Circadian rhythms dictate the 24-hour shifts in gene expression, protein levels, and various cellular processes throughout the day, such as melatonin affecting our sleep-wake cycle. Such changes in cell activity—in particular, cyclical changes in metabolism— can greatly influence the effectiveness of a drug and the severity of its side effects, depending on when it is administered.
However, each individual has unique circadian timing, with "body time" being offset by as much as 6 hours between people, making it difficult—if not impossible—for doctors to take into account when giving drugs. Previous attempts to assess a person's body time have relied on intense, repeated sampling procedures that were impractical for clinical applications. But in a study, published yesterday (August 27) in Proceedings of the National Academy of Sciences, researchers have demonstrated a new method that requires only two blood samples, taken 12 hours apart.
"Due to a combination of genetics and...
Determining where in the cycle a person's body clock is at any given time typically involves measuring levels of melatonin and/or cortisol, chemicals that show robust patterns over a 24 hour period. However, sampling has to be done at continuous intervals for more than a day under controlled environmental conditions to determine the patient’s baseline levels. In the new study, Hiroki Ueda and colleagues at the RIKEN Center for Developmental Biology in Kobe, Japan, measured as many oscillating metabolites as possible, to create a chart of how they fluctuate in proportion to each other.
The concept is based on 16th-century botanist Carolus Linnaeus’ flower clock. "Each flower has different timing for opening and closing," said Ueda. Linnaeus reasoned that if he knew when a range of flowers opened and closed in a day, he could create a garden that could tell the time. "Likewise,” Ueda said, “each metabolite has different timing, so I applied this concept to the human body."
Three study participants had blood samples taken every hour for 1.5 days, under normal sleep-wake conditions, and then again after their normal cycles had been disrupted by a forced 28-hour sleep-wake schedule. Such disruption of natural circadian cycles is known to occur in shift workers, or people traveling between time zones, and can cause weight gain and obesity, metabolic abnormalities and diabetes, and even heart disease.
The researchers measured the levels of 58 metabolites by liquid chromatography mass spectrometry, and used radioimmunological assays to assess cortisol and meatonin levels. The metabolites, whose levels cycled in participants during their normal cycles, were tracked against patterns of melatonin and cortisol to calibrate the metabolite levels with the body clock. The researchers then drew up a table based on the proportions of metabolites across body times, and used it to estimate the body time of study participants using just two samples, taken 12 hours apart. During both disrupted and normal cycles, the team was able to estimate body times within 3 hours of real body time, as shown by the traditional cortisol/melatonin method involving sampling as often as every 20 minutes.
"In principle, the method holds great promise as a way of replacing the cumbersome melatonin assay," said Brown. "In practice, however, the method is still in its infancy." The method is still limited the accuracy of liquid chromatography mass spectrometry, for example, and more work is required to verify this proof of concept result.
But Ueda hopes he can move forward and scale up the study to track the metabolites of thousands of participants and build a comprehensive metabolite timetable. Such a massive dataset could reduce body clock estimation to a single sample per patient, and may eventually help make the practice common in clinical settings. "My small dream is that internal body time is going to be one of the ways for your health to be checked," he said.
T. Kasukawa et al., "Human blood metabolite timetable indicates internal body time," Proceedings of the National Academy of Sciences, doi: 10.1073/pnas.1207768109, 2012.
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