Polysomnographic Phenotypes of Obstructive Sleep Apnea and Incident Type 2 Diabetes: Results from the DREAM Study

Ding, Qinglan; Li, Qin; Wojeck, Brian S.; Inzucchi, Silvio E.; Ibrahim, A.; Bravata, Dawn M.; Yaggi, H. Klar; Zinchuk, Andrey

doi:10.1513/annalsats.202012-1556oc

Cited by 18 publications

(7 citation statements)

References 57 publications

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“…In the study carried out by Ding et al. ( 38 ) mentioned above, patients with “PLMS” phenotype, which was another marker of sympathetic activation, independently predict risk of T2DM. However, they were unable to find similar result in patients with “arousal and poor sleep” phenotype.…”

Section: Discussionmentioning

confidence: 98%

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Shorter respiratory event duration is related to prevalence of type 2 diabetes

Guo

Dai²,

Luo³

et al. 2023

Front. Endocrinol.

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BackgroundObstructive sleep apnea (OSA) is a heterogeneous sleep disorder often comorbid with metabolic diseases, and type 2 diabetes (T2DM) is one of them. Although apnea hypopnea index (AHI) is currently the diagnostic criteria for OSA severity, a controversial relationship between AHI and T2DM has been found. On the other hand, the duration of apnea–hypopnea events has been shown to be a useful metric for predicting mortality. This study aimed to test whether average respiratory event duration was associated with prevalence of T2DM.MethodsPatients referred to the sleep clinic were recruited in the study. Baseline clinical characteristics and polysomnography parameters including average respiratory event duration were collected. The association of average respiratory event duration with the prevalence of T2DM was evaluated by univariate and multivariate logistic regression analyses.ResultsA total of 260 participants were enrolled, and 92 (35.4%) had T2DM. Univariate analysis revealed that age, body mass index (BMI), total sleep time, sleep efficiency, history of hypertension, and shorter average respiratory event duration were associated with T2DM. In multivariate analysis, only age and BMI remained significant. While average respiratory event duration was insignificant in multivariate analysis, subtype event analysis showed that shorter average apnea duration was both significant in univariate (OR, 0.95; 95% CI, 0.92–0.98) and multivariate analyses (OR, 0.95; 95% CI, 0.91–0.99). Neither average hypopnea duration nor AHI was associated with T2DM. Significant association (OR, 1.19; 95% CI, 1.12–1.25) was observed between shorter average apnea duration and lower respiratory arousal threshold after multivariate adjustment. However, causal mediation analysis revealed no mediating effect of arousal threshold on average apnea duration and T2DM.ConclusionThe average apnea duration may be a useful metric in the diagnosis of OSA comorbidity. Shorter average apnea duration indicating poor sleep quality and augmented autonomic nervous system responses might be the potential pathological mechanisms leading to T2DM.

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Section: Discussionmentioning

confidence: 98%

“…Besides these traditional metrics, Ding et al. ( 38 ) identified certain phenotypes of OSA based on cluster analysis using PSG data. In comparison to AHI, PSG phenotypes improved T2DM risk prediction.…”

Section: Discussionmentioning

confidence: 99%

Shorter respiratory event duration is related to prevalence of type 2 diabetes

Guo

Dai²,

Luo³

et al. 2023

Front. Endocrinol.

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“…The increased diabetes risk among older adults in cluster 3 could be attributed to potential factors such as poor sleep quality, where the proportion of stage N1 and N2 sleep increases, while stage N3 deep sleep slow wave sleep decreases with age, and time awake after sleep onset tends to rise 42. Moreover, obstructive sleep apnea, which is more prevalent in individuals with long sleep duration, is known to be associated with an increased risk of incident diabetes 43 44. Additionally, altered levels of leptin and ghrelin, and their impact on appetite and glycemic control, may contribute to the heightened type 2 diabetes risk in cluster 3, particularly as these older adults were the least physically active 43 45.…”

Section: Discussionmentioning

confidence: 99%

Uncovering heterogeneous cardiometabolic risk profiles in US adults: the role of social and behavioral determinants of health

Ding,

Lu,

Herrin

et al. 2023

BMJ Open Diab Res Care

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IntroductionSocial and behavioral determinants of health (SBDH) have been linked to diabetes risk, but their role in explaining variations in cardiometabolic risk across race/ethnicity in US adults is unclear. This study aimed to classify adults into distinct cardiometabolic risk subgroups using SBDH and clinically measured metabolic risk factors, while comparing their associations with undiagnosed diabetes and pre-diabetes by race/ethnicity.Research design and methodsWe analyzed data from 38,476 US adults without prior diabetes diagnosis from the National Health and Nutrition Examination Survey (NHANES) 1999–2018. The k-prototypes clustering algorithm was used to identify subgroups based on 16 SBDH and 13 metabolic risk factors. Each participant was classified as having no diabetes, pre-diabetes or undiagnosed diabetes using contemporaneous laboratory data. Logistic regression was used to assess associations between subgroups and diabetes status, focusing on differences by race/ethnicity.ResultsThree subgroups were identified: cluster 1, primarily middle-aged adults with high rates of smoking, alcohol use, short sleep duration, and low diet quality; cluster 2, mostly young non-white adults with low income, low health insurance coverage, and limited healthcare access; and cluster 3, mostly older males who were the least physically active, but with high insurance coverage and healthcare access. Compared with cluster 2, adjusted ORs (95% CI) for undiagnosed diabetes were 14.9 (10.9, 20.2) in cluster 3 and 3.7 (2.8, 4.8) in cluster 1. Clusters 1 and 3 (vs cluster 2) had high odds of pre-diabetes, with ORs of 1.8 (1.6, 1.9) and 2.1 (1.8, 2.4), respectively. Race/ethnicity was found to modify the relationship between identified subgroups and pre-diabetes risk.ConclusionsSelf-reported SBDH combined with metabolic factors can be used to classify adults into subgroups with distinct cardiometabolic risk profiles. This approach may help identify individuals who would benefit from screening for diabetes and pre-diabetes and potentially suggest effective prevention strategies.

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“…Meanwhile, categorized AHI was not associated with increased CVD risk. 44,45 These subtypes may represent certain pathophysiological characteristics including hypoxemia and sympathetic activation and were superior in predicting OSA comorbidities comparing to AHI. The utility of unsupervised learning method with abundant PSG information could serve as an important clinical guidance towards OSA evaluation.…”

Section: Cluster Analysismentioning

confidence: 99%

New Metrics from Polysomnography: Precision Medicine for OSA Interventions

Guo¹,

Xiao²

2023

NSS

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Obstructive sleep apnea (OSA) is a highly preventable disease accompanied by multiple comorbid conditions. Despite the well-established cardiovascular and neurocognitive sequelae with OSA, the optimal metric for assessing the OSA severity and response to therapy remains controversial. Although overnight polysomnography (PSG) is the golden standard for OSA diagnosis, the abundant information is not fully exploited. With the development of deep learning and the era of big data, new metrics derived from PSG have been validated in some OSA consequences and personalized treatment. In this review, these metrics are introduced based on the pathophysiological mechanisms of OSA and new technologies. Emphasis is laid on the advantages and the prognostic value against apnea-hypopnea index. New classification criteria should be established based on these metrics and other clinical characters for precision medicine.

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Polysomnographic Phenotypes of Obstructive Sleep Apnea and Incident Type 2 Diabetes: Results from the DREAM Study

Cited by 18 publications

References 57 publications

Shorter respiratory event duration is related to prevalence of type 2 diabetes

Shorter respiratory event duration is related to prevalence of type 2 diabetes

Uncovering heterogeneous cardiometabolic risk profiles in US adults: the role of social and behavioral determinants of health

New Metrics from Polysomnography: Precision Medicine for OSA Interventions

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