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Combined Administration of Cannabidiol and L-Theanine Improves Sleep-Related Outcomes in Caffeine-Induced Sleep Disturbances Mouse Model

Year: 2026
Type: article
Abstract: Sleep disruption is associated with increased risks of metabolic, cardiovascular, and neuropsychiatric disorders. Cannabidiol (CBD) and L-theanine have attracted attention as potential sleep-supporting agents due to their neuroactive properties. This study investigated the individual and combined effects of CBD and L-theanine in a caffeine-induced sleep disturbance mouse model using behavioral assessments and neurochemical analyses. Mice were orally administered CBD and L-theanine at ratios of 1:1, 2:1, or 1:2 prior to pentobarbital-induced sleep testing. Co-administration significantly reduced sleep onset latency and increase total sleep duration compared with single treatments under sleep-disturbed conditions. Combination index analysis indicated a synergistic interaction at lower doses, whereas such interaction was not observed at higher doses under normal conditions. To further characterize associated neurochemical changes, serum serotonin and melatonin levels, as well as cortical gamma-aminobutyric acid (GABA), were measured using enzyme-linked immunosorbent assay. CBD increased serotonin levels in a dose-dependent manner, while L-theanine elevated serotonin at lower doses. Combination treatment was associated with increased serotonin and melatonin levels which rose by more than 40% relative to the caffeine-treated group. Cortical GABA levels were also elevated following combination treatment. Collectively, these findings indicate that co-administration of CBD and L-theanine improves sleep-related outcomes and is associated with neurochemical changes, although the precise mechanisms remain to be determined. This study suggests the potential of CBD and L-theanine co-administration as an alternative approach for managing stimulant-induced sleep disturbances.
Language: English
Subfield: Pharmacology
Field: Medicine
Open Access status: hybrid
OpenAlex ID: W7166703499
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