Sex-specific association of sleep duration with subclinical indicators of metabolic diseases among asymptomatic adults

Huang, Lili; Long, Zichong; Xu, Gang; Chen, Yi-Ting; Li, Rong; Wang, Yanlin; Li, Shenghui

doi:10.1186/s12944-022-01626-w

Cited by 4 publications

(2 citation statements)

References 65 publications

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“…39 Sex differences have been reported in the associations between sleep duration and adverse health consequences, which may be attributed to sex-specific hormonal and behavioral differences. 40,41 In this study, we detected significant interactions between sleep duration and sex for virus shedding duration. Sleeping <6 h prolonged virus shedding duration in males but not in females, and in patients sleeping <6 h, males presented with a longer virus shedding duration than females.…”

mentioning

confidence: 51%

Short Sleep Duration is Associated with Prolonged Virus Shedding in SARS-CoV-2 Omicron-Infected Patients

Zhou¹,

Liu²,

Wang³

et al. 2023

NSS

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Sleep disturbance has been implicated in poor prognosis of coronavirus disease 2019 (COVID-19), but less is known about the influence of short sleep duration on COVID-19 outcomes. We aim to investigate whether short sleep duration is associated with prolonged virus shedding duration in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron-infected patients. Patients and Methods: A total of 270 patients with a laboratory confirmed COVID-19 diagnosis during SARS-CoV-2 Omicronpredominant period were recruited. Self-reported sleep duration of the patients was collected. The two-way analysis of variance (ANOVA) was used to determine the interactions between sleep duration and variables, and multivariate logistic regression analysis was used to analyze the effect of independent variables on longer virus shedding duration. Results:The two-way ANOVA revealed a significant sleep duration × snoring interaction effect for virus shedding duration, and a sleep duration × sex interaction effect for virus shedding duration. Multivariate logistic regression model illustrated that patients sleeping <6 h were at greater risk of prolonged virus shedding duration compared to those sleeping ≥6 hours (OR = 1.80, 95% CI = 1.01-3.26), independent of age, sex, co-existing diseases, vaccination condition, and antiviral treatment. Conclusion: Short sleep duration (<6 h) was associated with increased virus shedding in SARS-CoV-2 Omicron-infected patients.

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mentioning

confidence: 51%

Short Sleep Duration is Associated with Prolonged Virus Shedding in SARS-CoV-2 Omicron-Infected Patients

Zhou¹,

Liu²,

Wang³

et al. 2023

NSS

View full text Add to dashboard Cite

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“…Disorders of glycolipid metabolism are important mechanisms in the development of hypertension. Patients with sleep disorders often have abnormalities in their nervous and endocrine systems, such as sympathetic nerves and the hypothalamic-pituitary-adrenal axis, which affect the secretion of appetite-regulating hormones and cortisol in the body, thereby reducing the insulin sensitivity of the tissues [38,39] A decrease in glucose utilization causes an increase in the levels of late-phase glycosylation end-products [40], which increase the extracellular matrix area through protein adhesion [41]. The connected collagen is less susceptible to hydrolytic turnover, leading to thickening and sclerosis of the vascular wall [42], which triggers hypertension by decreasing vascular compliance.…”

Section: Discussionmentioning

confidence: 99%

Detection of risk factors of hypertension in people with sleep disorders using machine learning

Wenzhong,

Weixiang,

et al. 2024

Preprint

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Background: Sleep disorders are one of the etiologic factors in the development of hypertension, and the risk of hypertension in patients with sleep disorders is increasing due to the increase in the prevalence of sleep disorders in recent years. We hypothesized that machine learning could establish a prediction model for hypertension in patients with sleep disorders. Methods: The data for patients diagnosed with sleep disorders were collected from two hospitals from 2019 to 2023, including medical history and biochemical indicators. After data processing, Logistic Regression, Decision Tree, Artificial Neural Network, Support Vector Machine, Naive Bayes, Adaptive Boosting, Random Forest, and Extreme Gradient Boosting (XGBoost) were selected for training. Five-fold cross-validation was used to evaluate the models, and accuracy, precision, recall, F1-score, and the area under the curve (AUC) were used to verify the discrimination and clinical practicability of the models. SHapley Additive exPlanation (SHAP) was used to explain the optimal model. Results: The XGBoost model was superior to other models, with an accuracy of 0.7216, a precision of 0.7576, a recall of 0.7660, an F1-score of 0.7430, and an AUC of 0.844. The SHAP results showed that age, weight, white blood cells, creatine, uric acid, glycosylated hemoglobin, and platelets were the risk factors of hypertension in people with sleep disorders, while high density lipoprotein cholesterol was a protective factor. Conclusion: Machine learning algorithms established a predictive risk model of hypertension in people with sleep disorders, which provides significant guidance to prevent and treat hypertension in people with sleep disorders.

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Trimethylamine N-oxide / SREBP2 pathway is involved in sleep deprivation-induced cognitive dysfunction through regulating astrocytic cholesterol metabolism

Zhu,

Wang,

et al. 2023

Preprint

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Sleep deprivation (SD) contributes to cognitive impairment. Astrocytic cholesterol biosynthesis is crucial for brain cholesterol homeostasis and cognitive function. However, the underlying mechanism of astrocytic cholesterol metabolism in SD-induced cognitive impairment has not been fully explored. Trimethylamine N-oxide (TMAO), a product of liver flavin-containing monooxygenase-3 (FMO3), has been shown to be increased in the urine of sleep-deprived humans and implicated with peripheral cholesterol metabolism. Nevertheless, how TMAO affects brain cholesterol metabolism remains unclear. In our study, increased FMO3 and brain TMAO levels were observed in the SD mice and elevated levels of TMAO were confirmed to lead to SD-induced cognitive dysfunction. In addition, we found that the expression of sterol regulatory element-binding protein 2 (SREBP2) is decreased in the brain of SD mice, resulting in the reduction in brain cholesterol synthesis, which in turn causes synaptic damage. Moreover, we demonstrated that TMAO inhibits the expression of SREBP2 by direct action. In contrast, FMO3 inhibitor 3,3'-diindolylmethane (DIM) alleviates SD-induced cognitive impairment by targeting the liver-brain axis. In conclusion, our study revealed that TMAO / SREBP2 pathway is involved in memory impairment in SD mice through deregulating astrocytic cholesterol metabolism.

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Sex-specific association of sleep duration with subclinical indicators of metabolic diseases among asymptomatic adults

Cited by 4 publications

References 65 publications

Short Sleep Duration is Associated with Prolonged Virus Shedding in SARS-CoV-2 Omicron-Infected Patients

Short Sleep Duration is Associated with Prolonged Virus Shedding in SARS-CoV-2 Omicron-Infected Patients

Detection of risk factors of hypertension in people with sleep disorders using machine learning

Trimethylamine N-oxide / SREBP2 pathway is involved in sleep deprivation-induced cognitive dysfunction through regulating astrocytic cholesterol metabolism

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