Obstructive sleep apnea alters microRNA levels: Effects of continuous positive airway pressure.

Background: Obstructive sleep apnea (OSA) has been linked to cytokine-mediated chronic inflammatory states. Continuous positive airway pressure (CPAP) is an established therapy for OSA, but its effects on inflammation remain unclear. A recent study from our group identified soluble cytokine receptors altered in OSA patients and modified by CPAP adherence. However, the upstream regulatory pathways responsible for these shifts in proinflammatory cascades with OSA and CPAP therapy remained unknown. Accordingly, this study mapped OSA and CPAP-modulated soluble cytokine receptors to specific microRNAs and then tested the hypothesis that OSA and CPAP adherence shift cytokine-related microRNA expression profiles. Study Design: Plasma samples were collected from patients with OSA (n=50) at baseline and approximately 90 days after CPAP initiation and compared to referent control subjects (n=10). Patients with OSA were further divided into cohorts defined by adherence vs nonadherence to CPAP therapy. The microRNAs that mapped to soluble cytokine receptors of interest were subjected to quantitative polymerase chain reaction. Results: At baseline, increased hsa-miR-15a-5p, hsa-miR-15b-5p, hsa-miR-16-5p, hsa-miR-195-5p, hsa-miR-424-5p, hsa-miR-223-3p, and hsa-miR-223-5p were observed in patients with OSA compared to controls (p<0.05). In CPAP adherent patients (n=22), hsa-miR233-3p and hsa-miR233-5p decreased at follow-up (p<0.05) whereas there was no change in miR levels from baseline in non-adherent CPAP patients (n=28). The miRs hsa-miR233-3p and hsa-miR233-5p mapped to both proinflammatory and innate immunity activation; the inflammasome. Conclusion: A specific set of microRNAs, including hsa-miR233-3p and hsa-miR233-5p, may serve as a marker of inflammatory responses in patients with OSA, and be used to assess attenuation of inflammasome activation by CPAP.

Machine learning derived serum creatinine trajectories in acute kidney injury in critically ill patients with sepsis.

BACKGROUND: Current classification for acute kidney injury (AKI) in critically ill patients with sepsis relies only on its severity-measured by maximum creatinine which overlooks inherent complexities and longitudinal evaluation of this heterogenous syndrome. The role of classification of AKI based on early creatinine trajectories is unclear. METHODS: This retrospective study identified patients with Sepsis-3 who developed AKI within 48-h of intensive care unit admission using Medical Information Mart for Intensive Care-IV database. We used latent class mixed modelling to identify early creatinine trajectory-based classes of AKI in critically ill patients with sepsis. Our primary outcome was development of acute kidney disease (AKD). Secondary outcomes were composite of AKD or all-cause in-hospital mortality by day 7, and AKD or all-cause in-hospital mortality by hospital discharge. We used multivariable regression to assess impact of creatinine trajectory-based classification on outcomes, and eICU database for external validation. RESULTS: Among 4197 patients with AKI in critically ill patients with sepsis, we identified eight creatinine trajectory-based classes with distinct characteristics. Compared to the class with transient AKI, the class that showed severe AKI with mild improvement but persistence had highest adjusted risks for developing AKD (OR 5.16; 95% CI 2.87-9.24) and composite 7-day outcome (HR 4.51; 95% CI 2.69-7.56). The class that demonstrated late mild AKI with persistence and worsening had highest risks for developing composite hospital discharge outcome (HR 2.04; 95% CI 1.41-2.94). These associations were similar on external validation. CONCLUSIONS: These 8 classes of AKI in critically ill patients with sepsis, stratified by early creatinine trajectories, were good predictors for key outcomes in patients with AKI in critically ill patients with sepsis independent of their AKI staging.

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.

Metabolomic profiles of sleep-disordered breathing are associated with hypertension and diabetes mellitus development.

Sleep-disordered breathing (SDB) is a prevalent disorder characterized by recurrent episodic upper airway obstruction. Using data from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), we apply principal component analysis (PCA) to seven SDB-related measures. We estimate the associations of the top two SDB PCs with serum levels of 617 metabolites, in both single-metabolite analysis, and a joint penalized regression analysis. The discovery analysis includes 3299 individuals, with validation in a separate dataset of 1522 individuals. Five metabolite associations with SDB PCs are discovered and replicated. SDB PC1, characterized by frequent respiratory events common in older and male adults, is associated with pregnanolone and progesterone-related sulfated metabolites. SDB PC2, characterized by short respiratory event length and self-reported restless sleep, enriched in young adults, is associated with sphingomyelins. Metabolite risk scores (MRSs), representing metabolite signatures associated with the two SDB PCs, are associated with 6-year incident hypertension and diabetes. These MRSs have the potential to serve as biomarkers for SDB, guiding risk stratification and treatment decisions.

Heterogeneous Effects of CPAP in Non-Sleepy OSA on CVD Outcomes: Post-hoc Machine Learning Analysis of the ISAACC Trial (ECSACT Study).

RATIONALE: Randomized controlled trials of continuous positive airway pressure (CPAP) therapy for cardiovascular disease (CVD) prevention among patients with obstructive sleep apnea (OSA) have been largely neutral. However, given OSA is a heterogeneous disease, there may be unidentified subgroups demonstrating differential treatment effects. OBJECTIVES: Apply a novel data-drive approach to identify non-sleepy OSA subgroups with heterogeneous effects of CPAP on CVD outcomes within the ISAACC study. METHODS: Participants were randomly partitioned into two datasets. One for training (70%) our machine learning model and a second (30%) for validation of significant findings. Model-based recursive partitioning was applied to identify subgroups with heterogeneous treatment effects. Survival analysis was conducted to compare treatment (CPAP versus usual care [UC]) outcomes within subgroups. RESULTS: A total of 1,224 non-sleepy OSA participants were included. Of fifty-five features entered into our model only two appeared in the final model (i.e., average OSA event duration and hypercholesterolemia). Among participants at or below the model-derived average event duration threshold (19.5 seconds), CPAP was protective for a composite of CVD events (training Hazard Ratio [HR] 0.46, p=0.002). For those with longer event duration (>19.5 seconds), an additional split occurred by hypercholesterolemia status. Among participants with longer event duration and hypercholesterolemia, CPAP resulted in more CVD events compared to UC (training HR 2.24, p=0.011). The point estimate for this harmful signal was also replicated in the testing dataset (HR 1.83, p=0.118). CONCLUSIONS: We discovered subgroups of non-sleepy OSA participants within the ISAACC study with heterogeneous effects of CPAP. Among the training dataset, those with longer OSA event duration and hypercholesterolemia had nearly 2.5-times more CVD events with CPAP compared to UC, while those with shorter OSA event duration had roughly half the rate of CVD events if randomized to CPAP.

Analysis by sex of safety and effectiveness of transvenous phrenic nerve stimulation.

PURPOSE: Little is known about sex differences in the treatment of central sleep apnea (CSA). Our post hoc analysis of the remede System Pivotal Trial aimed to determine sex-specific differences in the safety and effectiveness of treating moderate to severe CSA in adults with transvenous phrenic nerve stimulation (TPNS). METHODS: Men and women enrolled in the remede System Pivotal Trial were included in this post hoc analysis of the effect of TPNS on polysomnographic measures, Epworth Sleepiness Scale, and patient global assessment for quality of life. RESULTS: Women (n = 16) experienced improvement in CSA metrics that were comparable to the benefits experienced by men (n = 135), with central apneas being practically eliminated post TPNS. Women experienced improvement in sleep quality and architecture that was comparable to men post TPNS. While women had lower baseline apnea hypopnea index than men, their quality of life was worse at baseline. Additionally, women reported a 25-percentage point greater improvement in quality of life compared to men after 12 months of TPNS therapy. TPNS was found to be safe in women, with no related serious adverse events through 12 months post-implant, while men had a low rate of 10%. CONCLUSION: Although women had less prevalent and less severe CSA than men, they were more likely to report reduced quality of life. Transvenous phrenic nerve stimulation may be a safe and effective tool in the treatment of moderate to severe CSA in women. Larger studies of women with CSA are needed to confirm our findings. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT01816776; March 22, 2013.

Metabolomic Profiles of Sleep-Disordered Breathing are Associated with Hypertension and Diabetes Mellitus Development: the HCHS/SOL.

Sleep-disordered breathing (SDB) is a prevalent disorder characterized by recurrent episodic upper airway obstruction. In a dataset from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), we applied principal component analysis (PCA) on seven measures characterizing SDB-associated respiratory events. We estimated the association of the top two SDB PCs with serum levels of 617 metabolites, in both single-metabolite analysis, and a joint, penalized regression analysis using the least absolute shrinkage and selection operator (LASSO). Discovery analysis included n = 3,299 HCHS/SOL individuals; associations were validated in a separate dataset of n = 1,522 HCHS/SOL individuals. Seven metabolite associations with SDB PCs were discovered and replicated. Metabolite risk scores (MRSs) developed based on LASSO association results and representing metabolite signatures associated with the two SDB PCs were associated with 6-year incident hypertension and incident diabetes. MRSs have the potential to serve as biomarkers for SDB, guiding risk stratification and treatment decisions.

Sleep Irregularity and Subclinical Markers of Cardiovascular Disease: The Multi-Ethnic Study of Atherosclerosis.

Background Sleep irregularity has been linked to incident cardiovascular disease. Less is known about associations of sleep regularity with atherosclerosis. We examined cross-sectional associations of actigraphy-assessed sleep duration and sleep timing regularity with subclinical atherosclerosis in the community-based MESA (Multi-Ethnic Study of Atherosclerosis). Methods and Results MESA Sleep Ancillary Study participants (N=2032; mean age, 68.6±9.2 years; 37.9% White) completed 7-day wrist actigraphy. Participants underwent assessments of coronary artery calcium, carotid plaque presence, carotid intima-media thickness, and the ankle-brachial index. Sleep regularity was quantified by the 7-day with-in person SD of sleep duration and sleep onset timing. Relative risk regression models were used to calculate prevalence ratios and 95% CIs. Models are adjusted for demographics, cardiovascular disease risk factors, and other objectively assessed sleep characteristics including obstructive sleep apnea, sleep duration, and sleep fragmentation. After adjustment, compared with participants with more regular sleep durations (SD ≤60 minutes), participants with greater sleep duration irregularity (SD >120 minutes) were more likely to have high coronary artery calcium burden (>300; prevalence ratio, 1.33 [95% CI, 1.03-1.71]) and abnormal ankle-brachial index (<0.9; prevalence ratio, 1.75 [95% CI, 1.03-2.95]). Compared with participants with more regular sleep timing (SD ≤30 minutes), participants with irregular sleep timing (SD >90 minutes) were more likely to have high coronary artery calcium burden (prevalence ratio, 1.39 [95% CI, 1.07-1.82]). Associations persisted after adjustment for cardiovascular disease risk factors and average sleep duration, obstructive sleep apnea, and sleep fragmentation. Conclusions Sleep irregularity, particularly sleep duration irregularity, was associated with several measures of subclinical atherosclerosis. Sleep regularity may be a modifiable target for reducing atherosclerosis risk. Future investigation into cardiovascular risk reduction interventions targeting sleep irregularity may be warranted.

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.

Sleep apnea and carotid atherosclerosis in the Multi-Ethnic Study of Atherosclerosis (MESA): leveraging state-of-the-art vascular imaging.

PURPOSE: To further characterize the relationship between obstructive sleep apnea (OSA) and carotid atherosclerosis, we examined the structural and metabolic features of carotid plaque using hybrid 18-F-fluorodeoxyglucose (FDG) Positron Emission Tomography/Magnetic Resonance Imaging (PET/MRI) in the Multi-Ethnic Study of Atherosclerosis (MESA). METHODS: We studied 46 individuals from the MESA-PET and MESA-Sleep ancillary studies. OSA was defined as an apnea hypopnea index [AHI] ≥ 15 events per hour (4% desaturation). PET/MRI was used to measure carotid plaque inflammation (using target-to-background-ratios [TBR]) and carotid wall thickness (CWT). Linear regression was used to assess the associations between OSA, CWT and TBR. RESULTS: The mean age was 67.9 years (SD 8.53) and the mean BMI was 28.9 kg/m2 (SD 4.47). There was a trend toward a higher mean CWT in the OSA (n = 11) vs. non-OSA group (n = 35), 1.51 vs. 1.41 (p = 0.098). TBR did not differ by OSA groups, and there was no significant association between OSA and carotid plaque inflammation (TBR) in adjusted analyses. Although there was a significant interaction between OSA and obesity, there were no statistically significant associations between OSA and vascular inflammation in stratified analysis by obesity. CONCLUSION: Despite a trend toward a higher carotid wall thickness in OSA vs. non-OSA participants, we did not find an independent association between OSA and carotid plaque inflammation using PET/MRI in MESA. Our findings suggest that simultaneous assessments of structural and metabolic features of atherosclerosis may fill current knowledge gaps pertaining to the influence of OSA on atherosclerosis prevalence and progression.

Pharyngeal Inflammation on Positron Emission Tomography/Magnetic Resonance Imaging Before and After Obstructive Sleep Apnea Treatment.

Rationale: There is upper airway inflammation in patients with obstructive sleep apnea (OSA), which reduces with continuous positive airway pressure (CPAP) therapy. Objectives: Validate the use of positron emission tomography (PET)/magnetic resonance imaging (MRI) to quantify metabolic activity within the pharyngeal mucosa of patients with OSA against nasal lavage proteomics and assess the impact of CPAP therapy. Methods: Adults with OSA underwent [18F]-Fluoro-2-deoxy-D-glucose PET/MRI of the neck before and 3 months after initiating CPAP. Nasal lavage samples were collected. Inflammatory protein expression from samples was analyzed using the Olink platform. Upper airway imaging segmentation was performed. Target-to-background ratio (TBRmax) was calculated from target pharyngeal maximum standard uptake values (SUV) and personalized background mean SUV. Most-diseased segment TBRmax was identified per participant at locations with the highest PET avidity. Correlation analysis was performed between baseline TBRmax and nasal lavage proteomics. TBRmax was compared before and after CPAP using linear mixed-effect models. Results: Among 38 participants, the baseline mean age was 46.3 years (standard deviation [SD], 12.5), 21% were female, the mean body mass index was 30.9 kg/m2 (SD, 4.6), and the mean respiratory disturbance index measured by peripheral arterial tonometry was 31 events/h (SD, 16.4). There was a significant positive correlation between pharyngeal mucosa most-diseased segment TBRmax and nasal lavage proteomic inflammation (r = 0.41 [P < 0.001, false discovery rate = 0.002]). Primary analysis revealed a reduction in the most-diseased segment TBRmax after a median of 2.91 months of CPAP therapy (-0.86 [standard error (SE) ± 0.30; P = 0.007]). Stratified analysis by smoking status revealed a significantly decreased most-diseased segment TBRmax after CPAP therapy among never-smokers but not among ever-smokers (-1.01 [SE ± 0.39; P = 0.015] vs. -0.64 [SE ± 0.49; P = 0.201]). Conclusions: CPAP therapy reduces metabolic activity measured by PET/MRI within the upper airway of adults with OSA. Furthermore, PET/MRI measures of upper airway metabolic activity correlate with a noninvasive marker of inflammation (i.e., nasal lavage inflammatory protein expression).

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.

Pathway-Specific Polygenic Risk Scores Identify Obstructive Sleep Apnea-Related Pathways Differentially Moderating Genetic Susceptibility to Coronary Artery Disease.

BACKGROUND: Obstructive sleep apnea (OSA) and its features, such as chronic intermittent hypoxia, may differentially affect specific molecular pathways and processes in the pathogenesis of coronary artery disease (CAD) and influence the subsequent risk and severity of CAD events. In particular, competing adverse (eg, inflammatory) and protective (eg, increased coronary collateral blood flow) mechanisms may operate, but remain poorly understood. We hypothesize that common genetic variation in selected molecular pathways influences the likelihood of CAD events differently in individuals with and without OSA, in a pathway-dependent manner. METHODS: We selected a cross-sectional sample of 471 877 participants from the UK Biobank, with 4974 ascertained to have OSA, 25 988 to have CAD, and 711 to have both. We calculated pathway-specific polygenic risk scores for CAD, based on 6.6 million common variants evaluated in the CARDIoGRAMplusC4D genome-wide association study (Coronary ARtery DIsease Genome wide Replication and Meta-analysis [CARDIoGRAM] plus The Coronary Artery Disease [C4D] Genetics), annotated to specific genes and pathways using functional genomics databases. Based on prior evidence of involvement with intermittent hypoxia and CAD, we tested pathway-specific polygenic risk scores for the HIF1 (hypoxia-inducible factor 1), VEGF (vascular endothelial growth factor), NFκB (nuclear factor kappa-light-chain-enhancer of activated B cells) and TNF (tumor necrosis factor) signaling pathways. RESULTS: In a multivariable-adjusted logistic generalized additive model, elevated pathway-specific polygenic risk scores for the Kyoto Encyclopedia of Genes and Genomes VEGF pathway (39 genes) associated with protection for CAD in OSA (interaction odds ratio 0.86, P=6×10-4). By contrast, the genome-wide CAD PRS did not show evidence of statistical interaction with OSA. CONCLUSIONS: We find evidence that pathway-specific genetic risk of CAD differs between individuals with and without OSA in a qualitatively pathway-dependent manner. These results provide evidence that gene-by-environment interaction influences CAD risk in certain pathways among people with OSA, an effect that is not well-captured by the genome-wide PRS. This invites further study of how OSA interacts with genetic risk at the molecular level and suggests eventual personalization of OSA treatment to reduce CAD risk according to individual pathway-specific genetic risk profiles.

Genetic determinants of cardiometabolic and pulmonary phenotypes and obstructive sleep apnoea in HCHS/SOL.

BACKGROUND: Obstructive Sleep Apnoea (OSA) often co-occurs with cardiometabolic and pulmonary diseases. This study is to apply genetic analysis methods to explain the associations between OSA and related phenotypes. METHODS: In the Hispanic Community Healthy Study/Study of Latinos, we estimated genetic correlations ρg between the respiratory event index (REI) and 54 anthropometric, glycemic, cardiometabolic, and pulmonary phenotypes. We used summary statistics from published genome-wide association studies to construct Polygenic Risk Scores (PRSs) representing the genetic basis of each correlated phenotype (ρg>0.2 and p-value<0.05), and of OSA. We studied the association of the PRSs of the correlated phenotypes with both REI and OSA (REI≥5), and the association of OSA PRS with the correlated phenotypes. Causal relationships were tested using Mendelian Randomization (MR) analysis. FINDINGS: The dataset included 11,155 participants, 31.03% with OSA. 22 phenotypes were genetically correlated with REI. 10 PRSs covering obesity and fat distribution (BMI, WHR, WHRadjBMI), blood pressure (DBP, PP, MAP), glycaemic control (fasting insulin, HbA1c, HOMA-B) and insomnia were associated with REI and/or OSA. OSA PRS was associated with BMI, WHR, DBP and glycaemic traits (fasting insulin, HbA1c, HOMA-B and HOMA-IR). MR analysis identified robust causal effects of BMI and WHR on OSA, and probable causal effects of DBP, PP, and HbA1c on OSA/REI. INTERPRETATION: There are shared genetic underpinnings of anthropometric, blood pressure, and glycaemic phenotypes with OSA, with evidence for causal relationships between some phenotypes. FUNDING: Described in Acknowledgments.

Sleep calibrates atherosclerotic cardiovascular disease.

Sleep modulates cardiovascular health, and recent studies have begun to uncover underlying mechanistic links. An integrated translational approach that combines animal models and human trials will enrich scientific discovery, improve therapy, and help to alleviate the global burden of insufficient sleep and cardiovascular disease.

Novel non-invasive assessment of upper airway inflammation in obstructive sleep apnea using positron emission tomography/magnetic resonance imaging.

PURPOSE: To develop a novel non-invasive technique to quantify upper airway inflammation using positron emission tomography/magnetic resonance imaging (PET/MRI) in patients with obstructive sleep apnea (OSA). METHODS: Patients with treatment naïve moderate-to-severe OSA underwent [18F]-fluoro-2-deoxy-D-glucose (FDG) PET/MRI. Three readers independently performed tracings of the pharyngeal soft tissue on MRI. Standardized uptake values (SUV) were generated from region of interest (ROI) tracings on corresponding PET images. Background SUV was measured from the sternocleidomastoid muscle. SUV and target-to-background (TBR) were compared across readers using intraclass correlation coefficient (ICC) analyses. SUV from individual image slices were compared between each reader using Bland-Altman plots and Pearson correlation coefficients. All tracings were repeated by one reader for assessment of intra-reader reliability. RESULTS: Five participants completed our imaging protocol and analysis. Median age, body mass index, and apnea-hypopnea index were 41 years (IQR 40.5-68.5), 32.7 kg/m2 (IQR 28.1-38.1), and 30.7 event per hour (IQR 19.5-48.1), respectively. The highest metabolic activity regions were consistently localized to palatine or lingual tonsil adjacent mucosa. Twenty-five ICC met criteria for excellent agreement. The remaining three were TBR measurements which met criteria for good agreement. Head-to-head comparisons revealed strong correlation between each reader. CONCLUSIONS: Our novel imaging technique demonstrated reliable quantification of upper airway FDG avidity. This technology has implications for future work exploring local airway inflammation in individuals with OSA and exposure to pollutants. It may also serve as an assessment tool for response to OSA therapies.

Measuring Visceral Adipose Tissue Metabolic Activity in Sleep Apnea Utilizing Hybrid 18F-FDG PET/MRI: A Pilot Study.

PURPOSE: Visceral adipose tissue (VAT) is proinflammatory and is associated with cardiovascular (CV) disease. We investigated the relationship between obstructive sleep apnea (OSA) and visceral adipose tissue (VAT) metabolic activity in a pilot group of patients using positron-emission tomography/magnetic resonance imaging (PET/MRI) with 18F-fluorodeoxyglucose (FDG) tracer as a novel marker of adipose tissue inflammation. PATIENTS AND METHODS: We analyzed patients from an ongoing study, recruiting those with newly diagnosed, untreated OSA (Respiratory Disturbance Index [RDI] ≥ 5), using home sleep apnea testing (WatchPAT-200 Central-Plus). PET/MRI scans were acquired before continuous positive airway pressure (CPAP)-initiation, and after 3 months of CPAP therapy. Adipose tissue metabolic activity (18F-FDG-uptake) was measured using standardized uptake values (SUV) within the adipose tissue depots. The primary outcome was VAT SUVmean, and secondary outcomes included VAT volume, and subcutaneous adipose tissue (SAT) volume/SUVmean. Reproducibility and reliability of outcome measures were analyzed using intraclass correlation coefficients (ICC). Multivariable linear regression was used to evaluate the association between OSA and primary/secondary outcomes. RESULTS: Our analytical sample (n = 16) was 81% male (mean age 47 ± 15 years, mean BMI of 29.9 ± 4.8kg/m2). About 56% had moderate to severe OSA (mean RDI 23 ± 6 events/hour), and 50% were adherent to CPAP. We demonstrated excellent inter/intra-rater reliability and reproducibility for the primary and secondary outcomes. Patients with moderate-to-severe OSA had a higher VAT SUV mean compared to those with mild OSA (0.795 ± 0.154 vs 0.602 ± 0.19, p = 0.04). OSA severity was positively associated with VAT SUVmean (primary outcome), adjusted for age and BMI (B [SE] = 0.013 ± 0.005, p = 0.03). Change in VAT volume was inversely correlated with CPAP adherence in unadjusted analysis (B [SE] = -48.4 ± 18.7, p = 0.02). CONCLUSION: Derangements in VAT metabolic activity are implicated in adverse cardiometabolic outcomes and may be one of the key drivers of CV risk in OSA. Our results are hypothesis-generating, and suggest that VAT should be investigated in future studies using multi-modal imaging to understand its role as a potential mediator of adverse cardiometabolic risk in OSA.