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

Assessing the influence of sleep and sampling time on metabolites in oral fluid: implications for metabolomics studies

INTRODUCTION

The human salivary metabolome is a rich source of information for metabolomics studies. Among other influences, individual differences in sleep-wake history and time of day may affect the metabolome.

OBJECTIVES

We aimed to characterize the influence of a single night of sleep deprivation compared to sufficient sleep on the metabolites present in oral fluid and to assess the implications of sampling time points for the design of metabolomics studies.

METHODS

Oral fluid specimens of 13 healthy young males were obtained in Salivette® devices at regular intervals in both a control condition (repeated 8-hour sleep) and a sleep deprivation condition (total sleep deprivation of 8 h, recovery sleep of 8 h) and their metabolic contents compared in a semi-targeted metabolomics approach.

RESULTS

Analysis of variance results showed factor 'time' (i.e., sampling time point) representing the major influencer (median 9.24%, range 3.02-42.91%), surpassing the intervention of sleep deprivation (median 1.81%, range 0.19-12.46%). In addition, we found about 10% of all metabolic features to have significantly changed in at least one time point after a night of sleep deprivation when compared to 8 h of sleep.

CONCLUSION

The majority of significant alterations in metabolites' abundances were found when sampled in the morning hours, which can lead to subsequent misinterpretations of experimental effects in metabolomics studies. Beyond applying a within-subject design with identical sample collection times, we highly recommend monitoring participants' sleep-wake schedules prior to and during experiments, even if the study focus is not sleep-related (e.g., via actigraphy).

Effect of age on metabolomic changes in a model of paclitaxel-induced peripheral neurotoxicity

BACKGROUND AND AIMS

Chemotherapy-induced peripheral neurotoxicity (CIPN) is one of the most common dose-limiting side effects of paclitaxel (PTX) treatment. Many age-related changes have been hypothesized to underlie susceptibility to damage or impaired regeneration/repair after nerve injury. The results of these studies, however, are inconclusive and other potential biomarkers of nerve impairment need to be investigated.

METHODS

Twenty-four young (2 months) and 24 adult (9 months) Wistar male rats were randomized to either PTX treatment (10 mg/kg i.v. once/week for 4 weeks) or vehicle administration. Neurophysiological and behavioral tests were performed at baseline, after 4 weeks of treatment and 2-week follow-up. Skin biopsies and nerve specimens collected from sacrificed animals were examined for intraepidermal nerve fiber (IENF) density assessment and nerve morphology/morphometry. Blood and liver samples were collected for targeted metabolomics analysis.

RESULTS

At the end of treatment, the neurophysiological studies revealed a reduction in sensory nerve action potential amplitude (p < .05) in the caudal nerve of young PTX-animals, and in both the digital and caudal nerve of adult PTX-animals (p < .05). A significant decrease in the mechanical threshold was observed only in young PTX-animals (p < .001), but not in adult PTX-ones. Nevertheless, both young and adult PTX-rats had reduced IENF density (p < .0001), which persisted at the end of follow-up period. Targeted metabolomics analysis showed significant differences in the plasma metabolite profiles between PTX-animals developing peripheral neuropathy and age-matched controls, with triglycerides, diglycerides, acylcarnitines, carnosine, long chain ceramides, sphingolipids, and bile acids playing a major role in the response to PTX administration.

INTERPRETATION

Our study identifies for the first time multiple related metabolic axes involved in PTX-induced peripheral neurotoxicity, and suggests age-related differences in CIPN manifestations and in the metabolic profile.

Interindividual variability in coherence between self-reported alertness and performance in shift workers

OBJECTIVES

Evidence indicates that self-reported measures of alertness do not always reflect performance impairments. The present study aims to explore whether subjective and objective measures of vigilance vary in the same direction in individuals working nights.

METHODS

A total of 76 police officers participated to a month-long observational study. They worked either a 2 or 3-shift system during which they self-reported alertness and completed a psychomotor vigilance task several times a day.

RESULTS

A reduction in alertness and reaction speed was observed with time awake. At the group level, changes in alertness and reaction speed with time awake were positively correlated during night shifts only. In 63.6% of the officers, changes were coherent between both variables. The other officers reported that their alertness dropped (25.5%) or improved (10.9%) whereas their performance changed in the opposite direction.

CONCLUSION

Significant interindividual variability exists in self-appraisal vigilance impairment due to night shift work.

Exploratory analyses on the effect of time since last meal on concentrations of amino acids, lipids, one-carbon metabolites, and vitamins in the Hordaland Health Study

PURPOSE

Dietary intake may have pronounced effects on circulating biomarker concentrations. Therefore, the aim was to provide a descriptive overview of serum metabolite concentrations in relation to time since last meal, focusing on amino acids, lipids, one-carbon metabolites, and biomarkers of vitamin status.

METHODS

We used baseline data from the observational community-based Hordaland Health Study, including 2960 participants aged 46-49 years and 2874 participants aged 70-74 years. A single blood draw was taken from each participant, and time since last meal varied. Estimated marginal geometric mean metabolite concentrations were plotted as a function of time since last meal, up to 7 h, adjusted for age, sex, and BMI.

RESULTS

We observed a common pattern for nearly all amino acids and one-carbon metabolites with highest concentrations during the first 3 h after dietary intake. Homocysteine and cysteine were lowest the 1st hour after a meal, while no patterns were observed for glutamate and glutamic acid. The concentrations of phylloquinone and triglycerides were highest 1 h after dietary intake. Thiamine and thiamine monophosphate concentrations were highest, while flavin mononucleotide concentrations were lowest within the first 2 h after a meal. No clear patterns emerged for the other fat-soluble vitamins, blood lipids, or B-vitamin biomarkers.

CONCLUSION

Our findings suggest that distinguishing between "fasting" and "non-fasting" blood samples may be inadequate, and a more granular approach is warranted. This may have implications for how to account for dietary intake when blood sampling in both clinical and research settings.

Machine learning estimation of human body time using metabolomic profiling

Circadian rhythms influence physiology, metabolism, and molecular processes in the human body. Estimation of individual body time (circadian phase) is therefore highly relevant for individual optimization of behavior (sleep, meals, sports), diagnostic sampling, medical treatment, and for treatment of circadian rhythm disorders. Here, we provide a partial least squares regression (PLSR) machine learning approach that uses plasma-derived metabolomics data in one or more samples to estimate dim light melatonin onset (DLMO) as a proxy for circadian phase of the human body. For this purpose, our protocol was aimed to stay close to real-life conditions. We found that a metabolomics approach optimized for either women or men under entrained conditions performed equally well or better than existing approaches using more labor-intensive RNA sequencing-based methods. Although estimation of circadian body time using blood-targeted metabolomics requires further validation in shift work and other real-world conditions, it currently may offer a robust, feasible technique with relatively high accuracy to aid personalized optimization of behavior and clinical treatment after appropriate validation in patient populations.

Rhythms in barriers and fluids: Circadian clock regulation in the aging neurovascular unit

The neurovascular unit is where two very distinct physiological systems meet: The central nervous system (CNS) and the blood. The permeability of the barriers separating these systems is regulated by time, including both the 24 h circadian clock and the longer processes of aging. An endogenous circadian rhythm regulates the transport of molecules across the blood-brain barrier and the circulation of the cerebrospinal fluid and the glymphatic system. These fluid dynamics change with time of day, and with age, and especially in the context of neurodegeneration. Factors may differ depending on brain region, as can be highlighted by consideration of circadian regulation of the neurovascular niche in white matter. As an example of a potential target for clinical applications, we highlight chaperone-mediated autophagy as one mechanism at the intersection of circadian dysregulation, aging and neurodegenerative disease. In this review we emphasize key areas for future research.

Demographic, Health and Lifestyle Factors Associated with the Metabolome in Older Women

Demographic and clinical factors influence the metabolome. The discovery and validation of disease biomarkers are often challenged by potential confounding effects from such factors. To address this challenge, we investigated the magnitude of the correlation between serum and urine metabolites and demographic and clinical parameters in a well-characterized observational cohort of 444 post-menopausal women participating in the Women’s Health Initiative (WHI). Using LC-MS and lipidomics, we measured 157 aqueous metabolites and 756 lipid species across 13 lipid classes in serum, along with 195 metabolites detected by GC-MS and NMR in urine and evaluated their correlations with 29 potential disease risk factors, including demographic, dietary and lifestyle factors, and medication use. After controlling for multiple testing (FDR < 0.01), we found that log-transformed metabolites were mainly associated with age, BMI, alcohol intake, race, sample storage time (urine only), and dietary supplement use. Statistically significant correlations were in the absolute range of 0.2–0.6, with the majority falling below 0.4. Incorporation of important potential confounding factors in metabolite and disease association analyses may lead to improved statistical power as well as reduced false discovery rates in a variety of data analysis settings.

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

PURPOSE

To characterize and analytically validate the MSDA Test, a multi-protein, serum-based biomarker assay developed using Olink^® PEA methodology.

EXPERIMENTAL DESIGN

Two lots of the MSDA Test panel were manufactured and subjected to a comprehensive analytical characterization and validation protocol to detect biomarkers present in the serum of patients with multiple sclerosis (MS). Biomarker concentrations were incorporated into a final algorithm used for calculating four Disease Pathway scores (Immunomodulation, Neuroinflammation, Myelin Biology, and Neuroaxonal Integrity) and an overall Disease Activity score.

RESULTS

Analytical characterization demonstrated that the multi-protein panel satisfied the criteria necessary for a fit-for-purpose validation considering the assay's intended clinical use. This panel met acceptability criteria for 18 biomarkers included in the final algorithm out of 21 biomarkers evaluated. VCAN was omitted based on factors outside of analytical validation; COL4A1 and GH were excluded based on imprecision and diurnal variability, respectively. Performance of the four Disease Pathway and overall Disease Activity scores met the established acceptability criteria.

CONCLUSIONS AND CLINICAL RELEVANCE

Analytical validation of this multi-protein, serum-based assay is the first step in establishing its potential utility as a quantitative, minimally invasive, and scalable biomarker panel to enhance the standard of care for patients with MS.

Metabolomics-based Sleepiness Markers for Risk Prevention and Traffic Safety (ME-SMART): a monocentric, controlled, randomized, crossover trial

BACKGROUND

Too little sleep and the consequences thereof are a heavy burden in modern societies. In contrast to alcohol or illicit drug use, there are no quick roadside or workplace tests for objective biomarkers for sleepiness. We hypothesize that changes in physiological functions (such as sleep-wake regulation) are reflected in changes of endogenous metabolism and should therefore be detectable as a change in metabolic profiles. This study will allow for creating a reliable and objective panel of candidate biomarkers being indicative for sleepiness and its behavioral outcomes.

METHODS

This is a monocentric, controlled, randomized, crossover, clinical study to detect potential biomarkers. Each of the anticipated 24 participants will be allocated in randomized order to each of the three study arms (control, sleep restriction, and sleep deprivation). These only differ in the amount of hours slept per night. In the control condition, participants will adhere to a 16/8 h wake/sleep regime. In both sleep restriction and sleep deprivation conditions, participants will accumulate a total sleep deficit of 8 h, achieved by different wake/sleep regimes that simulate real-life scenarios. The primary outcome is changes in the metabolic profile (i.e., metabolome) in oral fluid. Secondary outcome measures will include driving performance, psychomotor vigilance test, d2 Test of Attention, visual attention test, subjective (situational) sleepiness, electroencephalographic changes, behavioral markers of sleepiness, changes in metabolite concentrations in exhaled breath and finger sweat, and correlation of metabolic changes among biological matrices.

DISCUSSION

This is the first trial of its kind that investigates complete metabolic profiles combined with performance monitoring in humans over a multi-day period involving different sleep-wake schedules. Hereby, we aim to establish a candidate biomarker panel being indicative for sleepiness and its behavioral outcomes. To date, there are no robust and easily accessible biomarkers for the detection of sleepiness, even though the vast damage on society is well known. Thus, our findings will be of high value for many related disciplines.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier NCT05585515, released on 18.10.2022; Swiss National Clinical Trial Portal SNCTP000005089, registered on 12 August 2022.

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

Shift workers face an increased risk of metabolic health problems, but the direct metabolic response to working nights is not fully understood. The aim of this study was to investigate the effect of night shifts on the 24-h urinary metabolome of shift workers. Eleven police officers working rotating shifts completed two 24-h laboratory visits that took place before and after they worked 7 consecutive nights. Sleep and meals were scheduled on a day schedule in the first visit and then on a night schedule (i.e., sleep and meals shifted by approximately 12 h) in the second visit. Targeted metabolomic analysis was performed on urine samples collected throughout these laboratory visits. Differential rhythmicity analysis was used to compare 24-h rhythms in urinary metabolites in both conditions. Our results show that on the day schedule, 24-h rhythms are present in the urinary levels of the majority of metabolites, but that this is significantly reduced on the night schedule, partly due to loss of organic acid rhythmicity. Furthermore, misalignment of 24-h metabolite rhythms with the shifted behavioral cycles in the night schedule was observed in more than half of the metabolites that were rhythmic in both conditions (all acylcarnitines). These results show that working nights alters the daily rhythms of the urinary metabolome in rotating shift workers, with the most notable impact observed for acylcarnitines and organic acids, 2 metabolite classes involved in mitochondrial function. Further research is warranted to study how these changes relate to the increased metabolic risks associated with shift work.

The Mammalian Circadian Time-Keeping System

Our physiology and behavior follow precise daily programs that adapt us to the alternating opportunities and challenges of day and night. Under experimental isolation, these rhythms persist with a period of approximately one day (circadian), demonstrating their control by an internal autonomous clock. Circadian time is created at the cellular level by a transcriptional/translational feedback loop (TTFL) in which the protein products of the Period and Cryptochrome genes inhibit their own transcription. Because the accumulation of protein is slow and delayed, the system oscillates spontaneously with a period of ∼24 hours. This cell-autonomous TTFL controls cycles of gene expression in all major tissues and these cycles underpin our daily metabolic programs. In turn, our innumerable cellular clocks are coordinated by a central pacemaker, the suprachiasmatic nucleus (SCN) of the hypothalamus. When isolated in slice culture, the SCN TTFL and its dependent cycles of neural activity persist indefinitely, operating as "a clock in a dish". In vivo, SCN time is synchronized to solar time by direct innervation from specialized retinal photoreceptors. In turn, the precise circadian cycle of action potential firing signals SCN-generated time to hypothalamic and brain stem targets, which co-ordinate downstream autonomic, endocrine, and behavioral (feeding) cues to synchronize and sustain the distributed cellular clock network. Circadian time therefore pervades every level of biological organization, from molecules to society. Understanding its mechanisms offers important opportunities to mitigate the consequences of circadian disruption, so prevalent in modern societies, that arise from shiftwork, aging, and neurodegenerative diseases, not least Huntington's disease.

Metabolic profiling of night shift work - The HORMONIT study

Mechanistic studies are needed to understand how rotating shift work perturbs metabolic processing. We collected plasma samples (n = 196) from 49 males, rotating car factory shift workers at the beginning and end of a night-shift (22:00-06:00 h) and day-shift (06:00 h-14:00 h). Samples underwent targeted LC-MS/MS metabolomics and concentrations of 130 metabolites were log2-transformed and pareto-scaled. An elastic net selected the most influential metabolites for linear mixed models examining within-person variation in metabolite levels at night-shift end (06:00 h) compared to day-shift start (06:00 h). Quantitative enrichment analysis explored differentially enriched biological pathways between sample time points. We included 20 metabolites (amino acids, biogenic amines, acylcarnitines, glycerophospholipids) in mixed models. Night-shift was associated with changes in concentrations of arginine (geometric mean ratio [GMR] 2.30, 95%CI 1.25, 4.23), glutamine (GMR 2.22, 95%CI 1.53, 3.24), kynurenine (GMR 3.22, 95%CI 1.05, 9.87), lysoPC18:2 (GMR 1.86, 95%CI 1.11, 3.11), lysoPC20:3 (GMR 2.48, 95%CI 1.05, 5.83), PCaa34:2 (GMR 2.27, 95%CI 1.16, 4.44), and PCae38:5 (GMR 1.66, 95%CI 1.02, 2.68). Tryptophan metabolism, glutathione metabolism, alanine metabolism, glycine and serine metabolism, and urea cycle were pathways differing between shifts. Night shift work was associated with changes in metabolites and the perturbation of metabolic and biochemical pathways related to a variety of health outcomes.

The Diurnal Blood Metabolome and Effects of Vitamin D Supplementation: A Randomised Crossover Trial in Postmenopausal Women

A way to maintain an adequate vitamin D status is through supplementation. Demonstration of blood-metabolome rhythmicity of vitamin D3 post-dosing effects is lacking in the pharmaco-metabonomics area. Thus, the overall aim of this study was to investigate the diurnal changes in the blood metabolome and how these are affected by vitamin D3 supplementation. The study was conducted as a crossover study, and the treatment included 200 µg (8000 IU) of vitamin D3 as compared with placebo with a washout period of at least 10 days. The participants were postmenopausal women aged 60−80 years (N = 29) with vitamin D insufficiency (serum 25-hydroxyvitamin D < 50 nmol/L) but otherwise healthy. During the intervention day, blood samples were taken at 0 h, 2 h, 4 h, 6 h, 8 h, 10 h, 12 h, and 24 h, and plasma was analysed by proton nuclear magnetic resonance (NMR) spectroscopy as a metabolomics approach. In general, diurnal effects were identified for the majority of the 20 quantified metabolites, and hierarchical cluster analysis revealed a change in the overall plasma metabolome around 12 AM (6 h after intervention), suggesting that the diurnal rhythm is reflected in two diurnal plasma metabolomes; a morning metabolome (8−12 AM) and an afternoon/evening metabolome (2−8 PM). Overall, the effect of vitamin D supplementation on the blood metabolome was minor, with no effect on the diurnal rhythm. However, a significant effect of the vitamin D supplementation on plasma acetone levels was identified. Collectively, our findings reveal an influence of diurnal rhythm on the plasma metabolome, while vitamin D supplementation appears to have minor influence on fluctuations in the plasma metabolome.

Rapid and reversible control of human metabolism by individual sleep states

Sleep is crucial to restore body functions and metabolism across nearly all tissues and cells, and sleep restriction is linked to various metabolic dysfunctions in humans. Using exhaled breath analysis by secondary electrospray ionization high-resolution mass spectrometry, we measured the human exhaled metabolome at 10-s resolution across a night of sleep in combination with conventional polysomnography. Our subsequent analysis of almost 2,000 metabolite features demonstrates rapid, reversible control of major metabolic pathways by the individual vigilance states. Within this framework, whereas a switch to wake reduces fatty acid oxidation, a switch to slow-wave sleep increases it, and the transition to rapid eye movement sleep results in elevation of tricarboxylic acid (TCA) cycle intermediates. Thus, in addition to daily regulation of metabolism, there exists a surprising and complex underlying orchestration across sleep and wake. Both likely play an important role in optimizing metabolic circuits for human performance and health.