Dr Victoria Revell

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.

Isolation from external time cues allows endogenous circadian rhythmicity to be demonstrated. In this study, also filmed as a television documentary, we assessed rhythmic changes in a healthy man time isolated in a bunker for 9 days/nights. During this period the lighting conditions were varied between: (1) self-selected light/dark cycle, (2) constant dim light, and (3) light/dark cycle with early wake up. A range of variables was assessed and related to the sleep-wake cycle, psychomotor and physical performance and clock-time estimation. This case study using modern non-invasive monitoring techniques emphasizes how different physiological circadian rhythms persist in temporal isolation under constant dim light conditions with different waveforms, free-running with a period (t) between 24 and 25 h. In addition, a significant correlation between time estimation and mid-sleep time, a proxy for circadian phase, was demonstrated.

Studying circadian rhythms in most human tissues is hampered by difficulty in collecting serial samples. Here we reveal circadian rhythms in the transcriptome and metabolic pathways of human white adipose tissue. Subcutaneous adipose tissue was taken from seven healthy males under highly controlled ‘constant routine’ conditions. Five biopsies per participant were taken at six-hourly intervals for microarray analysis and in silico integrative metabolic modelling. We identified 837 transcripts exhibiting circadian expression profiles (2% of 41619 transcript targeting probes on the array), with clear separation of transcripts peaking in the morning (258 probes) and evening (579 probes). There was only partial overlap of our rhythmic transcripts with published animal adipose and human blood transcriptome data. Morning-peaking transcripts associated with regulation of gene expression, nitrogen compound metabolism, and nucleic acid biology; evening-peaking transcripts associated with organic acid metabolism, cofactor metabolism and redox activity. In silico pathway analysis further indicated circadian regulation of lipid and nucleic acid metabolism; it also predicted circadian variation in key metabolic pathways such as the citric acid cycle and branched chain amino acid degradation. In summary, in vivo circadian rhythms exist in multiple adipose metabolic pathways, including those involved in lipid metabolism, and core aspects of cellular biochemistry.

Humans have largely supplanted natural light cycles with a variety of artificial light sources and schedules misaligned with day-night cycles. Circadian disruption has been linked to a number of disease processes, but the extent of circadian disruption among the population is unknown. We measured light exposure and wrist temperature among residents of an urban area for a full week during each of the four seasons, as well as light illuminance in nearby outdoor locations. Daily light exposure was significantly lower for individuals, compared to outdoor light sensors, for all four seasons. There was also little seasonal variation in the realized photoperiod experienced by individuals, with the only significant difference between winter and summer. We tested the hypothesis that differential light exposure impacts circadian phase timing, detected via the wrist temperature rhythm. To determine the influence of light exposure on circadian rhythms, we modeled the impact of morning, afternoon, and nighttime light exposure on the timing of the midline-estimating statistic of rhythm (MESOR). We found that morning light exposure and nighttime light exposure had a significant but opposing impact on MESOR timing. Our results demonstrate that nighttime light can shift/alter circadian rhythms to delay the morning transition from nighttime to daytime physiology, while morning light can lead to earlier onset. Our results demonstrate that circadian shifts and disruptions may be a more regular occurrence in the general population than is currently recognized. Significance Statement: Disruption of circadian rhythms has been linked to various diseases, but the prevalence of circadian disruption among the general population is unknown. Light plays a pivotal role in entraining circadian rhythms to the 24-hour day. Humans have largely supplanted natural light cycles with electrical lighting and through time spent indoors. We have shown that individuals experience a disconnect from natural light cycles, with low daytime light exposure, high levels of light-at-night, and minimal seasonal variation in light exposure. We identified measurable changes in the timing of wrist temperature rhythms as a function of differential light exposure during the morning and nighttime hours. Our findings suggest that circadian shifts, and potentially disruption, may be common in the general population.

Background Nocturnal disturbance is frequently observed in dementia and is a major contributor to institutionalisation. Unobtrusive technology that can quantify sleep/wake and determine bed occupancy during the major nocturnal sleep episode may be beneficial for long-term clinical monitoring and the carer. Such technologies have, however, not been validated in older people. Here we assessed the performance of the Withings Sleep Mattress (WSM) in a heterogenous older population to ensure external validity. Method Eighteen participants (65 – 80 years, 10M:8F) completed 7-12 days of sleep/wake monitoring at home prior to an overnight laboratory session. WSM performance was compared to gold-standard (laboratory polysomnography [PSG] with video) and silver standard (actiwatch [AWS] and sleep diary at home). WSM data were downloaded from a third party API and the minute-to-minute sleep/wake timeseries extracted and time-ordered to create a sleep profile. Discontinuities in the timeseries were labelled as ‘missing data’ events. Results Participants contributed 107 nights with WSM and PSG or AWS data. In the laboratory, the overall epoch to epoch agreement (accuracy) of sleep/wake detection of WSM compared to PSG was 0.71 (sensitivity 0.8; specificity 0.45) and to AWS was 0.74 (sensitivity 0.77; specificity 0.53). Visual inspection of video recordings demonstrated that 20 of 21 ‘missing data’ events were true ‘out of bed’ events. These events were always associated with an increase in activity (AWS). At home, all 97 WSM ‘missing data’ events that occurred within the major nocturnal sleep episode defined by sleep diary data, were associated with an increase in activity levels in the AWS data and 36 of these events were also associated with an increase in light levels, indicating that the participant had left the bed. In several participants, data recorded by the WSM during daytime coincided with reported naps in the sleep diary. Conclusion Although WSM cannot reliably distinguish between sleep and wake, the presence/absence of data in WSM seem to be an accurate representation of whether older people are in or out of bed (bed occupancy). Thus, in dementia, this contactless, low-burden technology may be able to provide information about nocturnal disturbances and daytime naps in bed.

Background The incidence of sleep disturbances increases with normal aging and is highly prevalent among people living with dementia (PLWD). To facilitate management and improvement of sleep quality in PLWD, validated unintrusive contactless technologies for long term objective monitoring of sleep are needed. Here we evaluate the ability of a contactless sleep tracker to accurately determine Time in Bed (TIB), Wake vs Sleep and Sleep stages (wake, light, deep, and REM sleep). Method We deployed the Emfit (Emfit QS), a contactless sleep tracker placed under the mattress. The Emfit uses ballistography to estimate respiration and heart rate and sleep stages. We collected data from 16 participants (Age: Mean‐72.12; SD‐4.6 years [6F:10M]) at home for a 14‐day period followed by a single overnight laboratory polysomnography (PSG) sleep assessment. The Emfit outputs a) timeseries at 30 s intervals (four sleep stages) and b) overnight summary sleep parameters. Sleep staging and sleep parameter estimation by Emfit was compared to, a) in‐lab gold standard PSG, and b) at‐home wristworn accelerometer (Actiwatch spectrum (AWS)) and sleep diary (SD) data. The epoch‐to‐epoch sleep staging concordance of Emfit was estimated over the total recording interval (∼10hrs) of the PSG for the laboratory session and between 1800hrs and 1200hrs for each SD entry for the home recordings. The concordance analysis for the sleep parameters, bed entry and exit times were performed using the summary data automatically generated by Emfit. Result The concordance between the four‐class sleep staging of the Emfit and PSG was poor (Figure 1). The two class (sleep/wake) analysis (Table 1) showed high sleep classification accuracy (sensitivity) but poor wake classification accuracy (specificity) compared to PSG. The sleep parameter estimates of Emfit also showed poor agreement with PSG (Figure 2). The home analysis indicated excellent accuracy for Time in Bed (TIB) (i.e., the bed entry and exit times) as registered by the SD (Table 2) and total sleep time (TST) for both sleep diary and AWS (Figure 3). Conclusion : The contactless sleep tracker provides accurate information about Time in Bed (TIB), but there is a lack of consensus of the sleep state classification with the PSG.

Light influences diverse aspects of human physiology and behaviour including neuroendocrine function, the circadian system and sleep. A role for melanopsin-expressing intrinsically photosensitive retinal ganglion cells (ipRGCs) in driving such effects is well-established. However, rod and/or cone signals routed through ipRGCs could also influence 'non-visual' spectral sensitivity. In humans, this has been most extensively studied for acute, light-dependent, suppression of nocturnal melatonin production. Of the published action spectra for melatonin suppression, one demonstrates a spectral sensitivity consistent with that expected for melanopsin while our own (using briefer 30 min light exposures) displays very high sensitivity to short wavelength light, suggesting a contribution of S-cones. To clarify that possibility, six healthy young male participants were each exposed to 30 min of five irradiances of 415 nm monochromatic light (1 - 40 µW/cm ) across different nights. These data were then combined with the original action spectrum. The aggregated data are incompatible with the involvement of any single opsin and multi-opsin models based on the original action spectrum (including Circadian Stimulus) fail to predict the responses to 415 nm stimuli. Instead, the extended action spectrum can be most simply approximated by an ~2:1 combination of melanopsin and S-cone signals. Such a model also better describes the magnitude of melatonin suppression observed in other studies using an equivalent 30 min mono- or polychromatic light paradigm but not those using longer (90 min) light exposures. In sum, these data provide evidence for an initial S-cone contribution to melatonin suppression that rapidly decays under extended light exposure.

Wearable heart rate monitors offer a cost-effective way of non-invasive, long-term monitoring of cardiac health. Validation of wearable technologies in an older populations is essential for evaluating their effectiveness during deployment in healthcare settings. To this end, we evaluated the validity of heart rate measures from a wearable device, Empatica E4, and compared them to the electrocardiography (ECG). We collected E4 data simultaneously with ECG in thirty-five older men and women during an overnight sleep recording in the laboratory. We propose a robust approach to resolve the missing inter-beat interval (IBI) data and improve the quality of E4 derived measures. We also evaluated the concordance of heart rate (HR) and heart rate variability (HRV) measures with ECG. The results demonstrate that the automatic E4 heart rate measures capture long-term HRV whilst the short-term metrics are affected by missing IBIs. Our approach provides an effective way to resolve the missing IBI issue of E4 and extracts reliable heart rate measures that are concordant with ECG. Clinical Relevance— This work discusses data quality challenges in heart rate data acquired by wearables and provides an efficient and reliable approach for extracting heart rate measures from the E4 wearable device and validates the metrics in older adults

Introduction Disturbances of sleep/wake behaviour are amongst the most disabling symptoms of dementia, leading to increased carers’ burden and institutionalisation. The lack of unobtrusive, low- burden technologies validated to monitor sleep in patients living with dementia (PLWD) has prevented longitudinal studies of nocturnal disturbances and their correlates. Aims To examine the effect of medication changes and clinical status on the intraindividual variation in sleep/wake behaviour in PLWD. Methods Using under-mattress pressure-sensing mat in 46 PLWD, we monitored sleep/wake behavioural metrics for 13,711 nights between 2019-2021. Machine learning and >3.6million nightly summaries from 13,671 individuals from the general population were used to detect abnormalities in PLWD’s nightly sleep/wake metrics and convert them to risk scores. Additionally, GP records were reviewed for each patient to determine whether medication changes and clinical events affected sleep parameters. Results PLWD’s went to bed earlier and rose later than sex- and age-matched controls. They had more nocturnal awakenings with longer out-of-bed durations. Notably, at the individual patient level, increased metric-specific risk scores were temporally related to changes in antipsychotics and antidepressants, and acute illness, including UTI, cardiac events, and depressive episodes. Conclusions Passive monitoring of sleep/wake behaviours is a promising way to identify novel markers of disease progression and evaluate the effectiveness of pharmaceutical interventions in patients with dementia.

Nocturnal disturbance is frequently observed in dementia and is a major contributor to institutionalisation. Unobtrusive technology that can quantify sleep/wake and determine bed occupancy during the major nocturnal sleep episode may be beneficial for long-term clinical monitoring and the carer. Such technologies have, however, not been validated in older people. Here we assessed the performance of the Withings Sleep Mattress (WSM) in a heterogenous older population to ensure external validity.

A recent proof-of-concept pilot study proposed using microRNA (miRNA) markers for time of death determination. The markers – miRNA-142-5p and miRNA-541, were reported to show considerable expression differences in vitreous humor between individuals who died during the day or night. Here, we investigated whether these miRNA markers show the same diurnal expression pattern in blood, which would make them useful for estimating bloodstain deposition time to allow molecular alibi testing for forensic casework. We analyzed venous blood samples collected from 12 healthy individuals every 4 h during the 24 h day/night period under controlled sleep-laboratory conditions. MiRNA-142-5p normalized against miRNA-222 showed no statistically significant expression differences between blood samples collected during daytime and nighttime (one-way ANOVA p = 0.81), and also no statistically significant rhythmicity during the 24 h day/night period (cosine fit for all individuals p > 0.05, averaged data p = 0.932). MicroRNA-541 amplification in blood was above the 34-cycle threshold applied in the study, indicating too low quantities for obtaining reliable data. Overall, we conclude that the two miRNA markers previously suggested for time of death determination in vitreous humor are not suitable for estimating the deposition time of forensic bloodstains. Future studies may find out if miRNA markers with significant diurnal expression patterns can be identified and how useful they would be for forensic trace deposition timing.

Blue light sensitivity of melatonin suppression and subjective mood and alertness responses in humans is recognised as being melanopsin based. Observations that long wavelength (red) light can potentiate responses to subsequent short wavelength (blue) light have been attributed to the bistable nature of melanopsin whereby it forms stable associations with both 11-cis and alltrans isoforms of retinaldehyde and uses light to transition between these states. The current study examined the effect of concurrent administration of blue and red monochromatic light, as would occur in real-world white light, on acute melatonin suppression and subjective mood and alertness responses in humans. Young healthy males (18-35 years; n = 21) were studied in highly controlled laboratory sessions that included an individually timed 30 min light stimulus of blue (λmax 479 nm) or red (λmax 627 nm) monochromatic light at varying intensities (1013 - 1014 photons/cm2/s) presented, either alone or in combination, in a within-subject randomised design. Plasma melatonin levels and subjective mood and alertness were assessed at regular intervals relative to the light stimulus. Subjective alertness levels were elevated after light onset irrespective of light wavelength or irradiance. For melatonin suppression, a significant irradiance response was observed with blue light. Co-administration of red light, at any of the irradiances tested, did not significantly alter the response to blue light alone. Under the current experimental conditions the primary determinant of the melatonin suppression response was the irradiance of blue 479 nm light and this was unaffected by simultaneous red light administration.

Ageing is associated with increased disturbances in the timing, duration, and quality of sleep. These disruptions may reflect changes in the circadian timing system and/or the sleep homeostat which are both necessary to produce consolidated sleep at an appropriate time. In addition, it is possible that age-related alterations in the detection and transmission of the photic signal responsible for synchronizing the circadian clock may play a role. Ageing is accompanied by many changes within the eye including alterations in pupil size, lens transmission, and number of photoreceptors. The observed increase in ocular lens density with age will diminish the transmission of short wavelength blue light to which the circadian system has been shown to be most sensitive, and may contribute, in part, to the observed increase in sleep disturbances in older people. We were the first group to test the hypothesis that non-visual responses to blue light would be impaired in older individuals. Our research has demonstrated that whilst acute non-visual effects of blue light are impaired with age, the light resetting effect appears unaltered. Future research should work towards optimizing the light environment for older people to promote good quality sleep and daytime functioning.

Conflicting evidence exists as to whether there are differences between males and females in circadian timing. The aim of the current study was to assess whether sex differences are present in the circadian regulation of melatonin and cortisol in plasma and urine matrices during a constant routine protocol. Thirty-two healthy individuals (16 females taking the oral contraceptive pill (OCP)), aged 23.8 ± 3.7 (mean ± SD) years, participated. Blood (hourly) and urine (4-hourly) samples were collected for measurement of plasma melatonin and cortisol, and urinary 6-sulfatoxymelatonin (aMT6s) and cortisol, respectively. Data from 28 individuals (14 females) showed no significant differences in the timing of plasma and urinary circadian phase markers between sexes. Females, however, exhibited significantly greater levels of plasma melatonin and cortisol than males (AUC melatonin: 937 ± 104 (mean ± SEM) vs. 642 ± 47 pg/ml.h; AUC cortisol: 13581 ± 1313 vs. 7340 ± 368 mmol/L.h). Females also exhibited a significantly higher amplitude rhythm in both hormones (melatonin: 43.8 ± 5.8 vs. 29.9 ± 2.3 pg/ml; cortisol: 241.7 ± 23.1 vs. 161.8 ± 15.9 mmol/L). Males excreted significantly more urinary cortisol than females during the CR (519.5 ± 63.8 vs. 349.2 ± 39.3 mol) but aMT6s levels did not differ between sexes. It was not possible to distinguish whether the elevated plasma melatonin and cortisol levels observed in females resulted from innate sex differences or the OCP affecting the synthetic and metabolic pathways of these hormones. The fact that the sex differences observed in total plasma concentrations for melatonin and cortisol were not reproduced in the urinary markers challenges their use as a proxy for plasma levels in circadian research, especially in OCP users.

Determining the time a biological trace was left at a scene of crime reflects a crucial aspect of forensic investigations as – if possible – it would permit testing the sample donor’s alibi directly from the trace evidence, helping to link (or not) the DNA-identified sample donor with the crime event. However, reliable and robust methodology is lacking thus far. In this study, we assessed the suitability of mRNA for the purpose of estimating blood deposition time, and its added value relative to melatonin and cortisol, two circadian hormones we previously introduced for this purpose. By analysing 21 candidate mRNA markers in blood samples from 12 individuals collected around the clock at 2 h intervals for 36 h under real-life, controlled conditions, we identified 11 mRNAs with statistically significant expression rhythms. We then used these 11 significantly rhythmic mRNA markers, with and without melatonin and cortisol also analysed in these samples, to establish statistical models for predicting day/night time categories. We found that although in general mRNA-based estimation of time categories was less accurate than hormone-based estimation, the use of three mRNA markers HSPA1B, MKNK2 and PER3 together with melatonin and cortisol generally enhanced the time prediction accuracy relative to the use of the two hormones alone. Our data best support a model that by using these five molecular biomarkers estimates three time categories, i.e. night/early morning, morning/noon, and afternoon/evening with prediction accuracies expressed as AUC values of 0.88, 0.88, and 0.95, respectively. For the first time, we demonstrate the value of mRNA for blood deposition timing and introduce a statistical model for estimating day/night time categories based on molecular biomarkers, which shall be further validated with additional samples in the future. Moreover, our work provides new leads for molecular approaches on time of death estimation using the significantly rhythmic mRNA markers established here.

Understanding how metabolite levels change over the 24 hour day is of crucial importance for clinical and epidemiological studies. Additionally, the association between sleep deprivation and metabolic disorders such as diabetes and obesity requires investigation into the links between sleep and metabolism. Here, we characterise time-of-day variation and the effects of sleep deprivation on urinary metabolite profiles. Healthy male participants (n = 15) completed an in-laboratory study comprising one 24 h sleep/wake cycle prior to 24 h of continual wakefulness under highly controlled environmental conditions. Urine samples were collected over set 2-8 h intervals and analysed by (1)H NMR spectroscopy. Significant changes were observed with respect to both time of day and sleep deprivation. Of 32 identified metabolites, 7 (22%) exhibited cosine rhythmicity over at least one 24 h period; 5 exhibiting a cosine rhythm on both days. Eight metabolites significantly increased during sleep deprivation compared with sleep (taurine, formate, citrate, 3-indoxyl sulfate, carnitine, 3-hydroxyisobutyrate, TMAO and acetate) and 8 significantly decreased (dimethylamine, 4-DTA, creatinine, ascorbate, 2-hydroxyisobutyrate, allantoin, 4-DEA, 4-hydroxyphenylacetate). These data indicate that sampling time, the presence or absence of sleep and the response to sleep deprivation are highly relevant when identifying biomarkers in urinary metabolic profiling studies.

The increased prevalence of circadian disruptions due to abnormal coupling between internal and external time makes the detection of circadian phase in humans by ambulatory recordings a compelling need. Here, we propose an accurate practical procedure to estimate circadian phase with the least possible burden for the subject, that is, without the restraints of a constant routine protocol or laboratory techniques such as melatonin quantification, both of which are standard procedures. In this validation study, subjects (N = 13) wore ambulatory monitoring devices, kept daily sleep diaries and went about their daily routine for 10 days. The devices measured skin temperature at wrist level (WT), motor activity and body position on the arm, and light exposure by means of a sensor placed on the chest. Dim light melatonin onset (DLMO) was used to compare and evaluate the accuracy of the ambulatory variables in assessing circadian phase. An evening increase in WT: WTOnset (WTOn) and "WT increase onset" (WTiO) was found to anticipate the evening increase in melatonin, while decreases in motor activity (Activity Offset or AcOff), body position (Position Offset (POff)), integrative TAP (a combination of WT, activity and body position) (TAPOffset or TAPOff) and an increase in declared sleep propensity were phase delayed with respect to DLMO. The phase markers obtained from subjective sleep (R = 0.811), WT (R = 0.756) and the composite variable TAP (R = 0.720) were highly and significantly correlated with DLMO. The findings strongly support a new method to calculate circadian phase based on WT (WTiO) that accurately predicts and shows a temporal association with DLMO. WTiO is especially recommended due to its simplicity and applicability to clinical use under conditions where knowing endogenous circadian phase is important, such as in cancer chronotherapy and light therapy.

Trace deposition timing reflects a novel concept in forensic molecular biology involving the use of rhythmic biomarkers for estimating the time within a 24-h day/night cycle a human biological sample was left at the crime scene, which in principle allows verifying a sample donor’s alibi. Previously, we introduced two circadian hormones for trace deposition timing and recently demonstrated that messenger RNA (mRNA) biomarkers significantly improve time prediction accuracy. Here, we investigate the suitability of metabolites measured using a targeted metabolomics approach, for trace deposition timing. Analysis of 171 plasma metabolites collected around the clock at 2-h intervals for 36 h from 12 male participants under controlled laboratory conditions identified 56 metabolites showing statistically significant oscillations, with peak times falling into three day/night time categories: morning/noon, afternoon/evening and night/early morning. Time prediction modelling identified 10 independently contributing metabolite biomarkers, which together achieved prediction accuracies expressed as AUC of 0.81, 0.86 and 0.90 for these three time categories respectively. Combining metabolites with previously established hormone and mRNA biomarkers in time prediction modelling resulted in an improved prediction accuracy reaching AUCs of 0.85, 0.89 and 0.96 respectively. The additional impact of metabolite biomarkers, however, was rather minor as the previously established model with melatonin, cortisol and three mRNA biomarkers achieved AUC values of 0.88, 0.88 and 0.95 for the same three time categories respectively. Nevertheless, the selected metabolites could become practically useful in scenarios where RNA marker information is unavailable such as due to RNA degradation. This is the first metabolomics study investigating circulating metabolites for trace deposition timing, and more work is needed to fully establish their usefulness for this forensic purpose.

The identification and investigation of novel clock-controlled genes (CCGs) has been conducted thus far mainly in model organisms such as nocturnal rodents, with limited information in humans. Here, we aimed to characterize daily and circadian expression rhythms of CCGs in human peripheral blood during a sleep/sleep deprivation (S/SD) study and a constant routine (CR) study. Blood expression levels of 9 candidate CCGs (SREBF1, TRIB1, USF1, THRA1, SIRT1, STAT3, CAPRIN1, MKNK2, and ROCK2), were measured across 48 h in 12 participants in the S/SD study and across 33 h in 12 participants in the CR study. Statistically significant rhythms in expression were observed for STAT3, SREBF1, TRIB1, and THRA1 in samples from both the S/SD and the CR studies, indicating that their rhythmicity is driven by the endogenous clock. The MKNK2 gene was significantly rhythmic in the S/SD but not the CR study, which implies its exogenously driven rhythmic expression. In addition, we confirmed the circadian expression of PER1, PER3, and REV-ERBα in the CR study samples, while BMAL1 and HSPA1B were not significantly rhythmic in the CR samples; all 5 genes previously showed significant expression in the S/SD study samples. Overall, our results demonstrate that rhythmic expression patterns of clock and selected clock-controlled genes in human blood cells are in part determined by exogenous factors (sleep and fasting state) and in part by the endogenous circadian timing system. Knowledge of the exogenous and endogenous regulation of gene expression rhythms is needed prior to the selection of potential candidate marker genes for future applications in medical and forensic settings.

MAPK pathway activation is frequently observed in human malignancies, including melanoma, and is associated with sensitivity to MEK inhibition and changes in cellular metabolism. Using quantitative mass spectrometry-based metabolomics, we identified in preclinical models 21 plasma metabolites including amino acids, propionylcarnitine, phosphatidylcholines and sphingomyelins that were significantly altered in two B-RAF mutant melanoma xenografts and that were reversed following a single dose of the potent and selective MEK inhibitor RO4987655. Treatment of non-tumour bearing animals and mice bearing the PTEN null U87MG human glioblastoma xenograft elicited plasma changes only in amino acids and propionylcarnitine. In patients with advanced melanoma treated with RO4987655, on-treatment changes of amino acids were observed in patients with disease progression and not in responders. In contrast, changes in phosphatidylcholines and sphingomyelins were observed in responders. Furthermore, pre-treatment levels of 7 lipids identified in the preclinical screen were statistically significantly able to predict objective responses to RO4987655. The RO4987655 treatment-related changes were greater than baseline physiological variability in non-treated individuals. This study provides evidence of a translational exo-metabolomic plasma readout predictive of clinical efficacy together with pharmacodynamic utility following treatment with a signal transduction inhibitor.

OBJECTIVE: In an effort to enhance the efficiency, brightness, and contrast of light-emitting (LE) devices during the day, displays often generate substantial short-wavelength (blue-enriched) light emissions that can adversely affect sleep. We set out to verify the extent of such short-wavelength emissions, produced by a tablet (iPad Air), e-reader (Kindle Paperwhite 1st generation), and smartphone (iPhone 5s) and to determine the impact of strategies designed to reduce these light emissions. SETTING: University of Surrey dedicated chronobiology facility. METHODS: First, the spectral power of all the LE devices was assessed when displaying identical text. Second, we compared the text output with that of "Angry Birds" - a popular top 100 "App Store" game. Finally, we measured the impact of two strategies that attempt to reduce the output of short-wavelength light emissions. The first strategy employed an inexpensive commercially available pair of orange-tinted "blue-blocking" glasses. The second strategy tested an app designed to be "sleep-aware" whose designers deliberately attempted to reduce short-wavelength light emissions. RESULTS: All the LE devices shared very similar enhanced short-wavelength peaks when displaying text. This included the output from the backlit Kindle Paperwhite device. The spectra when comparing text to the Angry Birds game were also very similar, although the text emissions were higher intensity. Both the orange-tinted glasses and the "sleep-aware" app significantly reduced short-wavelength emissions. CONCLUSION: The LE devices tested were all bright and characterized by short-wavelength enriched emissions. Since this type of light is likely to cause the most disruption to sleep as it most effectively suppresses melatonin and increases alertness, there needs to be the recognition that at night-time "brighter and bluer" is not synonymous with "better." Ideally future software design could be better optimized when night-time use is anticipated, and hardware should allow an automatic "bedtime mode" that shifts blue and green light emissions to yellow and red as well as reduce backlight/light intensity.

Diurnal behavior in humans is governed by the period length of a circadian clock in the suprachiasmatic nuclei of the brain hypothalamus. Nevertheless, the cell-intrinsic mechanism of this clock is present in most cells of the body. We have shown previously that for individuals of extreme chronotype ("larks" and "owls"), clock properties measured in human fibroblasts correlated with extreme diurnal behavior.

Intrinsically photosensitive retinal ganglion cells (ipRGCs), whose photopigment melanopsin has a peak of sensitivity in the short wavelength range of the spectrum, constitute a common light input pathway to the olivary pretectal nucleus (OPN), the pupillary light reflex (PLR) regulatory centre, and to the suprachiasmatic nuclei (SCN), the major pacemaker of the circadian system. Thus, evaluating PLR under short wavelength light (λmax 500 nm) and creating an integrated PLR parameter, as a possible tool to indirectly assess the status of the circadian system, becomes of interest. Nine monochromatic, photon-matched light stimuli (300 s), in 10 nm increments from λmax 420 to 500 nm were administered to 15 healthy young participants (8 females), analyzing: i) the PLR; ii) wrist temperature (WT) and motor activity rhythms (WA), iii) light exposure (L) pattern and iv) diurnal preference (Horne- Östberg), sleep quality (Pittsburgh) and daytime sleepiness (Epworth). Linear correlations between the different PLR parameters and circadian status index obtained from WT, WA and L recordings and scores from questionnaires were calculated. In summary, we found markers of robust circadian rhythms, namely high stability, reduced fragmentation, high amplitude, phase advance and low internal desynchronization, were correlated with a reduced PLR to 460–490 nm wavelengths. Integrated circadian (CSI) and PLR (cp-PLR) parameters are proposed, that also showed an inverse correlation. These results demonstrate, for the first time, the existence of a close relationship between the circadian system robustness and the pupillary reflex response, two non-visual functions primarily under melanopsin-ipRGC input.

Electroencephalography (EEG) recordings represent a vital component of the assessment of sleep physiology, but the methodology presently used is costly, intrusive to participants, and laborious in application. There is a recognized need to develop more easily applicable yet reliable EEG systems that allow unobtrusive long-term recording of sleep-wake EEG ideally away from the laboratory setting. cEEGrid is a recently developed flex-printed around-the-ear electrode array, which holds great potential for sleep-wake monitoring research. It is comfortable to wear, simple to apply, and minimally intrusive during sleep. Moreover, it can be combined with a smartphone-controlled miniaturized amplifier and is fully portable. Evaluation of cEEGrid as a motion-tolerant device is ongoing, but initial findings clearly indicate that it is very well suited for cognitive research. The present study aimed to explore the suitability of cEEGrid for sleep research, by testing whether cEEGrid data affords the signal quality and characteristics necessary for sleep stage scoring. In an accredited sleep laboratory, sleep data from cEEGrid and a standard PSG system were acquired simultaneously. Twenty participants were recorded for one extended nocturnal sleep opportunity. Fifteen data sets were scored manually. Sleep parameters relating to sleep maintenance and sleep architecture were then extracted and statistically assessed for signal quality and concordance. The findings suggest that the cEEGrid system is a viable and robust recording tool to capture sleep and wake EEG. Further research is needed to fully determine the suitability of cEEGrid for basic and applied research as well as sleep medicine.

Although daily rhythms regulate multiple aspects of human physiology, rhythmic control of the metabolome remains poorly understood. The primary objective of this proof-of-concept study was identification of metabolites in human plasma that exhibit significant 24-h variation. This was assessed via an untargeted metabolomic approach using liquid chromatography-mass spectrometry (LC-MS). Eight lean, healthy, and unmedicated men, mean age 53.6 (SD ± 6.0) yrs, maintained a fixed sleep/wake schedule and dietary regime for 1 wk at home prior to an adaptation night and followed by a 25-h experimental session in the laboratory where the light/dark cycle, sleep/wake, posture, and calorific intake were strictly controlled. Plasma samples from each individual at selected time points were prepared using liquid-phase extraction followed by reverse-phase LC coupled to quadrupole time-of-flight MS analysis in positive ionization mode. Time-of-day variation in the metabolites was screened for using orthogonal partial least square discrimination between selected time points of 10:00 vs. 22:00 h, 16:00 vs. 04:00 h, and 07:00 (d 1) vs. 16:00 h, as well as repeated-measures analysis of variance with time as an independent variable. Subsequently, cosinor analysis was performed on all the sampled time points across the 24-h day to assess for significant daily variation. In this study, analytical variability, assessed using known internal standards, was low with coefficients of variation

The pupillary light reflex (PLR) is a neurological reflex driven by rods, cones, and melanopsin-containing retinal ganglion cells. Our aim was to achieve a more precise picture of the effects of 5-min duration monochromatic light stimuli, alone or in combination, on the human PLR, to determine its spectral sensitivity and to assess the importance of photon flux. Using pupillometry, the PLR was assessed in 13 participants (6 women) aged 27.2 ± 5.41 years (mean ± SD) during 5-min light stimuli of purple (437 nm), blue (479 nm), red (627 nm), and combinations of red+purple or red+blue light. In addition, nine 5-min, photon-matched light stimuli, ranging in 10 nm increments peaking between 420 and 500 nm were tested in 15 participants (8 women) aged 25.7 ± 8.90 years. Maximum pupil constriction, time to achieve this, constriction velocity, area under the curve (AUC) at short (0–60 s), and longer duration (240–300 s) light exposures, and 6-s post-illumination pupillary response (6-s PIPR) were assessed. Photoreceptor activation was estimated by mathematical modeling. The velocity of constriction was significantly faster with blue monochromatic light than with red or purple light. Within the blue light spectrum (between 420 and 500 nm), the velocity of constriction was significantly faster with the 480 nm light stimulus, while the slowest pupil constriction was observed with 430 nm light. Maximum pupil constriction was achieved with 470 nm light, and the greatest AUC0−60 and AUC240−300 was observed with 490 and 460 nm light, respectively. The 6-s PIPR was maximum after 490 nm light stimulus. Both the transient (AUC0−60) and sustained (AUC240−300) response was significantly correlated with melanopic activation. Higher photon fluxes for both purple and blue light produced greater amplitude sustained pupillary constriction. The findings confirm human PLR dependence on wavelength, monochromatic or bichromatic light and photon flux under 5-min duration light stimuli. Since the most rapid and high amplitude PLR occurred within the 460–490 nm light range (alone or combined), our results suggest that color discrimination should be studied under total or partial substitution of this blue light range (460–490 nm) by shorter wavelengths (~440 nm). Thus for nocturnal lighting, replacement of blue light with purple light might be a plausible solution to preserve color discrimination while minimizing melanopic activation.

Disruption to sleep and circadian rhythms can impact on metabolism. The study aimed to investigate the effect of acute sleep deprivation on plasma melatonin, cortisol and metabolites, to increase understanding of the metabolic pathways involved in sleep/wake regulation processes. Twelve healthy young female subjects remained in controlled laboratory conditions for ~92 h with respect to posture, meals and environment light (18:00‐23:00 h and 07:00‐09:00 h

Common cold sufferers frequently report sleep disruption during the symptomatic period of infections. We examined the effects of treatment with a topical aromatic pharmaceutical ointment (Vicks VapoRub®), on associated sleep disturbances. The effects of Vicks VapoRub® versus placebo (petrolatum ointment) on subjective and objective measured sleep parameters were assessed in an exploratory study of 100 common cold patients, in a randomized, single blind, controlled, two-arm, parallel design study. The primary efficacy variable was subjective sleep quality measured with the SQSQ (Subjective Quality of Sleep Questionnaire). Additional measures included, ease of falling asleep and depth of sleep (measured with a post-sleep Visual Analog Scale), total sleep time, sleep onset latency, activity score, percentage of sleep, sleep efficiency (measured with actigraphy and SQSQ) and sleep quality index measured with a modified Karolinska Sleep Diary (KSD). The primary endpoint, “How was the quality of your sleep last night?” showed a statistically significant difference in change from baseline in favour of VapoRub treatment (p = 0.0392) versus placebo. Positive effects of VapoRub versus placebo were also observed for “How refreshed did you feel upon waking up?” (p = 0.0122) (SQSQ), “Did you get enough sleep?” (p = 0.0036) (KSD), “How was it to get up?” (p = 0.0120) (KSD) and “Do you feel well-rested?” (p = 0.0125) (KSD). No statistically significant changes from baseline versus placebo were detected in the Actiwatch endpoints. Vicks VapoRub®when applied before retiring to bed can reduce subjective sleep disturbances during a common cold. The results of this exploratory study support the belief among patients that the use of VapoRub improves subjective sleep quality during common cold which was associated with more refreshing sleep.

This study investigated the impact of sleep deprivation on the human circadian system. Plasma melatonin and cortisol levels and leukocyte expression levels of 12 genes were examined over 48 h (sleep vs. no-sleep nights) in 12 young males (mean ± SD: 23 ± 5 yrs). During one night of total sleep deprivation, BMAL1 expression was suppressed, the heat shock gene HSPA1B expression was induced, and the amplitude of the melatonin rhythm increased, whereas other high-amplitude clock gene rhythms (e.g., PER1-3, REV-ERBα) remained unaffected. These data suggest that the core clock mechanism in peripheral oscillators is compromised during acute sleep deprivation.

Quantification of sleep is important for the diagnosis of sleep disorders and sleep research. However, the only widely accepted method to obtain sleep staging is by visual analysis of polysomnography (PSG), which is expensive and time consuming. Here, we investigate automated sleep scoring based on a low‐cost, mobile electroencephalogram (EEG) platform consisting of a lightweight EEG amplifier combined with flex‐printed cEEGrid electrodes placed around the ear, which can be implemented as a fully self‐applicable sleep system. However, cEEGrid signals have different amplitude characteristics to normal scalp PSG signals, which might be challenging for visual scoring. Therefore, this study evaluates the potential of automatic scoring of cEEGrid signals using a machine learning classifier (“random forests”) and compares its performance with manual scoring of standard PSG. In addition, the automatic scoring of cEEGrid signals is compared with manual annotation of the cEEGrid recording and with simultaneous actigraphy. Acceptable recordings were obtained in 15 healthy volunteers (aged 35 ± 14.3 years) during an extended nocturnal sleep opportunity, which induced disrupted sleep with a large inter‐individual variation in sleep parameters. The results demonstrate that machine‐learning‐based scoring of around‐the‐ear EEG outperforms actigraphy with respect to sleep onset and total sleep time assessments. The automated scoring outperforms human scoring of cEEGrid by standard criteria. The accuracy of machine‐learning‐based automated scoring of cEEGrid sleep recordings compared with manual scoring of standard PSG was satisfactory. The findings show that cEEGrid recordings combined with machine‐learning‐based scoring holds promise for large‐scale sleep studies.

The sleep/wake cycle is accompanied by changes in circulating numbers of immune cells. The goal of this study was to provide an in-depth characterization of diurnal rhythms in different blood cell populations and to investigate the effect of acute sleep deprivation on the immune system, as an indicator of the body's acute stress response.