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

Association between human blood metabolome and risk of myocarditis: a mendelian randomization study

Myocarditis is a common disease of the cardiovascular and immune systems, but the relationship between relevant blood metabolites and the risk of myocarditis has not been well-established. To identify potential biometabolic markers associated with myocarditis, we conducted a two-sample Mendelian randomization (MR) study. We performed preliminary MR analysis using the inverse variance weighted (IVW) method, supplemented by MR-Egger, weighted median, and weighted mode methods to adjust for false discovery rate (FDR). Confounders were screened using the GWAS Catalog website. Sensitivity analyses included Cochrane Q-test, Egger regression, Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO), scatterplots, funnel plots, and forest plots. For genetic and directional analysis, we employed co-localization analysis and the Steiger test. MR analysis was performed using the FinnGen database and meta-analysis was performed using the IEU database. MR analysis identified significant correlations for five metabolic biomarkers after FDR correction. These included four known metabolites: kynurenine, 1-stearoyl-GPE (18:0), deoxycarnitine, and 5-acetylamino-6-formylamino-3-methyluracil, as well as one unknown metabolite, X-25,422. Among these, kynurenine (OR = 1.441, 95%CI = 1.089-1.906, p-value = 0.018) and 1-stearoyl-GPE (18:0) (OR = 1.263, 95%CI = 1.029-1.550, p-value = 0.029) were identified as risk factors for myocarditis, while deoxycarnitine (OR = 0.813, 95%CI = 0.676-0.979, p-value = 0.029), 5-acetylamino-6-formylamino-3-methyluracil (OR = 0.864, 95% CI = 0.775-0.962, p-value = 0.018), and X-25,422 (OR = 0.721, 95%CI = 0.587-0.886, p-value = 0.009) were found to be protective factors. No evidence of heterogeneity, horizontal pleiotropy, or sensitivity issues was observed, and no shared genetic factors between exposure and outcome were detected. The causality was in the correct direction. Meta-analysis further confirmed the causal relationship between the five metabolites and myocarditis. This study identifies a causal relationship between five circulating metabolites and myocarditis. Kynurenine, 1-stearoyl-GPE (18:0), deoxycarnitine, X-25,422, and 5-acetylamino-6-formylamino-3-methyluracil may serve as potential drug targets for myocarditis, providing a theoretical basis for the prevention, diagnosis, and treatment of the condition.

Untargeted Metabolome Atlas for Sleep Phenotypes in the Hispanic Community Health Study/Study of Latinos

Sleep is essential to maintaining health and wellbeing of individuals, influencing a variety of outcomes from mental health to cardiometabolic disease. This study aims to assess the relationships between various sleep phenotypes and blood metabolites. Utilizing data from the Hispanic Community Health Study/Study of Latinos, we performed association analyses between 40 sleep phenotypes, grouped in several domains (i.e., sleep disordered breathing (SDB), sleep duration, timing, insomnia symptoms, and heart rate during sleep), and 768 metabolites measured via untargeted metabolomics profiling. Network analysis was employed to visualize and interpret the associations between sleep phenotypes and metabolites. The patterns of statistically significant associations between sleep phenotypes and metabolites differed by superpathways, and highlighted subpathways of interest for future studies. For example, some xenobiotic metabolites were associated with sleep duration and heart rate phenotypes (e.g. 1H-indole-7-acetic acid, 4-allylphenol sulfate), while ketone bodies and fatty acid metabolism metabolites were associated with sleep timing measures (e.g. 3-hydroxybutyrate (BHBA), 3-hydroxyhexanoylcarnitine (1)). Heart rate phenotypes had the overall largest number of detected metabolite associations. Many of these associations were shared with both SDB and with sleep timing phenotypes, while SDB phenotypes shared relatively few metabolite associations with sleep duration measures. A number of metabolites were associated with multiple sleep phenotypes, from a few domains. The amino acids vanillylmandelate (VMA) and 1-carboxyethylisoleucine were associated with the greatest number of sleep phenotypes, from all domains other than insomnia. This atlas of sleep-metabolite associations will facilitate hypothesis generation and further study of the metabolic underpinnings of sleep health.

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.

Circulating metabolic markers after surgery identify patients at risk for severe postoperative complications: a prospective cohort study in colorectal cancer

BACKGROUND

Early detection of postoperative complications after colorectal cancer (CRC) surgery is associated with improved outcomes. The aim was to investigate early metabolomics signatures capable to detect patients at risk for severe postoperative complications after CRC surgery.

MATERIALS AND METHODS

Prospective cohort study of patients undergoing CRC surgery from 2015 to 2018. Plasma samples were collected before and after surgery, and analyzed by mass spectrometry obtaining 188 metabolites and 21 ratios. Postoperative complications were registered with Clavien-Dindo Classification and Comprehensive Complication Index.

RESULTS

One hundred forty-six patients were included. Surgery substantially modified metabolome and metabolic changes after surgery were quantitatively associated with the severity of postoperative complications. The strongest positive relationship with both Clavien-Dindo and Comprehensive Complication Index (β=4.09 and 63.05, P <0.001) corresponded to kynurenine/tryptophan, against an inverse relationship with lysophosphatidylcholines (LPCs) and phosphatidylcholines (PCs). Patients with LPC18:2/PCa36:2 below the cut-off 0.084 µM/µM resulted in a sevenfold higher risk of major complications (OR=7.38, 95% CI: 2.82-21.25, P <0.001), while kynurenine/tryptophan above 0.067 µM/µM a ninefold (OR=9.35, 95% CI: 3.03-32.66, P <0.001). Hexadecanoylcarnitine below 0.093 µM displayed a 12-fold higher risk of anastomotic leakage-related complications (OR=11.99, 95% CI: 2.62-80.79, P =0.004).

CONCLUSION

Surgery-induced phospholipids and amino acid dysregulation is associated with the severity of postoperative complications after CRC surgery, including anastomotic leakage-related outcomes. The authors provide quantitative insight on metabolic markers, measuring vulnerability to postoperative morbidity that might help guide early decision-making and improve surgical outcomes.

Sleep insufficiency, circadian rhythms, and metabolomics: the connection between metabolic and sleep disorders

PURPOSE

US adults who report experiencing insufficient sleep are more likely to suffer from metabolic disorders such as hyperlipidemia, diabetes, and obesity than those with sufficient sleep. Less is understood about the underlying molecular mechanisms connecting these phenomena. A systematic, qualitative review of metabolomics studies exploring metabolic changes in response to sleep insufficiency, sleep deprivation, or circadian disruption was conducted in accordance with PRISMA guidelines.

METHODS

An electronic literature review in the PubMed database was performed considering publications through May 2021 and screening and eligibility criteria were applied to articles retrieved. The following keywords were used: "metabolomics" and "sleep disorders" or "sleep deprivation" or "sleep disturbance" or "circadian rhythm." After screening and addition of studies included from reference lists of retrieved studies, 16 records were identified for review.

RESULTS

Consistent changes in metabolites were observed across studies between individuals experiencing sleep deprivation compared to non-sleep deprived controls. Significant increases in phosphatidylcholines, acylcarnitines, sphingolipids, and other lipids were consistent across studies. Increased levels of amino acids such as tryptophan and phenylalanine were also noted. However, studies were limited to small samples of young, healthy, mostly male participants conducted in short inpatient sessions, limiting generalizability.

CONCLUSION

Changes in lipid and amino acid metabolites accompanying sleep deprivation and/or circadian rhythms may indicate cellular membrane and protein breakdown underlying the connection between sleep disturbance, hyperlipidemia, and other metabolic disorders. Larger epidemiological studies examining changes in the human metabolome in response to chronic insufficient sleep would help elucidate this relationship.

The ZJU index is associated with the risk of obstructive sleep apnea syndrome in Chinese middle-aged and older people: a cross-sectional study

BACKGROUND

The ZJU index, a novel calculation that combines body mass index, triglycerides, fasting blood glucose and the ratio of alanine aminotransferase to aspartate aminotransferase, is a closely related measure of obesity and insulin resistance. Studies of the ZJU index in relation to obstructive sleep apnea syndrome (OSAS) have not been reported. This study assessed the correlation between the ZJU values and OSAS risk.

METHODS

A total of 2,130 participants who underwent polysomnographic monitoring were included in the study. The participants' basic information and laboratory biochemical indicators were collected, and the ZJU index was computed. The ZJU index was divided into quartiles. The correlation between the different ZJU index levels and OSAS risk was assessed using logistic regression. Drew a receiver operating characteristic (ROC) relationship curve, with prediction efficacy judged by the area under the curve (AUC), and found the optimum cut-off point for ZJU index to predict OSAS. Relative risks were presented as odds ratios (OR). The range of OR values is expressed in the form of 95% confidence intervals (95% CI).

RESULTS

The number of patients diagnosed with OSAS increased progressively with increasing ZJU index (T1: 9.4%; T2: 20.6%; T3: 28.3%; T4: 41.7%; P < 0.001). The additional confounders were adjusted by the logistic regression models, the study revealed an independent correlation between ZJU index and OSAS. (P < 0.001). The OSAS risk was notably higher at the highest ZJU index levels. (OR = 2.046 [95% CI: 1.057 to 3.964]). The ROC curve for the ZJU index showed an AUC of 0.64 (P < 0.001) for males and 0.75 (P < 0.001) for females, with a specificity of 64% and 55% and a sensitivity of 60% and 92% for males and females, respectively, with the optimum cut-off values of 36.568 and 34.722, respectively.

CONCLUSION

A high ZJU index was significantly associated with an increasing risk of OSAS. The ZJU is expected to be a meaningful index for detecting OSAS in the general population.

Multi-Omics Analysis of Circulating Exosomes in Adherent Long-Term Treated OSA Patients

Obstructive sleep apnea (OSA) is a highly prevalent chronic disease affecting nearly a billion people globally and increasing the risk of multi-organ morbidity and overall mortality. However, the mechanisms underlying such adverse outcomes remain incompletely delineated. Extracellular vesicles (exosomes) are secreted by most cells, are involved in both proximal and long-distance intercellular communication, and contribute toward homeostasis under physiological conditions. A multi-omics integrative assessment of plasma-derived exosomes from adult OSA patients prior to and after 1-year adherent CPAP treatment is lacking. We conducted multi-omic integrative assessments of plasma-derived exosomes from adult OSA patients prior to and following 1-year adherent CPAP treatment to identify potential specific disease candidates. Fasting morning plasma exosomes isolated from 12 adult patients with polysomnographically-diagnosed OSA were analyzed before and after 12 months of adherent CPAP therapy (mean ≥ 6 h/night) (OSAT). Exosomes were characterized by flow cytometry, transmission electron microscopy, and nanoparticle tracking analysis. Endothelial cell barrier integrity, wound healing, and tube formation were also performed. Multi-omics analysis for exosome cargos was integrated. Exosomes derived from OSAT improved endothelial permeability and dysfunction as well as significant improvement in tube formation compared with OSA. Multi-omic approaches for OSA circulating exosomes included lipidomic, proteomic, and small RNA (miRNAs) assessments. We found 30 differentially expressed proteins (DEPs), 72 lipids (DELs), and 13 miRNAs (DEMs). We found that the cholesterol metabolism (has04979) pathway is associated with lipid classes in OSA patients. Among the 12 subjects of OSA and OSAT, seven subjects had complete comprehensive exosome cargo information including lipids, proteins, and miRNAs. Multi-omic approaches identify potential signature biomarkers in plasma exosomes that are responsive to adherent OSA treatment. These differentially expressed molecules may also play a mechanistic role in OSA-induced morbidities and their reversibility. Our data suggest that a multi-omic integrative approach might be useful in understanding how exosomes function, their origin, and their potential clinical relevance, all of which merit future exploration in the context of relevant phenotypic variance. Developing an integrated molecular classification should lead to improved diagnostic classification, risk stratification, and patient management of OSA by assigning molecular disease-specific therapies.

Cerebrospinal fluid lipidomic fingerprint of obstructive sleep apnoea in Alzheimer's disease

BACKGROUND

Obstructive sleep apnoea (OSA) has a high prevalence in patients with Alzheimer's disease (AD). Both conditions have been shown to be associated with lipid dysregulation. However, the relationship between OSA severity and alterations in lipid metabolism in the brains of patients with AD has yet to be fully elucidated. In this context, we examined the cerebrospinal fluid (CSF) lipidome of patients with suspected OSA to identify potential diagnostic biomarkers and to provide insights into the pathophysiological mechanisms underlying the effect of OSA on AD.

METHODS

The study included 91 consecutive AD patients who underwent overnight polysomnography (PSG) to diagnose severe OSA (apnoea-hypopnea index ≥ 30/h). The next morning, CSF samples were collected and analysed by liquid chromatography coupled to mass spectrometry in an LC-ESI-QTOF-MS/MS platform.

RESULTS

The CSF levels of 11 lipid species were significantly different between AD patients with (N = 38) and without (N = 58) severe OSA. Five lipids (including oxidized triglyceride OxTG(57:2) and four unknown lipids) were significantly correlated with specific PSG measures of OSA severity related to sleep fragmentation and hypoxemia. Our analyses revealed a 4-lipid signature (including oxidized ceramide OxCer(40:6) and three unknown lipids) that provided an accuracy of 0.80 (95% CI: 0.71-0.89) in the detection of severe OSA. These lipids increased the discriminative power of the STOP-Bang questionnaire in terms of the area under the curve (AUC) from 0.61 (0.50-0.74) to 0.85 (0.71-0.93).

CONCLUSIONS

Our results reveal a CSF lipidomic fingerprint that allows the identification of AD patients with severe OSA. Our findings suggest that an increase in central nervous system lipoxidation may be the principal mechanism underlying the association between OSA and AD.

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.

Emerging role of metabolomics for biomarker discovery in obstructive sleep apnea

Obstructive sleep apnea (OSA) is characterized by the complete or partial blockage of the upper airway passage during sleep which causes repetitive breaks in sleep and may result in excessive daytime sleepiness. OSA has been linked to various metabolic disorders and chronic health conditions, such as obesity, diabetes, hypertension, and depression. Profiling of alterations in metabolites and their regulation in OSA has been hypothesized to be an effective approach for early diagnosis and prognosis of OSA. Several studies have characterized metabolic fingerprints associated with sleep disorders. There is a lack of understanding of metabolite contents and their alterations in OSA that may help to identify specific biomarkers. The information provided in this review will help update new methodologies and interventions of high throughput advanced molecular/metabolomics tools which may clarify the metabolic aspects and mechanisms for improved management and treatment of OSA.

Physical fitness, hormonal profile, nutritional and psychological aspects assessment of transgender women volleyball players submitted to physical tests: protocol paper of a prospective cohort

To evaluate aerobic capacity, strength and other physiological, nutritional, and psychological variables which may influence the performance of transgender women (TW) athletes and compare them to cisgender women (CW) and cisgender men (CM) athletes, as well as changes in TW performance over the course of a year. Prospective cohort study including three groups: TW, CW and CM volleyball athletes. Subjects will be comprehensively assessed at two different moments: baseline and after 6-12 months of adequate hormonal therapy. Evaluation will comprise clinical, medical, nutritional and psychological interviews, incremental treadmill cardiopulmonary exercise testing, hand grip strength test, vertical jump test, analysis of sleep quality (Pittsburgh Sleep Quality Index), hormonal profile, echocardiogram, analysis of resting energy expenditure, assessment of bone mass and body composition through dual-energy X-ray absorptiometry scans, and untargeted metabolomic analysis. CW and CM matched by age, body mass index and level of physical activity will undergo a similar evaluation. The assessment of the strength, aerobic capacity, haematological, nutritional and psychological status of TW using gold-standard tests will contribute to understanding the impact of oestrogen therapy on the exercise performance of these athletes and how they compare with CW and CM.

Metabolomic approach for obstructive sleep apnea in adults: a systematic review

Obstructive Sleep Apnea (OSA) corresponds to episodes of complete or partial upper airway obstruction during sleep. The gold standard for diagnosing OSA is polysomnography; however, metabolomics is an innovative and highly sensitive method that seeks to identify and quantify small molecules in biological systems. Identify the metabolites most frequently associated with obstructive sleep apnea in adults. The search for articles was conducted between October 2020 and August 2021, in electronic databases, such as MEDLINE/PubMed, Scielo, Embase, and Cochrane, through the combination of descriptors: obstructive sleep apnea, metabolomic, adult. This systematic review included all cross-sectional studies published, including human patients aged 18 years or older, of both genders who underwent type I or II polysomnography and metabolomics study. The search strategy selected 3697 surveys, and 4 of them were selected to be a part of this systematic review. Based on the analyzed surveys, it was found that all of them were able to diagnose OSA, reaching a sensitivity of 75-97%, and specificity that ranged from 72 to 100%; besides differentiating patients with OSA (severe, moderate, and mild) from simple snorers with a mean sensitivity of 77.2% and specificity of 66.25%. These findings suggest that, in addition to being used as a screening and diagnostic strategy for OSA, metabolomics has the potential to be used for severity stratification and to monitor the disease's progression.

Molecular Pathology, Oxidative Stress, and Biomarkers in Obstructive Sleep Apnea

Obstructive sleep apnea syndrome (OSAS) is characterized by intermittent hypoxia (IH) during sleep due to recurrent upper airway obstruction. The derived oxidative stress (OS) leads to complications that do not only concern the sleep-wake rhythm but also systemic dysfunctions. The aim of this narrative literature review is to investigate molecular alterations, diagnostic markers, and potential medical therapies for OSAS. We analyzed the literature and synthesized the evidence collected. IH increases oxygen free radicals (ROS) and reduces antioxidant capacities. OS and metabolic alterations lead OSAS patients to undergo endothelial dysfunction, osteoporosis, systemic inflammation, increased cardiovascular risk, pulmonary remodeling, and neurological alterations. We treated molecular alterations known to date as useful for understanding the pathogenetic mechanisms and for their potential application as diagnostic markers. The most promising pharmacological therapies are those based on N-acetylcysteine (NAC), Vitamin C, Leptin, Dronabinol, or Atomoxetine + Oxybutynin, but all require further experimentation. CPAP remains the approved therapy capable of reversing most of the known molecular alterations; future drugs may be useful in treating the remaining dysfunctions.

Development and validation of a metabolite index for obstructive sleep apnea across race/ethnicities

Obstructive sleep apnea (OSA) is a common disorder characterized by recurrent episodes of upper airway obstruction during sleep resulting in oxygen desaturation and sleep fragmentation, and associated with increased risk of adverse health outcomes. Metabolites are being increasingly used for biomarker discovery and evaluation of disease processes and progression. Studying metabolomic associations with OSA in a diverse community-based cohort may provide insights into the pathophysiology of OSA. We aimed to develop and replicate a metabolite index for OSA and identify individual metabolites associated with OSA. We studied 219 metabolites and their associations with the apnea hypopnea index (AHI) and with moderate-severe OSA (AHI ≥ 15) in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) (n = 3507) using two methods: (1) association analysis of individual metabolites, and (2) least absolute shrinkage and selection operator (LASSO) regression to identify a subset of metabolites jointly associated with OSA, which was used to develop a metabolite index for OSA. Results were validated in the Multi-Ethnic Study of Atherosclerosis (MESA) (n = 475). When assessing the associations with individual metabolites, we identified seven metabolites significantly positively associated with OSA in HCHS/SOL (FDR p < 0.05), of which four associations-glutamate, oleoyl-linoleoyl-glycerol (18:1/18:2), linoleoyl-linoleoyl-glycerol (18:2/18:2) and phenylalanine, were replicated in MESA (one sided-p < 0.05). The OSA metabolite index, composed of 14 metabolites, was associated with a 50% increased risk for moderate-severe OSA (OR = 1.50 [95% CI 1.21-1.85] per 1 SD of OSA metabolite index, p < 0.001) in HCHS/SOL and 55% increased risk (OR = 1.55 [95% CI 1.10-2.20] per 1 SD of OSA metabolite index, p = 0.013) in MESA, both adjusted for demographics, lifestyle, and comorbidities. Similar albeit less significant associations were observed for AHI. Replication of the metabolite index in an independent multi-ethnic dataset demonstrates the robustness of metabolomic-based OSA index to population heterogeneity. Replicated metabolite associations may provide insights into OSA-related molecular and metabolic mechanisms.

Identification of metabolic fingerprints in severe obstructive sleep apnea using gas chromatography-Mass spectrometry

Objective: Obstructive sleep apnea (OSA) is considered a major sleep-related breathing problem with an increasing prevalence rate. Retrospective studies have revealed the risk of various comorbidities associated with increased severity of OSA. This study aims to identify novel metabolic biomarkers associated with severe OSA. Methods: In total, 50 cases of OSA patients (49.74 ± 11.87 years) and 30 controls (39.20 ± 3.29 years) were included in the study. According to the polysomnography reports and questionnaire-based assessment, only patients with an apnea-hypopnea index (AHI >30 events/hour) exceeding the threshold representing severe OSA patients were considered for metabolite analysis. Plasma metabolites were analyzed using gas chromatography-mass spectrometry (GC-MS). Results: A total of 92 metabolites were identified in the OSA group compared with the control group after metabolic profiling. Metabolites and their correlated metabolic pathways were significantly altered in OSA patients with respect to controls. The fold-change analysis revealed markers of chronic kidney disease, cardiovascular risk, and oxidative stress-like indoxyl sulfate, 5-hydroxytryptamine, and 5-aminolevulenic acid, respectively, which were significantly upregulated in OSA patients. Conclusion: Identifying these metabolic signatures paves the way to monitor comorbid disease progression due to OSA. Results of this study suggest that blood plasma-based biomarkers may have the potential for disease management.

Blood-based lipidomic signature of severe obstructive sleep apnoea in Alzheimer's disease

Background

Obstructive sleep apnoea (OSA) is the most frequent form of sleep-disordered breathing in patients with Alzheimer’s disease (AD). Available evidence demonstrates that both conditions are independently associated with alterations in lipid metabolism. However, it is unknown whether the expression of lipids is different between AD patients with and without severe OSA. In this context, we examined the plasma lipidome of patients with suspected OSA, aiming to identify potential diagnostic biomarkers and to provide insights into the pathophysiological mechanisms underlying the disease.

Methods

The study included 103 consecutive patients from the memory unit of our institution with a diagnosis of AD. The individuals were subjected to overnight polysomnography (PSG) to diagnose severe OSA (apnoea-hypopnea index ≥30/h), and blood was collected the following morning. Untargeted plasma lipidomic profiling was performed using liquid chromatography coupled with mass spectrometry.

Results

We identified a subset of 44 lipids (mainly phospholipids and glycerolipids) that were expressed differently between patients with AD and severe and nonsevere OSA. Among the lipids in this profile, 30 were significantly correlated with specific PSG measures of OSA severity related to sleep fragmentation and hypoxemia. Machine learning analyses revealed a 4-lipid signature (phosphatidylcholine PC(35:4), cis-8,11,14,17-eicosatetraenoic acid and two oxidized triglycerides (OxTG(58:5) and OxTG(62:12)) that provided an accuracy (95% CI) of 0.78 (0.69–0.86) in the detection of OSA. These same lipids improved the predictive power of the STOP-Bang questionnaire in terms of the area under the curve (AUC) from 0.61 (0.50–0.74) to 0.80 (0.70–0.90).

Conclusion

Our results show a plasma lipidomic fingerprint that allows the identification of patients with AD and severe OSA, allowing the personalized management of these individuals. The findings suggest that oxidative stress and inflammation are potential prominent mechanisms underlying the association between OSA and AD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-022-01102-8.

Comprehensive Metabolomics and Machine Learning Identify Profound Oxidative Stress and Inflammation Signatures in Hypertensive Patients with Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) can aggravate blood pressure and increase the risk of cardiovascular diseases in hypertensive individuals, yet the underlying pathophysiological process is still incompletely understood. More importantly, OSA remains a significantly undiagnosed condition. In this study, a total of 559 hypertensive patients with and without OSA were included. Metabolome and lipidome-wide analyses were performed to explore the pathophysiological processes of hypertension comorbid OSA and derive potential biomarkers for diagnosing OSA in hypertensive subjects. Compared to non-OSA hypertensive patients (discovery set = 120; validation set = 116), patients with OSA (discovery set = 165; validation set = 158) demonstrated a unique sera metabolic phenotype dominated by abnormalities in biological processes of oxidative stress and inflammation. By integrating three machine learning algorithms, six discriminatory metabolites (including 5-hydroxyeicosatetraenoic acid, taurine, histidine, lysophosphatidic acid 16:0, lysophosphatidylcholine 18:0, and dihydrosphingosine) were selected for constructing diagnostic and classified model. Notably, the established multivariate-model could accurately identify OSA subjects. The corresponding area under the curve values and the correct classification rates were 0.995 and 96.8% for discovery sets, 0.997 and 99.1% for validation sets. This work updates the molecular insights of hypertension comorbid OSA and paves the way for the use of metabolomics for the diagnosis of OSA in hypertensive individuals.

Metabolomics in Otorhinolaryngology

Otorhinolaryngology (Ear, Nose and Throat-ENT) focuses on inflammatory, immunological, infectious, and neoplastic disorders of the head and neck and on their medical and surgical therapy. The fields of interest of this discipline are the ear, the nose and its paranasal sinuses, the oral cavity, the pharynx, the larynx, and the neck. Besides surgery, there are many other diagnostic aspects of ENT such as audiology and Vestibology, laryngology, phoniatrics, and rhinology. A new advanced technology, named metabolomics, is significantly impacting the field of ENT. All the “omics” sciences, such as genomics, transcriptomics, and proteomics, converge at the level of metabolomics, which is considered the integration of all “omics.” Its application will change the way several of ENT disorders are diagnosed and treated. This review highlights the power of metabolomics, including its pitfalls and promise, and several of its most relevant applications in ENT to provide a basic understanding of the metabolites associated with these districts. In particular, the attention has been focused on different heterogeneous diseases, from head and neck cancer to allergic rhinitis, hearing loss, obstructive sleep apnea, noise trauma, sinusitis, and Meniere’s disease. In conclusion, metabolomics study indicates a “fil rouge” that links these pathologies to improve three aspects of patient care: diagnostics, prognostics, and therapeutics, which in one word is defined as precision medicine.

Effects of CPAP on Metabolic Syndrome in Patients With OSA: A Randomized Trial

BACKGROUND

OSA is associated with metabolic syndrome (MS), but it is unclear whether OSA treatment with CPAP can revert MS.

RESEARCH QUESTION

Does OSA treatment with CPAP per se have effects on the MS reversibility and the associated metabolic, adiposity and vascular parameters?

STUDY DESIGN AND METHODS

The TREATOSA-MS trial is a randomized placebo-controlled trial that enrolled adult patients with a recent diagnosis of MS and moderate or severe OSA (apnea-hypopnea index [AHI], ≥ 15 events/h) to undergo therapeutic CPAP or nasal dilator strips (placebo group) for 6 months. Before and after each intervention, we measured anthropometric variables, BP, glucose, and lipid profile. To control potential-related mechanisms and consequences, we also measured adiposity biomarkers (leptin and adiponectin), body composition, food intake, physical activity, subcutaneous and abdominal fat (visceral and hepatic fat), and endothelial function.

RESULTS

One hundred patients (79% men; mean age, 48 ± 9 years; BMI, 33 ± 4 kg/m²; AHI, 58 ± 29 events/h) completed the study (n = 50 per group). The mean CPAP adherence was 5.5 ± 1.5 h/night. After 6 months, most patients with OSA randomized to CPAP retained the MS diagnosis, but the rate of MS reversibility was higher than observed in the placebo group (18% vs 4%; OR, 5.27; 95% CI, 1.27-35.86; P = .04). In the secondary analysis, CPAP did not promote significant reductions in the individual components of MS, weight, hepatic steatosis, lipid profile, adiponectin, and leptin, but did promote a very modest reduction in visceral fat and improved endothelial function (all analyses were adjusted for baseline values).

INTERPRETATION

Despite the higher rate of MS reversibility after CPAP therapy as compared with placebo, most patients retained this diagnosis. The lack of significant or relevant effects on adiposity biomarkers and depots supports the modest role of OSA in modulating MS.

TRIAL REGISTRATION

ClinicalTrials.gov; No.: NCT02295202; URL: www.

CLINICALTRIALS

gov.

The correlation of serum/plasma IGF-1 concentrations with obstructive sleep apnea hypopnea syndrome: A meta-analysis and meta-regression

BACKGROUND

Obstructive sleep apnea hypopnea syndrome (OSAHS) is a common disease that has serious cardiovascular and metabolic effects. Insulin-like growth factor 1 (IGF-1) levels are reportedly reduced in patients with OSAHS; however, this is still a matter of debate. Therefore, we investigated the association between serum/plasma IGF-1 levels and OSAHS in this meta-analysis.

METHODS

Wan Fang, Excerpta Medica dataBASE, Web of Science, China National Knowledge Infrastructure, VIP, PubMed, and other databases were searched for materials published in any language before April 2, 2022. Two researchers analyzed the studies for quality according to the Newcastle-Ottawa Scale. The acquired data were analyzed using Stata 11.0 and R 3.6.1 software. The effect size was estimated and calculated using standard mean differences and correlation coefficients. Moreover, a combined analysis was conducted using either a random- or fixed-effects model.

RESULTS

Ultimately, 34 studies met our inclusion criteria. Our findings revealed that the plasma/serum IGF-1 concentrations in patients with OSAHS was significantly reduced compared with those in healthy subjects. Subgroup analyses were performed according to OSAHS severity, ethnicity, age, body mass index, specimen testing method, and study design. The outcomes suggested that nearly all subgroups of patients with OSAHS had reduced serum IGF-1 levels. Disease severity and differences in ethnicity were identified as possible influencing factors of serum IGF-1 levels in patients with OSAHS in the meta-regression analysis, and no other factors were found to alter plasma/serum IGF-1 concentrations. Moreover, plasma/serum IGF-1 concentrations were negatively correlated with apnea-hypopnea index and oxygen desaturation index scores and positively associated with minimum oxygen saturation.

CONCLUSION

Serum/plasma IGF-1 concentrations in patients with OSAHS were greatly reduced compared with those of patients in the control group, and were negatively correlated with apnea-hypopnea index and oxygen desaturation index scores and positively correlated with minimum oxygen saturation.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022322738.

The Causal Effects of Lipid Profiles on Sleep Apnea

Introduction

Observational studies have suggested that lipid profiles were associated with risk of sleep apnea (SA). However, the specific lipid types and whether this relationship has a causal effect are uncertain. This study conducted two-sample Mendelian randomization (MR) and multivariable Mendelian randomization (MVMR) to investigate the potential causal relationship between lipid profiles and risk of SA.

Materials and Methods

We used the largest genome-wide association study (GWAS) on European participants on the UK Biobank. After a rigorous single nucleotide polymorphism screening process to remove confounding effects, we performed MR and MVMR to explore the causal relationship between lipid profiles and SA risk.

Results

Both MR and MVMR showed causal effects of increased triglyceride on SA risk [MR: per 10 units, odds ratio (OR): 1.0156; 95% CI: 1.0057-1.0257; P value = 0.002; MVMR: per 10 units, OR: 1.0229; 95% CI: 1.0051-1.0411; P value = 0.011]. The sensitivity analysis including Cochran's Q test, MR-Egger intercept, and MR pleiotropy residual sum and outlier (MR-PRESSO) test indicated that our findings were robust. The causal effects of triglyceride on SA did not change after adjusting for potential confounders (obesity, age, sex, and airway obstruction).

Conclusion

Genetically increased triglyceride levels have independent causal effects on risk of sleep apnea without the confounding effects of obesity, suggesting that lowering triglyceride concentrations may help to reduce the risk of sleep apnea.

Plasma profiling reveals a blood-based metabolic fingerprint of obstructive sleep apnea

INTRODUCTION

Obstructive sleep apnea (OSA) is a chronic, heterogeneous and multicomponent disorder with associated cardiovascular and metabolic alterations. Despite being the most common sleep-disordered breathing, it remains a significantly undiagnosed condition.

OBJECTIVE

We examined the plasma metabolome and lipidome of patients with suspected OSA, aiming to identify potential diagnosis biomarkers and to provide insights into the pathophysiological mechanisms underlying the disease. Additionally, we evaluated the impact of continuous positive airway pressure (CPAP) treatment on the circulating metabolomic and lipidomic profile.

MATERIAL AND METHODS

Observational-prospective-longitudinal study including 206 consecutive subjects referred to the sleep unit. OSA was defined as an apnea-hypopnoea index ≥ 15 events/h after polysomnography (PSG). Patients treated with CPAP were followed-up for 6 months. Untargeted plasma metabolomic and lipidomic profiling was performed using liquid chromatography coulpled to massspectrometry.

RESULTS

A plasma profile composed of 33 metabolites (mainly glycerophospholipids and bile acids) was identified in OSA vs. non-OSA patients. This profile correlated with specific PSG measures of OSA severity related to sleep fragmentation and hypoxemia. Machine learning analyses disclosed a 4-metabolites-signature that provided an accuracy (95% CI) of 0.98 (0.95-0.99) for OSA detection. CPAP treatment was associated with changes in 5 plasma metabolites previously altered by OSA.

CONCLUSIONS

This analysis of the circulating metabolome and lipidome reveals a molecular fingerprint of OSA, which was modulated after effective CPAP treatment. Our results suggest blood-based biomarker candidates with potential application in the personalized management of OSA and suggest the activation of adaptive mechanisms in response to OSA-derived hypoxia.

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.

Validation of breath biomarkers for obstructive sleep apnea

BACKGROUND AND OBJECTIVES

Obstructive sleep apnea (OSA) is an underdiagnosed respiratory disease with negative metabolic and cardiovascular effects. The current gold standard for diagnosing OSA is in-hospital polysomnography, a time-consuming and costly procedure, often inconvenient for the patient. Recent studies revealed evidence for the potential of breath analysis for the diagnosis of OSA based on a disease-specific metabolic pattern. However, none of these findings were validated in a larger and broader cohort, an essential step for its application in clinics.

METHODS

In the present study, we validated a panel of breath biomarkers in a cohort of patients with possible OSA (N = 149). These markers were previously identified in our group by secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS).

RESULTS

Here, we could confirm significant differences between metabolic patterns in exhaled breath from OSA patients compared to control subjects without OSA as well as the association of breath biomarker levels with disease severity. Our prediction of the diagnosis for the patients from this completely independent validation study using a classification model trained on the data from the previous study resulted in an area under the receiver operating characteristic curve of 0.66, which is comparable to questionnaire-based OSA screenings.

CONCLUSIONS

Thus, our results suggest that breath analysis by SESI-HRMS might be useful to screen for OSA as an objective measure. However, its true predictive power should be tested in combination with OSA screening questionnaires.

CLINICAL TRIAL

"Mass Spectral Fingerprinting in Obstructive Sleep Apnoea", NCT02810158, www.ClinicalTrials.gov.

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.

Metabolomics and microbiome profiling as biomarkers in obstructive sleep apnoea: a comprehensive review

Introduction

Obstructive sleep apnoea (OSA) is a common sleep disorder with a high social and economic burden. Thus, early prediction and diagnosis of OSA are important. Changes in metabolism and the microbiome may serve as biomarkers for OSA. Herein, we review the literature on the metabolomic and microbiome changes associated with OSA, and identify the metabolites and microorganisms involved.

Methods

We searched the PUBMED and EMBASE electronic databases using the following terms: “obstructive sleep apnea”, “OSA”, “sleep disordered breathing”, “SDB”, “intermittent hypoxia”, “sleep fragmentation”, and either “metabolomics” or “microbiome”. In total, 273 papers were identified, of which 28 were included in our study.

Results

Changes in the levels of certain metabolites related to fatty acid, carbohydrate and amino acid metabolism were associated with the incidence of OSA. The diversity and abundance of microflora, particularly Firmicutes and Bacteroidetes, were altered in humans and rodents with OSA.

Conclusions

Certain changes in metabolism and the microbiota play an integral role in the pathophysiology of OSA and OSA-induced cardiovascular complications. Metabolomic and microbiome biomarkers shed light on the pathogenesis of OSA, and facilitate early diagnosis and treatment.

Unique alterations in metabolism and the microbiome play an integral role in the pathophysiology of OSA and OSA-induced cardiovascular complicationshttps://bit.ly/3mW2rD5

[The role of biomarkers in the detection of the OSA syndrome. A narrative review of the literature]

INTRODUCTION

Obstructive sleep apnoea (OSA) is a common sleep-related breath disorder associated with cardiovascular and cerebrovascular complications, such as hypertension, arrhythmia, coronary artery disease and stroke. Unfortunately, OSA is underdiagnosed.

BACKGROUND

Because of its clinical and therapeutic variability, OSA could benefit a personalized medicine approach. Diagnosis with polysomnography is expensive and access is limited. Clinical scoring systems allow screening of OSA, but many limitations exist. Because of this, biomarkers could be useful for the detection of OSA.

OUTLOOK

Biomarkers specific to OSA would allow for better mass screening and more personalized treatment of the disease. This narrative review of the literature aims to summarize the biomarkers already described for the diagnosis of OSA and clarify both their advantages and limitations in daily practice.

CONCLUSIONS

Our review of the literature did not actually identify an ideal biomarker even if promising research is ongoing.

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.

Metabolomics Analysis on Obesity-Related Obstructive Sleep Apnea After Weight Loss Management: A Preliminary Study

OBJECTIVE

Roux-en-Y gastric bypass (RYGB) surgery is an effective type of weight loss management and may improve obesity-related obstructive sleep apnea (OSA). Obese subjects who meet the criteria for surgery with OSA were enrolled. We investigated the metabolomic effects of RYGB on OSA.

METHODS

Clinical data, serum measurements including indices of glycolipid metabolism, and polysomnography (PSG) measurements were collected at baseline and 6 months after RYGB surgery. Metabolomic analysis was performed using ultra-performance liquid chromatography-mass spectrometry.

RESULTS

A group of 37 patients with obesity, type 2 diabetes (T2DM) and suspected OSA were enrolled of which 27 were OSA subjects. After RYGB surgery, metabolic outcomes and sleep parameters were all significantly improved. The OSA remission group had lower valine, isoleucine, and C24:1(cis-15) levels, and higher trimethylamine N-oxide, hippurate, and indole-3-propionic acid levels after RYGB surgery. A combination of preoperative indices (age, apnea-hypopnea index (AHI), fasting C-peptide level, and hippurate level) predicted the RYGB effect size in obese patients with T2DM and OSA, with an area under receiver operating characteristic curve of 0.947, specificity of 82.4%, and sensitivity of 100%.

CONCLUSIONS

RYGB surgery may significantly improve the metabolic status of patients with obesity, T2DM and OSA. A combination of preoperative indices (age, AHI, fasting C peptide level, and hippurate level) may be useful for predicting the effect size of RYGB in obese patients with T2DM and OSA. The mechanisms underlying OSA remission need to be explored.

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.

An Optimized Dual Extraction Method for the Simultaneous and Accurate Analysis of Polar Metabolites and Lipids Carried out on Single Biological Samples

The functional understanding of metabolic changes requires both a significant investigation into metabolic pathways, as enabled by global metabolomics and lipidomics approaches, and the comprehensive and accurate exploration of specific key pathways. To answer this pivotal challenge, we propose an optimized approach, which combines an efficient sample preparation, aiming to reduce the variability, with a biphasic extraction method, where both the aqueous and organic phases of the same sample are used for mass spectrometry analyses. We demonstrated that this double extraction protocol allows working with one single sample without decreasing the metabolome and lipidome coverage. It enables the targeted analysis of 40 polar metabolites and 82 lipids, together with the absolute quantification of 32 polar metabolites, providing comprehensive coverage and quantitative measurement of the metabolites involved in central carbon energy pathways. With this method, we evidenced modulations of several lipids, amino acids, and energy metabolites in HepaRG cells exposed to fenofibrate, a model hepatic toxicant, and metabolic modulator. This new protocol is particularly relevant for experiments involving limited amounts of biological material and for functional metabolic explorations and is thus of particular interest for studies aiming to decipher the effects and modes of action of metabolic disrupting compounds.

New method for rapid identification and quantification of fungal biomass using ergosterol autofluorescence

This research reports on the development of a method to identify and quantify fungal biomass based on ergosterol autofluorescence using excitation-emission matrix (EEM) measurements. In the first stage of this work, several ergosterol extraction methods were evaluated by APCI-MS, where the ultrasound-assisted procedure showed the best results. Following an experimental design, various quantities of the dried mycelium of the fungus Schizophyllum commune were mixed with the starchy solid residue (BBR) from the babassu (Orbignya sp.) oil industry, and these samples were subjected to several ergosterol extraction methods. The EEM spectral data of the samples were subjected to Principal Component Analysis (PCA), which showed the possibility to qualitatively evaluate the presence of ergosterol in the samples by ergosterol autofluorescence without the addition of any reagent. In order to assess the feasibility of quantifying fungal biomass using ergosterol autofluorescence, the EEM spectral data and known amounts of fungal biomass were modeled using partial least squares (PLS) regression and a procedure of backward selection of predictors (AutoPLS) was applied to select the Excitation-Emission wavelength pairs that provide the lowest prediction error. The results revealed that the amount of fungal biomass in samples containing interfering substances (BBR) can be accurately predicted with R²CV = 0.939, R²P = 0.936, RPDcv = 4.07, RPDp = 4.06, RMSECV = 0.0731 and RMSEP = 0.0797. In order to obtain an easy-to-understand equation that expresses the relationship between fungal biomass and fluorescence intensity, multiple linear regression (MLR) was applied to the VIP variables selected by the AutoPLS method. The MLR model selected only 2 variables and showed a very good performance, with R²CV = 0.862, R²P = 0.809, RPDcv = 2.18, RPDp = 2.35, RMSECV = 0.137 and RMSEP = 0.138. This study demonstrated that ergosterol autofluorescence can be successfully used to quantify fungal biomass even when mixed with agroindustrial residues, in this case BBR.

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.

Advances and challenges in pursuing biomarkers for obstructive sleep apnea: Implications for the cardiovascular risk

Obstructive sleep apnea (OSA) is a common clinical condition associated with increased cardiovascular morbidity and mortality. Recent evidence from clinical studies and animal models suggest that OSA can promote cardiovascular disease by inducing autonomic, hemodynamic, inflammatory and metabolic dysregulation. However, most of the evidence addressing hard endpoints in humans is derived from observational studies. Several challenges have been noted in the pursuit of a comprehensive knowledge base about the impact of OSA including: 1) the precise mechanisms by which OSA causes metabolic and cardiovascular consequences are not clear, which limits our current ability to address potential targets in OSA; 2) several patients with OSA, even with severe forms, present with no or mild daytime symptoms. Beyond the obvious challenges for obtaining good adherence for conventional OSA treatments, there is evidence that symptomatic vs. asymptomatic patients with OSA do not necessarily have the same metabolic and cardiovascular outcomes; and 3) the cardiovascular response to OSA treatment may vary even in those patients with good adherence. In this scenario, there is an obvious need to develop biomarkers in the OSA research area. This review focuses on describing the advances that have occurred so far in exploring potential OSA biomarkers with clear emphasis for the cardiovascular risk. Particular attention will be devoted to discuss molecular biomarkers including the potential role of microRNAs, proteomics and metabolomics. We also discuss the major challenges and perspectives in this growing research field.

Severe obstructive sleep apnea is associated with circulating microRNAs related to heart failure, myocardial ischemia, and cancer proliferation

PURPOSE

Obstructive sleep apnea (OSA) is associated with multiple comorbid conditions including cardiovascular diseases and cancer. There is a growing interest in exploring biomarkers to understand the related mechanisms and improve the risk stratification of OSA. Circulating microRNAs (miRNAs) are single noncoding strands of nearly 22 nucleotides that posttranscriptionally regulate target gene expression. Our aim was to identify miRNA profiles associated with OSA.

METHODS

We studied 48 male subjects, mostly Caucasian (63%) and overweight, divided by polysomnography into the no OSA control group (n = 6), mild OSA group (n = 12), moderate OSA group (n = 15), and severe OSA group (n = 15). The study groups were matched for age, body mass index (BMI), and body fat composition. miRNA profiles were measured from peripheral whole blood using two steps: (1) microarray analysis comprising more than 2500 miRNAs in a subsample of 12 subjects (three from each group); and (2) validation phase using real-time quantitative polymerase chain reaction (RTqPCR).

RESULTS

The microarray assessment identified 21 differentially expressed miRNAs among the groups. The RT-qPCR assessment showed that miR-1254 and miR-320e presented a gradual increase in expression parallel to OSA severity. Linear regression analysis showed that severe OSA was independently associated with miR-1254 (ß = 68.4; EP = 29.8; p = 0.02) and miR-320e (ß = 76.1; EP = 31.3; p = 0.02).

CONCLUSION

Severe OSA is independently associated with miRNAs that are involved in heart failure (miR-1254), myocardial ischemia/reperfusion (miR-320e), and cell proliferation in some cancer types (miR-1254 and miR-320e). Future investigations addressing whether these miRs may provide prognostic information in OSA are needed.

Circulating microRNA profile as a potential biomarker for obstructive sleep apnea diagnosis

Evaluation of microRNAs (miRNAs) could allow characterization of the obstructive sleep apnea (OSA) and help diagnose it more accurately. We aimed to examine circulating miRNA profiles to establish the differences between non-OSA and OSA patients. Additionally, we aimed to analyse the effect of continuous positive airway pressure (CPAP) treatment on the miRNA profile. This observational, longitudinal study included 230 subjects referred to the Sleep Unit due to suspected OSA. Expression profiling of 188 miRNAs in plasma was performed in 27 subjects by TaqMan-Low-Density-Array. OSA-related miRNAs were selected for validation by RT-qPCR in 203 patients. Prediction models were built to discriminate between non-OSA and OSA: 1) NoSAS-score, 2) differentially expressed miRNAs, and 3) combination of NoSAS-score plus miRNAs. The differentially expressed miRNAs were measured after 6 months of follow-up. From the 14 miRNAs selected for validation, 6 were confirmed to be differentially expressed. The areas under the curve were 0.73 for the NoSAS-score, 0.81 for the miRNAs and 0.86 for the combination. After 6 months of CPAP treatment, miRNA levels in the OSA group seem to approximate to non-OSA levels. A cluster of miRNAs was identified to differentiate between non-OSA and OSA patients. CPAP treatment was associated with changes in the circulating miRNA profile.

Adipose tissue as a key player in obstructive sleep apnoea

Obstructive sleep apnoea (OSA) is a major health concern worldwide and adversely affects multiple organs and systems. OSA is associated with obesity in >60% of cases and is independently linked with the development of numerous comorbidities including hypertension, arrhythmia, stroke, coronary heart disease and metabolic dysfunction. The complex interaction between these conditions has a significant impact on patient care and mortality. The pathophysiology of cardiometabolic complications in OSA is still incompletely understood; however, the particular form of intermittent hypoxia (IH) observed in OSA, with repetitive short cycles of desaturation and re-oxygenation, probably plays a pivotal role. There is fast growing evidence that IH mediates some of its detrimental effects through adipose tissue inflammation and dysfunction. This article aims to summarise the effects of IH on adipose tissue in experimental models in a comprehensive way. Data from well-designed controlled trials are also reported with the final goal of proposing new avenues for improving phenotyping and personalised care in OSA.

Fast growing evidence strongly suggests that cardiovascular and metabolic alterations induced by intermittent hypoxia in OSA are mediated through adipose tissue inflammation and dysfunction.bit.ly/2W929Pe

Metabolomics and Biomarker Discovery

Recently, metabolomics-the study of metabolite profiles within biological samples-has found a wide range of applications. This chapter describes the different techniques available for metabolomic analysis, the various samples that can be utilised for analysis and applications of both global and targeted metabolomic analysis to biomarker discovery in medicine.