Figure - uploaded by Emrah Çaylak
Content may be subject to copyright.
International Classification of Sleep Disorders, Version 2 (ICSD, 2005)
Source publication
Common sleep disorders include narcolepsy, restless legs syndrome, obstructive sleep apnea syndrome, circadian sleep disorders and parasomnias. They are influenced by genes and several research groups to attempt to identify susceptibility genes of sleep disorders through the sequential analysis of genetic linkage and association. Strong evidence ha...
Context in source publication
Context 1
... or hypersomnia), a presumed basic aetiology (e.g. biological clock disturbances for circadian sleep disorders (CSD)), or the organ system from which the problems arise, such as sleep-related breathing disorders (see Table 1). These disorders and the resulting sleep deprivation interfere with work, driving and social activities. ...Similar publications
Introduction: sleep disorder can affect an overall health, safety and quality of life. Sleep has a relevant facilitatory role in learning and memory processes. Medical students who suffer from sleep deprivation run a major risk of creating serious medical problems.
Objectives: To determine the magnitude and types of multiple sleep disorders among...
Objective: The consequences of sleep deprivation in type 1 diabetes (T1D) patients are poorly
understood. Our aim was to determine how sleep disorders influence lipid profile and insulin
sensitivity in T1D patients. Materials and methods: This was a cross-sectional study at a public
university hospital. Demographic information and medical histories...
Sleep physiology is a field of increasing importance because the recent awareness of how sleep affects us all, whether it is good or bad. Sleep disorders have a big impact on daily life and functioning, but this is true, also for other disorders that are not primarily associated with sleep disturbances. Subsequently, several disorders should be inv...
Sleep is involved in many physiological processes and is essential for both physical and mental health. Obesity and sleep deprivation due to sleep disorders are major public health issues. Their incidence is increasing, and they have a wide range of adverse health-related consequences, including life-threatening cardiovascular disease. The impact o...
Objective
The consequences of sleep deprivation in type 1 diabetes (T1D) patients are poorly understood. Our aim was to determine how sleep disorders influence lipid profile and insulin sensitivity in T1D patients.
Materials and methods
This was a cross-sectional study at a public university hospital. Demographic information and medical histories...
Citations
... Understanding the influence of OSA on urinary profiles is important as molecular research in OSA may increase our understanding of complex sleep mechanisms and provide a platform for future therapeutic interventions [31]. For example, in recent years, genomic studies have been performed to identify susceptibility and candidate genes for OSA [32]. ...
Background
Obstructive sleep apnoea (OSA) is a common complication of obesity and can have a substantial negative impact on a patient's quality of life and risk of cardiovascular disease. The aim of this case-control study was to undertake discovery profiling of urinary peptides using capillary electrophoresis-mass spectrometry (CE-MS) in obese subjects with and without obstructive sleep apnoea, without a history of coronary artery disease.Methods
Urinary samples were analysed by CE-MS. Body composition and blood pressure measurements were recorded. Overnight polysomnography was conducted to confirm or refute OSA. OSA patients were naïve to continuous positive airway pressure treatment.ResultsSixty-one subjects with OSA (age 47±9years, BMI 43±8kg/m2) and 31 controls (age 49±10years, BMI 40±5kg/m2) were studied; p=ns for age and BMI. Apnoea-hypopnoea Index was higher in patients with OSA (24±18.6) than controls without OSA (non-OSA) (2.6±1.1; p<0.0001). Metabolic syndrome was present in 35 (57%) of those with OSA compared with 4 (13%) of controls (p<0.0001). 24 polypeptides were candidates for differential distribution (p<0.01), although these differences did not reach significance after multiple testing. Sequences were determined for 8 peptides demonstrating origins from collagens and fibrinogen alpha.Conclusion
In this study, we report for the first time, urinary proteomic profile analyses using CE-MS in OSA and non-OSA obese groups. The differences in urinary proteomic profiles prior to adjustment for multiple testing, with increased metabolic syndrome in obese OSA subjects, suggests that there may be a role for CE-MS in characterising urinary profiles in severely obese populations with OSA.This article is protected by copyright. All rights reserved.
Parasomnia is a broad term used to describe various disruptive sleep-related disorders characterized by abnormal behavioral or physiological events occurring in association with sleep, specific sleep stages, or sleep–wake transitions. Some common parasomnias include confusional arousals, sleepwalking (somnambulism), sleep terrors, sleep talking (somniloquy), nightmares, recurrent isolated sleep paralysis, rapid eye movement (REM) sleep behavior disorder (RBD), sleep enuresis (bedwetting), and sleep bruxism.
Several studies on parasomnias have suggested a genetic background, postulated many years ago based on twin family heredity studies. Parasomnias in childhood are common, and often more frequent than in adults. A few molecular genetic approaches analyzed the association with the HLA system. For sleep walking and REM behavior disorder an association with the HLA system was shown.
This report seeks to establish the prevalence of sleep apnea in patients with the fragile X mental retardation 1 (FMR1) premutation with and without fragile X-associated tremor/ataxia syndrome (FXTAS) and to determine any correlation between CGG repeat and FMR1 mRNA levels with sleep apnea prevalence. Demographic and medical data from 430 (229 males, 201 females) participants were used in this analysis. Participants included premutation carriers with (n = 118) and without FXTAS (n = 174) as well as controls without the premutation (n = 123). Logistic regression models were employed to estimate the odds ratio of sleep apnea relative to controls, adjusted for age and gender, and also to examine potential association with CGG size and FMR1 mRNA expression level. The observed proportion of sleep apnea in premutation carriers with and without FXTAS and controls are 31.4% (37/118), 8.6% (15/174), and 13.8% (17/123), respectively. The adjusted odds of sleep apnea for premutation carriers with FXTAS is about 3.4 times that compared to controls (odds ratio, OR = 3.4, 95% confidence interval (CI) 1.8-7.4; P = 0.001), and similarly relative to premutation carriers without FXTAS (OR = 2.9, 95% CI 1.2-6.9; P = 0.014). The risk of sleep apnea was not different between controls and premutation carriers without FXTAS. The presence of sleep apnea is not associated with CGG repeat numbers nor FMR1 mRNA expression level among premutation carriers. Our data supports a higher prevalence and risk of sleep apnea in patients with FXTAS. We recommend that all patients diagnosed with FXTAS be screened for sleep apnea given the negative and perhaps accelerative impact sleep apnea may have on their FXTAS progression.
