Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2026 Feb 27.
Published in final edited form as: Alcohol. 2025 Aug 6;128:35–42. doi: 10.1016/j.alcohol.2025.07.004

Voluntary wheel-running reduces harmful drinking in a genetic risk model for drinking to intoxication

Kolter Grigsby a,b,c,*, Zaynah Usmani b,c, Amy E Chan b,c, Luis Tzab b,c, Justin Anderson b,c, Angela R Ozburn b,c
PMCID: PMC12939583  NIHMSID: NIHMS2134779  PMID: 40780376

Abstract

Physical activity (PA) may provide an effective and equitable treatment option for addressing the harm associated with Alcohol Use Disorders (AUDs). Wheel-running (WR) – a well characterized rodent model of PA – reduces intake and craving for many drugs of abuse; however, its effects on models of harmful ethanol intake are mixed. This may in part be due to critical differences in drinking paradigm, genetics background, chronicity of ethanol, and the modality and duration of PA being tested. To compliment and extend prior work, we evaluated whether key stages of PA development would differentially reduce binge-like ethanol drinking in inbred High Drinking in the Dark (iHDID-1) mice, a unique genetic risk model for drinking to intoxication. AUD is a chronic, relapsing disorder. To better reflect this condition, adult female and male iHDID-1 mice underwent a chronic (4-weeks) “Drinking in the Dark” (DID) protocol – a model of binge-like ethanol drinking - along with a locked running (to control for the effect of novelty). Early stages of PA evoke much higher signs of physiological and neurological stress than more chronic, habitual stages of PA. Therefore, we tested whether acute WR (1-week) altered ethanol intake differently than chronic WR (4-weeks). Here, we found that both acute and chronic WR reduced ethanol intake in female and male iHDID-1 mice. To evaluate whether the effect of PA was specific to ethanol, we further tested whether acute WR reduced water intake in the DID protocol. Analysis revealed that male WR iHDID-1 mice had greater water intake than wheel-locked controls. Moreover, WR during the time of DID was positively correlated with water intake, but not ethanol intake, suggesting WR and DID are not competing behaviors. Taken together, these findings offer support for the role of PA as a meaningful intervention strategy for reducing harmful drinking and emphasize the need to explore the underlying neurobiological mechanisms as a means of guiding PA as an adjunctive therapy for AUD.

1. Introduction

Alcohol use disorders (AUDs) pose significant public health and economic challenges in the United States and abroad (Glantz et al., 2020; Witkiewitz et al., 2019). Binge drinking, characterized by excessive alcohol consumption within a short period of time, contributes significantly to the development and severity of AUDs and remains the most common, costly, and harmful pattern of alcohol use (Molina & Nelson, 2018). There have been outstanding advances in pharmacological and psychological approaches for managing AUDs (Connor et al., 2016; Grigsby et al., 2023); however, there remains a clear and urgent need to identify attainable, holistic, and equitable treatment options (Ozburn & Spencer, 2023). Here, we explore the efficacy and therapeutic potential of physical activity (PA) to reduce ethanol intake in a unique genetic risk model for drinking to intoxication, the inbred High Drinking in the Dark (iHDID-1) mouse line.

PA is well positioned to reverse the many health consequences and comorbid health problems associated with excessive drinking, including cardiometabolic health, cognitive function, sleep disturbances, and mental health disorders (Lardier et al., 2021; Leasure et al., 2015; Stoutenberg et al., 2016). Moreover, it follows that PA interventions have the potential to address broader facets of harmful drinking than pharmacological and behavioral therapies alone. Population-based studies indicate a positive relationship between PA levels and alcohol intake across moderate drinkers, while non-drinkers and heavy drinkers tend to be less physically active (Buscemi et al., 2011; Conroy et al., 2015). This suggests healthy PA levels may promote moderate alcohol intake and offer a path toward harm reduction. Clinical studies as early as 1982 have shown the utility of PA to improve overall health in those suffering from an AUD, wherein a 12-week fitness program (consisting of 60-min of structured, daily PA) was shown to reduce abstinence rates in treatment seeking individuals (Sinyor et al., 1982). While significant work underscores the therapeutic capacity of PA to treat the negative physical and mental health effects of alcohol misuse, few have directly reported a reduction in intake in response to PA (Lardier et al., 2021). A primary goal of the present work is to investigate the effect of voluntary PA on binge-like drinking in mice with a history of chronic excessive alcohol drinking as a means of better guiding effective PA interventions in the future.

Wheel-running (WR) – a well characterized rodent model of voluntary PA – reduces self-administration and craving for many drugs of abuse; however, its effects on alcohol intake are mixed (Leasure et al., 2015). Determining whether PA alters behavioral measures of ethanol intake and preference has been a topic of interest in biomedical research for several decades (Duncan & Baez, 1981; Ehringer et al., 2009; Ozburn et al., 2008; Werme et al., 2002). Evidence shows that WR reduces ethanol preference and intake in 24-hr access models, but has little effect on limited access drinking in C57BL/6J mice (Buhr et al., 2021; Ehringer et al., 2009; Ozburn et al., 2008). For instance, WR was found to reduce continual ethanol consumption and preference, but not binge-like ethanol drinking in female C57BL/6IBG mice (Ehringer et al., 2009). Alternating weekly WR access was shown to have no effect on ethanol intake in female C57BL/6J mice with a history of drinking (Ozburn et al., 2008). In contrast, Booher et al. found that 17–20 days of WR prior to drinking reduced 2 bottle-choice (2BC) intake in male C3H/Ibg mice, but not female C3H/Ibg or 129/SvEvTac mice (of both sexes; Booher et al., 2019). Together, these findings indicate sex specific differences in the ability of WR to reduce ethanol intake and further highlight the major gaps in our understanding of the effect of voluntary PA on harmful ethanol intake across sex, strains, drinking paradigms, and other behavioral conditions (i.e., PA and alcohol duration). The present work complements and significantly expands on previous research by determining whether acute or chronic WR reduces binge-like ethanol intake in female and male iHDID-1 mice.

Widely adopted models of PA in rodents, such as treadmill running and forced swimming, are known to increase hypothalamic-pituitary-adrenal axis (HPA) activity and other measures of stress (Dal-Zotto et al., 2000; Kelliher et al., 2000). Although less stressful than forced models, acute wheel activity has been shown to increase plasma corticosterone levels (a marker of HPA activity) after 1-week of voluntary WR in rats, but not after 4-weeks (Fediuc et al., 2006; K. B. Grigsby et al., 2022). This suggests that voluntary PA increases the stress response in the short term, but not when performed habitually. Given the physiological stress of acute WR (not seen in chronic WR) and a well-established role of stress in facilitating harmful drinking, the present work further tested whether chronic WR, which is behaviorally reinforcing, reduces binge-like ethanol drinking to a greater extent than acute WR in female and male iHDID-1 mice (Fediuc et al., 2006; Greenwood et al., 2011; Grigsby et al., 2019, 2022).

Exercise adherence remains a significant barrier in PA intervention strategies for all chronic disease, including AUDs (Welford et al., 2023). To model the therapeutic potential of PA to reduce harmful drinking in humans with AUD, we evaluated whether acute (1-week) or chronic (4-weeks) WR would differentially reduce binge-like drinking in iHDID-1 mice with a history (4-weeks) of binge-like drinking. By integrating important features of PA and harmful drinking in the context of a genetic risk model for drinking to intoxication (and carrying out studies using both sexes), the present work lays the foundation for elucidating novel pathways underlying the ability of PA to reduce harmful drinking.

2. Materials & methods

2.1. Animals

Adult male and female inbred High Drinking in the Dark (iHDID-1; S26:G28-32) mice were used for all experiments. HDID-1 mice were initially selectively bred to drink ethanol to intoxication and then inbred to maintain this phenotype (Crabbe et al., 2009, 2019). The iHDID-1 colony is maintained within the VA Portland Healthcare System Veterinary Medical Unit, where they are group-housed, bred, and maintained on a reverse 12-h light/dark cycle with lights off at 07:30 (Pacific Standard Time [PST]). Animals were moved to their behavioral testing room one week prior to testing to habituate them to individual housing, new sipper tubes, and a shifted light/dark cycle. Light cycles were as follows: Experiments 1 and 3 (08:20 lights off - 20:20 lights on PST); Experiment 2 (08:20 lights off - 20:20 lights on PST [H2O drinkers] and 09:20 lights off - 21:20 lights on PST [EtOH drinkers]; of note — testing was conducted in separate experimental rooms). All animals remained individually housed throughout the duration of the study. Mice had ad libitum access to water and Purina 5LOD chow (PMI Nutrition International, Brentwood, MO, USA), and were housed on Bed-o’ cobs® bedding (The Andersons, Inc., Maumee, OH, USA) in standard polycarbonate cages with stainless steel wire tops. All procedures were approved by the VA Portland Health Care System Animal Care and Use Committee and were conducted in accordance with NIH Guidelines for the Care and Use of Laboratory Animals.

2.2. Baseline ethanol (or water control) “Drinking in the Dark”

To establish a history of chronic binge-like drinking, male and female iHDID-1 mice (N = 96; n = 12/fluid type/wheel condition/wheel-running time point/sex) underwent 4-weeks of the limited access 4-day “Drinking in the Dark” (DID) paradigm with either 20 % ethanol or tap water. The DID paradigm models binge-like drinking and consists of 4 consecutive days of drinking per week, where 3-h into the dark cycle, fluid is available for 2-h on days 1–3 and 4-h on day 4 (as performed in Rhodes et al., 2005). HDID mice were selectively bred to reach intoxicating blood ethanol concentrations following a 4-h DID (Crabbe et al., 2009, 2014). All animals also received a locked running wheel, to control for the effect of novelty (Grigsby et al., 2024)

2.3. Experiment 1 and 2: effects of acute wheel running on Drinking in the Dark

To test the effects of acute wheel-running on binge-like ethanol drinking, half the mice were granted unlimited access to unlocked running wheels for 1-week following the 4-week baseline drinking period. Wheel access was given alone (i.e., in the absence of DID testing) in week 5 to model the effect of an acute PA intervention on harmful drinking (week 6; Fig. 1a). Moreover, this allowed for the opportunity to evaluate WR characteristics in response to chronic harmful drinking compared to DID water intake (Experiment 2). More information about DSC (“Dependable, Simple, Cost-effective”) wheel design, assembly, and data collection is available in Grigsby et al., 2024; ). All unlocked wheels were connected to an Arduino Uno where activity was continuously recorded. Data from wheel-running animals was collected and saved every morning prior to the beginning of their dark cycle during each experiment.

Fig. 1.

Fig. 1.

Open in a new tab

Experiment 1 – Acute wheel-running (WR) reduces binge-like ethanol intake in female and male iHDID-1 mice. a) Timeline for experiment 1; WL (wheel-lock) and DID (“Drinking in the Dark”). b) 4-week baseline EtOH intake; no significant effects. c) EtOH intake (g/kg) during week 6 (running wheels unlocked during drinking); main effect of wheel condition [F(1,30) = 8.45; p < 0.01], no effect of sex or wheel condition x sex interaction. d) Blood ethanol concentration (BEC; mg%) following 4-h intake on day 4 of DID; no significant effects. Dotted line denotes threshold for intoxication (80 mg%). e) Average daily WR distance during DID; no significant effects. (n = 8/sex/wheel condition). ** = p < 0.01.

In the 6th week (the second week of WR; Fig. 1a), iHDID-1 mice were given voluntary wheel access alongside a 4-day DID test (compared to WL controls). During week 6, a 4-day 20 % ethanol DID (and water DID in Experiment 2) was conducted to test the effects of acute wheel-running on binge-like ethanol intake and physiological intoxication [blood-ethanol concentration (BEC)]. Access on day 4 was extended to 4-h to reflect prior comparable testing procedures in iHDID-1 mice and to evaluate whether the suppressive effect of PA on ethanol intake would persist under conditions of prolonged access. To measure BEC, 20 μL periorbital blood samples were collected from ethanol-drinking animals after the last 4-h drinking period during acute WR. Blood samples were processed, and ethanol was quantified as in Finn et al., 2007; Finn et al., 2007). Water-drinking animals were similarly scruffed (but no blood was collected) to control for handling during the periorbital sampling procedure.

2.4. Experiment 3: effects of chronic wheel running on Drinking in the Dark

Following the 4-week baseline drinking period, half the mice were granted 24-h access to their newly unlocked DSC-wheel for 4-weeks to model the effects of chronic PA interventions on harmful ethanol intake in humans with a history of harmful drinking. On the basis there was no reduction in water intake in response to acute wheel-running, a water group was not tested in the present experiment. Data from wheel-running animals was collected and saved prior to the beginning of their dark cycle. During week 8 (fourth week of WR; Fig. 4a), a 4-day 20 % ethanol DID was conducted to test the effects of chronic wheel-running on binge-like ethanol intake and physiological intoxication. Periorbital blood samples were taken from ethanol-drinking animals after the last 4-h drinking period during chronic WR to determine BEC (as described above).

Fig. 4.

Fig. 4.

Open in a new tab

Experiment 3 – Chronic WR reduces binge-like ethanol intake in female and male iHDID-1 mice. a) Timeline for experiment 3. b) 4-week baseline EtOH intake; no significant effect. c) EtOH intake (g/kg) during week 8 (running wheels unlocked during drinking); main effect of wheel condition [F(1,29) = 4.37; p < 0.05], no effect of sex or wheel condition x sex interaction. d) Blood ethanol content (mg%) immediately following 4-h drinking on day 4 of DID; no significant effects. e) Average daily WR distance during DID; no significant effects. (n = 8 iHDID-1/sex/wheel condition). * = p < 0.05.

2.5. Statistics

All statistical analyses were conducted with GraphPad Prism Software Version 9.0 (Graphpad Software, San Diego, CA) and RStudio (version 06.2.561). The sample sizes for each experiment are reported in the appropriate figure legend. If no significant main effect of, or interaction with, sex were observed, we performed statistical analyses on data collapsed across sexes. Baseline fluid intake during weeks 1–4 was analyzed using a two-way ANOVA (sex x day) for the first 2-h of DID days 1–4. DID intake during acute and chronic WR (weeks 6 and 8, respectively) was analyzed using a three-way repeated measures ANOVA (sex x wheel condition x day; for the first 2-h of DID on days 1–4). Total 4-h fluid intake on day 4 of DID during acute and chronic WR (weeks 6 and 8, respectively) was analyzed separately using a two-way ANOVA (sex x wheel condition). Average daily running distance (km/day), duration (active minutes/day; which we defined as the lower quartile value of wheel rotations/minute), and speed (km/hr; only during active minutes) were analyzed using ‘R’ (https://github.com/grigsbkb/Dependable-Simple-and-Cost-effective-DSC-running-wheel) and further analyzed via three-way RM ANOVAs in GraphPad (sex x fluid x day). If a mouse did not run for at least 20 active minutes in one day, the data from that day was excluded from analyses. This cutoff was implemented to minimize the inclusion of data from broken/offline wheels, and to reflect adult human PA guidelines more accurately (~20–40 min/day; US Department of Health and Human Services, 2018). Significant interactions were followed up with Šidák post-hoc testing. For both fluid and wheel-running data, a mixed-effects analysis was used in place of an ANOVA when data points were excluded or missing, in which case Tukey post-hoc testing was used. All values are presented as mean ± standard error (SE) and significance is set at an alpha value of 0.05 (p < 0.05).

3. Results

3.1. Experiment 1: acute wheel-running reduces binge-like ethanol intake in iHDID-1 mice

To assess the effects of acute wheel-running on binge-like ethanol drinking in female and male iHDID-1 mice, a 4-day DID test was administered during week 6 following 4-weeks of ethanol baseline drinking (Fig. 1b) and one week of WR with only home cage water bottles (week 5; supplemental fig. 1a). A mixed-effects analysis of 2-h ethanol intake (Days 1–3 and 0–2hr on Day 4) during week 6 revealed a main effect of wheel condition on intake [F(1,30) = 8.45; p < 0.01], where WR iH-DID-1 mice consumed less ethanol than wheel locked controls (Fig. 1c). To determine the effect of WR during a longer duration of ethanol access, the results of day 4 were analyzed separately. A two-way ANOVA of total 4-h drinking on day 4 of ethanol DID in week 6 revealed no significant effects. Similarly, there was no effect of wheel condition on BECs, nor was there an effect of sex on average daily running distance (km) during DID (Fig. 1d & e).

3.2. Experiment 2: acute wheel-running reduces binge-like ethanol intake in iHDID-1 mice, but not water intake

To ensure that the observed reduction in ethanol intake could be replicated, and was not due to WR and DID being competing behaviors, an identical experiment was conducted at the acute WR timepoint with the addition of a water control DID group. Following 4-weeks of baseline drinking (20 % ethanol, or water; Fig. 2a and d) and one week of WR with access to water (week 5; supplemental Fig. 1b), a two-way RM ANOVA of the first 2-h of each ethanol DID day during week 6 revealed a main effect of wheel condition [F(1, 32) = 12.08; p < 0.01], where WR mice consumed less ethanol than their wheel-locked counterparts (Fig. 2b). A two-way ANOVA of total 4-h drinking on day 4 of DID revealed no main effects or interaction of sex or wheel condition. Like experiment 1, there was no significant effect of wheel condition on BECs (Fig. 2c).

Fig. 2.

Fig. 2.

Open in a new tab

Experiment 2 – Acute WR reduces limited access ethanol intake, but not water intake in female and male iHDID-1 mice. Note: the same experimental design as experiment 1, with the addition of a water DID group. a) 4-week baseline EtOH intake; no significant effects. b) EtOH intake (g/kg) during week 6 (running wheels unlocked during drinking); main effect of wheel condition [F(1,32) = 12.08; p < 0.01]. c) Blood ethanol concentration (BEC; mg%) immediately following 4-h intake on day 4; no significant effects. d) 4-week baseline water intake; no significant effects. e) H2O intake (ml/kg) during week 6 (running wheels unlocked during drinking); interaction effect of sex x wheel condition [F(1,30) = 6.91; p < 0.05]. Tukey post-hoc test reveals that male WR animals consumed significantly more water than male WL animals (p < 0.05). f) Average daily WR distance during DID; no significant effects. (n = 8–9/sex/fluid/wheel condition). ** = p < 0.01.

A mixed-effects analysis of the first 2-h of water intake during week 6 revealed no main effect of wheel condition (Fig. 2e). A two-way ANOVA of total 4-h drinking on day 4 of DID during week 6 revealed a significant sex x wheel condition interaction on water consumption [F(1,30) = 6.91; p < 0.05]. A Tukey's post-hoc test showed that male WR mice consumed significantly more water than male mice with a locked wheel (p < 0.05; Fig. 2e). There were no significant differences in average daily running distance (km) among male and female ethanol-drinking animals or water-drinking animals during DID (Fig. 2f).

3.3. Experiment 2: WR during DID is positively correlated with DID water intake, but not ethanol intake

To further explore the relationship between WR and DID intake in week 6, we performed Pearson’s correlation tests of water (mL/kg/2 or 4hrs) or 20 % ethanol (g/kg/2 or 4hrs) intake across all 4 days of DID with the number of active minutes (active minutes/2 or 4hrs) and hourly running distance (km/2 or 4hrs) during the time of DID. Analysis of hourly running data (3-way ANOVA for fluid x sex x time) found no effect of sex on days 1–4; therefore, data was collapsed across sex. There were no effects of time or fluid on the number of active minutes run on days 1–3 (Fig. 3a-c). A two-way ANOVA of number of active minutes between water and ethanol mice (of both sexes) revealed a main effect of time [F(2,47) = 4.4; p < 0.05] on day 4, with no main effect of fluid or time x fluid interaction (Fig. 3d). Pearson’s correlations for average number of active minutes run during the time of DID plotted against 2 or 4hr ethanol intake (g/kg) on days 1–4 revealed no significant correlations (Fig. 3e-h). Similarly, there were no significant correlations with water intake (mL/kg) on days 1–4 (Fig. 3e-h).

Fig. 3. Water intake is positively correlated with WR behavior.

Fig. 3.

Open in a new tab

a) Active minutes (min/hr) during DID on day 1; no significant effects. b) Active minutes (min/hr) during DID on day 2; no significant effects. c) Active minutes (min/hr) during DID on day 3; no significant effects. d) Active minutes (min/hr) during DID on day 4; significant effect of time [F(2,47) = 4.4; p < 0.05. e) Active minutes/2hrs plotted against 2hr ethanol intake (g/kg/2hrs; left y-axis; black circles) and 2 h water intake (ml/kg/2hrs; right y-axis, blue triangles) on day 1; no significant correlation. f) Active minutes/2hrs plotted against 2hr ethanol intake (g/kg/2hrs; left y-axis) and water intake (ml/kg/2hrs; right y-axis) on day 2; no significant correlation. g) Active minutes/2hrs plotted against 2hr ethanol intake (g/kg/2hrs; left y-axis) and water intake (ml/kg/2hrs; right y-axis) on day 3; no significant correlation. h) Active minutes/2hrs plotted against 4hr ethanol intake (g/kg/4hrs; left y-axis) and water intake (ml/kg/4hrs; right y-axis) on day 4; no significant correlation. i) Hourly running distance (km) during DID on day 1; no significant effects. j) Hourly running distance (km) during DID on day 2; interaction effect of hour x fluid [F(1,27) = 4.48; p < 0.05). k) Hourly running distance (km) during DID on day 3; main effect of fluid [F(1,27) = 5.47; p < 0.05). l) Hourly running distance (km) during DID on day 4; no significant effects. m) Distance (km/2hrs plotted against 2hr ethanol intake (g/kg/2hrs; left y-axis) and 2 h water intake (ml/kg/2hrs; right y-axis) on day 1; no significant correlation. n) Distance (km/2hrs) plotted against 2hr ethanol intake (g/kg/2hrs; left y-axis) and water intake (ml/kg/2hrs; right y-axis) on day 2; no significant correlation. o) Distance (km/2hrs) plotted against 2hr ethanol intake (g/kg/2hrs; left y-axis) and water intake (ml/kg/2hrs; right y-axis) on day 3; no significant correlation for ethanol intake; significant correlation for water intake (R2 = 0.25; p < 0.05). p) Distance (km/2hrs) plotted against 4hr ethanol intake (g/kg/4hrs; left y-axis) and water intake (ml/kg/4hrs; right y-axis) on day 4; no significant correlation for ethanol intake; significant correlation for water intake (R2 = 0.31; p < 0.05). (n = 6–9 iHDID-1/sex/wheel condition).

A two-way ANOVA of hourly running distance (km/hour) between water and ethanol mice (of both sexes) revealed a main effect of fluid [F(1,27) = 5.47; p < 0.05] on day 3 (Fig. 3k) and a interaction effect of hour x fluid [F(1,27) = 4.48; p < 0.05] on day 2 (Fig. 3j), with no other main effects or interactions for days 1 and 4 (Fig. 3i&l). Pearson's correlations for average 2 or 4hr running distance (km) plotted against 2 or 4hr ethanol intake (g/kg) on days 1–4 revealed no significant correlations (Fig. 3m-p). In contrast, running distance (km/2hrs) was correlated with concurrent water intake (mL/kg/2hrs) on day 3 (Fig. 3o). Similarly, 4hr distance was correlated with 4hr water intake on day 4 (Fig. 3p). These findings indicated a positive relationship between WR and water intake; however, this relationship does not appear to extend to ethanol intake in iHDID-1 mice.

3.4. Experiment 3: chronic wheel-running reduces binge-like ethanol intake in iHDID-1 mice

To determine the effects of chronic wheel-running on binge-like ethanol drinking in male and female iHDID-1 mice, a 4-day DID test was administered during week 8 (following 4 weeks of ethanol baseline drinking [Fig. 4b] and 3 weeks of WR or WL with only home cage water bottles [supplemental fig.1c]). A two-way RM ANOVA of the first 2 h of each day of DID during week 8 revealed a main effect of wheel condition on ethanol intake [F(1,29) = 4.37; p < 0.05], where WR iHDID-1 mice consumed less ethanol than those with a locked wheel (Fig. 4c). A two-way ANOVA of total 4-h drinking on day 4 of DID in week 8 revealed no significant effects. There was no effect of wheel condition on BEC, nor was there an effect of sex on average daily running distance (km) during DID (Fig. 4d & e).

4. Discussion

Finding non-invasive and equitable treatment options for AUD is critically important to help reverse the physical, economical, and psychosocial consequences of harmful drinking. The present work contributes to a growing field of research in search of adjunctive therapies, like PA. To ensure replicable and translatable outcomes, it remains important to rigorously test the capacity of PA to regulate alcohol intake across relevant behavioral and genetic models for AUD, and in both sexes. We provide evidence that acute and chronic access to voluntary wheel-running during periods of abstinence decreases subsequent binge-like ethanol intake in female and male iHDID-1 mice with a history of binge-like drinking. The reproducibility crisis of biomedical research has long been reflected in behavioral neuroscience, including preclinical models of alcohol intake (Crabbe et al., 1999). Therefore, finding that acute WR reduced 4-day binge-like ethanol intake in female and male mice in two independent experiments adds validity to the present work and helps establish a behavioral foundation from which to build from. Prior use of this genetic model of risk for drinking to intoxication has proven to be a powerful approach in the screening of potential pharmacotherapies for AUD (Crabbe et al., 2017, 2020; Grigsby et al., 2020, 2023; Ozburn et al., 2020; Pozhidayeva et al., 2020). Leveraging the current findings could help identify important neurobiological mechanisms underlying the relationship between PA and harmful drinking, and ultimately guide future PA-mediated interventions for AUD and its related symptomology.

Published data suggests that voluntary wheel access – whether provided continuously or for a limited time – does not alter binge-like ethanol drinking in C57BL/6 mice, a widely adopted and notably high drinking strain (Buhr et al., 2021; Ehringer et al., 2009). In contrast, we found that unlimited access to voluntary running wheels for 1–4 weeks during abstinence reduced subsequent binge-like ethanol intake in a genetic model of risk for harmful drinking. Our results parallel findings from McMillan et al., wherein wheel access reduced ethanol intake in alcohol preferring rats (P rats; an established genetic model of high ethanol preference and consumption) but not in non-preferring (NP) rats (McMillan et al., 1995). Collectively, these findings indicate that PA may be an effective adjunctive AUD therapy. Considering these data encompass genetic risk models, family history may play an important role – however, further work is needed to determine the effects of PA in non-selected controls, such as the Heterogenous/Northport (HS/Npt) mouse line, from which the (i)HDID were derived. Further, this work highlights the importance of testing PA, and other potential interventions, across several paradigms, species, and genetic backgrounds.

Prior research found that 2-weeks of voluntary wheel-running did not alter ethanol clearance rates in female or male mice, suggesting that PA-mediated reductions in ethanol intake are likely not due to altered metabolism (Ehringer et al., 2009). In the present work, we found that WR mice displayed lower ethanol intake on days 1–3 of DID (2hrs of access) and only the first 2 h of day 4 – timepoints when BECs were not measured. However, we found no effect of PA on ethanol intake during the final 2 h of day 4, or the subsequent BECs measured at the end of day 4. While the reported BECs do not reflect periods of reduced consumption in WR mice, the consistent reduction in binge-like ethanol intake across all three experiments underscores a potentially important role for PA in harm reduction.

Voluntary PA, which is naturally reinforcing, may act as a viable hedonic substitute for ethanol. For instance, work by Ozburn et al. found that chronic 2-bottle choice drinking and alternating wheel access in combination with forced abstinence led to increased wheel-running behavior in female C57BL/6J mice, with running levels returning to normal after re-exposure to ethanol (Ozburn et al., 2008). In the current study, we saw no major differences in voluntary running distances between weeks 5 (WR alone; no DID) and week 6 (WR + DID), suggesting DID may not alter broad running characteristics. Moreover, the hourly running distance of water drinking mice in the present study are comparable to prior findings in naïve female and male iHDID-1 given 2-weeks of voluntary wheel-running access. In experiment 2, we found that iHDID-1 mice with a history of binge-like ethanol intake ran further on days 1–3 in week 6 (WR + DID) than water-drinking controls. We also found that ethanol drinking mice displayed higher hourly running during the time of DID on days 2 and 3 compared to water drinking mice. A major caveat to consider is that ethanol “abstinence” is a primary feature of DID, wherein 4 consecutive days of drinking is followed by 3 days off. Therefore, a direct comparison between concurrent wheel and ethanol access versus wheel-running alone is less straightforward. Although these findings point to chronic harmful drinking bolstering WR engagement during the time of DID, more work is needed to fully elucidate the effect of ethanol intake on WR behaviors in these mice and to better understand the saliency and reinforcement of PA in the context of harmful drinking in general.

To investigate the relationship between WR and DID, we tested the effect of WR on limited access water intake. Unlike ethanol intake, WR did not reduce water drinking in female iHDID-1 mice, and in fact increased water intake in males. This supports work from McMillan et al., which found that P rats increased water intake and decreased ethanol intake following 10 days of voluntary wheel access (McMillan et al., 1995). Similarly, we found a positive correlation between WR and water intake during DID on 2 of the 4 days. In contrast, we saw no relationship between WR and ethanol intake. This differs from prior findings in female C57BL/6J mice, which showed a strong negative correlation between ethanol preference and running distance (Centanni et al., 2022). Of note, there are distinct differences in drinking and running paradigms between this study and the present work, wherein Centanni et al. gave mice intermittent wheel access (either 3–4 days of wheel-access and 3–4 days of wheel-lock for 6-weeks) following 3-weeks of 2-bottle choice drinking. The observed reduction in ethanol intake in response to WR in iHDID-1 appears to be specific to ethanol and not a generalized reduction in fluid intake. That said, further support addressing other reinforcers (i.e., saccharin intake) is needed to fully evaluate the relationship between these two behaviors.

There is increasing interest in implementing PA as an adjunctive treatment for AUDs in humans (Cabé et al., 2021; Roessler et al., 2017; Thompson et al., 2020). A meta-analysis evaluating the impact of PA on critical metrics of AUD and substance use progression (i.e., prevention, harm reduction, and treatment) found that PA resulted in a 28% lower rate of alcohol use initiation at the time of follow-up (Thompson et al., 2020). Further evidence supports a dose-response relationship between PA engagement (number of days exercised) and alcohol consumption, where adult individuals with AUD diagnosis (based on ICA-10 criteria) display a 4% decrease in alcohol intake for each incremental day of exercise (Roessler et al., 2017). Moreover, participants with moderate PA levels displayed lower odds of excessive drinking and higher rates of abstinence compared to individuals with lower levels of PA. In response, future work would benefit from considering intensity level and consistency of PA in evaluating the effectiveness of PA as an adjunctive therapy for AUD.

PA is well known to improve anxio-depressive symptoms and positively regulate cognitive and memory deficits (aan het Rot et al., 2009; Schuch et al., 2017; Stanton & Reaburn, 2014; Stonerock et al., 2015; Wegner et al., 2014). It follows that PA would be a meaningful intervention for the maladaptive behavioral and cognitive consequences of harmful alcohol use. Despite being an established physiological stressor in rodents, recent evidence found that treadmill running (i.e, forced PA) reduced measures of anxiety-like behavior, increased open-field activity, and improved other metrics of emotionality in adolescent male C57BL/6J mice, but did not reduce binge-like ethanol intake across 5-weeks of DID (similar to the present design; 4 days/week; Sampedro-Piquero et al., 2020; Moraska et al., 2000). Voluntary wheel access was also shown to reverse measures of negative affect-like behavior in mice following ethanol abstinence (Centanni et al., 2022). Pang et al. similarly reported that voluntary wheel-running improved deficits in depressive-like behaviors in response to chronic ethanol intake in male mice (Pang et al., 2013). Taken together, the efficacy of PA as a harm reduction approach appears to parallel its capacity as an intervention for treating the psychosocial consequences of alcohol misuse.

Seminal work by Leasure and Nixon demonstrated that voluntary WR rescued markers of brain damage and cognitive deficits associated with ethanol exposure in female rats (Leasure & Nixon, 2010). Moreover, WR was found to completely reverse ethanol-induced reductions in dentate gyrus volume and granule neuron density (Maynard & Leasure, 2013). The effects of WR on behavioral and cognitive outcomes of harmful drinking in iHDID-1 mice remain unknown. There are few differences in anxiety-like behaviors or ethanol-induced anxiolysis between HDID-1 and their heterogenous founders, with male HDID-1 displaying slightly lower baseline anxiety-like measures (Barkley-Levenson & Crabbe, 2015). In line with prior research, we anticipate that PA would mitigate ethanol-induced anxiety- and depression-like behaviors in iHDID-1 mice.

In contrast to their stark difference in binge-like ethanol intake, iHDID-1 display no major differences in voluntary WR compared to HS/Npt mice (their heterogenous founders; Grigsby et al., 2024). When paired with existing pharmacotherapies, PA has proven to be a promising adjunctive approach in the treatment of major depressive disorder, cardiometabolic diseases, and some forms of cancer (Mura et al., 2014; Quindry & Franklin, 2018; Touillaud et al., 2013). There is growing interest in the implementation of PA alongside existing treatment plans. To the best of our knowledge, there are no studies that have yielded clear evidence that PA is efficacious in combination with FDA approved AUD treatments. Therefore, exploring PA as a potential adjunctive therapy alongside FDA approved AUD treatments could be a powerful and translationally relevant next step for improving health.

Supplementary Material

Supplemental Figure 1

Sources of support

This work was supported by NIH (U01 AA013519, P60 AA010760, K99 AA030806, F32 AA028686, T32 AA007468, F31 AA030908), the U.S. Department of Veteran Affairs (I01 BX004699, I01 BX006570), and a gift from the John R. Andrews Family.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.alcohol.2025.07.004.

Footnotes

CRediT authorship contribution statement

Kolter Grigsby: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Zaynah Usmani: Writing – review & editing, Writing – original draft, Visualization, Validation, Investigation, Formal analysis, Data curation. Amy E. Chan: Writing – review & editing, Writing – original draft, Visualization, Methodology, Investigation, Formal analysis, Data curation. Luis Tzab: Validation, Methodology, Investigation, Formal analysis, Data curation. Justin Anderson: Writing – review & editing, Writing – original draft, Visualization, Validation, Software, Formal analysis, Data curation. Angela R. Ozburn: Writing – review & editing, Writing – original draft, Visualization, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Conceptualization.

Declaration of competing interest

The authors declare no conflicts or competing interests.

References

  1. aan het Rot M, Collins KA, & Fitterling HL (2009). Physical exercise and depression. The Mount Sinai Journal of Medicine, New York, 76(2), 204–214. 10.1179/1743288X11Y.0000000026. [DOI] [PubMed] [Google Scholar]
  2. Barkley-Levenson AM, & Crabbe JC (2015). Genotypic and sex differences in anxiety-like behavior and alcohol-induced anxiolysis in High Drinking in the Dark selected mice. Alcohol (Fayetteville, N.Y.), 49(1), 29–36. 10.1016/j.alcohol.2014.07.022. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Booher WC, Hoft NR, & Ehringer MA (2019). The effect of voluntary wheel running on 129/SvEvTac and C3H/Ibg alcohol consumption. Alcohol, 77, 91–99. [DOI] [PubMed] [Google Scholar]
  4. Buhr TJ, Reed CH, Shoeman A, Bauer EE, Valentine RJ, & Clark PJ (2021). The influence of moderate physical activity on brain monoaminergic responses to binge-patterned alcohol ingestion in female mice. Frontiers in Behavioral Neuroscience, 15, 12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Buscemi J, Martens MP, Murphy JG, Yurasek AM, & Smith AE (2011). Moderators of the relationship between physical activity and alcohol consumption in college students. Journal of American College Health, 59(6), 503–509. [DOI] [PubMed] [Google Scholar]
  6. Cabé N, Lanièpce A, & Pitel AL (2021). Physical activity: A promising adjunctive treatment for severe alcohol use disorder. Addictive Behaviors, 113, 106667. 10.1016/j.addbeh.2020.106667. [DOI] [PubMed] [Google Scholar]
  7. Centanni SW, Conley SY, Luchsinger JR, Lantier L, & Winder DG (2022). The impact of intermittent exercise on mouse ethanol drinking and abstinence-associated affective behavior and physiology. Alcoholism: Clinical and Experimental Research, 46 (1), 114–128. 10.1111/acer.14742. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Cippitelli A, Damadzic R, Hamelink C, Brunnquell M, Thorsell A, Heilig M, & Eskay RL (2014). Binge-like ethanol consumption increases corticosterone levels and neurodegneration whereas occupancy of type II glucocorticoid receptors with mifepristone is neuroprotective. Addiction Biology, 19(1), 27–36. 10.1111/j.1369-1600.2012.00451.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Connor JP, Haber PS, & Hall WD (2016). Alcohol use disorders. The Lancet. 10.1016/S0140-6736(15)00122-1. [DOI] [PubMed] [Google Scholar]
  10. Conroy DE, Ram N, Pincus AL, Coffman DL, Lorek AE, Rebar AL, & Roche MJ (2015). Daily physical activity and alcohol use across the adult lifespan. Health Psychology, 34(6), 653. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Crabbe JC, Metten P, Rhodes JS, Yu CH, Brown LL, Phillips TJ, & Finn DA (2009). A line of mice selected for high blood ethanol concentrations shows drinking in the dark to intoxication. Biological Psychiatry. 10.1016/j.biopsych.2008.11.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Crabbe JC, Metten P, Savarese AM, Ozburn AR, Schlumbohm JP, Spence SE, & Hack WR (2019). Ethanol conditioned taste aversion in high drinking in the dark mice. Brain Sciences, 9(1). 10.3390/brainsci9010002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Crabbe JC, Ozburn AR, Hitzemann RJ, Spence SE, Hack WR, Schlumbohm JP, & Metten P. (2020). Tetracycline derivatives reduce binge alcohol consumption in High Drinking in the Dark mice. Brain, Behavior, & Immunity-Health, 4, 100061. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Crabbe JC, Ozburn AR, Metten P, Barkley-Levenson A, Schlumbohm JP, Spence SE, … Huang LC (2017). High Drinking in the Dark (HDID) mice are sensitive to the effects of some clinically relevant drugs to reduce binge-like drinking. Pharmacology Biochemistry and Behavior. 10.1016/j.pbb.2017.08.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Crabbe JC, Wahlsten D, & Dudek BC (1999). Genetics of mouse behavior: Interactions with laboratory environment. Science (New York, N.Y.), 284(5420), 1670–1672. 10.1126/science.284.5420.1670. [DOI] [PubMed] [Google Scholar]
  16. Dal-Zotto S, Martí O, & Armario A. (2000). Influence of single or repeated experience of rats with forced swimming on behavioural and physiological responses to the stressor. Behavioural Brain Research. 10.1016/S0166-4328(00)00220-5. [DOI] [PubMed] [Google Scholar]
  17. Duncan PM, & Baez AM (1981). The effect of ethanol on wheel running in rats. Pharmacology Biochemistry and Behavior, 15(5), 819–821. 10.1016/0091-3057(81)90028-9. [DOI] [PubMed] [Google Scholar]
  18. Ehringer MA, Hoft NR, & Zunhammer M. (2009). Reduced alcohol consumption in mice with access to a running wheel. Alcohol, 43(6), 443–452. [DOI] [PubMed] [Google Scholar]
  19. Fediuc S, Campbell JE, & Riddell MC (2006). Effect of voluntary wheel running on circadian corticosterone release and on HPA axis responsiveness to restraint stress in Sprague-Dawley rats. Journal of Applied Physiology, 100(6), 1867–1875. 10.1152/japplphysiol.01416.2005. [DOI] [PubMed] [Google Scholar]
  20. Finn DA, Snelling C, Fretwell AM, Tanchuck MA, Underwood L, Cole M, … Roberts AJ (2007). Increased drinking during withdrawal from intermittent ethanol exposure is blocked by the CRF receptor antagonist D-Phe-CRF(12-41). Alcoholism: Clinical and Experimental Research. 10.1111/j.1530-0277.2007.00379.x. [DOI] [PubMed] [Google Scholar]
  21. Glantz MD, Bharat C, Degenhardt L, Sampson NA, Scott KM, Lim CCW, … Lee S, & WHO World Mental Health Survey Collaborators. (2020). The epidemiology of alcohol use disorders cross-nationally: Findings from the World Mental Health Surveys. Addictive Behaviors, 102, 106128. 10.1016/j.addbeh.2019.106128. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Greenwood BN, Foley TE, Le TV, Strong PV, Loughridge AB, Day HEW, & Fleshner M. (2011). Long-term voluntary wheel running is rewarding and produces plasticity in the mesolimbic reward pathway. Behavioural Brain Research, 217(2), 354–362. 10.1016/j.bbr.2010.11.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Grigsby KB, Kerr NR, Kelty TJ, Mao X, Childs TE, & Booth FW (2022). Acute wheel-running increases markers of stress and aversion-related signaling in the basolateral amygdala of male rats. Journal of Functional Morphology and Kinesiology, 8 (1), 6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Grigsby KB, Mangieri RA, Roberts AJ, Lopez MF, Firsick EJ, Townsley KG, … Meissler JJ (2023). Pre-clinical and clinical evidence for suppression of alcohol intake by apremilast. The Journal of Clinical Investigation. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Grigsby KB, Ruegsegger GN, Childs TE, & Booth FW (2019). Overexpression of protein kinase inhibitor alpha reverses rat low voluntary running behavior. Molecular Neurobiology, 56(3). 10.1007/s12035-018-1171-0. [DOI] [PubMed] [Google Scholar]
  26. Grigsby KB, Savarese AM, Metten P, Mason BJ, Blednov YA, Crabbe JC, & Ozburn AR (2020). Effects of tacrolimus and other immune targeting compounds on binge-like ethanol drinking in high drinking in the dark mice. Neuroscience Insights, 15, 2633105520975412. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Grigsby K, Usmani Z, Anderson J, & Ozburn A. (2024). Development and implementation of a dependable, simple, and cost-effective (DSC), open-source running wheel in high drinking in the dark and heterogeneous stock/northport mice. Frontiers in Behavioral Neuroscience, 17, 1321349. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Kelliher P, Connor TJ, Harkin A, Sanchez C, Kelly JP, & Leonard BE (2000). Varying responses to the rat forced-swim test under diurnal and nocturnal conditions. Physiology and Behavior. 10.1016/S0031-9384(00)00213-4. [DOI] [PubMed] [Google Scholar]
  29. Lardier DT, Coakley KE, Holladay KR, Amorim FT, & Zuhl MN (2021). Exercise as a useful intervention to reduce alcohol consumption and improve physical fitness in individuals with alcohol use disorder: A systematic review and meta-analysis. Frontiers in Psychology, 12, 675285. 10.3389/fpsyg.2021.675285. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Leasure JL, Neighbors C, Henderson CE, & Young CM (2015). Exercise and alcohol consumption: What we know, what we need to know, and why it is important. Frontiers in Psychiatry, 6, 156. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Leasure JL, & Nixon K. (2010). Exercise neuroprotection in a rat model of binge alcohol consumption. Alcoholism: Clinical and Experimental Research, 34(3), 404–414. 10.1111/j.1530-0277.2009.01105.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Maynard ME, & Leasure JL (2013). Exercise enhances hippocampal recovery following binge ethanol exposure. PLoS One, 8(9), e76644. 10.1371/journal.pone.0076644. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. McMillan DE, McClure GY, & Hardwick WC (1995). Effects of access to a running wheel on food, water and ethanol intake in rats bred to accept ethanol. Drug and Alcohol Dependence, 40(1), 1–7. 10.1016/0376-8716(95)01162-5. [DOI] [PubMed] [Google Scholar]
  34. Molina PE, & Nelson S. (2018). Binge Drinking’s effects on the body. Alcohol Research: Current Reviews, 39(1), 99–109. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Moraska A, Deak T, Spencer RL, Roth D, & Fleshner M. (2000). Treadmill running produces both positive and negative physiological adaptations in Sprague-Dawley rats. American Journal of Physiology - Regulatory, Integrative and Comparative Physiology, 279(4), R1321–R1329. 10.1152/ajpregu.2000.279.4.R1321. [DOI] [PubMed] [Google Scholar]
  36. Mura G, Moro MF, Patten SB, & Carta MG (2014). Exercise as an add-on strategy for the treatment of major depressive disorder: A systematic review. CNS Spectrums, 19(6), 496–508. 10.1017/S1092852913000953. [DOI] [PubMed] [Google Scholar]
  37. Ozburn AR, Harris RA, & Blednov YA (2008). Wheel running, voluntary ethanol consumption, and hedonic substitution. Alcohol, 42(5), 417–424. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Ozburn AR, Metten P, Potretzke S, Townsley KG, Blednov YA, & Crabbe JC (2020). Effects of pharmacologically targeting neuroimmune pathways on alcohol drinking in mice selectively bred to drink to intoxication. Alcoholism: Clinical and Experimental Research, 44(2), 553–566. 10.1111/acer.14269. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Ozburn AR, & Spencer SM (2023). Repurposing anti-inflammatory medications for alcohol and substance use disorders. Neuropsychopharmacology, 10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Pang TY, Renoir T, Du X, Lawrence AJ, & Hannan AJ (2013). Depression-related behaviours displayed by female C57BL/6J mice during abstinence from chronic ethanol consumption are rescued by wheel-running. European Journal of Neuroscience, 37(11), 1803–1810. 10.1111/ejn.12195. [DOI] [PubMed] [Google Scholar]
  41. Pozhidayeva DY, Farris SP, Goeke CM, Firsick EJ, Townsley KG, Guizzetti M, & Ozburn AR (2020). Chronic chemogenetic stimulation of the nucleus accumbens produces lasting reductions in binge drinking and ameliorates alcohol-related morphological and transcriptional changes. Brain Sciences. 10.3390/brainsci10020109. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Quindry JC, & Franklin BA (2018). Cardioprotective exercise and pharmacologic interventions as complementary antidotes to cardiovascular disease. Exercise and Sport Sciences Reviews, 46(1), 5–17. 10.1249/JES.0000000000000134. [DOI] [PubMed] [Google Scholar]
  43. Rhodes JS, Best K, Belknap JK, Finn DA, & Crabbe JC (2005). Evaluation of a simple model of ethanol drinking to intoxication in C57BL/6J mice. Physiology and Behavior. 10.1016/j.physbeh.2004.10.007. [DOI] [PubMed] [Google Scholar]
  44. Roessler KK, Bilberg R, Søgaard Nielsen A, Jensen K, Ekstrøm CT, & Sari S. (2017). Exercise as adjunctive treatment for alcohol use disorder: A randomized controlled trial. PLoS One, 12(10), e0186076. 10.1371/journal.pone.0186076. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Sampedro-Piquero P, Millón C, Moreno-Fernández RD, García-Fernández M, Diaz-Cabiale Z, & Santin LJ (2020). Treadmill exercise buffers behavioral alterations related to ethanol binge-drinking in adolescent mice. Brain Sciences, 10(9). 10.3390/brainsci10090576. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Savarese AM, Grigsby KB, Jensen BE, Borrego MB, Finn DA, Crabbe JC, & Ozburn AR (2022). Corticosterone levels and glucocorticoid receptor gene expression in high drinking in the dark mice and their heterogeneous stock (HS/NPT) founder line. Frontiers in Behavioral Neuroscience, 16, 821859. 10.3389/fnbeh.2022.821859. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Savarese AM, Ozburn AR, Metten P, Schlumbohm JP, Hack WR, LeMoine K, … Crabbe JC (2020). Targeting the glucocorticoid receptor reduces binge-like drinking in High Drinking in the Dark (HDID-1) mice. Alcoholism: Clinical and Experimental Research. 10.1111/acer.14318. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Schuch FB, Morres ID, Ekkekakis P, Rosenbaum S, & Stubbs B. (2017). A critical review of exercise as a treatment for clinically depressed adults: Time to get pragmatic. Acta neuropsychiatrica. 10.1017/neu.2016.21. [DOI] [PubMed] [Google Scholar]
  49. Sinyor D, Brown T, Rostant L, & Seraganian P. (1982). The role of a physical fitness program in the treatment of alcoholism. Journal of Studies on Alcohol, 43(3), 380–386. 10.15288/jsa.1982.43.380. [DOI] [PubMed] [Google Scholar]
  50. Sipp TL, Blank SE, Lee EG, & Meadows GG (1993). Plasma corticosterone response to chronic ethanol consumption and exercise stress. Proceedings of the Society for Experimental Biology and Medicine. Society for Experimental Biology and Medicine (New York, N.Y.), 204(2), 184–190. 10.3181/00379727-204-43650. [DOI] [PubMed] [Google Scholar]
  51. Stanton R, & Reaburn P. (2014). Exercise and the treatment of depression: A review of the exercise program variables. Journal of Science and Medicine in Sport, 17(2), 177–182. [DOI] [PubMed] [Google Scholar]
  52. Stonerock GL, Hoffman BM, Smith PJ, & Blumenthal JA (2015). Exercise as treatment for anxiety: Systematic review and analysis. Annals of Behavioral Medicine: A Publication of the Society of Behavioral Medicine, 49(4), 542–556. 10.1007/s12160-014-9685-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Stoutenberg M, Rethorst CD, Lawson O, & Read JP (2016). Exercise training - a beneficial intervention in the treatment of alcohol use disorders? Drug and Alcohol Dependence, 160, 2–11. 10.1016/j.drugalcdep.2015.11.019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Thompson TP, Horrell J, Taylor AH, Wanner A, Husk K, Wei Y, … Wallace G. (2020). Physical activity and the prevention, reduction, and treatment of alcohol and other drug use across the lifespan (the PHASE review): A systematic review. Mental Health and Physical Activity, 19, 100360. 10.1016/j.mhpa.2020.100360. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Touillaud M, Foucaut A-M, Berthouze SE, Reynes E, Kempf-Lépine A-S, Carretier J, … Bachmann P. (2013). Design of a randomised controlled trial of adapted physical activity during adjuvant treatment for localised breast cancer: The PASAPAS feasibility study. BMJ Open, 3(10), e003855. 10.1136/bmjopen-2013-003855. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Wegner M, Helmich I, Machado S, Nardi A, Arias-Carrion O, & Budde H. (2014). Effects of exercise on anxiety and depression disorders: Review of meta- analyses and neurobiological mechanisms. CNS & Neurological Disorders - Drug Targets, 13(6), 1002–1014. 10.2174/1871527313666140612102841. [DOI] [PubMed] [Google Scholar]
  57. Welford P, Gunillasdotter V, Andreasson S, Herring MP, Vancampfort D, & Hallgren M. (2023). Sticking with it? Factors associated with exercise adherence in people with alcohol use disorder. Addictive Behaviors, 144, 107730. 10.1016/j.addbeh.2023.107730. [DOI] [PubMed] [Google Scholar]
  58. Werme M, Lindholm S, Thorén P, Franck J, & Brené S. (2002). Running increases ethanol preference. Behavioural Brain Research, 133(2), 301–308. 10.1016/s0166-4328(02)00027-x. [DOI] [PubMed] [Google Scholar]
  59. Witkiewitz K, Litten RZ, & Leggio L. (2019). Advances in the science and treatment of alcohol use disorder. Science Advances, 5(9), eaax4043. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental Figure 1
NIHMS2134779-supplement-Supplemental_Figure_1.tif (982.8KB, tif)

RESOURCES