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Abstract Background Body mass index (BMI) and lipid disorders are both known to be strongly associated with the development of diabetes, however, the indirect effect of lipid parameters in the BMI-related diabetes risk is currently unknown. This study aimed to investigate the mediating role of lipid parameters in the association of BMI with diabetes risk. Methods We assessed the association of diabetes risk with BMI, as well as lipid parameters including high-density lipoprotein cholesterol(HDL-C), low-density lipoprotein cholesterol(LDL-CF and LDL-CS), triglycerides(TG), total cholesterol(TC), remnant cholesterol(RC), non-HDL-C, and combined indices of lipid parameters with HDL-C (RC/HDL-C ratio, TG/HDL-C ratio, TC/HDL-C ratio, non-HDL/HDL-C ratio, LDL/HDL-C ratio) using data from 15,453 subjects in the NAGALA project. Mediation models were used to explore the mediating role of lipid parameters in the association of BMI with diabetes risk, and mediation percentages were calculated for quantifying the strength of the indirect effects. Finally, receiver operating characteristic curve (ROC) analysis was used to compare the accuracy of BMI and BMI combined with lipid parameters in predicting incident diabetes. Results Multivariate regression models, adjusted for confounding factors, demonstrated robust associations of lipid parameters, BMI, with diabetes risk, with the exception of TC, LDL-CF, LDL-CS, and non-HDL-C. Mediation analysis showed that lipid parameters except TC, LDL-CF, LDL-CS, and Non-HDL-C were involved in and mediated the association of BMI with diabetes risk, with the largest mediation percentage being the RC/HDL-C ratio, which was as high as 40%; it is worth mentioning that HDL-C and HDL-C-related lipid ratio parameters also play an important mediating role in the association between BMI and diabetes, with the mediator proportion being greater than 30%. Finally, based on the ROC results, we found that the prediction performance of all lipid parameters in the current study except TC was significantly improved when combined with BMI. Conclusion Our fresh findings suggested that lipid parameters partially mediated the association of BMI with diabetes risk; this result indicated that in the context of diabetes risk screening and disease management, it is important to not only monitor BMI but also pay attention to lipid parameters, particularly HDL-C and HDL-C-related lipid ratio parameters.

Abstract Background Kounis syndrome is a rare clinical condition characterized by the occurrence of an acute coronary event induced by an acute allergic episode. The ongoing pandemic of coronavirus disease 2019 (COVID-19) has contributed to an increase in the incidence of allergic reactions to a certain extent, thereby increasing the incidence of Kounis syndrome. Timely diagnosis and effective management of this disease are important in clinical practice. Case presentation We report a 43-year-old woman who developed generalized pruritus, breathlessness, paroxysmal precordial crushing pain, and dyspnea after receiving the third dose of the COVID-19 vaccine. After anti-allergic treatment and therapy for acute myocardial ischemia, her symptoms resolved with improvement in cardiac function and resolution of ST-segment changes. The prognosis was satisfactory, and the final diagnosis was type I Kounis syndrome. Conclusion This patient with type I Kounis syndrome rapidly developed acute coronary syndrome (ACS) after an acute allergic reaction to the COVID-19 vaccine. ​Timely diagnosis of acute allergic reaction and ACS, and targeted treatment based on the relevant guidelines are the key to successful treatment of the syndrome.​

Abstract Background Recent numerous epidemiology and clinical association studies reported that ApoE polymorphism might be associated with the risk and severity of coronavirus disease 2019 (COVID-19), and yielded inconsistent results. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection relies on its spike protein binding to angiotensin-converting enzyme 2 (ACE2) receptor expressed on host cell membranes. Methods A meta-analysis was conducted to clarify the association between ApoE polymorphism and the risk and severity of COVID-19. Multiple protein interaction assays were utilized to investigate the potential molecular link between ApoE and the SARS-CoV-2 primary receptor ACE2, ApoE and spike protein. Immunoblotting and immunofluorescence staining methods were used to access the regulatory effect of different ApoE isoform on ACE2 protein expression. Results ApoE gene polymorphism (ε4 carrier genotypes VS non-ε4 carrier genotypes) is associated with the increased risk (P = 0.0003, OR = 1.44, 95% CI 1.18–1.76) and progression (P

Abstract Background Left-sided heart failure (HF) is documented as a key prognostic factor in HF. However, the relative molecular mechanisms underlying left-sided HF is unknown. The purpose of this study is to unearth significant modules, pivotal genes and candidate regulatory components governing the progression of left-sided HF by bioinformatical analysis. Methods A total of 319 samples in GSE57345 dataset were used for weighted gene correlation network analysis (WGCNA). ClusterProfiler package in R was used to conduct functional enrichment for genes uncovered from the modules of interest. Regulatory networks of genes were built using Cytoscape while Enrichr database was used for identification of transcription factors (TFs). The MCODE plugin was used for identifying hub genes in the modules of interest and their validation was performed based on GSE1869 dataset. Results A total of six significant modules were identified. Notably, the blue module was confirmed as the most crucially associated with left-sided HF, ischemic heart disease (ISCH) and dilated cardiomyopathy (CMP). Functional enrichment conveyed that genes belonging to this module were mainly those driving the extracellular matrix-associated processes such as extracellular matrix structural constituent and collagen binding. A total of seven transcriptional factors, including Suppressor of Zeste 12 Protein Homolog (SUZ12) and nuclear factor erythroid 2 like 2 (NFE2L2), adrenergic receptor (AR), were identified as possible regulators of coexpression genes identified in the blue module. A total of three key genes (OGN, HTRA1 and MXRA5) were retained after validation of their prognostic value in left-sided HF. The results of functional enrichment confirmed that these key genes were primarily involved in response to transforming growth factor beta and extracellular matrix. Conclusion We uncovered a candidate gene signature correlated with HF, ISCH and CMP in the left ventricle, which may help provide better prognosis and therapeutic decisions and in HF, ISCH and CMP patients.