Tick-Tock Consider the Clock: The Influence of Circadian and External Cycles on Time of Day Variation in the Human Metabolome—A Review

Abstract

The past decade has seen a large influx of work investigating time of day variation in different human biofluid and tissue metabolomes. The driver of this daily variation can be endogenous circadian rhythms driven by the central and/or peripheral clocks, or exogenous diurnal rhythms driven by behavioural and environmental cycles, which manifest as regular 24 h cycles of metabolite concentrations. This review, of all published studies to date, establishes the extent of daily variation with regard to the number and identity of ‘rhythmic’ metabolites observed in blood, saliva, urine, breath, and skeletal muscle. The probable sources driving such variation, in addition to what metabolite classes are most susceptible in adhering to or uncoupling from such cycles is described in addition to a compiled list of common rhythmic metabolites. The reviewed studies show that the metabolome undergoes significant time of day variation, primarily observed for amino acids and multiple lipid classes. Such 24 h rhythms, driven by various factors discussed herein, are an additional source of intra/inter-individual variation and are thus highly pertinent to all studies applying untargeted and targeted metabolomics platforms, particularly for the construction of biomarker panels. The potential implications are discussed alongside proposed minimum reporting criteria suggested to acknowledge time of day variation as a potential influence of results and to facilitate improved reproducibility.

The Effect of Night Shifts on 24-h Rhythms in the Urinary Metabolome of Police Officers on a Rotating Work Schedule

“…However, the actigraphyderived sleep and wake times of our study population, as reported in Koshy et al (2019), suggest that the extent of sleep restriction due to night shift work was relatively small (i.e., on average less than 1 h) compared with previous studies, in which the sleep period was restricted to 4 h or less. Therefore, it is unlikely that sleep deprivation had a major impact on our results, a conclusion corroborated by a recent review that concluded that time of day has a larger impact than sleep disturbances on the urinary metabolome (Hancox et al, 2021).…”

“…However, despite its practicality, an important point of consideration when using urine for these types of analyses is the need for a suitable normalization method to account for differences in urinary flow rate. Creatinine normalization is routinely used but less appropriate since creatinine excretion may display diurnal variation-although this was not observed in the current study-and show substantial interindividual variation (Hancox et al, 2021). Taking advantage of the fact that urine volumes and voiding times were precisely documented during both study visits, we were able to calculate the urinary flow rate of each sample and use this to normalize metabolomic concentrations.…”

Rapid and reversible control of human metabolism by individual sleep states

“…Much of our knowledge of the control of metabolism by circadian clocks and sleep in humans comes from metabolomics, the systematic study of small molecules produced by anabolic and catabolic reactions, which can be sampled periodically across the day from blood, urine, and saliva (Ang et al, 2012;Dallmann et al, 2012;Bell et al, 2013;Davies et al, 2014;Skene et al, 2018;Grant et al, 2019;Kervezee et al, 2019;Honma et al, 2020;Hancox et al, 2021). These have been complemented by sampling accessible tissues, such as blood and adipose tissue, across time and analyzing the temporal pattern of RNAs (transcriptomics) or proteins (proteomics) therein (Spo ¨rl et al, 2012;Robles and Mann, 2013;Archer et al, 2014;Christou et al, 2019).…”

Analytical validation of a multi-protein, serum-based assay for disease activity assessments in multiple sclerosis

“…GH was also found to be more variable compared with the other biomarkers, which is not surprising, as GH has been previously reported to have a high degree of ultradian and diurnal variability. [28] For this reason, GH was removed from consideration for inclusion in the algorithm.…”