Validation of real-time field-based markers of circadian phase

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Project Summary Despite mounting evidence that the body’s internal 24-hour circadian clock plays key roles in both the diagnosis and effective treatment of many diseases, including diseases of aging such as Alzheimer’s disease, there remain significant barriers to implementing circadian-based diagnostic and treatment strategies. Our major focus in this proposal is on the lack of accurate and validated tools to measure circadian rhythms in real-time in a non- research setting. The current gold-standard approaches require measurement of a robust output marker of the circadian system (e.g., melatonin or cortisol) from frequent serial samples of blood, saliva, or urine collected over an 8-48 hour period under highly controlled conditions, which is impractical in patient populations. Moreover, a significant limitation of this approach is that results cannot be obtained immediately, as samples must be sent for assay and analyzed before results can be obtained. This delay, which can be several days or weeks, is problematic, because if the circadian system is disrupted or unstable, then the results may no longer be useful, e.g., for timing of effective treatment, by the time they are received. No point-of-care methods currently exist to measure circadian rhythms in our most robust circadian marker, melatonin. Recently, however, we have identified other markers of the circadian clock that maintain robust rhythms in field-based non-research settings, and these markers can be measured in real-time using existing point-of-care devices. We have an ongoing study in healthy participants between the ages of 26 and 55 years old to validate field-based measures of circadian rhythms in these novel markers. Before this approach can be extended to patient populations, however, we need to validate our findings in older individuals 55-70 years old (Aim 1), who would be the expected target population for subsequent studies of circadian-based diagnostic and treatment strategies. We also need to understand the impact of certain types of medications on our ability to detect rhythms in these markers (Aim 2), as to date these methods have been tested in non-medicated individuals only. Participants in our study will be asked to measure and record readings from point-of-care devices at home for a 48-hour period while also recording their sleep- wake activity, meal timing, and medication usage. Cosinor analyses will be applied to each 48-hour profile to quantify the presence of a significant circadian rhythm. The findings from this study are a critical step in the development of circadian-based treatment for diseases of aging, including Alzheimer’s disease, in which disruption of circadian rhythms is highly prevalent and for which treatment of circadian disruption can alleviate symptoms and may even slow the progression of disease. This pilot study thus will provide important preliminary data for a future R01 to measure circadian rhythms in a broader population at home or in the outpatient/PCP clinic as well as to prospectively test circadian-based timing of treatment using real-time assessment of circadian rhythms.