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

Phenome-wide associations of sleep characteristics in the Human Phenotype Project

Sleep tests commonly diagnose sleep disorders, but the diverse sleep-related biomarkers recorded by such tests can also provide broader health insights. In this study, we leveraged the uniquely comprehensive data from the Human Phenotype Project cohort, which includes 448 sleep characteristics collected from 16,812 nights of home sleep apnea test monitoring in 6,366 adults (3,043 male and 3,323 female participants), to study associations between sleep traits and body characteristics across 16 body systems. In this analysis, which identified thousands of significant associations, visceral adipose tissue (VAT) was the body characteristic that was most strongly correlated with the peripheral apnea-hypopnea index, as adjusted by sex, age and body mass index (BMI). Moreover, using sleep characteristics, we could predict over 15% of body characteristics, spanning 15 of the 16 body systems, in a held-out set of individuals. Notably, sleep characteristics contributed more to the prediction of certain insulin resistance, blood lipids (such as triglycerides) and cardiovascular measurements than to the characteristics of other body systems. This contribution was independent of VAT, as sleep characteristics outperformed age, BMI and VAT as predictors for these measurements in both male and female participants. Gut microbiome-related pathways and diet (especially for female participants) were notably predictive of clinical obstructive sleep apnea symptoms, particularly sleepiness, surpassing the prediction power of age, BMI and VAT on these symptoms. Together, lifestyle factors contributed to the prediction of over 50% of the sleep characteristics. This work lays the groundwork for exploring the associations of sleep traits with body characteristics and developing predictive models based on sleep monitoring.

Untargeted metabolome atlas for sleep-related phenotypes in the Hispanic community health study/study of Latinos

BACKGROUND

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-related phenotypes and blood metabolites.

METHODS

Utilising data from the Hispanic Community Health Study/Study of Latinos, we performed association analyses between 40 sleep-related phenotypes, grouped in several domains (sleep disordered breathing (SDB), sleep duration, sleep timing, self-reported insomnia symptoms, excessive daytime sleepiness (EDS), and heart rate during sleep), and 768 metabolites measured via untargeted metabolomics profiling. Network analysis was employed to visualise and interpret the associations between sleep phenotypes and metabolites.

FINDINGS

The patterns of statistically significant associations between sleep phenotypes and metabolites differed by superpathways, and highlighted subpathways of interest for future studies. For example, primary bile acid metabolism showed the highest cumulative percentage of statistically significant associations across all sleep phenotype domains except for SDB and EDS phenotypes. Several metabolites were associated with multiple sleep phenotypes, from a few domains. Glycochenodeoxycholate, vanillyl mandelate (VMA) and 1-stearoyl-2-oleoyl-GPE (18:0/18:1) were associated with the highest number of sleep phenotypes, while pregnenolone sulfate was associated with all sleep phenotype domains except for sleep duration. N-lactoyl amino acids such as N-lactoyl phenylalanine (lac-Phe), were associated with sleep duration, SDB, sleep timing and heart rate during sleep.

INTERPRETATION

This atlas of sleep-metabolite associations will facilitate hypothesis generation and further study of the metabolic underpinnings of sleep health.

FUNDING

R01HL161012, R35HL135818, R01AG80598.

Sleep Apnea and Amyotrophic Lateral Sclerosis: Cause, Correlation, Any Relation?

Amyotrophic lateral sclerosis (ALS) is a motor neuron disease with progressive neurodegeneration, affecting both the cortical and the spinal component of the motor neuron circuitry in patients. The cellular and molecular basis of selective neuronal vulnerability is beginning to emerge. Yet, there are no effective cures for ALS, which affects more than 200,000 people worldwide each year. Recent studies highlight the importance of the glymphatic system and its proper function for the clearance of the cerebral spinal fluid, which is achieved mostly during the sleep period. Therefore, a potential link between problems with sleep and neurodegenerative diseases has been postulated. This paper discusses the present understanding of this potential correlation.

Steroid Hormone Biosynthesis and Dietary Related Metabolites Associated with Excessive Daytime Sleepiness

Background

Excessive daytime sleepiness (EDS) is a complex sleep problem that affects approximately 33% of the United States population. Although EDS usually occurs in conjunction with insufficient sleep, and other sleep and circadian disorders, recent studies have shown unique genetic markers and metabolic pathways underlying EDS. Here, we aimed to further elucidate the biological profile of EDS using large scale single- and pathway-level metabolomics analyses.

Methods

Metabolomics data were available for 877 metabolites in 6,071 individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) and EDS was assessed using the Epworth Sleepiness Scale (ESS) questionnaire. We performed linear regression for each metabolite on continuous ESS, adjusting for demographic, lifestyle, and physiological confounders, and in sex specific groups. Subsequently, gaussian graphical modelling was performed coupled with pathway and enrichment analyses to generate a holistic interactive network of the metabolomic profile of EDS associations.

Findings

We identified seven metabolites belonging to steroids, sphingomyelin, and long chain fatty acids sub-pathways in the primary model associated with EDS, and an additional three metabolites in the male-specific analysis. The identified metabolites particularly played a role in steroid hormone biosynthesis.

Interpretation

Our findings indicate that an EDS metabolomic profile is characterized by endogenous and dietary metabolites within the steroid hormone biosynthesis pathway, with some pathways that differ by sex. Our findings identify potential pathways to target for addressing the causes or consequences of EDS and related sleep disorders.

Funding

Details regarding funding supporting this work and all studies involved are provided in the acknowledgments section.

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.

SGLT1 and SGLT2 inhibition, circulating metabolites, and cerebral small vessel disease: a mediation Mendelian Randomization study

BACKGROUND

Sodium-glucose cotransporter 2 (SGLT2) and SGLT1 inhibitors may have additional beneficial metabolic effects on circulating metabolites beyond glucose regulation, which could contribute to a reduction in the burden of cerebral small vessel disease (CSVD). Accordingly, we used Mendelian Randomization (MR) to examine the role of circulating metabolites in mediating SGLT2 and SGLT1 inhibition in CSVD.

METHODS

Genetic instruments for SGLT1/2 inhibition were identified as genetic variants, which were both associated with the expression of encoding genes of SGLT1/2 inhibitors and glycated hemoglobin A1c (HbA1c) level. A two-sample two-step MR was used to determine the causal effects of SGLT1/2 inhibition on CSVD manifestations and the mediating effects of 1400 circulating metabolites linking SGLT1/2 inhibition with CSVD manifestations.

RESULTS

A lower risk of deep cerebral microbleeds (CMBs) and small vessel stroke (SVS) was linked to genetically predicted SGLT2 inhibition. Better white matter structure integrity was also achieved, as evidenced by decreased mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), as well as lower deep (DWMH) and periventrivular white matter hyperintensity (PWMH) volume. Inhibiting SGLT2 could also lessen the incidence of severe enlarged perivascular spaces (EPVS) located at white matter, basal ganglia (BG) and hippocampus (HIP). SGLT1 inhibition could preserve white matter integrity, shown as decreased MD of white matter and DWMH volume. The effect of SGLT2 inhibition on SVS and MD of white matter through the concentration of 4-acetamidobutanoate and the cholesterol to oleoyl-linoleoyl-glycerol (18:1 to 18:2) ratio, with a mediated proportion of 30.3% and 35.5% of the total effect, respectively.

CONCLUSIONS

SGLT2 and SGLT1 inhibition play protective roles in CSVD development. The SGLT2 inhibition could lower the risk of SVS and improve the integrity of white matter microstructure via modulating the level of 4-acetamidobutanoate and cholesterol metabolism. Further mechanistic and clinical studies research are needed to validate our findings.

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.

Anaerobic pathogens associated with OSA may contribute to pathophysiology via amino-acid depletion

BACKGROUND

The human microbiome is linked to multiple metabolic disorders such as obesity and diabetes. Obstructive sleep apnoea (OSA) is a common sleep disorder with several metabolic risk factors. We investigated the associations between the gut microbiome composition and function, and measures of OSA severity in participants from a prospective community-based cohort study: the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).

METHODS

Bacterial-Wide Association Analysis (BWAS) of gut microbiome measured via metagenomics with OSA measures was performed adjusting for clinical, lifestyle and co-morbidities. This was followed by functional analysis of the OSA-enriched bacteria. We utilized additional metabolomic and transcriptomic associations to suggest possible mechanisms explaining the microbiome effects on OSA.

FINDINGS

Several uncommon anaerobic human pathogens were associated with OSA severity. These belong to the Lachnospira, Actinomyces, Kingella and Eubacterium genera. Functional analysis revealed enrichment in 49 processes including many anaerobic-related ones. Severe OSA was associated with the depletion of the amino acids glycine and glutamine in the blood, yet neither diet nor gene expression revealed any changes in the production or consumption of these amino acids.

INTERPRETATION

We show anaerobic bacterial communities to be a novel component of OSA pathophysiology. These are established in the oxygen-poor environments characteristic of OSA. We hypothesize that these bacteria deplete certain amino acids required for normal human homeostasis and muscle tone, contributing to OSA phenotypes. Future work should test this hypothesis as well as consider diagnostics via anaerobic bacteria detection and possible interventions via antibiotics and amino-acid supplementation.

FUNDING

Described in methods.

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.

Influence of glutamatergic and GABAergic neurotransmission on obstructive sleep apnea

Glutamate and γ-aminobutyric acid (GABA) are the two main neurotransmitters in the human brain. The balance between their excitatory and inhibitory functions is crucial for maintaining the brain's physiological functions. Disturbance of glutamatergic or GABAergic neurotransmission leads to serious health problems including neurodegeneration, affective and sleep disorders. Both GABA and glutamate are involved in the control of the sleep-wake cycle. The disturbances in their function may cause sleep and sleep-related disorders. Obstructive sleep apnea (OSA) is the most common sleep respiratory disorder and is characterized by repetitive collapse of the upper airway resulting in intermittent hypoxia and sleep fragmentation. The complex pathophysiology of OSA is the basis of the development of numerous comorbid diseases. There is emerging evidence that GABA and glutamate disturbances may be involved in the pathogenesis of OSA, as well as its comorbidities. Additionally, the GABA/glutamate targeted pharmacotherapy may also influence the course of OSA, which is important in the implementation of wildly used drugs including benzodiazepines, anesthetics, and gabapentinoids. In this review, we summarize current knowledge on the influence of disturbances in glutamatergic and GABAergic neurotransmission on obstructive sleep apnea.