Developing preliminary blood metabolomics-based biomarkers of insufficient sleep in humans. Issue 7 (2nd January 2020)

• Record Type: Journal Article
• Authors: Depner, Christopher M; Cogswell, Dasha T; Bisesi, Paul J; Markwald, Rachel R; Cruickshank-Quinn, Charmion; Quinn, Kevin; Melanson, Edward L; Reisdorph, Nichole; Wright, Kenneth P
• Is Part Of: Sleep. Volume 43:Issue 7(2020)
• Publication Date: 2020-01-02
• Subjects: sleep loss -- sleep restriction -- biomarker -- metabolomics -- sleep deprivation -- personalized medicine -- lipid metabolism -- sex differences; Sleep -- Physiological aspects -- Periodicals; Sleep disorders -- Periodicals; Sommeil -- Aspect physiologique -- Périodiques; Sommeil, Troubles du -- Périodiques; Sleep disorders; Sleep -- Physiological aspects; Sleep -- physiological aspects; Sleep Wake Disorders; Psychophysiology; Electronic journals; Periodicals; 616.8498
• DOI: 10.1093/sleep/zsz321
• Languages: English
• ISSNs: 0161-8105

Abstract

Abstract: Study Objective: Identify small molecule biomarkers of insufficient sleep using untargeted plasma metabolomics in humans undergoing experimental insufficient sleep. Methods: We conducted a crossover laboratory study where 16 normal-weight participants (eight men; age 22 ± 5 years; body mass index < 25 kg/m 2 ) completed three baseline days (9 hours sleep opportunity per night) followed by 5-day insufficient (5 hours sleep opportunity per night) and adequate (9 hours sleep opportunity per night) sleep conditions. Energy balanced diets were provided during baseline, with ad libitum energy intake provided during the insufficient and adequate sleep conditions. Untargeted plasma metabolomics analyses were performed using blood samples collected every 4 hours across the final 24 hours of each condition. Biomarker models were developed using logistic regression and linear support vector machine (SVM) algorithms. Results: The top-performing biomarker model was developed by linear SVM modeling, consisted of 65 compounds, and discriminated insufficient versus adequate sleep with 74% overall accuracy and a Matthew's Correlation Coefficient of 0.39. The compounds in the top-performing biomarker model were associated with ATP Binding Cassette Transporters in Lipid Homeostasis, Phospholipid Metabolic Process, Plasma Lipoprotein Remodeling, and sphingolipid metabolism. Conclusion: We identified potential metabolomics-based biomarkers of insufficient sleep in humans. Although our current biomarkers require further development and validation using independent cohorts, they have potential to advance our understanding of the negative consequences of insufficient sleep, improve diagnosis of poor sleep health, and could eventually help identify targets for countermeasures designed to mitigate the negative health consequences of insufficient sleep.