Alterations in sympathetic and parasympathetic brain networks in obstructive sleep apnea

Lin, Wei-Che; Hsu, Tun-Wei; Lu, Cheng-Hsien; Chen, Hsiu-Ling

doi:10.1016/j.sleep.2020.05.038

Cited by 4 publications

(3 citation statements)

References 40 publications

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“…Our previous study found reduced DMN network connectivity and topological reorganization in patients with OSA ( Li H. J. et al, 2016 ; Chen et al, 2018 ), which may underlie the cognitive deficits in patients with OSA. Some scholars have also found that the FC of the SN, bilateral ECN and DMN in OSA patients is decreased, which is related to autonomic disorders, suggesting that autonomic dysfunction in OSA is associated with central autonomic network alterations ( Lin et al, 2020 ). Similar to these findings, this study found that OSA patients had lower connections within the SN and ECN, and internetwork connections between the DMN, ECN and SN, indicating that FNC was separated and integration ability decreased, which may be the basis of advanced cognitive impairment in OSA patients, and further supplemented the mechanism of cognitive impairment in OSA from a dynamic perspective of OSA patients.…”

Section: Discussionmentioning

confidence: 99%

Abnormal dynamic functional network connectivity in male obstructive sleep apnea with mild cognitive impairment: A data-driven functional magnetic resonance imaging study

Li²,

Li³

et al. 2022

Front. Aging Neurosci.

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ObjectiveThe purpose of this study was to investigate the dynamic functional network connectivity (FNC) and its relationship with cognitive function in obstructive sleep apnea (OSA) patients from normal cognition (OSA-NC) to mild cognitive impairment (OSA-MCI).Materials and methodsEighty-two male OSA patients and 48 male healthy controls (HC) were included in this study. OSA patients were classified to OSA-MCI (n = 41) and OSA-NC (n = 41) based on cognitive assessments. The independent component analysis was used to determine resting-state functional networks. Then, a sliding-window approach was used to construct the dynamic FNC, and differences in temporal properties of dynamic FNC and functional connectivity strength were compared between OSA patients and the HC. Furthermore, the relationship between temporal properties and clinical assessments were analyzed in OSA patients.ResultsTwo different connectivity states were identified, namely, State I with stronger connectivity and lower frequency, and State II with lower connectivity and relatively higher frequency. Compared to HC, OSA patients had a longer mean dwell time and higher fractional window in stronger connectivity State I, and opposite result were found in State II, which was mainly reflected in OSA-MCI patients. The number of transitions was an increasing trend and positively correlated with cognitive assessment in OSA-MCI patients. Compared with HC, OSA patients showed extensive abnormal functional connectivity in stronger connected State I and less reduced functional connectivity in lower connected State II, which were mainly located in the salience network, default mode network, and executive control network.ConclusionOur study found that OSA patients showed abnormal dynamic FNC properties, which was a continuous trend from HC, and OSA-NC to OSA-MCI, and OSA patients showed abnormal dynamic functional connectivity strength. The number of transformations was associated with cognitive impairment in OSA-MCI patients, which may provide new insights into the neural mechanisms in OSA patients.

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Section: Discussionmentioning

confidence: 99%

Abnormal dynamic functional network connectivity in male obstructive sleep apnea with mild cognitive impairment: A data-driven functional magnetic resonance imaging study

Li²,

Li³

et al. 2022

Front. Aging Neurosci.

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“…Sleep related disease may also be related to neurodegeneration. Indeed, obstructive sleep apnea (OSA) is associated both with increases in blood markers associated with the development of AD (33) and with reduced FC in cognitively normal adults (34,35) but not those with mild cognitive impairment (35). Speci c resting state networks are implicated in cognitive aging.…”

Section: Introductionmentioning

confidence: 99%

Cardiovascular Fitness and Sleep, but not Physical Activity, are Associated with Improved Brain Functional Connectivity in Older Adults.

Wing,

Roelands,

Wetherell

et al. 2024

Preprint

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Background Aging results in changes in resting state functional connectivity within key networks associated with cognition. Cardiovascular function, physical activity, sleep, and body composition may influence these age-related changes in the brain. Better understanding these associations may help clarify mechanisms related to brain aging and guide interventional strategies to reduce these changes. In a large (n = 398) sample of healthy community dwelling older adults we conducted cross sectional analyses of the relationship between several modifiable behaviors and resting state functional connectivity within the brain in key regions associated with cognition and emotional regulation. Additionally, maximal aerobic capacity with a graded exercise test, physical activity and sleep with accelerometers, and body composition with dual energy x-ray absorptiometry were assessed. Associations were explored both through correlation and best vs. worst group comparisons. Results Greater cardiovascular fitness, but not larger volume of daily physical activity, was associated with greater connectivity within the Default Monde and Salience Networks, both of which are key networks associated with aging. Better sleep, in terms of increased total sleep time, higher sleep efficiency and fewer nighttime awakenings was also associated with greater connectivity within multiple networks including the Default Mode, Executive Control, and Salience Networks. Higher body fat percentage was associated with increased connectivity in the Dorsal Attentional Network. Conclusion These findings confirm and expand on previous work indicating that, in older adults, higher levels of cardiovascular fitness and better sleep in terms of greater efficiency and less total awakenings, but not greater volume of physical activity or lower volume of body fat are associated with increased functional connectivity within key brain regions. Also, assessing sleep quality and quantity may be a useful tool for identifying potentially clinically meaningful declines in brain function.

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“…Several therapeutic approaches have been applied to address CSA and OSA, but none of these pharmacologic interventions have been shown to significantly improve patients' prognoses for HF [6][7][8][9]. Due to its correlation with poorer left ventricular function and an advanced New York Heart Association (NYHA) class [10], CSA seems to be a significant indication of HF severity, despite OSA being considered an independent risk factor augmenting HF morbidity and death [11][12][13][14][15][16][17], while the benefits of non-invasive ventilation (NIV) for CSA therapy in HF are still debatable [18][19][20], as suggested by the findings of both SERVE-HF [21] and ADVENT-HF [22] randomized clinical trials. Sodium-glucose cotransporter 2 inhibitors (SGLT2i) lower blood glucose levels inhibiting SGLT2 in the renal tubules; however, despite some intriguing hypotheses, the main mechanisms underlying its cardioprotective effects are largely unknown.…”

Section: Introductionmentioning

confidence: 99%

Effect of SGLT2-Inhibitors on Polygraphic Parameters in Elderly Patients Affected by Heart Failure, Type 2 Diabetes Mellitus, and Sleep Apnea

Armentaro,

Pelaia,

Condoleo

et al. 2024

Biomedicines

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Obstructive sleep apneas (OSAs) and central sleep apneas (CSAs) are the most common comorbidities in Heart Failure (HF) that are strongly associated with all-cause mortality. Several therapeutic approaches have been used to treat CSA and OSA, but none have been shown to significantly improve HF prognosis. Our study evaluated the effects of a 3-months treatment with sodium-glucose cotransporter type 2 inhibitor (SGLT2i) on polygraphic parameters in patients with sleep apnea (SA) and HF, across the spectrum of ejection fraction, not treated with continuous positive air pressure (CPAP). A group of 514 consecutive elderly outpatients with HF, type 2 diabetes mellitus (T2DM) and SA, eligible for treatment with SGLT2i, were included in the investigation before starting any CPAP therapy. The two groups were compared with the t-test and Mann–Whitney test for unpaired data when appropriate. Then, a simple logistic regression model was built using 50% reduction in AHI as the dependent variable and other variables as covariates. A multivariate stepwise logistic regression model was constructed using the variables that linked with the dependent variable to calculate the odds ratio (OR) for the independent predictors associated with the reduction of 50% in AHI. The treated group experienced significant improvements in polygraphic parameters between baseline values and follow-up with reduction in AHI (28.4 ± 12.9 e/h vs. 15.2 ± 6.5 e/h; p < 0.0001), ODI (15.4 ± 3.3 e/h vs. 11.1 ± 2.6 e/h; p < 0.0001), and TC90 (14.1 ± 4.2% vs. 8.2 ± 2.0%; p < 0.0001), while mean SpO2 improved (91. 3 ± 2.3 vs. 93.8 ± 2.5); p < 0.0001. These benefits were not seen in the untreated population. The use of SGLT2i in patients suffering from HF and mixed-type SA not on CPAP therapy significantly contributes to improving polygraphic parameters.

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Alterations in sympathetic and parasympathetic brain networks in obstructive sleep apnea

Cited by 4 publications

References 40 publications

Abnormal dynamic functional network connectivity in male obstructive sleep apnea with mild cognitive impairment: A data-driven functional magnetic resonance imaging study

Abnormal dynamic functional network connectivity in male obstructive sleep apnea with mild cognitive impairment: A data-driven functional magnetic resonance imaging study

Cardiovascular Fitness and Sleep, but not Physical Activity, are Associated with Improved Brain Functional Connectivity in Older Adults.

Effect of SGLT2-Inhibitors on Polygraphic Parameters in Elderly Patients Affected by Heart Failure, Type 2 Diabetes Mellitus, and Sleep Apnea

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