Associated lifestyle factors of elevated plasma aldosterone concentration in community population, gender-stratified analysis of a cross-sectional survey.

BACKGROUND: Aldosterone plays important parts in development of cardio-metabolic diseases as end product of renin-angiotensin-aldosterone system. However, factors elevating circulating aldosterone are not clear, and lifestyle-related factors are suggested to be involved, whereas less studied. Therefore, we aimed to explore the association of lifestyle factors with plasma aldosterone concentration (PAC) in community population. METHODS: In this cross-sectional study, we recruited participants using multistage random sampling from Emin China in 2019, and collected data and fasting blood samples. The considered lifestyle factors included obesity parameters (neck circumference, abdominal circumference), alcohol consumption, blood pressure (BP), physical activity, sleep duration, sleep quality, mental state (depression and anxiety), fasting blood glucose (FBG), and lipid profiles (total cholesterol and triglyceride). PAC was measured using radioimmunoassay. We performed sex-stratified linear and logistic regressions to explore associated factors of PAC. Component analysis was further performed to identify the main factors affecting PAC. RESULTS: Twenty-seven thousand four hundred thirty-six participants with 47.1% men were included. Obesity parameters (neck circumference, abdominal circumference), glucose metabolism (FBG), psychological status (anxiety status in men and women, depression status in men), BP, liver function (in men), lipid metabolism (TC and TG in men), sleep parameters (sleep quality in women), and renal function (in women) are the main factors associated with elevated PAC. CONCLUSION: lower physical activity, alcohol consumption, higher BP, fat accumulation, dyslipidemia, higher fasting blood glucose, and presence of depression and anxiety were the main factors associated with eleveated PAC.

The relationship between obstructive sleep apnea and risk of renal impairment in patients with hypertension, a longitudinal study.

OBJECTIVE: Association of obstructive sleep apnea (OSA) with renal damage is undetermined, especially in the population with hypertension, a high-risk group for chronic kidney disease. Therefore, we aimed to explore whether OSA is an independent risk factor for renal impairment in patients with hypertension, by considering the effects of gender, age, obesity and OSA severity. METHODS: The longitudinal observational study included patients with hypertension and suspected OSA without renal damage at baseline who visited Hypertension Center between January 2011 and December 2018, and followed up till renal outcomes, death, loss to follow-up, or May 31, 2022, using annual health check-ups, hospital readmission or out-patient visits. Main renal outcome was chronic kidney disease (CKD), defined as estimated glomerular filtration rate <60 ml/min per 1.73 m2 and/or positive proteinuria. Cox proportional hazard models were used to evaluate the association, and repeated after propensity score matching. Sensitivity analysis were performed by excluding those with primary aldosteronism. RESULTS: 7961 patients with hypertension were included with 5022 ones with OSA, and 82% were followed up. During median follow-up of 3.42 years, 1486 patients developed CKD. Per 1000 person-year incidence of CKD was 56.72 in OSA group. In Cox regression analysis, OSA and severe OSA group respectively showed 1.21 (95% CI: 1.08-1.35) and 1.27 (95% CI: 1.09-1.47) fold risk for CKD in total, compared with non-OSA group. Overall results remained consistent in propensity score matching and sensitivity analysis. CONCLUSION: OSA is independently associated with higher risk of chronic kidney disease in hypertension.

Prevalence of primary aldosteronism in patients with concomitant hypertension and obstructive sleep apnea, baseline data of a cohort.

Obstructive sleep apnea (OSA) and primary aldosteronism (PA) often coexist in hypertension, whereas whether hypertensive patients with OSA should be screened for PA is controversial and whether gender, age, obesity and OSA severity should be considered is unexplored. We explored cross-sectionally prevalence and associated factors of PA in co-existent hypertension and OSA by considering gender, age, obesity and OSA severity. OSA was defined as AHI ≥5 events/h. PA diagnosis was defined, based on the 2016 Endocrine Society Guideline. We included 3306 patients with hypertension (2564 with OSA). PA prevalence was significantly higher in hypertensives with OSA than in those without OSA (13.2 vs 10.0%, P = 0.018). In gender-specific analysis, PA prevalence was significantly higher in hypertensive men with OSA, compared to non-OSA ones (13.8 vs 7.7%, P = 0.001). In further analysis, PA prevalence was significantly higher in hypertensive men with OSA aged <45 years (12.7 vs 7.0%), 45-59 years (16.6 vs 8.5%), and with overweight and obesity (14.1 vs 7.1%) than did their counterparts (P < 0.05). For OSA severity, men participants showed increased PA prevalence from non to moderate OSA and a decrease in the severe OSA group (7.7 vs 12.9 vs 15.1 vs 13.7%, P = 0.008). Young and middle age, moderate-severe OSA, weight, and blood pressure showed a positive independent association with PA presence in logistic regression. In conclusion, PA is prevalent in co-existent hypertension and OSA, indicating the need for PA screening. Studies are needed for women, older and lean population due to the smaller samples in this study.

A Prediction Model Based on Noninvasive Indicators to Predict the 8-Year Incidence of Type 2 Diabetes in Patients with Nonalcoholic Fatty Liver Disease: A Population-Based Retrospective Cohort Study.

BACKGROUND: The prevention of type 2 diabetes (T2D) and its associated complications has become a major priority of global public health. In addition, there is growing evidence that nonalcoholic fatty liver disease (NAFLD) is associated with an increased risk of diabetes. Therefore, the purpose of this study was to develop and validate a nomogram based on independent predictors to better assess the 8-year risk of T2D in Japanese patients with NAFLD. METHODS: This is a historical cohort study from a collection of databases that included 2741 Japanese participants with NAFLD without T2D at baseline. All participants were randomized to a training cohort (n = 2058) and a validation cohort (n = 683). The data of the training cohort were analyzed using the least absolute shrinkage and selection operator method to screen the suitable and effective risk factors for Japanese patients with NAFLD. A cox regression analysis was applied to build a nomogram incorporating the selected features. The C-index, receiver operating characteristic curve (ROC), calibration plot, decision curve analysis, and Kaplan-Meier analysis were used to validate the discrimination, calibration, and clinical usefulness of the model. The results were reevaluated by internal validation in the validation cohort. RESULTS: We developed a simple nomogram that predicts the risk of T2D for Japanese patients with NAFLD by using the parameters of smoking status, waist circumference, hemoglobin A1c, and fasting blood glucose. For the prediction model, the C-index of training cohort and validation cohort was 0.839 (95% confidence interval (CI), 0.804-0.874) and 0.822 (95% CI, 0.777-0.868), respectively. The pooled area under the ROC of 8-year T2D risk in the training cohort and validation cohort was 0.811 and 0.805, respectively. The calibration curve indicated a good agreement between the probability predicted by the nomogram and the actual probability. The decision curve analysis demonstrated that the nomogram was clinically useful. CONCLUSIONS: We developed and validated a nomogram for the 8-year risk of incident T2D among Japanese patients with NAFLD. Our nomogram can effectively predict the 8-year incidence of T2D in Japanese patients with NAFLD and helps to identify people at high risk of T2D early, thus contributing to effective prevention programs for T2D.

Assessment of the association between red blood cell distribution width and disease activity in patients with systemic vasculitis.

The present study aimed to investigate whether red blood cell distribution width (RDW) could serve as a marker for estimating disease activity in patients with systemic vasculitis (SV). A total of 287 patients with SV and 64 age- and sex-matched healthy controls (HCs) were included in the present study. Biochemical indicators and hematologic parameters were evaluated in patients with SV and the HCs. Disease activity was assessed on the basis of the Birmingham Vasculitis Activity Score (BVAS). RDW was significantly elevated in patients with SV compared with HCs (P<0.05). A similar result was obtained for the comparison of patients with various disease states, active vs. inactive (P<0.05). RDW was significantly increased in patients with kidney injury compared with patients without kidney injury (P<0.05). The correlation analysis indicated that there were positive correlations between RDW and BVAS, erythrocyte sedimentation rate, high-sensitivity C-reactive protein, white blood cells and serum creatinine (Scr; all P<0.05). In addition, there was a significant negative correlation between RDW and hemoglobin levels (P<0.05). Multivariate logistic regression analysis indicated that RDW was independently correlated with patients with active SV. The combined diagnosis of RDW and Scr indicated that the sensitivity and specificity were 68.6 and 88.9%, respectively, in terms of assessing disease activity in patients with SV. Therefore, the present study suggested that RDW may serve as a useful index for estimating disease activity and kidney injury in patients with SV. Moreover, the combination of RDW and Scr may be more effective than RDW alone when assessing the risk of disease activity in patients with SV.

Increased Urinary CD163 Levels in Systemic Vasculitis with Renal Involvement.

OBJECTIVES: Systemic vasculitis includes a group of disorders characterized by inflammation of the vessel wall, involving multiple systems, and can cause malignant hypertension. CD163 is a specific marker of anti-inflammatory macrophages. This study is aimed at evaluating the CD163 levels in relation to systemic vasculitis and renal involvements. METHODS: Urinary CD163 levels were retrospectively measured by enzyme-linked immunosorbent assay (ELISA) in 51 patients with systemic vasculitis, 42 essential hypertensions, and 36 healthy volunteers. The associations between urinary CD163 levels and clinical indicators were analyzed. RESULTS: Urinary CD163 levels were significantly higher in patients with systemic vasculitis [68.20 (38.25~158.78) (pg/ml)] compared to essential hypertension [43.86 (23.30-60.71) (pg/ml)] (p = 0.003) and the healthy volunteers [30.76 (9.30-54.16) (pg/ml)] (p < 0.001). Furthermore, systemic vasculitis patients with renal involvement had significantly higher urinary CD163 levels relative to patients without renal involvement [86.95 (47.61 and 192.38) pg/ml] vs. [41.99 (17.70 and 71.95) pg/ml, p = 0.005]. After control factors age, sex, and BMI, urinary CD163 levels in systemic vasculitis patients were positively correlated with serum creatinine, blood urea nitrogen, and ß-2 microglobulin (r = 0.45, 0.48, and 0.46; p = 0.001, 0.001, and 0.002, respectively). In addition, we found the level of urinary CD163 in granulomatous vasculitis (including TA, GPA, and EGPA) was significantly higher than that in necrotizing vasculitis (including PAN) [86.95 (41.99 and 184.82) pg/ml] vs. [45.73 (21.43 and 74.43) pg/ml, p = 0.016]. CONCLUSION: Urinary CD163 levels were significantly higher in patients with systemic vasculitis, especially in patients with renal involvement. Thus, urinary CD163 has the potential to be a biomarker for systemic vasculitis with renal involvement.

Glial Cell-Derived Neurotrophic Factor Functions as a Potential Candidate Gene in Obstructive Sleep Apnea Based on a Combination of Bioinformatics and Targeted Capture Sequencing Analyses.

BACKGROUND: Obstructive sleep apnea (OSA) is a prevalent chronic disease that increases the risk of cardiovascular disease and metabolic and neuropsychiatric disorders, resulting in a considerable socioeconomic burden. The present study was aimed at identifying potential key genes influencing the mechanisms and consequences of OSA. METHODS: Gene expression profiles associated with OSA were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in subcutaneous adipose tissues from patients with OSA and normal tissues were screened using R software, followed by gene ontology and pathway enrichment analyses. Subsequently, a protein-protein interaction (PPI) network was constructed and hub genes were extracted using Cytoscape plugins. The intersected core genes derived from different topological algorithms were considered hub genes, and the potential candidate gene was selected from them for further analyses of expression variations using another GEO dataset and targeted capture sequencing in 100 subjects (50 with severe OSA and 50 without OSA). RESULTS: A total of 373 DEGs were identified in OSA samples relative to normal controls, which were primarily associated with olfactory transduction and neuroactive ligand-receptor interaction. Upon analyses of nine topological algorithms and available literature, we finally focused on glial cell-derived neurotrophic factor (GDNF) as the candidate gene and validated its low expression in OSA samples. Two rare nonsynonymous variants (p.D56N and p.R93Q) were identified among the 100 cases through targeted sequencing of GDNF, which could be potentially deleterious based on pathogenicity prediction programs; however, no significant association was detected in single nucleotide polymorphisms. CONCLUSION: The present study identified GDNF as a promising candidate gene for OSA and its two rare and potentially deleterious mutations through a combination of bioinformatics and targeted capture sequencing analyses.

A Nomogram Model Based on Noninvasive Bioindicators to Predict 3-Year Risk of Nonalcoholic Fatty Liver in Nonobese Mainland Chinese: A Prospective Cohort Study.

The purpose of this study is to establish and validate an accurate and personalized nonalcoholic fatty liver disease (NAFLD) prediction model based on the nonobese population in China. This study is a secondary analysis of a prospective study. We included 6,155 nonobese adults without NAFLD at baseline, with a median follow-up of 2.3 years. Univariate and multivariate Cox regression analyses were used to determine independent predictors. The least absolute shrinkage and selection operator (LASSO) regression analysis was used to optimize the selection of variables. Based on the results of multivariate analysis, a prediction model was established. Harrell's consistency index (C-index) and area under the curve (AUC) were used to determine the discrimination of the proposed model. The goodness of fit of the calibration model was tested, and the clinical application value of the model was evaluated by decision curve analysis (DCA). The participants were randomly divided into a training cohort (n = 4,605) and a validation cohort (n = 1,550). Finally, seven of the variables (HDL-c, BMI, GGT, ALT, TB, DBIL, and TG) were included in the prediction model. In the training cohort, the C-index and AUC value of this prediction model were 0.832 (95% confidence interval (CI), 0.820-0.844) and 0.861 (95% CI, 0.849-0.873), respectively. In the validation cohort, the C-index and AUC values of this prediction model were 0.829 (95% CI, 0.806-0.852) and 0.859 (95% CI, 0.841-0.877), respectively. The calibration plots demonstrated good agreement between the estimated probability and the actual observation. DCA demonstrated a clinically effective predictive model. Our nomogram can be used as a simple, reasonable, economical, and widely used tool to predict the 3-year risk of NAFLD in nonobese populations in China, which is helpful for timely intervention and reducing the incidence of NAFLD.

Development and Validation of a Novel Model for Predicting the 5-Year Risk of Type 2 Diabetes in Patients with Hypertension: A Retrospective Cohort Study.

BACKGROUND: Hypertension is now common in China. Patients with hypertension and type 2 diabetes are prone to severe cardiovascular complications and poor prognosis. Therefore, this study is aimed at establishing an effective risk prediction model to provide early prediction of the risk of new-onset diabetes for patients with a history of hypertension. METHODS: A LASSO regression model was used to select potentially relevant features. Univariate and multivariate Cox regression analyses were used to determine independent predictors. Based on the results of multivariate analysis, a nomogram of the 5-year incidence of T2D in patients with hypertension in mainland China was established. The discriminative capacity was assessed by Harrell's C-index, AUC value, calibration plot, and clinical utility. RESULTS: After random sampling, 1273 and 415 patients with hypertension were included in the derivation and validation cohorts, respectively. The prediction model included age, body mass index, FPG, and TC as predictors. In the derivation cohort, the AUC value and C-index of the prediction model are 0.878 (95% CI, 0.861-0.895) and 0.862 (95% CI, 0.830-0.894), respectively. In the validation cohort, the AUC value and C-index of the prediction model were 0.855 (95% CI, 0.836-0.874) and 0.841 (95% CI, 0.817-0.865), respectively. The calibration plots demonstrated good agreement between the estimated probability and the actual observation. Decision curve analysis shows that nomograms are clinically useful. CONCLUSION: Our nomogram can be used as a simple, affordable, reasonable, and widely implemented tool to predict the 5-year T2D risk of hypertension patients in mainland China. This application helps timely intervention to reduce the incidence of T2D in patients with hypertension in mainland China.

Association of circulating resistin and adiponectin levels with Kawasaki disease: A meta-analysis.

The present meta-analysis was performed to examine the association between circulating blood adipokine levels and Kawasaki disease (KD). Studies were identified by searching various databases, including Web of Science, EMBASE, PubMed, Wanfang and China National Knowledge Infrastructure. After the studies were pooled, the mean difference (MD) and corresponding 95% CI were calculated. Subgroup analyses and publication bias detection were also performed. The Cochrane Q test and I2 statistics were performed using Review Manager software (version 5.3) to test for heterogeneity. A Begg's test was used to assess publication bias and STATA software (version 12.0) was used for statistical analysis. The results revealed that the KD group exhibited higher levels of resistin compared with those in the healthy controls or disease controls (non-KD; MD=20.76, 95% CI=16.16-25.36, P<0.001; MD=21.27, 95% CI=14.24-28.29, P<0.001, respectively). In addition, when compared with those in patients exhibiting non-coronary artery lesions (NCAL), those with coronary artery lesions (CAL) had higher levels of adiponectin and resistin (MD=1.00, 95% CI=0.06-1.96, P=0.04; MD=2.77, 95% CI=1.32-4.22, P<0.001). Furthermore, compared with those in the inactive-phase group, patients in the active-phase group exhibited higher levels of resistin (MD=17.73, 95% CI=12.82-22.65, P<0.001). In conclusion, the present meta-analysis indicated that resistin levels were elevated in patients with KD. It was also revealed that circulating resistin and adiponectin levels in the CAL group were significantly increased compared with those in patients with NCAL. Furthermore, the active group had higher levels of resistin than the inactive group. The results of these meta-analyses indicated that resistin may serve an important role in the pathogenesis of KD and may therefore be used as biomarkers for the diagnosis of KD, whereas adiponectin may only serve an important role in the pathogenesis of CAL and may therefore be used as a biomarker to distinguish CAL from NCAL.