ABSTRACT The goal of the project is to optimize human health, performance, and safety by developing robust diagnostic biomarkers for circadian timing to identify, from a single biospecimen, the biological time within an individual. Our understanding of the importance of circadian timing to human health is increasing; disruption of circadian timing is associated with metabolic disorders, cardiovascular disease, immune dysregulation, and cancers. A recent study tested ~17,000 genes and found that nearly half cycled in at least one human tissue, and more than 900 of those cycling genes coded for proteins that are drug targets, transport drugs, or are involved in drug metabolism1. Building on this emerging knowledge, we should be able to regularize circadian timing to prevent disease, and to administer many short half-life drugs at their ideal circadian time to increase efficacy and/or reduce side effects. However, our ability to incorporate circadian timing into clinical decision-making and treatment is impaired by our current inability to measure circadian phase quickly and easily. Current methods for assessing circadian timing require sampling over hours (or even up to a day) while the patient is in controlled conditions. We aim to develop a method that can estimate individual circadian time with a single blood sample taken at any time of the day or night. To do this, we will use two state of the art methods, a plasma proteomics-based method to identify a panel of rhythmic proteins (extending our preliminary data) and a whole blood-derived monocyte-based method using a panel of 15 transcripts (to validate and extend a recent study). We will ensure the selected protein biomarker panel is robust to varying sleep-wake patterns by collecting samples under conditions of habitual sleep timing, under shortened ?weekday? sleep and extended ?weekend? sleep, and across ~40 hours of controlled posture, wake, and behaviour from a group of healthy, entrained, well- rested adults studied for a week in highly controlled laboratory conditions. We will also test both methods in a series of patients with circadian rhythm sleep disorders. We will validate separately the proteomics-based biomarker and the monocyte-based transcript biomarker, and also explore whether combining them can improve the accuracy of our timing estimates. In all cases, circadian phase estimates from the biomarker panels will be compared with those derived from plasma or saliva melatonin (the current ?gold-standard? circadian phase marker). The proposed project has the potential to: 1) reveal novel physiological pathways affected by circadian timing and sleep; 2) pave the way for improved diagnosis and treatment for patients with suspected circadian rhythm disorders (delayed sleep-wake phase disorder, shift work disorder) and other sleep pathologies (insomnia, hypersomnia); 3) advance personalized medicine through individualized treatment timing (chronomedicine).