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. Author manuscript; available in PMC: 2016 May 20.
Published in final edited form as: Behav Neurosci. 2015 Jun 8;129(4):371–379. doi: 10.1037/bne0000075

Alcohol gains access to appetitive learning through adolescent heavy drinking

Alyssa DiLeo 1,#, Kristina M Wright 1,#, Elizabeth Mangone 1, Michael A McDannald 1
PMCID: PMC4874812  NIHMSID: NIHMS690860  PMID: 26052793

Abstract

Adolescent heavy alcohol drinking increases the risk for alcohol use disorders in adulthood, yet mechanisms conferring increased risk are not well understood. We propose that adolescent alcohol drinking shapes alcohol’s aversive or appetitive properties in adulthood. Alcohol normally drives aversive learning and alcohol-predictive cues are avoided. We hypothesize that through adolescent heavy drinking alcohol gains access to appetitive learning. A primary consequence is that alcohol-predictive cues become valued and sought out. To test this hypothesis, we gave genetically heterogeneous, male Long Evans rats voluntary, chronic intermittent access to water or alcohol throughout adolescence and then identified moderate and heavy alcohol drinkers. After a short abstinence period, we assessed the aversive or appetitive properties of alcohol using flavor learning procedures. We compared alcohol to the known appetitive properties of sugar. Flavor learning in adult rats who were alcohol-naïve or adolescent moderate alcohol drinkers revealed alcohol to be aversive and sugar to be appetitive. The same flavor learning procedures revealed both alcohol and sugar to be appetitive in adult rats who were adolescent heavy drinkers. The results demonstrate that alcohol gains access to neurobehavioral circuits for appetitive learning through adolescent heavy alcohol drinking.

Keywords: alcohol, adolescent, aversive, reward, binge, appetitive

Introduction

A 2012 national survey found that 45% of adolescents ages 18–20 had used alcohol in the past month (SAMHSA, 2013) and 10% exhibited heavy drinking. Compared to abstinence or moderate drinking, heavy adolescent drinking significantly increases the risk for alcohol use disorders in adulthood (Chassin, Pitts, & Prost, 2002; Duncan, Alpert, Duncan, & Hops, 1997; Grant et al., 2006). Animal studies are only beginning to examine the behavioral and neural mechanisms by which adolescent heavy drinking promotes alcohol-associated behaviors in adulthood (Gilpin, Karanikas, & Richardson, 2012; Guerri & Pascual, 2010; Pascual, Boix, Felipo, & Guerri, 2009; Vargas, Bengston, Gilpin, Whitcomb, & Richardson, 2014). For example, a number of studies have examined if adolescent alcohol exposure increases adult alcohol drinking. While some studies have reported such increases (Gilpin et al., 2012; Pascual et al., 2009), others have found only modest increases (Criado & Ehlers, 2013), and still others have found no relationship (Slawecki & Betancourt, 2002; Vetter, Doremus-Fitzwater, & Spear, 2007). The inconsistent findings may be due in part to methodological differences; however, they also suggest that adult increases in alcohol drinking may not be the primary means by which adolescent heavy drinking confers increased risk for alcohol use disorders.

We propose one mechanism by which adolescent heavy drinking elevates the risk for alcohol use disorders is by permitting alcohol access to neurobehavioral circuits for appetitive learning. In naïve rats, alcohol is an aversive outcome that will drive aversive learning (Anderson, Varlinskaya, & Spear, 2010; Cunningham, 1981; Philpot, Badanich, & Kirstein, 2003; Saalfield & Spear, 2015). As a result, cues associated with alcohol will acquire aversive properties and will be avoided. We hypothesize that through adolescent heavy drinking, alcohol becomes an appetitive outcome. Cues associated with alcohol will acquire appetitive properties and will become valued and sought out. By gaining access to neurobehavioral circuits for appetitive learning, adolescent heavy alcohol drinking fundamentally changes how alcohol drives learning and behavior in adulthood.

To test this hypothesis, we gave genetically heterogeneous Long Evans rats voluntary, chronic intermittent access to alcohol (Simms et al., 2008), or water (as a control), across adolescence. Based on levels reported in the literature (Marchant, Khuc, Pickens, Bonci, & Shaham, 2013; Simms et al., 2008), we identified moderate and heavy drinkers within the alcohol population. After a brief abstinence period, rats underwent a flavor learning procedure in which a neutral flavor was presented with alcohol. As a control, flavor learning for a natural reward, sugar, was also assessed. Formation of a flavor aversion would indicate alcohol was an aversive outcome while formation of a flavor preference would indicate alcohol was an appetitive outcome. We found alcohol-naïve adult rats and those with a history of moderate alcohol drinking formed an aversion to the alcohol-associated flavor, but formed a preference for the sugar-associated flavor. Thus, in normal rats alcohol drives aversive learning, but sugar drives appetitive learning. In contrast, adolescent heavy alcohol drinkers formed a preference for the alcohol-associated flavor, as well as the sugar-associated flavor, indicating that both sugar and alcohol drove appetitive learning. These results suggest that adolescent heavy alcohol drinking may increase the risk for alcohol use disorders by permitting alcohol access to neurobehavioral circuits for appetitive learning.

Methods and Materials

Subjects

Subjects were 46 male Long Evans rats approximately 21 days old on arrival, obtained from Charles River Laboratories and maintained on a 12-hr light cycle (lights off at 6:00 PM). Food and water were freely available at all times. All protocols were approved by the Boston College Animal Care and Use Committee and all experiments were carried out in accordance with the NIH guidelines regarding the care and use of rats for experimental procedures.

Apparatus

Experiments took place in the rat’s home cage. Solutions were provided via 50 mL centrifuge tubes with rubber stoppers and ball bearing sipper tubes (Doremus, Brunell, Rajendran, & Spear, 2005), referred to as experimental bottles. Experimental bottles were fixed to the wire top of the home cage with a large binder clip.

Dependent measures

Drinking of solutions in experimental bottles is reported in two ways: absolute drinking in grams and drinking by body weight in grams/kilogram/24hrs. Bottle weights were measured prior to and following exposure to solutions. Body weight is reported in grams and was recorded Monday, Wednesday and Friday of each week.

Chronic intermittent access to alcohol or water

After postnatal day 21 arrival and two days of acclimation to the animal facility, 24 rats were given chronic intermittent access (CIA) to alcohol (20% ethanol, v/v) starting on postnatal day 23. At 11:00 AM on Sunday, Tuesday and Thursday, experimental bottles containing alcohol were placed on the home cage. At all times, the rat’s normal food and water were freely available. Experimental bottles were removed at 11:00 AM on Monday, Wednesday and Friday. Rats received CIA until postnatal day 56, resulting in a total of 16, 24-hr exposures to alcohol (Figure 1A). The remaining rats, Water Controls (n = 22), received the exact same treatment with experimental bottles containing water, the same water used to make the 20% ethanol.

Figure 1. Experimental outline and flavor learning procedures.

Figure 1

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(A) Rats were given voluntary, chronic intermittent access to 20% ethanol (Alcohol) or water from postnatal days 23 to 56 (grey bar). Moderate and Heavy drinkers were identified within the alcohol group. Flavor learning was assessed in Moderate Drinkers, Heavy drinkers and Water Controls in adulthood (blue (light grey) and red (dark grey) striped bar). During each learning procedure all rats were first exposed to a flavored solution: (B) almond for flavor-alcohol learning and (C) peppermint for flavor-sugar learning. In flavor learning half of the rats were then assigned to the Paired condition in which the flavor was given jointly with 20% ethanol or 10% sucrose. Unpaired rats received the flavor and alcohol or sugar separately. Learning about the flavor was then assessed in test sessions during which only flavored water was present. (D) The sequence of flavor learning was fully counterbalanced. Half of the rats received flavor-alcohol learning first and were assigned to either the Unpaired or Paired condition. When these rats next received flavor-sugar learning, Alcohol-Paired (blue, blue arrows) rats were split into the Sugar-Unpaired and Sugar-Paired conditions. Alcohol-Unpaired (black, black arrows) rats were split similarly and the same counterbalancing was applied to rats that received flavor-sugar learning first.

Identification of moderate and heavy drinkers

We identified moderate and heavy alcohol drinkers by their peak alcohol drinking during the final 10 CIA sessions. Peak alcohol drinking was chosen because it best captured moderate and heavy drinking: the maximum amount a rat drank in a single session. Peak drinking was strongly correlated with other possible measures including average drinking. The peak session was taken from the final 10 sessions because this is when absolute alcohol drinking escalated and drinking by body weight stabilized across all rats with alcohol access (data shown in Figure 2). Moderate Drinkers were identified as rats whose peak drinking session over the final ten CIA sessions was less than 5 g/kg/24hr. This was chosen as a threshold based on reports that adult, Long Evans rats reach terminal drinking levels of 5.1 ± 0.6 g/kg/24hr using this chronic access procedure (Simms et al., 2008). Heavy Drinkers were identified as rats whose peak drinking session over the final ten CIA sessions was at least 10 g/kg/24hr. This level is comparable to that demonstrated by alcohol-preferring P rats when first given access to 20% ethanol (Marchant et al., 2013) and is double terminal levels reported in adult Long Evans rats (Simms et al., 2008). Upon completion of the CIA procedure, all rats were given one week during which no experimental bottles were placed on the home cages. Flavor learning was then assessed.

Figure 2. Chronic intermittent access to alcohol or water.

Figure 2

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(A) Absolute drinking from the experimental bottles (mean g ± SEM) over the 16 sessions of the chronic intermittent access procedure is shown for rats given access to water (WC, black) and alcohol (ALC, grey). Water drinking is plotted against the left y-axis and alcohol drinking against the right y-axis. Black asterisks indicate significance of the post-hoc comparison between water drinking on session 1 and each subsequent water session. Grey asterisks indicate significance of the post-hoc comparison between alcohol drinking on session 1 and each subsequent alcohol session. (B) Drinking by body weight from the experimental bottles (mean g/kg/24hr ± SEM) over the 16 sessions of the chronic intermittent access procedure is shown (colors, post-hoc comparisons and asterisks maintained from (A). (C) Absolute drinking from the experimental bottles (mean g ± SEM) over the 16 sessions of the chronic intermittent access procedure is shown for Moderate Drinkers (MD, open) and Heavy Drinkers (HD, grey). Asterisks indicate significance of the post-hoc comparison between Moderate Drinkers and Heavy Drinkers drinking levels for each of the 16 sessions. (D) Drinking by body weight from the experimental bottles (mean g/kg/24hr ± SEM) over the 16 sessions of the chronic intermittent access procedure is shown for Moderate Drinkers (open) and Heavy Drinkers (grey). Asterisks indicate significance of the post-hoc comparison between Moderate Drinkers and Heavy Drinkers drinking levels for each of the 16 sessions. * p < 0.05.

Flavor-alcohol learning

Flavor-alcohol learning procedures are outlined in Figure 1B. For each drinking session, an experimental bottle was placed on the rat’s home cage from 5:00 PM to 9:00 AM (~16 hour exposure). In the first drinking session, all rats were pre-exposed to almond-flavored water (McCormick almond extract in distilled water, 2% v/v). Water Controls, Moderate Drinkers and Heavy Drinkers were then assigned to the Paired or Unpaired conditions. The next four sessions were designed to establish a flavor-alcohol association in Paired, but not Unpaired rats. In sessions 2 and 4, Paired rats were given access to almond-flavored alcohol (2% almond v/v, 20% ethanol, v/v), and Unpaired rats given access to only alcohol (20% ethanol, v/v). In sessions 3 and 5, Paired rats were given access to only water, and Unpaired rats given access to only almond-flavored water. Thus, all rats were exposed to almond and alcohol, but only rats in the Paired condition experienced them jointly. Flavor learning was assessed in sessions 6–11 during which all rats were given access to only almond-flavored water.

Flavor-sugar learning

Flavor-sugar learning procedures are outlined in Figure 1C. The behavioral design closely followed that of the flavor-alcohol experiment. The major differences were that peppermint (McCormick) was used as a flavorant and sugar (10% sucrose, w/v) as a reward. All rats were pre-exposed to peppermint-flavored water (0.5% peppermint v/v) and then assigned to Paired or Unpaired conditions. In sessions 2 and 4, Paired rats were given access to peppermint-flavored, sugar water (0.5% peppermint v/v, 10% sucrose, w/v), and Unpaired rats given access to only sugar water (10% sucrose, w/v). In sessions 3 and 5, Paired rats were given access to only water, and Unpaired rats given access to only peppermint-flavored water. Thus, all rats were given access to peppermint and sugar, but only rats in the Paired condition experienced them jointly. Flavor learning was assessed in sessions 6–11 during which rats were given access to only peppermint-flavored water.

Almond was used exclusively for flavor-alcohol learning and peppermint exclusively for flavor-sugar learning because pilot studies found that almond supported numerically higher levels of drinking. This allowed for greater detection of both flavor aversions (decreases in flavor drinking) and flavor preferences (increases in flavor drinking). The ability to detect bidirectional changes in alcohol-associated flavor drinking was integral to testing our hypothesis. The relatively lower levels of baseline peppermint drinking were acceptable because sugar has universally been found to support conditioned flavor preferences (Bonacchi, Ackroff, & Sclafani, 2008; Capaldi, Owens, & Palmer, 1994; Harris, Shand, Carroll, & Westbrook, 2004; Messier & White, 1984).

All rats were tested sequentially in the two flavor-learning procedures, but within each procedure rats were divided into Unpaired or Paired conditions (Figure 1D). The sequence in which rats received flavor-alcohol and flavor-sugar learning was counterbalanced, with half receiving flavor-alcohol learning first. Importantly, assignment to Paired and Unpaired conditions between learning procedures was also fully counterbalanced. For example, rats in the Paired condition for flavor-alcohol learning were divided into the Paired and Unpaired conditions for flavor-sugar learning (Figure 1D, blue arrows). The same counterbalancing was done for all associative groups (Figure 1D, black and red arrows). Rats were given one week between the two flavor learning procedures during which no experimental bottles were placed on home cages.

Statistical analyses

Body weight, absolute drinking (g), and drinking by body weight (g/kg/24hr) were analyzed with SPSS using analysis of variance (ANOVA). Post-hoc comparisons were performed with two-tailed t-tests and planned comparisons performed with one-tailed t-tests when there was an a priori, directional hypothesis. The standard water bottles on the home cage were designed to be slightly leaky to ensure they did not clog, which would result in rats being water deprived. This made them unreliable indices of drinking and thus data from these bottles were not recorded. By contrast, experimental bottles placed on empty cages found no leakage, ensuring that changes in volume on the rats’ cages were the result of drinking.

To be included in flavor learning analyses, rats must have drank 15 g or less of flavored solution in the pre-exposure session. Rats drinking 15 g or more already preferred the flavor, confounding effects of learning. In all cases, p ≤ 0.05 was considered significant.

Results

Chronic intermittent access to alcohol or water

Starting on postnatal day 23, rats underwent the CIA procedure during which they received 24-hr access to 20% ethanol, three sessions per week. At all times food and water were freely available, meaning any alcohol drinking would reflect voluntary and pleasurable drinking. All rats markedly increased their body weight over the course of CIA and there were no differences between groups (Supplemental Figure 1). Critical to the interpretation of CIA drinking patterns, weight gain during early CIA sessions was much greater than that in later sessions. Indeed, rats almost doubled their body weight from the first to fourth CIA session.

Chronic drinking was measured in two ways: absolute drinking (g) and drinking by body weight (g/kg/24hr). In both measures, rats with water access drank significantly more than rats with alcohol access. There was a significant increase in absolute drinking from the beginning to the end of the CIA procedure for both water and alcohol rats (Figure 2A). However, the rate at which drinking increased did not precisely follow the rate for body weight. Rats with water access rapidly increased drinking by body weight, then decreased before stabilizing for the remainder of CIA (Figure 2B – black line). Rats with alcohol access showed the highest drinking by body weight on the first session, when weights were lowest, decreasing in subsequent sessions before stabilizing (Figure 2B – grey line). In support ANOVAs for either absolute drinking (g) or drinking by body weight (g/kg/24hr) [between factor: drinking history (water vs alcohol); within factor: session (1–16)] found significant effects of drinking history, (g – F1,40 = 19.13, p < 0.01; g/kg/24hr – F1,40 = 27.71, p < 0.01), session (g – F15,600 = 3.50, p < 0.01; g/kg/24hr – F15,600 = 3.90, p < 0.01) and the drinking history × session interaction (g – F15,600 = 2.21, p < 0.01; g/kg/24hr – F15,600 = 3.91, p < 0.01).

For each group and drinking measure, post-hoc comparisons were made between drinking levels on the first CIA session and each subsequent session. Absolute water drinking was significantly higher on every session following the first, while absolute alcohol drinking became significantly higher on the 11th session, maintaining this difference until the final session (Figure 2A). Water drinking by body weight significantly increased early then declined, while alcohol drinking by body weight was greater on the first session than every subsequent session (Figure 2B).

Identification of moderate and heavy drinkers

The change in alcohol drinking across CIA sessions was not uniform across rats, with the majority falling into one of two categories: Moderate Drinkers or Heavy Drinkers. When looking at absolute drinking (g), Moderate Drinkers showed little escalation of drinking over the course of CIA, while Heavy Drinkers showed significant escalation in the final ten sessions (Figure 2C). In drinking by body weight (g/kg/24hr), all rats initially showed high drinking levels that declined after the first session. However, Moderate Drinkers continued to decline throughout CIA while Heavy Drinkers escalated drinking in the final ten sessions (Figure 2D). Thus, there was strong concordance in alcohol drinking patterns exhibited by Moderate and Heavy Drinkers in both measures.

These descriptions are supported by ANOVA [between factor: drinking history (Moderate Drinker vs Heavy Drinker); within factor: session (1–16)] for drinking in both g and g/kg/24hr. Both analyses found significant main effects of session and group (Fs > 5, ps < 0.05), but most critically, both found a significant session × group interaction: drinking in grams (F15,270 = 5.76, p < 0.05); drinking in g/kg/24hr (F15,270 = 1.70, p = 0.05). Post-hoc comparisons between Moderate Drinkers and Heavy Drinkers for each CIA session found no differences in drinking in the first six sessions, but significant differences for each of the final ten sessions in absolute drinking (Figure 2C). Nearly the exact same pattern was found in drinking by body weight, with only one of the final ten sessions failing to meet significance (Figure 2D).

Our measure of heavy drinking was consistent with other possible measures. Peak alcohol drinking in g/kg/24hr significantly correlated with peak alcohol drinking in g, as well as mean alcohol drinking over the final ten sessions in either g or g/kg/24hr (all R2 > 0.8, all p < 0.05). Finally, while not shown in Figure 2D; post-hoc comparisons between the first and last CIA session found that Moderate Drinkers significantly decreased drinking by body weight (p < 0.05) while Heavy Drinkers showed no significant differences. By the end of chronic access, Heavy Drinkers returned alcohol drinking by body weight to levels demonstrated on the first session.

Flavor-alcohol learning

In the first session of flavor-alcohol learning all rats were pre-exposed to almond. Rats in each group (Water Controls, Moderate Drinkers and Heavy Drinkers) were then assigned to the Paired or Unpaired conditions. The final numbers of rats in each group are shown in Table 1. The next four sessions were meant to establish a flavor-alcohol association in Paired rats by presenting almond jointly with 20% ethanol in two sessions and only water in the other two sessions. Unpaired rats were given almond in two sessions and 20% ethanol in the other two sessions – equating for overall exposure, but preventing the formation of a flavor-alcohol association.

Table 1.

Final subject numbers for each experimental group.

Drinking History Group Flavor-Alcohol Flavor-Sugar
Water Control Unpaired n = 7 n = 11
Paired n = 7 n = 11
Moderate Drinkers Unpaired n = 4 n = 4
Paired n = 4 n = 7
Heavy Drinkers Unpaired n = 4 n = 5
paired n = 3 n = 4
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Consistent with their drinking history, Heavy Drinkers drank more during alcohol sessions, but less during water sessions, compared to Water Controls (Supplemental Figure 3A). Water Controls and Moderate Drinkers did not differ in their drinking over the four learning sessions. This was confirmed with ANOVA [within factor: session (water vs. alcohol); between factors: drinking history (Water Controls vs. Moderate Drinkers vs. Heavy Drinkers), associative condition (Unpaired vs. Paired)] for drinking over the four learning sessions which found a significant session × drinking history interaction (F2,23 = 3.36, p = 0.05). ANOVA restricted to Water Controls and Moderate Drinkers found no effects of or interactions with group while ANOVA restricted to Water Controls and Heavy Drinkers found a significant session × drinking history interaction (F1,19 = 6.94, p < 0.05).

The data of primary interest came from the test sessions. One outlier was excluded from this analysis (Supplemental Figure 3). Almond drinking during pre-exposure was identical and low across all rats (planned comparison t-tests: WC/MD-Unpaired vs WC/MD-Paired, HD-Unpaired vs HD-Paired, both p > 0.2; Figure 3A). Almond drinking in test sessions revealed alcohol to be aversive in Water Controls and Moderate Drinkers (WC/MD). Paired rats sharply decreased almond drinking, relative to Unpaired rats, in test sessions (planned comparison t-test: Unpaired vs Paired, #p < 0.05; Figure 3B). By contrast, almond drinking revealed alcohol to be appetitive in Heavy Drinkers. Paired rats demonstrated a robust increase in almond drinking, relative to Unpaired rats in test sessions (planned comparison t-test: Unpaired vs Paired, #p < 0.05; Figure 3B). These descriptions were confirmed by ANOVA for absolute almond drinking [within factor: test session (6); between factors: drinking history (Water Controls vs. Moderate Drinkers vs. Heavy Drinkers) and associative condition (Unpaired vs. Paired)] which found a significant drinking history × associative condition interaction (F2,23 = 8.43, p < 0.01) as well as a session × drinking history × associative condition interaction (F10,115 = 2.66, p < 0.01). Importantly, ANOVA restricted to Water Controls and Moderate Drinkers [all other factors same as full ANOVA] revealed a significant effect of associative condition (F1,18 = 4.30, p = 0.05) but no effect of or interaction with group (all F < 2, p > 0.2). Mean drinking for Water Controls and Moderate Drinkers during flavor-alcohol learning is shown separately in Supplemental Figure 4A–B. By contrast, ANOVA restricted to Water Controls and Heavy Drinkers [all other factors same as full ANOVA] revealed a significant drinking history × associative condition interaction (F1,17 = 12.10, p < 0.01) as well as a significant session × drinking history × associative condition interaction (F5,85 = 3.42, p < 0.05). Consistent with the ANOVA results, post-hoc comparisons between only WC/MD and HD rats, found a significant difference in almond test drinking in Paired rats (t-test: WC/MD vs HD, *p < 0.05; Figure 3B).

Figure 3. Flavor-alcohol and flavor-sugar learning.

Figure 3

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(A) Absolute drinking (mean g ± SEM) during almond pre-exposure is shown for Water Controls and Moderate Drinkers combined (WC/MD; white bars) and Heavy Drinkers (HD; grey bars) assigned to the Unpaired and Paired conditions. Water Controls and Moderate Drinkers were only combined for purposes of illustration – all statistics were performed with these groups separated. Post-hoc comparisons found no significant differences in pre-exposure almond drinking between rats in any group. (B) Absolute drinking (mean g ± SEM for all six test almond sessions) is shown (meaning of color maintained from A). Post-hoc comparisons found no significant differences between WC/MD and HD rats in the Unpaired groups but did find significant differences between those in the Paired groups (*p < 0.05). Planned comparisons found significant differences drinking in HD-Paired rats compared to HD-Unpaired rats (#p < 0.05), as well as significant differences in drinking between WC/MD-Paired and WC/MD-Unpaired rats (#p < 0.05). (C) Absolute drinking (mean g ± SEM) during peppermint pre-exposure is shown for WC/MD and HD rats assigned to the Unpaired and Paired conditions. Post-hoc comparisons found no significant differences between pre-exposure peppermint drinking between rats in any group. (D) Absolute drinking (mean g ± SEM) for the first peppermint test session is shown (color maintained from C). Post-hoc comparisons for test peppermint drinking only found a significant difference between Paired and Unpaired rats across all groups (*p < 0.05). There were no significant differences between WC/MD and HD rats in either the Unpaired or Paired groups. While not shown, planned comparisons found a significant difference between Unpaired and Paired rats in the WC/MD group (t-test, #p < 0.05), a trend toward significance between Unpaired and Paired rats in the HD group (t-test, #p = 0.07). *post-hoc t-test, p < 0.05; #planned-comparison t-test p < 0.05.

Importantly, the same significant statistical patterns were also observed when drinking by body weight was analyzed. ANOVA for almond drinking by body weight [within factor: test session (6); between factors: drinking history (Water Controls vs. Moderate Drinkers vs. Heavy Drinkers) and associative condition (Unpaired vs. Paired)] found a significant drinking history × associative condition interaction (F2,23 = 7.93, p < 0.01) as well as a session × drinking history × associative condition interaction (F10,115 = 2.65, p < 0.01). ANOVA restricted to Water Controls and Moderate Drinkers [all other factors same as full ANOVA] revealed a significant effect of associative condition (F1,18 = 4.98, p < 0.05) but no effect of or interaction with group (all F < 2, p > 0.2). Finally, ANOVA restricted to Water Controls and Heavy Drinkers [all other factors same as full ANOVA] revealed a significant drinking history × associative condition interaction (F1,17 = 11.18, p < 0.01) as well as a significant session × drinking history × associative condition interaction (F5,85 = 3.37, p < 0.01).

Flavor-sugar learning

In the first session of flavor-sugar learning all rats were pre-exposed to peppermint. Rats in each group were then assigned to Paired or Unpaired conditions. The final numbers of rats in each group are shown in Table 1. The next four sessions were meant to establish a flavor-sugar association in Paired rats by presenting peppermint jointly with 10% sucrose in two sessions and water only in the other two sessions. Unpaired rats were given peppermint in two sessions and 10% sucrose in the other two sessions – equating for overall experience, but preventing the formation of a flavor-sugar association. All rats drank more sugar than water over the course of learning, consistent with sugar being appetitive (Supplemental Figure 2B). There were no differences in overall levels of drinking between Water Controls, Moderate Drinkers and Heavy Drinkers. In support, ANOVA for drinking [within factor: session (water vs. sugar); between factors: drinking history (Water Controls vs. Moderate Drinkers vs. Heavy Drinkers), associative condition (Unpaired vs. Paired)] found a significant effect of session (F1,36 = 92.77, p < 0.01) but no effect of drinking history or drinking history × session interaction (both F < 2, p > 0.2).

Peppermint drinking in test revealed sugar to be appetitive. All rats initially drank low and equivalent amounts of peppermint during pre-exposure (planned comparison t-tests: WC/MD-Unpaired vs WC/MD-Paired, HD-Unpaired vs HD-Paired, both p > 0.2; Figure 3C). Only Paired rats – but critically for Water Controls, Moderate Drinkers and Heavy Drinkers – increased peppermint drinking in test sessions. This effect was most apparent in the first-test session. Accordingly, ANOVA for absolute peppermint drinking [within factor: test session (6); between factors: drinking history (Water Controls vs. Moderate Drinkers vs. Heavy Drinkers), associative condition (Unpaired vs. Paired)] found a significant effect of associative condition (F1,36 = 13.52, p < 0.01) as well as a significant session × associative condition interaction (F5,180 = 3.55, p < 0.01). There was no effect of drinking history, the drinking history × associative condition interaction or the drinking history × session × associative condition interaction (all F < 2, all p > 0.2). Consistent with the ANOVA results, post-hoc comparisons only found a significant difference in peppermint test drinking between Unpaired and Paired conditions across all rats (t-test: WC/MD/HD-Unpaired vs WC/MD/HD-Paired, *p < 0.05; Figure 3D).

The significant effect of associative condition was also found when only Water Controls and Moderate Drinkers were analyzed (F1,29 = 12.34, p < 0.01) and when only Water Controls and Heavy Drinkers were analyzed (F1,27 = 12.66, p < 0.01). Mean drinking for Water Controls and Moderate Drinkers during flavor-sugar learning is shown separately in Supplemental Figure 4C–D. Finally, the same significant statistical patterns were also observed for drinking by body weight. The main effect of associative condition was found for all three ANOVAs (WC vs. MD vs. HD; WC vs. MD, and WC vs. HD – all F > 12, all p < 0.01).

Discussion

Here we gave genetically heterogeneous Long Evans rats chronic access to water or alcohol and identified Moderate and Heavy drinkers within the alcohol population. We then demonstrated that alcohol is an aversive outcome and sugar an appetitive outcome, to alcohol-naïve adult rats and adults with an adolescent history of moderate alcohol drinking. Both of these groups demonstrated aversive learning to a flavor paired with alcohol, but appetitive learning to a flavor paired with sugar. While heavy adolescent drinkers still found sugar to be an appetitive outcome, they also found alcohol to be appetitive. As a consequence, heavy drinkers demonstrated appetitive learning to a flavor paired with either sugar or alcohol.

At first glance, our finding that absolute alcohol drinking and drinking by body weight peaked at opposite ends of chronic access appears at odds. However, peak alcohol drinking by body weight in early adolescence that decreases with maturity is consistent with previous studies (Garcia-Burgos, Gonzalez, Manrique, & Gallo, 2009; Schramm-Sapyta et al., 2014; Vetter et al., 2007). High drinking by body weight early in adolescence may involve metabolic, hormonal and/or neurodevelopmental factors (Spear, 2014). One more practical consideration is that body weight is increasing rapidly early in adolescence. The adolescent rats in the current experiment nearly doubled their body weights in the first four chronic access sessions. Especially in adolescents, drinking by body weight is a comparison between the increase in body weight and the increase in absolute drinking. The stabilization of drinking by body weight in the last half of chronic alcohol access indicates that weight and alcohol drinking were increasing at the same rate across all rats. Heavy drinkers showed a more straightforward pattern. By the end of chronic access absolute drinking was at its peak and drinking by body weight did not statistically differ from the first session.

Notably, all alcohol drinking during this procedure was entirely voluntary and rats were never water-deprived or food-deprived at any point. This is significant because the few studies that have found alcohol to establish a flavor preference used less alcoholic solutions (5–10% ethanol) in food-deprived rats (Cunningham & Niehus, 1997; Deems, Oetting, Sherman, & Garcia, 1986; Fedorchak & Bolles, 1987). In these studies, alcohol’s appetitive properties appear to be largely derived from its caloric content. Here, we found a highly alcoholic solution (20% ethanol) to drive appetitive learning in heavy drinkers with no need for caloric restriction. This suggests that the alcohol drinking observed was for pleasure rather than caloric need. Further, simple access to alcohol during adolescence was insufficient to make it appetitive – moderate alcohol drinking during adolescence resulted in alcohol maintaining its aversive property.

It could be argued that the differences in flavor-alcohol learning observed in moderate- and heavy drinkers were not due to changes resulting from alcohol drinking but were innate. That is, the rats found to be heavy drinkers would have gone on to form a preference for alcohol-associated flavors even if they had never been given access to alcohol. We find this account less plausible. Rats were randomly assigned to the alcohol and water groups prior to the start of the experiment. If there was a predisposition in some rats for alcohol to be appetitive in adulthood, then a similar proportion of water controls should have also gone on to form a strong preference for the alcohol-associated flavor. This was not observed. Water controls uniformly displayed an aversion to the alcohol-associated flavor and only adolescent heavy-drinkers formed a preference.

An account we find more plausible is that alcohol acquires appetitive properties through an interaction between innate predisposition and alcohol access. However, this predisposition may not be directly linked to alcohol. The rats we found to be heavy drinkers did not have a predisposition towards increased alcohol drinking at the onset of alcohol access. It is more likely that other traits interact with alcohol access, such as impulsivity. In support, wild-type mice who show greater impulsivity in a delayed discounting task showed altered locomotive responses to ethanol compared to mice demonstrating less impulsivity (Mitchell, Reeves, Li, & Phillips, 2006). Increased impulsivity is also observed in alcohol preferring P rats (Beckwith & Czachowski, 2014; Oberlin & Grahame, 2009; Perkel, Bentzley, Andrzejewski, & Martinetti, 2015). Rats demonstrating high impulsivity show greater compulsive drug-taking (Belin, Mar, Dalley, Robbins, & Everitt, 2008). Traits related to exploration & novelty seeking (Bardo, Donohew, & Harrington, 1996; Stansfield & Kirstein, 2006) and rewarded approach (Flagel, Akil, & Robinson, 2009; Flagel et al., 2010; Srey, Maddux, & Chaudhri, 2015) are also likely to contribute.

How might adolescent heavy alcohol drinking increase the risk for alcohol use disorders? Current theories of addiction describe initial drug intake as controlled and pleasurable. Continued use results in escalating, uncontrolled drug intake (Everitt, 2014; Everitt et al., 2008) and withdrawal following periods of heavy intake is characterized by a negative motivational state (Koob, 2015; Koob & Volkow, 2010). The desire to resume drug use in withdrawal is argued not to stem from its pleasurable, appetitive properties (positive reinforcement) but rather from the desire to terminate the negative motivational state (negative reinforcement) (Koob, 2015; Koob & Volkow, 2010).

Based on current theories of addiction, we suggest two likely mechanisms by which adolescent heavy alcohol drinking increases the risk for alcohol use disorders. First, by establishing alcohol as an appetitive outcome, adolescent heavy drinking may amplify alcohol’s positive reinforcing effects; speed the transition from controlled to compulsive use, or both. Second, enhancing alcohol’s positive reinforcement properties may exacerbate the negative motivational state brought on by withdrawal. While this negative motivational state is a distinct process, it is intimately related to positive reinforcing properties of drugs. The peak in drug reinforcement (determining factors including but not limited to: dose, duration, amount of intake) is theorized to be directly related to the depth or duration of the negative motivational state (Koob & Le Moal, 1997). Casually put, rats with a history of adolescent heavy drinking may experience more severe negative motivational states following withdrawal periods.

Of course it is also possible that adolescence is not a unique developmental time period during which heavy drinking increases the risk for alcohol use disorders, but simply allows the path to abuse to start earlier in life. If this were the case, we would predict that giving naïve adults chronic access to alcohol would result in alcohol acquiring appetitive properties in heavy drinkers. Further, it is possible that alcohol’s switch from aversive to appetitive could be achieved with fewer voluntary drinking sessions than the sixteen given in this study. Future experiments controlling the developmental timing and duration of alcohol access will directly examine these factors.

While speculative, we hypothesize the basolateral amygdala (BLA) and nucleus accumbens core (NAcc) are key players in alcohol’s transition from aversive to appetitive through adolescent heavy drinking. The BLA and NAcc have been heavily implicated in addiction (Cornish & Kalivas, 2000; Di Chiara et al., 2004; Di Ciano & Everitt, 2004; Koob & Volkow, 2010) and show neural activity consistent with encoding of appetitive and aversive outcomes and learning (Paton, Belova, Morrison, & Salzman, 2006; Schoenbaum, Chiba, & Gallagher, 1998; Setlow, Schoenbaum, & Gallagher, 2003). Most relevant to the current results, the BLA and NAcc are critical to the formation of conditioned flavor preference for natural rewards (Dwyer & Iordanova, 2010; Gilbert, Campbell, & Kesner, 2003; Touzani, Bodnar, & Sclafani, 2008; Touzani & Sclafani, 2005). The BLA and NAcc may be critical sites of neuroadaptation or plasticity underlying alcohol’s switch from aversive to appetitive through adolescent heavy drinking.

Here we have demonstrated that in normal adult rats, alcohol drives aversive learning. Through adolescent heavy drinking alcohol gains access to neurobehavioral circuits for appetitive learning. Most prominently, cues associated with alcohol will come to be valued and sought out. These results provide the foundation for future studies that will provide a more complete description of the behavioral and neural mechanisms by which adolescent heavy drinking confers increased risk for alcohol use disorders.

Supplementary Material

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Acknowledgments

Support: This work was supported by National Institutes of Health grant DA034010 (MAM).

Footnotes

Financial Disclosures

The authors report no biomedical financial interests or potential conflicts of interest.

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NIHMS690860-supplement-3.pdf (786KB, pdf)
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