Circadian Lipidomics in Constant Routine, Forced Desynchrony, and Non-lab Setting

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 DESCRIPTION (provided by applicant): Disrupted circadian timing has emerged as a serious health and safety issue, yet there are no objective means of easily assessing circadian timing or alignment without performing a highly controlled, multiple-day in- patient study. Altered circadian timing can cause both sleep loss and sleepiness, cause performance errors such as motor vehicle accidents, and impair memory/learning. Thus, despite the obvious need to recognize an individual's circadian phase/alignment, we cannot assess circadian timing clinically or in retrospective studies. Not surprisingly, the first goal of the 2011 NIH Sleep Disorders Research Plan is to identify: "...metabolic... biomarkers of sleep deficiency and biological timing...and circadian disorders that will facilitate personalized treatments, and clarify the risk associated with untreated sleep and circadian disorders and disturbances." We are aware that major challenges face biomarker development, including multi-factorial causes of metabolite shifts normally controlled across multiple time-points. Because circadian time is associated with profound metabolic, immune and cardiovascular changes, however, we hypothesize that a biomarker signature for circadian phase derived from -omic markers can be obtained from a single blood sample. We therefore propose to utilize the analytical and bioinformatics platforms and experience in population-level metabolomics studies in the PIs lab to study banked plasma samples from the well-characterized individuals in six tightly controlled circadian rhythm studies run by the four co-investigators.The Aims are: Aim 1: To identify, to optimize, to validate, and t cross-validate a set of nested plasma lipidomics- based biomarker profiles that report circadian phase and alignment using well-characterized samples drawn from three constant routine protocols Aim 2: To identify, to optimize, to validate, and to cross-validate a set of nested plasma lipidomics based biomarker profiles that report circadian phase and alignment using well-characterized samples drawn from four forced desynchrony protocols Aim 3: To systematically evaluate the validated profiles from Aims 1 and 2 and their mathematical similarities and differences so as to improve accuracy and precision of the biomarkers Aim 4: To test the markers identified above under poorly controlled real world applications Identification of biomarker panels will impact multiple aspects of science and health: (i) contribute to clinical recognition and treatment on circadian disorders; (ii) advance personalized medicine through individualized treatment timing to enhance efficacy/reduce side effects of medications (e.g., chemotherapy); (iii) creating epidemiologic tools to relate circadian with disease risk; and aiding development of other disease biomarkers, and; (iv) contribute to research on circadian biology and its implications for human health.