Fingerprinting-based metabolomic approach with LC-MS to sleep apnea and hypopnea syndrome: a pilot study

Changes in human sweat metabolome conditioned by severity of obstructive sleep apnea and intermittent hypoxemia

Obstructive sleep apnea (OSA) is a sleep disorder that has been associated with the incidence of other pathologies. Diagnosis is mainly based on the apnea-hypopnea index (AHI) obviating other repercussions such as intermittent hypoxemia, which has been found to be associated to cardiovascular complications. Blood-based samples and urine have been the most utilised biofluids in metabolomics studies related to OSA, while sweat could be an alternative due to its non-invasive and accessible sampling, its reduced complexity, and comparability with other biofluids. Therefore, this research aimed to evaluate metabolic overnight changes in sweat collected from patients with OSA classified according to the AHI and oxygen desaturation index (ODI), looking for potential cardiovascular repercussions. Pre- and post-sleeping sweat samples from all individuals (n = 61) were analysed by gas chromatography coupled to high-resolution mass spectrometry after appropriate sample preparation to detect as many metabolites as possible. Permanent significant alterations in the sweat were reported for pyruvate, serine, lactose, and hydroxybutyrate. The most relevant overnight metabolic alterations in sweat were reported for lactose, succinate, urea, and oxoproline, which presented significantly different effects on factors such as the AHI and ODI for OSA severity classification. Overall metabolic alterations mainly affected energy production-related processes, nitrogen metabolism, and oxidative stress. In conclusion, this research demonstrated the applicability of sweat for evaluation of OSA diagnosis and severity supported by the detected metabolic changes during sleep.

Effects of obstructive sleep apnea on myocardial injury and dysfunction: a review focused on the molecular mechanisms of intermittent hypoxia

Obstructive sleep apnea (OSA) is characterized by intermittent hypoxia (IH) and is strongly associated with adverse cardiovascular outcomes. Myocardial injury and dysfunction have been commonly observed in clinical practice, particularly in patients with severe OSA. However, the underlying mechanisms remain obscure. In this review, we summarized the molecular mechanisms by which IH impact on myocardial injury and dysfunction. In brief, IH-induced cardiomyocyte death proceeds through the regulation of multiple biological processes, including differentially expressed transcription factors, alternative epigenetic programs, and altered post-translational modification. Besides cell death, various cardiomyocyte injuries, such as endoplasmic reticulum stress, occurs with IH. In addition to the direct effects on cardiomyocytes, IH has been found to deteriorate myocardial blood and energy supply by affecting the microvascular structure and disrupting glucose and lipid metabolism. For better diagnosis and treatment of OSA, further studies on the molecular mechanisms of IH-induced myocardial injury and dysfunction are essential.

Hyperfructosemia in sleep disordered breathing: metabolome analysis of Nagahama study

Sleep disordered breathing (SDB), mainly obstructive sleep apnea (OSA), constitutes a major health problem due to the large number of patients. Intermittent hypoxia caused by SDB induces alterations in metabolic function. Nevertheless, metabolites characteristic for SDB are largely unknown. In this study, we performed gas chromatography-mass spectrometry-based targeted metabolome analysis using data from The Nagahama Study (n = 6373). SDB-related metabolites were defined based on their variable importance score in orthogonal partial least squares discriminant analysis and fold changes in normalized peak-intensity levels between moderate-severe SDB patients and participants without SDB. We identified 20 metabolites as SDB-related, and interestingly, these metabolites were frequently included in pathways related to fructose. Multivariate analysis revealed that moderate-severe SDB was a significant factor for increased plasma fructose levels (β = 0.210, P = 0.006, generalized linear model) even after the adjustment of confounding factors. We further investigated changes in plasma fructose levels after continuous positive airway pressure (CPAP) treatment using samples from patients with OSA (n = 60) diagnosed by polysomnography at Kyoto University Hospital, and found that patients with marked hypoxemia exhibited prominent hyperfructosemia and their plasma fructose levels lowered after CPAP treatment. These data suggest that hyperfructosemia is the abnormality characteristic to SDB, which can be reduced by CPAP treatment.

Obstructive sleep apnea and metabolic syndrome

Metabolic syndrome (MS) is a heterogeneous condition associated with increased cardiovascular risk. There is growing evidence from experimental, translational, and clinical investigations that has suggested that obstructive sleep apnea (OSA) is associated with prevalent and incident components of MS and MS itself. The biological plausibility is supportive, primarily related to one of the main features of OSA, namely intermittent hypoxia: increased sympathetic activation with hemodynamic repercussions, increased hepatic glucose output, insulin resistance through adipose tissue inflammation, pancreatic β-cell dysfunction, hyperlipidemia through the worsening of fasting lipid profiles, and the reduced clearance of triglyceride-rich lipoproteins. Although there are multiple related pathways, the clinical evidence relies mainly on cross-sectional data preventing any causality assumptions. The overlapping presence of visceral obesity or other confounders such as medications challenges the ability to understand the independent contribution of OSA on MS. In this review, we revisit the evidence on how OSA/intermittent hypoxia could mediate adverse effects of MS parameters independent of adiposity. Particular attention is devoted to discussing recent evidence from interventional studies. This review describes the research gaps, the challenges in the field, perspectives, and the need for additional high-quality data from interventional studies addressing the impact of not only established but promising therapies for OSA/obesity.

The association between plasma metabolites and sleep quality in the Southall and Brent Revisited (SABRE) Study: A cross-sectional analysis

We examined the association between plasma metabolites and abnormal sleep patterns using data from the Southall and Brent REvisited (SABRE) cohort. Nuclear magnetic resonance spectroscopy provided 146 circulating plasma metabolites. Sleep questionnaires identified the presence or absence of: difficulty falling asleep, early morning waking, waking up tired, and snoring. Metabolites were compared between the sleep quality categories using the t test, and then filtered using a false discovery rate of 0.05. Generalised linear models with logit-link assessed the associations between filtered metabolites and sleep phenotypes. Adjustment was made for important demographic and health-related covariates. In all, 2,718 participants were included in the analysis. After correcting for multiple testing, three metabolites remained for difficulty falling asleep, 59 for snoring, and none for early morning waking and waking up tired. After adjusting for sex, age, ethnicity and years of education, 1 standard deviation increase in serum histidine and valine associated with lower odds of difficulty falling asleep by 0.89-0.90 (95% confidence intervals [CIs] 0.80-0.99). Branched-chain and aromatic amino acids (odds ratios [ORs] 1.19-1.25, 95% CIs 1.09-1.36) were positively associated with snoring. Total cholesterol in low-density lipoprotein (OR 0.90, 95% CI 0.83-0.97) and high-density lipoprotein (OR 0.88, 95% CI 0.81-0.95) associated with lower odds of snoring. In the fully adjusted model, most associations persisted. To conclude, histidine and valine associated with lower odds of difficulty falling asleep, while docosahexaenoic acid and cholesterol in low-density lipoprotein and high-density lipoprotein subfractions associated with lower odds of snoring. Identified metabolites could provide guidance on the metabolic pathways associated with adverse sleep quality.

Untargeted Metabolomic Profiling of Liver in a Chronic Intermittent Hypoxia Mouse Model

Obstructive sleep apnea (OSA) has been demonstrated to be associated with liver injury. Nevertheless, the mechanisms linking the two disorders remain largely unexplored to date. Based on UHPLC/Q-TOF MS platform, the present study aimed to study the hepatic metabolomic profiling in a chronic intermittent hypoxia (CIH) mouse model to identify altered metabolites and related metabolic pathways. C57BL/6 Mice (n = 12 each group) were exposed to intermittent hypoxia or control conditions (room air) for 12 weeks. At the end of the exposure, liver enzymes and histological changes were assessed. Untargeted metabolomics approach by UHPLC/Q-TOF MS and orthogonal partial least squares-discriminant analysis (OPLS-DA) were applied to screen altered metabolites in mice liver. Bioinformatics analyses were applied to identify the related metabolic pathways. CIH treatment caused a remarkable liver injury in mice. A total of 27 differential metabolites in negative ion mode and 44 in positive ion mode were identified between the two groups. These metabolites were correlated to multiple biological and metabolic processes, including various amino acid metabolism, membrane transport, lipid metabolism, carbohydrate metabolism, nucleotide metabolism, ferroptosis, etc. three differential metabolites including glutathione, glutathione disulfide, arachidonic acid (peroxide free) were identified in the ferroptosis pathway. CIH was associated with a significant metabolic profiling change in mice liver. The metabolites in amino acid metabolism, membrane transport, lipid metabolism, carbohydrate metabolism, nucleotide metabolism, and ferroptosis played an important role in CIH-induced liver injury. These findings contribute to a better understanding of the mechanisms linking OSA and liver injury and help identify potential therapeutic targets.

A review of the "OMICS" for management of patients with obstructive sleep apnoea

Obstructive sleep apnaea (OSA) syndrome is a condition characterised by the presence of complete or partial collapse of the upper airways during sleep, resulting in fragmentation of sleep associated with rapid episodes of intermittent hypoxia (IH), activation of the sympathetic nervous system and oxidative stress. OSA is associated with a broad spectrum of cardiovascular, metabolic and neurocognitive comorbidities that appear to be particularly evident in obese patients, while affecting both sexes in a different manner and varying in severity according to gender and age. In recent years, studies on OSA have increased considerably, but in clinical practice, it is still a highly underdiagnosed disease. To date, the gold standard for the diagnosis of OSA is nocturnal polysomnography (PSG). However, since it is not well suited for a large number of patients, the Home Sleep Test (HST) is also an accepted diagnostic method. Currently, the major aim of research is to identify non-invasive methods to achieve a highly predictive, non-invasive screening system for these subjects. The most recent reports indicate that research in this field has made significant progress in identifying possible biomarkers in OSA, using -OMIC approaches, particularly in the fields of proteomics and metabolomics. In this review, we analyse these OMIC biomarkers found in the literature.

Metabolomic profile associated with obstructive sleep apnoea severity in obese pregnant women with gestational diabetes mellitus: A pilot study

Obstructive sleep apnoea (OSA) is prevalent in obese women with gestational diabetes mellitus (GDM). The present pilot study explored associations between OSA severity and metabolites in women with GDM. A total of 81 obese women with diet-controlled GDM had OSA assessment (median gestational age [GA] 29 weeks). The metabolic profile was assayed from fasting serum samples via liquid chromatography-mass spectrometry (LC-MS) using an untargeted approach. Metabolites were extracted and subjected to an Agilent 1,290 UPLC coupled to an Agilent 6,545 quadrupole time-of-flight (Q-TOF) MS. Data were acquired using electrospray ionisation in positive and negative ion modes. The raw LC-MS data were processed using the OpenMS toolkit to detect and quantify features, and these features were annotated using the Human Metabolite Database. The feature data were compared with OSA status, apnea-hypopnea index (AHI), body mass index (BMI) and GA using "limma" in R. Correlation analyses of the continuous covariates were performed using Kendall's Tau test. The p values were adjusted for multiple testing using the Benjamini-Hochberg false discovery rate correction. A total of 42 women (51.8%) had OSA, with a median AHI of 9.1 events/hr. There were no significant differences in metabolomics profiles between those with and without OSA. However, differential analyses modelling in GA and BMI found 12 features that significantly associated with the AHI. These features could be annotated to oestradiols, lysophospholipids, and fatty acids, with higher levels related to higher AHI. Metabolites including oestradiols and phospholipids may be involved in pathogenesis of OSA in pregnant women with GDM. A targeted approach may help elucidate our understanding of their role in OSA in this population.

Hippocampal Sector-Specific Metabolic Profiles Reflect Endogenous Strategy for Ischemia-Reperfusion Insult Resistance

The gerbil is a well-known model for studying cerebral ischemia. The CA1 of the hippocampus is vulnerable to 5 min of ischemia, while the CA2–4 and dentate gyrus (DG) are resistant to it. Short-lasting ischemia, a model of transient ischemic attacks in men, results in CA1 neuron death within 2–4 days of reperfusion. Untargeted metabolomics, using LC-QTOF-MS, was used to enrich the knowledge about intrinsic vulnerability and resistance of hippocampal regions and their early post-ischemic response (IR). In total, 30 significant metabolites were detected. In controls, taurine was significantly lower and guanosine monophosphate was higher in CA1, as compared to that in CA2–4,DG. LysoPG and LysoPE were more abundant in CA1, while LysoPI 18:0 was detected only in CA2–4,DG. After IR, a substantial decrease in the citric acid level in CA1, an accumulation of pipecolic acid in both regions, and opposite changes in the amount of PE and LysoPE were observed. The following metabolic pathways were identified as being differentially active in control CA1 vs. CA2–4,DG: metabolism of taurine and hypotaurine, glycerophospholipid, and purine. These results may indicate that a regulation of cell volume, altered structure of cell membranes, and energy metabolism differentiate hippocampal regions. Early post-ischemia, spatial differences in the metabolism of aminoacyl-tRNA biosynthesis, and amino acids and their metabolites with a predominance of those which upkeep their well-being in CA2–4,DG are shown. Presented results are consistent with genetic, morphological, and functional data, which may be useful in further study on endogenous mechanisms of neuroprotection and search for new targets for therapeutic interventions.

Metabolomics in Sleep, Insomnia and Sleep Apnea

Sleep-wake disorders are highly prevalent disorders, which can lead to negative effects on cognitive, emotional and interpersonal functioning, and can cause maladaptive metabolic changes. Recent studies support the notion that metabolic processes correlate with sleep. The study of metabolite biomarkers (metabolomics) in a large-scale manner offers unique opportunities to provide insights into the pathology of diseases by revealing alterations in metabolic pathways. This review aims to summarize the status of metabolomic analyses-based knowledge on sleep disorders and to present knowledge in understanding the metabolic role of sleep in psychiatric disorders. Overall, findings suggest that sleep-wake disorders lead to pronounced alterations in specific metabolic pathways, which might contribute to the association of sleep disorders with other psychiatric disorders and medical conditions. These alterations are mainly related to changes in the metabolism of branched-chain amino acids, as well as glucose and lipid metabolism. In insomnia, alterations in branched-chain amino acid and glucose metabolism were shown among studies. In obstructive sleep apnea, biomarkers related to lipid metabolism seem to be of special importance. Future studies are needed to examine severity, subtypes and treatment of sleep-wake disorders in the context of metabolite levels.

Targeted Metabolomics Analysis on Obstructive Sleep Apnea Patients after Multilevel Sleep Surgery

BACKGROUND

Obstructive sleep apnea (OSA) is caused by partial or complete obstruction of the upper airways. Corrective surgeries aim at removing obstructions in the nasopharynx, oropharynx, and hypopharynx. OSA is associated with an increased risk of various metabolic diseases. Our objective was to evaluate the effect of surgery on the plasma metabolome.

METHODS

This study included 39 OSA patients who underwent Multilevel Sleep Surgery (MLS). Clinical and anthropometric measures were taken at baseline and five months after surgery.

RESULTS

The mean Apnea-Hypopnea Index (AHI) significantly dropped from 22.0 ± 18.5 events/hour to 8.97 ± 9.57 events/hour (p-Value < 0.001). Epworth's sleepiness Score (ESS) dropped from 12.8 ± 6.23 to 2.95 ± 2.40 (p-Value < 0.001), indicating the success of the surgery in treating OSA. Plasma levels of metabolites, phosphocholines (PC) PC.41.5, PC.42.3, ceremide (Cer) Cer.44.0, and triglyceride (TG) TG.53.6, TG.55.6 and TG.56.8 were decreased (p-Value < 0.05), whereas lysophosphatidylcholines (LPC) 20.0 and PC.39.3 were increased (p-Value < 0.05) after surgery.

CONCLUSION

This study highlights the success of MLS in treating OSA. Treatment of OSA resulted in an improvement of the metabolic status that was characterized by decreased TG, PCs, and Cer metabolites after surgery, indicating that the success of the surgery positively impacted the metabolic status of these patients.

Circadian and Sleep Metabolomics Across Species

Under normal circadian function, metabolic control is temporally coordinated across tissues and behaviors with a 24-h period. However, circadian disruption results in negative consequences for metabolic homeostasis including energy or redox imbalances. Yet, circadian disruption has become increasingly prevalent within today's society due to many factors including sleep loss. Metabolic consequences of both have been revealed by metabolomics analyses of circadian biology and sleep. Specifically, two primary analytical platforms, mass spectrometry and nuclear magnetic resonance spectroscopy, have been used to study molecular clock and sleep influences on overall metabolic rhythmicity. For example, human studies have demonstrated the prevalence of metabolic rhythms in human biology, as well as pan-metabolome consequences of sleep disruption. However, human studies are limited to peripheral metabolic readouts primarily through minimally invasive procedures. For further tissue- and organism-specific investigations, a number of model systems have been studied, based upon the conserved nature of both the molecular clock and sleep across species. Here we summarize human studies as well as key findings from metabolomics studies using mice, Drosophila, and zebrafish. While informative, a limitation in existing literature is a lack of interpretation regarding dynamic synthesis or catabolism within metabolite pools. To this extent, future work incorporating isotope tracers, specific metabolite reporters, and single-cell metabolomics may provide a means of exploring dynamic activity in pathways of interest.

Habitual sleep quality, plasma metabolites and risk of coronary heart disease in post-menopausal women

BACKGROUND

Epidemiologic studies suggest a strong link between poor habitual sleep quality and increased cardiovascular disease risk. However, the underlying mechanisms are not entirely clear. Metabolomic profiling may elucidate systemic differences associated with sleep quality that influence cardiometabolic health.

METHODS

We explored cross-sectional associations between sleep quality and plasma metabolites in a nested case-control study of coronary heart disease (CHD) in the Women's Health Initiative (WHI; n = 1956) and attempted to replicate the results in an independent sample from the Nurses' Health Study II (NHSII; n = 209). A sleep-quality score (SQS) was derived from self-reported sleep problems asked in both populations. Plasma metabolomics were assayed using LC-MS with 347 known metabolites. General linear regression was used to identify individual metabolites associated with continuous SQS (false-discovery rate <0.05). Using least absolute shrinkage and selection operator (LASSO) algorithms, a metabolite score was created from replicated metabolites and evaluated with CHD risk in the WHI.

RESULTS

After adjusting for age, race/ethnicity, body mass index (BMI) and smoking, we identified 69 metabolites associated with SQS in the WHI (59 were lipids). Of these, 16 were replicated in NHSII (15 were lipids), including 6 triglycerides (TAGs), 4 phosphatidylethanolamines (PEs), 3 phosphatidylcholines (PCs), 1 diglyceride (DAG), 1 lysophosphatidylcholine and N6-acetyl-L-lysine (a product of histone acetylation). These metabolites were consistently higher among women with poorer sleep quality. The LASSO selection resulted in a nine-metabolite score (TAGs 45: 1, 48: 1, 50: 4; DAG 32: 1; PEs 36: 4, 38: 5; PCs 30: 1, 40: 6; N6-acetyl-L-lysine), which was positively associated with CHD risk (odds ratio per SD increase in the score: 1.16; 95% confidence interval: 1.05, 1.28; p = 0.0003) in the WHI after adjustment for matching factors and conventional CHD risk factors.

CONCLUSIONS

Differences in lipid metabolites may be an important pathogenic pathway linking poor habitual sleep quality and CHD risk.

Metabolism of sleep and aging: Bridging the gap using metabolomics

Sleep is a conserved behavior across the evolutionary timescale. Almost all known animal species demonstrate sleep or sleep like states. Despite extensive study, the mechanistic aspects of sleep need are not very well characterized. Sleep appears to be needed to generate resources that are utilized during the active stage/wakefulness as well as clearance of waste products that accumulate during wakefulness. From a metabolic perspective, this means sleep is crucial for anabolic activities. Decrease in anabolism and build-up of harmful catabolic waste products is also a hallmark of aging processes. Through this lens, sleep and aging processes are remarkably parallel- for example behavioral studies demonstrate an interaction between sleep and aging. Changes in sleep behavior affect neurocognitive phenotypes important in aging such as learning and memory, although the underlying connections are largely unknown. Here we draw inspiration from the similar metabolic effects of sleep and aging and posit that large scale metabolic phenotyping, commonly known as metabolomics, can shed light to interleaving effects of sleep, aging and progression of diseases related to aging. In this review, data from recent sleep and aging literature using metabolomics as principal molecular phenotyping methods is collated and compared. The present data suggests that metabolic effects of aging and sleep also demonstrate similarities, particularly in lipid metabolism and amino acid metabolism. Some of these changes also overlap with metabolomic data available from clinical studies of Alzheimer's disease. Together, metabolomic technologies show promise in elucidating interleaving effects of sleep, aging and progression of aging disorders at a molecular level.

Pediatric Obstructive Sleep Apnea is Associated With Changes in the Oral Microbiome and Urinary Metabolomics Profile: A Pilot Study

STUDY OBJECTIVES

Several cross-sectional studies have reported associations between oral diseases and obstructive sleep apnea (OSA). However, there have been no reports regarding the structure and composition of the oral microbiota with simultaneous evaluation of potential associations with perturbed metabolic profiles in pediatric OSA.

METHODS

An integrated approach, combining metagenomics based on high-throughput 16S rRNA gene sequencing, and metabolomics based on ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry and gas chromatography coupled with time-of-flight mass spectrometry, was used to evaluate the oral microbiome and the urinary metabolome.

RESULTS

16S rRNA gene sequencing indicated that the oral microbiome composition was significantly perturbed in pediatric OSA compared with normal controls, especially with regard to Firmicutes, Proteobacteria, Bacteroidetes, Fusobacteria, and Actinobacteria. Moreover, metabolomics profiling indicated that 57 metabolites, 5 of which were metabolites related to the microflora of the digestive tract, were differentially present in the urine of pediatric patients with OSA and controls. Co-inertia and correlation analyses revealed that several oral microbiome changes were correlated with urinary metabolite perturbations in pediatric OSA. However, this correlation relationship does not imply causality.

CONCLUSIONS

High-throughput sequencing revealed that the oral microbiome composition and function were significantly altered in pediatric OSA. Further studies are needed to confirm and determine the mechanisms underlying these findings.

Metabolomic and lipidomic profile in men with obstructive sleep apnoea: implications for diagnosis and biomarkers of cardiovascular risk

The use of metabolomic and lipidomic strategies for selecting potential biomarkers for obstructive sleep apnoea (OSA) has been little explored. We examined adult male patients with OSA (defined by an apnoea-hypopnoea index ≥15 events/hour), as well as age-, gender-, and fat-composition-matched volunteers without OSA. All subjects were subjected to clinical evaluation, sleep questionnaires for detecting the risk of OSA (Berlin and NoSAS score), metabolomic analysis by gas chromatography coupled to mass spectrometry and lipidomic analysis with liquid chromatography followed by detection by MALDI-MS. This study included 37 patients with OSA and 16 controls. From the 6 metabolites and 22 lipids initially selected, those with the best association with OSA were glutamic acid, deoxy sugar and arachidonic acid (metabolites), and glycerophosphoethanolamines, sphingomyelin and lyso-phosphocholines (lipids). For the questionnaires, the NoSAS score performed best with screening for OSA (area under the curve [AUC] = 0.724, p = 0.003). The combination of the NoSAS score with metabolites or lipids resulted in an AUC for detecting OSA of 0.911 and 0.951, respectively. In conclusion, metabolomic and lipidomic strategies suggested potential early biomarkers in OSA that could also be helpful in screening for this sleep disorder beyond traditional questionnaires.

Metabolomics Profiling for Obstructive Sleep Apnea and Simple Snorers

Few clinical studies have explored altered urinary metabolite levels in patients with obstructive sleep apnea (OSA). Thus, we applied a metabolomics approach to analyze urinary metabolites in three groups of participants: patients with polysomnography (PSG)-confirmed OSA, simple snorers (SS), and normal subjects. Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry and gas chromatography coupled with time-of-flight mass spectrometry were used. A total of 21 and 31 metabolites were differentially expressed in the SS and OSA groups, respectively. Patients with OSA had 18 metabolites different from those with SS. Of the 56 metabolites detected among the 3 groups, 24 were consistently higher or lower. A receiver operator curve analysis revealed that the combination of 4-hydroxypentenoic acid, arabinose, glycochenodeoxycholate-3-sulfate, isoleucine, serine, and xanthine produced a moderate diagnostic score with a sensitivity (specificity) of 75% (78%) for distinguishing OSA from those without OSA. The combination of 4-hydroxypentenoic acid, 5-dihydrotestosterone sulfate, serine, spermine, and xanthine distinguished OSA from SS with a sensitivity of 85% and specificity of 80%. Multiple metabolites and metabolic pathways associated with SS and OSA were identified using the metabolomics approach, and the altered metabolite signatures could potentially serve as an alternative diagnostic method to PSG.

Biological plausibility linking sleep apnoea and metabolic dysfunction

Obstructive sleep apnoea (OSA) is a very common disorder that affects 10-25% of the general population. In the past two decades, OSA has emerged as a cardiometabolic risk factor in both paediatric and adult populations. OSA-induced metabolic perturbations include dyslipidaemia, atherogenesis, liver dysfunction and abnormal glucose metabolism. The mainstay of treatment for OSA is adenotonsillectomy in children and continuous positive airway pressure therapy in adults. Although these therapies are effective at resolving the sleep-disordered breathing component of OSA, they do not always produce beneficial effects on metabolic function. Thus, a deeper understanding of the underlying mechanisms by which OSA influences metabolic dysfunction might yield improved therapeutic approaches and outcomes. In this Review, we summarize the evidence obtained from animal models and studies of patients with OSA of potential mechanistic pathways linking the hallmarks of OSA (intermittent hypoxia and sleep fragmentation) with metabolic dysfunction. Special emphasis is given to adipose tissue dysfunction induced by sleep apnoea, which bears a striking resemblance to adipose dysfunction resulting from obesity. In addition, important gaps in current knowledge and promising lines of future investigation are identified.

Diagnostic capability of biological markers in assessment of obstructive sleep apnea: a systematic review and meta-analysis

OBJECTIVE

The purpose of this systematic review is to evaluate the diagnostic value of biological markers (exhaled breath condensate, blood, salivary and urinary) in the diagnosis of OSA in comparison to the gold standard of nocturnal PSG.

METHODS

Studies that differentiated OSA from controls based on PSG results, without age restriction, were eligible for inclusion. The sample of selected studies could include studies in obese patients and with known cardiac disease. A detailed individual search strategy for each of the following bibliographic databases was developed: Cochrane, EMBASE, MEDLINE, PubMed, and LILACS. The references cited in these articles were also crosschecked and a partial grey literature search was undertaken using Google Scholar. The methodology of selected studies was evaluated using the 14-item Quality Assessment Tool for Diagnostic Accuracy Studies.

RESULTS

After a two-step selection process, nine articles were identified and subjected to qualitative and quantitative analyses. Among them, only one study conducted in children and one in adults found biomarkers that exhibit sufficiently satisfactory diagnostic accuracy that enables application as a diagnostic method for OSA.

CONCLUSION

Kallikrein-1, uromodulin, urocotin-3, and orosomucoid-1 when combined have enough accuracy to be an OSA diagnostic test in children. IL-6 and IL-10 plasma levels have potential to be good biomarkers in identifying or excluding the presence of OSA in adults.

Fusion of the 1H NMR data of serum, urine and exhaled breath condensate in order to discriminate chronic obstructive pulmonary disease and obstructive sleep apnea syndrome

Chronic obstructive pulmonary disease, COPD, affects the condition of the entire human organism and causes multiple comorbidities. Pathological lung changes lead to quantitative changes in the composition of the metabolites in different body fluids. The obstructive sleep apnea syndrome, OSAS, occurs in conjunction with chronic obstructive pulmonary disease in about 10-20 % of individuals who have COPD. Both conditions share the same comorbidities and this makes differentiating them difficult. The aim of this study was to investigate whether it is possible to diagnose a patient with either COPD or the OSA syndrome using a set of selected metabolites and to determine whether the metabolites that are present in one type of biofluid (serum, exhaled breath condensate or urine) or whether a combination of metabolites that are present in two biofluids or whether a set of metabolites that are present in all three biofluids are necessary to correctly diagnose a patient. A quantitative analysis of the metabolites in all three biofluid samples was performed using ¹H NMR spectroscopy. A multivariate bootstrap approach that combines partial least squares regression with the variable importance in projection score (VIP-score) and selectivity ratio (SR) was adopted in order to construct discriminant diagnostic models for the groups of individuals with COPD and OSAS. A comparison study of all of the discriminant models that were constructed and validated showed that the discriminant partial least squares model using only ten urine metabolites (selected with the SR approach) has a specificity of 100 % and a sensitivity of 86.67 %. This model (AUC_test = 0.95) presented the best prediction performance. The main conclusion of this study is that urine metabolites, among the others, present the highest probability for correctly identifying patents with COPD and the lowest probability for an incorrect identification of the OSA syndrome as developed COPD. Another important conclusion is that the changes in the metabolite levels of exhaled breath condensates do not appear to be specific enough to differentiate between patients with COPD and OSAS.

Biomarkers associated with obstructive sleep apnea: A scoping review

The overall validity of biomarkers in the diagnosis of obstructive sleep apnea (OSA) remains unclear. We conducted a scoping review to provide assessments of biomarkers characteristics in the context of obstructive sleep apnea (OSA) and to identify gaps in the literature. A scoping review of studies in humans without age restriction that evaluated the potential diagnostic value of biological markers (blood, exhaled breath condensate, salivary, and urinary) in the OSA diagnosis was undertaken. Retained articles were those focused on the identification of biomarkers in subjects with OSA, the latter being confirmed with a full overnight or home-based polysomnography (PSG). Search strategies for six different databases were developed. The methodology of selected studies was classified using an adaptation of the evidence quality criteria from the American Academy of Pediatrics. Additionally the biomarkers were classified according to their potential clinical application. We identified 572 relevant studies, of which 117 met the inclusion criteria. Eighty-two studies were conducted in adults, 34 studies involved children, and one study had a sample composed of both adults and children. Most of the studies evaluated blood biomarkers. Potential diagnostic biomarkers were found in nine pediatric studies and in 58 adults studies. Only nine studies reported sensitivity and specificity, which varied substantially from 43% to 100%, and from 45% to 100%, respectively. Studies in adults have focused on the investigation of IL-6, TNF-α and hsCRP. There was no specific biomarker that was tested by a majority of authors in pediatric studies, and combinatorial urine biomarker approaches have shown preliminary promising results. In adults IL-6 and IL-10 seem to have a favorable potential to become a good biomarker to identify OSA.