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Objective:To explore the association between suboptimal health status (SHS) and plasma IgG N-glycans levels among undergraduates in a college in Shandong Province.Methods:A case-control study was conducted from September to November 2017, 100 college students who underwent physical examinations at Weifang University in Shandong, were selected as study participants based on the inclasion and exclusion criteria of the study. According to the criteria of SHS, the participants were divided into an SHS group ( n=50) and a health control group ( n=50). Plasma IgG N-glycosylaton levels were analyzed by means of ultra-high liquid chromatography (UPLC), and 24 glycan peaks were obtained. The Mann-Whitney U-test and binary logistic regression analysis were performed to investigate the association between IgG N-glycans and SHS. P<0.05 was considered statistically significant. Receiver operating characteristic (ROC) curve analyses were used to evaluate the possibility of plasma IgG N-glycans being a biomarker of SHS. Results:The results of univariate and multivariate analysis showed that GP17 was associated with SHS ( P<0.05), and the relative abundance of initial glycan peaks (GP17) was higher in the SHS group compared with the control group. ROC curve analysis showed that the area under the curve (AUC) of the baseline model was 0.826 (95% confidence interval [ CI]: 0.747-0.905, P<0.001); the AUC of the glycan-based model was 0.631 (95% CI: 0.519-0.744, P=0.002), and the AUC of the combined model was 0.848 (95% CI: 0.763-0.912, P<0.001). Compared with the baseline model, the diagnostic efficiency of the combined model revealed a trend of improvement. Conclusions:The SHS of the students in a college in Shandong Province was associated with an IgG N-glycan level of GP17, which was significantly higher than that of the control group.
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BackgroundObservational studies showed that coronavirus disease 2019 (COVID-19) attacks universally and its most menacing progression uniquely endangers the elderly with cardiovascular disease (CVD). Whether COVID-19 is causally related to increasing susceptibility and severity of atrial fibrillation (AF), the main form of CVD, remains still unknown. MethodsThe study aims to investigate the bidirectional causal relations of COVID-19 with AF using two-sample Mendelian randomization (MR) analysis. ResultsMR evidence suggested genetically predicted severe COVID-19 was significantly associated with higher risk of AF (odds ratio [OR], 1.041; 95% confidence interval (CI), 1.007-1.076; P = 0.017), while genetically predicted AF was not causally associated with severe COVID-19 (OR, 0.831; 95% CI, 1.619-1.115; P=0.217). There was limited evidence to support association of genetically proxied COVID-19 with risk of AF (OR, 1.051; 95% CI, 0.991-1.114; P=0.097), and vice versa (OR, 0.163; 95% CI, 0.004-6.790; P=0.341). MR-Egger indicated no evidence of pleiotropic bias. ConclusionOverall, severe COVID-19 may causally affect AF through independent biological pathway. Survivors from severe COVID-19 might be of high risk of AF in the future.
