Abstract
Accurate determination of circadian phase is necessary for research and clinical purposes because of the influence of the master circadian pacemaker on multiple physiologic functions. Melatonin is presently the most accurate marker of the activity of the human circadian pacemaker. Current methods of analyzing the plasma melatonin rhythm can be grouped into three categories: curve-fitting, threshold-based and physiologically-based linear differential equations. To determine which method provides the most accurate assessment of circadian phase, we compared the ability to fit the data and the variability of phase estimates for seventeen different markers of melatonin phase derived from these methodological categories. We used data from three experimental conditions under which circadian rhythms - and therefore calculated melatonin phase - were expected to remain constant or progress uniformly. Melatonin profiles from older subjects and subjects with lower melatonin amplitude were less likely to be fit by all analysis methods. When circadian drift over multiple study days was algebraically removed, there were no significant differences between analysis methods of melatonin onsets (P = 0.57), but there were significant differences between those of melatonin offsets (P<0.0001). For a subset of phase assessment methods, we also examined the effects of data loss on variability of phase estimates by systematically removing data in 2-hour segments. Data loss near onset of melatonin secretion differentially affected phase estimates from the methods, with some methods incorrectly assigning phases too early while other methods assigning phases too late; missing data at other times did not affect analyses of the melatonin profile. We conclude that melatonin data set characteristics, including amplitude and completeness of data collection, differentially affect the results depending on the melatonin analysis method used.
Highlights
Circadian phase is a major determinant of the time course and level of sleepiness, cognitive performance, many hormone concentrations and multiple other physiologic functions
The data sets that could not be fit by a method had significantly smaller amplitudes than the data sets that could be fit (63.5657.3 (s.d.) vs. 129.7675.5 pmol/L; p,0.001 by t-test), there was overlap in the range of amplitudes of those that could not and those that could be fit by analysis methods
When data were fit without first removing circadian drift, there were significant differences (P,0.05) in calculated variabilities between the six study groups using all but one melatonin method (Syn-off)
Summary
Circadian phase is a major determinant of the time course and level of sleepiness, cognitive performance, many hormone concentrations and multiple other physiologic functions. Accurate measurement of circadian phase is vital for the correct diagnosis and appropriate treatment for circadian rhythm sleep disorders. Since circadian phase of the suprachiasmatic nucleus (SCN), the site of the mammalian circadian pacemaker, cannot be measured directly in humans, outputs of the clock must be used as markers of the circadian system. Used circadian phase markers include core body temperature (CBT), cortisol, and melatonin. A critical factor in choosing an appropriate marker for assessing circadian phase, either for clinical applications or research, is the influence of exogenous factors that can directly mask, or obscure, the underlying endogenous circadian rhythm of the output marker. Concentrations of melatonin or its metabolites can be obtained from blood, saliva, or urine specimens [4,5,6,7]
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