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

A patient with an uncommon complication from insertion of a central venous catheter: A case report

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Increased Ventricular Premature Contraction Frequency During REM Sleep in Patients with Coronary Artery Disease and Obstructive Sleep Apnea

Background Patients with obstructive sleep apnea are reported to have a peak of sudden cardiac death at night, in contrast to patients without apnea whose peak is in the morning. We hypothesized that ventricular premature contraction (VPC) frequency would correlate with measures of apnea and sympathetic activity.Methods Electrocardiograms from a sleep study of 125 patients with coronary artery disease were evaluated. Patients were categorized by apnea-hypopnea index (AHI) into Moderate (AHI <15) or Severe (AHI>15) apnea groups. Sleep stages studied were Wake, S1, S2, S34, and rapid eye movement (REM). Parameters of a potent autonomically-based risk predictor for sudden cardiac death called heart rate turbulence were calculated.Results There were 74 Moderate and 51 Severe obstructive sleep apnea patients. VPC frequency was affected significantly by sleep stage (Wake, S2 and REM, F=5.8, p<.005) and by AHI (F=8.7, p<.005). In Severe apnea patients, VPC frequency was higher in REM than in Wake (p=.011). In contrast, patients with Moderate apnea had fewer VPCs and exhibited no sleep stage dependence (p=.19). Oxygen desaturation duration per apnea episode correlated positively with AHI (r2=.71, p<.0001), and was longer in REM than in non-REM (p<.0001). The heart rate turbulence parameter TS correlated negatively with oxygen desaturation duration in REM (r2=.06, p=.014).Conclusions Higher VPC frequency coupled with higher sympathetic activity caused by longer apnea episodes in REM sleep may be one reason for increased nocturnal death in apneic patients

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

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

Identification of a biomarker for sleep drive in flies and humans

It is a common experience to sacrifice sleep to meet the demands of our 24-h society. Current estimates reveal that as a society, we sleep on average 2 h less than we did 40 years ago. This level of sleep restriction results in negative health outcomes and is sufficient to produce cognitive deficits and reduced attention and is associated with increased risk for traffic and occupational accidents. Unfortunately, there is no simple quantifiable marker that can detect an individual who is excessively sleepy before adverse outcomes become evident. To address this issue, we have developed a simple and effective strategy for identifying biomarkers of sleepiness by using genetic and pharmacological tools that dissociate sleep drive from wake time in the model organism Drosophila melanogaster. These studies have identified a biomarker, Amylase, that is highly correlated with sleep drive. More importantly, both salivary Amylase activity and mRNA levels are also responsive to extended waking in humans. These data indicate that the fly is relevant for human sleep research and represents a first step in developing an effective method for detecting sleepiness in vulnerable populations