The Effects of Citalopram and Thalamic Dopamine D2/3 Receptor Availability on Decision-Making and Loss Aversion in Alcohol Dependence

Todd Zorick, Kyoji Okita, K Brooke Renard, Mark A Mandelkern, Arthur L Brody, Edythe D London, Todd Zorick, Kyoji Okita, K Brooke Renard, Mark A Mandelkern, Arthur L Brody, Edythe D London

Abstract

Selective serotonin reuptake inhibitors (SSRIs) are commonly prescribed for patients who misuse alcohol, especially in the context of comorbid depressive symptoms. Deficits in impulse control and decision-making are linked to routine alcohol consumption and alcohol dependence. The goal of this study was to determine the effects of a single dose of citalopram on measures of impulsivity, decision-making, and/or brain dopamine receptor availability in alcohol-dependent individuals. A double-blind, placebo-controlled, within-subject, outpatient study was conducted with active alcohol-dependent (DSM-IV-TR criteria) participants (n = 12) and matched healthy controls (n = 13). Serial doses of both citalopram (40 mg) and saline were administered intravenously before laboratory tests of decision-making (Balloon Analogue Risk Task, delay discounting task, and Loss Aversion Gambling Task) and positron emission tomography with [18F]-fallypride to measure dopamine D2/3 receptor availability, separated by at least one week. Alcohol-dependent participants demonstrated greater loss aversion than healthy controls, but there were no group differences in risk taking on the Balloon Analogue Risk Task. Citalopram increased delay discounting across groups, with no group difference in the effect. There were no effects of citalopram on risk taking on the Balloon Analogue Risk Task. PET showed a negative correlation between thalamic dopamine D2/3 receptor availability and loss aversion across groups. The effect of citalopram to decrease the valuation of monetary reward as a function of delay raises the possibility that SSRIs can influence risky decision-making in clinical populations. In addition, these results suggest that altered thalamic dopamine signaling may play an important role in disproportionately valuing losses in patients with Alcohol Use Disorder. This trial is registered under ClinicalTrials.gov registration NCT01657760.

Conflict of interest statement

The authors declare that they have no conflicts of interest.

Copyright © 2022 Todd Zorick et al.

Figures

Figure 1
Figure 1
Mazur's k values for discount delay task, by condition. Bars represent mean (s.d.) natural logarithmically transformed k values calculated from participants in each condition. Participants displayed a greater degree of temporal discounting (larger k value) in the citalopram compared to saline conditions. Citalopram-citalopram (40 mg) iv infusion; saline-matched saline placebo. ∗ indicates p < 0.05 for effect of condition by linear mixed effects modeling.
Figure 2
Figure 2
LAGT coefficient values, by participant group. Bars represent mean (s.d.) LAGT coefficients from each participant group. AD: alcohol-dependent participants; HC: control participants. ∗ indicates p < 0.05 for effect of group by linear mixed effects modeling.
Figure 3
Figure 3
Correlation plots of LAGT coefficients (lambda) vs. regional [18F]-fallypride binding potential, by group. Each data point represents a participant in a particular study arm. (a) Thalamic BPND vs. lambda values for participants. (b) Globus pallidus BPND vs. lambda values for participants. Inscribed values represent Pearson's product-moment correlation values, along with the corresponding p values. Group: AD: alcohol-dependent participants (orange circles); HC: control participants (blue circles). Correlations were robust to removing the data for subject with the highest lambda value (>6; p = 0.015 for thalamus, p = 0.0031 for globus pallidus).

References

    1. Management of substance abuse: alcohol [Internet]2020. 2020,
    1. Grant B. F., Goldstein R. B., Saha T. D., et al. Epidemiology of DSM-5 alcohol use disorder: results from the National Epidemiologic Survey on Alcohol and Related Conditions III. JAMA psychiatry . 2015;72(8):757–766. doi: 10.1001/jamapsychiatry.2015.0584.
    1. Centers for Disease Control and Prevention. Alcohol related disease impact (ARDI) application . Atlanta, GA: Centers for Disease Control and Prevention; 2013.
    1. Bechara A., Noel X., Crone E. Abnormal neural mechanisms of impulse control and decision making in addiction. In: Wiers R. W., Stacy A. W., editors. Handbook of Implicit Cognition and Addiction . 1st Edition ed. Thousand Oaks: SAGE Publications; 2006. pp. 214–232.
    1. Stacy A. W., Ames S. L., Leigh B. C. An implicit cognition assessment approach to relapse, secondary prevention, and media effects. Cognitive and Behavioral Practice . 2004;11(2):139–149. doi: 10.1016/S1077-7229(04)80025-7.
    1. Camchong J., Endres M., Fein G. Decision making, risky behavior, and alcoholism. Handbook of Clinical Neurology . 2014;125:227–236. doi: 10.1016/b978-0-444-62619-6.00014-8.
    1. Campbell J. A., Samartgis J. R., Crowe S. F. Impaired decision making on the Balloon Analogue Risk Task as a result of long-term alcohol use. Journal of Clinical and Experimental Neuropsychology . 2013;35(10):1071–1081. doi: 10.1080/13803395.2013.856382.
    1. Lejuez C. W., Aklin W. M., Jones H. A., et al. The Balloon Analogue Risk Task (BART) differentiates smokers and nonsmokers. Experimental and Clinical Psychopharmacology . 2003;11(1):26–33. doi: 10.1037//1064-1297.11.1.26.
    1. Rose A. K., Jones A., Clarke N., Christiansen P. Alcohol-induced risk taking on the BART mediates alcohol priming. Psychopharmacology . 2014;231(11):2273–2280. doi: 10.1007/s00213-013-3377-1.
    1. Kohno M., Ghahremani D. G., Morales A. M., et al. Risk-taking behavior: dopamine D2/D3 receptors, feedback, and frontolimbic activity. Cerebral cortex . 2015;25(1):236–245. doi: 10.1093/cercor/bht218.
    1. Gerst K. R., Gunn R. L., Finn P. R. Delay discounting of losses in alcohol use disorders and antisocial psychopathology: Effects of a working memory load. Alcoholism: Clinical and Experimental Research . 2017;41(10):1768–1774. doi: 10.1111/acer.13472.
    1. MacKillop J. The behavioral economics and neuroeconomics of alcohol use disorders. Alcoholism: Clinical and Experimental Research . 2016;40(4):672–685. doi: 10.1111/acer.13004.
    1. Ward M. Psychiatric nursing. Nursing Standard . 1988;2(37):36–37. doi: 10.7748/ns.2.37.36.s67.
    1. Ballard M. E., Mandelkern M. A., Monterosso J. R., et al. Low dopamine D2/D3 receptor availability is associated with steep discounting of delayed rewards in methamphetamine dependence. International Journal of Neuropsychopharmacology . 2015;18(7) doi: 10.1093/ijnp/pyu119.
    1. MacKillop J., Amlung M. T., Few L. R., Ray L. A., Sweet L. H., Munafò M. R. Delayed reward discounting and addictive behavior: a meta-analysis. Psychopharmacology . 2011;216(3):305–321. doi: 10.1007/s00213-011-2229-0.
    1. MacKillop J., Miranda R., Jr., Monti P. M., et al. Alcohol demand, delayed reward discounting, and craving in relation to drinking and alcohol use disorders. Journal of Abnormal Psychology . 2010;119(1):106–114. doi: 10.1037/a0017513.
    1. Kahneman D., Tversky A. Prospect theory: an analysis of decision under risk. Econometrica . 1979;47(2):263–291. doi: 10.2307/1914185.
    1. Tversky A., Kahneman D. Advances in prospect theory: cumulative representation of uncertainty. Journal of Risk and Uncertainty . 1992;5(4):297–323. doi: 10.1007/BF00122574.
    1. Bernhardt N., Nebe S., Pooseh S., et al. Impulsive decision making in young adult social drinkers and detoxified alcohol-dependent patients: a cross-sectional and longitudinal study. Alcoholism, Clinical and Experimental Research . 2017;41(10):1794–1807. doi: 10.1111/acer.13481.
    1. Genauck A., Quester S., Wüstenberg T., Mörsen C., Heinz A., Romanczuk-Seiferth N. Reduced loss aversion in pathological gambling and alcohol dependence is associated with differential alterations in amygdala and prefrontal functioning. Scientific Reports . 2017;7(1):p. 16306. doi: 10.1038/s41598-017-16433-y.
    1. Gowin J., Sloan M. E., Swan J. E., Momenan R., Ramchandani V. A. The relationship between delay discounting and alcohol dependence in individuals with and without comorbid psychopathology. Psychopharmacology . 2019;236(2):775–785. doi: 10.1007/s00213-018-5113-3.
    1. Lim A. C., Cservenka A., Ray L. A. Effects of alcohol dependence severity on neural correlates of delay discounting. Alcohol and Alcoholism . 2017;52(4):506–515. doi: 10.1093/alcalc/agx015.
    1. Kenna G. A. Medications acting on the serotonergic system for the treatment of alcohol dependent patients. Current Pharmaceutical Design . 2010;16(19):2126–2135. doi: 10.2174/138161210791516396.
    1. Naranjo C. A., Bremner K. E. Serotonin-altering medications and desire, consumption and effects of alcohol-treatment implications. Toward A Molecular Basis of Alcohol Use and Abuse . 1994;71:209–219.
    1. Schweighofer N., Bertin M., Shishida K., et al. Low-serotonin levels increase delayed reward discounting in humans. Journal of Neuroscience . 2008;28(17):4528–4532. doi: 10.1523/JNEUROSCI.4982-07.2008.
    1. Kim Y., Hack L. M., Ahn E. S., Kim J. Practical outpatient pharmacotherapy for alcohol use disorder. Drugs in context . 2018;7:1–14. doi: 10.7573/dic.212308.
    1. Pettinati H. M. Antidepressant treatment of co-occurring depression and alcohol dependence. Biological Psychiatry . 2004;56(10):785–792. doi: 10.1016/j.biopsych.2004.07.016.
    1. Hashimoto E., Tayama M., Ishikawa H., Yamamoto M., Saito T. Influence of comorbid alcohol use disorder on treatment response of depressive patients. Journal of Neural Transmission (Vienna) . 2015;122(2):301–306. doi: 10.1007/s00702-014-1254-7.
    1. Torrens M., Fonseca F., Mateu G., Farre M. Efficacy of antidepressants in substance use disorders with and without comorbid depression. Drug and Alcohol Dependence . 2005;78(1):1–22. doi: 10.1016/j.drugalcdep.2004.09.004.
    1. Charney D. A., Heath L. M., Zikos E., Palacios-Boix J., Gill K. J. Poorer drinking outcomes with citalopram treatment for alcohol dependence: a randomized, double-blind, placebo-controlled trial. Alcoholism, Clinical and Experimental Research . 2015;39(9):1756–1765. doi: 10.1111/acer.12802.
    1. Bielefeldt A. O., Danborg P. B., Gøtzsche P. C. Precursors to suicidality and violence on antidepressants: systematic review of trials in adult healthy volunteers. Journal of the Royal Society of Medicine . 2016;109(10):381–392. doi: 10.1177/0141076816666805.
    1. Glick A. R. The role of serotonin in impulsive aggression, suicide, and homicide in adolescents and adults: a literature review. International Journal of Adolescent Medicine and Health . 2015;27(2):143–150. doi: 10.1515/ijamh-2015-5005. Epub 2015/04/30.
    1. Bezchlibnyk-Butler K., Aleksic I., Kennedy S. H. Citalopram--a review of pharmacological and clinical effects. Journal of Psychiatry and Neuroscience . 2000;25(3):241–254.
    1. Dewey S. L., Smith G. S., Logan J., et al. Serotonergic modulation of striatal dopamine measured with positron emission tomography (PET) and in vivo microdialysis. Journal of Neuroscience . 1995;15(1):821–829. doi: 10.1523/JNEUROSCI.15-01-00821.1995.
    1. Tiihonen J., Kuoppamaki M., Nagren K., et al. Serotonergic modulation of striatal D2 dopamine receptor binding in humans measured with positron emission tomography. Psychopharmacology . 1996;126(4):277–280. doi: 10.1007/bf02247377.
    1. Smith G. S., Ma Y., Dhawan V., Chaly T., Eidelberg D. Selective serotonin reuptake inhibitor (SSRI) modulation of striatal dopamine measured with [11C]-raclopride and positron emission tomography. Synapse . 2009;63(1):1–6. doi: 10.1002/syn.20574.
    1. Tsutsui-Kimura I., Ohmura Y., Yoshida T., Yoshioka M. Milnacipran affects mouse impulsive, aggressive, and depressive-like behaviors in a distinct dose-dependent manner. Journal of Pharmacological Sciences . 2017;134(3):181–189. doi: 10.1016/j.jphs.2017.06.004.
    1. Zorick T., Okita K., Mandelkern M. A., London E. D., Brody A. L. Effects of citalopram on cue-induced alcohol craving and thalamic D2/3 dopamine receptor availability. International Journal of Neuropsychopharmacology . 2019;22(4):286–291. doi: 10.1093/ijnp/pyz010.
    1. Johnson M. W., Bickel W. K. Within‐subject comparison of real and hypothetical money rewards in delay discounting. Journal of the Experimental Analysis of Behavior . 2002;77(2):129–146. doi: 10.1901/jeab.2002.77-129.
    1. Sullivan J. T., Sykora K., Schneiderman J., Naranjo C. A., Sellers E. M. Assessment of alcohol withdrawal: the revised clinical institute withdrawal assessment for alcohol scale (CIWA-Ar) British Journal of Addiction . 1989;84(11):1353–1357. doi: 10.1111/j.1360-0443.1989.tb00737.x.
    1. Mueller S. T., Piper B. J. The psychology experiment building language (PEBL) and PEBL test battery. Journal of Neuroscience Methods . 2014;222:250–259. doi: 10.1016/j.jneumeth.2013.10.024.
    1. White T. L., Lejuez C. W., de Wit H. Test-retest characteristics of the Balloon Analogue Risk Task (BART) Experimental and Clinical Psychopharmacology . 2008;16(6):565–570. doi: 10.1037/a0014083.
    1. Kirby K. N., Petry N. M., Bickel W. K. Heroin addicts have higher discount rates for delayed rewards than non-drug-using controls. Journal of Experimental Psychology. General . 1999;128(1):78–87. doi: 10.1037//0096-3445.128.1.78.
    1. Yi R., Pitcock J. A., Landes R. D., Bickel W. K. The short of it: abbreviating the temporal discounting procedure. Experimental and Clinical Psychopharmacology . 2010;18(4):366–374. doi: 10.1037/a0019904.
    1. Brainard D. H. The psychophysics toolbox. Spatial Vision . 1997;10:433–436.
    1. Tom S. M., Fox C. R., Trepel C., Poldrack R. A. The neural basis of loss aversion in decision-making under risk. Science . 2007;315(5811):515–518. doi: 10.1126/science.1134239.
    1. Okita K., Mandelkern M. A., London E. D. Cigarette use and striatal dopamine D2/3 receptors: possible role in the link between smoking and nicotine dependence. International Journal of Neuropsychopharmacology . 2016;19(11) doi: 10.1093/ijnp/pyw074.
    1. Lee B., London E. D., Poldrack R. A., et al. Striatal dopamine d2/d3 receptor availability is reduced in methamphetamine dependence and is linked to impulsivity. Journal of Neuroscience . 2009;29(47):14734–14740. doi: 10.1523/JNEUROSCI.3765-09.2009.
    1. Innis R. B., Cunningham V. J., Delforge J., et al. Consensus nomenclature for in vivo imaging of reversibly binding radioligands. Journal of Cerebral Blood Flow & Metabolism . 2007;27(9):1533–1539. doi: 10.1038/sj.jcbfm.9600493.
    1. Okita K., Ghahremani D. G., Payer D. E., Robertson C. L., Mandelkern M. A., London E. D. Relationship of alexithymia ratings to dopamine D2-type receptors in anterior cingulate and insula of healthy control subjects but not methamphetamine-dependent individuals. International Journal of Neuropsychopharmacology . 2016;19(5):p. pyv129. doi: 10.1093/ijnp/pyv129.
    1. Team RC R. A language and environment for statistical computing . R Foundation for Statistical Computing; 2019.
    1. Pinheiro J., Bates D., DebRoy D. S., Sarkar D. nmle: linear and nonlinear mixed effects models . R package version 3; 2019.
    1. Reynolds B., Richards J. B., Dassinger M., de Wit H. Therapeutic doses of diazepam do not alter impulsive behavior in humans. Pharmacology, Biochemistry, and Behavior . 2004;79(1):17–24. doi: 10.1016/j.pbb.2004.06.011.
    1. Lane S. D., Tcheremissine O. V., Lieving L. M., Nouvion S., Cherek D. R. Acute effects of alprazolam on risky decision making in humans. Psychopharmacology . 2005;181(2):364–373. doi: 10.1007/s00213-005-2265-8.
    1. Hıdıroğlu C., Esen Ö. D., Tunca Z., et al. Can risk-taking be an endophenotype for bipolar disorder? A study on patients with bipolar disorder type I and their first-degree relatives. Journal of the International Neuropsychological Society . 2013;19(4):474–482. doi: 10.1017/S1355617713000015.
    1. Champely S. pwr: basic functions for power analysis . R package version 1.2-2; 2018.
    1. Cohen J. Statistical Power Analysis for the Behavioral Sciences . Routledge; 1988.
    1. Zorick T., Mandelkern M. A., Brody A. L. A naturalistic study of the association between antidepressant treatment and outcome of smoking cessation treatment. The Journal of Clinical Psychiatry . 2014;75(12):e1433–e1438. doi: 10.4088/JCP.14m09012.
    1. Chandrasekhar Pammi V. S., Pillai Geethabhavan Rajesh P., Kesavadas C., et al. Neural loss aversion differences between depression patients and healthy individuals: a functional MRI investigation. The Neuroradiology Journal . 2015;28(2):97–105. doi: 10.1177/1971400915576670.
    1. Engelmann J. B., Berns G. S., Dunlop B. W. Hyper-responsivity to losses in the anterior insula during economic choice scales with depression severity. Psychological Medicine . 2017;47(16):2879–2891. doi: 10.1017/s0033291717001428.
    1. Becker H. C. Effects of alcohol dependence and withdrawal on stress responsiveness and alcohol consumption. Alcohol Research: Current Reviews . 2012;34(4):448–458.
    1. Bernhardt N., Obst E., Nebe S., et al. Acute alcohol effects on impulsive choice in adolescents. Journal of Psychopharmacology . 2019;33(3):316–325. doi: 10.1177/0269881118822063.
    1. Stephens M. A., Wand G. Stress and the HPA axis: Role of glucocorticoids in alcohol dependence. Alcohol Research: Current Reviews . 2012;34(4):468–483.
    1. Margittai Z., Nave G., Van Wingerden M., Schnitzler A., Schwabe L., Kalenscher T. Combined effects of glucocorticoid and noradrenergic activity on loss aversion. Neuropsychopharmacology . 2018;43(2):334–341. doi: 10.1038/npp.2017.75.
    1. Metz S., Waiblinger-Grigull T., Schulreich S., et al. Effects of hydrocortisone and yohimbine on decision-making under risk. Psychoneuroendocrinology . 2020;114:p. 104589. doi: 10.1016/j.psyneuen.2020.104589.
    1. Ernst M., Plate R. C., Carlisi C. O., Gorodetsky E., Goldman D., Pine D. S. Loss aversion and 5HTT gene variants in adolescent anxiety. Developmental Cognitive Neuroscience . 2014;8(8):77–85. doi: 10.1016/j.dcn.2013.10.002.
    1. Neukam P. T., Kroemer N. B., Deza Araujo Y. I., et al. Risk-seeking for losses is associated with 5-HTTLPR, but not with transient changes in 5-HT levels. Psychopharmacology . 2018;235(7):2151–2165. doi: 10.1007/s00213-018-4913-9.
    1. Voigt G., Montag C., Markett S., Reuter M. On the genetics of loss aversion: an interaction effect of BDNF Val66Met and DRD2/ANKK1 Taq1a. Behavioral Neuroscience . 2015;129(6):801–811. doi: 10.1037/bne0000102.
    1. Cesarini D., Johannesson M., Magnusseon P. K. E., Wallace B. The behavioral genetics of behavioral anomalies. Mananagement Science . 2012;58(1):21–34. doi: 10.1287/mnsc.1110.1329.
    1. Takahashi H., Fujie S., Camerer C., et al. Norepinephrine in the brain is associated with aversion to financial loss. Molecular Psychiatry . 2013;18(1):3–4. doi: 10.1038/mp.2012.7.
    1. Khan H. A., Urstadt K. R., Mostovoi N. A., Berridge K. C. Mapping excessive “disgust” in the brain: Ventral pallidum inactivation recruits distributed circuitry to make sweetness “disgusting”. Cognitive, Affective, & Behavioral Neuroscience . 2020;20(1):141–159. doi: 10.3758/s13415-019-00758-4.
    1. Cromwell H. C., Berridge K. C. Mapping of globus pallidus and ventral pallidum lesions that produce hyperkinetic treading. Brain Research . 1994;668(1-2):16–29. doi: 10.1016/0006-8993(94)90506-1.
    1. Canessa N., Crespi C., Motterlini M., et al. The functional and structural neural basis of individual differences in loss aversion. Journal of Neuroscience . 2013;33(36):14307–14317. doi: 10.1523/JNEUROSCI.0497-13.2013.
    1. Schulreich S., Gerhardt H., Meshi D., Heekeren H. R. Fear-induced increases in loss aversion are linked to increased neural negative-value coding. Social Cognitive and Affective Neuroscience . 2020;15(6):661–670. doi: 10.1093/scan/nsaa091.
    1. Schonberg T., Fox C. R., Poldrack R. A. Mind the gap: bridging economic and naturalistic risk-taking with cognitive neuroscience. Trends in Cognitive Sciences . 2011;15(1):11–19. doi: 10.1016/j.tics.2010.10.002.
    1. Schulreich S., Heussen Y. G., Gerhardt H., et al. Music-evoked incidental happiness modulates probability weighting during risky lottery choices. Frontiers in Psychology . 2014;4(4):p. 981. doi: 10.3389/fpsyg.2013.00981.
    1. Grant B. F., Hasin D. S., Chou S. P., Stinson F. S., Dawson D. A. Nicotine dependence and psychiatric disorders in the United States. Archives of General Psychiatry . 2004;61(11):1107–1115. doi: 10.1001/archpsyc.61.11.1107.
    1. Ashenhurst J. R., Bujarski S., Jentsch J. D., Ray L. A. Modeling behavioral reactivity to losses and rewards on the Balloon Analogue Risk Task (BART): moderation by alcohol problem severity. Experimental and Clinical Psychopharmacology . 2014;22(4):298–306. doi: 10.1037/a0036837.

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