAs for each measure. Fenfluramine produced significantly greater anxiogenic effects in adult rats than adolescents on the percent time spent in the closed arms (Fig.13d) [age x treatment interaction [F(1,55)=4.41, p<0.05], and the latency to enter an open arm (Fig.13c) [age x treatment interaction F(1,55)=4.40, p<0.05]. Post-hoc testing showed that fenfluramine-treated adults spent more time in the closed arms and took longer to enter an open arm than adult controls, while adolescents were unaffected. A main effect of age [F(1,55)=9.89, p<0.001] was found for the number of entries into the open arms (Fig.13b), which was driven by a decrease in open entries in fenfluramine-treated adults. No main effects or interactions were identified by an ANOVA of the percent time spent in the open arms (Fig.13a). There were no significant effects of fenfluramine on the number of closed entries (Fig.13e), but
ANOVA revealed a main effect of age [F(1,55)=18.81, p<0.001].
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Figure 13: Fenfluramine Elevated Plus Maze The effects of 2 mg/kg fenfluramine on behavior in the elevated plus maze. A.) The percent of total time spent in the open arms. B.) The number of entries into open arms. C.) Latency to enter an open arm for the first time. D.) The percent of total time spent in closed arms. E.) The number of entries into closed arms. * = different from age matched saline (p<0.05), # = different from fenfluramine treated adolescents, (p<0.05). n = 15 per treatment group.
3.3.1.3 MDMA Light/Dark Test
MDMA produced anxiogenic effects in each age group, but produced greater anxiogenic effects in adults compared to adolescents. Treatment with MDMA strongly suppressed time spent in the light compartment in both age groups (Fig.14a) [main effect of treatment F(1,44)=49.16, p<0.001]. There was no age difference in MDMA suppression of time in light, perhaps due to a floor effect. MDMA increased the latency to emerge into the light compartment in an age-dependent manner (Fig.14b) [main effect of treatment F(1,44)=18.09, p<0.001, age x treatment interaction F(1,44)=16.73, p<0.001]. 106
Post-hoc testing showed that MDMA increased latency to emerge in adult rats, but not adolescents. The number of entries into the light compartment was similarly reduced by
MDMA in each age group (Fig.14c) [main effect of treatment F(1,44)=26.70, p<0.001].
MDMA also produced age-dependent effects on locomotion (Fig.14d) [age x treatment interaction F(1,44)=5.49, p<0.05], with a trend for increased distance traveled in adolescents and reduced distance in adults.
Figure 14: MDMA Light/Dark Test The effects of 5 mg/kg MDMA on behavior in the light dark test. A.) Time spent in the light compartment. B.) Latency to emerge into the light compartment. * = different from all other groups (p<0.05). C.) Number of entries into the light compartment. D.) Total distance traveled. * = different from age matched saline (p<0.05), # = different from MDMA treated adolescents, (p<0.05). n = 12 per treatment group.
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3.3.2 Serotonin Uptake Inhibitor
3.3.2.1 Fluoxetine Light/Dark Test
Fluoxetine (10 mg/kg i.p.) also produced greater anxiogenic effects in adult rats than in adolescent rats. Adult rats spent less time in the light than adolescent rats
(Fig.15a) [main effect of age F(1,68)=30.03, p<0.001], but there was not a significant age difference in the effects of fluoxetine. As with the serotonin-releasing drugs, the most dramatic age differences were observed with the latency to emerge into the light compartment. Adult rats took longer than adolescents to emerge into the light (Fig.15b)
[main effect of age F(1,68)=27.74, p<0.001], and fluoxetine produced age-dependent effects on latency to emerge [age x treatment interaction F(1,68)=8.78, p<0.01]. Post-hoc testing revealed that fluoxetine increased adult latency to emerge, but did not increase adolescent latency. Fluoxetine suppressed light entries (Fig.15c) [main effect of treatment F(1,67)=12.63, p<0.001] and locomotion (Fig.15d) [main effect of treatment
F(1,68)=15.48, p<0.001] similarly in each age group.
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Figure 15: Fluoxetine Light/Dark Test The effects of 10 mg/kg fluoxetine on behavior in the light/dark test. A.) Time spent in the light compartment. B.) Latency to emerge into the light compartment. C.) Number of entries into the light compartment. D.) Total distance traveled. * = different from age matched saline (p<0.05), # = different from fluoxetine treated adolescents, (p<0.05). n = 18 per treatment group.
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4. The Effects of Indirect Serotonin Agonists on Extracellular Serotonin
The simplest explanation for the greater behavioral effects of indirect serotonin agonists in adult rats versus adolescents would be greater drug-induced increases in extracellular serotonin in adult rats. We assessed several aspects of presynaptic serotonergic function in adult and adolescent rats, and tested whether indirect serotonin agonists produce greater increases in extracellular serotonin in adult rats using microdialysis.
4.1 Indices of Serotonergic Innervation and Function
4.1.1 Tissue Serotonin Content, Turnover, and Synthesis
Adolescent rats had lower serotonin content (Fig.16a-c) than adults in prefrontal cortex, amygdala, and hippocampus [main effect of age F(1,14)=49.57, p<0.001].
ANOVA for serotonin content also produced an age x region interaction [F(2,28)=7.45, p<0.01], and post hoc testing confirmed that adolescents had lower serotonin content than adults in all three brain regions. No age differences were detected in 5-HIAA levels. There were regional differences in both serotonin [main effect of region
F(2,28)=210.69, p<0.001] and 5-HIAA [main effect of region F(2,28)=258.98, p<0.001], with levels of each being highest in the amygdala. Adolescent rats had higher serotonin turnover (5-HIAA/5-HT) than adults across all three regions [main effect of age
F(1,14)=52.82, p<0.001], which reflected the lower serotonin levels and comparable
5HIAA. Treatment with the decarboxylase inhibitor NSD-1015 increased 5-HTP levels 110
similarly in each age group (Fig.16d) [main effect of treatment F(1,28)=265.54, p<0.001], indicating comparable rates of serotonin synthesis.
Figure 16: Tissue Serotonin Content, 5-HIAA Levels, and Serotonin Synthesis Tissue levels of serotonin, 5-HIAA, and serotonin turnover (5-HIAA/5-HT) in prefrontal cortex (A.), amygdala (B.), and hippocampus (C.). D.) 5-HTP content is shown in prefrontal cortex (PFC), amygdala (AMG), and hippocampus (HPC). S = saline treated rats, N = NSD-1015 treated rats. * = significant age difference (p<0.05). A-C.) n = 8 per age group, D.) n = 8 per treatment group.
4.1.2 Density of Serotonin Transporter Immunostaining
The density of SERT-immunoreactive innervation was quantitated in prefrontal cortex, amygdala, and hippocampus to investigate possible age differences (Fig 17, 18). There were significant regional differences in the density of SERT immunoreactive axons
[main effect region F(5, 104)=192.4, p<0.001]. SERT immunoreactivity was highest in the
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basolateral amygdala, as has been seen in previous immunostaining and autoradiography studies (Hrdina et al., 1990; Sur et al., 1996). No age difference in SERT immunoreactivity was detected in these brain regions and there was no interaction of region and age.
Figure 17: Density of SERT-Immunoreactive Axons Data are shown as the percent of total image area occupied by SERT immunoreactive axons. mPFC = medial prefrontal cortex, BLA = basolateral amygdala, CeA=central amygdala, DG = dentate gyrus. CA1, CA3, and dentate gyrus are from dorsal hippocampus. n = 12 per age group.
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Figure 18: Example SERT Immunostaining
All images are composed of stitched deconvoluted panels of images taken at 20X magnification. Scale bars represent 200 µm in parts A. and B. and 50 µm in parts C. and D. A.) SERT immunoreactivity in prefrontal cortex. The white arrow indicates the midline of the brain. B.) SERT immunoreactivity in the amygdala. The white arrow indicates the basolateral amygdala (enlarged in C.) and the white arrowhead indicates the central nucleus of the amygdala (enlarged in D.).
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4.1.3 3H-Paroxetine Serotonin Transporter Binding
We performed 3H-paroxetine binding in homogenates of prefrontal cortex, amygdala, and hippocampus to compare total SERT levels between age groups. Single point binding with 50 pM 3H-paroxetine (Fig.19a) revealed no significant effect of age on ligand binding, though there were regional differences in binding [main effect of region
F(2,28)=84.37, p<0.001]. Single point binding with a saturating concentration of 1000 pM
3H-paroxetine (Fig.19b) produced similar results [main effect of region F(2,28)=80.30, p<0.001]. The amygdala had higher binding levels than cortex or hippocampus, which is consistent with the higher serotonin content and SERT immunoreactivity found in the brain region. Saturation binding of pooled homogenates revealed no age differences in
Bmax or Kd (Table 3).
Figure 19: 3H-Paroxetine Single Point Binding Single point binding experiments were performed with 50 pM (A.) and 1000 pM (B.) 3H- paroxetine. PFC = prefrontal cortex, AMG = amygdala, HPC = hippocampus. n = 8 per age group.
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Table 3: 3H-Paroxetine Saturation Binding Results Results of saturation binding curves for pooled tissue homogenates. Data are presented as mean SEM. n = 8 per age group.
Prefrontal Cortex Amygdala Hippocampus Adolescents Bmax = 289 21 Bmax = 592 51 Bmax = 231 19 Kd = 22.4 8.4 Kd = 38.2 14.5 Kd = 23.5 8.6 Adults Bmax = 305 32 Bmax = 526 57 Bmax = 279 28 Kd = 26.9 13.9 Kd = 35.4 16.6 Kd = 32.2 12.7
4.2 Comparison of Probe Recovery and Baseline Extracellular Serotonin Using the Zero Net Flux Method of Quantitative Microdialysis
In vivo probe recovery in each age group was investigated using the zero net flux method to rule out the possibility that age differences in probe recovery could confound microdialysis experiments (Lonnroth et al., 1987). Diffusion characteristics of the tissue being sampled and neurotransmitter uptake significantly affect in vivo probe recovery, so assessing a probe’s in vitro probe recovery prior to performing microdialysis does not provide an accurate estimate of actual in vivo analyte concentrations (Justice, 1993). No age differences were observed in in vivo probe recovery (p>0.97, Fig. 20a). The zero net flux method also provides an estimate of extracellular serotonin. Adolescent rats had higher baseline extracellular serotonin as estimated by the zero net flux method (p<0.05,
Fig. 20b). In order to confirm this observation, all baseline samples from standard experiments were pooled and analyzed by two-way ANOVA (age, time) (Fig.20c).
Adolescents also had higher baseline serotonin by this method of comparison (main effect of age F(1,106)=5.81, p<0.05)
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Figure 20: Zero Net Flux Results and Baseline Extracellular Serotonin Estimated baseline extracellular serotonin (A.) and in vivo probe recovery (B.) as determined by zero net flux microdialysis. Pooled baseline samples from all experiments are shown in C). * = significant age difference, p<0.05. A-B.) n = 8 per age group, C.) n = 57 adults and 52 adolescents.
4.3 Fenfluramine
Fenfluramine-stimulated serotonin levels were greater in adult rats than adolescents. Each dose of fenfluramine produced greater extracellular serotonin levels
[main effect of dose F(3,45)=319.36, p<0.001], and serotonin levels peaked at one hour after each injection. Serotonin levels did not completely return to baseline during the three hours after each dose, resulting in a cumulative increase in serotonin across time
[main effect of time F(3,45)=100.3, p<0.001, time x dose interaction F(9,135)=9.12, p<0.001]. Global ANOVA indicated differential effects of the fenfluramine dose response curve in each age group with an age x time x dose interaction for serotonin levels in each sample (Fig.21a) [F(9,135)=3.17, p<0.01] and the percent increase from baseline (Fig.21b) [F(9,135)=3.16, p<0.01]. This interaction was further investigated by two factor (age, time) repeated measures ANOVA and post-hoc testing for each dose of fenfluramine. Significant age x time interactions were observed at each dose for
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serotonin levels [1 mg/kg F(5,74)=2.73, p<0.05, 2.5 mg/kg F(5,75)=4.42, p<0.01, 10 mg/kg
F(5,75)=3.79, p<0.01] and the percent increase from baseline [1 mg/kg F(5,74)=2.98, p<0.05, 2.5 mg/kg F(5,75)=3.96, p<0.01, 10 mg/kg F(5,75)=3.19, p<0.05], indicating differential effects of each dose between age groups. Post-hoc testing showed that adolescents had lower fenfluramine-stimulated serotonin release than adults during the two peak samples following each dose. There was also an age x time interaction in baseline samples [serotonin F(3,45)=3.38, p<0.05, percent increase F(3,45)=3.49, p<0.05].
Post-hoc testing revealed slightly higher extracellular serotonin at the one hour time point in adolescents.
Figure 21: Fenfluramine Microdialysis The effects of sequential doses of 1, 2.5, and 10 mg/kg fenfluramine on extracellular serotonin levels in medial prefrontal cortex (A.) and the percent increase in serotonin from baseline (B.). Arrows indicate time points at which fenfluramine was administered. * = significant age difference (p<0.05). n = 9 adults and 8 adolescents.
4.4 Potassium Evoked Release
Potassium evoked release was also greater in adult rats than in adolescents. A 20 minute infusion of 100 mM KCl into the mPFC increased serotonin levels above baseline 117
for 40 minutes and produced a greater increase in extracellular serotonin in adult rats compared to adolescents. ANOVA revealed an age x time interaction for serotonin levels (Fig.22a) [F(15,285)=2.37, p<0.01] and percent increase from baseline (Fig.22b)
[F(15,285)=3.64, p<0.001], suggesting age differences in the response to potassium infusion. Post hoc testing showed that adolescent extracellular serotonin levels were significantly lower than those of adults at both time points of elevated serotonin following potassium infusion.
Figure 22: Potassium-Evoked Serotonin Release The effects of local infusion of 100 mM KCl in mPFC on extracellular serotonin (A.) and the percent increase from baseline (B.). The duration of potassium infusion is indicated by the bar under the peak in serotonin levels. * = significant age difference (p<0.05). n = 12 adults and 10 adolescents.
4.5 Fluoxetine
Fluoxetine produced similar increases in extracellular serotonin in each age group. Each subsequent dose of fluoxetine produced greater extracellular serotonin levels (Fig.23a) [effect of dose (3,72)=327.14, p<0.001], resulting in a cumulative increase
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in extracellular serotonin over time [effect of time F(5,120)=23.85, p<0.001, time x dose interaction F(15,334)=5.29, p<0.001]. No significant effect of age or interaction of age with other variables was detected, indicating a similar response to fluoxetine in each age group. The percent increase in serotonin from baseline was also similar between age groups (Fig.23b).
Figure 23: Fluoxetine Microdialysis The effects of sequential doses of 2.5, 5, and 10 mg/kg fluoxetine on extracellular serotonin levels in medial prefrontal cortex (A.) and the percent increase in serotonin from baseline (B.). Arrows indicate time points at which fluoxetine was administered. n = 13 adults and 13 adolescents.
4.6 Local Fluoxetine Infusion
The effects of local infusion of 30 µM fluoxetine were also assessed to bypass any age differences in fluoxetine metabolism or autoreceptor function. Local infusion of fluoxetine stimulated a comparable increase in extracellular serotonin that reached similar levels in both age groups (Fig.24a) [main effect of time F(17,254)=77.79, p<0.001].
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The percent increase in extracellular serotonin was also similar in each age group
(Fig.24b) [main effect of time F(17,254)=43.46, p<0.001].
Figure 24: Local Fluoxetine Administration in Medial Prefrontal Cortex The effects of local infusion of 30 µM fluoxetine into the mPFC on extracellular serotonin levels (A.) and the percent increase in serotonin from baseline (B.). The duration of fluoxetine infusion is indicated by the bar at the top of the graph. n = 10 adults and 7 adolescents.
4.7 Confirmation of Probe Placements
Correct placement of microdialysis probes was determined in brain sections stained with cresyl violet. Rats with probes greater than 0.5 mm anterior or posterior to the target coordinate of 3.2 mm anterior from bregma were excluded from further analysis. One rat was also excluded due to probe placement in the midline of the brain.
The total number of animals excluded due to poor probe placement were 3 adults and 6 adolescents. The following figure depicts probe placements from all rats included in microdialyis studies.
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Figure 25: Microdialysis Probe Placement Illustration of microdialysis probe placement in medial prefrontal cortex. Gray lines represent adolescent placements and black lines represent adult placements. Figure adapted from (Paxinos and Watson, 1986).
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5. Comparison of the Post-synaptic Response to Serotonergic Signaling
5.1 Behavioral Effects of Serotonin Receptor Agonists
5.1.1 8-OH DPAT Light/Dark Test
Adult and adolescent rats were treated with the 5-HT1A agonist 8-OH DPAT prior to performing the LD test to investigate age differences in 5-HT1A mediated behavioral effects. As with indirect serotonergic agonists, 8-OH DPAT produced greater anxiogenic effects in adults compared to adolescents. Analysis of time spent in the light compartment (Fig.26a) revealed main effects of age [F(1,30)=15.73, p<0.001], treatment
[F(2,28)=17.65, p<0.001], and an age x treatment interaction [F(2,28)=7.81, p<0.01], showing that 8-OH DPAT produced different effects in each age group. Post-hoc testing revealed that both doses of 8-OH DPAT reduced the time spent in the light compartment relative to controls in adults but not adolescents. Adult rats spent significantly less time in the light compartment at both doses of 8-OH DPAT than adolescents treated with the same dose. 8-OH DPAT also increased the latency to emerge into the light compartment (Fig.26b) [main effect of treatment F(2,28)=4.17, p<0.05]. Adult rats took longer to emerge than adolescents across treatment groups
[main effect of age F(1,30)=9.13, p<0.01], but there was not a significant age x treatment interaction for the latency to emerge into the light compartment. 8-OH DPAT reduced entries into the light compartment (Fig.26c) [main effect of treatment F(2,28)=7.31,
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p<0.01] and locomotion (Fig.26d) [main effect of treatment F(2,28)=17.24, p<0.001] similarly in each age group.
Figure 26: Effects of 8-OH DPAT in the LD Test The effects of 0.25 and 0.5 mg/kg 8-OH DPAT on behavior in the light/dark test. A.) Time spent in the light compartment. B.) Latency to emerge into the light compartment. C.) Number of entries into the light compartment. D.) Total distance traveled. * = different from age matched saline (p<0.05), # = different from 8-OH DPAT treated adolescents (p<0.05). n = 16 saline treated animals and 8 animals per 8-OH DPAT dose for each age group.
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5.1.2 mCPP Light/Dark Test
Adult and adolescent rats were treated with the 5-HT2 agonist mCPP prior to performing the LD test to probe for age differences in 5-HT2 modulation of behavior. In contrast to indirect serotonin agonists and 8-OH DPAT, mCPP produced similar anxiogenic effects in each age group. mCPP lowered time in the light compartment
(Fig.27a) [main effect of treatment F(2,66)=9.56, p<0.001] and increased latency to emerge
(Fig.27b) [main effect of treatment F(2,66)=16.33, p<0.001], but no age differences were detected in these effects. The number of light entries was similarly reduced by mCPP treatment in each age group (Fig.27c) [main effect of treatment F(2,66)=21.12, p<0.001]. mCPP reduced locomotion in both age groups at the highest dose used (Fig.27d), though
0.5 mg/kg mCPP produced trends in opposite directions for each age group [main effect of treatment F(2,66)=21.9, p<0.001, age x treatment interaction F(2,66)=5.37, p<0.01]. Post- hoc testing showed that mCPP significantly reduced locomotion in each age group at 1 mg/kg and that the trends for changes at 0.5 mg/kg were not significant.
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Figure 27: Effects of mCPP in the LD Test The effects of 0.5 and 1 mg/kg mCPP on behavior in the light/dark test. A.) Time spent in the light compartment. B.) Latency to emerge into the light compartment. C.) Number of entries into the light compartment. D.) Total distance traveled. * = different from age matched control (p<0.05). n = 18 saline, 8 0.5 mg/kg, and 10 1 mg/kg for each age group.
5.1.3 3H-8-OH DPAT Binding
3H-8-OH DPAT binding was compared between adult and adolescent rats to determine if the lower adolescent behavioral response to 8-OH DPAT could be 125
explained by age differences in 5-HT1A receptor levels. No age differences were detected in a single point binding experiment with 1 nM 3H-8-OH DPAT in homogenates of prefrontal cortex, amygdala, and hippocampus (Fig.28). There were regional differences in binding, with the hippocampus having the most 5-HT1A binding, followed by cortex and amygdala [main effect of region F(2,27)=388.22, p<0.001].
Figure 28: 3H-8-OH DPAT Binding in Tissue Homogenates 3H-8-OH DPAT binding in homogenates of prefrontal cortex (PFC), amygdala (AMG), and hippocampus (HPC) of adult and adolescent rats. n = 8 per age group.
5.1.4 Site Specific Injection of 8-OH DPAT
5.1.4.1 Control Animal Behavior
The surgery and handling procedure used for site specific injections produced changes in some measures of behavior in the LD test (Fig. 29). Behavior of control animals from systemic injection experiments was compared to controls from site specific injection experiments. There was no significant effect of the site-specific procedure on time spent in the light compartment, but analysis of time spent in the light compartment
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produced a main effect of age (Fig.29a) [F(1,227)=6.58, p<0.05], showing that across experiments adolescents spent more time in the light than adults. No age difference was observed in a prior analysis of only systemic control animals, so this age difference was created by addition of the site-specific controls. Animals of both age groups emerged into the light more quickly in the site specific experiments compared to the systemic experiments (Fig.29b) [main effect of experiment F(1,223)=5.25, p<0.05]. The site-specific procedure abolished the age difference observed in systemically treated animals, resulting in the lack of a significant age effect when animals from both experiments were analyzed simultaneously. These changes in latency to emerge may have been caused by the extensive handling these animals received to ameliorate the stress of surgery. No significant effects of the site specific injection procedure were detected for the number of entries into the light compartment (Fig.29c), but the procedure did change the total distance traveled (Fig.29d) [main effect of experiment F(1,227)=10.02, p<0.01]. This effect differed between age groups as shown by a significant age x experiment interaction
[F(1,227)=12.13, p<0.001]. Post-hoc testing showed that the site-specific handling and surgery procedure enhanced locomotion in adolescent rats, but not adults.
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Figure 29: Comparison of Light/Dark Test Behavior of Controls from Systemic and Site Specific Experiments Comparison of control animal behavior from systemic (IP) versus site specific (Site) experiments. A.) Time spent in the light compartment. B.) Latency to emerge into the light compartment. C.) Number of entries into the light compartment. D.) Total distance traveled. * = significantly different from age matched i.p. injected animals, p<0.05.
5.1.4.2 Prelimbic Cortex
Infusion of 8-OH DPAT into the prelimbic division of medial prefrontal cortex did not produce a significant effect on behavior in either age group. A main effect of age was found for time spent in the light compartment (Fig. 30a) [F(1,60)=12.73, p<0.001], indicating lower time in light in adult rats across drug treatments. Adults also had
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higher latency to emerge than adolescents (Fig. 30b) as indicated by a main effect of age
[F(1,60)=10.74, p<0.01], but there was not a significant effect of treatment or age x treatment interaction. Finally, a main effect of age [F(1,60)=15.07, p<0.001] was also observed for total distance traveled (Fig. 30d), indicating less overall locomotion in adults.
Figure 30: Behavior in LD Test After Infusion of 8-OH DPAT into Prelimbic Cortex The effects of infusion of 50, 100, and 200 ng 8-OH DPAT into prelimbic cortex. A.) Time spent in the light compartment. B.) Latency to emerge into the light compartment. C.) Number of entries into the light compartment. D.) Total distance traveled. n = 14-15 aCSF, 2-3 50 ng, 8-9 100 ng, 8-9 200 ng per age group.
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5.1.4.3 Ventral Hippocampus
A small number of adult and adolescent rats were tested in a pilot experiment with infusion of 100 ng 8-OH DPAT into ventral hippocampus. Adult aCSF treated rats had very low time in light compartment in this experiment (Fig.31a), possibly due to the large lesion necessary to implant a cannula in ventral hippocampus. This high baseline anxiety-like behavior in adults would create a floor effect that would make it difficult to measure any increases in anxiety, so further animals were not tested with injections into ventral hippocampus.
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Figure 31: Behavior in LD Test After Infusion of 8-OH DPAT into Ventral Hippocampus The effects of infusion of 100 ng 8-OH DPAT into ventral hippocampus. A.) Time spent in the light compartment. B.) Latency to emerge into the light compartment. C.) Number of entries into the light compartment. D.) Total distance traveled. n = 3 per treatment group.
5.1.4.4 Basolateral and Central Amygdala
Data collection from central amygdala infusions was unsuccessful due to lack of animals with correct cannula placement in both hemispheres. Infusions into the basolateral amygdala were more successful, and enough animals were collected to assess the effects of 100 ng 8-OH DPAT infusion. Infusion of 8-OH DPAT into
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basolateral amygdala produced significant effects on several behavioral measures.
Analysis of the time spent in the light compartment (Fig. 32a) revealed an age x treatment interaction [F(1,17)=5.52, p<0.05], though neither 8-OH DPAT treated group was significantly different from controls by post-hoc testing. No main effects or interactions were found for latency to emerge into the light (Fig.32b). A main effect of age [F(1,17)=6.94, p<0.05] was found for the number of light entries (Fig.32c), reflecting more light entries made by adult rats. There was also an age x treatment interaction for light entries [F(1,17)=8.26, p<0.05], and post-hoc testing revelaed that 8-OH DPAT increased the number of light entries made by adult rats. Similarly, ANOVA and post- hoc testing revealed that 8-OH DPAT increased total distance traveled in adult rats
(Fig.32d), but not adolescents [age x treatment interaction F(1,17)=13.33, p<0.01).
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Figure 32: Behavior in LD Test After Infusion of 8-OH DPAT into Basolateral Amygdala The effects of infusion of 100 ng 8-OH DPAT into basolateral amygdala. A.) Time spent in the light compartment. B.) Latency to emerge into the light compartment. C.) Number of entries into the light compartment. D.) Total distance traveled. * = significantly different from age matched controls, p<0.05. n = 6 adolescent aCSF, 5 adolescent 8-OH DPAT, 6 adult aCSF, 3 adult 8-OH DPAT.
5.2 Measuring c-Fos Activation After Treatment with Fluoxetine, 8-OH DPAT, and mCPP
5.2.1 Determining Maximal c-Fos Expression
The number of c-Fos positive nuclei was determined in adult and adolescent rats following stimulation of the medial forebrain bundle (MFB) to determine the maximal c-
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Fos response in each age group. This was performed to confirm the validity of c-Fos expression as a marker of neuronal activation in both adolescent and adult rats. Sections containing prefrontal cortex, bed nucleus of the stria terminalis, striatum, and amygdala were processed for c-Fos immunohistochemistry. Stimulation of the MFB induced robust c-Fos activation across all cortical regions examined, but no stimulation was observed in any subcortical region. Cells were counted in the lateral orbital cortex from prefrontal cortical sections, and from the perirhinal cortex and central amygdala from sections at the level of the amygdala. Analysis of all three regions showed that MFB stimulation significantly increased c-Fos expression [main effect of stimulation
F(1,6)=305.88, p<0.001]. The lack of effect of MFB stimulation was reflected in a main effect of region [F(2,11)=33.56, p<0.001] and a stimulation x region interaction
[F(2,11)=77.56, p<0.001]. There was no significant main effect of age or interaction of age with either region or stimulation, indicating that each age group responded similarly to
MFB stimulation.
Table 4: c-Fos Immunoreactive Nuclei After Medial Forebrain Bundle Stimulation Data are shown as mean number of c-Fos IR nuclei ± SEM. n = 4 per age. Unstimulated and stimulated counts are repeated measures from each animal.
Age Brain Region Lateral Orbital Ctx Perirhinal Ctx Central Amygdala Unstim Stim Unstim Stim Unstim Stim Adolescent 2±1 415±33 8±5 760±82 110±31 102±22 Adult 3±2 410±32 10±5 733±26 80±46 103±53
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Figure 33: c-Fos Staining in Lateral Orbital Cortex Lateral orbital cortex from unstimulated (A.) and stimulated (B.) hemispheres of the same section. The scale bars in each figure represent 100 microns.
5.2.3 c-Fos Expression Following Fluoxetine or 8-OH DPAT Treatment
The effects of fluoxetine and 8-OH DPAT on c-Fos immunoreactivity were compared in adult and adolescent rats in regions of the prefrontal cortex (prelimbic and lateral orbital cortices), the paraventricular nucleus of the hypothalamus, and regions of the extended amygdala (central amygdala, medial amygdala, and the lateral and ventral subdivisions of the bed nucleus of the stria terminalis). Fluoxetine and 8-OH DPAT significantly increased the number of c-Fos-IR cells as shown by a main effect of treatment in a global ANOVA [F(2,66)=3.46, p<0.05]. The effects of fluoxetine and 8-OH
DPAT differed across brain regions [main effect of region F(6,335)=19.71, p<0.001, treatment x region interaction F(12,335)=8.52, p<0.001]. There were also age differences across brain regions as shown by an age x region interaction [F(6,335)=3.97, p<0.001].
The significant interactions in the global ANOVA for c-Fos-IR cell numbers were 135
followed by two way ANOVAs (age, treatment) for each brain region. These analyses revealed a main effect of drug treatment in the lateral orbital cortex [F(2,39)=5.42, p<0.01], central amygdala [F(2,66)=8.72, p<0.001], lateral bed nucleus of the stria terminalis [F(2,65)=3.47, p<0.05], and paraventricular nucleus of the hypothalamus
[F(2,60)=3.54, p<0.05]. There were also age differences in both cortical regions, as shown by main effects of age [PrL F(1,45)=6.71, p<0.05, LO F(1,39)=4.29, p<0.05].
Global analysis of the percent increase in c-Fos-IR cells in animals treated with fluoxetine or 8-OH DPAT revealed an overall age difference in drug effects (Fig.36)
[main effect of age F(1,44)=8.06, p<0.01]. There was also a main effect of region
[F(6,225)=17.52, p<0.001] and interactions of age and region [F(6,225)=6.19, p<0.001] and treatment and region [F(6,225)=8.05, p<0.001], indicating age differences across brain regions and differential treatment effects across region. Finally, the analysis produced an age x treatment x region interaction [F(6,225)=3.07, p<0.001], showing that the drugs affected each age group differently across brain regions. The global analysis was followed by multiple repeated measures ANOVA for each drug with age and region as factors. These analyses were conducted by regional grouping, which included the extended amygdala (central amygdala, medial amygdala, and the lateral and ventral bed nucleus of the stria terminalis), the prefrontal cortex (prelimbic and lateral orbital cortices), and the paraventricular nucleus of the hypothalamus. For fluoxetine (Fig.36a), the ANOVA for the extended amygdala revealed a main effect of age [F(1,22)=5.99,
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p<0.05], showing that adult rats had greater increases in c-Fos expression across the extended amygdala. The ANOVAs for prefrontal cortex and paraventricular hypothalamus did not reveal main effects of age, indicating that adult and adolescent rats responded similarly in these brain regions. The ANOVA for 8-OH DPAT treated rats (Fig.36b) revealed a main effect of age [F(1,18)=4.98, p<0.05] and an age x region interaction [F(1,12)=42.33, p<0.001] for the prefrontal cortex, showing that adult rats had a greater response to 8-OH DPAT in this region. Post-hoc testing confirmed that adult rats exhibited a greater increase in c-Fos in the lateral orbital cortex than adolescents.
Analysis of the extended amygdala also produced an age x region interaction
[F(3,63)=2.76, p<0.05], and post-hoc testing showed that adult rats had a greater response than adolescents in the central nucleus of the amygdala. Taken together, these data show that fluoxetine produced greater increases in c-Fos expression in adult rats across the extended amygdala, while 8-OH DPAT produced greater responses in adult rats in the lateral orbital cortex and the central nucleus of the amygdala.
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Table 5: Numbers of c-Fos-IR Cells in Adult and Adolescent Rats Treated With Fluoxetine or 8-OH DPAT Data are shown as mean number of c-Fos IR nuclei ± SEM. n = 12 per treatment group.
Age Treatment Region PrL LO CeA MeA BNSTl BNSTv PVH Adolescent Vehicle 52±20 38±21 48±7 108±17 44±7 104±23 93±13 Fluoxetine 39±13 25±9 104±14 110±15 45±10 73±19 218±46 8-OH 75±22 51±17 92±23 97±16 72±15 90±10 118±24 DPAT Adult Vehicle 102±24 28±13 38±10 59±9 43±8 78±18 73±14 Fluoxetine 73±29 51±22 127±25 118±20 84±14 110±22 198±45 8-OH 149±32 145±39 126±27 90±15 73±13 62±13 122±23 DPAT
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Figure 34: Percent Increase in c-Fos Immunoreactive Nuclei After Fluoxetine or 8-OH DPAT The percent increase in c-Fos immunoreactive nuclei relative to vehicle after treatment with A.) fluoxetine (10 mg/kg i.p.) or B.) 8-OH DPAT (0.5 mg/kg i.p.). PrL=prelimbic cortex, LO=lateral orbital cortex, CeA=central nucleus of the amygdala, MeA=medial nucleus of the amygdala, BSTl=lateral subdivision of the bed nucleus of the stria terminalis, BSTv=ventral subdivision of the bed nucleus of the stria terminalis. * = significant age difference (p<0.05). n = 12 per treatment group. Examples of c-Fos immunostaining in central amygdala (C-F) and lateral orbital cortex (G-J), scale bars in all images represent 100 µm. Representative staining from C.) adolescent vehicle, D.) adolescent fluoxetine, E.) adult vehicle, F.) adult fluoxetine in central amygdala. Representative staining from G.) adolescent vehicle, H.) adolescent 8-OH DPAT, I.) adult vehicle, J.) adult 8-OH DPAT in lateral orbital cortex.
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5.2.4 c-Fos Expression Following mCPP Treatment
The effects of treatment with mCPP (1 mg/kg i.p.) versus saline were assessed in the same regions measured with fluoxetine and 8-OH DPAT, with the exception of the ventral subdivision of the bed nucleus of the stria terminalis. mCPP did not produce a significant increase in c-Fos IR nuclei in any brain region. Global analysis of the number of c-Fos IR nuclei revealed regional differences in c-Fos [main effect of region
F(5,94)=2.80, p<0.05] and an age x treatment x region interaction [F(5,94)=3.15, p<0.05].
Each brain region was then analyzed by two way ANOVA with age and treatment as factors. These analyses revealed no effect of treatment in any region, but a main effect of age was found in prelimbic cortex [F(1,18)=7.68, p<0.05]. Analysis of the percent change in c-Fos IR nuclei relative to saline revealed an age x region interaction (Fig.37)
[F(5,45)=3.43, p<0.05)], and post-hoc testing revealed an age difference in the percent change in lateral orbital cortex.
Table 6: Number of c-Fos-IR Cells in Adult and Adolescent Rats Treated With mCPP
Age Treatment Region PrL LO CeA MeA BSTl PVH Adolescent Saline 18±8 19±7 13±4 59±11 14±7 21±6 mCPP 15±7 38±20 23±6 38±6 15±8 15±5 Adult Saline 48±28 110±65 31±22 51±18 28±14 49±25 mCPP 75±18 28±14 39±11 35±12 32±5 43±9
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Figure 35: Percent Increase in c-Fos Immunoreactive Nuclei After mCPP
The percent increase in c-Fos immunoreactive nuclei relative to vehicle after treatment with mCPP (1 mg/kg i.p.) PrL=prelimbic cortex, LO=lateral orbital cortex, CeA=central nucleus of the amygdala, MeA=medial nucleus of the amygdala, BSTl=lateral subdivision of the bed nucleus of the stria terminalis, BSTv=ventral subdivision of the bed nucleus of the stria terminalis. * = significant age difference (p<0.05). n = 6 per treatment group.
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6. Discussion
The main finding of this project is that adolescent male rats are less sensitive to the behaviorally inhibiting effects of acute treatment with indirect serotonin agonists.
This finding may have relevance to the major adolescent health problems of risk-taking behavior, drug abuse and suicidality during SSRI treatment (Barbui et al., 2009; Eaton et al., 2012; Hammad et al., 2006; Schneeweiss et al., 2010). Drugs of abuse are known to be less aversive to adolescents, which could contribute to increased drug use and subsequent vulnerability to addiction (Infurna and Spear, 1979; Schramm-Sapyta et al.,
2007; Schramm-Sapyta et al., 2006; Shram et al., 2006). Serotonin contributes to the aversive effects of these drugs, so less sensitivity to anxiogenic or inhibitory drug effects may lead to the reduced aversion seen in adolescents (Ettenberg and Bernardi, 2006,
2007; Ettenberg et al., 2011; Jones et al., 2009; Jones et al., 2010; Rocha et al., 2002; Serafine and Riley, 2010). Suicide is associated with impulsivity, so behavioral inhibition in the early phases of treatment with SSRIs may exert a protective effect in adults that does not occur in adolescents (reviewed in Hawton et al., 2012; Mann, 2003). The lower behavioral inhibition in indirect agonist-treated adolescents could also be relevant for the general increase in risk taking that occurs during adolescence. Serotonin release increases in stressful situations, and this increase has been related to anxiety-like behavior (Matsuo et al., 1996; Rex et al., 1999, 2005; Wright et al., 1992). Adolescents could be less sensitive to the postsynaptic effects of such increases in serotonin release
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and thus be more likely to act in a less inhibited manner when faced with potential adverse consequences.
The experiments of this project were designed to test the hypothesis that immature adolescent serotonergic function contributes to the disinhibited, risk taking behavior observed during this age period, and can alter responses to drugs targeting the serotonergic system. The lower behaviorally-inhibiting effects of indirect serotonin agonists in adolescents are consistent with this hypothesis. We then investigated which aspects of serotonergic function may be immature during adolescence. We investigated presynaptic serotonergic function, postsynaptic serotonin receptor expression and function, and function of neural circuits modulated by serotonin.
Microdialysis experiments showed that indirect agonist-stimulated increases in extracellular serotonin are not sufficient to completely explain the lower behaviorally inhibiting effects of these drugs in adolescents. Adolescents had lower fenfluramine- stimulated increases in mPFC extracellular serotonin than adults, so presynaptic serotonergic function may be partially responsible for lower adolescent sensitivity to releasing drugs such as fenfluramine and MDMA. However, adults and adolescents had a comparable increase in mPFC extracellular serotonin after fluoxetine treatment.
The most likely explanation for the discrepancy between fluoxetine’s behavioral and neurochemical effects is a developmental difference in serotonin’s postsynaptic effects.
It is possible that age differences in fluoxetine-stimulated increases in extracellular
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serotonin in other brain regions could underlie age differences in fluoxetine’s behavioral effects. However, investigation of serotonin and 5-HIAA content, SERT-IR innervation, and SERT radioligand binding in hippocampus and amygdala do not support this possibility. Additionally, the prefrontal cortex is one of the latest brain regions to mature, making it the most likely region to reveal immature fluoxetine effects in adolescents (reviewed in Casey et al., 2008).
Behavior experiments with s(reviewed in erotonin receptor agonists showed that
5-HT1A receptors might be involved in lower adolescent sensitivity to indirect serotonin agonists. Adolescents exhibited a comparable level of behavioral inhibition to adults in response to the 5-HT2 agonist mCPP, but were less sensitive to the 5-HT1A agonist 8-OH
DPAT. The lower effects of 8-OH DPAT in adolescents may not be due to lower 5-HT1A receptor levels, as we detected no age differences in 3H-8-OH DPAT binding in several forebrain regions. Site-specific injection of 8-OH DPAT into the medial prefrontal cortex, hippocampus, and basolateral amygdala failed to reconstitute the behavioral effects of systemic 8-OH DPAT, so 5-HT1A receptor activation across a network of brain regions may be needed to produce behavioral inhibition. These experiments extended the initial finding of lower serotonin-mediated behavioral inhibition in adolescents by showing that adolescents are also less sensitive to 5-HT1A-mediated behavioral inhibition, but they did not provide evidence that 5-HT1A function in a specific brain region is responsible for these age differences.
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We then investigated age differences in the neural circuits responsible for behavioral inhibition as a mechanism for age differences in behavior. Numerous human and animal studies show adolescent immaturity of the connections between brain regions mediating behavioral inhibition (Cressman et al., 2010; Cunningham et al., 2002; reviewed in Casey et al., 2008; Ernst and Fudge, 2009; Ernst et al., 2006). It is therefore possible that increased extracellular serotonin or stimulation of 5-HT1A receptors are less effective at inhibiting adolescent behavior because the circuits modulated by serotonin are immature. Investigation of the circuit-level effects of fluoxetine and 8-OH DPAT on neuronal activation using the immediate early gene c-Fos revealed greater activation of the extended amygdala by fluoxetine and of the lateral orbital cortex and central amygdala by 8-OH DPAT in adult rats compared to adolescents. The effects of these drugs on neuronal activation in these brain regions may be associated with their greater behavioral effects in adults. These findings are consistent with human imaging and animal histology studies showing immature prefrontal cortical and amygdala function and connectivity, and suggest that immature cortical and amygdala circuits underlie the lower adolescent sensitivity to the behaviorally inhibiting effects of indirect serotonin agonists (Bourgeois et al., 1994; Cressman et al., 2010; Cunningham et al., 2002; Ernst et al., 2005; Guyer et al., 2008; Hare et al., 2008; Monk et al., 2003; Sturman and
Moghaddam, 2011a; Zehr et al., 2006).
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6.1 Age Differences in Baseline Behavior
The only measure of anxiety-like behavior with an age difference at baseline was latency to emerge into the light in the LD test. Adolescent rats consistently emerged into the light more quickly than adults. This has been seen in previous studies of adolescents in the LD test (Schramm-Sapyta et al., 2007). Latency to emerge may reflect a different component of behavior than time spent in the light compartment. A detailed analysis of the EPM revealed that latency to emerge from a closed arm to an open arm (avoidance behavior) is pharmacologically distinguishable from latency to escape from an open arm to a closed arm (escape behavior) (Viana et al., 1994). The LD and EPM are similar tests, so this data may be relevant to LD behavior. Latency to emerge into the light compartment should be a pure avoidance measure, while time spent in the light compartment would involve both avoidance and escape. If latency to emerge is a measure of avoidance behavior, then shorter latency in adolescents in consistent with the triadic model’s prediction of a less active avoidance system in adolescents (reviewed in Ernst et al., 2006). Despite shorter adolescent latency at baseline, latency to emerge should still be a valid measure to assess drug effects in each age group, as the data from mCPP-treated animals show that adolescents are capable of slowing down to a similar level as adults.
No age differences in behavior of control animals were detected for most other behavioral measures in the LD and EPM. This facilitates comparison of drug effects
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between age groups. A number of studies have investigated anxiety-like behavior across adolescence in rodents and generated conflicting results. These studies have found increased, decreased, or similar anxiety-like behavior between adolescent and adult rodents (Andrade et al., 2003; Hascoet et al., 1999; Hefner and Holmes, 2007; Imhof et al., 1993; Lynn and Brown, 2010; Macri, 2002; Slawecki, 2005). These contradictory findings could be driven by species and strain differences in the ontogeny of anxiety-like behavior. Differences in testing conditions between laboratories could also be driving this lack of consensus, as adults have been shown to be more sensitive than adolescents to environmental factors in anxiety tests (Doremus et al., 2004). When optimizing conditions for the LD test, we noted that age differences in time in light began to emerge as lighting levels were increased. We therefore ran the test with lighting levels that gave similar time spent in the light compartment in each age group to facilitate comparison of drug effects.
6.2 Behavioral Response to Serotonin Depletion
We observed age- and test-specific behavioral effects of serotonin depletion with
PCPA. PCPA reduced anxiety-like behavior in adult rats in both the NIH and EPM tests, but was only effective in adolescents in the EPM. There are several potential explanations for these test-specific age differences. Both tests are built around an approach/avoidance conflict, but there are several key differences. The NIH test involves presentation of the rewarding stimulus of familiar, palatable food in a novel,
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aversive environment (reviewed in Dulawa and Hen, 2005). The factors affecting behavior in the EPM are simpler, as EPM involves no explicit rewarding stimulus
(Pellow and File, 1986). The presence of a rewarding stimulus in the NIH test could contribute to age differences in PCPA effects, given the interaction of dopamine and serotonin in mediating approach versus avoidance behavior, respectively (reviewed in
Boureau and Dayan, 2011; Cools et al., 2011; Daw et al., 2002; Dayan and Huys, 2009).
Dopamine/serotonin interactions could be a key difference between adolescent and adult behavior, as the serotonin system may be hypoactive relative to the dopaminergic system during adolescence (Fairbanks et al., 1999). Another key difference between the two tests is that the NIH test involves eating. Serotonin negatively regulates feeding and enhances the sensation of satiety by actions in the hypothalamus and in the periphery (reviewed in Lucki, 1998; Simansky, 1996). We observed PCPA enhancement of home cage eating in adolescents, but not adults, indicating potential age differences in regulation of feeding behavior.
Our observation of reduced anxiety-like behavior and behavioral inhibition after serotonin depletion in the NIH and EPM tests is consistent with previous studies
(Bechtholt et al., 2007; Gibson et al., 1994; Kshama et al., 1990; Treit et al., 1993).
However, we did not observe the expected anxiolytic effect in adult animals in the LD test (Koprowska et al., 1999; Kshama et al., 1990). This may be due to methodological issues. The rat LD test has been reported as sensitive to anxiolytic drug effects when
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animals begin the test in the light compartment, but not the dark compartment
(Chaouloff et al., 1997). We placed animals in the dark compartment at the beginning of the test to facilitate measurement of latency to emerge into the light compartment. Our
LD test protocol may therefore be insensitive to anxiolytic drug effects in adult rats, though it is clearly sensitive to anxiogenic drug effects.
Age differences in PCPA’s behavioral effects are likely not due to differential serotonin depletion, because PCPA induced similar levels of serotonin depletion across several forebrain regions in each age group. The depletion of serotonin ranged from 82-
90%, which should be sufficient to reduce extracellular serotonin. A study of the relationship of tissue serotonin content and extracellular serotonin in 5,7- dihydroxytryptamine lesioned animals showed that depletion of greater than 60% is needed to see reductions in extracellular serotonin (Hall et al., 1999).
The test-specific effects of PCPA on anxiety-like behavior in adult and adolescent rats show that some serotonergic regulation of anxiety-like behavior is in place by adolescence. Studies in humans and non-human primates also show that serotonin modulates behavioral inhibition during adolescence, as low central serotonergic function is associated with aggression and impulsivity in adolescents as well as in adults
(Higley et al., 1996; Mehlman et al., 1994; Zepf et al., 2008). Serotonin is also capable of modulating locomotor behavior and arousal during adolescence, as PCPA enhances spontaneous and amphetamine-stimulated locomotion beginning around PN15-20
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(Mabry and Campbell, 1974). However, our data with indirect serotonin agonists show that serotonin is capable of causing behavioral inhibition in adolescents, only not as effectively as in adults. Taken together, these data suggest that serotonin acts to increase behavioral inhibition in adolescents, but that its modulation of behavior is not yet mature.
6.3 Behavioral Response to Indirect Serotonin Agonists
Adult and adolescent rats were tested with three indirect serotonin agonists in the LD test; the serotonin releasing drugs fenfluramine and MDMA and the serotonin uptake inhibitor fluoxetine. Similar behavioral effects were observed for each drug, with adolescents showing less behavioral inhibition than adults. Of the two anxiety- related measures, the latency to emerge into the light more dramatically distinguished the two age groups. All three drugs significantly increased adult latency to emerge into the light compartment, while failing to slow down adolescents. Interestingly, this is the only measure that showed an age difference in baseline behavior. Fenfluramine was the only one of the three drugs to produce an age x treatment interaction for time in the light compartment, showing that adults experienced greater anxiogenic effects on this measure than adolescents. Both age groups experienced dramatically reduced time in light after MDMA treatment that may have resulted in a floor effect and inability to see age differences between adults and adolescents. Fluoxetine failed to produce a significant effect on time spent in the light compartment. The lesser behavioral effects of
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fluoxetine relative to the releasing drugs are likely due to greater increases in extracellular serotonin induced by releasing drugs compared to uptake inhibitors
(Gundlah et al., 1997).
Age differences in the locomotor effects of indirect serotonin agonists are unlikely to explain the lower adolescent sensitivity to the behaviorally inhibiting effects of these drugs. No significant age differences were detected in the locomotor effects of fenfluramine or fluoxetine. MDMA produced opposite trends in locomotion between age groups, with a trend for an increase in adolescents and a decrease in adults.
However, these effects were small in magnitude relative to the suppression of time in light in each age group. These small changes in locomotion are also unlikely to explain the dramatic increase in adult latency to emerge in relation to the lack of an effect in adolescents. The differences in locomotor effects between MDMA and the other two drugs may be due to MDMA’s greater affinity for the dopamine transporter relative to fenfluramine or fluoxetine (Rothman et al., 2001; Sanchez and Hyttel, 1999).
Adult and adolescent rats were also tested in the EPM with fenfluramine.
Similarly to the LD test, fenfluramine produced greater anxiogenic effects in adults than adolescents on the latency to emerge into an open arm. Fenfluramine-treated adults, but not adolescents, also spent more time in the closed arms than controls. Fenfluramine did not produce significant age differences in the other measures of anxiety-like behavior, in part due to variability in saline-treated adult behavior and subsequent floor
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effects. Rat behavior in the EPM is variable and is affected by many environmental factors (reviewed in File et al., 2004). Adolescents are less sensitive than adult to environmental effects on EPM behavior, which may have contributed to the lower variability in saline-treated adolescents (Doremus et al., 2004).
These experiments collectively show that adolescents are less sensitive than adults to the behaviorally inhibiting effects of indirect serotonin agonists in the LD and
EPM tests. Adolescent insensitivity to behavioral inhibition induced by these drugs suggests that immature serotonergic function could contribute to vulnerability to drug abuse and adverse antidepressant effects in adolescents. Determining the mechanism for adolescent insensitivity to the behaviorally inhibiting effects of indirect serotonergic agonists may reveal key age differences in serotonergic function that could inform treatment of affective disorders in adolescents and enhance understanding of adolescent vulnerability to drug abuse.
6.4 Age Differences in Presynaptic Serotonergic Function
We investigated multiple aspects of presynaptic serotonergic function in adults and adolescents, including the density of innvervation, SERT levels, tissue serotonin content and synthesis, and baseline extracellular serotonin. Adult and adolescent rats had similar density of SERT-IR axons in prefrontal cortex, amygdala, and hippocampus, indicating comparable density of serotonergic innervation. This finding is consistent with prior studies of serotonergic innervation showing comparable density of serotonin-
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IR axons in juvenile (PN21) and adult rats (Lidov and Molliver, 1982; Loizou, 1972). We also observed similar levels of SERT in each age group using 3H-paroxetine binding in tissue homogenates of prefrontal cortex, amygdala, and hippocampus. Previous autoradiography studies have reported lower SERT binding in cortex, and the discrepancy between our SERT binding data and previously reported autoradiography data may be explained by the use of different radioligands or the greater anatomic resolution of autoradiography versus homogenate binding (Dao et al., 2011; Moll et al.,
2000). Studies of SERT binding in subcortical structures in adolescence have also produced mixed results, so adolescent deficits in SERT expression may be relatively subtle (Dao et al., 2011; Galineau et al., 2004; Moll et al., 2000; Tarazi et al., 1998).
We observed lower tissue serotonin content in adolescent rats than in adults in prefrontal cortex, amygdala, and hippocampus, as has been seen in previous studies
(Loizou, 1972; Loizou and Salt, 1970; Mercugliano et al., 1996). Given the comparable innervation density in each age group, lower serotonin content in adolescents may be indicative of lower vesicular serotonin stores. Lower tissue serotonin in adolescents is not due to lower rates of serotonin synthesis, as shown by similar accumulation of 5-
HTP when adults and adolescents were treated with the l-AADC inhibitor NSD-1015.
Tryptophan hydroxylase activity matures around PN30 in rats, so early adolescent animals at PN28 may have not yet built up mature levels of vesicular serotonin (Deguchi and Barchas, 1972; Park et al., 1986; Schmidt and Sanders-Bush, 1971). Data on the
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ontogeny of VMAT2 do not support a role for immature VMAT2 function in lower adolescent tissue serotonin content. Serotonergic neurons express vmat2 mRNA from the earliest stages of postnatal development, and VMAT2 radioligand binding is similar between PN28 and adult animals in most forebrain regions, with the exception of the olfactory bulb (Hansson et al., 1998; Leroux-Nicollet et al., 1990).
Microdialysis studies revealed that adolescents had higher baseline extracellular serotonin in mPFC than adults, and tissue levels of 5-HIAA were similar between age groups in PFC, amygdala, and hippocampus. These data show that adolescent rats do not have lower baseline serotonergic tone than adults, and even have elevated baseline extracellular serotonin in some brain regions. Elevated baseline extracellular serotonin in adolescent mPFC could indicate age differences in serotonergic neuronal activity or autoreceptor function. Serotonergic neuron firing rates are similar between juvenile
(PN24) and adult rats, but no study has reported firing rates in adolescent rats
(Lanfumey and Jacobs, 1982). Age differences in serotonin autoreceptor function have not been investigated in adult and adolescent rats.
Overall, these data show that early adolescent rats have a similar density of forebrain serotonergic innervation as adults, but that these terminals have lower serotonin stores. These data do not support a developmental deficit in serotonergic tone in the adolescent forebrain similar to that associated with individual differences in aggression, impulsivity, and risk taking (Higley and Linnoila, 1997; Higley et al., 1996;
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Mehlman et al., 1994; Virkkunen et al., 1995). However, adolescent presynaptic serotonergic function may play a role in risk taking behavior by other mechanisms. A study of grivet monkeys showed that the ratio of 5-HIAA/HVA in CSF was at its lowest during adolescence (Fairbanks et al., 1999). This suggests that the ratio of serotonergic to dopaminergic tone is at its lowest during adolescence. Dopamine and serotonin are thought to act in opposition to each other, with dopamine signaling reinforcement and mediating approach behavior and serotonin signaling punishment and mediating avoidance (reviewed in Boureau and Dayan, 2011; Cools et al., 2011; Daw et al., 2002;
Dayan and Huys, 2009). A reduced 5-HIAA/HVA ratio fits with the skewed approach/avoidance model of adolescence and suggests that the serotonergic system is perhaps less able to counteract the dopaminergic system during adolescence (reviewed in Ernst et al., 2006).
The elevated baseline extracellular serotonin seen in the adolescent mPFC may also contribute to adolescent risk taking behavior. While global serotonin depletion increases impulsive behavior, several studies have found a positive correlation between mPFC extracellular serotonin or serotonin turnover and impulsivity in a behavioral inhibition task (Dalley et al., 2002a; Dalley et al., 2002b; Harrison et al., 1997, 1999;
Puumala and Sirvio, 1998). This reflects the complex region-specific regulation of behavior by serotonin (reviewed in Dalley et al., 2008). The study showing an association between frontal cortex serotonin turnover and impulsivity also found trends
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for higher serotonin turnover in the nucleus accumbens and striatum of impulsive rats
(Puumala and Sirvio, 1998). Given our findings in cortex, amygdala, and hippocampus, adolescent rats may also have higher serotonin turnover in these brain regions. The mechanism underlying this association is unknown, but it has been shown that antagonizing 5-HT2A receptors in mPFC reduces impulsivity in the same behavioral task
(Winstanley et al., 2003). It may be the case that higher tonic stimulation of 5-HT2A in the mPFC can result in increased impulsivity. In summary, adolescent serotonergic tone could contribute to risk taking behavior by either its lower ratio to dopaminergic tone compared to adults or by regional differences such as in the mPFC.
6.5 Neurochemical Effects of Indirect Serotonin Agonists
Adolescent rats exhibited lower increases in mPFC extracellular serotonin than adults in response to all three doses of the serotonin releasing drug fenfluramine and to local infusion of 100 mM KCl. In contrast, systemic and local administration of fluoxetine produced similar increases in mPFC extracellular serotonin in each age group.
The greater serotonergic response to releasing drugs in adults shows that extracellular serotonin could contribute to the greater behaviorally inhibiting effects of these drugs in adults, as well as the increased aversive effects that have been observed for drugs of abuse that release serotonin such as amphetamine (Infurna and Spear, 1979; reviewed in
Sulzer et al., 2005). However, the comparable serotonergic response to fluoxetine in adolescents, who experienced lower behaviorally inhibiting effects of this drug relative
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to adults, shows that extracellular serotonin does not completely explain why indirect serotonin agonists are less behaviorally inhibiting in adolescents. Either serotonin receptor function or a part of the neural circuit mediating behavioral inhibition in adolescents must be immature.
Lower tissue serotonin stores in adolescents may explain why fenfluramine and potassium infusion produced smaller increases in extracellular serotonin compared to adults. Serotonin releasing drugs such as fenfluramine release vesicular serotonin, which is then reverse transported through SERT (Berger et al., 1992; Rudnick and Wall,
1992; Schuldiner et al., 1993; reviewed in Sulzer et al., 2005). This effect is not limited by neuronal firing, but may be limited by the size of vesicular serotonin stores, as releasing drugs are capable of depleting the releasable pool of vesicles (Carboni and Di Chiara,
1989; John and Jones, 2007; Jones et al., 1998). Potassium infusion causes serotonin release by depolarizing axon terminals within diffusion distance of the probe.
Potassium depolarization stimulates neurons strongly enough to recruit storage vesicles, and may also be limited by vesicular serotonin stores (reviewed in Rizzoli and Betz,
2005). The higher tissue serotonin content in adults, but similar innervation density between adults and adolescents suggest that adults have greater vesicular serotonin stores than adolescents, which may explain why fenfluramine and potassium induced greater serotonin release in adults.
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In contrast to releasing drugs, the primary factor affecting the increase in extracellular serotonin after treatment with uptake inhibitors is neuronal firing, which remains stable from early postnatal development to adulthood (Gartside et al., 1995;
Lanfumey and Jacobs, 1982). Serotonin 5-HT1A autoreceptors are a major factor affecting extracellular serotonin after treatment with uptake inhibitors because they inhibit neuronal firing as extracellular serotonin rises (Gartside et al., 1995; Hjorth, 1993;
Romero et al., 1996; Sprouse and Aghajanian, 1987). Serotonin uptake inhibitors cause an increase in extracellular serotonin in the raphe nuclei that activates 5-HT1A autoreceptors and limits increases in extracellular serotonin at target sites (Adell and
Artigas, 1991; Rutter et al., 1995). Terminal 5-HT1B autoreceptors also suppress the effects of uptake inhibitors, and this effect may be more pronounced in hippocampus than in cortex (Hervas et al., 2000; Malagie et al., 2001). Local infusion of fluoxetine into the mPFC bypasses the suppressive effect of 5-HT1A autoreceptors in the raphe nuclei, but not terminal autoreceptors. The lack of 5-HT1A autoreceptor influence was reflected in the much greater increase in extracellular serotonin after local compared to systemic fluoxetine administration. The similar increases in extracellular serotonin in each age group seen with local infusion may indicate somewhat tighter 5-HT1A regulation of neuronal activity in adults, given that adolescents were able to achieve higher extracellular serotonin levels when fluoxetine was administered systemically. To our
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knowledge, no study has compared 5-HT1A autoreceptor function in adolescents and adults, so this remains a possibility.
6.6 Behavioral Effects of 5-HT1A and 5-HT2 Receptor Agonists
Adolescents experienced similar anxiogenic effects as adults in response to the 5-
HT2 agonist mCPP. mCPP has similar affinity for the 5-HT2A, 5-HT2B, and 5-HT2C receptors, but the 5-HT2C receptor may be primarily responsible for its anxiogenic effects
(Baxter et al., 1995; Campbell and Merchant, 2003; Kennett et al., 1989). The 5-HT2C receptor has been well studied in tests for anxiety-like behavior, and stimulation of the receptor elicits increases in anxiety-like behavior across multiple tests (Millan, 2003).
Antagonists of the 5-HT2C receptor are able to block the anxiogenic effects of acute fluoxetine treatment (Bagdy et al., 2001; Burghardt et al., 2007; Dekeyne et al., 2000;
Vicente and Zangrossi, 2011). Similarly, 5-HT2C stimulation produces behavioral inhibition in impulsivity tests (Fletcher et al., 2007; Winstanley et al., 2004). 5-HT2C has been shown to act in the basolateral and central amygdala to regulate anxiety-like behavior, and in the nucleus accumbens in regulating impulsivity (Campbell and
Merchant, 2003; Christianson et al., 2010; Overstreet et al., 2006; Robinson et al., 2008;
Vicente and Zangrossi, 2011). The similar anxiogenic effects of mCPP in each age group suggests that 5-HT2C function and its modulation of neural circuits mediating anxiety- like behavior are mature by adolescence.
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In contrast, adolescent rats were less sensitive than adults to the anxiogenic effects of systemic administration of the 5-HT1A agonist 8-OH DPAT, suggesting that either 5-HT1A receptor expression, 5-HT1A receptor function, or the neural circuits modulated by 5-HT1A are immature during adolescence. It is likely that postsynaptic 5-
HT1A receptors are responsible for the acute anxiogenic effects of 8-OH DPAT, as infusion of 5-HT1A agonists into the dorsal and median raphe has been repeatedly shown to produce anxiolytic effects (Cheeta et al., 2000; File and Gonzalez, 1996; File et al., 1996;
Graeff et al., 1996b; Hogg et al., 1994; reviewed in Engin and Treit, 2008). Postsynaptic stimulation of 5-HT1A receptors in the hippocampus, medial prefrontal cortex, and basolateral amygdala increases anxiety, though these effects vary by behavior test (File et al., 1996; Gonzalez et al., 1996; Solati et al., 2011; reviewed in Engin and Treit, 2008).
Lower adolescent sensitivity to the anxiogenic effects of both fluoxetine and 8-OH DPAT could mean that stimulation of an immature population of postsynaptic 5-HT1A receptors mediates some of fluoxetine’s age-dependent behavioral effects, or that fluoxetine and 8-OH DPAT act on similar immature circuits to mediate anxiety-like behavior.
We observed no significant age differences in 5-HT1A receptor levels by 3H-8-OH
DPAT binding in PFC, amygdala, and hippocampus, though higher 5-HT1A binding has been previously reported in adolescent cortex and hippocampus (Slotkin et al., 2008; Xu et al., 2002). Several rat lines with elevated anxiety-like behavior or depressive behavior
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exhibit 20-30% decreases or increases 3H-8-OH DPAT binding in cortex and hippocampus, so it is possible that small differences in 3H-8-OH DPAT binding not detected in the present study could be relevant for behavior (Keck et al., 2005; Knapp et al., 1998; Nishi et al., 2009). The neural connections between prefrontal cortex and basolateral amygdala are also known to be immature during adolescence, raising the alternate possibility that 5-HT1A signaling in higher brain regions such as prefrontal cortex or hippocampus does not increase anxiety-like behavior in adolescents due to inefficient connections with downstream brain regions (Cressman et al., 2010;
Cunningham et al., 2002).
Site-specific injection of 8-OH DPAT into the mPFC, basolateral amygdala, and ventral hippocampus failed to produce anxiogenic effects in adults in the LD test.
Infusion of 8-OH DPAT into mPFC and ventral hippocampus also failed to produce anxiogenic effects in adolescents, though infusion into the basolateral amygdala produced an anxiogenic trend. It is possible that 5-HT1A activation in other brain regions is more critical for behavior in this test. For example, infusion of 8-OH DPAT into the lateral septum also produces anxiety-like behavior in the social interaction test. (Cheeta et al., 2000). The age-dependent effects observed in the basolateral amygdala show that interrogating individual nodes of a mature versus an immature circuit may yield results that are difficult to interpret. Another possibility is that the greater anxiogenic effects of systemic 8-OH DPAT in adults may be due to 5-HT1A activation across a distributed
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network of brain regions. Interactions with other neurotransmitter systems could also be important. 8-OH DPAT disinhibits activity of the locus coeruleus and thus increases release of norepinephrine, which could contribute to its acute anxiogenic effects (Hajos et al., 1999). This could contribute to the age differences in 8-OH DPAT effects, as the noradrenergic system matures even later than the serotonin system (Murrin et al., 2007).
6.7 Circuit-Level Effects of Fluoxetine, 8-OH DPAT, and mCPP
Fluoxetine and 8-OH DPAT produced greater activation of brain regions associated with behavioral inhibition and anxiety-like behavior in adult rats compared to adolescents. These results are consistent with their greater behavioral effects in adults, and may highlight critical brain regions that mediate the age differences in behavior.
Fluoxetine produced increases in c-Fos immunoreactive nuclei in the central and medial amygdala, lateral bed nucleus of the stria terminalis, and paraventricular nucleus of the hypothalamus. These findings are consistent with previous reports of the effects of fluoxetine and other SSRIs on c-fos mRNA or c-Fos protein expression (Beck, 1995;
Jongsma et al., 2002; Miyata et al., 2005; Morelli, 1999; Sumner et al., 2004; Torres et al.,
1998; Veening et al., 1998). The increase in c-Fos expression was greater across the extended amygdala in adult rats compared to adolescents, indicating greater activation of these brain regions. The extended amygdala includes both the central and medial nuclei of the amygdala and the bed nucleus of the stria terminalis (Alheid and Heimer,
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1988). Regions of the extended amygdala are involved in expression of anxiety-like behavior, fear, and defensive responses in a variety of experimental paradigms, including conditioned fear, exposure to predator cues, tests of the startle reflex, and unconditioned tests of anxiety-like behavior (reviewed in Ciocchi et al., 2010; Davis et al., 2010; Ehrlich et al., 2009; Gross and Canteras, 2012; Walker and Davis, 1997). Lesion and inactivation studies have shown the central amygdala to be a critical brain region for expression of anxiety-like behavior or fear in numerous paradigms (reviewed in
Ciocchi et al., 2010; Ehrlich et al., 2009; Gross and Canteras, 2012; Walker and Davis,
1997). The medial amygdala is involved in fear and anxiety-like behavior in response to predators or aggressive members of the same species (reviewed in Gross and Canteras,
2012). The lateral subdivision of the bed nucleus of the stria terminalis is critical for anxiety-like behavior under conditions of uncertainty (reviewed in Davis et al., 2010;
Walker and Davis, 1997). These brain regions are activated in animals performing anxiety tests similar to the LD test such as the open field, and activation of these regions has been associated with increased anxiety-like behavior (Bechtholt et al., 2008; Duncan et al., 1996; Emmert and Herman, 1999; Hale et al., 2008; Salome et al., 2004; Silveira et al., 1993; Silveira et al., 2001). Fluoxetine could therefore be more anxiogenic to adult rats than adolescents due to greater activation of the extended amygdala.
Animals treated with 8-OH DPAT exhibited increases in c-Fos immunoreactive nuclei in the lateral orbital cortex, central amygdala, and lateral bed nucleus of the stria
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terminalis, which is generally consistent with the pattern of activation previously reported for 8-OH DPAT and other 5-HT1A agonists (Compaan et al., 1996; Hajos et al.,
1999; Tilakaratne and Friedman, 1996). We observed a large increase in c-Fos positive nuclei in the lateral orbital cortex (also known as orbitofrontal cortex) of adult rats, while adolescents showed no such increase. This age difference in activation of orbital cortex could contribute to the age differences in anxiety-like behavior after systemic 8-OH
DPAT, as the lateral orbital cortex is associated with anxiety-like behavior, behavioral inhibition, and impulsivity. Lesions of the lateral orbital cortex decrease anxiety-like behavior and increase impulsivity in delay discounting tasks (Fox et al., 2010; Kalin et al., 2007; Mar et al., 2011; Rudebeck et al., 2007). The orbitofrontal cortex is also important for decision making and cognitive function, and dysfunction of the orbitofrontal cortex may be important in development of drug addiction (Koob and
Volkow, 2010; Winstanley, 2007). Lower 5-HT1A-mediated activation of lateral orbital cortex in adolescents may therefore reveal immaturity of this brain region or its inputs from other brain regions that could be important for adolescent risk taking behavior and vulnerability to drug abuse.
Unlike fluoxetine, 8-OH DPAT did not produce greater activation of the entire extended amygdala in adults relative to adolescents. Both age groups experienced similar activation of the lateral BNST, but the central amygdala was more activated in adults than in adolescents. Greater central amygdala activation in adults could also
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contribute to greater anxiety-like behavior induced by 8-OH DPAT. Studies of the roles of the BNST and central amygdala in anxiety-like behavior using the fear-potentiated startle paradigm have revealed different contributions of these brain regions to behavior. The central amygdala mediates both fear responses to immediate aversive cues and anxiety-like behavior under conditions of uncertainty, while the BNST is only involved in anxiety-like behavior under conditions of uncertainty (reviewed in Ciocchi et al., 2010; Davis et al., 2010; Gozzi et al., 2010; Walker and Davis, 1997). The LD test likely involves both types of anxiety-like behavior. The animal is initially placed in the dark compartment and must decide whether to venture into the uncertain conditions of the light compartment. Once in the light compartment and directly exposed to the aversive bright light and open space, the animal has the opportunity to escape back into the dark compartment. The time spent in the light compartment includes both avoidance and escape behavior, while the latency to emerge should only reflect avoidance behavior as the animal has not yet entered the aversive area of the box. Given their roles in these two types of behavior, the greater activation by 8-OH DPAT of central amygdala, but not BNST, in adult rats may explain why there was a clear age difference in time spent in the light after 8-OH DPAT treatment, while latency to emerge was more variable.
We observed no significant induction of c-Fos expression in animals treated with the 5-HT2 agonist mCPP (1 mg/kg). Studies of mCPP-induced c-Fos expression have
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shown increases in c-Fos positive nuclei in the medial prefrontal cortex, orbitofrontal cortex, paraventricular and lateral hypothalamus, central amygdala, and BNST
(Campbell and Merchant, 2003; Singewald et al., 2003; Stark et al., 2006). While these studies used a similar time course between injection and tissue collection (1.5-2 hours), larger doses of mCPP were used (3-5 mg/kg) (Singewald et al., 2003; Stark et al., 2006).
These data show that tests for anxiety-like behavior may be more sensitive to anxiogenic drug effects than c-Fos experiments conducted in the home cage.
The greater percent increase in c-Fos in adult rats after fluoxetine or 8-OH DPAT treatment was due to several patterns of cell counts. In some brain regions such as lateral orbital cortex after 8-OH DPAT or lateral BNST after fluoxetine, the two age groups started from a similar baseline and the drugs produced larger numbers of cells in adult rats. In other regions such as the central and medial amygdala, adolescent rats had higher baseline cell counts that contributed to the lower percent increases in c-Fos positive cells. Higher baseline c-fos mRNA has been observed in adolescent rats in numerous studies (Cao et al., 2007; Caster and Kuhn, 2009; Dao et al., 2011; Shram et al.,
2007). We therefore reasoned that the change in c-Fos between control and treated animals would be more important to behavior than the absolute number of cells. The higher adolescent baselines created concern over a ceiling effect in this age group, but the equivalent cortical activation in each age group following medial forebrain bundle stimulation suggests that each age group is capable of similar maximal activation in
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response to a strong stimulus. This suggests that the lower percent increases in c-Fos positive cells observed in adolescent rats reflect a true lack of activation by fluoxetine and 8-OH DPAT of the extended amygdala and lateral orbital cortex.
The greater activation of adult lateral orbital cortex and central amygdala after 8-
OH DPAT and of the extended amygdala after fluoxetine may reflect immaturity of neural circuits similar to those found in imaging studies of human adolescents. Several studies show greater activation of orbitofrontal cortex in adults relative to adolescents when performing cognitive tasks and tests for behavioral inhibition (Monk et al., 2003;
Rubia et al., 2006; Tamm et al., 2002). Another study found greater overall activation of orbitofrontal cortex in children and adolescents than adults, but the pattern of activity was more diffuse, suggesting immature neural pathways (Galvan et al., 2006). Human imaging studies also show age differences in amygdala activation. Adolescents had lower amygdala activation than adults when losing money in a gambling task, but typically have greater activation of the amygdala in response to fearful faces (Ernst et al.,
2005; Guyer et al., 2008; Hare et al., 2008; Monk et al., 2003). These task-dependent age differences in amygdala activation may be due to differences in neural systems responding to rewarding versus social stimuli.
Several facets of using c-Fos as a marker of neuronal activation should be kept in mind when interpreting these data. First, animals in all c-Fos experiments were kept in the home cage throughout testing to allow investigation of drug effects without the
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confounding influences of behavior on c-Fos expression. Given the known age differences in behavior following fluoxetine or 8-OH DPAT, any age differences in c-Fos expression in animals treated with these drugs after behavior testing could be due to age differences in drug effects or differential behavior in the LD test. Performance of behavior tests similar to the LD activates c-Fos expression in rats and there is some overlap between the brain regions activated by the tests and those activated by fluoxetine and 8-OH DPAT (Bechtholt et al., 2008; Duncan et al., 1996; Emmert and
Herman, 1999; Hale et al., 2008; Salome et al., 2004; Silveira et al., 1993; Silveira et al.,
2001). It would be impossible to distinguish whether age differences in behavior or drug effects lead to age differences in c-Fos expression, so animals were kept in the home cage after drug treatment. The greater activation of c-Fos in adult rats suggests that fluoxetine and 8-OH DPAT activate brain regions associated with behavior inhibition independently of an aversive environment. It is possible that even greater age differences would be observed in animals treated with these drugs and placed in the LD test. Another factor in c-Fos expression is that increased c-Fos in a particular brain region may not be due to direct pharmacologic effects of fluoxetine or 8-OH DPAT in that brain region, but could be due to actions on neurons projecting to the activated region (Compaan et al., 1996; Hajos et al., 1999). This is especially true for 8-OH DPAT due to the direct inhibitory effects of the 5-HT1A receptor. Instead, activation of c-Fos could also reflect disinhibition of cells either by actions on local interneurons or distant
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sites that project to the activated brain region. Nonetheless, c-Fos provides a useful tool to compare which brain regions were activated in each age group.
6.8 Conclusions
We took a circuit-based approach in considering the mechanism behind adolescent insensitivity to the behaviorally inhibiting effect of indirect serotonergic agonists and 8-OH DPAT. We investigated three hypotheses that could explain the lesser behavioral response of adolescents to indirect serotonergic agonists. These hypotheses were that: 1.) lower presynaptic serotonergic function, 2.) lower serotonin receptor expression or function, or 3.) immature neural circuits modulated by serotonin could explain the lower adolescent sensitivity to the behaviorally inhibiting effects of indirect serotonergic agonists. The circuit we considered in designing experiments to test these hypotheses is illustrated below. The diagram features a simplified circuit based on several tests for anxiety-like behavior with well-known circuitry, as well as c-
Fos experiments conducted in animals after performance of unconditioned anxiety tests
(Bechtholt et al., 2008; Davis and Shi, 1999; Davis et al., 2010; Hale et al., 2008; LeDoux,
2000; Silveira et al., 1993). Serotonin projects to all of the regions featured in this circuit, and a variety of serotonin receptor subtypes are expressed within these regions (Barnes and Sharp, 1999; Steinbusch, 1981). Studies of serotonin receptor subtype modulation of anxiety-like behavior and behavioral inhibition suggest that stimulation of 5-HT2C receptors in the basolateral amygdala or 5-HT1A receptors in the prefrontal cortex,
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hippocampus, or basolateral amygdala may increase avoidance behavior in anxiety tests
(Campbell and Merchant, 2003; Christianson et al., 2010; File et al., 1996; Gonzalez et al.,
1996; Solati et al., 2011).
Figure 36: Neural Circuits Involved in Serotonergic Modulation of Anxiety- like Behavior
A simplified circuit describing the mechanism of serotonergic modulation of anxiety-like behavior and behavioral inhibition. Serotonergic innervation to the forebrain is depicted by the gray neuron. All brain regions shown in the circuit receive serotonergic innervation from the dorsal and/or median raphe nuclei. PFC=prefrontal cortex, BNST=bed nucleus of the stria terminalis
The first hypothesis we investigated was that the presynaptic side of the above system could be immature, resulting in lower extracellular serotonin after treatment with indirect agonists compared to adults. The fenfluramine and fluoxetine microdialysis experiments show that a lower increase in extracellular serotonin may
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partially explain the lower adolescent behavioral response to serotonin-releasing drugs, but extracellular serotonin does not explain the lower sensitivity to fluoxetine
Another possibility is that adolescents could have immature serotonin receptor expression or function. Studies of serotonin receptor ontogeny generally show mature expression and function by adolescence, though some studies have found age differences in 5-HT1A receptor expression and modulation of cyclase activity (Daval et al., 1987; Garcia-Alcocer et al., 2006; Pranzatelli and Galvan, 1994; Slotkin et al., 2008;
Vizuete et al., 1997; Waeber et al., 1996; Waeber et al., 1994; Xu et al., 2002). Treatment with systemic mCPP and 8-OH DPAT revealed no significant age differences in 5-HT2 mediated anxiety-like behavior, but adolescent rats were less sensitive to 5-HT1A mediated anxiogenic effects. We did not detect a difference in 5-HT1A receptor binding between adolescents and adults, though contribution of potentially higher adolescent 5-
HT1A binding in adolescent cannot be ruled out based on results with selectively bred lines of animals (Keck et al., 2005; Knapp et al., 1998; Nishi et al., 2009). We were also unable to replicate the effects of systemic 8-OH DPAT by infusion into medial prefrontal cortex, basolateral amygdala, or ventral hippocampus. These data do not support the hypothesis that immature 5-HT1A function in prefrontal cortex, hippocampus, or amygdala is responsible for adolescent insensitivity to fluoxetine and 8-OH DPAT.
Neural circuits between brain regions mediating anxiety-like behavior are immature during adolescence and could explain the lower behavioral inhibition in
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adolescents treated with indirect serotonin agonists. Numerous human and animal studies show immature connectivity between prefrontal cortex and limbic brain regions
(Cressman et al., 2010; Cunningham et al., 2002; reviewed in Casey et al., 2008; Ernst and
Fudge, 2009; Ernst et al., 2006). It could therefore be possible that serotonin is unable to mediate behavioral inhibition in adolescents as effectively as in adults due to inefficient signaling within downstream neural circuits. These immature neural circuits could be modulated by 5-HT1A but not 5-HT2 receptors, which would explain adolescent insensitivity to 8-OH DPAT. Immature prefrontal cortex to amygdala connections could fit this criterion, as mCPP is known to exert anxiogenic effects via 5-HT2C signaling in the amygdala, while 5-HT1A signaling is more prevalent in higher brain regions such as cortex and hippocampus (Campbell and Merchant, 2003; File et al., 1996; Gonzalez et al.,
1996; Hall et al., 1997; Khawaja, 1995; Kung et al., 1995; Miquel et al., 1992; Radja et al.,
1991; Solati et al., 2011; Wright et al., 1995).
The following diagram illustrates the hypothesis that immature prefrontal cortical to amygdala connections could contribute to the age differences in behavioral effects of serotonergic drugs.
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Figure 37: Immature Prefrontal Cortical Circuits in Adolescents and Consequences for Behavior Illustration of potential contribution of immature adolescent neural circuits between prefrontal cortex and amygdala to lack of behavioral inhibiton. Lower top down regulation of basolateral amygdala from prefrontal cortex could result in less activation of central amygdala and subsequent changes in behavior. Gray brain regions indicate parts of circuit hypothesized to be less active in adolescents relative to adults under conditions of behavioral inhibition.
A final possibility for explaining lower serotonin-mediated behavioral inhibition in adolescents is that serotonergic behavioral inhibition could be outweighed by the hyperactive adolescent reward/approach system. This concept is based upon Ernst et al’s triadic model of adolescence, in which a hyperactive approach system overrides a potentially hypoactive avoidance system (reviewed in Ernst et al., 2006). Behavior in the
LD, EPM, and NIH tests consists of an approach avoidance conflict that pits the rodent- typical approach drives to explore novel areas or consume palatable food against the rodent avoidance drives to stay out of brightly lit, open, and elevated areas (File et al.,
2004). Data from human and animal studies suggests a hyperactive approach drive 173
during adolescence, and adolescent rats have greater novelty stimulated locomotion, novelty preference, and novel object interaction than adults (Adriani et al., 1998;
Douglas et al., 2003; Stansfield and Kirstein, 2006; reviewed in Ernst et al., 2006). The literature does not show consistent age differences in tests for anxiety-like behavior, but our own finding of faster latency to emerge in adolescents in the LD test supports the hypothesis of a hyperactive adolescent approach drive (Andrade et al., 2003; Hascoet et al., 1999; Hefner and Holmes, 2007; Imhof et al., 1993; Lynn and Brown, 2010; Macri,
2002; Slawecki, 2005). This hypothesis is not mutually exclusive with our proposal of immature neural circuits mediating lower serotonergic behavioral inhibition in adolescents. Instead, the hyperactive approach drive of adolescents may work in combination with less effective serotonergic behavioral inhibition to create age differences in behavior after treatment with indirect serotonergic agonists.
Age differences in metabolism of the indirect serotonin agonists used in behavior testing are unlikely to explain the age differences in behavioral responses to indirect serotonin agonists. We know of no study comparing fenfluramine metabolism in adults and adolescents. MDMA has similar pharmacokinetics in plasma of adolescent (PN35) and adult (PN60) rats, and both age groups have similar levels of MDMA and its metabolite MDA 30 minutes after a subcutaneous injection (Meyer et al., 2008).
Adolescent rats appear to metabolize fluoxetine more quickly than adults, and have lower plasma fluoxetine and norfluoxetine levels than adults shortly after chronic
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fluoxetine administration (Homberg et al., 2011). However, our microdialysis data show that fluoxetine has similar effects on extracellular serotonin in each age group, which would produce comparable anxiety-like behavior in adults and adolescents if adolescent downstream neural circuits were mature.
6.9 Significance
Adolescence is the final period of postnatal development that culminates in the attainment of physical, cognitive, and social attributes of adulthood (reviewed in Casey et al., 2008; Sisk and Foster, 2004; Spear, 2000). Changes in brain circuits and neurochemistry and the related changes in behavior are critical in psychological and social maturation, but also lead to major causes of adolescent injury and mortality
(reviewed in Casey et al., 2008; Eaton et al., 2012; Spear, 2000). In the United States, death rates fall to very low levels after infancy and remain low throughout childhood
(Minino et al., 2011). Death rates begin to climb as individuals enter early adolescence and maintain a slow increase before rapidly climbing much later in life (Minino et al.,
2011). In older populations heart disease and cancer are major causes of death, but these make up only a small portion of mortality in younger people (Minino and Murphy,
2012; Minino et al., 2011). Instead, the increase in death rates during adolescence is driven by car accidents and other accidents, homicide, and suicide (Eaton et al., 2012).
Other major causes of adolescent injury and illness include experimentation with drugs and unsafe sexual behavior (reviewed in Arnett, 1992; Eaton et al., 2012). It therefore
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appears that, unlike other age groups, risk taking behavior, impulsivity, and lack of behavioral inhibition underlie most of the primary causes of adolescent injury and mortality.
Serotonin is important for mediating behavioral inhibition in response to threat, and exposure to stressful environments increases forebrain extracellular serotonin
(Crockett et al., 2009; Matsuo et al., 1996; Rex et al., 1999, 2005; Soubrie, 1986; Wright et al., 1992). It is not known if there are age differences between adult and adolescent rats in the effects of aversive or threatening environments on extracellular serotonin.
However, the fluoxetine behavior and microdialysis experiments show that even if adolescent rats had a comparable increase in extracellular serotonin as adults, it would be less effective at inhibiting behavior. The PCPA EPM experiment showed that serotonin does modulate some types of anxiety-like behavior in adolescents, but lacked power to investigate age differences in the magnitude of this modulation. The experiments with indirect serotonergic agonists showed that serotonin is less effective at inhibiting behavior in adolescents than adults. The immature postsynaptic effects of serotonin may therefore contribute to adolescent risk taking behavior.
The lower sensitivity to serotonin-mediated behavioral inhibition observed in adolescents may have particular relevance to experimentation with drugs of abuse during adolescence. Serotonin contributes to the aversive effects of psychostimulants such as cocaine, amphetamine, methamphetamine, and MDMA, and adolescents are less
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sensitive to the aversive effects of these drugs (Ettenberg and Bernardi, 2006, 2007;
Ettenberg et al., 2011; Infurna and Spear, 1979; Jones et al., 2009; Jones et al., 2010; Rocha et al., 2002; Schramm-Sapyta et al., 2006; Serafine and Riley, 2010). The results with indirect serotonergic agonists in tests of anxiety-like behavior suggest that serotonin may contribute to this lack of aversion in adolescents. Based on microdialysis experiments, adolescent insensitivity to these aversive drug effects could be partially due to smaller increases in extracellular serotonin for releasing drugs like amphetamine.
Immature postsynaptic effects on neural circuits in cortex and amygdala may contribute both for releasing drugs and uptake inhibitors such as cocaine. These reduced aversive effects of psychostimulants in adolescents may be particularly problematic given evidence of the enhanced rewarding effects of these drugs in adolescents (reviewed in
Schramm-Sapyta et al., 2009).
Reduced serotonergically mediated behavioral inhibition in adolescents may also be relevant to the problem of adolescent suicide. Suicide rates increase between childhood and adolescence, and suicide is one of the top four causes of death in United
States adolescents (Bertolote and Fleischmann, 2002; Eaton et al., 2012; Eaton et al., 2010;
Patton et al., 2009). Lower central serotonergic function may be associated with suicide, as lower prefrontal cortex serotonin transporter binding, lower 5-HIAA levels in cerebrospinal fluid or hindbrain, and lower prolactin or cortisol response to fenfluramine are all associated with suicide or suicide attempts (Arango et al., 1995;
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Asberg et al., 1976; Bourne et al., 1968; Cleare et al., 1996; Keilp et al., 2010; Mann, 2003;
Nordstrom et al., 1994; Purselle and Nemeroff, 2003; Stanley et al., 1982). Increased binding to cortical 5-HT1A and 5-HT2A receptors has also been found in the brains of suicide victims, but this may reflect receptor upregulation in response to low serotonergic tone (Arango et al., 1995; Stanley et al., 1982; reviewed in Mann, 2003).
Expression of the S allele of the well studied serotonin transporter 5-HTTLPR polymorphism is also associated with suicide (Anguelova et al., 2003; Bondy et al., 2006;
Purselle and Nemeroff, 2003). These data collectively suggest that increased serotonergic tone protects against suicide. Adolescent insensitivity to serotonergically mediated behavioral inhibition suggests that some of serotonin’s behavioral effects are immature during adolescence, which could negate this protective effect. This lack of a protective effect may also contribute to the problem of increased suicidality in adolescents treated with SSRIs (Barbui et al., 2009; Hammad et al., 2006; Schneeweiss et al., 2010).
The goal of this project was to determine if immaturity of the serotonergic system could contribute to adolescent risk taking behavior. This investigation led to the novel finding that adolescent male rats are less sensitive than adults to serotonergically mediated behavioral inhibition. As discussed above, this may have broad implications for adolescent risk taking behavior, drug abuse, and suicidality. We used rodent models of anxiety-like behavior to assess age differences in serotonergic behavioral inhibition
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between adult and adolescent rats because these models provide several advantages in addressing this question. The serotonergic system is well conserved between rodents and humans, with similar innervation patterns and receptor subtypes. Serotonergic drug treatments have similar effects in human and animal models of anxiety-like behavior (Graeff et al., 1996a). Confounding factors in studying human adults and adolescents such as differences in life experience or incentive value of monetary rewards can be avoided in rodent models. This provides further support for the neurobiological underpinnings of adolescent risk taking, and argues against the concept of adolescent risk taking as a social phenomenon specific to humans. Finally, rodent models allow more detailed mechanistic investigation of the neural mechanisms of behavior, that have allowed us to rule out presynaptic serotonergic function as the primary cause of age differences in behavioral responses to indirect serotonin agonists. The microdialysis studies conducted in this dissertation are the only published comparisons of extracellular serotonin between early adolescents and adult rats. These studies and the other experiments characterizing pre- and postsynaptic serotonergic function suggest that adolescent insensitivity to serotonin-mediated behavioral inhibition may not be due only to immaturity of the serotonergic system itself, but also to immaturity of neural circuits mediating behavioral inhibition.
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6.10 Future Directions
This project was designed to assess developmental differences between adult and adolescent rats in serotonergic modulation of behavioral inhibition using tests for anxiety-like behavior. Another major goal was to compare serotonergic function between age groups at the presynaptic, serotonin receptor, and neural circuit levels.
While the data shown above provide insight into these problems, important questions remain for developmental differences in serotonergic function at all three levels.
More research is needed to define how age differences in presynaptic serotonergic function affect baseline performance in tests for anxiety-like behavior. Our
PCPA data across three behavioral tests show that serotonergic signaling plays some role in adolescent anxiety-like behavior, but that these effects are test dependent. One way to approach how serotonin affects anxiety-like behavior would be to measure extracellular serotonin levels during performance of the test. Microdialysis in prefrontal cortex, amygdala, or hippocampus of adult and adolescent rats could be helpful in determining whether there are age differences in activation of serotonergic neurons by these tasks. These experiments could also include fluoxetine-treated groups to determine if there is an interaction between the behavior tests and indirect serotonin agonists that could contribute to the greater behavioral effects of these drugs in adults.
This project focused on raphe inputs to the forebrain, but another interesting area for further study will be to compare developmental differences in modulation of
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serotonergic neuron firing by forebrain inputs to the raphe nuclei. The number of synaptic profiles in dorsal raphe at PN30 is lower than in adults, so it appears that modulation of serotonergic neuron firing by the forebrain could be immature during early adolescence (Lauder and Bloom, 1975). Prefrontal cortical inputs to the dorsal raphe may be a particularly interesting circuit for further study. Activation of 5-HT1A receptors in the prefrontal cortex activates long loop inhibitory feedback to the dorsal raphe nucleus, which could be important for developmental differences in the response to either aversive environments or indirect serotonin agonists (Ceci et al., 1994; Celada et al., 2001; Hajos et al., 1999). It seems plausible that these connections could be immature during adolescence given the known immaturity of prefrontal inputs to forebrain regions such as the amygdala (Cressman et al., 2010; Cunningham et al., 2002). Site specific injections of 5-HT1A agonists into the prefrontal cortex paired with electrophysiology in the raphe nuclei are one way to investigate this possibility.
Anterograde tracers could also be injected into mPFC to compare innervation of the raphe between age groups.
There is also more work to be done at the level of postsynaptic serotonin receptors. We compared age differences in the response to 5-HT1A and 5-HT2 agonists, but age differences in function of the other five families of serotonin receptors could also affect serotonergic modulation of behavioral inhibition. The 5-HT3 receptor is an interesting target for further research, as 5-HT3 signaling in the amygdala has been
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consistently shown to modulate anxiety-like behavior (reviewed in Engin and Treit,
2008). Behavioral testing of 5-HT3 agonists, and potentially 5-HT4, 5-HT6, and 5-HT7 agonists could provide a more complete assessment of the signaling pathways underlying the immature adolescent response to indirect serotonin agonists. It will also be important to investigate age differences in serotonin receptor coupling to G proteins.
There is some evidence of this for the 5-HT1A receptor, which could contribute to the developmental differences in behavioral effects of 8-OH DPAT (Xu et al., 2002).
Measuring the effects of 8-OH DPAT upon adenylyl cyclase activity could test this possibility.
Perhaps the most fruitful area for future investigation will be to compare circuit level responses to serotonergic or behavioral manipulations in adolescents and adults.
An important follow-up to the studies presented in this dissertation will be to determine if any brain regions have age-dependent responses to tests for anxiety-like behavior, and if serotonin agonists produce age-specific effects in the context of anxiety tests. This could be accomplished by exposing vehicle and serotonin agonist-treated animals to the
LD or EPM and measuring changes in c-Fos expression. A more sophisticated way to approach this problem would be the use of multi-electrode arrays. This approach has proven successful in elucidating the role of medial prefrontal and hippocampal connections in the EPM, and in assessing age differences in medial prefrontal and striatal function in operant paradigms (Adhikari et al., 2010, 2011; Sturman and
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Moghaddam, 2011b, 2012). This type of approach has the potential to reveal a wealth of information on age differences in circuit-level neuronal function in response to behavioral tests and drug treatment, and the interaction between these behavioral and pharmacologic challenges.
Single unit electrophysiological studies could also be very helpful in revealing important age differences in neuronal function. The prefrontal cortex and amygdala are particularly interesting regions for further study. Human imaging studies report less connectivity between these regions by fMRI, and rodent histological studies have reported anatomic immaturity of these connections, but few studies have investigated these circuits with electrophysiology (Cressman et al., 2010; Cunningham et al., 2002; reviewed in Casey et al., 2008). Electrophysiological studies could reveal which cell types in each region receive immature inputs, as well as the consequences of these inputs for local networks. For example, juvenile rats receive fewer inhibitory cortical inputs to basolateral amygdala neurons than adults, but the state of these inputs during adolescence is unknown (Rainnie, 1999; Smith and Dudek, 1996). A developmental study of the effects of serotonin in prefrontal cortical and amygdala neurons would also be helpful. The electrophysiological effects of serotonin in the cortex have been well studied in adults, and serotonin has quite different effects in the cortex of early postnatal rats compared to adults (Amargos-Bosch et al., 2004; Andrade, 2011; Araneda and
Andrade, 1991; Beique et al., 2004; Burnet et al., 1995; de Almeida and Mengod, 2007;
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Morilak et al., 1994; Santana et al., 2004). However, a direct comparison of adolescent and adult rats has not been reported in prefrontal cortex or any amygdala region. These types of experiments hold great potential for better understanding age differences in the effects of serotonin, as they could provide information about serotonin’s effects on certain cell types and allow construction of more specific models of age differences in circuit-level function than are currently possible.
A final direction for future research will be to expand beyond the serotonergic system. Serotonin does not act alone in the brain, and other neurotransmitter systems such as the dopaminergic and noradrenergic systems could also be important for adolescent risk taking. Developmental overexpression of dopamine receptors and peaks in dopaminergic neuron firing during adolescence could contribute to age differences in baseline behavior and drug response in tests for anxiety-like behavior (Andersen et al.,
2000; Brenhouse et al., 2008; Gelbard et al., 1989; Giorgi et al., 1987; McCutcheon and
Marinelli, 2009; Teicher et al., 1995). Noradrenergic innervation of the forebrain is immature until mid-adolescence, which could also contribute to developmental differences in behavior and drug response (reviewed in Murrin et al., 2007). The role of these systems in adolescent behavioral inhibition could be investigated with similar strategies as those used for the serotonergic system. Extracellular levels of norepinephrine and dopamine could be assessed by microdialysis during performance of anxiety tests to determine potential age differences in the response of these systems to
184
novel, aversive environments. Behavioral studies with direct and indirect agonists for these systems could provide a more global understanding of developmental differences in the neural systems mediating behavioral inhibition.
Adolescent rodents exhibit a lack of sensitivity to the aversive effects of drugs and other stimuli in a variety of paradigms, including conditioned taste aversion and conditioned fear (Anderson et al., 2010; Doremus et al., 2003; Holstein et al., 2011 2007;
Infurna and Spear, 1979; Pattwell et al., 2011; Philpot et al., 2003; Schramm-Sapyta et al.,
2007; Schramm-Sapyta et al., 2010; Schramm-Sapyta et al., 2006; Shram et al., 2006;
Wilmouth and Spear, 2004). Along with the insensitivity to the anxiogenic effects of serotonergic agonists described in this project, these data from a variety of behavioral paradigms and numerous independent laboratories may reflect immaturity of a common neural system in adolescents that could have important implications for risk taking behavior and drug responses. These proposed future experiments have the potential to reveal details about this important adolescent immaturity. This would be a significant advance in our understanding of adolescent neural function that could result in improved pharmacotherapy for this age group and better identification of vulnerable individuals for a variety of disorders such as affective and substance use disorders.
185
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Biography
Andrew Emmett Arrant
Education Duke University, Durham, NC 2007-2012 PhD, Pharmacology, December 2012 Thesis title “Why does risk-taking peak during adolescence?: contribution of neurochemical and circuit-level function to lower serotonin-mediated behavioral inhibition in adolescents
University of Louisiana at Monroe, Monroe, LA 2003-2007 B.S., Toxicology May 2007
Personal Born: Monroe, LA March 7, 1985
Fellowships Ruth L. Kirschstein National Research Service Award, 2011-2012 Project title: “Serotonergic Contribution to Adolescent Risk Taking”
Publications Walker, Q.D., Morris, S.E., Arrant, A.E., Nagel, J.M., Parylak, S., Zhou, G., Caster, J.M., and Kuhn, C.M. 2010. Dopamine uptake inhibitors but not dopamine releasers induce greater increases in motor behavior and extracellular dopamine in adolescent than adult male rats. JPET. 335(1):124-132.
Walker, Q.D., Johnson, M.L., Day, A.E., Arrant, A.E., Caster, J.M., and Kuhn, C.M. 2012. Individual differences in psychostimulant responses of female rats are associated with ovarian hormones and dopamine neuroanatomy. Neuropharmacology. 62(7):2266-2276.
Biskup, C.S., Sanchez, C.L., Arrant, A., Van Swearingen, A.E.D., Kuhn, C., and Zepf F.D. 2012. Effects of acute tryptophan depletion on brain serotonin function and concentrations of dopamine and norepinephrine in C57BL/6J and BALB/cJ mice. PLoS One. 7(5):e35916.
Arrant, A.E., Jemal, H., and Kuhn, C.M. 2012. Adolescent male rats are less sensitive than adults to the anxiogenic and serotonin-releasing effects of fenfluramine. Neuropharmacology. 65C:213-222.
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Abstracts Andrew E. Arrant, Q. David Walker, and Cynthia M. Kuhn, “The Effects of Amphetamine on Electrically Stimulated Dopamine Release in the Striatum of Adult and Adolescent Rats”, Society for Neuroscience Annual Meeting, 2008
Andrew E. Arrant and Cynthia M. Kuhn, “Divergent Effects of Serotonergic Drugs on Anxiety in Adult and Adolescent Rats”, Duke University Department of Pharmacology & Cancer Biology Annual Retreat, 2009
Andrew E. Arrant and Cynthia M. Kuhn, “Divergent Effects of Serotonin Depletion on Anxiety in Adult and Adolescent Rats”, Society for Neuroscience Annual Meeting, 2009
Andrew E. Arrant, Hikma Jemal, and Cynthia M. Kuhn, “Adolescent Rats Are Less Sensitive to the Anxiogenic and Serotonin Releasing Effects of Fenfluramine”, Society for Neuroscience Annual Meeting, 2010
Andrew E. Arrant and Cynthia M. Kuhn, “Development of the Serotonin System Influences the Behavioral Effects of SSRIs”, Duke University Department of Pharmacology & Cancer Biology Annual Retreat, 2011
Andrew E. Arrant and Cynthia M. Kuhn, “Dissociation of the Anxiogenic and Serotonergic Effects of Acute Fluoxetine Treatment in Adolescent Rats”, Society for Neuroscience Annual Meeting, 2011
Andrew E. Arrant and Cynthia M. Kuhn, “Immature Serotonergic Regulation of Anxiety-like Behavior in Adolescent Male Rats”, Experimental Biology/American Society for Pharmacology and Experimental Therapeutics Annual Meeting, 2012
Andrew E. Arrant and Cynthia M. Kuhn, “Reduced 5-HT1A Regulation of Anxiety-like Behavior in Adolescent Male Rats”, Society for Neuroscience Annual Meeting, 2012
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