Aims  The association between low-to-moderate alcohol consumption and atrial fibrillation (AF) has yet to be fully elucidated. The main purpose of this meta-analysis was to estimate the risk of incident AF related to low-to-moderate alcohol consumption. Methods and results  A meta-analysis was performed on 13 publications discussing the estimated risk for AF with habitual low-to-moderate alcohol intake in 10 266 315 participants. Graphical augmentations to the funnel plots were used to illustrate the potential impact of additional evidence on the current meta-analysis. Thirteen eligible studies were included in this meta-analysis. We found that moderate alcohol consumption was associated with an increased risk of incident AF in males [hazard ratio (HR) 1.09, 95% confidence interval (CI): 1.07–1.11, P < 0.00001], Europeans (HR 1.32, 95% CI: 1.23–1.42, P < 0.00001), and Asians (HR 1.09, 95% CI: 1.07–1.11, P < 0.00001). Moderate beer consumption was associated with an increased risk of developing AF (HR 1.11, 95% CI: 1.02–1.21, P = 0.01). Low alcohol consumption conferred an increased risk of AF in males (HR 1.14, 95% CI: 1.01–1.28, P = 0.04) and Europeans (HR 1.12, 95% CI: 1.07–1.17, P < 0.00001). Conclusions  This analysis represents the increased risk of incident AF in males, Europeans, and Asians at moderate alcohol consumption levels and in males and Europeans at low alcohol consumption levels. Those who drink any preferred alcohol beverage at moderate levels should be cautious for incident AF. More studies are warranted to find those factors that influence alcohol’s effect on predisposing AF.

BackgroundAtrial fibrillation (AF) is the most common sustained cardiac arrhythmia and engenders significant global health care burden. The underlying mechanisms of AF is remained to be revealed and current treatment options for AF have limitations. Besides, a detection system can help identify those at risk of developing AF and will enable personalized management.Materials and MethodsIn this study, we utilized the robust rank aggregation method to integrate six AF microarray datasets from the Gene Expression Omnibus database, and identified a set of differentially expressed genes between patients with AF and controls. Potential compounds were identified by mining the Connectivity Map database. Functional modules and closely-interacted clusters were identified using weighted gene co-expression network analysis and protein–protein interaction network, respectively. The overlapped hub genes were further filtered. Subsequent analyses were performed to analyze the function, biological features, and regulatory networks. Moreover, a reliable Machine Learning-based diagnostic model was constructed and visualized to clarify the diagnostic features of these genes.ResultsA total of 156 upregulated and 34 downregulated genes were identified, some of which had not been previously investigated. We showed that mitogen-activated protein kinase and epidermal growth factor receptor inhibitors were likely to mitigate AF based on Connectivity Map analysis. Four genes, including CXCL12, LTBP1, LOXL1, and IGFBP3, were identified as hub genes. CXCL12 was shown to play an important role in regulation of local inflammatory response and immune cell infiltration. Regulation of CXCL12 expression in AF was analyzed by constructing a transcription factor-miRNA-mRNA network. The Machine Learning-based diagnostic model generated in this study showed good efficacy and reliability.ConclusionKey genes involving in the pathogenesis of AF and potential therapeutic compounds for AF were identified. The biological features of CXCL12 in AF were investigated using integrative bioinformatics tools. The results suggested that CXCL12 might be a biomarker that could be used for distinguishing subsets of AF, and indicated that CXCL12 might be an important intermediate in the development of AF. A reliable Machine Learning-based diagnostic model was constructed. Our work improved understanding of the mechanisms of AF predisposition and progression, and identified potential therapeutic avenues for treatment of AF.

No previous meta‐analysis has evaluated the relationship between pulmonary artery enlargement (PAE) measured by computed tomography (CT) and prognosis for patients with chronic obstructive pulmonary disease (COPD). Recently, several studies have suggested poor survival and reduced exercise capacity in COPD patients with PAE on CT scan, but there were conflicting results. We aimed to assess the prognostic value of PAE‐CT in patients with COPD. Relevant studies were identified by searching major databases. Pooled outcomes were determined to assess the prognostic value of PAE‐CT in COPD patients. Eighteen studies including 5694 participants were included. PAE indicated higher mortality in COPD patients (odds ratio [OR] = 3.06; 95% confidence interval [95% CI]: 1.76–5.32; p < 0.0001), shorter 6‐minute walk distance (mean difference [MD] = −67.53 m; 95% CI: −85.98 to −49.08; p < 0.00001), higher pulmonary artery systolic pressure (MD = 15.65 mmHg; 95% CI: 13.20–18.11; p < 0.00001), longer length of hospital stay (MD = 2.92 days; 95% CI: 0.71–5.12; p = 0.009) and more severe symptom such as dyspnea (COPD Assessment Test MD = 3.14; 95% CI: 2.48–3.81; p < 0.00001). We also conducted a subgroup analysis regarding the lung function and blood gas analysis for a stable period and acute exacerbation of COPD patients. In conclusion, PAE is significantly associated with mortality, lower exercise tolerance, and poor quality of life in patients with COPD. PAE may serve as a novel imaging biomarker for risk stratification in patients with COPD in the future.

Introduction: An improved understanding of the pathogenesis of AF and atrial substrate remodeling is necessary for development of novel therapeutic approaches and new management strategies. Hypothesis: CXCL12 could be involved in the regulation of AF inflammatory microenvironment and have the potential to be a marker for AF subset classification. Methods: In this study, we utilized the Robust Rank Aggregation method to integrate AF microarray datasets. Potential compounds were identified by mining the Connectivity Map database. Functional modules and closely-interacted clusters were identified using WGCNA analysis and PPI network, respectively. Biological functions were further analysed. Moreover, a reliable Machine Learning-based diagnostic model was constructed and visualized to clarify the diagnostic features of these genes. Results: Differentially expressed genes were identified. We showed that mitogen-activated protein kinase and epidermal growth factor receptor inhibitors were likely to mitigate AF based on Connectivity Map analysis. Four genes were identified as hub genes. CXCL12 was shown to play an important role in regulation of local inflammatory response and immune cell infiltration. Conclusions: Key genes involving in the pathogenesis of AF were identified. The biological features of CXCL12 in AF were investigated using integrative bioinformatics tools. The results suggested that CXCL12 might be a biomarker that could be used for distinguishing subsets of AF, and indicated that CXCL12 might be an important intermediate in the development of AF by increasing the infiltration of mast cells, neutrophils, and γδ T cells, and reducing infiltration of regulatory T cells. A reliable Machine Learning-based diagnostic model was constructed. Our work improved understanding of the mechanisms of AF predisposition and progression, and identified potential therapeutic avenues for treatment of AF.

Background: Pulmonary arterial hypertension (PAH) is a malignant vascular disease characterized by pulmonary arterial remodeling. Neural cell adhesion molecule 1 (NCAM1) is a cell surface glycoprotein that is involved in a variety of diseases, including cardiovascular disease. However, the relationship between NCAM1 and PAH is unknown. Methods: Enzyme-linked immunosorbent assay, Bioinformatics methods, Echocardiography, Right heart catheterization, Hematoxylin-eosin staining, Immunofluorescent staining, Quantitative reverse transcription polymerase chain reaction, Western blotting, Cell Counting Kit-8, EdU staining, Scratch wound healing assay and Transwell migration assay were used to elucidate the role of NCAM1 in PAH. Results: The protein expression levels of NCAM1 were increased in the plasma of PAH patients. Using bioinformatics methods, we found that the transcript levels of NCAM1 were also upregulated in the lung tissues of PAH patients. The expression levels of NCAM1 protein in the plasma of MCT-induced PAH rats were also increased. We found that both NCAM1 protein and mRNA expression levels were significantly enhanced in MCT rat lung tissues. Furthermore, we found that NCAM1 mRNA and protein levels were significantly upregulated in PDGF-BB-treated PASMCs. NCAM1 knockdown could partially reverse PDGF-BB-induced proliferation and migration of PASMCs. However, the effects were partially restored by tert-butylhydroquinone (TBHQ), an ERK1/2 activator. And recombinant rat NCAM1 protein promotes PASMC proliferation and migration and activates the ERK1/2 signaling pathway. Conclusion: Our findings suggest that NCAM1 may be associated with pulmonary arterial hypertension and promotes the proliferation and migration of PASMCs via the ERK1/2 signaling pathway.

Idiopathic pulmonary arterial hypertension (IPAH) and chronic thromboembolic pulmonary hypertension (CTEPH) can result in right heart failure. We aimed to evaluate the plasma protein levels of a disintegrin and metalloproteinase with thrombospondin motifs like 4 (ADAMTSL4) and its relationship with IPAH and CTEPH. Plasma ADAMTSL4 protein levels were measured using proteomics analysis in eight patients with IPAH and nine healthy controls. ADAMTSL4 levels in pulmonary tissues were assessed using bioinformatics tools. Protein expression of ADAMTSL4 in platelet‐derived growth factor (PDGF)‐BB‐treated primary rat pulmonary arterial smooth muscle cells (PASMCs) was detected by Western blot. Plasma ADAMTSL4 concentrations were measured in 45 patients (15 with IPAH and 30 with CTEPH) using enzyme‐linked immunosorbent assay (ELISA). Correlation between ADAMTSL4 levels and clinical parameters was evaluated. In patients with IPAH, the plasma levels of ADAMTSL4 protein were significantly higher than those in healthy controls (flod change [FC] 1.85, p < 0.05), and mRNA expression levels were significantly elevated (log FC 0.66, p < 0.05). The protein expression of ADAMTSL4 was significantly increased in PDGF‐BB‐treated PASMCs compared to that in the control grAoup (p < 0.05). Plasma ADAMTSL4 protein levels in patients with IPAH (4.71 ± 0.73 ng/mL, p < 0.01) and CTEPH (4.22 ± 0.66 ng/mL, p < 0.01) were higher than in healthy controls (3.01 ± 0.46 ng/mL). Plasma ADAMATL4 protein levels had a cutoff value of 3.55 ng/mL based on the receiver operator characteristic curve and were positively correlated with mean pulmonary artery pressure (mPAP) (r = 0.305, p < 0.05). In patients with IPAH and CTEPH, elevated plasma ADAMTSL4 levels were positively associated with mPAP.