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Abstract Background This study investigates the relationship between triglyceride-glucose (TyG) index trajectories and the results of ablation in patients with stage 3D atrial fibrillation (AF). Methods A retrospective cohort study was carried out on patients who underwent AF Radiofrequency Catheter Ablation (RFCA) at the Cardiology Department of the Fourth Affiliated Hospital of Zhejiang University and Taizhou Hospital of Zhejiang Province from January 2016 to December 2022. The main clinical endpoint was determined as the occurrence of atrial arrhythmia for at least 30 s following a 3-month period after ablation. Using a latent class trajectory model, different trajectory groups were identified based on TyG levels. The relationship between TyG trajectory and the outcome of AF recurrence in patients was assessed through Kaplan-Meier survival curve analysis and multivariable Cox proportional hazards regression model. Results The study included 997 participants, with an average age of 63.21 ± 9.84 years, of whom 630 were males (63.19%). The mean follow-up period for the participants was 30.43 ± 17.75 months, during which 200 individuals experienced AF recurrence. Utilizing the minimum Bayesian Information Criterion (BIC) and the maximum Entropy principle, TyG levels post-AF RFCA were divided into three groups: Locus 1 low-low group (n = 791), Locus 2 low-high-low group (n = 14), and Locus 3 high-high group (n = 192). Significant differences in survival rates among the different trajectories were observed through the Kaplan-Meier curve (P

Abstract Background Coronary artery disease (CAD) is a widespread heart condition caused by atherosclerosis and influences millions of people worldwide. Early detection of CAD is challenging due to the lack of specific biomarkers. The gut microbiota and host-microbiota interactions have been well documented to affect human health. However, investigation that reveals the role of gut microbes in CAD is still limited. This study aims to uncover the synergistic effects of host genes and gut microbes associated with CAD through integrative genomic analyses. Results Herein, we collected 52 fecal and 50 blood samples from CAD patients and matched controls, and performed amplicon and transcriptomic sequencing on these samples, respectively. By comparing CAD patients with health controls, we found that dysregulated gut microbes were significantly associated with CAD. By leveraging the Random Forest method, we found that combining 20 bacteria and 30 gene biomarkers could distinguish CAD patients from health controls with a high performance (AUC = 0.92). We observed that there existed prominent associations of gut microbes with several clinical indices relevant to heart functions. Integration analysis revealed that CAD-relevant gut microbe genus Fusicatenibacter was associated with expression of CAD-risk genes, such as GBP2, MLKL, and CPR65, which is in line with previous evidence (Tang et al., Nat Rev Cardiol 16:137-154, 2019; Kummen et al., J Am Coll Cardiol 71:1184-1186, 2018). In addition, the upregulation of immune-related pathways in CAD patients were identified to be primarily associated with higher abundance of genus Blautia, Eubacterium, Fusicatenibacter, and Monoglobus. Conclusions Our results highlight that dysregulated gut microbes contribute risk to CAD by interacting with host genes. These identified microbes and interacted risk genes may have high potentials as biomarkers for CAD.

Summary: This study investigates the relationship and genetic mechanisms of liver and heart diseases, focusing on the liver-heart axis (LHA) as a fundamental biological basis. Through genome-wide association study analysis, we explore shared genes and pathways related to LHA. Shared genetic factors are found in 8 out of 20 pairs, indicating genetic correlations. The analysis reveals 53 loci with pleiotropic effects, including 8 loci exhibiting shared causality across multiple traits. Based on SNP-p level tissue-specific multi-marker analysis of genomic annotation (MAGMA) analysis demonstrates significant enrichment of pleiotropy in liver and heart diseases within different cardiovascular tissues and female reproductive appendages. Gene-specific MAGMA analysis identifies 343 pleiotropic genes associated with various traits; these genes show tissue-specific enrichment primarily in the liver, cardiovascular system, and other tissues. Shared risk loci between immune cells and both liver and cardiovascular diseases are also discovered. Mendelian randomization analyses provide support for causal relationships among the investigated trait pairs.

Abstract Background Tumour necrosis factor superfamily protein 14 (TNFSF14), also called LIGHT, is an important regulator of immunological and fibrosis diseases. However, its specific involvement in cardiac fibrosis and atrial fibrillation (AF) has not been fully elucidated. The objective of this study is to examine the influence of LIGHT on the development of myocardial fibrosis and AF. Methods PCR arrays of peripheral blood mononuclear cells (PBMCs) from patients with AF and sinus rhythm was used to identify the dominant differentially expressed genes, followed by ELISA to evaluate its serum protein levels. Morphological, functional, and electrophysiological changes in the heart were detected in vivo after the tail intravenous injection of recombinant LIGHT (rLIGHT) in mice for 4 weeks. rLIGHT was used to stimulate bone marrow-derived macrophages (BMDMs) to prepare a macrophage-conditioned medium (MCM) in vitro. Then, the MCM was used to culture mouse cardiac fibroblasts (CFs). The expression of relevant proteins and genes was determined using qRT-PCR, western blotting, and immunostaining. Results The mRNA levels of LIGHT and TNFRSF14 were higher in the PBMCs of patients with AF than in those of the healthy controls. Additionally, the serum protein levels of LIGHT were higher in patients with AF than those in the healthy controls and were correlated with left atrial reverse remodelling. Furthermore, we demonstrated that rLIGHT injection promoted macrophage infiltration and M2 polarisation in the heart, in addition to promoting atrial fibrosis and AF inducibility in vivo, as detected with MASSON staining and atrial burst pacing respectively. RNA sequencing of heart samples revealed that the PI3Kγ/SGK1 pathway may participate in these pathological processes. Therefore, we confirmed the hypothesis that rLIGHT promotes BMDM M2 polarisation and TGB-β1 secretion, and that this process can be inhibited by PI3Kγ and SGK1 inhibitors in vitro. Meanwhile, increased collagen synthesis and myofibroblast transition were observed in LIGHT-stimulated MCM-cultured CFs and were ameliorated in the groups treated with PI3Kγ and SGK1 inhibitors. Conclusion LIGHT protein levels in peripheral blood can be used as a prognostic marker for AF and to evaluate its severity. LIGHT promotes cardiac fibrosis and AF inducibility by promoting macrophage M2 polarisation, wherein PI3Kγ and SGK1 activation is indispensable.

ObjectiveTo analyze the risk factors of in-stent restenosis (ISR) after the first implantation of drug-eluting stent (DES) patients with coronary heart disease (CHD) and to establish a nomogram model to predict the risk of ISR.MethodsThis study retrospectively analyzed the clinical data of patients with CHD who underwent DES treatment for the first time at the Fourth Affiliated Hospital of Zhejiang University School of Medicine from January 2016 to June 2020. Patients were divided into an ISR group and a non-ISR (N-ISR) group according to the results of coronary angiography. The least absolute shrinkage and selection operator (LASSO) regression analysis was performed on the clinical variables to screen out the characteristic variables. Then we constructed the nomogram prediction model using conditional multivariate logistic regression analysis combined with the clinical variables selected in the LASSO regression analysis. Finally, the decision curve analysis, clinical impact curve, area under the receiver operating characteristic curve, and calibration curve were used to evaluate the nomogram prediction model's clinical applicability, validity, discrimination, and consistency. And we double-validate the prediction model using ten-fold cross-validation and bootstrap validation.ResultsIn this study, hypertension, HbA1c, mean stent diameter, total stent length, thyroxine, and fibrinogen were all predictive factors for ISR. We successfully constructed a nomogram prediction model using these variables to quantify the risk of ISR. The AUC value of the nomogram prediction model was 0.806 (95%CI: 0.739–0.873), indicating that the model had a good discriminative ability for ISR. The high quality of the calibration curve of the model demonstrated the strong consistency of the model. Moreover, the DCA and CIC curve showed the model's high clinical applicability and effectiveness.ConclusionsHypertension, HbA1c, mean stent diameter, total stent length, thyroxine, and fibrinogen are important predictors for ISR. The nomogram prediction model can better identify the high-risk population of ISR and provide practical decision-making information for the follow-up intervention in the high-risk population.

Due to the complex situation of disorder of consciousness (DOC) patients, the assessment of conscious states of these patients has become a huge challenge for a long time (Laureys et al., 2010). At present, the main clinical diagnostic method to assess the conscious state of a DOC patient is the use of a relevant behavior scale like the Coma Recovery Scale-Revised (CRS-R). In this article, we will focus on auditory stimulation and select some representative auditory stimulus, like calling names and music stimulation, to discuss the function and application of the auditory stimulus in patients with DOC and provide guidance for future research.