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.

Public Health Relevance

We propose to identify blood-based markers that can inform a clinician or researcher about an individual's internal biological clock. At the broad levels of society and public health research, the work has the potential direct benefit of identifying individuals with 'off-set' clocks (enabling diagnosis and potential therapy), increasing accuracy and precision of studies of blood lipids, facilitating understanding of certain sleep disorders, increasing understanding of the role of biological clocks in chronic disease processes (e.g., cancer, diabetes, cardiovascular disease), and potentially improving the administration of certain pharmaceuticals, eg, chemotherapy agents.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL132556-03
Application #
9457491
Study Section
Neural Basis of Psychopathology, Addictions and Sleep Disorders Study Section (NPAS)
Program Officer
Brown, Marishka
Project Start
2016-04-18
Project End
2020-03-31
Budget Start
2018-04-01
Budget End
2019-03-31
Support Year
3
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
Gathungu, Rose M; Larrea, Pablo; Sniatynski, Matthew J et al. (2018) Optimization of Electrospray Ionization Source Parameters for Lipidomics To Reduce Misannotation of In-Source Fragments as Precursor Ions. Anal Chem 90:13523-13532