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. Author manuscript; available in PMC: 2024 Nov 20.
Published in final edited form as: Drug Alcohol Depend. 2023 Sep 27;252:110983. doi: 10.1016/j.drugalcdep.2023.110983

Synthetic contraceptive hormones occlude the ability of nicotine to reduce ethanol consumption in ovary-intact female rats

Erin E Maher 1, Ashley M White 1, Ashley Craig 1, Shailesh Khatri 1, Percell T Kendrick Jr 1, Mary E Matocha, Emma O Bondy 1, Nikhil Pallem 1, Grace Breakfield 1, Madison Botkins 1, Olivia Sweatt 2, William C Griffin 2, Brent Kaplan 4, Jessica J Weafer 5, Joshua S Beckmann 3,*, Cassandra D Gipson 1,*
PMCID: PMC11577355  NIHMSID: NIHMS1936495  PMID: 37778097

Abstract

Rates of tobacco and alcohol use in women are rising, and women are more vulnerable than men to escalating tobacco and alcohol use. Many women use hormonal birth control, with the oral contraceptive pill being the most prevalent. Oral contraceptives contain both a progestin (synthetic progesterone) and a synthetic estrogen (ethinyl estradiol; EE) and are contraindicated for women over 35 years who smoke. Despite this, no studies have examined how synthetic contraceptive hormones impact this pattern of polysubstance use in females. To address this critical gap in the field, we treated ovary-intact female rats with either sesame oil (vehicle), the progestin levonorgestrel (LEVO; contained in formulations such as Alesse®), or the combination of EE+LEVO in addition to either undergoing single (nicotine or saline) or polydrug (nicotine and ethanol; EtOH) self-administration (SA) in a sequential use model. Rats preferred EtOH over water following extended EtOH drinking experience as well as after nicotine or saline SA experience, and rats undergoing only nicotine SA (water controls) consumed more nicotine as compared to rats co-using EtOH and nicotine. Importantly, this effect was occluded in groups treated with contraceptive hormones. In the sequential use group, both LEVO alone and the EE+LEVO combination occluded the ability of nicotine to decrease EtOH consumption. Interestingly, demand experiments suggest an economic substitute effect between nicotine and EtOH. Together, we show that chronic synthetic hormone exposure impacts nicotine and EtOH sequential use, demonstrating the crucial need to understand how chronic use of different contraceptive formulations alter patterns of polydrug use in women.

Keywords: Contraceptive hormones, nicotine, ethanol, economic substitute, ethinyl estradiol, levonorgestrel

1. Introduction

Tobacco and alcohol use disorders (TUD and AUD, respectively) are tremendous health liabilities and leading preventable causes of death in the United States (US; Danaei et al., 2009; Mokdad et al., 2004). TUD and AUD are highly comorbid, as 80–90% of individuals with AUD also smoke (Breslau, 1995; Falk et al., 2006). Despite this, the vast majority of preclinical and clinical research on TUD and AUD typically evaluate consumption of these drugs in isolation which may limit translational value of preclinical studies and treatment outcomes.

Women face unique challenges with AUD and TUD compared to men. Occurrences of AUD among women are increasing at a faster rate than that of men (Grant et al., 2017), which is particularly alarming because women are more susceptible to the long-term negative health effects of alcohol compared to men (Erol and Karpyak, 2015). Underscoring potential sex differences, some smoking cessation treatments appear to be more effective in men than women (Perkins and Scott, 2008; Piper et al., 2007) and long-term smoking cessation is often more difficult to achieve for women than men (Perkins and Scott, 2008; Piper et al., 2007; Piper et al., 2017). A final consideration is that the currently available pharmacotherapies for both disorders are based largely on data derived from male subjects.

Women are targeted for hormonal contraceptive use, whereas men are not typically prescribed synthetic hormones for this purpose (Jacobsohn et al., 2022; Thirumalai et al., 2019). Given that routine and continuous contraceptive hormone use is unique to women, it is important to understand the influence of their use on alcohol and nicotine use. It is estimated that one fifth of women in the US use hormone-containing contraceptives of some kind, with the most common being the oral contraceptive pill (Daniels and Abma, 2020). Oral contraceptives typically contain a combination of a synthetic estrogen (most commonly, ethinyl estradiol, or EE) and a synthetic progesterone (termed “progestins”). There are several common progestins, including levonorgestrel (LEVO; Stanczyk et al., 2013). The need to include a progestin in EE-containing oral contraceptives is well established as it offsets the heightened risk of endometrial hyperplasia that can be caused by prolonged unopposed estrogen treatment (Smith et al., 1975).

Contraceptive hormones interact with nicotine. For example, oral contraceptive users have faster nicotine metabolism than naturally cycling women (Benowitz et al., 2009; Benowitz et al., 2006), which may be driven by EE (Benowitz et al., 2006). Additionally, during weeks of the contraceptive pill pack with low progestin levels, women experience higher smoking satisfaction (Hinderaker et al., 2015). Together, contraceptive hormones can have a meaningful impact on smoking in women, and women who use oral contraceptives may have different patterns of smoking than those who are naturally cycling.

Significantly less work has examined the effects of oral contraceptive use on alcohol consumption (Warren, et al., 2021). There is preliminary evidence that women using hormonal contraceptives report higher alcohol consumption and craving as compared to naturally cycling women (Warren et al., 2021); although one study found the opposite (Dumas et al., 1984). Additionally, one study found that length of hormonal contraceptive use is positively associated with a current diagnosis of alcohol dependence (Toffol et al., 2011). Importantly, none of these studies systematically evaluated the type of synthetic hormones used by subjects, leaving a rather large gap in the clinical literature.

The large proportion of women who co-use alcohol and nicotine while also using oral contraceptives is an important group to consider when studying female-specific mechanisms of nicotine and alcohol co-use. The preclinical literature on ethanol (EtOH) and nicotine co-use are mixed in outcomes regarding how co-use of these substances influence consumption of each other (Blomqvist et al., 1996; Clark et al., 2001; Dyr et al., 1999; Hauser et al., 2012; Lê et al., 2003; Nadal et al., 1998; Olausson et al., 2001; Sharpe and Samson, 2002; Smith et al., 1999; Tolu et al., 2017). Thus, the goal of the current rodent study was two-fold: to examine (1) how sequential EtOH and nicotine self-administration (SA) affect consumption of each other in ovary-intact female rats; and (2) how synthetic hormones found in contraceptives impact EtOH and nicotine consumption. We utilized a sequential use model in which ovary-intact female rats drank either EtOH or water in the morning, immediately followed by nicotine SA, and later nicotine demand, in the afternoon. A separate control cohort of female rats drank EtOH in the morning, followed by saline SA in the afternoon. Rats also underwent daily injections of either LEVO, a combination of EE+LEVO, or vehicle (sesame oil) during nicotine/saline and EtOH/water sequential use. LEVO was chosen here as it is a commonly utilized progestin that occurs in oral contraceptives that also contain EE, such as Alesse®, and it has also been associated with improved cognitive outcomes in a preclinical menopause model (Braden et al., 2017). We hypothesized that sequential use of EtOH and nicotine would result in increased consumption of both substances. Although there are few studies evaluating contraceptive hormones on EtOH and/or nicotine use and thus little upon which to formulate a priori hypotheses, our prior study showed that EE increased nicotine SA in ovariectomized females (Maher et al., 2021). Thus, we hypothesized that EE+LEVO treatment would increase sequential use, and finally, that LEVO alone would decrease use of these two drugs given its beneficial effects on cognition.

2. Methods

2.1. Animals

Eighty ovary-intact female Long-Evans rats (Charles River; 200 – 250 g with an arrival age of approximately 8 weeks) were individually housed on a 12-hour reverse light cycle with ad libitum access to food prior to experimental procedures, and ad libitum access to water (via Lixit system) in the home cage throughout the study, excluding morning drinking in the dark (DID) procedures. Animals were handled daily upon arrival. Five animals were excluded from analysis following nicotine or saline acquisition due to loss of catheter patency, resulting in 75 animals completing the task. All animal use practices were approved by the Institutional Animal Care and Use Committee of the University of Kentucky (Protocol #2020–3438).

2.2. Apparatus

DID procedures (Holgate et al., 2017; Thiele and Navarro, 2014) occurred in each animal’s home cage. Nicotine sessions occurred in 28 operant chambers (MED Associates, St. Albans, VT) within sound-attenuating chambers, described in detail previously (Leyrer-Jackson et al., 2020; Overby et al., 2018) and described further in supplemental material (S1).

2.3. DID Procedure and Two-Bottle Preference Test

Figure 1A displays the experimental timeline. Rats were randomly assigned to either the water control or EtOH drinking groups and began a 15-day DID procedure. The justification for this methodological decision is that some individuals who co-use these substances drink alcohol prior to using nicotine-containing products (Field et al., 2005; Jackson et al., 2010). Thus, we chose the order of drug SA acquisition to maximize our translational model of this pattern of co-use. Three hours after lights off (3 hours into the active cycle, at 0900 hours), home cage water lixit access was removed by pulling the cage forward several inches. EtOH (10% v/v) was presented in sipper tubes with double ball bearings (Amuza Inc; San Diego CA). The justification for this dose of EtOH was to replicate prior studies demonstrating that rats readily drink and seek EtOH following SA of this percent EtOH concentration (Timme et al., 2020; Timme et al., 2022). As a control, a proportion (n=24) of the rats were presented with sipper tubes containing only water. Sipper tubes were weighed before and after sessions, and rats were weighed immediately following drinking in order to calculate fluid consumption relative to body weight.

Figure 1. EtOH Drinking Acquisition and Two-Bottle Preference Test.

Figure 1.

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(A) The timeline of experimental procedures. Red box indicates data collection for current figure during Phase 1 of EtOH acquisition. (B) A main effect of session (day) was found on EtOH consumption (p<0.05). (C) A main effect of session (day) was found on EtOH consumption (p<0.05). (D) No differences in EtOH consumption were found between eventual hormone treatment groups (these data represent EtOH consumption as a function of pre-hormone treatment groups averaged across the 15 sessions of Phase 1; p>0.05). (E) Preference for EtOH was significantly greater than preference for water (dotted line = indifference set at 50%; p<0.05).

Next, only the EtOH animals began a 12-day 2-bottle preference test (4 hr access period) each day. Three hours after the lights turned off, access to the lixit was again removed and animals were given two single sipper tubes, (10% EtOH or water). Each bottle was placed in one of the two identical water bottle slots of the home cage, spaced equal distance apart in the front of the cage, and the position of EtOH was alternated across cages to limit side preferences. Percent EtOH volume consumed was calculated from the difference in EtOH sipper tube weight divided by total weight difference of both EtOH and water sipper tubes.

After recovery from surgery, all animals resumed 4 hours of single sipper tube DID experiments for the duration of nicotine or saline SA behavioral experiments. Following nicotine or saline SA and demand phases, rats underwent 3 additional days of 2-bottle preference for 4 hours, 3 hours after lights off.

2.4. Surgical Procedures and Hormone Treatments

Following Phase 1, rats were implanted with an indwelling jugular vein catheter (Leyrer-Jackson et al., 2020; Maher et al., 2021). Rats were anesthetized with intramuscular (i.m.) ketamine (80–100 mg/kg i.m.) and xylazine (8 mg/kg, i.m.), and aseptic surgical techniques were utilized. Rats were divided into hormone treatment group based on non-significant differences in baseline hormone consumption. Beginning on surgery day, subcutaneous hormone injections of either LEVO (0.6 μg/0.1 mL sesame oil; this dose was chosen based on (Braden et al., 2017), EE+LEVO (0.6 μg LEVO + 0.18 μg EE/0.1 mL sesame oil; (Maher et al., 2021) or vehicle (0.1 mL sesame oil) began. Please see S1 for additional methodology and references, and Figure S2–1 for vaginal cytology to confirm hormone treatments.

2.5. SA Procedures

Following recovery from surgery, rats were food restricted and food trained prior to nicotine or saline SA. All animals entered the SA paradigm 7 hrs following the beginning of the dark cycle and immediately following 4 hrs of single sipper tube DID procedures. Infusions of saline or 0.06 mg/kg/infusion nicotine (0.1 mL/infusion) were delivered across 5.9 s following one response on the active lever (fixed ratio-1 or FR-1). The justification for using this nicotine dose during this phase is that it is the highest dose utilized in the subsequent threshold procedure (Maher et al., 2021). Upon an active lever press, lights above both levers were illuminated, and a tone (2900 Hz) was presented simultaneously with drug infusion. Infusions were followed by a 20-s dark timeout period, during which active lever responses were recorded but produced no consequences. An inactive lever was present at all times but produced no consequences when pressed. All sessions lasted for 2 hr. Rats in the nicotine SA groups completed 15 sessions before moving into the demand phase; saline SA groups underwent 15 sessions of saline SA and then completed the operant phase of the experimental timeline. Please see S1 for nicotine demand procedures and demand curve generation methodology.

2.6. Statistical Analysis

Data for SA acquisition, infusions, and lever presses (active, inactive) across the first 15 sessions were collected and analyzed using linear mixed effects (LME) modeling using JMP software from SAS. In all experiments, subject was treated as a random factor. Total number of infusions per animal during acquisition was recorded per session and groups were compared using LME. The most parsimonious model for determining differences in both EtOH and nicotine consumption was one that excludes hormone treatment as an effect. For this reason, all statistical analyses below were run separately for each hormone treatment using LME with subject as a random effect, session as a continuous variable, and drug (EtOH or water) nested within subject.

Lever discrimination was assessed as the ratio of active/active+inactive lever presses, and discrimination above 66.67% was considered as meeting acquisition criteria (2:1 ratio). For analyses in Figure 2 below, Day 1 of EtOH or water drinking was omitted from analysis in all groups from both phases, which allowed for better comparison of drinking across days following the first exposure in each phase.

Figure 2. Nicotine but not Saline Sequential Use Decreases EtOH Consumption, which is Occluded by LEVO and EE+LEVO Treatment During Nicotine EtOH Sequential Use.

Figure 2.

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(A) The timeline of experimental procedures. Red boxes indicate data collection for current figure, which includes EtOH consumption prior to (Phase 1) and during nicotine SA (Phase 2). (B1) A main effect of nicotine sequential use on EtOH consumption in the vehicle treatment nicotine SA group whereby rats co-using nicotine consumed less EtOH (individual values represent average consumption across animals on each session; *p<0.05). (B2) EtOH consumption during EtOH acquisition (Phase 1) and during nicotine sequential use (morning DID sessions during Phase 2) in vehicle-treated rats (*p<0.05 comparing EtOH consumption before versus during nicotine SA), graphed across sessions. (B3) EtOH consumption did not differ when compared between pre-versus during saline SA in vehicle-treated rats (individual values represent average consumption across animals on each session; p>0.05). (B4) EtOH consumption on during EtOH acquisition (Phase 1) and during saline sequential use (morning DID sessions during Phase 2) in vehicle-treated rats, graphed across sessions. (C1) There was no main effect of nicotine sequential use on EtOH consumption in the EE+LEVO treatment group (individual values represent average consumption across animals on each session; p>0.05). (C2) EtOH consumption during EtOH acquisition (Phase 1) and during nicotine sequential use (morning DID sessions during Phase 2) in EE+LEVO-treated rats, graphed across sessions. (C3) EtOH consumption did not differ when compared prior to versus during saline SA in EE+LEVO-treated saline SA rats (individual values represent average consumption across animals on each session; p>0.05). (C4) EtOH consumption during EtOH acquisition (Phase 1) and during saline sequential use (morning DID sessions during Phase 2) in EE+LEVO-treated rats, graphed across sessions. (D1) There was no main effect of nicotine sequential use on EtOH consumption in the LEVO treatment group (individual values represent average consumption across animals on each session; p>0.05). (D2) EtOH consumption during EtOH acquisition (Phase 1) and during nicotine sequential use (morning DID sessions during Phase 2) in LEVO-treated rats, graphed across sessions. (D3) EtOH consumption did not differ when compared prior to versus during saline SA in EE+LEVO-treated saline SA rats (individual values represent average consumption across animals on each session; p>0.05). (D4) EtOH consumption during EtOH acquisition (Phase 1) and during nicotine sequential use (morning DID sessions during Phase 2) in LEVO-treated rats, graphed across sessions.

For the demand phase, daily infusions and responses were recorded. Consumption was calculated infusions earned multiplied by the dose, and demand curves were calculated according to the exponentiated demand equation (Koffarnus et al., 2015a), a simple mathematical re-expression of the exponential model of demand that does not require log transformations and thus replacements or exclusions of zero values (Hursh and Silberberg, 2008):

logQ=logQ0+k(e−α⋅Q0⋅C−1)

In this analysis, Q represents consumption, Q0 represents the estimated maximum consumption at a zero-unit price point, α represents the rate of change of consumption, C is unit price, and k is a constant. Demand curves were fit to the data via nonlinear mixed effects (NLME) modeling in R using the ‘nlme’ package (Hammerslag et al., 2020; Hofford et al., 2016; Powell et al., 2019). The advantages of utilizing NLME analyses over typical ANOVAs are that it allows for independent measurement of demand intensity (Q0) and demand elasticity (α) for inferential and descriptive statistics. Further, this equation describes demand data well and has been utilized across a number of species including rats and humans (Koffarnus et al., 2015a; Koffarnus et al., 2015b; Maher et al., 2021; Powell et al., 2019). Graphing was performed in Prism 10.1 (Graphpad Software, San Diego, CA). Data are represented as means ± standard error of the mean (SEM) where appropriate.

2.7. Blood Collection

Four to 7 days following two bottle preference testing and hormone treatments, animals were again given one bottle of EtOH in the morning. 30 min (N=8) and 240 min (N=11) after the start of EtOH drinking, bottles were removed, and blood was collected from rat tail tips between days 62–65, with a minimum of 4–7 days post-hormone treatment, via a small incision of the lateral tail vein and collected in heparinized capillaries. The justification for this timepoint for BEC analysis was to minimize the possible impact of stress from the blood draw procedure on behavioral outcomes throughout the study (see S1 for methodology).

3. Results

3.1. Phase 1: EtOH Drinking Acquisition.

One-Bottle DID.

First, all rats received 15 sessions of DID with water or EtOH in Phase 1. LME analysis was conducted on consumption of water and EtOH across sessions. A main effect of session was found on drinking in both water (Figure 1C; F1,23 = 25.5, p<0.05) and EtOH (Figure 1B; F1,55 = 13.1, p<0.05) groups, in which EtOH drinking increased across sessions (Figure 1B) and water drinking decreased across sessions (Figure 1C). When separated by future hormone group assignment, LME analysis on the average EtOH consumption across the 15 days of Phase 1 revealed no main effect of hormone treatment on EtOH consumption between eventual hormone treatment groups (Figure 1D; F1,52 = 0.4, p>0.05). These results indicate that future hormone groups did not differ in baseline EtOH consumption.

Two-Bottle Choice Test.

Following one-bottle DID, the EtOH group underwent 12 days of a 2-bottle preference test. LME analysis was conducted on EtOH preference relative to indifference (i.e., distribution of consumption set to 50%). Results showed that EtOH preference was significantly above 50% (Figure 1E; F1,110 = 19.3, p<0.05), indicating that EtOH-drinking rats preferred EtOH over water. LME also showed a significant effect of session on EtOH preference (F1,110 = 21.5, p<0.05), indicating that preference for EtOH increased across preference test sessions.

3.2. Phase 2: EtOH and Nicotine Sequential Use.

In the second phase of the experiment, rats were chronically treated with either vehicle, LEVO, or EE+LEVO between daily DID and nicotine or saline SA. Prior to nicotine or saline SA and after hormone treatment had begun, rats underwent overnight food training, and active and inactive lever press data were analyzed using LME and are presented in S2 and Figure S2–2. Within-subject LME analysis was conducted on consumption of EtOH across both EtOH acquisition during Phase 1 and EtOH drinking sessions during nicotine or saline SA for each hormone treatment group to assess changes in EtOH consumption after the onset of nicotine SA (water consumption pre-nicotine and during nicotine SA was also analyzed via LME and are presented in S2 and Figure S2–3). In vehicle-treated rats undergoing nicotine SA, LME revealed a main effect of nicotine SA on EtOH consumption (Figures 2B1; F1,10 = 19.9, p<0.05), showing that sequential use of nicotine with EtOH decreased EtOH drinking. Additionally, there was a main effect of session on EtOH consumption (Figure 2B2; F1,10 = 5.2, p<0.05). Unlike the vehicle group, nicotine SA did not affect EtOH consumption in rats treated with EE+LEVO. LME showed no main effect of nicotine on EtOH consumption (Figures 2C1; F1,10.2 = 0.43, p>0.05) and no main effect of session on EtOH consumption (Figure 2C2; F1,10.4 = 0.02, p>0.05). Similarly, in LEVO-treated rats, LME showed no main effect of nicotine on EtOH consumption (Figures 2D1; F1,9 = 1.4, p>0.05) and no main effect of session on EtOH consumption (Figure 2D2; F1,9 = 2.1, p>0.05). Together, these results indicate that nicotine decreases consumption of EtOH when taken in a sequential pattern, but this effect is occluded by chronic treatment with both the EE+LEVO combination and LEVO alone.

In vehicle-treated saline SA rats, LME revealed no main effect of saline SA on EtOH consumption (Figures 2B3; F1,6.2 = 1.5, p>0.05), showing that sequential use of saline with EtOH did not decrease EtOH drinking in the absence of contraceptive hormones. Additionally, there was a main effect of session on EtOH consumption (Figure 2B4; F1,7.2 = 5.7, p<0.05). Similar to the vehicle group, saline SA did not affect EtOH consumption in rats treated with EE+LEVO. LME showed no main effect of nicotine on EtOH consumption (Figures 2C3; F1,6.5 = 1.1, p>0.05) but did find a main effect of session on EtOH consumption (Figure 2C4; F1,6.3 = 21.6, p<0.05). Finally, in LEVO-treated rats, LME showed no main effect of saline on EtOH consumption (Figures 2D3; F6.8 = 0.46, p>0.05) and no main effect of session on EtOH consumption (Figure 2D4; F7.1 = 1, p>0.05). Together, these results indicate that saline does not decrease consumption of EtOH when taken in a sequential pattern, and this effect is not impacted by chronic treatment with the EE+LEVO combination or LEVO alone.

To determine if EtOH drinking influenced nicotine consumption, we next compared nicotine SA data between the EtOH group and water control group for each hormone treatment (this analysis was also conducted on saline consumption in the EtOH saline control groups, see S2 and Figure S2–4). In vehicle-treated rats, LME analysis showed a main effect of EtOH on nicotine consumption, indicating that the EtOH group consumed less nicotine compared to the water control group in the absence of contraceptive hormones (Figure 3B; F1,17 = 4.9, p<0.05). LME showed no main effect of session on nicotine consumption (Figure 3C; F1,17 = 3.7, p>0.05). Unlike the vehicle group, the EE+LEVO group showed no main effect of EtOH experience (Figures 3D; F1,16.8 = 1.7, p>0.05). There was, however, a main effect of session (Figure 3E; F1,16.8 = 5.8, p<0.05), indicating that nicotine consumption escalated throughout SA experiments. In LEVO-treated rats, LME showed no main effect of EtOH-experience (Figures 3F; F1,16 = 0.5, p>0.05) or session (Figure 3G; F1,16 = 2.7, p>0.05) on nicotine consumption. Finally, LME showed no main effect of hormone treatment (F2,49.8 = 2.9, p>0.05) or EtOH experience (F1,49.8 = 1.1, p>0.05) on active lever discrimination in all groups, and all groups showed lever discrimination above 66.67% (Figures 3H,I), demonstrating that all rats learned the task regardless of hormone treatment. Together, these results indicate that EtOH use decreases consumption of nicotine when taken in a sequential pattern, but this effect again is occluded by chronic treatment with synthetic contraceptive hormones.

Figure 3. EtOH Sequential Use Decreases Nicotine Consumption, which is Occluded by Contraceptive Hormone Treatment.

Figure 3.

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(A) The timeline of experimental procedures. Red box indicates nicotine self-administration (SA) data collection for current figure during Phase 2. (B) A main effect of EtOH drinking on nicotine sequential use was found in the vehicle treatment group whereas rats co-using nicotine consumed less EtOH (individual values represent average consumption across animals on each session; *p<0.05). (C) Nicotine consumption on days 1–15 of nicotine SA in vehicle-treated rats. (D) No main effect of EtOH drinking on nicotine consumption was found in the EE+LEVO treatment group (individual values represent average consumption across animals on each session; p>0.05). (E) Nicotine consumption on days 1–15 of nicotine SA in EE+LEVO-treated rats. (F) No main effect of EtOH drinking on nicotine consumption in the LEVO treatment group (individual values represent average consumption across animals on each session; p>0.05). (G) Nicotine consumption on days 1–15 of nicotine SA in LEVO-treated rats. (H) Percent active lever pressing did not differ as a function of hormone treatment during nicotine SA in either the water or (I) EtOH groups. The dotted line represents a 66.67% active lever pressing criterion (or a 2:1 ratio using the following equation: active/active+inactive).

3.3. Phase 2: Nicotine Demand

Rats that underwent nicotine SA also underwent a subsequent within-session nicotine demand procedure following acquisition (Figure 4A). The NLME model specified here allows for demand curves to be generated for each group (Figure 4B) as well as for each rat across each day (Figures S2–5–7). The model characterized both the group- and individual-level data well. Fixed-effect estimates of change in demand elasticity (α) and demand intensity (Q0) were used to examine experimental effects. NLME revealed a significant main effect of day on Q0 (Figure 4C; F1,2352= 8.4, p<0.05) and α (Figure 4D; F1,2352= 9.7, p<0.05). Across days, Q0 tended to increase while α tended to decrease (reflecting greater valuation). In addition, there was a main effect of EtOH-experience (Figure 4D; F1,2352= 5.6, p<0.05) and hormone (Figure 4D; F1,2352= 4.1, p<0.05) on α. Post-hoc multiple pairwise comparisons revealed no significant differences between specific groups (p>0.05), suggesting that while a significant main effect exists, more power may be needed to determine significant pair-wise effects. No significant main effects of EtOH-experience (Figure 4C; F1,2352=0.4, p>0.05) or hormone (Figure 4C; F1,2352=1, p>0.05) were found on Q0. NLME revealed that in animals receiving EE+LEVO treatment, Q0 (Figure 4E; r=0.424, p<0.05) and α (Figure 4F; r=−0.389, p<0.05) were significantly correlated with water consumption. However, no significant correlation was found between either α or Q0 with EtOH consumption in animals treated with EE+LEVO (Figure 4E,F; p>0.05). Finally, no significant correlation was found between α or Q0 and consumption of either EtOH or water in animals treated with LEVO alone or vehicle (Figure 4E,F; p>0.05).

Figure 4. Hormone Treatment and EtOH Experience Influence Nicotine Demand.

Figure 4.

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(A) The timeline of experimental procedures. Red box indicates data collection for current figure. (B) Population demand curves for each hormone group and drug treatment (EtOH vs water). Faded lines represent individual animal curves, and darker lines represent group averages. Dotted lines = water control, solid lines = EtOH groups. (C) Estimates for Q0. NLME revealed a main effect of day on Q0 (p<0.05). (D) Estimates for α. NLME revealed a main effect of day (p<0.05), EtOH experience (p<0.05), and hormone (p<0.05) on α. (E) Correlation of daily Q0 estimate over five days with EtOH and water consumption. Q0 was significantly correlated with water consumption in animals treated with EE+LEVO (p<0.05). (F) Correlation of daily α estimate over five days with EtOH and water consumption. α was significantly correlated with water consumption in animals treated with EE+LEVO (p<0.05).

3.4. Phase 3: Post-Nicotine EtOH Consumption and Blood EtOH

Two-Bottle Choice Test.

To determine the effect of the removal of nicotine on EtOH consumption and preference, both EtOH and water control groups underwent 3 additional days of EtOH 2-bottle preference testing (for nicotine SA rats, this began on the day following completion of nicotine demand procedures; for saline SA rats, this occurred on the same day of the timeline as nicotine SA groups but did not follow any demand procedures, Figure 5A). LME analysis was first conducted on EtOH consumption between previous EtOH and water groups (Figure 5B). LME revealed no significant main effect of group (F1,70 = 3.1, p>0.05), but there was a significant main effect of session (F1,70 = 27.9, p<0.05), indicating that EtOH consumption increased across time. LME analysis was next conducted on EtOH preference relative to indifference (i.e., distribution of consumption set to 50%). Results showed that EtOH preference was significantly above 50% both for the EtOH (Figure 5C; F1,23.6 = 164.4, p<0.05) and the water control group (Figure 5C1,C2; F1,46 = 25.9, p<0.05), indicating that after nicotine SA, rats prefer EtOH over water regardless of prior EtOH experience. Although EtOH and water control animals both preferred EtOH over water, LME revealed a main effect of group whereas EtOH animals had a stronger preference for EtOH over water control animals (Figure 5C2; F1,73 = 5.4, p<0.05). Finally, the consumption of EtOH before nicotine sequential use (from Phase 1) to the ratio of EtOH consumption/water consumption after nicotine sequential use was compared to determine if preference for EtOH after nicotine SA was related to their average EtOH consumption before nicotine SA. Linear regression analysis showed a positive correlation between pre-nicotine EtOH consumption levels and post-nicotine EtOH/water consumption ratios (Figure 5D; R2 = 0.11, p<0.05), indicating that consumption patterns of EtOH are related before and after nicotine consumption and consumption of EtOH is related to EtOH preference over water.

Figure 5. EtOH Drinking and Preference Persists after Completion of Nicotine SA.

Figure 5.

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(A) The timeline of experimental procedures. Red box indicates data collection for current figure (Phase 3). (B) Past EtOH experience did not affect amount of EtOH consumed as compared to water-experienced rats during two-bottle preference tests (p>0.05), however, there was a significant main effect of session, indicating that EtOH consumption increased across time (p<0.05). (C1) Past EtOH experience did not affect percent of EtOH consumption during two-bottle preference tests (individual values represent average percent EtOH consumption across animals on each preference session; p>0.05). (C2) Percent EtOH consumption in EtOH-experienced and water control rats for days 1–3. *p<0.05; main effect of group. (D) EtOH to water consumption ratio from post-nicotine or saline SA two-bottle EtOH preference tests was positively correlated to pre-nicotine SA EtOH consumption (*p<0.05). (E) BEC was significantly correlated with EtOH consumption both after 30 minutes (black) and after 240 minutes (red) of DID (p<0.05).

Blood EtOH Levels.

Blood EtOH concentration (BEC) levels were measured to determine if they were correlated with EtOH consumption at different timepoints within the 4-hr DID session. Prior studies have shown that rodents front-load their drinking in the beginning of DID sessions, which is evidence of motivation to drink EtOH. Thus, we collected blood via the tail at 30-minute and 4-hr (240-minute) timepoints on different days. There was a positive correlation between BEC and EtOH consumption (Figure 5E; R2= 0.34, p<0.05) at 30 mins as well as a positive correlation at the 240-minute timepoint (Figure 5E; R2=0.49, p<0.05). These results show that rats drank EtOH throughout the session.

4. Discussion

Here we show that ovary-intact Long Evans female rats consume stable amounts of EtOH and highly prefer EtOH over a water alternative after extended training using the DID procedure. We also show that EtOH consumption decreased when used sequentially with nicotine as compared to EtOH and saline co-use. Further, we are the first to show that treatment with both the EE+LEVO combination and LEVO alone eliminates the decrease in EtOH consumption when nicotine is used sequentially. Contrary to our hypothesis, EtOH-experienced ovary-intact female rats consumed less nicotine as compared to water controls, which was occluded by LEVO treatment both independently from and interactively with EE. Also contrary to our hypothesis, LEVO treatment alone did not reduce nicotine consumption in water control animals, despite clinical evidence that progesterone, which is also in the progestogen family, reduces smoking-related behavior in women (Sofuoglu et al., 2001). However, LEVO is a synthetic steroid hormone that is more structurally similar to testosterone than progesterone and thus may have very different impacts on nicotine-related outcomes. To our knowledge, we are the first to manipulate nicotine dose in animals chronically treated with EE+LEVO, LEVO, or vehicle.

As mentioned above, we show differences in demand elasticity between hormone and drug treatment (see Figure 4). It must be noted this is the first study to look at the effects of synthetic hormones and EtOH sequential-use on nicotine demand and with no a priori information, these data are preliminary. We also show that prior to nicotine SA, rats acquired EtOH drinking and preferred EtOH over water during a two-bottle preference test. Further, we show that water control animals without a long history of EtOH drinking experience also showed a strong preference for EtOH over water when nicotine SA ceased. Finally, BEC measurements taken at two separate time-points revealed that amount of EtOH consumed was positively correlated with BEC.

Sequential Use of Nicotine and EtOH: Synergizing with Clinical Findings

Surprisingly, sequential-use of nicotine and EtOH decreased consumption of each other in rats. Contrary to current preclinical findings, evidence from clinical populations of comorbid nicotine and alcohol use indicates a potential positive correlation between alcohol and nicotine consumption (King et al., 2009; Piasecki et al., 2011; Piasecki et al., 2008; Piasecki et al., 2012; Shiffman et al., 2007). Human laboratory studies that manipulate drug exposure consistently report that alcohol use increases nicotine and cigarette SA (Blomqvist et al., 1996; McKee et al., 2006; Mitchell et al., 1995), suggestive of a complimentary economic relationship. Importantly, the converse effects of nicotine on alcohol consumption are less clear. Specifically, studies showed that nicotine either enhanced (Acheson et al., 2006; Barrett et al., 2006), decreased (Acheson et al., 2006; McKee et al., 2006), or did not change (Udo et al., 2013) alcohol SA. In most of these studies, however, the latency between use of the two drugs is relatively short. For example, in one study, alcohol was administered 3 min prior to the first cigarette administration (Barrett et al., 2006) and thus it is unlikely that alcohol metabolic processes occurred between consumption of the two drugs.

Similar to clinical data of nicotine and alcohol co-use, results from preclinical studies are mixed. While the majority of preclinical studies show nicotine decreases consumption of EtOH (Blomqvist et al., 1996; Clark et al., 2001; Hauser et al., 2012; Lê et al., 2003; Olausson et al., 2001; Smith et al., 1999; Tolu et al., 2017), others show the opposite effect (Dyr et al., 1999; Hauser et al., 2012; Nadal et al., 1998; Sharpe and Samson, 2002). These studies are designed so that only EtOH is self-administered while nicotine is experimenter-administered (usually via injection). Here, we utilized a sequential use model in which rats self-administered both EtOH and nicotine, which models human nicotine and alcohol sequential use. The few studies that have utilized SA for both nicotine and EtOH have shown similar results to what we see here (Chandler et al., 2020; Lê et al., 2014; Lê et al., 2010). When given an EtOH 2-bottle preference test at the same time as a nicotine two-lever SA, female rats show significant decreases in EtOH consumption at the onset of nicotine SA (Chandler et al., 2020; Maggio et al., 2018a; Maggio et al., 2018b). In addition, EtOH drinking only increased as the response schedule for nicotine increased (Chandler et al., 2020; Maggio et al., 2018b; i.e., EtOH drinking increased as the unit price of nicotine increased (i.e., when nicotine dose decreased), similar to our current findings). Together, it is possible that nicotine and EtOH act as substitute reinforcers for each other within the procedural parameters tested to date in preclinical models of co-use. In support, the current data demonstrate that, much like the effects of an open economy manipulation, when an alternative reinforcer is introduced (i.e., nicotine) EtOH consumption significantly decreased, when EtOH was absent as an alternative reinforcer, nicotine demand was increased, and when access to the previously trained nicotine reinforcer is omitted, animals with no prior EtOH training strongly prefer EtOH over a water alternative. Although additional studies are needed to determine the exact economic relationship between these two reinforcers, our results here are consistent with and support a potential economic substitution effect, while also suggesting that sex hormone signaling may mediate such effects.

Here, consumption of EtOH occurred throughout the 4-hr DID session, and nicotine SA occurred immediately following the DID session. Thus, the duration of time between onset of EtOH consumption and initiation of nicotine SA likely resulted in some metabolism of EtOH prior to nicotine SA. This may be a critically different feature of our paradigm as compared to human laboratory studies in which the latency between when the two drugs are consumed is within minutes (Barrett et al., 2006), as acetaldehyde is a metabolite of EtOH that has abuse potential (Amit and Smith, 1985; Aragon et al., 1986; Hoffman and Evans, 2013) and is also a metabolite of burning tobacco products (Hoffmann et al., 2001). Thus, our contrary results showing decreases in consumption of the two drugs in the sequential use condition may reflect an important aspect of the clinical condition not captured in human laboratory studies whereby people consume EtOH at longer intervals prior to nicotine use. It is important to note that not all individuals who engage in alcohol and nicotine co-use do so concurrently (Harrison et al., 2009; Jackson et al., 2010), and various patterns of sequential use occur in which EtOH and nicotine may occur prior to use of the other. Thus, future studies are needed to model different iterations of co-use to better tailor to specific clinical patterns of use, and also examine contributions of EtOH metabolites to subsequent nicotine use.

Potential Biological Interactions of Contraceptive Hormones and Nicotine/EtOH Sequential Use

Here we show that chronic exposure to LEVO independently and interactively with EE occludes the ability of nicotine to decrease consumption of EtOH. Although metabolism outcomes were not measured here, there is a body of literature which may support metabolic interactions between these substances of abuse and steroid hormones. In clinical populations, alcohol consumption is associated with higher levels of endogenous estrogens as well as androstenedione and testosterone (Hartman et al., 2016; Playdon et al., 2018; Sarkola et al., 2000). Relatedly, nicotine results in enhanced estrogen metabolism, which has clinical relevance as women who smoke that are undergoing hormone replacement therapy require higher estrogen doses for therapeutic efficacy (Tansavatdi et al., 2004). In addition, EE increases gene expression of the acetaldehyde dehydrogenase A2 subfamily, which metabolizes alcohol (although not tested in brain tissue; Naciff et al., 2005). EE is metabolized by cytochrome P450 3A (CYP3A; Lin et al., 2002), which is part of a family of enzymes that also metabolize EtOH. Another interesting potential future direction involves interactions between LEVO and EtOH, as chronic EtOH treatment prior to LEVO treatment decreases the half-life of LEVO, and plasma levels of LEVO have been shown to drop dramatically following EtOH (when administered in the diet) as compared to LEVO given in the absence of chronic EtOH (Gomaa et al., 1984). Future studies are needed to determine if chronic EtOH drinking alters LEVO metabolism.

Taken together, it is possible that EE and LEVO may impact metabolic pathways of EtOH when used with nicotine, and this may underlie changes in patterns of EtOH consumption induced by EE exposure. Future studies are needed to evaluate these potentially critical and translationally impactful metabolic interactions. However, it should be noted that an EE-alone group was not included here given the increased risk of reproductive health issues associated with chronic unopposed EE treatment, and thus we cannot rule out the possibility that these effects were driven by EE.

Limitations of the Current Study

In the current study, we evaluated EtOH and nicotine use in a sequential model, however, individuals at the clinical level can also use these substances simultaneously or in other patterns. One inherent challenge in modeling polysubstance use at the preclinical level is that there is a wide array of permutations in which humans use multiple drugs (Crummy et al., 2020), and thus accurately modeling each of these patterns in one model is not possible. However, it is important that the field continues to examine different types of co-use patterns to better understand the clinical condition. It is also important to note that in the post-nicotine SA preference testing portion of the current study, rats no longer received hormone treatments on the days of testing, and thus a limitation of the current study is that we did not evaluate these data as a function of hormone treatment group. However, these data provide supportive evidence that nicotine and EtOH act as economic substitutes. We also did not analyze BEC as a function of hormone treatment, which is an important future direction to determine if contraceptive hormones influence ethanol metabolism. We also were not able to evaluate EtOH drinking patterns throughout the 4-hr DID sessions as a function of contraceptive hormone treatment or nicotine SA, which is a limitation to the current study, and which should be evaluated.

It is important that we note other limitations to our current study. On day 1 of Phase 1, water drinking was elevated, but quickly declined across the rest of the sessions. Data from this day were not omitted from analyses because it is not clear what caused the increase in water drinking on that day, and this was not systematically evaluated. However, it is possible that this increase in behavior could be meaningful, warranting further study. Further, we utilized an intravenous route of nicotine SA, whereas nicotine is typically consumed via other routes of administration (e.g., smoking). The pharmacodynamic differences in these routes of administration may impact outcome measures, and future studies should evaluate vaporized nicotine interactions with contraceptive hormones. Here we evaluated LEVO in combination with or independent from EE on nicotine and EtOH consumption. However, only one dose of each hormone was tested in the current study, and thus additional research is needed to determine if there are dose-dependent effects of these hormones on drug use outcomes. Further, an EE-alone group was not evaluated here. Although additional preclinical studies may reveal a relatively safe dose and length of EE treatment without a progestogen, potential detrimental health effects precluded the inclusion of this group in this study. Further bolstering a translational justification against its inclusion, only one clinical study to our knowledge evaluated short-term estradiol treatment in uterus-intact women, and showed no health benefits on the primary outcome measure (in Alzheimer’s disease) and also reported a high attrition rate often due to vaginal bleeding or worsening of dementia symptoms (Wharton et al., 2011).

Conclusions and Future Directions

We report the first study showing that chronic treatment with LEVO alone or in combination with the most common synthetic estrogen found in oral contraceptives, EE, occludes the ability of nicotine to decrease EtOH SA. This is significant because there are no other studies to date that have examined these interactions, which may have meaningful translational value to women who use synthetic contraceptive hormones and who also drink alcohol and use nicotine-containing products. Our results lay a foundation upon which future studies can evaluate mechanistic impacts of contraceptive hormone use on alcohol and nicotine sequential use. Given the unique reproductive experiences of women, as well as this highly prevalent polysubstance use pattern, it is important for future work to systematically evaluate how use of contraceptive hormones by women may impact use of these drugs.

Supplementary Material

1

Highlights.

  • The synthetic hormones contained in oral contraceptives, ethinyl estradiol and levonorgestrel, impact nicotine and ethanol sequential use consumption patterns in ovary-intact female rats.

  • Nicotine and ethanol act as economic substitutes when examined in a sequential use model.

  • Ovary-intact female rats prefer ethanol over a water alternative following either nicotine self-administration or extended ethanol training in a drinking in the dark paradigm.

Acknowledgements.

We would like to thank Dr. Foster Olive for advice on ethanol bottle selection, as well as Mei Hong for technical assistance. We would also like to thank Dr. Heather Bimonte-Nelson for advice on hormone dose and administration parameters.

Funding and Disclosures.

This work was supported by the National Institutes of Health Grant DA044479, DA046526, DA049130, DA055879, and DA045881, DA058933 (to C.D.G) as well as a pilot grant from the University of Kentucky Ignite Program (to J.J.W. and C.D.G.). All authors have no disclosures to declare.

Footnotes

Competing Interests.

The authors have no competing interests to declare.

Declaration of Competing Interest

None.

Disclosures:

None.

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