Back to Search Start Over

Naltrexone ameliorates functional network abnormalities in alcohol-dependent individuals.

Authors :
Morris, Laurel S.
Baek, Kwangyeol
Tait, Roger
Elliott, Rebecca
Ersche, Karen D.
Flechais, Remy
McGonigle, John
Murphy, Anna
Nestor, Liam J.
Orban, Csaba
Passetti, Filippo
Paterson, Louise M.
Rabiner, Ilan
Reed, Laurence
Smith, Dana
Suckling, John
Taylor, Eleanor M.
Bullmore, Edward T.
Lingford‐Hughes, Anne R.
Deakin, Bill
Source :
Addiction Biology. Jan2018, Vol. 23 Issue 1, p425-436. 12p.
Publication Year :
2018

Abstract

Naltrexone, an opioid receptor antagonist, is commonly used as a relapse prevention medication in alcohol and opiate addiction, but its efficacy and the mechanisms underpinning its clinical usefulness are not well characterized. In the current study, we examined the effects of 50-mg naltrexone compared with placebo on neural network changes associated with substance dependence in 21 alcohol and 36 poly-drug-dependent individuals compared with 36 healthy volunteers. Graph theoretic and network-based statistical analysis of resting-state functional magnetic resonance imaging (MRI) data revealed that alcohol-dependent subjects had reduced functional connectivity of a dispersed network compared with both poly-drug-dependent and healthy subjects. Higher local efficiency was observed in both patient groups, indicating clustered and segregated network topology and information processing. Naltrexone normalized heightened local efficiency of the neural network in alcohol-dependent individuals, to the same levels as healthy volunteers. Naltrexone failed to have an effect on the local efficiency in abstinent poly-substance-dependent individuals. Across groups, local efficiency was associated with substance, but no alcohol exposure implicating local efficiency as a potential premorbid risk factor in alcohol use disorders that can be ameliorated by naltrexone. These findings suggest one possible mechanism for the clinical effects of naltrexone, namely, the amelioration of disrupted network topology. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13556215
Volume :
23
Issue :
1
Database :
Academic Search Index
Journal :
Addiction Biology
Publication Type :
Academic Journal
Accession number :
127423800
Full Text :
https://doi.org/10.1111/adb.12503