Usage Information
Citation Information: JCI Insight. 2022;7(19):e159863. https://doi.org/10.1172/jci.insight.159863.
Abstract
Background Alcohol use disorder (AUD) is a chronic, relapsing brain disorder that accounts for 5% of deaths annually, and there is an urgent need to develop new targets for therapeutic intervention. The glucagon-like peptide-1 (GLP-1) receptor agonist exenatide reduces alcohol consumption in rodents and nonhuman primates, but its efficacy in patients with AUD is unknown.Methods In a randomized, double-blinded, placebo-controlled clinical trial, treatment-seeking AUD patients were assigned to receive exenatide (2 mg subcutaneously) or placebo once weekly for 26 weeks, in addition to standard cognitive-behavioral therapy. The primary outcome was reduction in number of heavy drinking days. A subgroup also completed functional MRI (fMRI) and single-photon emission CT (SPECT) brain scans.Results A total of 127 patients were enrolled. Our data revealed that although exenatide did not significantly reduce the number of heavy drinking days compared with placebo, it significantly attenuated fMRI alcohol cue reactivity in the ventral striatum and septal area, which are crucial brain areas for drug reward and addiction. In addition, dopamine transporter availability was lower in the exenatide group compared with the placebo group. Exploratory analyses revealed that exenatide significantly reduced heavy drinking days and total alcohol intake in a subgroup of obese patients (BMI > 30 kg/m2). Adverse events were mainly gastrointestinal.Conclusion This randomized controlled trial on the effects of a GLP-1 receptor agonist in AUD patients provides new important knowledge on the effects of GLP-1 receptor agonists as a novel treatment target in addiction.Trial registration EudraCT: 2016-003343-11. ClinicalTrials.gov (NCT03232112).Funding Novavi Foundation; Research Foundation, Mental Health Services, Capital Region of Denmark; Research Foundation, Capital Region of Denmark; Ivan Nielsen Foundation; A.P. Moeller Foundation; Augustinus Foundation; Woerzner Foundation; Grosserer L.F. Foghts Foundation; Hartmann Foundation; Aase and Ejnar Danielsen Foundation; P.A. Messerschmidt and Wife Foundation; and Lundbeck Foundation.
Authors
Mette Kruse Klausen, Mathias Ebbesen Jensen, Marco Møller, Nina Le Dous, Anne-Marie Østergaard Jensen, Victoria Alberte Zeeman, Claas-Frederik Johannsen, Alycia Lee, Gerda Krog Thomsen, Julian Macoveanu, Patrick MacDonald Fisher, Matthew Paul Gillum, Niklas Rye Jørgensen, Marianne Lerbæk Bergmann, Henrik Enghusen Poulsen, Ulrik Becker, Jens Juul Holst, Helene Benveniste, Nora D. Volkow, Sabine Vollstädt-Klein, Kamilla Woznica Miskowiak, Claus Thorn Ekstrøm, Gitte Moos Knudsen, Tina Vilsbøll, Anders Fink-Jensen
Usage data is cumulative from January 2024 through January 2025.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 7,562 | 3,372 |
| 614 | 752 | |
| Figure | 543 | 58 |
| Table | 223 | 0 |
| Supplemental data | 255 | 128 |
| Citation downloads | 145 | 0 |
| Totals | 9,342 | 4,310 |
| Total Views | 13,652 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.
