Abstract
Diagnosis and treatment of circadian rhythm sleep-wake disorders requires assessment of circadian phase of the brain’s circadian pacemaker. The gold-standard univariate method is based on collection of a 24 h time series of plasma melatonin, a suprachiasmatic nucleus driven pineal hormone. We developed and validated a multivariate whole-blood mRNA based predictor of melatonin phase which requires few samples. Transcriptome data were collected under normal, sleep-deprivation and abnormal sleep-timing conditions to assess robustness of the predictor. Partial least square regression (PLSR), applied to the transcriptome, identified a set of 100 biomarkers primarily related to glucocorticoid signaling and immune function. Validation showed that PLSR-based predictors outperform published blood-derived circadian phase predictors. When given one sample as input, the R2 of predicted vs observed phase was 0.74, whereas for two samples taken 12 h apart, R2 was 0.90. This blood transcriptome based model enables assessment of circadian phase from a few samples.