Identifying and validating blood mRNA biomarkers for acute and chronic insufficient sleep in humans: a machine learning approach.

ABSTRACT: Acute and chronic insufficient sleep are associated with adverse health outcomes and risk of accidents. There is therefore a need for biomarkers to monitor sleep debt status. None are currently available. We applied elastic net and ridge regression to transcriptome samples collected in 36 healthy young adults during acute total sleep deprivation and following 1 week of either chronic insufficient (<6 hr) or sufficient sleep (~8.6 hr) to identify panels of mRNA biomarkers of sleep debt status. The size of identified panels ranged from 9 to 74 biomarkers. Panel performance, assessed by leave-one-subject-out cross-validation and independent validation, varied between sleep debt conditions. Using between-subject assessments based on one blood sample, the accuracy of classifying "acute sleep lo

SUBMITTER: Laing EE 

PROVIDER: S-EPMC6335875 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature