Association between proteomics and obstructive sleep apnea phenotypes in a community‐based cohort of women

Novel susceptibility genes and biomarkers for obstructive sleep apnea: insights from genetic and inflammatory proteins

STUDY OBJECTIVES

Numerous observational studies link obstructive sleep apnea (OSA) to inflammatory proteins, yet the directionality of these associations remains ambiguous. Therefore, we aimed to clarify the potential associations of gene-predicted inflammatory proteins with OSA.

METHODS

Based on genome-wide association study data, we applied Mendelian randomization (MR) to explore potential connections between circulating inflammatory proteins and OSA, primarily using the inverse-variance weighting method for robustness. Cochran's Q test, MR‒Egger intercept test, MR-PRESSO, and leave-one-out method were used to perform sensitivity tests for pleiotropy and heterogeneity. Replication analyses and meta-analyses were performed using other independent data. Steiger tests and multivariate MR assessed the independent effects of exposure factors, and the functional mapping and annotation (FUMA) platform was used to identify key genes to enhance the understanding of genetics.

RESULTS

Our investigation revealed 21 circulating inflammatory proteins significantly associated with OSA-related phenotypes. Notably, IL-10RA, IL-18R1, TNFSF14, CCL23, ADA, and SLAMF1 had significant effects on multiple phenotypes. After FDR correction, IL-18R1, SLAMF1, IL-10RA, and IL-17C were identified as important candidates for OSA, and multivariate MR analysis strengthened the independent heritability of 20 inflammatory factors. The FUMA platform revealed seven overlapping genes: ROBO1, PRIM1, NACA, SHBG, HSD17B6, RBMS2, and WWOX. All reverse MR analyses and sensitivity analyses confirmed the robustness of these associations.

CONCLUSIONS

Our results underscore crucial associations between inflammatory proteins and OSA pathogenesis, revealing new correlates and susceptibility genes. These findings advance biomarker identification for OSA risk and highlight the importance of genetic and inflammatory profiles in OSA management.

Quantitative Proteomics Analysis of Serum and Urine With DIA Mass Spectrometry Reveals Biomarkers for Pediatric Obstructive Sleep Apnea

OBJECTIVES

Identification of suitable biomarkers that facilitate the screening and evaluation of pediatric obstructive sleep apnea (OSA) and its severity was explored.

METHODS

Data-independent acquisition quantitative proteomic analysis was employed to identify serum and urine proteins with differential expression patterns between children with OSA and controls. Differentially expressed proteins that gradually increased or decreased with the severity of OSA were retained as potential biomarkers and underwent ELISA validation.

RESULTS

We found that with increasing severity of OSA, there was a gradual upregulation of 34 proteins in the serum and 124 proteins in the urine, along with a respective downregulation of 10 serum proteins and 64 urinary proteins in the initial cohort of 40 children. These proteins primarily participate in immune activation, the complement pathway, oxygen transport, and reactive oxygen metabolism. Notably, cathepsin Z exhibited a positive correlation with the obstructive apnea hypopnea index, whereas sex hormone-binding globulin (SHBG) was negatively correlated. These proteins were then validated by ELISA in an independent cohort (n=21). Circulating cathepsin Z and SHBG levels displayed acceptable diagnostic performance of OSA with AUC values of 0.863 and 0.738, respectively.

CONCLUSIONS

We identified two promising circulating proteins as novel biomarkers for clinical diagnosis and assessment of pediatric OSA severity. Furthermore, the comprehensive proteomic profile in pediatric OSA should aid in exploring the underlying pathophysiological mechanisms associated with this prevalent condition.

Achieving Better Understanding of Obstructive Sleep Apnea Treatment Effects on Cardiovascular Disease Outcomes through Machine Learning Approaches: A Narrative Review

Obstructive sleep apnea (OSA) affects almost a billion people worldwide and is associated with a myriad of adverse health outcomes. Among the most prevalent and morbid are cardiovascular diseases (CVDs). Nonetheless, randomized controlled trials (RCTs) of OSA treatment have failed to show improvements in CVD outcomes. A major limitation in our field is the lack of precision in defining OSA and specifically subgroups with the potential to benefit from therapy. Further, this has called into question the validity of using the time-honored apnea-hypopnea index as the ultimate defining criteria for OSA. Recent applications of advanced statistical methods and machine learning have brought to light a variety of OSA endotypes and phenotypes. These methods also provide an opportunity to understand the interaction between OSA and comorbid diseases for better CVD risk stratification. Lastly, machine learning and specifically heterogeneous treatment effects modeling can help uncover subgroups with differential outcomes after treatment initiation. In an era of data sharing and big data, these techniques will be at the forefront of OSA research. Advanced data science methods, such as machine-learning analyses and artificial intelligence, will improve our ability to determine the unique influence of OSA on CVD outcomes and ultimately allow us to better determine precision medicine approaches in OSA patients for CVD risk reduction. In this narrative review, we will highlight how team science via machine learning and artificial intelligence applied to existing clinical data, polysomnography, proteomics, and imaging can do just that.

Obstructive sleep apnea during rapid eye movement sleep and cognitive performance in adults

STUDY OBJECTIVES

Obstructive sleep apnea (OSA) during rapid eye movement (REM) sleep is often characterized with more frequent and lengthy breathing events and greater oxygen desaturation than during other sleep stages. Current evidence suggests an association between OSA and cognitive decline, however whether OSA during REM sleep plays a vital role in this link is understudied.

METHODS

A cross-sectional sample of 728 men and women (aged 59.1 ± 11.3 years) underwent a full night polysomnography for determining apnea-hypopnea index (AHI) and sleep stages. Trail Making Test (TMT) part A and B were conducted during the following day for assessing participants' cognitive function. Linear regression analyses were performed to test the possible association between AHI and AHI during REM sleep with TMT-A and B results. Similar analyses were carried out in a subsample involving participants aged ≥60 years with ≥30 min of REM sleep (n = 356).

RESULTS

Despite a slight difference in TMT-B between participants with and without OSA (AHI ≥5 vs AHI <5, β-coefficient: 4.83, 95 % CI: [-9.44, -0.22], P = 0.040), no other association between AHI or REM-AHI and TMT results were found in the full sample. In older participants (aged ≥60 years), a REM-AHI ≥5 events/hour was associated with longer time taken to finish TMT-A (vs REM-AHI <5 events/hour, 3.93, [0.96, 6.90], P = 0.010). There was no association between REM-AHI and time taken to finish TMT-B in older participants.

CONCLUSIONS

The results indicate that OSA during REM sleep may be of particular concern for attention-related cognitive function in older adults.

REM-OSA as a Tool to Understand Both the Architecture of Sleep and Pathogenesis of Sleep Apnea-Literature Review

Sleep is a complex physiological state, which can be divided into the non-rapid eye movement (NREM) phase and the REM phase. Both have some unique features and functions. This difference is best visible in electroencephalography recordings, respiratory system activity, arousals, autonomic nervous system activity, or metabolism. Obstructive sleep apnea (OSA) is a common condition characterized by recurrent episodes of pauses in breathing during sleep caused by blockage of the upper airways. This common condition has multifactorial ethiopathogenesis (e.g., anatomical predisposition, sex, obesity, and age). Within this heterogenous syndrome, some distinctive phenotypes sharing similar clinical features can be recognized, one of them being REM sleep predominant OSA (REM-OSA). The aim of this review was to describe the pathomechanism of REM-OSA phenotype, its specific clinical presentation, and its consequences. Available data suggest that in this group of patients, the severity of specific cardiovascular and metabolic complications is increased. Due to the impact of apneas and hypopneas predominance during REM sleep, patients are more prone to develop hypertension or glucose metabolism impairment. Additionally, due to the specific function of REM sleep, which is predominantly fragmented in the REM-OSA, this group presents with decreased neurocognitive performance, reflected in memory deterioration, and mood changes including depression. REM-OSA clinical diagnosis and treatment can alleviate these outcomes, surpassing the traditional treatment and focusing on a more personalized approach, such as using longer therapy of continuous positive airway pressure or oral appliance use.

Advanced Proteomics and Cluster Analysis for Identifying Novel Obstructive Sleep Apnea Subtypes before and after Continuous Positive Airway Pressure Therapy

Rationale: Studies have shown elevated inflammatory biomarkers in obstructive sleep apnea (OSA), but data after continuous positive airway pressure (CPAP) treatment are inconsistent. Objectives: We used the Olink proteomics panel to identify unique OSA clusters on the basis of inflammatory protein expression and assess the impact of CPAP therapy. Methods: Adults with newly diagnosed OSA had blood drawn at baseline and three to four months after CPAP. Samples were analyzed using the Olink proteomics platform, which measures 92 prespecified inflammatory proteins using proximity extension assay. Linear mixed-effects models were used to model changes in protein expression during the period of CPAP use, adjusting for batch, age, and sex. Unsupervised hierarchical clustering was performed to identify unique inflammatory OSA clusters on the basis of inflammatory biomarkers. Within-cluster impact of CPAP on inflammatory protein expression was assessed. Results: Among 46 patients, the mean age was 46 ± 12 years (22% women), mean body mass index was 31 ± 5 kg/m2, and mean respiratory disturbance index was 33 ± 17 events/hour. Unsupervised cluster and heatmap analysis revealed three unique proteomic clusters, with low (n = 21), intermediate (n = 19), and high (n = 6) inflammatory protein expression. After CPAP, there were significant within-cluster differences in protein expression. The low inflammatory cluster had a significant increase in protein expression (16%; P = 0.02), and the high inflammatory cluster had a significant decrease in protein expression (-20%; P = 0.003), more significant among those compliant with CPAP in the low (25%; P = 0.04) and high (-22%; P = 0.01) clusters. Conclusions: We identified three unique inflammatory clusters in patients with OSA using plasma proteomics, with a differential response to CPAP by cluster. Our results are hypothesis generating and require further investigation in larger longitudinal studies for enhanced cardiovascular risk profiling in OSA.

Asthma and asthma-related comorbidity: effects on nocturnal oxygen saturation

STUDY OBJECTIVES

Nocturnal symptoms are very common in asthma, which is associated with worse sleep quality. The nocturnal oxygen saturation may be decreased in asthma; however, whether this association is dependent on nocturnal asthma symptoms, lung function, coexisting obstructive sleep apnea (OSA), or other asthma-related comorbidities is unknown. The objective of this study was to examine the effects of asthma, OSA, lung function, airway symptoms, and asthma-related comorbidities on the nocturnal oxygen saturation in a cross-sectional community-based population study.

METHODS

In total, 395 women and 392 men underwent overnight polysomnography, performed spirometry, and completed questionnaires on airway symptoms and asthma-related comorbidities.

RESULTS

Participants with asthma (n = 88) had a lower nocturnal oxygen saturation than those without asthma (93.8% vs 94.3%, P = .01) also after adjusting for comorbidity, age, body mass index, and smoking status (coefficient -0.38; CI -0.67, -0.10; P < .01). The nocturnal oxygen saturation was lower among participants with wheezing, nocturnal chest tightness, fixed airflow limitation, gastroesophageal reflux, obesity, and OSA than in those without these conditions. The associations between lower oxygen saturation and wheezing, forced expiratory volume in 1 second, gastroesophageal reflux, and apnea-hypopnea index were significant also after adjusting for age, sex, body mass index, and smoking status. Participants with both wheezing and OSA had a significantly lower nocturnal oxygen saturation (92.5 ± 0.5%) than participants with wheezing only (94.3 ± 0.3%) and OSA only (93.6 ± 0.2% %) (P < .01).

CONCLUSIONS

Participants with asthma displayed a lower mean oxygen saturation during sleep, which could not be explained only by coexisting OSA or obesity. Also, asthma symptoms and lung function were associated with lower nocturnal oxygen saturation. The lower oxygen saturation seen in asthma is hence multifactorial in origin and is a result of the combination of symptoms, lung function, and comorbidity.

CITATION

Sundbom F, Janson C, Ljunggren M, Lindberg E. Asthma and asthma-related comorbidity: effects on nocturnal oxygen saturation. J Clin Sleep Med. 2022;18(11):2635-2641.

Rapid eye movement sleep apnea and carotid intima thickness in men and women: a SHE-MUSTACHE cohort study

Rapid eye movement (REM) obstructive sleep apnea might be particularly harmful to the cardiovascular system. We aimed to investigate the association between sleep apnea during REM sleep and signs of atherosclerotic disease in the form of carotid intima thickness in a community-based sample of men and women and possible sex differences in this association. The association between sleep apnea during REM sleep and intima thickness was analysed cross-sectionally in women from the community-based "Sleep and Health in Women" (SHE) study (n = 253) and age- and body mass index (BMI)-matched men from the "Men in Uppsala; a Study of sleep, Apnea and Cardiometabolic Health" (MUSTACHE) study (n = 338). Confounders adjusted for were age, BMI, gender, alcohol, and smoking. All participants underwent a full-night polysomnography, high-resolution ultrasonography of the common carotid artery, anthropometric measurements, blood pressure measurements, and answered questionnaires. There was an association between sleep apnea during REM sleep and thicker carotid intima that remained after adjustment for confounding (adjusted β = 0.008, p = 0.032). The intima was increased by 9.9% in the group with severe sleep apnea during REM sleep, and this association between severe sleep apnea during REM sleep and increased intima thickness remained after adjustment for confounders (adjusted β = 0.043, p = 0.021). More women than men had severe sleep apnea during REM sleep; moreover, in sex-stratified analyses, the association between sleep apnea during REM sleep and intima thickness was found in women but not in men. We conclude that severe REM sleep apnea is independently associated with signs of atherosclerosis. When stratified by sex, the association is seen in women but not in men.

Screening of plasma exosomal lncRNAs to identify potential biomarkers for obstructive sleep apnea

Background

Obstructive sleep apnea (OSA) is highly prevalent, but frequently undiagnosed. The existing biomarkers of OSA are relatively insensitive and inaccurate. Long non-coding RNAs (lncRNAs) have no protein-coding ability but have a role in regulating gene expression. They are stably expressed in exosomes, easily and rapidly measurable. Changes in expression of exosomal lncRNAs can be useful for disease diagnoses. However, there are few reports on the association of exosomal lncRNAs with OSA. We aimed to investigate the exosomal lncRNA profiles to establish the differences between non-OSA, OSA with or without hypertension (HTN) and serve as a potential diagnostic biomarker.

Methods

This diagnostic test included 63 participants: [normal control (NC) =25], (OSA =23), and (HTN-OSA =15). Expression profiling of lncRNAs in isolated exosomes was performed through high-throughput sequencing in 9 participants. Subsequently, OSA/HTN-OSA related lncRNAs were selected for validation by droplet digital polymerase chain reaction (ddPCR), receiver operating characteristic (ROC) curves were used to determine the diagnostic value. The reliabilities of the screened gene were further validated in another independent cohort: (NC =10), (OSA mild =10), (OSA moderate =11), and (OSA severe =10), the correlation between clinical features and its expression was analyzed. The MiRanda software was used to predict the binding sites of interaction between microRNA (miRNA) and target genes regulated by screened lncRNA.

Results

We identified the differentially expressed lncRNAs and mRNAs in plasma exosomes of the NC, OSA, HTN-OSA groups. Most pathways enriched in differentially expressed lncRNAs and mRNAs had previously been linked to OSA. Among them, ENST00000592016 enables discrimination between NC and OSA individuals [area under curve (AUC) =0.846, 95% confidence interval (CI): 0.72–0.97]. The severity of OSA was associated with changes in the ENST00000592016 expression. Furthermore, ENST00000592016 affected the PI3K-Akt, MAPK, and TNF pathways by regulating miRNA expressions.

Conclusions

This is the first report about differential expression of lncRNA in OSA and HTN-OSA exosomes. ENST00000592016 enables discrimination between NC and OSA individuals. This work enabled characterization of OSA and provided the preliminary work for the study of biomarker of OSA.

Molecular determinants of obstructive sleep apnea

Obstructive sleep apnea (OSA) is characterized as recurrent episodes of obstruction in the upper airway during the period of sleep. The condition occurs in approximately 11% and 4% of middle-aged men and middle-aged women, respectively. Polysomnography is a diagnostic procedure that involves the constant observation of oxygen saturation and unsaturation during sleep. Usually, positive airway pressure is considered a benchmark treatment for OSA. This review summarizes the recent developments and emerging evidence from molecular biology-based research studies that show that genetic factors have an influence on OSA. The genetic aspects of OSA that have been identified include heritability and other phenotypic co-factors such as anatomical morphology. It also draws attention to the results of a polymorphic-based study that was conducted to determine the causative single nucleotide mutations associated with obesity and adverse cardiovascular risk in OSA. However, the role of such mutations and their linkage to OSA can not yet be established. Nonetheless, a large body of evidence supports a strong association between inflammatory cytokine polymorphism and obesity in the development of OSA. There are also probable intermediate factors with several gene-gene interactions. Therefore, advanced applications and modern techniques should be applied to facilitate new findings and to minimize the risk of developing OSA.

The CONSTANCES Cohort Biobank: An Open Tool for Research in Epidemiology and Prevention of Diseases

“General-purpose cohorts” in epidemiology and public health are designed to cover a broad scope of determinants and outcomes, in order to answer several research questions, including those not defined at study inception. In this context, the general objective of the CONSTANCES project is to set up a large population-based cohort that will contribute to the development of epidemiological research by hosting ancillary projects on a wide range of scientific domains, and to provide public health information. CONSTANCES was designed as a randomly selected sample of French adults aged 18–69 years at study inception; 202,045 subjects were included over an 8-year period. At inclusion, the selected participants are invited to attend one of the 24 participating Health Prevention Centers (HPCs) for a comprehensive health examination. The follow-up includes a yearly self-administered questionnaire, and a periodic visit to an HPC. Procedures have been developed to use the national healthcare databases to allow identification and validation of diseases over the follow-up. The biological collection (serum, lithium heparinized plasma, EDTA plasma, urine and buffy coat) began gradually in June 2018. At the end of the inclusions, specimens from 83,000 donors will have been collected. Specimens are collected according to a standardized protocol, identical in all recruitment centers. All operations relating to bio-banking have been entrusted by Inserm to the Integrated Biobank of Luxembourg (IBBL). A quality management system has been put in place. Particular attention has been paid to the traceability of all operations. The nature of the biological samples stored has been deliberately limited due to the economic and organizational constraints of the inclusion centers. Some research works may require specific collection conditions, and can be developed on request for a limited number of subjects and in specially trained centers. The biological specimens that are collected will allow for a large spectrum of biomarkers studies and genetic and epigenetic markers through candidate or agnostic approaches. By linking the extensive data on personal, lifestyle, environmental, occupational and social factors with the biomarker data, the CONSTANCES cohort offers the opportunity to study the interplays between these factors using an integrative approach and state-of-the-art methods.