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Prebiotics, Probiotics, and Acetate Supplementation Prevent Hypertension in a Model of Obstructive Sleep Apnea.

ABSTRACT: Disruption of the gut microbiota, termed gut dysbiosis, has been described in animal models of hypertension and hypertensive patients. We have shown that gut dysbiosis plays a causal role in the development of hypertension in a rat model of obstructive sleep apnea (OSA). Functional analysis of the dysbiotic microbiota in OSA demonstrates a loss of short chain fatty acid-producing bacteria. However, measurements of short chain fatty acid concentrations and testing of their role in blood pressure regulation are lacking. We hypothesized that reduced short chain fatty acids in the gut are responsible for OSA-induced hypertension. OSA significantly increased systolic blood pressure at 7 and 14 days ( P<0.05), an effect that was abolished by the probiotic Clostridium butyricum or the prebiotic Hylon VII. The 16S rRNA analysis identified several short chain fatty acid-producing bacteria that were significantly increased by Cbutyricum and Hylon treatment. Acetate concentration in the cecum was decreased by 48% after OSA ( P<0.05), an effect that was prevented by Cbutyricum and Hylon. Cbutyricum and Hylon reduced OSA-induced dysbiosis, epithelial goblet cell loss, mucus barrier thinning, and activation of brain microglia ( P<0.05 for each). To examine the role of acetate in OSA-induced hypertension, we chronically infused acetate into the cecum during 2 weeks of sham or OSA. Restoring cecal acetate concentration prevented OSA-induced gut inflammation and hypertension ( P<0.05). These studies identify acetate as a key player in OSA-induced hypertension. We demonstrate that various methods to increase cecal acetate concentrations are protective from the adverse effects of OSA on the microbiota, gut, brain, and blood pressure.

SUBMITTER: Ganesh BP

PROVIDER: S-EPMC6209125 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Prebiotics, Probiotics, and Acetate Supplementation Prevent Hypertension in a Model of Obstructive Sleep Apnea.

Ganesh Bhanu P BP Nelson James W JW Eskew Joshua R JR Ganesan Arunkumar A Ajami Nadim J NJ Petrosino Joseph F JF Bryan Robert M RM Durgan David J DJ

Hypertension (Dallas, Tex. : 1979) 20181101 5

Disruption of the gut microbiota, termed gut dysbiosis, has been described in animal models of hypertension and hypertensive patients. We have shown that gut dysbiosis plays a causal role in the development of hypertension in a rat model of obstructive sleep apnea (OSA). Functional analysis of the dysbiotic microbiota in OSA demonstrates a loss of short chain fatty acid-producing bacteria. However, measurements of short chain fatty acid concentrations and testing of their role in blood pressure ...[more]

PMID: 30354816

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Project description:Due to its effects, like an exaggerated negative intrathoracic pressure, sympathetic activation, systemic inflammation, oxidative stress, and endothelial dysfunction, obstructive sleep apnea (OSA) has been involved as a cause in multiple cardiovascular diseases. These diseases include coronary artery disease, hypertension, heart failure, and pulmonary hypertension (PH). Furthermore, OSA often coexists with chronic thromboembolic pulmonary hypertension (CTEPH) in clinical practice. However, few studies focus on OSA and its relationship with CTEPH. This study aims to determine whether OSA has an influence on the clinic status of patients with CTEPH, and to identify what possible factors are associated with OSA in CTEPH. Patients who were newly diagnosed with CTEPH and received overnight polysomnography (PSG) monitoring from September 2015 to December 2017 were enrolled. OSA was defined as apnea-hypopnea index (AHI) of ?5/h and the obstructive events at ?50%. Baseline clinical characteristics and parameters were collected and compared between CTEPH patients with and without OSA. In addition, logistic regression analysis was performed to identify possible factors associated with OSA in CTEPH. Fifty-seven patients with CTEPH were eventually enrolled. Among them, 32 patients were diagnosed with OSA by PSG. CTEPH patients with OSA showed an older age, a higher body mass index (BMI), a higher hemoglobin level, a lower oxygen saturation and a worse World Health Organization functional class (WHO FC) (all P<0.05) when compared to CTEPH patients without OSA. In addition, sleep data including AHI, oxygen desaturation index and minimum oxygen saturation were also statistically different between two groups (all P<0.05). Adjusted for age, sex and BMI, hemoglobin [odd ratio (OR) =1.057, 95% confidence interval (CI): 1.001-1.117, P=0.046], oxygen saturation (OR =0.718, 95% CI: 0.554-0.929, P=0.012), N-terminal pro-brain natriuretic peptide (OR =1.001, 95% CI: 1.000-1.002, P=0.016), mean right atrium pressure (OR =1.284, 95% CI: 1.030-1.600, P=0.026), mean pulmonary arterial pressure (mPAP) (OR =1.087, 95% CI: 1.001-1.180, P=0.048), cardiac index (CI) (OR =0.058, 95% CI: 0.008-0.433, P=0.037), pulmonary vascular resistance (OR =1.004, 95% CI: 1.001-1.007, P=0.014) and WHO FC III-IV (OR =18.550, 95% CI: 2.363-144.128, P=0.005) were associated with OSA in CTEPH. Multivariate logistic regression analysis demonstrated CI (OR =0.051, 95% CI: 0.003-0.868, P=0.040) was independently associated with OSA in CTEPH in addition to age, sex and BMI. OSA may aggravate the clinical status of CTEPH patients to some degree. In turn, a worse hemodynamics, oxygenation state and cardiac function are associated with OSA in CTEPH after being adjusted for age, sex and BMI. Among them, CI is the most important parameter in indicating the coexistence of OSA and CTEPH.

Project description:BackgroundObstructive sleep apnea (OSA) is a globally prevalent disease closely associated with hypertension. To date, no predictive model for OSA-related hypertension has been established. We aimed to use machine learning (ML) to construct a model to analyze risk factors and predict OSA-related hypertension.Materials and methodsWe retrospectively collected the clinical data of OSA patients diagnosed by polysomnography from October 2019 to December 2021 and randomly divided them into training and validation sets. A total of 1,493 OSA patients with 27 variables were included. Independent risk factors for the risk of OSA-related hypertension were screened by the multifactorial logistic regression models. Six ML algorithms, including the logistic regression (LR), the gradient boosting machine (GBM), the extreme gradient boosting (XGBoost), adaptive boosting (AdaBoost), bootstrapped aggregating (Bagging), and the multilayer perceptron (MLP), were used to develop the model on the training set. The validation set was used to tune the model hyperparameters to determine the final prediction model. We compared the accuracy and discrimination of the models to identify the best machine learning algorithm for predicting OSA-related hypertension. In addition, a web-based tool was developed to promote its clinical application. We used permutation importance and Shapley additive explanations (SHAP) to determine the importance of the selected features and interpret the ML models.ResultsA total of 18 variables were selected for the models. The GBM model achieved the most extraordinary discriminatory ability (area under the receiver operating characteristic curve = 0.873, accuracy = 0.885, sensitivity = 0.713), and on the basis of this model, an online tool was built to help clinicians optimize OSA-related hypertension patient diagnosis. Finally, age, family history of hypertension, minimum arterial oxygen saturation, body mass index, and percentage of time of SaO2 < 90% were revealed by the SHAP method as the top five critical variables contributing to the diagnosis of OSA-related hypertension.ConclusionWe established a risk prediction model for OSA-related hypertension patients using the ML method and demonstrated that among the six ML models, the gradient boosting machine model performs best. This prediction model could help to identify high-risk OSA-related hypertension patients, provide early and individualized diagnoses and treatment plans, protect patients from the serious consequences of OSA-related hypertension, and minimize the burden on society.

Project description:Systemic hypertension is prevalent among patients with obstructive sleep apnea (OSA). Short-term studies indicate that continuous positive airway pressure (CPAP) therapy reduces blood pressure in patients with hypertension and OSA.To determine whether CPAP therapy is associated with a lower risk of incident hypertension.A prospective cohort study of 1889 participants without hypertension who were referred to a sleep center in Zaragoza, Spain, for nocturnal polysomnography between January 1, 1994, and December 31, 2000. Incident hypertension was documented at annual follow-up visits up to January 1, 2011. Multivariable models adjusted for confounding factors, including change in body mass index from baseline to censored time, were used to calculate hazard ratios (HRs) of incident hypertension in participants without OSA (controls), with untreated OSA, and in those treated with CPAP therapy according to national guidelines.Incidence of new-onset hypertension.During 21,003 person-years of follow-up (median, 12.2 years), 705 cases (37.3%) of incident hypertension were observed. The crude incidence of hypertension per 100 person-years was 2.19 (95% CI, 1.71-2.67) in controls, 3.34 (95% CI, 2.85-3.82) in patients with OSA ineligible for CPAP therapy, 5.84 (95% CI, 4.82-6.86) in patients with OSA who declined CPAP therapy, 5.12 (95% CI, 3.76-6.47) in patients with OSA nonadherent to CPAP therapy, and 3.06 (95% CI, 2.70-3.41) in patients with OSA and treated with CPAP therapy. Compared with controls, the adjusted HRs for incident hypertension were greater among patients with OSA ineligible for CPAP therapy (1.33; 95% CI, 1.01-1.75), among those who declined CPAP therapy (1.96; 95% CI, 1.44-2.66), and among those nonadherent to CPAP therapy (1.78; 95% CI, 1.23-2.58), whereas the HR was lower in patients with OSA who were treated with CPAP therapy (0.71; 95% CI, 0.53-0.94).Compared with participants without OSA, the presence of OSA was associated with increased adjusted risk of incident hypertension; however, treatment with CPAP therapy was associated with a lower risk of hypertension.

Dataset Information

Prebiotics, Probiotics, and Acetate Supplementation Prevent Hypertension in a Model of Obstructive Sleep Apnea.

Publications

Prebiotics, Probiotics, and Acetate Supplementation Prevent Hypertension in a Model of Obstructive Sleep Apnea.

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