Dataset Information

Simplified drug efficacy screening system for sleep-disorder drugs using non-human primates.

ABSTRACT: The most widely used animal models to develop sleep-disorder drugs are rodents, particularly rats and mice. However, unlike humans, these rodents are nocturnal. Thus, diurnal non-human primates represent a valuable and more translational animal model to study sleep. Although sleep-disorder drugs have been screened in non-human primates, the use of a telemetry system is not a desirable method for a rapid drug efficacy assessment system because of the need for expensive equipment, complicated surgery, and the long time before results can be obtained from analysis by inspection. Locomotor activity has traditionally been used as an indicator of the effects of drugs, genes, and disease models. The Nano-Tag, a new device for analyzing activity after an easy implantation surgery, measures locomotor activity without expensive equipment and the need for inspection for data processing, and the overall cost is much lower than that of a telemetry system. In this study, we compared the data obtained from polysomnography and on locomotor activity in telemetry transmitter-embedded cynomolgus monkeys by implanting the Nano-Tag subcutaneously in the forehead and administering sleep-disorder drugs to confirm if sleep-wake states could be measured using the Nano-Tag. When we compared the changes in awake time per unit time measured using polysomnography and locomotor activity counts per unit time measured using the Nano-Tag, cynomolgus monkeys exhibited a diurnal preference, and the correlation coefficients were positive during the 24-h period. Additionally, the correlation coefficients during the 12-h dark period were positive when the hypersomnia treatment drug modafinil was administered. The correlation coefficients during the 12-h light period were also positive when the insomnia treatment drug triazolam was administered. These results suggest that measuring locomotor activity is an effective tool for identifying sleep-wake states and screening sleep-disorder drugs at low cost and with less burden to animal subjects.

SUBMITTER: Sakai K

PROVIDER: S-EPMC7058904 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Simplified drug efficacy screening system for sleep-disorder drugs using non-human primates.

Sakai Keita K Ishikawa Akiyoshi A Mizuno Yuri Y Maki Takehiro T Oda Yasuhiro Y Takahashi Eiki E

Heliyon 20200304 3

The most widely used animal models to develop sleep-disorder drugs are rodents, particularly rats and mice. However, unlike humans, these rodents are nocturnal. Thus, diurnal non-human primates represent a valuable and more translational animal model to study sleep. Although sleep-disorder drugs have been screened in non-human primates, the use of a telemetry system is not a desirable method for a rapid drug efficacy assessment system because of the need for expensive equipment, complicated surg ...[more]

PMID: 32154428

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Project description:Highlights • Exploratory study: no systematically altered sleep macrostructure in MDD patients.• Non-REM fast sleep spindle amplitudes higher in unmedicated patients.• Antidepressants altered slow-wave activity and coupling to fast sleep spindles.• Long-term, not short-term medication linked to lower spindle density in patients.• Medicated patients had impaired procedural memory consolidation. Disturbed sleep is a key symptom in major depressive disorder (MDD). REM sleep alterations are well described in the current literature, but little is known about non-REM sleep alterations. Additionally, sleep disturbances relate to a variety of cognitive symptoms in MDD, but which features of non-REM sleep EEG contribute to this, remains unknown. We comprehensively analyzed non-REM sleep EEG features in two central channels in three independently collected datasets (N = 284 recordings of 216 participants). This exploratory and descriptive study included MDD patients with a broad age range, varying duration and severity of depression, unmedicated or medicated, age- and gender-matched to healthy controls. We explored changes in sleep architecture including sleep stages and cycles, spectral power, sleep spindles, slow waves (SW), and SW-spindle coupling. Next, we analyzed the association of these sleep features with acute measures of depression severity and overnight consolidation of procedural memory. Overall, no major systematic alterations in non-REM sleep architecture were found in patients compared to controls. For the microstructure of non-REM sleep, we observed a higher spindle amplitude in unmedicated patients compared to controls, and after the start of antidepressant medication longer SWs with lower amplitude and a more dispersed SW-spindle coupling. In addition, long-term, but not short-term medication seemed to lower spindle density. Overnight procedural memory consolidation was impaired in medicated patients and associated with lower sleep spindle density. Our results suggest that alterations of non-REM sleep EEG in MDD might be more subtle than previously reported. We discuss these findings in the context of antidepressant medication intake and age.

Project description:Study objectivesThere is currently no questionnaire-based pre-screening tool available to detect non-24-hour sleep-wake rhythm disorder (N24HSWD) among blind patients. Our goal was to develop such a tool, derived from gold standard, objective hormonal measures of circadian entrainment status, for the detection of N24HSWD among those with visual impairment.MethodsWe evaluated the contribution of 40 variables in their ability to predict N24HSWD among 127 blind women, classified using urinary 6-sulfatoxymelatonin period, an objective marker of circadian entrainment status in this population. We subjected the 40 candidate predictors to 1,000 bootstrapped iterations of a logistic regression forward selection model to predict N24HSWD, with model inclusion set at the p < 0.05 level. We removed any predictors that were not selected at least 1% of the time in the 1,000 bootstrapped models and applied a second round of 1,000 bootstrapped logistic regression forward selection models to the remaining 23 candidate predictors. We included all questions that were selected at least 10% of the time in the final model. We subjected the selected predictors to a final logistic regression model to predict N24SWD over 1,000 bootstrapped models to calculate the concordance statistic and adjusted optimism of the final model. We used this information to generate a predictive model and determined the sensitivity and specificity of the model. Finally, we applied the model to a cohort of 1,262 blind women who completed the survey, but did not collect urine samples.ResultsThe final model consisted of eight questions. The concordance statistic, adjusted for bootstrapping, was 0.85. The positive predictive value was 88%, the negative predictive value was 79%. Applying this model to our larger dataset of women, we found that 61% of those without light perception, and 27% with some degree of light perception, would be referred for further screening for N24HSWD.ConclusionsOur model has predictive utility sufficient to serve as a pre-screening questionnaire for N24HSWD among the blind.

Dataset Information

Simplified drug efficacy screening system for sleep-disorder drugs using non-human primates.

Publications

Simplified drug efficacy screening system for sleep-disorder drugs using non-human primates.

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