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Psychopharmacology

, Volume 235, Issue 9, pp 2755–2769 | Cite as

Selective breeding for high alcohol consumption and response to nicotine: locomotor activity, dopaminergic in the mesolimbic system, and innate genetic differences in male and female alcohol-preferring, non-preferring, and replicate lines of high-alcohol drinking and low-alcohol drinking rats

  • Gerald A. DeehanJr
  • Sheketha R. Hauser
  • Bruk Getachew
  • R. Aaron Waeiss
  • Eric A. Engleman
  • Christopher P. Knight
  • William J. McBride
  • William A. Truitt
  • Richard L. Bell
  • Zachary A. Rodd
Original Investigation

Abstract

Rationale

There is evidence for a common genetic link between alcohol and nicotine dependence. Rodents selectively bred for high alcohol consumption/responsivity are also more likely to self-administer nicotine than controls.

Objectives

The experiments examined the response to systemic nicotine, the effects of nicotine within the drug reward pathway, and innate expression of nicotine-related genes in a brain region regulating drug reward/self-administration in multiple lines of rats selectively bred for high and low alcohol consumption.

Methods

The experiments examined the effects of systemic administration of nicotine on locomotor activity, the effects of nicotine administered directly into the (posterior ventral tegmental area; pVTA) on dopamine (DA) release in the nucleus accumbens shell (AcbSh), and innate mRNA levels of acetylcholine receptor genes in the pVTA were determined in 6 selectively bred high/low alcohol consuming and Wistar rat lines.

Results

The high alcohol-consuming rat lines had greater nicotine-induced locomotor activity compared to low alcohol-consuming rat lines. Microinjections of nicotine into the pVTA resulted in DA release in the AcbSh with the dose response curves for high alcohol-consuming rats shifted leftward and upward. Genetic analysis of the pVTA indicated P rats expressed higher levels of α2 and β4.

Conclusion

Selective breeding for high alcohol preference resulted in a genetically divergent behavioral and neurobiological sensitivity to nicotine. The observed behavioral and neurochemical differences between the rat lines would predict an increased likelihood of nicotine reinforcement. The data support the hypothesis of a common genetic basis for drug addiction and identifies potential receptor targets.

Keywords

Alcohol-preferring P rats Locomotor activity Nicotine High-alcohol-drinking HAD rats Ventral tegmental area Nucleus accumbens Dopamine 

Notes

Acknowledgments

This study was supported by NIAAA grants: AA07611, AA07462, AA020908, AA024612, AA019366, and AA012262

Authors’ contribution

GAD, SRH, RLB, WJM, and ZAR were responsible for study concept, writing, and editing the manuscript. GAD, CPK and WAT were responsible for performing the gene analysis. SRH and BG were responsible for conducting the locomotor activity experiments. GAD and EAE were responsible for conducting and collecting data for the microdialysis experiments. All authors critically reviewed content and approved final version for publication.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

References

  1. Bauer LO, Ceballos NA (2014) Neural and genetic correlates of binge drinking among college women. Biol Psychol 97:43–48.  https://doi.org/10.1016/j.biopsycho.2014.01.005 CrossRefPubMedPubMedCentralGoogle Scholar
  2. Bell RL, Hauser SR, Rodd ZA, Liang T, Sari Y, McClintick J, Rahman S, Engleman EA (2016) A genetic animal model of alcoholism for screening medications to treat addiction. Int Rev Neurobiol 126:179–261.  https://doi.org/10.1016/bs.irn.2016.02.017 CrossRefPubMedPubMedCentralGoogle Scholar
  3. Berg SA, Chambers RA (2008) Accentuated behavioral sensitization to nicotine in the neonatal ventral hippocampal lesion model of schizophrenia. Neuropharmacology 54:1201–1207.  https://doi.org/10.1016/j.neuropharm.2008.03.011 CrossRefPubMedPubMedCentralGoogle Scholar
  4. Bergstrom HC, Palmer AA, Wood RD, Burkhart-Kasch S, Mckinnon CS, Phillips TJ (2003) Reverse selection for differential response to the locomotor stimulant effects of ethanol provides evidence for pleiotropic genetic influence on locomotor response to other drugs of abuse. Alcohol Clin Exp Res 27:1535–1547CrossRefGoogle Scholar
  5. Bodnar TS, Hill LA, Taces MD, Yu W, Soma KK, Hammond GL, Weinberg J (2015) Colony-specific differences in endocrine and immune responses to an inflammatory challenge in female Sprague Dawley rats. Endocrinology 156:4604–4617.  https://doi.org/10.1210/en.2015-1497 CrossRefPubMedPubMedCentralGoogle Scholar
  6. Bracken AL, Chambers RA, Berg SA, Rodd ZA, McBride WJ (2011) Nicotine exposure during adolescence enhances behavioral sensitivity to nicotine during adulthood in Wistar rats. Pharmacol Biochem Behav 99:87–93.  https://doi.org/10.1016/j.pbb.2011.04.008 CrossRefPubMedPubMedCentralGoogle Scholar
  7. Breslau N (1995) Psychiatric comorbidity of smoking and nicotine dependence. Behav Genet 25:95–101CrossRefGoogle Scholar
  8. Brower M, Grace M, Kotz CM, Koya V (2015) Comparative analysis of growth characteristics of Sprague Dawley rats obtained from different sources. Lab Anim Res 31:166–173.  https://doi.org/10.5625/lar.2015.31.4.166 CrossRefPubMedPubMedCentralGoogle Scholar
  9. Buhler KM, Gine E, Echeverry-Alzate V, Calleja-Conde J, De Fonseca FR, Lopez-Moreno JA (2015) Common single nucleotide variants underlying drug addiction: more than a decade of research. Addict Biol 20:845–871. https//doi.org/doi:  https://doi.org/10.1111/adb.12204 CrossRefGoogle Scholar
  10. Cannon DS, Mermelstein RJ, Hedeker D, Coon H, Cook EH, Mcmahon WM, Hamil C, Dunn D, Weiss RB (2014) Effect of neuronal nicotinic acetylcholine receptor genes (CHRN) on longitudinal cigarettes per day in adolescents and young adults. Nicotine Tob Res 16:137–144. https//doi.org/ https://doi.org/10.1093/ntr/ntt125 CrossRefGoogle Scholar
  11. Corley RP, Zeiger JS, Crowley T, Ehringer MA, Hewitt JK, Hopfer CJ, Lessem J, Mcqueen MB, Rhee SH, Smolen A, Stallings MC, Young SE, Krauter K (2008) Association of candidate genes with antisocial drug dependence in adolescents. Drug Alcohol Depend 96:90–98.  https://doi.org/10.1016/j.drugalcdep.2008.02.004 CrossRefPubMedPubMedCentralGoogle Scholar
  12. Cunningham-Williams RM, Cottler LB, Compton WM, Spitznagel EL (1998) Taking chances: problem gamblers and mental health disorders--results from the St. Louis Epidemiologic Catchment Area Study. Am J Public Health 88 (7):1093–1096.CrossRefGoogle Scholar
  13. De Fiebre CM, Medhurst LJ, Collins AC (1987) Nicotine response and nicotinic receptors in long-sleep and short-sleep mice. Alcohol 4:493–501CrossRefGoogle Scholar
  14. De Fiebre NC, Dawson R Jr, De Fiebre CM (2002) The selectively bred high alcohol sensitivity (HAS) and low alcohol sensitivity (LAS) rats differ in sensitivity to nicotine. Alcohol Clin Exp Res 26:765–772CrossRefGoogle Scholar
  15. Deehan GA Jr, Engleman EA, Ding ZM, Mcbride WJ, Rodd ZA (2013) Microinjections of acetaldehyde or salsolinol into the posterior ventral tegmental area increase dopamine release in the nucleus accumbens shell. Alcohol Clin Exp Res 37:722–729.  https://doi.org/10.1111/acer.12034 CrossRefGoogle Scholar
  16. Deehan GA Jr, Hauser SR, Waeiss RA, Knight CP, Toalston JE, Truitt WA, McBride WJ, Rodd ZA (2015) Co-administration of ethanol and nicotine: the enduring alterations in the rewarding properties of nicotine and glutamate activity within the mesocorticolimbic system of female alcohol-preferring (P) rats. Psychopharmacology 232:4293–4302.  https://doi.org/10.1007/s00213-015-4056-1 CrossRefPubMedPubMedCentralGoogle Scholar
  17. Difranza JR, Guerrera MP (1990) Alcoholism and smoking. J Stud Alcohol 51:130–135CrossRefGoogle Scholar
  18. Engleman EA, Ingraham CM, McBride WJ, Lumeng L, Murphy JM (2006) Extracellular dopamine levels are lower in the medial prefrontal cortex of alcohol-preferring rats compared to Wistar rats. Alcohol 38:5–12CrossRefGoogle Scholar
  19. Furberg H, Ostroff J, Lerman C, Sullivan PF (2010) The public health utility of genome-wide association study results for smoking behavior. Genome Med 2:26.  https://doi.org/10.1186/gm147 CrossRefPubMedPubMedCentralGoogle Scholar
  20. Grant BF, Hasin DS, Chou SP, Stinson FS, Dawson DA (2004) Nicotine dependence and psychiatric disorders in the United States: results from the national epidemiologic survey on alcohol and related conditions. Arch Gen Psychiatry 61:1107–1115CrossRefGoogle Scholar
  21. Grant JE, Potenza MN, Weinstein A, Gorelick DA (2011) Introduction to behavioral addictions. Am J Drug Alcohol Abuse 36:233–241.  https://doi.org/10.3109/00952990.2010.491884 CrossRefGoogle Scholar
  22. Hall GB, Milne AM, Macqueen GM (2014) An fMRI study of reward circuitry in patients with minimal or extensive history of major depression. Eur Arch Psychiatry Clin Neurosci 264:187–198.  https://doi.org/10.1007/s00406-013-0437-9 CrossRefGoogle Scholar
  23. Hallfors J, Loukola A, Pitkaniemi J, Broms U, Mannisto S, Salomaa V, Heliovaara M, et al. (2013) Scrutiny of the CHRNA5-CHRNA3-CHRNB4 smoking behavior locus reveals a novel association with alcohol use in a Finnish population based study. Int J Mol Epidemiol Genet 4:109–119Google Scholar
  24. Hauser SR, Bracken AL, Deehan GA Jr, Toalston JE, Ding ZM, Truitt WA, Bell RL, McBride WJ, Rodd ZA (2014) Selective breeding for high alcohol preference increases the sensitivity of the posterior VTA to the reinforcing effects of nicotine. Addict Biol 19:800–811.  https://doi.org/10.1111/adb.12048 CrossRefGoogle Scholar
  25. Herve D, Pickel VM, Joh TH, Beaudet A (1987) Serotonin axon terminals in the ventral tegmental area of the rat: fine structure and synaptic input to dopaminergic neurons. Brain Res 435:71–83CrossRefGoogle Scholar
  26. Ikemoto S, Qin M, Liu ZH (2006) Primary reinforcing effects of nicotine are triggered from multiple regions both inside and outside the ventral tegmental area. J Neurosci 26:723–730CrossRefGoogle Scholar
  27. Kamarajan C, Pandey AK, Chorlian DB, Manz N, Stimus AT, Bauser LO, Hesselbrock VM, Schuckit MA, Kuperman S, Kramer J, Porjesz B (2015) Reward processing deficits and impulsivity in high-risk offspring of alcoholics: a study of event-related potentials during a onetary gambling task. Int J Psychophysiol 98:182–200.  https://doi.org/10.1016/j.ijpsycho.2015.09.005 CrossRefPubMedPubMedCentralGoogle Scholar
  28. Kamens HM, Mckinnon CS, Li N, Helms ML, Belknap JK, Phillips TJ (2009) The alpha 3 subunit gene of the nicotinic acetylcholine receptor is a candidate gene for ethanol stimulation. Genes Brain Behav 8:600–609.  https://doi.org/10.1111/j.1601-183X.2008.00444 CrossRefGoogle Scholar
  29. Koshimizu H, Leiter LM, Miyakawa T (2012) M4 muscarinic receptor knockout mice display abnormal social behavior and decreased prepulse inhibition. Mol Brain 5:10.  https://doi.org/10.1186/1756-6606-5-10 CrossRefPubMedPubMedCentralGoogle Scholar
  30. Le AD, Li Z, Funk D, Shram M, Li TK, Shaham Y (2006) Increased vulnerability to nicotine self-administration and relapse in alcohol-naive offspring of rats selectively bred for high alcohol intake. J Neurosci 26:1872–1879CrossRefGoogle Scholar
  31. Mansvelder HD, Keath JR, Mcgehee DS (2002) Synaptic mechanisms underlie nicotine-induced excitability of brain reward areas. Neuron 33:905–919CrossRefGoogle Scholar
  32. Morel C, Fattore L, Pons S, Hay YA, Marti F, Lambolez B, De Biasi M, Lathrop M, Fratta W, Maskos U, Faure, P (2014) Nicotine consumption is regulated by a human polymorphism in dopamine neurons. Mol Psychiatry 19:930–936. https//doi.org/ https://doi.org/10.1038/mp.2013.158 CrossRefGoogle Scholar
  33. Naaijkens BA, van Dijk A, Meinster E, Kramer K, Kamp O, Krijnen PA, Niessen HW, Jeffersman LJ (2014) Wistar rats from different suppliers have a different response in an acute myocardial infarction model. Res Vet Sci 96:377–379.  https://doi.org/10.1016/j.rvsc.2013.12.015 CrossRefGoogle Scholar
  34. Palm S, Roman E, Nylander I (2011a) Differences in voluntary ethanol consumption in Wistar rats from five different suppliers. Alcohol 45:607–614.  https://doi.org/10.1016/j.alcohol.2010.11.005 CrossRefGoogle Scholar
  35. Palm S, Roman E, Nylander I (2011b) When is a Wistar a Wistar? Behavioral profiling of outbred Wistar rats from five different suppliers using the MCSF test. Appl Anim Behav Sci 135:128–137CrossRefGoogle Scholar
  36. Palm S, Roman E, Nylander I (2012) Differences in basal and ethanol-induced levels of opioid peptides in Wistar rats from five different suppliers. Peptides 36:1–8.  https://doi.org/10.1016/j.peptides.2012.04.016 CrossRefGoogle Scholar
  37. Parsons LH, Hurd YL (2015) Endocannabinoid signalling in reward and addiction. Nat Rev Neurosci 16:579–594.  https://doi.org/10.1038/nrn4004 CrossRefPubMedPubMedCentralGoogle Scholar
  38. Paxinos G, Watson C 2005. The rat brain in stereotaxic coordinates, 5th ed.Google Scholar
  39. Research RIFLA 2011. Guide for the care and use of laboratory animals. 8th ed.Google Scholar
  40. Rodd ZA, Bell RL, Melendez RI, Kuc KA, Lumeng L, Li TK, Murphy JM, McBride WJ (2004a) Comparison of intracranial self-administration of ethanol within the posterior ventral tegmental area between alcohol-preferring and Wistar rats. Alcohol Clin Exp Res 28:1212–1219CrossRefGoogle Scholar
  41. Rodd ZA, Melendez RI, Bell RL, Kuc KA, Zhang Y, Murphy JM, McBride WJ (2004b) Intracranial self-administration of ethanol within the ventral tegmental area of male Wistar rats: evidence for involvement of dopamine neurons. J Neurosci 24:1050–1057CrossRefGoogle Scholar
  42. Rodd ZA, Bell RL, Zhang Y, Murphy JM, Goldstein A, Zaffaroni A, Li TK, McBride WJ (2005) Regional heterogeneity for the intracranial self-administration of ethanol and acetaldehyde within the ventral tegmental area of alcohol-preferring (P) rats: involvement of dopamine and serotonin. Neuropsychopharmacology 30:330–338CrossRefGoogle Scholar
  43. Rodd-Henricks ZA, Mckinzie DL, Crile RS, Murphy JM, McBride WJ (2000) Regional heterogeneity for the intracranial self-administration of ethanol within the ventral tegmental area of female Wistar rats. Psychopharmacology 149:217–224CrossRefGoogle Scholar
  44. Shmulewitz D, Meyers JL, Wall MM, Aharonovich E, Frisch A, Spivak B, Weizman A, Edenberg HJ, Gelernter J, Hasin DS (2016) CHRNA5/A3/B4 variant rs3743078 and nicotine-related phenotypes: indirect effects through nicotine craving. J Stud Alcohol Drugs 77:227–237CrossRefGoogle Scholar
  45. Stein IS, Hell JW (2010) CaMKII hunkers down on the muscarinic M4 receptor to help curb cocaine-induced hyperlocomotion. EMBO J 29:1943–1945.  https://doi.org/10.1038/emboj.2010.105 CrossRefPubMedPubMedCentralGoogle Scholar
  46. Thomas MJ, Kalivas PW, Shaham Y (2008) Neuroplasticity in the mesolimbic dopamine system and cocaine addiction. Br J Pharmacol 154:327–342.  https://doi.org/10.1038/bjp.2008.77 CrossRefPubMedPubMedCentralGoogle Scholar
  47. Truitt WA, Hauser SR, Deehan GA Jr, Toalston JE, Wilden JA, Bell RL, McBride WJ, Rodd ZA (2015) Ethanol and nicotine interaction within the posterior ventral tegmental area in male and female alcohol-preferring rats: evidence of synergy and differential gene activation in the nucleus accumbens shell. Psychopharmacology 232:639–649.  https://doi.org/10.1007/s00213-014-3702-3 CrossRefGoogle Scholar
  48. Uhl GR (2004) Molecular genetic underpinnings of human substance abuse vulnerability: likely contributions to understanding addiction as a mnemonic process. Neuropharmacology 47(Suppl 1):140–147CrossRefGoogle Scholar
  49. Uhl GR, Drgon T, Johnson C, Fatusin OO, Liu QR, Contoreggi C, Li CY, Buck K, Crabbe J (2008a) “Higher order” addiction molecular genetics: convergent data from genome-wide association in humans and mice. Biochem Pharmacol 75:98–111CrossRefGoogle Scholar
  50. Uhl GR, Drgon T, Johnson C, Li CY, Contoreggi C, Hess J, Naiman D, Liu QR (2008b) Molecular genetics of addiction and related heritable phenotypes: genome-wide association approaches identify “connectivity constellation” and drug target genes with pleiotropic effects. Ann N Y Acad Sci 1141:318–381.  https://doi.org/10.1196/annals.1441.018 CrossRefPubMedPubMedCentralGoogle Scholar
  51. Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paipe A, Speleman F (2002) Accurate normalization of real-time quantitative RT-PCR data be geometric averaging of multiple internal control genes. Geneom Biol 3Google Scholar
  52. Ware JJ, Van Den Bree MB, Munafo MR (2011) Association of the CHRNA5-A3-B4 gene cluster with heaviness of smoking: a meta-analysis. Nicotine Tob Res 13:1167–1175.  https://doi.org/10.1093/ntr/ntr118 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Gerald A. DeehanJr
    • 1
  • Sheketha R. Hauser
    • 2
  • Bruk Getachew
    • 2
  • R. Aaron Waeiss
    • 2
  • Eric A. Engleman
    • 2
  • Christopher P. Knight
    • 2
  • William J. McBride
    • 2
  • William A. Truitt
    • 2
  • Richard L. Bell
    • 2
  • Zachary A. Rodd
    • 2
  1. 1.Department of PsychologyEast Tennessee State UniversityJohnson CityUSA
  2. 2.Department of Psychiatry and Institute of Psychiatric ResearchIndiana University School of MedicineIndianapolisUSA

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