LAUSR

STUDY OBJECTIVE Identify small molecule biomarkers of insufficient sleep using untargeted plasma metabolomics in humans undergoing experimental insufficient sleep. METHODS We conducted a cross-over laboratory study where 16 normal weight participants (8 men; age 22 ± 5 years; body mass index < 25 kg/m2) completed three baseline days (9h sleep opportunity per night) followed by five day insufficient (5h sleep opportunity per night) and adequate (9h 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 4h across the final 24h of each condition. Biomarker models were developed using logistic regression and linear support vector machine algorithms. RESULTS The top performing biomarker model was developed by linear support vector machine 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.