Alcohol use disorder (AUD) occurs in about 18 million adults in the United States, while excessive drinking contributes to approximately 6% of all deaths worldwide (World Health Organization 2014). Alcohol use directly contributes to multiple organ pathologies (e.g., cardiovascular disease; Djoussé et al. 2009; Molina et al. 2014) in a dose-dependent fashion and is among the leading causes of premature death and disability in the United States (Bauer et al. 2014). AUD is fundamentally a behavioral disease, often referred to as a chronic relapsing disorder (Edwards and Gross 1976). As such, it can only be modeled by reproducing observable characteristics of the disease, such as excessive or impaired control over drinking, withdrawal symptoms, and relapse-like behavior (Edwards and Koob 2012; Leeman et al. 2014; Grant et al. 2014). Most physiological diseases originate from abnormal cellular processes that are largely independent of volitional behavior. In contrast, AUD develops through the gradual shaping of alcohol drinking over years as a cause and consequence of changes in the brain, resulting in a shift in the distribution of an individual’s behavior away from more natural incentives like career and family. Indeed, AUD diagnoses are almost exclusively based on behavior and patterns of drinking over time (APA 2013). There remains an urgent need to develop a comprehensive understanding of the mechanisms driving AUD, as well as to develop a variety of clinical tools to combat this disease.
Like other neurobehavioral disorders, AUD results from a complex interplay of genetics and environment (Bell et al. 2012). How these variables alter patterns and frequency of drinking related to AUD manifestation is a central research emphasis at both clinical and preclinical levels. Today, self-reporting of alcohol consumption is used as a proxy of drinking patterns and has lead to many fundamental insights, including the identification of sex differences and comorbidities (Goldstein et al. 2012), albeit with limitations. Self-report can categorize individuals in terms of alcohol consumption (Babor and Mendelson 1979) but there is no substitute for daily, long-term measures of drinking behavior and blood-alcohol concentrations as accomplished in animal studies (Leeman et al. 2010). Appropriate animal models sidestep the limitations of human studies such as self-report bias and can identify physiological factors that determine patterns of alcohol consumption while controlling for comorbidities and life history. The motivation for alcohol consumption is complex in both humans and animals, with specific contributions from metabolic, social and stress-related factors. A continuing work-in-progress within our field is to test the validity of various animal models and to select those most related to harmful alcohol use (e.g., animals consistently drinking at or above blood-alcohol concentrations exceeding the legal limit for intoxication, 80 mg/dl). These studies are essential for increasing our basic knowledge of mechanisms of alcohol reinforcement, and in turn, these discoveries will increase the likelihood of developing new and effective treatments for controlling excessive alcohol consumption.
In recent years, members of the non-profit group Physicians Committee for Responsible Medicine (PCRM) have regularly petitioned the NIAAA Advisory Council to exclude alcohol research in animals from their portfolio, and to instead focus on education and treatment in humans. Indeed, prevention and rehabilitation are important steps and strategies that are well funded by NIAAA and other groups. However, sustained commitment to basic research is necessary, and animals are required where there are no viable alternatives. We can glean important insight into the neural basis of self-reported alcohol consumption in humans using non-invasive neuroimaging techniques (Marinkovic et al. 2009; Niciu and Mason 2014), but both the behavioral measures and the resolution afforded by these methods is limited. By integrating animal models of excessive alcohol consumption with emerging, cutting-edge neurobiological methods (e.g., proteomics; Gorini et al., 2014) researchers are rapidly gaining new insight into the specific neural circuits and signaling pathways that control critical aspects of alcohol-drinking behavior. As just one recent example, using optogenetic studies in rats, a neurotransmitter-specific (i.e., glutamate) projection from the insular cortex to the nucleus accumbens core was shown to regulate aversion-resistant drinking, an animal model of persistent drinking despite adverse consequences (a behavior that is central to the diagnosis of AUD; Seif et al. 2013). These results exemplify the complexity of neurochemical signaling within the brain, which, in combination with humoral/hormonal cross-talk between non-neuronal and neuronal elements (Crews, 2012), represent irreducible systems unlikely to be recapitulated in vitro or even using the most sophisticated computer models. Animal models also are important for steering alcoholism therapies into the era of personalized medicine by defining gene×environment interactions (Hendershot 2014) far more complicated that what can be reliably modeled in vitro or in silico.
In addition to ushering in new targets for medical intervention, animal models are vital for the refinement of incomplete treatment conceptualizations that currently exist at the clinical level. A limitation of pharmacotherapies is that they target any cell in any part of the brain that contains the receptor at which the drug exhibits efficacy, leading to off-target effects. For example, naltrexone and naloxone, both non-selective opioid receptor antagonists, have repeatedly been shown to decrease both alcohol drinking and consumption of other concurrently available fluids in animal studies. Naltrexone is FDA-approved for AUD and is reported to reduce the number of heavy drinking days (Jonas et al. 2014). However, it is not effective in all patients and has substantial compliance issues (Swift et al., 2011). Opioid receptor-based medications with more selective mechanisms of action based on an understanding of the neurobiological basis of excessive drinking are still needed (Butelman et al., 2012). Preclinical studies are continuing to disentangle distinct opioid signaling mechanisms in dependence-related behavior (e.g., Walker and Koob, 2008), with several promising new medications currently undergoing clinical trials that target opioid (e.g., nalmefene) and non-opioid mechanisms (Litten et al. 2012; Davies et al. 2013). Importantly, preclinical animal models of dependent vs. non-dependent drinking have specified a role for many new drug candidates as targeting pathological excessive drinking vs. non-specific reward mechanisms (Vendruscolo and Roberts, 2014).
Progress in advancing the understanding of alcoholism with the aim of developing treatments using animal models must be, and is, carried out with a high degree of ethical oversight. In addition to the ongoing humane care and use of all research animals in our protection, Institutional Animal Care and Use Committees at institutions where studies are conducted require scientists to adhere to the principles of the 3Rs: reduction, replacement, and refinement (Russell and Burch, 1959). Within this ethical framework, investigators limit the number of animals to what is required for scientifically valid results, seek replacements for animal models (e.g., computer simulations), and constantly refine methods and techniques to minimize discomfort (e.g., environmental enrichment). Another obligation that stems from the use of animal models is the constant need to improve our experimental strategies to more closely match success rates at the preclinical and clinical levels (Egli, 2005). Rigorous and expert peer review before both grant award and publication make the science of alcohol dependence a community effort with feedback at various stages of a project. In a similar vein, because we study complex behavior over extended time periods, alcohol researchers are keenly aware of the importance of animal health in the generation of valid data, which contributes to best practices in animal welfare.
A long history of overwhelming evidence points to the benefits of animal research for both human and veterinary medicine (Royal Society 2004). What are needed now are patience and a renewed commitment to proven strategies that advance biology and medical technology. The most complicated diseases, such as those involving the brain, should require more time and effort to investigate. Human and non-human studies have discovered sex differences, effects of social status, stress and early-life experiences that affect the incidence, severity and outcomes of excessive alcohol consumption. Research on the impact of alcohol on communities (Flynn and Wells 2013), control of land use (Ashe et al. 2003) and brief interventions by physicians (Gaume et al. 2014) can reduce excessive alcohol within a population, but among vulnerable individuals, AUD may still develop. Alcohol use is particularly complicated because regular non-heavy drinking is associated with decreased mortality while particular patterns place individuals at risk (Plunk et al., 2014). Alcohol use has long been a dominant aspect of our vibrant culture, yet the transition to AUD reduces the quality of life for individuals, families and communities. Consistent with an aim of NIAAA (www.niaaa.nih.gov/about-niaaa), it is our responsibility to use all available skills to understand why and how some individuals become addicted, and how to reverse or decrease the cellular pathology mediating the behavior. This is a time of rapid advances in technology, so we expect new insights into the biological mechanisms of AUD if we continue to use animals in basic research. The combined efforts of scientists, clinicians, and bioethicists will ensure that the translational process of discovery and treatment will continue to include humane animal-based investigation.
Finally, we urge all individuals who wish to continue the use of animals in alcohol research to become more actively engaged in the dialogue. Below, we provide links to organizations that champion the utilization of animals to promote future medical breakthroughs:
-
Speaking of Research
References
- American Psychiatric Association. Diagnostic and statistical manual of mental disorders, fifth edition. Washington, DC: American Psychiatric Association; 2013. [Google Scholar]
- Ashe M, Jernigan D, Kline R, Galaz R. Land use planning and the control of alcohol, tobacco, firearms, and fast food restaurants. Am J Public Health. 2003;93:1404–1408. doi: 10.2105/ajph.93.9.1404. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Babor TF, Mendelson JH. Empirical correlates of self-report drinking measures. Curr Alcohol. 1979;7:161–168. [PubMed] [Google Scholar]
- Bauer UE, Briss PA, Goodman RA, Bowman BA. Prevention of chronic disease in the 21st century: elimination of the leading preventable causes of premature death and disability in the USA. Lancet. 2014;384:45–52. doi: 10.1016/S0140-6736(14)60648-6. [DOI] [PubMed] [Google Scholar]
- Bell RL, Sable HJ, Colombo G, Hyytia P, Rodd ZA, Lumeng L. Animal models for medications development targeting alcohol abuse using selectively bred rat lines: neurobiological and pharmacological validity. Pharmacol Biochem Behav. 2012;103:119–155. doi: 10.1016/j.pbb.2012.07.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Butelman ER, Yuferov V, Kreek MJ. κ-opioid receptor/dynorphin system: genetic and pharmacotherapeutic implications for addiction. Trends Neurosci. 2012;35:587–596. doi: 10.1016/j.tins.2012.05.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Crews FT. Immune function genes, genetics, and the neurobiology of addiction. Alcohol Res. 2012;34:355–361. doi: 10.35946/arcr.v34.3.11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Davies DL, Bortolato M, Finn DA, Ramaker MJ, Barak S, Ron D, Liang J, Olsen RW. Recent advances in the discovery and preclinical testing of novel compounds for the prevention and/or treatment of alcohol use disorders. Alcohol Clin Exp Res. 2013;37:8–15. doi: 10.1111/j.1530-0277.2012.01846.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Djoussé L, Gaziano JM. Alcohol consumption and heart failure: a systematic review. Curr Atheroscler Rep. 2009;10:117–120. doi: 10.1007/s11883-008-0017-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Edwards G, Gross MM. Alcohol dependence: Provisional description of a clinical syndrome. Br Med J. 1976;1:1058–1061. doi: 10.1136/bmj.1.6017.1058. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Edwards S, Koob GF. Experimental psychiatric illness and drug abuse models: from human to animal – an overview. Methods Mol Biol. 2012;829:31–48. doi: 10.1007/978-1-61779-458-2_2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Egli M. Can experimental paradigms and animal models be used to discover clinically effective medications for alcoholism? Addict Biol. 2005;10:309–319. doi: 10.1080/13556210500314550. [DOI] [PubMed] [Google Scholar]
- Flynn A, Wells S. Assessing the impact of alcohol use on communities. Alcohol Res. 2013;35:135–149. doi: 10.35946/arcr.v35.2.04. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Gaume J, McCambridge J, Bertholet N, Daeppen JB. Mechanisms of action of brief alcohol interventions remain largely unknown - a narrative review. Front Psychiatry. 2014;5:108. doi: 10.3389/fpsyt.2014.00108. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Goldstein RB, Dawson DA, Chou SP, Grant BF. Sex differences in prevalence and comorbidity of alcohol and drug use disorders: results from wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions. J Stud Alcohol Drugs. 2012;73:938–950. doi: 10.15288/jsad.2012.73.938. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Gorini G, Harris RA, Mayfield RD. Proteomic approaches and identification of novel therapeutic targets for alcoholism. Neuropsychopharmacology. 2014;39:104–130. doi: 10.1038/npp.2013.182. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Grant KA, Ferguson B, Helms CM, McClintick M. Drinking to dependence: risk factors in non-human primates. In: Noronha A, Cui C, Harris RA, Crabbe JC, editors. Neurobiology of Alcohol Dependence. Elsevier Press; 2014. pp. 411–424. [Google Scholar]
- Helms CM, Shaw J, Rau A, Stull C, Gonzales SW, Grant KA. The effects of age at the onset of drinking to intoxication and chronic ethanol self-administration in male rhesus macaques. Psychopharmacology (Berl) 2014;231:1853–1861. doi: 10.1007/s00213-013-3417-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Hendershot CS. Pharmacogenetic approaches in the treatment of alcohol use disorders: addressing clinical utility and implementation thresholds. Addict Sci Clin Pract. 2014;9:20. doi: 10.1186/1940-0640-9-20. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Jonas DE, Amick HR, Feltner C, Bobashev G, Thomas K, Wines R, Kim MM, Shanahan E, Gass CE, Rowe CJ, Garbutt JC. Pharmacotherapy for adults with alcohol use disorders in outpatient settings: a systematic review and meta-analysis. JAMA. 2014;311:1889–1900. doi: 10.1001/jama.2014.3628. [DOI] [PubMed] [Google Scholar]
- Kaminski BJ, Weerts EM. The effects of varenicline on alcohol seeking and self-administration in baboons. Alcohol Clin Exp Res. 2014;38:376–383. doi: 10.1111/acer.12233. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Leeman RF, Beseler CL, Helms CM, Patock-Peckham JA, Wakeling VA, Kahler CW. A brief, critical review of research on impaired control over alcohol use and suggestions for future studies. Alcohol Clin Exp Res. 2014;38:301–308. doi: 10.1111/acer.12269. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Leeman RF, Heilig M, Cunningham CL, Stephens DN, Duka T, O'Malley SS. Ethanol consumption: how should we measure it? Achieving consilience between human and animal phenotypes. Addict Biol. 2010;15:109–124. doi: 10.1111/j.1369-1600.2009.00192.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Litten RZ, Egli M, Heilig M, Cui C, Fertig JB, Ryan ML, Falk DE, Moss H, Huebner R, Noronha A. Medications development to treat alcohol dependence: a vision for the next decade. Addict Biol. 2012;17:513–527. doi: 10.1111/j.1369-1600.2012.00454.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Marinkovic K, Oscar-Berman M, Urban T, O'Reilly CE, Howard JA, Sawyer K, Harris GJ. Alcoholism and dampened temporal limbic activation to emotional faces. Alcohol Clin Exp Res. 2009;33:1880–1892. doi: 10.1111/j.1530-0277.2009.01026.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Mello NK, Mendelson JH. Drinking patterns during work-contingent and noncontingent alcohol acquisition. Psychosom Med. 1972;34:139–164. doi: 10.1097/00006842-197203000-00007. [DOI] [PubMed] [Google Scholar]
- Messaoudi I, Asquith M, Engelmann F, Park B, Brown M, Rau A, Shaw J, Grant KA. Moderate alcohol consumption enhances vaccine-induced responses in rhesus macaques. Vaccine. 2013;32:54–61. doi: 10.1016/j.vaccine.2013.10.076. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Molina PE, Gardner JD, Souza-Smith FM, Whitaker AM. Alcohol abuse: critical pathophysiological processes and contribution to disease burden. Physiology. 2014;29:203–215. doi: 10.1152/physiol.00055.2013. [DOI] [PMC free article] [PubMed] [Google Scholar]
- NC3Rs/BBSRC/Defra/MRC/NERC/Wellcome Trust. Responsibility in the use of animals in bioscience research: expectations of the major research councils and charitable funding bodies. London: NC3Rs; 2013. [Google Scholar]
- Niciu MJ, Mason GF. Neuroimaging in alcohol and drug dependence. Curr Behav Neurosci Rep. 2014;1:45–54. doi: 10.1007/s40473-013-0005-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Plunk AD, Syed-Mohammed H, Cavazos-Rehg P, Bierut LJ, Grucza RA. Alcohol consumption, heavy drinking, and mortality: rethinking the j-shaped curve. Alcohol Clin Exp Res. 2014;38:471–478. doi: 10.1111/acer.12250. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Royal Society. The Use of Non-Human Animals in Research: A Guide for Scientists. London, UK: The Royal Society; 2004. [Google Scholar]
- Russell WMS, Burch RL. The Principles of Humane Experimental Technique. London: Methuen; 1959. [Google Scholar]
- Seif T, Chang S-J, Simms JA, Gibb SL, Dadgar J, Chen BT, Harvey BK, Ron D, Messing RO, Bonci A, Hopf FW. Cortical activation of accumbens hyperpolarization-active NMDARs mediates aversion-resistant alcohol intake. Nat Neurosci. 2013;16:1094–1102. doi: 10.1038/nn.3445. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Swift R, Oslin DW, Alexander M, Forman R. Adherence monitoring in naltrexone pharmacotherapy trials: a systematic review. J Stud Alcohol Drugs. 2011;72:1012–1018. doi: 10.15288/jsad.2011.72.1012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Vendruscolo LF, Roberts AJ. Operant alcohol self-administration in dependent rats: focus on the vapor model. Alcohol. 2014;48:277–286. doi: 10.1016/j.alcohol.2013.08.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- World Health Organization. Global Status Report on Alcohol and Health. 2014 [Google Scholar]
- Walker BM, Koob GF. Pharmacological evidence for a motivational role of kappa-opioid systems in ethanol dependence. Neuropsychopharmacology. 2008;33:643–652. doi: 10.1038/sj.npp.1301438. [DOI] [PMC free article] [PubMed] [Google Scholar]
