A preliminary study on the effect of combined nicotine replacement therapy on alcohol responses and alcohol self-administration

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

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.

A novel human laboratory alcohol self-administration paradigm for medication screening: Modeling the ability to resist drinking and heavy drinking

Background

Human laboratory analogues of drinking behavior provide an efficient, cost-effective mechanistic evaluation of a medication signal on drinking. We developed a novel alcohol self-administration paradigm which models the ability to resist drinking and heavy drinking.

Methods

We compared a de-escalating schedule of monetary reinforcement (n=16, 50% female) to no schedule (n=16, 50% female) on the ability to resist drinking (i.e., latency to start drinking) and subsequent ad-libitum alcohol consumption of preferred alcoholic beverage in participants with alcohol use disorder (AUD). Participants completed two laboratory sessions designed to model the ability to resist drinking using stress (versus neutral imagery, within-subject factor) as a prime for drinking.

Results

Participants consumed more alcohol with no schedule (74.2%) versus with the de-escalating reinforcement schedule (40.3%,). The de-escalating schedule reduced alcohol consumption by 49%. Eighty-one percent of participants drank heavily with no schedule and this was reduced with the schedule. Use of the de-escalating schedule also increased the latency to pour and sip the first drink. Participants poured and sipped alcohol faster following stress imagery (vs. neutral), had greater craving, and consumed more alcohol in the first 30 minutes.

Conclusions

Our novel alcohol self-administration model generated heavy drinking. Over 80% of participants without reinforcement consumed more than 2/3 of their preferred alcoholic beverage designed to increase blood alcohol levels to 0.12 mg% within a 2-hour window. Our model was sensitive to stress, and the de-escalating schedule highlighted stress effects on drinking. Thus, this model is ideal for a cross-over design to test medications for AUD.

On computing critical factors based healthy behavior index for behavior assessment

OBJECTIVE

Ubiquitous computing has supported personalized health through a vast variety of wellness and healthcare self-quantification applications over the last decade. These applications provide insights for daily life activities but unable to portray the comprehensive impact of personal habits on human health. Therefore, in order to facilitate the individuals, we have correlated the lifestyle habits in an appropriate proportion to determine the overall impact of influenced behavior on the well-being of humans.

MATERIALS AND METHODS

To study the combined impact of personal behaviors, we have proposed a methodology to derive the comprehensive Healthy Behavior Index (HBI) consisting of two major processes: (1) Behaviors' Weight-age Identification (BWI), and (2) Healthy Behavior Quantification and Index (HBQI) modeling. The BWI process identifies the high ranked contributing behaviors through life-expectancy based weight-age, whereas HBQI derives a mathematical model based on quantification and indexing of behavior using wellness guidelines.

RESULTS

The contributing behaviors are identified through text mining technique and verified by seven experts with a Kappa agreement level of 0.379. A real-world user-centric statistical evaluation is applied through User Experience Questionnaire (UEQ) method to evaluate the impact of HBI service. This HBI service is developed for the Mining Minds, a wellness management application. This study involves 103 registered participants (curious about the chronic disease) for a Korean wellness management organization. They used the HBI service over 12 weeks, the results for which were evaluated through UEQ and user feedback. The service reliability for the Cronbach's alpha coefficient greater than 0.7 was achieved using HBI service whereas the stimulation coefficient of the value 0.86 revealed significant effect. We observed an overall novelty of the value 0.88 showing the potential interest of participants.

CONCLUSIONS

The comprehensive HBI has demonstrated positive user experience concerning the stimulation for adapting the healthy behaviors. The HBI service is designed independently to work as a service, so any other wellness management service-enabled platform can consume it to evaluate the healthy behavior index of the person for recommendation generation, behavior indication, and behavior adaptation.

Is the use of e-cigarettes for smoking cessation associated with alcohol consumption? A population-level survey of successful quitters in England

OBJECTIVE

To examine associations between the use of e-cigarettes for smoking cessation and levels of alcohol consumption, high-risk drinking, and attempts to cut down alcohol consumption compared with use of nicotine replacement therapy (NRT) or no aid.

METHODS

Cross-sectional survey of adults (≥16 years) in England. The sample included a total of 961 people who had quit smoking with the use of either e-cigarettes (n = 425), NRT (n = 116), or no aid (n = 421) within the past year and were still abstinent at the survey. Drinking behaviour was assessed with the AUDIT.

RESULTS

Mean (SD) alcohol consumption among those who quit smoking with e-cigarettes, NRT, and no aid was 7.78 (13.41), 7.12 (13.85), and 5.55 (8.70) units/week, respectively. The prevalence of high-risk drinking was 43.3% (n = 184), 32.2% (n = 37), and 36.8% (n = 155), respectively. Among high-risk drinkers, the prevalence of attempts to cut down alcohol consumption was 22.3% (n = 41), 18.9% (n = 7), and 27.7% (n = 43), respectively. After adjustment for covariates, those who quit with e-cigarettes had significantly higher alcohol consumption than those who quit unaided (B = 1.69, 95%CI 0.21-3.17), but there was no significant difference relative to those who quit with NRT. Differences in high-risk drinking and attempts to cut down were not significant, but Bayes factors indicated the data were insensitive (range: 0.47-0.95).

CONCLUSIONS

Recent ex-smokers who used e-cigarettes to help them quit consumed around two more units of alcohol each week than those who quit unaided, but their alcohol consumption was similar to those who quit with NRT. Data on differences in high-risk drinking and attempts to cut down alcohol consumption among high-risk drinkers were inconclusive.

Young adults report increased pleasure from using e-cigarettes and smoking tobacco cigarettes when drinking alcohol

BACKGROUND

Cigarettes share a high rate of co-use with alcohol, particularly among young adults. Studies have demonstrated greater perceived pleasure from smoking cigarettes when drinking alcohol. However, little is known about co-use of electronic cigarettes (e-cigs) and alcohol. The current study sought to compare extent of use and perceived pleasure from cigarettes and e-cigs when drinking alcohol.

METHODS

Young adult bar patrons in California cities (San Diego, Los Angeles, and San Francisco) were recruited in 2015-16 using randomized time-location sampling. Participants completed cross-sectional surveys in bars, reporting the percent of cigarette smoking/e-cig use that occurred under the influence of alcohol, and reported if pleasure from smoking cigarettes/using e-cigs changed when drinking alcohol. Analyses are limited to participants reporting current (past 30-day) use of cigarettes, e-cigs, and alcohol (N = 269; M age = 24.1; 40.1% female, 36.1% Non-Hispanic White).

RESULTS

Participants reported a greater percentage of cigarette smoking compared to e-cig use under the influence of alcohol (cigarettes M = 63.6%; e-cigs M = 46.7%; p < .001). Participants also reported increased pleasure both from smoking cigarettes (M = 3.9; [compared to midpoint of scale 3 - "no change"] p < .001) and using e-cigs (M = 3.3; p < .001) when drinking alcohol. The increase in pleasure was more pronounced for cigarettes compared to e-cigs (p < .001).

CONCLUSIONS

Drinking alcohol is associated with increases in perceived rewarding effects of both cigarettes and e-cigs and thus may increase their abuse liability. This effect may be stronger for cigarettes, which could be an important barrier to switching completely from smoking cigarettes to using e-cigs, or quitting both entirely.

An improved model of ethanol and nicotine co-use in female P rats: Effects of naltrexone, varenicline, and the selective nicotinic α6β2* antagonist r-bPiDI

Background Although pharmacotherapies are available for alcohol (EtOH) or tobacco use disorders individually, it may be possible to develop a single pharmacotherapy to treat heavy drinking tobacco smokers by capitalizing on the commonalities in their mechanisms of action. Methods Female alcohol-preferring (P) rats were trained for EtOH drinking and nicotine self-administration in two phases: (1) EtOH alone (0 vs. 15% EtOH, 2-bottle choice) and (2) concomitant access, during which EtOH access continued with access to nicotine (0.03 mg/kg/infusion, i.v.) using a 2-lever choice procedure (active vs. inactive lever) in which the fixed ratio (FR) requirement was gradually increased to FR30. When stable co-use was obtained, rats were pretreated with varying doses of naltrexone, varenicline, or r-bPiDI, an α6β2* subtype-selective nicotinic acetylcholine receptor antagonist shown previously to reduce nicotine self-administration. Results While EtOH intake was initially suppressed in phase 2 (co-use), pharmacologically relevant intake for both substances was achieved by raising the "price" of nicotine to FR30. In phase 2, naltrexone decreased EtOH and water consumption but not nicotine intake; in contrast, naltrexone in phase 1 (EtOH only) did not significantly alter EtOH intake. Varenicline and r-bPiDI in phase 2 both decreased nicotine self-administration and inactive lever pressing, but neither altered EtOH or water consumption. Conclusions These results indicate that increasing the "price" of nicotine increases EtOH intake during co-use. Additionally, the efficacy of naltrexone, varenicline, and r-bPiDI was specific to either EtOH or nicotine, with no efficacy for co-use. Nevertheless, future studies on combining these treatments may reveal synergistic efficacy.

Smoking Cessation for Those Pursuing Recovery from Substance Use Disorders

This article summarizes the literature regarding the similar biopsychosocial mechanisms of tobacco use and alcohol and substance use disorders, and the evidence for and against the provision of tobacco cessation for those in treatment for alcohol and substance use disorders. The practicality of treatment, focusing on methods, timing, and breadth of intervention strategies, are also presented. Common methodologies that may be used across tobacco use and alcohol and substance use disorder to prevent lapse and relapse are discussed. Physicians can and should adhere to the policy that tobacco use is a common and dangerous comorbid condition that demands concomitant treatment.

Effects of the nicotinic agonist varenicline, nicotinic antagonist r-bPiDI, and DAT inhibitor (R)-modafinil on co-use of ethanol and nicotine in female P rats

RATIONALE

Co-users of alcohol and nicotine are the largest group of polysubstance users worldwide. Commonalities in mechanisms of action for ethanol (EtOH) and nicotine proposes the possibility of developing a single pharmacotherapeutic to treat co-use.

OBJECTIVES

Toward developing a preclinical model of co-use, female alcohol-preferring (P) rats were trained for voluntary EtOH drinking and i.v. nicotine self-administration in three phases: (1) EtOH alone (0 vs. 15%, two-bottle choice), (2) nicotine alone (0.03 mg/kg/infusion, active vs. inactive lever), and (3) concurrent access to both EtOH and nicotine. Using this model, we examined the effects of (1) varenicline, a nicotinic acetylcholine receptor (nAChR) partial agonist with high affinity for the α4β2* subtype; (2) r-bPiDI, a subtype-selective antagonist at α6β2* nAChRs; and (3) (R)-modafinil, an atypical inhibitor of the dopamine transporter (DAT).

RESULTS

In phases 1 and 2, pharmacologically relevant intake of EtOH and nicotine was achieved. In the concurrent access phase (phase 3), EtOH consumption decreased while nicotine intake increased relative to phases 1 and 2. For drug pretreatments, in the EtOH access phase (phase 1), (R)-modafinil (100 mg/kg) decreased EtOH consumption, with no effect on water consumption. In the concurrent access phase, varenicline (3 mg/kg), r-bPiDI (20 mg/kg), and (R)-modafinil (100 mg/kg) decreased nicotine self-administration but did not alter EtOH consumption, water consumption, or inactive lever pressing.

CONCLUSIONS

These results indicate that therapeutics which may be useful for smoking cessation via selective inhibition of α4β2* or α6β2* nAChRs, or DAT inhibition, may not be sufficient to treat EtOH and nicotine co-use.

A Critical Review of the Effects of Nicotine and Alcohol Coadministration in Human Laboratory Studies

Simultaneous use of cigarettes and alcohol is common and may be driven by nicotine increasing alcohol self-administration or vice versa. To better evaluate the causal nature of this relationship, we systematically reviewed human experimental laboratory studies that coadministered nicotine and alcohol with control conditions. Searches of PubMed/MEDLINE and PsycINFO databases and study bibliographies identified 30 studies that met our inclusion criteria. Research methodologies were critically reviewed. Effects of coadministration on drug self-administration and related factors such as craving, subjective response, motivation, and heart rate are reported. Results most strongly supported that alcohol increases nicotine and cigarette self-administration, whereas, depending on the context, nicotine increased, decreased, or had no effect on alcohol self-administration. Craving and subjective drug effects were also impacted by coadministration. Interaction effects of nicotine and alcohol on self-administration and subjective responses were reported infrequently. The effects may be moderated by a number of factors, including dose of administered drug and sex. Recommendations are made for future research, and clinical and policy implications of findings are discussed.

Operant self-administration of alcohol and nicotine in a preclinical model of co-abuse

RATIONALE AND OBJECTIVES

Alcohol and nicotine are often taken together. In humans, intake of nicotine, via smoked tobacco, increases alcohol drinking, and alcohol increases smoking. Chronic nicotine treatment increases alcohol self-administration (SA) in laboratory animals; the reverse relationship is less clear. Most animal work modeling this has used passive administration, which lacks relevance to human co-abuse. Here, we describe a model based on sequential operant SA of alcohol and nicotine.

METHODS

Animals are first trained on alcohol SA (0.19 ml of 12 % alcohol (w/v)/delivery) and then receive separate alcohol (8 %, w/v) and nicotine (15 μg/kg/infusion) SA sessions on the same day ("daily dual access"). Animals then receive access to alcohol and then to nicotine (or in the reverse order) in alternating 5-min periods in 2-h sessions ("alternating access"). We then determine if alternating access modifies the effects of naltrexone on responding for alcohol and nicotine.

RESULTS

We found that with daily dual access, nicotine significantly increased alcohol SA when alcohol access occurred prior to nicotine access and that nicotine SA significantly decreased when the alcohol SA session preceded it. During alternating access, nicotine also significantly increased alcohol intake. Naltrexone (0.3 or 1 mg/kg) significantly reduced alcohol SA during these alternating access sessions in animals that also received nicotine SA, but had minimal effects on animals receiving alcohol SA alone. Naltrexone did not affect nicotine SA under any condition.

CONCLUSIONS

This sequential access procedure effectively models the effects of nicotine on alcohol intake noted in humans.