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Varenicline, the clinically effective smoking cessation agent, restores probabilistic response reversal performance during withdrawal from nicotine

Lookup NU author(s): Yazead Buhidma, Dr Mohammed Shoaib

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This is the authors' accepted manuscript of an article that has been published in its final definitive form by Wiley-Blackwell Publishing Ltd., 2016.

For re-use rights please refer to the publisher's terms and conditions.


Abstract

© 2016 Society for the Study of Addiction. There is recognition that cognitive problems can contribute to renewed drug taking in former addicts. Our previous work has indicated that current smokers show reduced performance on a probabilistic reversal learning (PRL) task, relative to former smokers. To further explore PRL performance and its relevance to smoking, in addition to the role of nicotine, we developed a model of nicotine withdrawal-induced deficits in rodents. A second goal was to test varenicline, an α4β2 partial agonist, for its ability to restore any cognitive impairment. Acute effects of nicotine and varenicline on PRL performance in non-dependent animals were minimal and confined to speed of responding. When rats were made dependent on nicotine via osmotic minipumps implanted for 7days (3.16mg/kg/day), repeated tests at specified withdrawal time points revealed PRL disruption peaking at 12 and 24hours following surgical removal of minipumps. Withdrawal was characterized by significant deficits in the number of reversals (P<0.05), speed of responding (P<0.01) and increases in omissions (P<0.05). Nicotine (0.2mg/kg SC) or varenicline (0.3 and 1.0mg/kg SC) administered 10-minute prior to PRL test sessions during withdrawal, relieved the performance deficits. At 24-hour withdrawal, nicotine and varenicline (1mg/kg) prevented decrements in reversals, in addition to ameliorating slower speed of responding. The high dose of varenicline only reduced omissions. These results confirm the role of nicotine in withdrawal-induced disruption of PRL performance and suggest that the model may be useful for investigating efficacy of potential new treatments for smoking cessation.


Publication metadata

Author(s): Jackson A, Silk S, Buhidma Y, Shoaib M

Publication type: Article

Publication status: Published

Journal: Addiction Biology

Year: 2016

Volume: 22

Issue: 5

Pages: 1316-1328

Print publication date: 01/09/2017

Online publication date: 20/07/2016

Acceptance date: 06/06/2016

Date deposited: 14/12/2017

ISSN (print): 1355-6215

ISSN (electronic): 1369-1600

Publisher: Wiley-Blackwell Publishing Ltd.

URL: https://doi.org/10.1111/adb.12423

DOI: 10.1111/adb.12423


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