Association of different obesity patterns with hypertension in US male adults: a cross-sectional study.

Obesity is an important risk factor for hypertension. We aimed to investigate the association between different obesity patterns and hypertension risk in a large male population in the US. Male participants from the National Health and Nutrition Examination Survey (NHANES) (2007-2018) were enrolled in this cross-sectional study. Social demographic information, lifestyle factors, anthropometric measurements and biochemical measurements were collected. Three obesity patterns were classified according to the body mass index (BMI) and waist circumference (WC), including overweight and general obesity, abdominal obesity, and compound obesity. We adopted multivariate logistic regression to investigate the associations between hypertension and different obesity patterns after adjusting for cofounding factors. Subgroup analysis, stratified by age, smoking, drinking and estimated glomerular filtration rate (eGFR), was also conducted to explore the associations between obesity patterns and hypertension risk among different populations. Moreover, the association between WC and hypertension among male individuals was also explored using restricted cubic spline (RCS) analysis. Receiver operating characteristic (ROC) was used to evaluate the discriminatory power of WC for screening hypertension risk. 13,859 male participants from NHANES survey (2007-2018) were enrolled. Comparing with the normal-weight group, the odds ratios (ORs) [95% confidence interval (CI)] for hypertension in individuals with overweight and general obesity, abdominal obesity and compound obesity were 1.41 [1.17-1.70], 1.97 [1.53-2.54] and 3.28 [2.70-3.99], respectively. Subgroup analysis showed that the effect of different obesity patterns on hypertension risk was highly stable among individuals with different clinical conditions. In addition, WC had a positive correlation with the risk of hypertension (OR: 1.43; 95% CI 1.37-1.52; P < 0.001) in fully adjusted multivariate logistic regression model. RCS analysis showed that the association between WC and hypertension risk was in a nonlinear pattern, and WC had a good discriminatory power for hypertension in ROC analysis. Different patterns of obesity have a great impact on the risk of hypertension among male individuals. Increment of WC significantly increased the hypertension risk. More attention should be paid to the prevention of obesity, especially abdominal obesity and compound obesity in male individuals.

Integrated genomic analysis defines molecular subgroups in dilated cardiomyopathy and identifies novel biomarkers based on machine learning methods.

Aim: As the most common cardiomyopathy, dilated cardiomyopathy (DCM) often leads to progressive heart failure and sudden cardiac death. This study was designed to investigate the molecular subgroups of DCM. Methods: Three datasets of DCM were downloaded from GEO database (GSE17800, GSE79962 and GSE3585). After log2-transformation and background correction with "limma" package in R software, the three datasets were merged into a metadata cohort. The consensus clustering was conducted by the "Consensus Cluster Plus" package to uncover the molecular subgroups of DCM. Moreover, clinical characteristics of different molecular subgroups were compared in detail. We also adopted Weighted gene co-expression network analysis (WGCNA) analysis based on subgroup-specific signatures of gene expression profiles to further explore the specific gene modules of each molecular subgroup and its biological function. Two machine learning methods of LASSO regression algorithm and SVM-RFE algorithm was used to screen out the genetic biomarkers, of which the discriminative ability of molecular subgroups was evaluated by receiver operating characteristic (ROC) curve. Results: Based on the gene expression profiles, heart tissue samples from patients with DCM were clustered into three molecular subgroups. No statistical difference was found in age, body mass index (BMI) and left ventricular internal diameter at end-diastole (LVIDD) among three molecular subgroups. However, the results of left ventricular ejection fraction (LVEF) statistics showed that patients from subgroup 2 had a worse condition than the other group. We found that some of the gene modules (pink, black and grey) in WGCNA analysis were significantly related to cardiac function, and each molecular subgroup had its specific gene modules functions in modulating occurrence and progression of DCM. LASSO regression algorithm and SVM-RFE algorithm was used to further screen out genetic biomarkers of molecular subgroup 2, including TCEAL4, ISG15, RWDD1, ALG5, MRPL20, JTB and LITAF. The results of ROC curves showed that all of the genetic biomarkers had favorable discriminative effectiveness. Conclusion: Patients from different molecular subgroups have their unique gene expression patterns and different clinical characteristics. More personalized treatment under the guidance of gene expression patterns should be realized.

The dietary inflammatory index and its association with the prevalence of hypertension: A cross-sectional study.

Aims: We aim to investigate the association of the Dietary Inflammatory Index (DII) with the prevalence of hypertension in a large multiracial population in the United States. Methods: Participants from the National Health and Nutrition Examination Survey (NHANES) (1999-2018) were included in this cross-sectional study. Dietary information was obtained and used to calculate DII. Blood pressures of participants were measured by experienced examiners. The NHANES used the method of "stratified multistage probability sampling," and this study is a weight analysis following the NHANES analytic guidance. Weight logistic regression analysis was adopted to investigate the association of hypertension with DII. Least Absolute Shrinkage and Selection Operator (LASSO) regression was carried out to screen the most important dietary factors associated with the risk of hypertension. Moreover, a nomogram model based on key dietary factors was established; the receiver operating characteristic (ROC) curve was used to evaluate the diagnostic power of the nomogram model for screening hypertension risk. Results: A total of 45,023 participants were included in this study, representing 191 million residents in the United States. Participants with hypertension had an elevated DII compared with those without hypertension. Weight logistic regression showed that an increment of DII was strongly associated with hypertension after adjusting for confounding factors. The nomogram model, based on key dietary factors screened by LASSO regression, showed a favorable discriminatory power with an area under the curve (AUC) of 78.5% (95% CI: 78.5%-79.3%). Results of the sensitivity analysis excluding participants who received any drug treatment were consistent with those in the main analysis. Conclusion: An increment of DII is associated with the risk of hypertension. For better prevention and treatment of hypertension, more attention should be paid to controlling dietary inflammation.

Rs10757274 gene polymorphisms in coronary artery disease: A systematic review and a meta-analysis.

BACKGROUND: It has been reported the rs10757274 SNP (present on locus 9p21 in the gene for CDKN2BAS1) might be associated with susceptibility to coronary artery disease (CAD). Owing to mixed and inconclusive results, we conducted a meta-analysis to investigate the association between rs10757274 polymorphism and the risk of CAD. OBJECTIVES: The present study aimed to investigate the relationship between rs10757274 polymorphism and the risk of CAD. METHODS: All studies of the rs10757274 SNP with CAD that were published between 2007 and 2018 were retrieved from the PubMed database. Meta-analysis was performed with Stata 14.0 software. The effect size of the rs10757274 SNP with CAD risk was assessed based on the odds ratios (ORs) with calculation of 95% confidence interval (CI). RESULTS: Eleven studies including 52,209 subjects (cases: 7990, controls: 44,219) were included in the final data combination. Pooled overall analyses showed that rs10757274 (allele model: P < .001; dominant model: P < .001; recessive model: P < .001; Heterozygote codominant: P = .002; Homozygote codominant: P < .001) polymorphisms were significantly associated with the likelihood of CAD. Significant heterogeneity between individual studies appears in all 5 models. Further subgroup analyses revealed that rs10757274 polymorphisms were all significantly correlated with the likelihood of CAD and no heterogeneity were observed in West Asians. CONCLUSIONS: Our findings indicated that rs10757274 polymorphisms may serve as genetic biomarkers of CAD, especially in West Asians.