Metabolites May Predict Risk of Developing Diabetes in Patients With Sleep-Disordered Breathing

News
Article

In some instances, metabolites can predict risk in patients who still have normal glucose biomarkers.

Estimates suggest that 17% of women and 34% of men in middle age suffer from sleep-disordered breathing (SDB), a condition that leads to upper airway obstruction during sleep. Results from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) study suggests that certain metabolite risk scores (MRSs) may be associated with diabetes mellitus (DM), according to investigators who published their findings in Nature Communications.

“These MRSs have the potential to serve as biomarkers for SDB, guiding risk stratification and treatment decisions,” wrote the study authors.

SDB occurs when the airways become partially or completely obstructed during sleep (called apneas and hypopneas, respectively). This can worsen sleep quality, reduce oxyhemoglobin desaturation, and can lead to short-term snoring and excessive daytime sleepiness.

In addition, an increasing amount of evidence from epidemiological studies suggests that SDB can also increase a person’s risk of vascular and metabolic diseases (eg, stroke, coronary heart disease, hypertension, and DM).

Understanding metabolites (ie, products of metabolism) during SDB “may yield insights into the metabolic environment of the disorder, elucidate sex differences, and suggest SDB subtypes and related molecular mechanisms involved in the progression of cardiometabolic conditions,” study authors write in the paper.

Knowing this, investigators conducted a discovery-replication study to understand if combining SDB measures and changes in SBD-related metabolites could be used to identify new SDB biomarkers that predict metabolic risk.

Image credit: sbw19 | stock.adobe.com

Image credit: sbw19 | stock.adobe.com

The team used principal component (PC) analysis to look at the physiological phenotypes of different types of SDB, then evaluated the metabolites associated with SDB PCs to create SDB PC-specific metabolite risk scores.

Data were collected pertaining to the 3299 individuals who participated in the HCHS/SOL study.Individuals were characterized by phenotype of SDB—people with PC1 had frequent respiratory events and hypoxia events, and patients with PC2 had shorter respiratory events.

Metabolic scores were associated with accurate prediction of cardiometabolic outcomes. PC1 had a higher association with incident diabetes and hypertension over approximately 6 years on average. Individuals with PC1 were more likely to be men, while individuals with SDB PC2 were more likely to include younger women, people with severe insomnia, and self-reported poor sleep, increased awakenings, and longer sleep duration.

Among patients with PC1, higher concentrations of sulfated metabolites of progesterone and pregnenolone were associated with reduced risk of poor outcomes. Among patients with SDB PC2, the risk of incident outcomes was associated with concentration of 3 sphingomyelins (a component of plasma membrane), although it was not statically significant.

“Dysregulation of sphingomyelin has been implicated in immune regulation, inflammation and apoptosis, and acute and chronic lung pathology,” study authors wrote.

In a secondary analysis, investigators stratified patients by glucose regulation. Patients with SDB PC1 who had normal glucose regulation did not have an elevated risk of developing diabetes compared to those with impaired glucose regulation, according to the SDB PC1 MRS; however, patients with SDB PC2 and normal glucose regulation may have a higher risk of developing diabetes, according to the SDB PC2 MRS, which makes it a promising tool for identifying risk.

According to the study authors, come limitations of the study include not analyzing results in other populations, using PCA analysis, not basing phenotypes as new clinical measures, information loss, and using observational measures, which limits the ability to determine causation.

“These findings provide a strong basis for the use of metabolomics in studying SDB, including for clarifying and measuring risks for incident outcomes by different quantitative SDB phenotypes and dichotomous subtypes,” study authors wrote in the paper.

REFERENCE

Zhang Y, Yu B, Qi Q, et al. Metabolomic profiles of sleep-disordered breathing are associated with hypertension and diabetes mellitus development. Nat Commun 15, 1845 (2024). doi:10.1038/s41467-024-46019-y

Related Videos
© 2024 MJH Life Sciences

All rights reserved.