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. Author manuscript; available in PMC: 2022 Oct 11.
Published in final edited form as: Behav Brain Res. 2021 Aug 10;415:113517. doi: 10.1016/j.bbr.2021.113517

Adolescent exposure to delta-9-tetrahydrocannabinol and ethanol heightens sensitivity to fear stimuli

Cora E Smiley a, Heyam K Saleh a, Katherine E Nimchuk a, Constanza Garcia-Keller a, Justin T Gass a
PMCID: PMC8404161  NIHMSID: NIHMS1732403  PMID: 34389427

Abstract

Cannabis use disorder (CUD) has doubled in prevalence over the past decade as a nation-wide trend toward legalization allows for increased drug accessibility. As a result, marijuana has become the most commonly used illicit drug in the United States particularly among the adolescent population. This is especially concerning since there is greater risk for the harmful side effects of drug use during this developmental period due to ongoing brain maturation. Increasing evidence indicates that CUD often occurs along with other debilitating conditions including both alcohol use disorder (AUD) and anxiety disorders such post-traumatic stress disorder (PTSD). Additionally, exposure to cannabis, alcohol, and stress can induce alterations in glutamate regulation and homeostasis in the prefrontal cortex (PFC) that may lead to impairments in neuronal functioning and cognition. Therefore, in order to study the relationship between drug exposure and the development of PTSD, these studies utilized rodent models to determine the impact of adolescent exposure to THC and ethanol on responses to fear stimuli during fear conditioning and used calcium imaging to measure glutamate activity in the prelimbic cortex during this behavioral paradigm. The results from these experiments indicate that adolescent exposure to THC and ethanol leads to enhanced sensitivity to fear stimuli both behaviorally and neuronally. Additionally, these effects were attenuated when animals were treated with the glutamatergic modulator N-acetylcysteine (NAC). In summary, these studies support the hypothesis that adolescent exposure to THC and ethanol leads to alterations in fear stimuli processing through glutamatergic reliant modifications in PFC signaling.

Keywords: Cannabis abuse, post-traumatic stress disorder, prelimbic cortex, N-acetylcysteine, glutamate, adolescence

1. Introduction

Cannabis use for recreational purposes has been steadily increasing as past year drug use has risen from 4.1% in 2002 to 15.9% in 2018 (SAMHSA 2018) with only ~10% of users citing drug use for exclusively medicinal reasons (National Academies of Sciences, 2017). Not only has cannabis become the most highly used illicit drug, concentrations of delta-9-tetrahydrocannabinol (THC), the psychoactive component of the drug, have increased as well (SAMHSA 2018, Stringfield and Torregrossa 2021a). In the 1990’s, the concentration of THC in common cannabis strains was around 2% while more recently the most popular strains acquired from Colorado dispensaries contain ~17–28% (Stuyt 2018, Lafaye et al. 2017, Licata et al. 2005). Importantly, while the THC concentration has sharply increased, the cannabidiol (CBD) concentration in cannabis has decreased from an average of 0.5% to ~0.09–0.2% (Stuyt 2018, Lafaye et al. 2017). This is especially concerning since the detrimental impact of cannabis has been shown to correlate with the amount of THC and increased CBD concentration can protect against these adverse effects (Niesink and vanLaar 2013, Lafaye et al. 2017). Almost all age groups have shown increases in past-month cannabis use (National Academies of Sciences, 2017), but the population in which both heavy and high intensity use is most prevalent is adolescents (Hasin et al. 2016). Surveys of high school students reveal that past year cannabis use in the 12–18 year old population has reached 37% (D’Amico et al. 2017) with a 5% rate of daily use (Schweinsburg et al. 2008). Chronic use of high-THC cannabis is associated with deficits in cognition, increased anxiety and psychosis, and a higher chance of developing CUD (Volkow et al. 2014, Lafaye et al. 2017, Fergusson and Boden 2008). While 9% of people who use cannabis will develop CUD, this rate increases to 17% in those who start using during adolescence (Volkow et al. 2014). Early cannabis use is also associated with further adverse consequences including comorbid psychiatric disorder, reduced life satisfaction, and cognitive impairment (Fergusson and Boden 2008, Rey et al. 2002). These effects are associated with drug-induced disruption of ongoing brain development, including deficits in the maturation of synaptic connectivity and in the refinement of the endocannabinoid system, processes that continue throughout mid- to late-adolescence (Tortoriello et al. 2014, Volkow et al. 2014, Berghuis et al. 2007, Keimpema et al 2011). Therefore, further research into the impact of cannabis exposure on the adolescent brain is critical since high rates of cannabis use have been increasingly observed amongst this at-risk population.

While cannabis is one of the most commonly used illicit substances, CUD has only been recently included as a diagnosis in the DSM-5 (Brezing and Levin 2018, Panlilio and Justinova 2018). CUD alone is associated with adverse long-term consequences, but this condition is also highly comorbid with other substance use and psychiatric disorders that lead to further impairments in brain function and cognition. Those with CUD are 10-times more likely to develop AUD and 6-times more likely to develop PTSD than those without CUD (Hasin et al. 2015, Hasin et al. 2016). Both cannabis and alcohol use are highly prevalent in patients with PTSD (Hasin et al. 2016), and evidence from clinical studies has found that CUD rates are especially high among veterans who have developed PTSD following trauma exposure (Khoury et al. 2010). Additionally, there is a bidirectional relationship observed between PTSD and CUD with up to 38.5% of cannabis users citing PTSD symptoms as their reason for obtaining the drug at dispensaries (Yarnell 2015, Mizrachi Zer-Aviv et al. 2016, Wilkinson et al. 2015). This is especially true for the adolescent population, where marijuana is the most commonly used illicit substance by patients with PTSD (Yarnell, 2015), and an adolescent with PTSD has a two-fold increase in the likelihood of developing CUD (Bujarski et al., 2012). Acutely, cannabis can have an anxiolytic effect for PTSD patients, but prolonged and frequent cannabis use leads to an increased risk of developing impairments in neuronal functioning and cognition. Use of this drug is often associated with worse symptom outcomes in adolescent patients with PTSD, potentially due to long-term effects on learning and memory that result from cannabis-induced impairments in the development of the prefrontal cortex (Wilkinson et al. 2015). The presence of comorbid CUD, AUD, and PTSD is firmly established and clinically relevant, but there has been a lack of preclinical research into the underlying brain mechanisms that contribute to the maintenance and treatment of these comorbid disorders.

The prefrontal cortex is especially sensitive to the effects of drug exposure during adolescence due to the ongoing development and synaptic pruning that occurs during this critical period (Tortoriello et al. 2014, Volkow et al. 2014, Berghuis et al. 2007, Keimpema et al 2011). The prelimbic (PrL) and infralimbic (IfL) subregions of the PFC are particularly relevant to consider when examining interactions between drug exposure and stress disorders due to their general role in modulating reactivity to fear stimuli. Specifically, the PrL cortex has been established as a region that is responsible for the promotion of fear behaviors. Preclinical studies have observed increased PrL activity in response to fear cues (Burgos-Robles et al. 2009), and activation/inactivation of this region has been shown to increase/decrease the expression of conditioned fear behaviors, respectively (Laurent and Westbrook 2009, Sierra-Mercado et al. 2006, Sierra-Mercado et al. 2011, Corcoran and Quirk 2007, Vidal-Gonzalez et al. 2006). Additional studies have found that the PrL exhibits fear conditioning-induced plasticity (Burgos-Robles et al. 2009, Corcoran and Quirk 2007, Mahan and Ressler 2012, Song et al. 2015) while time-course experiments have determined that neuronal activity in the PrL mirrors the freezing activity of the animal during conditioning (Gilmartin and Helmstetter 2010, Milad and Quirk 2012, Burgos-Robles et al. 2009). This region has also been shown to be sensitive to the effects of cannabis exposure during adolescence (Cass et al. 2014, Renard et al. 2017, Schneider et al. 2008). There is widespread developmental modification of the PFC during adolescence which includes endocannabinoid- and cannabinoid receptor 1 (CB1)-mediated synaptic pruning to maintain the excitatory/inhibitory signaling balance (Renard et al. 2017, Caballero et al. 2014, Thomases et al. 2013). Thus, aberrant CB1 activity during the adolescent phase of development has the potential to impair the maturation of GABA synapses and subsequently allows for hyperactivity of the glutamate synapses in the PFC (Cass et al. 2014, Renard et al. 2017). Essentially, if there is exogenous alteration of CB1 activity through cannabis exposure, this refinement process can be disrupted leading to a long-term imbalance in excitatory signaling in the PFC (Cass et al. 2014). Additionally, adolescent exposure to cannabis has the potential to alter endocannabinoid-mediated plasticity including depolarization induced suppression of excitation and inhibition (DSE/I) which further alters the balance between excitatory and inhibitory signaling throughout the brain (Araque et al. 2017, Mato et al. 2004). Therefore, drug use during adolescence could have long-term effects on PFC signaling and cognition that manifest across multiple psychiatric disorders due to the impact on GABA/glutamate synapse development and the endocannabinoid system (Meier et al. 2012, Solowij et al. 2002, O’Shea et al. 2004).

Since cannabis and alcohol have been previously shown to impact the development of the prefrontal cortex during adolescence, these experiments were designed to investigate the effects of adolescent THC and ethanol exposure on behavioral and neuronal activity in response to fear stimuli. Additionally, in an attempt to alleviate the detrimental effects of these drugs, these studies utilized N-acetylcysteine (NAC), a clinically available pharmaceutical that has been established as a possible treatment for a variety of psychological disorders, including PTSD and CUD, through its effects on glutamate homeostasis in the brain (Reissner and Kalivas 2010, Back et al. 2016, Brown et al. 2013). NAC is a promising candidate for the treatment of glutamatergic impairments resulting from THC and alcohol exposure, and further testing in animal models is required to discern the mechanism of action through which it is working to impart these effects (Kalivas and Volkow, 2011). Therefore, these studies were designed to address the hypothesis that adolescent exposure to THC and ethanol impairs the development of PFC, leading to hyperactivity during PFC-dependent behavioral tasks that manifests as exaggerated behavioral responses to fear stimuli, and that glutamatergic modulation through NAC will prevent these effects.

2. Materials and Methods

2.1. Animals

Male Wistar rats were Postnatal Day (PD) 28 and ~100 grams on arrival and were housed individually in standard polycarbonate cages. Following delivery, animals were given one week for habituation to a 12/12 reverse light-dark cycle allowing for behavioral testing to occur during the dark phase of the cycle that initiated with lights off at 0900. All experiments had prior approval by the Institutional Animal Care and Use Committee at the Medical University of South Carolina and were completed within guidelines set forth by the National Research Council’s Guideline for the Care and Use of Mammals in Neuroscience and Behavioral Research (2003)/The National Institutes of Health guide for the care and use of Laboratory animals (NIH Publications No. 8023, revised 1978). A total of 88 animals were used for these experiments and were broken up into the following treatment groups: Air, THC, CIE, THC+CIE, THC+CIE+NAC (n = 16/group). A subset of animals from each group (n = 8/group) received surgical implants to monitor brain activity during these behavioral paradigms. Additionally, a supplemental group was added that only received NAC treatment in the absence of all other drug manipulations and was only tested on the behavioral aspects of this experiment (n = 8). The experimental design utilized for these studies is outlined in Figure 1.

Figure 1. Experimental Design and Timeline.

Figure 1

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Surgical procedures were completed on either postnatal day 35 or 36 for animals in the surgical subset of each treatment group. Following a week of recovery, animals were exposed to THC vapor for a total of 20 minutes a day for five days total. On each day animals received two five-minute exposures in the morning followed by another set of two five-minute exposures in the afternoon approximately four hours apart. Animals in the NAC treatment group received injections of the drug directly after the second exposure in the morning and afternoon. The week following THC exposure, animals were exposed to two weeks of CIE where vapor exposure occurred for 14 hours followed by 10 hours of abstinence each day. Following a two-day break to recovery from ethanol exposure, animals were exposed to a three-day fear conditioning paradigm. On each day of conditioning, animals received a total of four tone/shock pairings and prelimbic signaling data was collected throughout each of the sessions. Following the completion of behavioral testing, animals were sacrificed, and brain tissue was collected for verification of virus and probe location. Abbreviations: delta-9-tetrahydrocannabinol, THC; N-acetylcysteine, NAC; chronic intermittent ethanol exposure, CIE.

2.2. Surgical Procedures

For the subset of animals used to analyze brain signaling in response to fear conditioning, fiber photometry was used to measure calcium transients induced by neuronal signaling in real time during behavioral testing. Animals were injected with a virus containing genetically encoded calcium indicators to be used as a correlative measure of neural activity. Surgeries occurred between PD 35–36 and were followed by a one-week recovery period. Rats were sedated using vaporized isoflurane and oxygen (flow rate of 0.4 L/min, 5% for induction and 2.5–3.5% for maintenance) and were mounted in a stereotaxic apparatus once fully anesthetized (Kopf Instruments, Tujunga, CA). An adeno-associated virus encoding GCaMP6f with a promoter for CaMKII (AAV1-CaMKII-GCaMP6f, AddGene, Watertown, MA) was injected into the PrL using a microsyringe (Hamilton Company, Reno, NV) at a volume of 300 nL and a rate of 1 nL/s. The PrL coordinates used in these surgeries were based on pilot experiments that used dye injections to optimize the PrL location in PD 35 male animals (in mm from bregma and the skull surface, anterior/posterior +3.2, medial/lateral ± 0.6, and dorsal/ventral −2.8). There was a ten-minute period allowed for virus infusion following injection. A handmade optical fiber probe (400 μm diameter patch cord in a 2. 5 mm ferrule, Thorlabs) was then implanted at the same coordinates. Two stainless steel screws were mounted in the skull and were covered in dental cement to secure the probe in place. The surgical incision was treated with 2% triple antibiotic ointment and 2% xylocaine directly after surgery and antibiotic ointment was applied as needed in the following days. Additionally, the following drugs at the listed doses were administered to each animal subcutaneously (s.c.) directly following surgery: ketorolac (0.2 mL, s.c.), cefazolin (0.1 mL s.c.), dexamethasone (0.2 mL, s.c.), and saline (2 mL s.c.). For post-operative care, ketorolac was used for pain management and delivered the day following surgery and cefazolin antibiotic was given for two days following surgery.

2.3. Drug Preparation

N-Acetyl-L-cysteine (NAC, Sigma-Aldrich, St. Louis, MO, USA) was administered at a dose of 100 mg/kg, prepared on the day of treatment, and injected directly following each drug exposure session. The dose and administration timeline were chosen to optimize the effects of NAC on the glutamate system based on thorough experiments done to determine time course and mechanism of action (Dickey et al. 2009, Garcia-Keller et al. 2020, Scofield et al. 2016). NAC was dissolved in 27 mg/mL sodium hydroxide (NaOH) and the pH was readjusted to ~7.2. On the day of injection animals were weighed and dosed accordingly and injections were delivered intraperitoneal (I.P.).

2.4. Adolescent THC Vapor Exposure

Exposure to THC vapor occurred following the method established by Spencer et. al. (2018) and commenced following surgical recovery. This protocol was developed to induce THC metabolite concentrations similar to those achieved during typical human consumption. Additionally, THC absorption was previously confirmed using both an ELISA and body temperature measurements (Spencer et al. 2018). Starting at PD 40, each animal received a total of 20 minutes of vapor exposure per day for 5 days. Each THC exposure session was broken up into 5-minute administrations to keep the concentration of THC in the air steady, with two in the morning and two in the afternoon after a four-hour break. Each exposure session used a vaporized solution consisting of THC at a concentration of 200 mg per mL of ethanol and CBD at 20 mg per mL of ethanol. These solutions were mixed at a 1:1:1 ratio with glycerol to obtain a final solution containing THC and CBD at a ratio of 10:1. Aliquots of 150 uL of this solution were vaporized using a Volcano (Storz and Bickel, Oakland, CA) and the resulting vapor was pumped into plastic vapor chambers (42×30×15 cm3). Animals assigned to the NAC treatment group received I.P. injections of the drug immediately following both the morning and afternoon sessions. Following five days of THC exposure, animals were permitted a two-day break before entering chronic intermittent ethanol exposure (CIE).

2.5. Chronic Intermittent Ethanol Exposure (CIE)

CIE commenced on PD 50 and was used to model binge-like alcohol consumption using repeated cycles of ethanol vapor exposure and abstinence. This paradigm consisted of four nights of vapor exposure from 1800–0800 (14 hours on/10 hours off) followed by a two-day break, and this cycle was repeated twice. A five-point behavioral scale was used to grade intoxication levels based on motor behavior. Rats were assigned the following scores based on behaviors exhibited upon exiting the chambers: 1: no signs of intoxication and no motor impairment, 2: slight intoxication and slight motor impairment, 3: moderate intoxication with obvious motor impairment but retains the ability to walk, 4: loss of righting reflex, highly intoxicated, 5: loss of righting reflex and eye blink reflex, extremely intoxicated (Nixon and Crews, 2002). An intoxication rating of 2–3 was the goal of each CIE session which corresponds to a blood ethanol concentration (BEC) of ~300 mg/dl. Animals in the NAC treatment group received injections two hours prior to CIE exposure and immediately after being removed from the chambers each day. All animals achieved a moderate level of intoxication with behavioral ratings between 2–3 (Figure 2A) and BEC levels between 300–400 mg/dL (Figure 2B). There was a significant difference in BEC and intoxication rating between the groups in the initial days of CIE exposure, but this reflects the experimental procedure rather than relevant group differences. Generally, the first four days of the CIE paradigm are used to establish reliable ethanol vapor levels that correlate with adequate behavioral intoxication ratings. The high score observed on Day 1 for THC+CIE+NAC treated animals along with their low score on Day 4 are due to this refinement process that is necessary to achieve adequate intoxication without harm to the animals.

Figure 2. All animals achieved adequate intoxication ratings during CIE exposure and exhibited no differences in pain sensitivity.

Figure 2

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A) The average behavioral intoxication rating for each day of exposure was determined for all animals in treatment groups that received ethanol exposure. There was a significant difference in intoxication on the first day of exposure due to vapor regulation settings on the vapor chambers, but all animals achieved similar intoxication levels throughout the rest of the exposure sessions. Further, intoxication ratings were moderate for all groups and averaged around 2–3 throughout exposure (*p<0.05, THC+CIE+NAC vs. all other groups, n = 7–8 animals/group). B) These behavioral ratings were complimented with blood ethanol measures taken on exposure Day #4 and 8 to confirm the absorption of ethanol. While there were differences in BEC on exposure Day #4, this is a result of the vapor regulation settings rather than treatment effects, and these concentrations confirmed similar and moderate intoxication levels for all treatment groups (*p<0.05, THC+CIE+NAC vs. all other groups, n = 7–8 animals/group). C) Pain sensitivity was determined as a complimentary measure to supplement the behavioral data gathered for these experiments to rule out off target effects of THC and ethanol exposure. There were no differences in pain sensitivity between the groups as determined by a hot water tail immersion task (n = 7–8 animals/group). Abbreviations: intox, intoxication; blood ethanol content, BEC; delta-9-tetrahydrocannabinol, THC; N-acetylcysteine, NAC; chronic intermittent ethanol exposure, CIE.

2.6. Fear Conditioning Procedure

Two days following the end of CIE exposure, fear conditioning was used to determine differences in behavioral responses to fear stimuli and followed previously published methods (Smiley et al. 2020). This paradigm consisted of exposure to multiple tone/shock pairings and freezing behavior was monitored throughout each session. Each trial lasted approximately five minutes and occurred once daily for three consecutive days. Conditioning sessions included an initial 120 second acclimation period followed by the presentation of four tones (30 second duration, 80 dB, 3 kHz) separated by a 10 second inter-stimulus interval. Each tone was paired with a 0.75 mA shock that occurred during the final two seconds of the tone. Thus, animals were presented with a total of 12 tone/shock pairings across three days. Trials were recorded and analyzed using AnyMaze software to determine freezing behavior (Stoelting Co. Wood Dale, IL).

2.7. Calcium Imaging

Calcium imaging was performed using a custom-built fiber photometry rig based on the design of the Deisseroth (Lerner et al. 2015) and Woodward labs (Braunscheidel et al. 2019). An LED driver (Thorlabs, Newton, New Jersey) provided both 405 nm and 490 nm illumination which were combined in a fluorescence mini-cube (Doric Lenses, Québec, QC, Canada). A custom made 400 μm diameter patch cord terminating in a ceramic sleeve was used to connect the mini-cube to the animal’s fiber optic implant. Synapse software was used to control a digital processor that received input from a photodetector that collected emission signals at both 405 and 490 nm (Tucker-Davis Technologies, Alachua, FL). Integrated TTL signals were used to time-lock neuronal recordings to the start of each fear conditioning session and signaled the start of each tone throughout the session. Custom-written MatLab codes were used to analyze these data (The MathWorks Inc.). Signals from the 405 and 490 nm channels were subtracted from each other to calculate ΔF/F, and data for each testing day was then z-normalized to a combined baseline of all signaling across the whole session for that day.

2.8. Tail Immersion Test

Following the completion of all behavioral testing, animals in the surgical subset groups were exposed to a tail immersion test to determine any effect of drug exposure on pain sensitivity. Prior to the test day, all animals were habituated to handling and immersion using room temperature water. Additionally, each animals’ tail was marked 3 cm above the tip to standardize immersion length. On the day of the test, water was heated to 52°C and kept constant for each animal. The tail was dipped into the water to the 3 cm mark and held in the water until the animal’s tail broke the surface. This was repeated for a total of three times per animal in succession, and immersion time was averaged across the three trials. This test was recorded and manually scored to determine average immersion time for each animal. There were no differences observed between any of the treatment groups in average immersion time during this test (Figure 2C) [F (4, 25) = 0.03744, p = 0.9971] and, therefore, no expected differences in pain tolerance that could underlie differences in shock reactivity.

2.9. Statistical Analyses

Freezing behavior was examined as the primary dependent variable of the behavioral experiments and was reported as the percentage of time spent freezing during each 30 second cue presentation. This behavior was used as an index of fear reactivity and a 2-way ANOVA was used for analysis with a post-hoc Holm-Sidak test to compare values between treatment groups (Prism 8.0, GraphPad Inc., La Jolla, CA). Additionally, these analyses were used for ethanol induced intoxication related data while a one-way ANOVA was used to assess differences in immersion time during the pain sensitivity task. Fiber photometry data were analyzed using a one-way ANOVA with a Holm-Sidak multiple comparison test used to compare brain activity between treatment groups. Animals were excluded from analysis of calcium activity if histology revealed incorrect placement of the virus or fiber optic implant. All data were reported as the average +/− the standard error and a value of p < 0.05 was considered statistically significant.

3. Results

3.1. Adolescent exposure to THC and CIE increases behavioral responding to fear stimuli during conditioning

Animals were exposed to THC and ethanol during adolescence prior to being tested for fear reactivity in fear conditioning paradigms. Percent freezing recorded during each cue presentation was averaged across the total cue presentation time for each day of conditioning. There was a significant effect of treatment observed in percent freezing with THC+CIE- and THC-exposed animals exhibiting an increased freezing response to the tones on Conditioning Day #2 when compared to all other treatment groups (Figure 3A, [F (5, 215) = 12.81, p < 0.0001, n = 12–16 animals/group]). Additionally, this effect carried over to Conditioning Day #3 where all drug-treated groups exhibited heightened levels of freezing when compared to both air-treated controls and animals exposed to THC+CIE that received NAC treatment concurrent with each drug exposure (Figure 3A, THC+CIE vs. Air, p < 0.0001 and THC+CIE vs. THC+CIE+NAC, p = 0.0011). Further, freezing responses to each individual tone presentation were examined to determine the effect of drug exposure on freezing behaviors over time. There was a significant effect of treatment on individual tone responses with drug treated animals exhibiting heightened levels of freezing when compared to control and NAC treated animals (Figure 3B, [F (5, 860) = 27.66, p < 0.0001, n = 12–16 animals/group]). This effect began to emerge on Conditioning Day #2 and was consistent throughout Conditioning Day #3, where THC+CIE-exposed animals exhibited exaggerated levels of freezing when compared to those that received NAC treatment or were air-exposed (Figure 3B, p = 0.0274 vs. Air, p = 0.0059 vs. THC+CIE+NAC).

Figure 3. Animals exposed to THC and CIE during adolescence exhibit heightened responding during fear conditioning.

Figure 3

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A) When examining average freezing in response to the four tones presented throughout each conditioning day, there were no differences between the groups on Conditioning Day #1. However, on Conditioning Day #2, animals in the THC+CIE- and THC-exposed groups exhibited heightened freezing in response to the tones and acquired a conditioned freezing response earlier than both the air-exposed controls as well as THC+CIE-treated animals that were given NAC. This effect was also present on Conditioning Day #3, where THC+CIE-, THC-, and CIE-exposed animals exhibited an increased rate of freezing to the cues when compared to air controls, animals administered NAC, and THC+CIE animals treated with NAC. B) Further examination of freezing in response to fear cues was performed by examining each individual tone (CS) presentation throughout each day of conditioning. There was a significant effect of treatment when examining individual CS responses throughout conditioning, and further analysis revealed that CS presentation #6 was the first instance where THC+CIE-exposed animals started to exhibit significantly increased rates of freezing when compared to air controls as well as THC+CIE+NAC-treated animals (*p < 0.05 THC + CIE vs. Air, THC+CIE+NAC and NAC, +p < 0.05 THC vs. Air, THC+CIE+NAC and NAC, #p < 0.05 CIE vs. Air, THC+CIE+NAC and NAC, n = 12–16/group). Abbreviations: conditioned stimulus, CS; Cond, conditioning day; delta-9-tetrahydrocannabinol, THC; N-acetylcysteine, NAC; chronic intermittent ethanol exposure, CIE.

3.2. THC and CIE exposure results in heightened prelimbic signaling in response to the shock during conditioning

In addition to the behavioral measures taken during fear conditioning, a subset of animals in each treatment group received viral injections of a genetically encoded calcium indicator along with a fiber optic implant to measure signaling from the PrL during behavioral testing. While signaling data was recorded throughout the session, the most variation in signaling was observed in response to each shock presentation and, therefore, is the data reported in this section. To examine differences in neuronal responses to each shock presentation, signaling data from the PrL was averaged across the time immediately following shock delivery and was subtracted from the average signal established in the time directly prior to the shock. Specifically, the exact five seconds prior to each shock and five seconds following each shock were selected for analysis. Thus, we were able to quantify the change in neuronal activity in response to each shock. Signaling data is presented from Conditioning Day #1 (Figure 4A) and Conditioning Day #3 (Figure 4B) to compare neuronal activity between the acquisition of conditioned fear behavior and following the establishment freezing behavior. On Conditioning Day #1, all groups exhibited positive values in the change in neuronal activity in response to the first and second shock presentations, signifying an increase in PrL signal in response to the shock. During the initial shock presentations on Conditioning Day #1, there were no significant differences observed between THC+CIE exposed animals when compared to air-exposed controls (Figure 4A). Further analysis focused on signaling data from Conditioning Day #3, since this phase reflects conditioned responding rather than novelty-induced responding that could be confounding the data acquired during early phases of conditioning. When examining PrL activity in response to each shock presentation on Conditioning Day #3, THC+CIE-exposed animals exhibited a significant increase in activity in response to all four shock presentations when compared to air-exposed controls and THC+CIE exposed animals that received NAC treatment (Figure 4B, [F (4, 25) = 74.94, p<0.0001). Calcium activity was averaged across all four shock presentations to determine changes in PrL responding to fear stimuli over time by comparing overall shock responses between each day of conditioning (Figure 5A). There was a significant effect of treatment [F (4, 70) = 15.02, p < 0.0001] and time [F (4, 70) = 7.516, p < 0.0001] observed with regard to PrL activity when comparing THC+CIE-treated animals to controls and between data from Conditioning Day #1 to Day #3 (Figure 5A). Further, the group differences in PrL activity were associated with the level of freezing behavior exhibited during conditioning (Figure 3). Following the completion of all behavioral testing, brains were extracted and sectioned to ensure virus expression and probe location were within the boundaries of the PrL (Figure 5B).

Figure 4. There was a significant difference between the groups in prelimbic signaling changes in response to each shock presentation on Conditioning Day #3.

Figure 4

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The change in signal in response to each shock was quantified as a difference between PrL activity recorded during the five seconds preceding the shock and the five seconds directly after the shock. A) All treatment groups maintain a relatively high increase in prelimbic signaling in response to the first and second shock presentations, but there is a more variable response in response to the third and fourth shock presentations. Throughout Conditioning Day #1, there were no significant differences in PrL activity in response to each shock when comparing THC+CIE-treated animals to air-exposed controls. B) Quantification of the change in prelimbic signal in response to the shocks reveals a significant effect of treatment on Conditioning Day #3, with THC+CIE-exposed animals exhibiting a larger increase in signal when compared to air-exposed controls, THC+CIE animals treated with NAC (*p < 0.05, n = 6–8/group).

Figure 5. Comparison of the response to all shocks on each conditioning day reveals a significant effect of time as well as treatment.

Figure 5

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A) On Conditioning Day #1, there are no significant differences between THC+CIE exposed animals and controls with regards to average change in signal in response to the shock average across all four shock presentations. In contrast, on Conditioning Day #3 when animals have acquired a conditioned freezing response, THC+CIE exposed animals exhibit a significantly higher increase in prelimbic signaling in response to the shocks when compared to all other treatment groups (*p < 0.05, n =6–8/group). B) Following the completion of all behavioral testing, brains were extracted and sectioned to determine the location of the virus injections and placement of the fiber optic probe. Animals were eliminated if the fiber optic probe did not terminate directly above the virus within the prelimbic cortex (representative image inset).

4. Discussion

To determine the impact of adolescent drug exposure on future response to fear stimuli, animals were exposed to vaporized THC and ethanol during mid-adolescence and tested on a fear conditioning paradigm. Further, we investigated the ability of NAC to impact drug induced alterations in fear responding by administering this treatment concurrently with drug exposure. Finally, behavioral data from these experiments was supplemented with in vivo recordings from the prelimbic cortex during the presentation of fear stimuli to determine the effects of THC, ethanol, and NAC on neuronal signaling within this region. Adolescent exposure to THC and ethanol resulted in heightened behavioral responding during fear conditioning along with an increase in prelimbic signaling in response to the shock presentations on Conditioning Day #3. Additionally, the detrimental effects of THC and ethanol on behavioral and neuronal responses to fear stimuli were attenuated with NAC treatment. These studies establish the deleterious effects of adolescent exposure to THC and ethanol and support the hypothesis that drug induced alterations in PFC signaling may lead to increased susceptibility of developing PTSD following trauma exposure.

Cannabis is commonly used to decrease anxiety despite the fact that THC has been shown to be an anxiogenic agent, especially when it is consumed at the high concentration that has been bred into popular cannabis strains (Sharpe et al. 2020). Preclinical anxiety measures along with clinical examinations of cannabis-dependent patients have demonstrated the relationship between THC intake and increased anxiety behaviors (Rock et al. 2017, Raymundi et al. 2020). More recently, the long-term effects of THC on anxiety disorders has emerged as a pressing topic of study. Clinical studies that utilize a fear conditioning paradigm have shown that cannabis use is associated with increases in threat generalization to safety stimuli (Papini et al. 2017). Further, this reduction in differentiation between safe and threatening stimuli was also associated with impairments in fear extinction (Papini et al. 2017). These behaviors are a hallmark of PTSD symptomology and could be responsible for the clinical association between cannabis use and increased PTSD incidence. Additionally, preclinical experiments have investigated this relationship in the adolescent population. Specifically, adolescent mice exposed to THC exhibit alterations in fear learning following stress exposure, but this effect was not observed when THC exposure occurred during adulthood (Saravia et al. 2019). Chronic exposure to ethanol during adolescence has variable behavioral effects on fear conditioning depending on the ethanol exposure paradigm, fear conditioning protocol, and timing of exposure. Due to varying ethanol and fear exposure paradigms, these studies have found differing effects on fear behaviors including no impact on fear conditioning (Broadwater and Spear 2013), impairments in learning during conditioning (Stephens et al. 2005), and heightened responding to fear stimuli (Moberg et al. 2017) following ethanol exposure. Further, THC and ethanol may interact to exacerbate these effects. Not only is there a combinatory effect of THC and ethanol on psychomotor performance (Ramaekers et al. 2000), but these drugs also interact pharmacologically to increase subjective intoxicating effects (Ronen et al. 2010). Specifically, cannabinoids can act on cytochrome P450 enzymes which affects the metabolism of drugs including ethanol (Alsherbiny and Li 2018) and, conversely, ethanol has been shown to increase the duration of cannabis intoxication (Hartman et al. 2016). Using THC vapor exposure followed by chronic intermittent ethanol exposure during adolescence, our experiments provide novel data regarding the effects of comorbid drug exposure on behavioral responses to fear stimuli.

In these experiments, the effects of THC and ethanol observed on behavioral responses to fear were associated with signaling alterations in the PrL subregion of the PFC. Previously, activity in the PrL has been correlated with freezing behavior during fear conditioning paradigms (Burgos-Robles et al. 2009) and, due to the ongoing development of this region during adolescence, exposure to either THC or ethanol has the potential to alter PrL activity in response to fear. During adolescence, the prefrontal cortex is uniquely situated to be affected by drugs of abuse due to the ongoing development, synaptic pruning, and maturation of the endocannabinoid system (Pattwell et al. 2016). In rodent models, THC exposure has been shown to disrupt developmental processes in the PrL by altering the gene networks that are responsible for dendritic development (Miller et al. 2019). Further, hyperactivity at CB1 receptors in the PFC during adolescence can lead to dysregulation of glutamatergic signaling at inhibitory interneurons leading to impaired development of these cells, ultimately resulting in downregulated inhibitory control in this region (Caballero and Tseng 2012). These findings are paralleled by clinical data illustrating that those with a history of adolescent cannabis exposure exhibit alterations in both the structure and function of the PFC (Medina et al. 2009, Orr et al. 2013). Similar impairments in prefrontal cortex development have been observed as a result of adolescent alcohol exposure (Squeglia et al. 2014). The PFC is known to be especially susceptible to the deleterious effects of alcohol, and significant differences in both gray and white matter have been observed following adolescent alcohol use (De Bellis et al. 2005, Medina et al. 2008). Given the ongoing development of the PrL as well as the ability of THC and ethanol to impact this region, these effects could underlie the behavioral and signaling alterations observed as a consequence of adolescent drug exposure in the present studies. Further, the overlap between THC and ethanol’s effects is most pronounced in the prefrontal cortex and, therefore, NAC may be working in this area to prevent the increased reactivity to fear stimuli observed in these experiments. In clinical studies, NAC can regulate both glutamate levels in the prefrontal cortex and the functional connectivity of this region (Mullier et al. 2019, McQueen et al. 2018). Additionally, NAC has been shown to modulate glutamate homeostasis in patients with substance abuse disorders, including adolescents with cannabis use disorder (Gray et al. 2010). Therefore, NAC could be acting through this pathway to diminish the increases in PrL signaling and behavioral responding observed in response to fear stimuli following THC and CIE exposure.

These experiments tested pain sensitivity as an alternative explanation for the group differences observed with regard to freezing behavior, but there are a number of additional explanations that should be explored. First, exposure to these drugs could be causing a reduction in motor activity during fear conditioning paradigms that is recorded as increased freezing. While exposure to THC has the potential to cause short-term decreases in motor activity observed in open field tests immediately following drug exposure, these are transient effects that are dependent on the drug being onboard and were not present 48 hours later (Bruijnzeel et al. 2016). Similarly, ethanol exposure can result in alterations in motor behavior, but these effects dissipate following the cessation of ethanol exposure (Ornelas et al. 2015). These motor effects that occur as a consequence of ethanol exposure on motor sedation are also less severe in adolescent animals when compared to adults (Acevedo et al. 2013, Little et al. 1996). As these experiments tested fear conditioning 18 days following the last THC exposure and four days after the last CIE session, we do not expect motor alterations as a result of these drugs to have impacted freezing behavior during fear conditioning. Additionally, the differences in fear behaviors recorded during conditioning could potentially be a result of enhanced learning following THC and ethanol exposure. While recent reports have observed a slight increase in working memory after adolescent male rats self-administered THC, these studies were confounded by the use of sucrose as the reward for this task (Stringfield and Torregrossa, 2021b). THC exposure has been shown to increase palatability and reward signaling for high sucrose food in rats (De Luca et al. 2012) and, further, has been more commonly shown to impair learning and memory processes (Niyuhire et al. 2007, Schoeler and Bhattacharyya 2013, Stringfield and Torregrossa, 2021a). Therefore, we do not expect increases in learning due to drug exposure to be the underlying cause for the effects observed on fear learning. While these experiments focused on alterations in prelimbic signaling, there are a number of additional fear-related areas that could also be affected by THC and ethanol exposure during adolescence. There are high levels of CB1 receptors in the amygdala, and cannabinoids are highly involved in signaling throughout this region especially in the basolateral subregion (BLA) (Katona et al. 2001, Pistis et al. 2004, Phan et al. 2008). In general, adolescents exhibit stronger amygdala reactivity in response to fearful stimuli when compared to adults (Guyer et al. 2008). Additionally, adolescent cannabis users exhibit increased amygdala reactivity in response to fearful stimuli and demonstrate impaired discrimination between threat and neutral stimuli resulting from increases in PFC activity (Spechler et al. 2015). Preclinical studies also observe alterations in amygdala activity as a result of cannabinoid exposure. Specifically, animal models have shown a reduction of GABA transmission in the amygdala following exposure to CB1 agonists (Katona et al. 2001) and, when animals were treated with THC and exposed to restraint stress, the effects on inhibitory transmission in the amygdala were enhanced (Patel et al. 2005). Therefore, further examination of the PFC to amygdala pathway would be helpful in identifying circuit level alterations that occur following adolescent exposure to THC and ethanol.

5. Conclusions

In summary, these experiments determined that adolescent exposure to THC and ethanol leads to heightened behavioral responding during fear conditioning along with increases in prelimbic signaling in response to fearful stimuli. Additionally, treatment with the glutamatergic modulator NAC was effective at reducing both the behavioral and neuronal deficits that result from adolescent THC and ethanol exposure. These results support the hypothesis that drug exposure during adolescence can lead to neurobiological alterations that enhance susceptibility to developing fear-related disorders such as PTSD and that normalization of glutamatergic functioning in the PFC could serve as a potential treatment option.

Funding Sources:

This work was supported by the National Institutes of Health (grant number R01AA024526, JTG) and the National Institute on Alcohol Abuse and Alcoholism (grant number 5T32AA007474, JJW & CES).

Abbreviations:

AUD

Alcohol Use Disorder

CBD

Cannabidiol

CUD

Cannabis use disorder

THC

delta-9-tetrahydrocannabinol

CB1

cannabinoid 1

I.P.

intraperitoneal

PFC

prefrontal cortex

PTSD

post-traumatic stress disorder

PrL

prelimbic

IfL

infralimbic

NAC

N-acetylcysteine

GLT1

glutamate transporter-1

CIE

chronic intermittent ethanol

Footnotes

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Declarations of interest: none

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