Identification of a biomarker for sleep drive in flies and humans

Salivary α-amylase as a marker of sleep disorders: A theoretical review

Sleep disorders are commonplace in our modern societies. Specialized hospital departments are generally overloaded, and sleep assessment is an expensive process in terms of equipment, human resources, and time. Biomarkers would usefully complement current measures in the screening and follow-up of sleep disorders and their daytime repercussions. Among salivary markers, a growing body of literature suggests that salivary α-amylase (sAA) may be a cross-species marker of sleep debt. However, there is no consensus as to the direction of variation in sAA with sleep disorders. Herein, after describing the mechanisms of sAA secretion and its relationship with stress, studies assessing the relationship between sAA and sleep parameters are reviewed. Finally, the influence of confounding factors is discussed, along with methodological considerations, to better understand the fluctuations in sAA and facilitate future studies in the field.

Accurate detection of acute sleep deprivation using a metabolomic biomarker-A machine learning approach

Sleep deprivation enhances risk for serious injury and fatality on the roads and in workplaces. To facilitate future management of these risks through advanced detection, we developed and validated a metabolomic biomarker of sleep deprivation in healthy, young participants, across three experiments. Bi-hourly plasma samples from 2 × 40-hour extended wake protocols (for train/test models) and 1 × 40-hour protocol with an 8-hour overnight sleep interval were analyzed by untargeted liquid chromatography-mass spectrometry. Using a knowledge-based machine learning approach, five consistently important variables were used to build predictive models. Sleep deprivation (24 to 38 hours awake) was predicted accurately in classification models [versus well-rested (0 to 16 hours)] (accuracy = 94.7%/AUC 99.2%, 79.3%/AUC 89.1%) and to a lesser extent in regression (R2 = 86.1 and 47.8%) models for within- and between-participant models, respectively. Metabolites were identified for replicability/future deployment. This approach for detecting acute sleep deprivation offers potential to reduce accidents through "fitness for duty" or "post-accident analysis" assessments.

Biomarkers linking habitual short sleep duration with risk of cardiometabolic disease: current progress and future directions

Approximately one in three adults in the United States sleeps less than the recommended 7 h per night. Decades of epidemiological data and data from experimental sleep restriction studies demonstrate short sleep duration is associated with adverse cardiometabolic risk, including risk of type 2 diabetes and cardiovascular disease. However, the precise mechanisms underlying this risk are not fully elucidated and there is a lack of sleep-based interventions designed to mitigate such risk. One strategy to overcome these limitations is to develop biomarkers that link habitual short sleep duration with adverse cardiometabolic risk. Such biomarkers could inform biochemical mechanisms, identify new targets for interventions, support precision medicine by identifying individuals most likely to benefit from sleep-based interventions, and ultimately lead to improved cardiometabolic health in people with habitual short sleep durations. Early progress demonstrates proof-of-principle that omics-based technologies are a viable approach to create biochemical signatures (biomarkers) of short sleep duration, primarily derived from acute studies of experimental sleep restriction. Yet, much work remains. Notably, studies that translate early findings from experimental sleep restriction to free-living adults with habitual short sleep duration have high potential to advance the field. Such studies also create an exciting opportunity for larger randomized controlled trials that simultaneously identify biomarkers of habitual short sleep duration and evaluate the efficacy of sleep-based interventions. Ultimately, early progress in developing molecular biomarkers of short sleep duration combined with the prior decades of progress in the sleep and metabolism fields provide the foundation for exciting progress in the biomarker development space.

Association between sleep duration and dental caries in a nationally representative U.S. population

BACKGROUND

Dental caries is considered one of the most prevalent chronic diseases worldwide despite all dental public health efforts. Short sleep duration has been established as a risk factor for several medical conditions. In this study, we aimed to examine the relationship between sleep duration and dental caries.

METHODS

Data were collected from the 2017-2018 cycle of the National Health and Nutrition Examination Survey, a nationally representative health survey conducted in the United States. Participants who completed sleep questionnaires were examined by dentists using standardized clinical criteria. Analysis was limited to Individuals aged ≥ 16 years with complete clinical oral examination data and who completed the sleep questionnaire (N = 5,205). The data were weighted to provide a national estimate, and multiple potential covariates were included in the analysis to account for the complex sample design. The main outcomes of the study were untreated dental caries and dental caries experience. The main predictor variables were average sleep hours/night and a binary variable with 7 h/night as a cut off. Multiple weighted Poisson and logistic regression analyses were conducted to test the hypothesis that people with short sleep duration are more likely to exhibit dental caries.

RESULTS

This study showed a statistically significant negative relationship between sleep duration and dental caries amongst all weighted adjusted analyses conducted. For a one hour increase in average sleep hours, the Adjusted Odds Ratio (AOR) of having a dental caries experience might decrease by 0.86 (AOR = 0.86, 95% CI = 0.75-0.98, P < 0.05). Individuals who reported an average sleep of ≥ 7 h were less likely to have a dental caries experience compared to individuals who reported an average sleep of < 7 h (AOR = 0.52, 95% CI = 0.33-0.82, P < 0.05). For a one hour increase in average sleep hours, the Adjusted Mean Ratio (AMR) of having a dental caries experience might decrease by 0.97 (AMR = 0.97, 95% CI = 0.96-0.99, P < 0.05), and was lower for those who reported sleeping ≥ 7 h/night than individuals who reported sleeping < 7 h/night (AMR = 0.92, 95% CI = 0.87-0.99, P < 0.05).

CONCLUSION

Findings of this cross-sectional representative study of the U.S. population revealed a statistically significant negative association between sleep duration and dental caries. In this study, individuals who slept < 7 h/night were more likely to exhibit dental caries.

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.

Interest of the BLAST paradigm and salivary markers for the evaluation of sleepiness in drivers

Objectives

Sleepiness is associated with decreased cognitive abilities and remains one of the main causes of fatal road accidents. The tools currently available to assess sleepiness, such as questionnaires, are subject to intra- and inter-individual variability, while multiple sleep latency tests are only feasible in few sleep laboratories. The main objective of this study was to explore new potential markers (neurocognitive, biological) to objectively assess sleepiness in drivers.

Methods

A total of 186 drivers (median age 44 years, range 20-74 years, 73% men, 14% obese) were included during a break at a highway service area, in the morning, while on the road for vacation. Questionnaires on sleepiness and sleep characteristics (habitual and on the night before travel), the Bron-Lyon Attention Stability Test (BLAST), and two salivary samples (α-amylase and oxalate) were collected. Associations between measures of sleepiness [Epworth Sleepiness Scale (ESS), and Stanford Sleepiness Scale (SSS)], sleep characteristics, neurocognitive, and biological markers were tested using regression models adjusted for confounding factors.

Results

The night before travel, 83% of the drivers reduced their sleep time and 30% slept 5 h or less. The higher the number of miles to be traveled, the higher the decrease, and the shorter the sleep time. The night before travel, 18 and 24% of the drivers complained of poor sleep quality and difficulty falling asleep. The sleep characteristics on the night before travel were associated with the habitual sleep characteristics. At the time of the test, 47% of the drivers scored pathologically on the SSS. Poor sleep quality and difficulty falling asleep the night before travel were associated with increased sleepiness as assessed by the SSS and decreased attentional ability as assessed by the BLAST. No association between salivary markers and acute sleepiness was observed.

Conclusions

The sleep characteristics of the night before travel were associated with sleepiness and attentional performance. The SSS and the BLAST could be used by individual drivers in a self-evaluation context. Biological markers showed a high variability and limited association with sleep parameters across subjects, emphasizing the need for within-subject designs to assess their usefulness.

Depriving Mice of Sleep also Deprives of Food

Both sleep-wake behavior and circadian rhythms are tightly coupled to energy metabolism and food intake. Altered feeding times in mice are known to entrain clock gene rhythms in the brain and liver, and sleep-deprived humans tend to eat more and gain weight. Previous observations in mice showing that sleep deprivation (SD) changes clock gene expression might thus relate to altered food intake, and not to the loss of sleep per se. Whether SD affects food intake in the mouse and how this might affect clock gene expression is, however, unknown. We therefore quantified (i) the cortical expression of the clock genes Per1, Per2, Dbp, and Cry1 in mice that had access to food or not during a 6 h SD, and (ii) food intake during baseline, SD, and recovery sleep. We found that food deprivation did not modify the SD-incurred clock gene changes in the cortex. Moreover, we discovered that although food intake during SD did not differ from the baseline, mice lost weight and increased food intake during subsequent recovery. We conclude that SD is associated with food deprivation and that the resulting energy deficit might contribute to the effects of SD that are commonly interpreted as a response to sleep loss.

Differential Gene Expression in Brain and Liver Tissue of Wistar Rats after Rapid Eye Movement Sleep Deprivation

Sleep is essential for the survival of most living beings. Numerous researchers have identified a series of genes that are thought to regulate "sleep-state" or the "deprived state". As sleep has a significant effect on physiology, we believe that lack of total sleep, or particularly rapid eye movement (REM) sleep, for a prolonged period would have a profound impact on various body tissues. Therefore, using the microarray method, we sought to determine which genes and processes are affected in the brain and liver of rats following nine days of REM sleep deprivation. Our findings showed that REM sleep deprivation affected a total of 652 genes in the brain and 426 genes in the liver. Only 23 genes were affected commonly, 10 oppositely, and 13 similarly across brain and liver tissue. Our results suggest that nine-day REM sleep deprivation differentially affects genes and processes in the brain and liver of rats.

Developing preliminary blood metabolomics-based biomarkers of insufficient sleep in humans

STUDY OBJECTIVE

Identify small molecule biomarkers of insufficient sleep using untargeted plasma metabolomics in humans undergoing experimental insufficient sleep.

METHODS

We conducted a crossover laboratory study where 16 normal-weight participants (eight men; age 22 ± 5 years; body mass index < 25 kg/m2) completed three baseline days (9 hours sleep opportunity per night) followed by 5-day insufficient (5 hours sleep opportunity per night) and adequate (9 hours sleep opportunity per night) sleep conditions. Energy balanced diets were provided during baseline, with ad libitum energy intake provided during the insufficient and adequate sleep conditions. Untargeted plasma metabolomics analyses were performed using blood samples collected every 4 hours across the final 24 hours of each condition. Biomarker models were developed using logistic regression and linear support vector machine (SVM) algorithms.

RESULTS

The top-performing biomarker model was developed by linear SVM modeling, consisted of 65 compounds, and discriminated insufficient versus adequate sleep with 74% overall accuracy and a Matthew's Correlation Coefficient of 0.39. The compounds in the top-performing biomarker model were associated with ATP Binding Cassette Transporters in Lipid Homeostasis, Phospholipid Metabolic Process, Plasma Lipoprotein Remodeling, and sphingolipid metabolism.

CONCLUSION

We identified potential metabolomics-based biomarkers of insufficient sleep in humans. Although our current biomarkers require further development and validation using independent cohorts, they have potential to advance our understanding of the negative consequences of insufficient sleep, improve diagnosis of poor sleep health, and could eventually help identify targets for countermeasures designed to mitigate the negative health consequences of insufficient sleep.

Identifying and validating blood mRNA biomarkers for acute and chronic insufficient sleep in humans: a machine learning approach

Acute and chronic insufficient sleep are associated with adverse health outcomes and risk of accidents. There is therefore a need for biomarkers to monitor sleep debt status. None are currently available. We applied elastic net and ridge regression to transcriptome samples collected in 36 healthy young adults during acute total sleep deprivation and following 1 week of either chronic insufficient (<6 hr) or sufficient sleep (~8.6 hr) to identify panels of mRNA biomarkers of sleep debt status. The size of identified panels ranged from 9 to 74 biomarkers. Panel performance, assessed by leave-one-subject-out cross-validation and independent validation, varied between sleep debt conditions. Using between-subject assessments based on one blood sample, the accuracy of classifying "acute sleep loss" was 92%, but only 57% for classifying "chronic sleep insufficiency." A reasonable accuracy for classifying "chronic sleep insufficiency" could only be achieved by a within-subject comparison of blood samples. Biomarkers for sleep debt status showed little overlap with previously identified biomarkers for circadian phase. Biomarkers for acute and chronic sleep loss also showed little overlap but were associated with common functions related to the cellular stress response, such as heat shock protein activity, the unfolded protein response, protein ubiquitination and endoplasmic reticulum-associated protein degradation, and apoptosis. This characteristic response of whole blood to sleep loss can further aid our understanding of how sleep insufficiencies negatively affect health. Further development of these novel biomarkers for research and clinical practice requires validation in other protocols and age groups.

Effects of strategic early-morning caffeine gum administration on association between salivary alpha-amylase and neurobehavioural performance during 50 h of sleep deprivation

Self-assessment is the most common method for monitoring performance and safety in the workplace. However, discrepancies between subjective and objective measures have increased interest in physiological assessment of performance. In a double-blind placebo-controlled study, 23 healthy adults were randomly assigned to either a placebo (n = 11; 5 F, 6 M) or caffeine condition (n = 12; 4 F, 8 M) while undergoing 50 h (i.e. two days) of total sleep deprivation. In previous work, higher salivary alpha-amylase (sAA) levels were associated with improved psychomotor vigilance and simulated driving performance in the placebo condition. In this follow-up article, the effects of strategic caffeine administration on the previously reported diurnal profiles of sAA and performance, and the association between sAA and neurobehavioural performance were investigated. Participants were given a 10 h baseline sleep opportunity (monitored via standard polysomnography techniques) prior to undergoing sleep deprivation (total sleep time: placebo = 8.83 ± 0.48 h; caffeine = 9.01 ± 0.48 h). During sleep deprivation, caffeine gum (200 mg) was administered at 01:00 h, 03:00 h, 05:00 h, and 07:00 h to participants in the caffeine condition (n = 12). This strategic administration of caffeine gum (200 mg) has been shown to be effective at maintaining cognitive performance during extended wakefulness. Saliva samples were collected, and psychomotor vigilance and simulated driving performance assessed at three-hour intervals throughout wakefulness. Caffeine effects on diurnal variability were compared with previously reported findings in the placebo condition (n = 11). The impact of caffeine on the circadian profile of sAA coincided with changes in neurobehavioural performance. Higher sAA levels were associated with improved performance on the psychomotor vigilance test during the first 24 h of wakefulness in the caffeine condition. However, only the association between sAA and response speed (i.e. reciprocal-transform of mean reaction time) was consistent across both days of sleep deprivation. The association between sAA and driving performance was not consistent across both days of sleep deprivation. Results show that the relationship between sAA and reciprocal-transform of mean reaction time on the psychomotor vigilance test persisted in the presence of caffeine, however the association was relatively weaker as compared with the placebo condition.

AMPK signaling linked to the schizophrenia-associated 1q21.1 deletion is required for neuronal and sleep maintenance

The human 1q21.1 deletion of ten genes is associated with increased risk of schizophrenia. This deletion involves the β-subunit of the AMP-activated protein kinase (AMPK) complex, a key energy sensor in the cell. Although neurons have a high demand for energy and low capacity to store nutrients, the role of AMPK in neuronal physiology is poorly defined. Here we show that AMPK is important in the nervous system for maintaining neuronal integrity and for stress survival and longevity in Drosophila. To understand the impact of this signaling system on behavior and its potential contribution to the 1q21.1 deletion syndrome, we focused on sleep, an important role of which is proposed to be the reestablishment of neuronal energy levels that are diminished during energy-demanding wakefulness. Sleep disturbances are one of the most common problems affecting individuals with psychiatric disorders. We show that AMPK is required for maintenance of proper sleep architecture and for sleep recovery following sleep deprivation. Neuronal AMPKβ loss specifically leads to sleep fragmentation and causes dysregulation of genes believed to play a role in sleep homeostasis. Our data also suggest that AMPKβ loss may contribute to the increased risk of developing mental disorders and sleep disturbances associated with the human 1q21.1 deletion.

The human 1q21.1 chromosomal deletion is associated with increased risk of schizophrenia. Because this deletion affects only a small number of genes, it provides a unique opportunity to identify the specific disease-causing gene(s) using animal models. Here, we report the use of a Drosophila model to identify the potential contribution of one gene affected by the 1q21.1 deletion–PRKAB2 –to the pathology of the 1q21.1 deletion syndrome. PRKAB2 encodes a subunit of the AMP-activated protein kinase (AMPK) complex, the main cellular energy sensor. We show that AMPK deficiency reduces lifespan and causes structural abnormalities in neuronal dendritic structures, a phenotype which has been linked to schizophrenia. Furthermore, cognitive impairment and altered sleep patterning are some of the most common symptoms of schizophrenia. Therefore, to understand the potential contribution of PRKAB2 to the 1q21.1 syndrome, we tested whether AMPK alterations might cause defects in learning and sleep. Our studies show that lack of PRKAB2 and AMPK-complex activity in the nervous system leads to reduced learning and to dramatic sleep disturbances. Thus, our data links a single 1q21.1-related gene with phenotypes that resemble common symptoms of neuropsychiatric disorders, suggesting that this gene, PRKAB2, may contribute to the risk of developing schizophrenia.

A Systematic Review on Non-mammalian Models in Epilepsy Research

Epilepsy is a common neurological disorder characterized by seizures which result in distinctive neurobiological and behavioral impairments. Not much is known about the causes of epilepsy, making it difficult to devise an effective cure for epilepsy. Moreover, clinical studies involving epileptogenesis and ictogenesis cannot be conducted in humans due to ethical reasons. As a result, animal models play a crucial role in the replication of epileptic seizures. In recent years, non-mammalian models have been given a primary focus in epilepsy research due to their advantages. This systematic review aims to summarize the importance of non-mammalian models in epilepsy research, such as in the screening of anti-convulsive compounds. The reason for this review is to integrate currently available information on the use and importance of non-mammalian models in epilepsy testing to aid in the planning of future studies as well as to provide an overview of the current state of this field. A PRISMA model was utilized and PubMed, Springer, ScienceDirect and SCOPUS were searched for articles published between January 2007 and November 2017. Fifty-one articles were finalized based on the inclusion/exclusion criteria and were discussed in this review. The results of this review demonstrated the current use of non-mammalian models in epilepsy research and reaffirmed their potential to supplement the typical rodent models of epilepsy in future research into both epileptogenesis and the treatment of epilepsy. This review also revealed a preference for zebrafish and fruit flies in lieu of other non-mammalian models, which is a shortcoming that should be corrected in future studies due to the great potential of these underutilized animal models.

Compliance with Saliva Collection Protocol in Healthy Volunteers: Strategies for Managing Risk and Errors

Salivary bioscience technologies such as electrophoresis are widely applied for diagnosing systemic health status. Diagnosis using a saliva sample has emerged as a preferred technique since the sample is easy to collect and the method is inexpensive and non-invasive. Salivary diagnostics have even been identified as potential substitutes for serum protein biomarkers. However, the optimal protocol for collecting saliva has not yet been established. In many scientific settings, such as randomized controlled trials, sampling and statistical errors often occur when handling samples from healthy volunteers. These errors can be due to the psychological behavior of the volunteers, subject nonadherence, questionnaire characteristics, collection methods, and/or sample processing. The purpose of the review presented here is to outline the strategies for managing the risk factors and to minimize the sampling errors during saliva collection in healthy volunteers.

Neuronal and molecular mechanisms of sleep homeostasis

Sleep is necessary for survival, and prolonged waking causes a homeostatic increase in the need for recovery sleep. Homeostasis is a core component of sleep regulation and has been tightly conserved across evolution from invertebrates to man. Homeostatic sleep regulation was first identified among insects in cockroaches several decades ago, but the characterization of sleep rebound in Drosophila melanogaster opened the use of insect model species to understand homeostatic functions and regulation of sleep. This review describes circuits in two neuropil structures, the central complex and mushroom bodies, that influence sleep homeostasis and neuromodulatory systems that influence the accrual of homeostatic sleep need.

Stilbene Glucoside, a Putative Sleep Promoting Constituent from Polygonum multiflorum Affects Sleep Homeostasis by Affecting the Activities of Lactate Dehydrogenase and Salivary Alpha Amylase

Chinese herbal medicine (CHM) has been used for treating insomnia for centuries. The most used CHM for insomnia was Polygonum multiflorum. However, the molecular mechanism for CHM preventing insomnia is unknown. Stilbene glucoside (THSG), an important active component of P. multiflorum, may play an important role for treating insomnia. To test the hypothesis, Kunming mice were treated with different dosages of THSG. To examine the sleep duration, a computer-controlled sleep-wake detection system was implemented. Electroencephalogram (EEG) and electromyogram (EMG) electrodes were implanted to determine sleep-wake state. RT-PCR and Western blot was used to measure the levels of lactate dehydrogenase (LDH) and saliva alpha amylase. Spearman's rank correlation coefficient was used to identify the strength of correlation between the variables. The results showed that THSG significantly prolonged the sleep time of the mice (p<0.01). THSG changed sleep profile by reducing wake and rapid eye movement (REM) period, and increasing non-REM period. RT-PCR and Western blot analysis showed that THSG could down-regulate the levels of LDH and saliva alpha amylase (p<0.05). The level of lactate and glucose was positively related with the activity of LDH and saliva alpha amylase (p<0.05), respectively. On the other hand, the activities of LDH and amylase were negatively associated with sleep duration (p<0.05). The levels of lactate and glucose affect sleep homeostasis. Thus, THSG may prevent insomnia by regulating sleep duration via LDH and salivary alpha amylase.

An Ecological Perspective on Sleep Disruption

Despite its evolutionary importance and apparent ubiquity among animals, the ecological significance of sleep is largely unresolved. The ecology of sleep has been particularly neglected in invertebrates. In insects, recent neurobehavioral research convincingly demonstrates that resting behavior shares several common characteristics with sleep in vertebrates. Laboratory studies have produced compelling evidence that sleep disruption can cause changes in insect daily activity patterns (via "sleep rebound") and have consequences for behavioral performance during active periods. However, factors that could cause insect sleep disruption in nature have not been considered nor have the ecological consequences. Drawing on evidence from laboratory studies, we argue that sleep disruption may be an overlooked component of insect ecology and could be caused by a variety of anthropogenic and nonanthropogenic factors in nature. We identify several candidate sleep-disrupting factors and provide new insights on the potential consequences of sleep disruption on individual fitness, species interactions, and ecosystem services. We propose an experimental framework to bridge the current gap in knowledge between laboratory and field studies. We conclude that sleep disruption is a potential mechanism underpinning variation in behavioral, population, and community-level processes associated with several aspects of global change.

Decreased salivary alpha-amylase levels are associated with performance deficits during sleep loss

During sleep deprivation, neurobehavioral functions requiring sustained levels of attention and alertness are significantly impaired. Discrepancies between subjective measures of sleepiness and objective performance during sustained operations have led to interest in physiological monitoring of operator performance. Alertness, vigilance, and arousal are modulated by the wake-promoting actions of the central noradrenergic system. Salivary alpha-amylase (sAA) has been proposed as a sensitive peripheral measure of noradrenergic activity, but limited research has investigated the relationship between sAA and performance. In a laboratory-controlled environment, we investigated the relationship between sAA levels, subjective sleepiness, and performance during two days (50h) of total sleep deprivation. Beginning at 09:00, twelve healthy participants (5 females) aged 22.5±2.5years (mean±SD) provided saliva samples, recorded ratings of subjective sleepiness, completed a brief 3-min psychomotor vigilance task (PVT-B) and performed a 40-min simulated driving task, at regular 3h intervals during wakefulness. Ratings of subjective sleepiness exhibited a constant linear increase (p<0.001) during sleep deprivation. In contrast, sAA levels showed a marked diurnal profile, with levels increasing during the day (p<0.001) and steadily declining in the evening and early-morning (p<0.001). PVT-B (mean reaction time and mean slowest 10% reaction time) and simulated driving performance (speed deviation and lane deviation) also exhibited diurnal profiles across the two days of sleep deprivation. Performance peaked in the afternoon (p<0.001) and then steadily worsened as wakefulness continued into the evening and early-morning (p<0.001). Further analysis revealed that higher sAA levels in the hour preceding each performance assessment were associated with better PVT-B and driving performance (p<0.001). These findings suggest that sAA measures may be suitable indicators of performance deficits during sustained wakefulness and highlight the potential for sAA to be considered for physiological monitoring of performance. In operational environments sAA levels, as part of a panel of physiological measures, may be useful for assessing fitness-for-duty prior to safety being compromised or when performance deficits are unknown.

Precision medicine in circadian rhythm sleep-wake disorders: current state and future perspectives

In circadian rhythm sleep-wake disorders precision medicine is less developed than in other medical disciplines mainly because homeostatic sleep and circadian timing have a very complex phenotype with multiple genetic regulation mechanisms. However, biomarkers, phenotyping and psychosocial characteristics are increasingly used. Devices for polysomnography, actigraphy and sleep-tracking applications in mobile phones and other consumer devices with eHealth technologies are increasingly used. Also sleep-related questionnaires and the assessment of co-morbidities influencing sleep in circadian rhythm sleep-wake disorders are major contributors to precision sleep medicine. To further strengthen the (pharmaco-)genetic and biomarker pillar, technology needs to be evolved further. Routinely measuring treatment results using patient-reported outcome measures and clinical neurophysiological instruments will boost precision sleep medicine.

Selection of Suitable Reference Genes for Analysis of Salivary Transcriptome in Non-Syndromic Autistic Male Children

Childhood autism is a severe form of complex genetically heterogeneous and behaviorally defined set of neurodevelopmental diseases, collectively termed as autism spectrum disorders (ASD). Reverse transcriptase quantitative real-time PCR (RT-qPCR) is a highly sensitive technique for transcriptome analysis, and it has been frequently used in ASD gene expression studies. However, normalization to stably expressed reference gene(s) is necessary to validate any alteration reported at the mRNA level for target genes. The main goal of the present study was to find the most stable reference genes in the salivary transcriptome for RT-qPCR analysis in non-syndromic male childhood autism. Saliva samples were obtained from nine drug naïve non-syndromic male children with autism and also sex-, age-, and location-matched healthy controls using the RNA-stabilizer kit from DNA Genotek. A systematic two-phased measurement of whole saliva mRNA levels for eight common housekeeping genes (HKGs) was carried out by RT-qPCR, and the stability of expression for each candidate gene was analyzed using two specialized algorithms, geNorm and NormFinder, in parallel. Our analysis shows that while the frequently used HKG ACTB is not a suitable reference gene, the combination of GAPDH and YWHAZ could be recommended for normalization of RT-qPCR analysis of salivary transcriptome in non-syndromic autistic male children.

Smartphone-based point-of-care testing of salivary α-amylase for personal psychological measurement

Here we report a smartphone-based potentiometric biosensor for point-of-care testing of salivary α-amylase (sAA), which is one of the most sensitive indices of autonomic nervous system activity, and therefore a promising non-invasive biomarker for mental health. The biosensing system includes a smartphone having a sAA-detection App, a potentiometric reader and a sensing chip with preloaded reagents. The saliva sample wicks into the reaction zone on the sensing chip so that the sAA reacts with the preloaded reagents, resulting in conversion of an electron mediator Fe(CN)6(3-) to Fe(CN)6(4-). The sensing chip is then pressed by fingers to push the reaction mixture into the detection zone for the potentiometric measurement. The potential measured by the smartphone-powered potentiometric reader is sent to the smartphone App via the USB port, and converted into sAA concentration based on a calibration curve. Using our method, sAA in real human sample is quantitatively analyzed within 5 min. The results are in good agreement with that obtained using a reference method, and correlated to psychological states of the subjects.

The Neonatal Salivary Transcriptome

The ability to noninvasively assess the physical and developmental status of a neonate is a goal of modern medicine. In recent years, technological advances have permitted the high-throughput analysis of saliva for thousands of genes, proteins, and metabolites from a single sample source. Saliva is an ideal biofluid to assess health, disease, and development in the newborn. It may be harnessed repeatedly, even in the most vulnerable patients, without risk of harm. Translating novel information about an infant's global development and risk of disease to the neonatal bedside through the salivary transcriptome has the potential to significantly improve clinical care and outcomes in this at-risk population.

Identification of miR-139-5p as a saliva biomarker for tongue squamous cell carcinoma: a pilot study

BACKGROUND

Of all human oral carcinomas, 41 % are localized to the tongue. Despite considerable improvements in both diagnosis and treatment, tongue squamous cell carcinoma (TSCC) has remained one of the most lethal types of cancer. Here, we aimed at identifying a salivary microRNA (miRNA) expression signature specific for TSCC patients.

METHODS

To identify putative diagnostic biomarkers, we compared the miRNA expression profiles of saliva samples from three TSCC patients and four healthy control individuals using an Agilent miRNA microarray platform (V19). Three of the differentially expressed miRNAs identified were selected for further validation using quantitative reverse-transcription PCR (qRT-PCR) in saliva samples from 25 TSCC patients and 25 healthy control individuals.

RESULTS

Through microarray-based expression profiling, we found that 419 miRNAs were deregulated in the saliva samples from the TSCC patients compared to those from the healthy control individuals tested. Subsequent qRT-PCR analysis revealed that the expression level of miR-139-5p was significantly reduced in the TSCC validation samples compared to the controls. Further analysis of post-operative saliva samples derived from TSCC patients revealed that the miR-139-5p expression levels had turned back to normal again. In addition, we found that miR-139-5p exhibited enough power to discriminate pre-operative TSCC patients from both normal individuals (AUC: 0.805) and post-operative TSCC patients (AUC: 0.713), thereby underscoring its diagnostic potential.

CONCLUSIONS

From our results we conclude that saliva can be used as a feasible source for routine TSCC diagnostics and that miR-139-5p may serve as a potential biomarker for early TSCC detection.

Identification of genes associated with resilience/vulnerability to sleep deprivation and starvation in Drosophila

BACKGROUND AND STUDY OBJECTIVES

Flies mutant for the canonical clock protein cycle (cyc(01)) exhibit a sleep rebound that is ∼10 times larger than wild-type flies and die after only 10 h of sleep deprivation. Surprisingly, when starved, cyc(01) mutants can remain awake for 28 h without demonstrating negative outcomes. Thus, we hypothesized that identifying transcripts that are differentially regulated between waking induced by sleep deprivation and waking induced by starvation would identify genes that underlie the deleterious effects of sleep deprivation and/or protect flies from the negative consequences of waking.

DESIGN

We used partial complementary DNA microarrays to identify transcripts that are differentially expressed between cyc(01) mutants that had been sleep deprived or starved for 7 h. We then used genetics to determine whether disrupting genes involved in lipid metabolism would exhibit alterations in their response to sleep deprivation.

SETTING

Laboratory.

PATIENTS OR PARTICIPANTS

Drosophila melanogaster.

INTERVENTIONS

Sleep deprivation and starvation.

MEASUREMENTS AND RESULTS

We identified 84 genes with transcript levels that were differentially modulated by 7 h of sleep deprivation and starvation in cyc(01) mutants and were confirmed in independent samples using quantitative polymerase chain reaction. Several of these genes were predicted to be lipid metabolism genes, including bubblegum, cueball, and CG4500, which based on our data we have renamed heimdall (hll). Using lipidomics we confirmed that knockdown of hll using RNA interference significantly decreased lipid stores. Importantly, genetically modifying bubblegum, cueball, or hll resulted in sleep rebound alterations following sleep deprivation compared to genetic background controls.

CONCLUSIONS

We have identified a set of genes that may confer resilience/vulnerability to sleep deprivation and demonstrate that genes involved in lipid metabolism modulate sleep homeostasis.

A new model to study sleep deprivation-induced seizure

BACKGROUND AND STUDY OBJECTIVES

A relationship between sleep and seizures is well-described in both humans and rodent animal models; however, the mechanism underlying this relationship is unknown. Using Drosophila melanogaster mutants with seizure phenotypes, we demonstrate that seizure activity can be modified by sleep deprivation.

DESIGN

Seizure activity was evaluated in an adult bang-sensitive seizure mutant, stress sensitive B (sesB(9ed4)), and in an adult temperature sensitive seizure mutant seizure (sei(ts1)) under baseline and following 12 h of sleep deprivation. The long-term effect of sleep deprivation on young, immature sesB(9ed4) flies was also assessed.

SETTING

Laboratory.

PARTICIPANTS

Drosophila melanogaster.

INTERVENTIONS

Sleep deprivation.

MEASUREMENTS AND RESULTS

Sleep deprivation increased seizure susceptibility in adult sesB(9ed4)/+ and sei(ts1) mutant flies. Sleep deprivation also increased seizure susceptibility when sesB was disrupted using RNAi. The effect of sleep deprivation on seizure activity was reduced when sesB(9ed4)/+ flies were given the anti-seizure drug, valproic acid. In contrast to adult flies, sleep deprivation during early fly development resulted in chronic seizure susceptibility when sesB(9ed4)/+ became adults.

CONCLUSIONS

These findings show that Drosophila is a model organism for investigating the relationship between sleep and seizure activity.

Circadian Clock Dysfunction and Psychiatric Disease: Could Fruit Flies have a Say?

There is evidence of a link between the circadian system and psychiatric diseases. Studies in humans and mammals suggest that environmental and/or genetic disruption of the circadian system leads to an increased liability to psychiatric disease. Disruption of clock genes and/or the clock network might be related to the etiology of these pathologies; also, some genes, known for their circadian clock functions, might be associated to mental illnesses through clock-independent pleiotropy. Here, we examine the features which we believe make Drosophila melanogaster a model apt to study the role of the circadian clock in psychiatric disease. Despite differences in the organization of the clock system, the molecular architecture of the Drosophila and mammalian circadian oscillators are comparable and many components are evolutionarily related. In addition, Drosophila has a rather complex nervous system, which shares much at the cell and neurobiological level with humans, i.e., a tripartite brain, the main neurotransmitter systems, and behavioral traits: circadian behavior, learning and memory, motivation, addiction, social behavior. There is evidence that the Drosophila brain shares some homologies with the vertebrate cerebellum, basal ganglia, and hypothalamus-pituitary-adrenal axis, the dysfunctions of which have been tied to mental illness. We discuss Drosophila in comparison to mammals with reference to the: organization of the brain and neurotransmitter systems; architecture of the circadian clock; clock-controlled behaviors. We sum up current knowledge on behavioral endophenotypes, which are amenable to modeling in flies, such as defects involving sleep, cognition, or social interactions, and discuss the relationship of the circadian system to these traits. Finally, we consider if Drosophila could be a valuable asset to understand the relationship between circadian clock malfunction and psychiatric disease.

Excessive daytime sleepiness is associated with changes in salivary inflammatory genes transcripts

Excessive daytime sleepiness (EDS) is a ubiquitous problem that affects public health and safety. A test that can reliably identify individuals that suffer from EDS is needed. In contrast to other methods, salivary biomarkers are an objective, inexpensive, and noninvasive method to identify individuals with inadequate sleep. Although we have previously shown that inflammatory genes are elevated in saliva samples taken from sleep deprived individuals, it is unclear if inflammatory genes will be elevated in clinical populations with EDS. In this study, salivary samples from individuals with sleep apnea were evaluated using the Taqman low density inflammation array. Transcript levels for 3 genes, including prostaglandin-endoperoxide synthase 2 (PTGS2), were elevated in patients with sleep apnea. Interestingly, PTGS2 was also elevated in patients with EDS but who did not have sleep apnea. These data demonstrate the feasibility of using salivary transcript levels to identify individuals that self-report excessive daytime sleepiness.

Sleep, Performance, and Memory in Flies

Drosophila has proven to be a powerful model to identify genes and circuits that impact sleep. While the majority of studies have primarily been interested in identifying manipulations that alter sleep time, a growing body of work has begun to focus on how changing sleep influences functional outcomes such as cognitive performance, structural plasticity, and metabolism to name a few. Evaluating sleep time provides an appropriate entry point into elucidating sleep function. However, it is not possible to fully understand how a manipulation has impacted sleep regulation without first establishing how it has affected the animals’ well-being. Synaptic plasticity and memory are important functional outcomes that can be used to asses an animal’s status. In this manuscript, we review recent advances in studies examining sleep, memory, and performance. We conclude that as Drosophila sleep researchers expand their analysis beyond sleep time, the opportunities to discover the function of sleep will be enhanced.

Genetic dissection of sleep homeostasis

Sleep is a complex behavior both in its manifestation and regulation, that is common to almost all animal species studied thus far. Sleep is not a unitary behavior and has many different aspects, each of which is tightly regulated and influenced by both genetic and environmental factors. Despite its essential role for performance, health, and well-being, genetic mechanisms underlying this complex behavior remain poorly understood. One important aspect of sleep concerns its homeostatic regulation, which ensures that levels of sleep need are kept within a range still allowing optimal functioning during wakefulness. Uncovering the genetic pathways underlying the homeostatic aspect of sleep is of particular importance because it could lead to insights concerning sleep's still elusive function and is therefore a main focus of current sleep research. In this chapter, we first give a definition of sleep homeostasis and describe the molecular genetics techniques that are used to examine it. We then provide a conceptual discussion on the problem of assessing a sleep homeostatic phenotype in various animal models. We finally highlight some of the studies with a focus on clock genes and adenosine signaling molecules.

Blood-gene expression reveals reduced circadian rhythmicity in individuals resistant to sleep deprivation

STUDY OBJECTIVES

To address whether changes in gene expression in blood cells with sleep loss are different in individuals resistant and sensitive to sleep deprivation.

DESIGN

Blood draws every 4 h during a 3-day study: 24-h normal baseline, 38 h of continuous wakefulness and subsequent recovery sleep, for a total of 19 time-points per subject, with every 2-h psychomotor vigilance task (PVT) assessment when awake.

SETTING

Sleep laboratory.

PARTICIPANTS

Fourteen subjects who were previously identified as behaviorally resistant (n = 7) or sensitive (n = 7) to sleep deprivation by PVT.

INTERVENTION

Thirty-eight hours of continuous wakefulness.

MEASUREMENTS AND RESULTS

We found 4,481 unique genes with a significant 24-h diurnal rhythm during a normal sleep-wake cycle in blood (false discovery rate [FDR] < 5%). Biological pathways were enriched for biosynthetic processes during sleep. After accounting for circadian effects, two genes (SREBF1 and CPT1A, both involved in lipid metabolism) exhibited small, but significant, linear changes in expression with the duration of sleep deprivation (FDR < 5%). The main change with sleep deprivation was a reduction in the amplitude of the diurnal rhythm of expression of normally cycling probe sets. This reduction was noticeably higher in behaviorally resistant subjects than sensitive subjects, at any given P value. Furthermore, blood cell type enrichment analysis showed that the expression pattern difference between sensitive and resistant subjects is mainly found in cells of myeloid origin, such as monocytes.

CONCLUSION

Individual differences in behavioral effects of sleep deprivation are associated with differences in diurnal amplitude of gene expression for genes that show circadian rhythmicity.

Saliva-based biosensors: noninvasive monitoring tool for clinical diagnostics

Saliva is increasingly recognised as an attractive diagnostic fluid. The presence of various disease signalling salivary biomarkers that accurately reflect normal and disease states in humans and the sampling benefits compared to blood sampling are some of the reasons for this recognition. This explains the burgeoning research field in assay developments and technological advancements for the detection of various salivary biomarkers to improve clinical diagnosis, management, and treatment. This paper reviews the significance of salivary biomarkers for clinical diagnosis and therapeutic applications, with focus on the technologies and biosensing platforms that have been reported for screening these biomarkers.

Genetic rescue of functional senescence in synaptic and behavioral plasticity

STUDY OBJECTIVES

Aging has been linked with decreased neural plasticity and memory formation in humans and in laboratory model species such as the fruit fly, Drosophila melanogaster. Here, we examine plastic responses following social experience in Drosophila as a high-throughput method to identify interventions that prevent these impairments.

PATIENTS OR PARTICIPANTS

Wild-type and transgenic Drosophila melanogaster.

DESIGN AND INTERVENTIONS

Young (5-day old) or aged (20-day old) adult female Drosophila were housed in socially enriched (n = 35-40) or isolated environments, then assayed for changes in sleep and for structural markers of synaptic terminal growth in the ventral lateral neurons (LNVs) of the circadian clock.

MEASUREMENTS AND RESULTS

When young flies are housed in a socially enriched environment, they exhibit synaptic elaboration within a component of the circadian circuitry, the LNVs, which is followed by increased sleep. Aged flies, however, no longer exhibit either of these plastic changes. Because of the tight correlation between neural plasticity and ensuing increases in sleep, we use sleep after enrichment as a high-throughput marker for neural plasticity to identify interventions that prolong youthful plasticity in aged flies. To validate this strategy, we find three independent genetic manipulations that delay age-related losses in plasticity: (1) elevation of dopaminergic signaling, (2) over-expression of the transcription factor blistered (bs) in the LNVs, and (3) reduction of the Imd immune signaling pathway. These findings provide proof-of-principle evidence that measuring changes in sleep in flies after social enrichment may provide a highly scalable assay for the study of age-related deficits in synaptic plasticity.

CONCLUSIONS

These studies demonstrate that Drosophila provides a promising model for the study of age-related loss of neural plasticity and begin to identify genes that might be manipulated to delay the onset of functional senescence.

Individual differences in the cortisol and salivary α-amylase awakening responses in early childhood: relations to age, sex, and sleep

Recent studies have examined post-waking changes in cortisol as a marker of HPA functioning, but questions remain about the stability of this response, as well as its relation to sleep and other ANS markers. The purposes of this study were to a) examine the presence and developmental changes in the cortisol awakening response (CAR) and salivary α-amylase awakening (sAA-AR) in a toddler sample and b) determine whether and how sleep relates to these responses in this age group. We measured cortisol and sAA upon awakening (and 30 min post-waking) and sleep characteristics using actigraphy (e.g., total sleep time, sleep efficiency, number of awakenings) in toddlers (N = 47; 36% female, ages 12-24 months). Forty-six percent of toddlers demonstrated a CAR and 52% demonstrated a sAA-AR. Strength of either response did not change linearly with age. Additionally, likelihood of demonstrating the CAR and sAA-AR was unrelated to age, sex, awakening time, time between samples, and time since feeding. Higher waking cortisol levels were associated with a shorter total sleep time and an earlier awakening. No associations were observed between sleep characteristics and the sAA-AR, ps > .05. Our findings suggest that these awakening responses function independently of sleep in toddlers. Additionally, the lack of change in percentage of children showing a CAR or sAA-AR across these ages suggests that these responses are stable and not emerging reliably across the second year of life.

Identification of Redeye, a new sleep-regulating protein whose expression is modulated by sleep amount

In this study, we report a new protein involved in the homeostatic regulation of sleep in Drosophila. We conducted a forward genetic screen of chemically mutagenized flies to identify short-sleeping mutants and found one, redeye (rye) that shows a severe reduction of sleep length. Cloning of rye reveals that it encodes a nicotinic acetylcholine receptor α subunit required for Drosophila sleep. Levels of RYE oscillate in light-dark cycles and peak at times of daily sleep. Cycling of RYE is independent of a functional circadian clock, but rather depends upon the sleep homeostat, as protein levels are up-regulated in short-sleeping mutants and also in wild type animals following sleep deprivation. We propose that the homeostatic drive to sleep increases levels of RYE, which responds to this drive by promoting sleep. DOI: http://dx.doi.org/10.7554/eLife.01473.001.

Salivary biomarkers of physical fatigue as markers of sleep deprivation

STUDY OBJECTIVE

Determine whether a salivary biomarker of physical fatigue, referred to as the fatigue biomarker index (FBI), can discriminate a control group from a sleep deprived group when saliva is collected under controlled conditions. The study expands on previous work examining changes in the composition of saliva during periods of prolonged exercise.

METHODS

Thirty (30) young adults (14 Control [CON]; 16 Sleep Deprived [SDEP]) were monitored for mood state (Profile of Mood States [POMS]), cognitive performance (Stroop Color-Conflict Tests), and salivary biomarkers of physical fatigue over a 48-h period with sampling at 3-h intervals. Trials lasted from 06:00 on day 1 (time = -3 h) to 09:00 on day 3 (time = 48 h). Levels of salivary biomarkers were calculated from liquid chromatography-mass spectrometry (LC-MS) data. Statistical comparisons were made using Wilcoxon rank sum tests with a Bonferroni correction to limit type 1 error. Receiver-operator characteristic (ROC) analysis was used to evaluate the ability of the various parameters to distinguish the SDEP population from the CON population.

RESULTS

Longitudinal analysis demonstrated significant between-group differences in all three parameters. ROC analysis demonstrated that cognitive performance tests and salivary biomarkers of physical fatigue distinguish the SDEP population from the CON population.

CONCLUSIONS

A previously identified salivary biomarker of physical fatigue may provide an alternative method for discriminating sleep deprived from rested individuals. The salivary biomarker of physical fatigue holds promise as an objective measure of sleep deprivation, perhaps eventually removing the reliance on self-reported sleep diaries and/or repeated polysomnographs for longitudinal tracking of sleep quality and/or diagnosis of sleep disorders.

Small RNA transcriptomes of two types of exosomes in human whole saliva determined by next generation sequencing

Small non-coding RNAs, such as microRNAs (miRNAs), are involved in diverse processes, including organ development and tissue differentiation. Exosomes are small membrane vesicles (30-100 nm in diameter) produced by numerous cells. Recently, exosomes have been shown to contain miRNAs. However, the small RNAs contained in exosomes are not fully characterized. In a previous study, we found at least two types of salivary exosome that are different in size and have different proteomes. Studies of salivary exosomal small RNAs are limited to miRNAs. In this study, we examined small RNA transcriptomes using next generation sequencing technology to elucidate a full transcriptome set of small RNAs expressed in the two types of salivary exosomes and in whole saliva (WS). Many types of small RNA, such as miRNA, piwi-interacting RNA (piRNA), small nucleolar RNA (snoRNA) and other small RNAs are contained in salivary exosomes and WS. Among these small RNAs we identified novel miRNA candidates.

Cross-translational studies in human and Drosophila identify markers of sleep loss

Inadequate sleep has become endemic, which imposes a substantial burden for public health and safety. At present, there are no objective tests to determine if an individual has gone without sleep for an extended period of time. Here we describe a novel approach that takes advantage of the evolutionary conservation of sleep to identify markers of sleep loss. To begin, we demonstrate that IL-6 is increased in rats following chronic total sleep deprivation and in humans following 30 h of waking. Discovery experiments were then conducted on saliva taken from sleep-deprived human subjects to identify candidate markers. Given the relationship between sleep and immunity, we used Human Inflammation Low Density Arrays to screen saliva for novel markers of sleep deprivation. Integrin αM (ITGAM) and Anaxin A3 (AnxA3) were significantly elevated following 30 h of sleep loss. To confirm these results, we used QPCR to evaluate ITGAM and AnxA3 in independent samples collected after 24 h of waking; both transcripts were increased. The behavior of these markers was then evaluated further using the power of Drosophila genetics as a cost-effective means to determine whether the marker is associated with vulnerability to sleep loss or other confounding factors (e.g., stress). Transcript profiling in flies indicated that the Drosophila homologues of ITGAM were not predictive of sleep loss. Thus, we examined transcript levels of additional members of the integrin family in flies. Only transcript levels of scab, the Drosophila homologue of Integrin α5 (ITGA5), were associated with vulnerability to extended waking. Since ITGA5 was not included on the Low Density Array, we returned to human samples and found that ITGA5 transcript levels were increased following sleep deprivation. These cross-translational data indicate that fly and human discovery experiments are mutually reinforcing and can be used interchangeably to identify candidate biomarkers of sleep loss.

On the origin and diagnostic use of salivary RNA

Saliva as a diagnostic fluid enables non-invasive sampling, which can be performed even by an untrained person. Saliva is, thus, particularly useful for large population screenings, for children, elderly and whenever repeated samplings are needed. Saliva is a plasma filtrate actively modified by the salivary glands. Saliva could replace some routine blood tests in the future. The sources of salivary RNA include oral epithelial cells and oral micro-organisms. Recent developments suggest that using known salivary RNA markers, it is possible to diagnose diseases such as oral carcinoma and other diseases will be added soon. Salivary RNA can be used to identify oral bacteria and to determine the expression of specific genes. On a systemic level, it provides information about the whole oral transcriptome and microbiome. Despite the small amount of salivary RNA, the issues with its isolation have been overcome. Saliva, thus, contains RNA of sufficient quality and quantity for sensitive and specific analyses. Salivary RNA can provide medically relevant information about oral microbiome, oral carcinoma, but also breast and pancreatic cancer and is, thus, a promising tool for future research and clinical diagnostics.

The use of salivary cytokines as a screening tool for oral squamous cell carcinoma : A review of the literature

Oral squamous cell carcinoma (OSCC) is the most common type of head and neck cancer. The 5-year survival rate has remained below 50% over the last two decades, and new tools for early diagnosis are needed. Saliva has been used for diagnosis of several systemic diseases, and its use for diagnosis of OSCC has been sought extensively. Among the many salivary analytes for diagnosis of OSCC, accumulating evidences indicate the possibility of using salivary cytokines. Overproduction of proinflammatory, proangiogenic cytokines by OSCC cells has been reported, and their role in tumor progression and angiogenesis is well established. However, many inflammatory conditions and immunological diseases could affect the levels of cytokines in serum and saliva. This article has reviewed publications in this matter, and some strengths and weaknesses have been pointed out. Conclusively, large-scale investigations are required for validation of the use of salivary cytokines for diagnosis of OSCC, with consideration to the influential role of periodontal inflammation in their levels.

Reduced slow-wave rebound during daytime recovery sleep in middle-aged subjects

Cortical synchronization during NREM sleep, characterized by electroencephalographic slow waves (SW <4Hz and >75 µV), is strongly related to the number of hours of wakefulness prior to sleep and to the quality of the waking experience. Whether a similar increase in wakefulness length leads to a comparable enhancement in NREM sleep cortical synchronization in young and older subjects is still a matter of debate in the literature. Here we evaluated the impact of 25-hours of wakefulness on SW during a daytime recovery sleep episode in 29 young (27y ±5), and 34 middle-aged (51y ±5) subjects. We also assessed whether age-related changes in NREM sleep cortical synchronization predicts the ability to maintain sleep during daytime recovery sleep. Compared to baseline sleep, sleep efficiency was lower during daytime recovery sleep in both age-groups but the effect was more prominent in the middle-aged than in the young subjects. In both age groups, SW density, amplitude, and slope increased whereas SW positive and negative phase duration decreased during daytime recovery sleep compared to baseline sleep, particularly in anterior brain areas. Importantly, compared to young subjects, middle-aged participants showed lower SW density rebound and SW positive phase duration enhancement after sleep deprivation during daytime recovery sleep. Furthermore, middle-aged subjects showed lower SW amplitude and slope enhancements after sleep deprivation than young subjects in frontal and prefrontal derivations only. None of the SW characteristics at baseline were associated with daytime recovery sleep efficiency. Our results support the notion that anterior brain areas elicit and may necessitate more intense recovery and that aging reduces enhancement of cortical synchronization after sleep loss, particularly in these areas. Age-related changes in the quality of wake experience may underlie age-related reduction in markers of cortical synchronization enhancement after sustained wakefulness.

Chronic psychosocial stressors and salivary biomarkers in emerging adults

We investigated whole saliva as a source of biomarkers to distinguish individuals who have, and who have not, been chronically exposed to severe and threatening life difficulties. We evaluated RNA and DNA metrics, expression of 37 candidate genes, and cortisol release in response to the Trier Social Stress Test, as well as clinical characteristics, from 48 individuals stratified on chronic exposure to psychosocial stressors within the last year as measured by the Life Events and Difficulties Schedule. Candidate genes were selected based on their differential gene expression ratio in circulating monocytes from a published genome-wide analysis of adults experiencing different levels of exposure to a chronic stressor. In univariate analyses, we observed significantly decreased RNA integrity (RIN) score (P = 0.04), and reduced expression of glucocorticoid receptor-regulated genes (Ps < 0.05) in whole saliva RNA from individuals exposed to chronic stressors, as compared to those with no exposure. In those exposed, we observed significantly decreased BMI (P < 0.001), increased ever-smoking and increased lifetime alcohol abuse or dependence (P ≤ 0.03), and a reduction of cortisol release. In post hoc multivariate analyses including clinical and biospecimen-derived variables, we consistently observed significantly decreased expression of IL8 (Ps<0.05) in individuals exposed, with no significant association to RIN score. Alcohol use disorders, tobacco use, a reduced acute stress response and decreased salivary IL8 gene expression characterize emerging adults chronically exposed to severe and threatening psychosocial stressors.

Changes in gene expression with sleep

There is general agreement within the sleep community and among public health officials of the need for an accessible biomarker of sleepiness. As the foregoing discussions emphasize, however, it may be more difficult to reach consensus on how to define such a biomarker than to identify candidate molecules that can be then evaluated to determine if they might be useful to solve a variety of real-world problems related to insufficient sleep. With that in mind, a goal of our laboratories has been to develop a rational strategy to expedite the identification of candidate biomarkers. 1 We began with the assumption that since both the genetic and environmental context of a gene can influence its behavior, an effective test of sleep loss will likely be composed of a panel of multiple biomarkers. That is, we believe that it is premature to exclude a candidate analyte simply because it might also be modulated in response to other conditions (e.g., illness, metabolism, sympathetic tone, etc.). Our next assumption was that an easily accessible biomarker would be more useful in real-world settings. Thus, we have focused on saliva, as opposed to urine or blood, as a rich source of biological analytes that can be mined to optimize the chances of bringing a biomarker out into the field. Finally, we recognize that conducting validation studies in humans can be expensive and time consuming. Thus, we have exploited genetic and pharmacological tools in the model organism Drosophila melanogaster to more fully characterize the behavior of the most exciting candidate biomarkers.