Di Liu

Objectives: Hypertension and type 2 diabetes mellitus comorbidity (HDC) is common, which confers a higher risk of cardiovascular disease than the presence of either condition alone. Describing the underlying glycomic changes of immunoglobulin G (IgG) that predispose individuals to HDC may help develop novel protective immune-targeted and anti-inflammatory therapies. Therefore, we investigated glycosylation changes of IgG associated with HDC. Methods: The IgG N-glycan profiles of 883 plasma samples from the three northwestern Chinese Muslim ethnic minorities and the Han Chinese were analyzed by ultra-performance liquid chromatography instrument. Results: We found that 12 and six IgG N-glycan traits showed significant associations with HDC in the Chinese Muslim ethnic minorities and the Han Chinese, respectively, after adjustment for potential confounders and false discovery rate. Adding the IgG N-glycan traits to the baseline models, the area under the receiver operating characteristic curves (AUCs) of the combined models differentiating HDC from hypertension (HTN), type 2 diabetes mellitus (T2DM), and healthy individuals were 0.717, 0.747, and 0.786 in the pooled samples of Chinese Muslim ethnic minorities, and 0.828, 0.689, and 0.901 in the Han Chinese, respectively, showing improved discriminating performance than both the baseline models and the glycan-based models. Conclusion: Altered IgG N-glycan profiles were shown to associate with HDC, suggesting the involvement of inflammatory processes of IgG glycosylation. The alterations of IgG N-glycome, illustrated here for the first time in HDC, demonstrate a biomarker potential, which may shed light on future studies investigating their potential for monitoring or preventing the progression from HTN or T2DM towards HDC.

Background: The relationship of immunoglobulin G (IgG) glycosylation with diabetes and diabetic nephropathy has been reported, but its role in diabetic retinopathy (DR) remains unclear. We aimed to investigate and validate the association of IgG glycosylation with DR.Methods: We analyzed the IgG N‐linked glycosylation profile and primarily selected candidate glycans by lasso (least absolute shrinkage and selection operator) regression analysis in the discovery population. The findings were validated in the replication population using a binary logistics model. The association between the significant glycosylation panel and clinical features was illustrated with Spearman's coefficient. The results were confirmed by sensitivity analyses.Results: Among 16 selected glycan candidates using lasso, two IgG glycans (GP15, GP20) and two derived traits (IGP32, IGP54) were identified and validated to be significantly associated with DR (P < .05), and the combined adjusted odds ratios (ORs) were 0.587, 0.613, 1.970, and 0.593, respectively. The glycosylation panel showed a weak correlation with clinical features, except for age. In addition, the results remained consistent when the subjects with prediabetes were excluded from the controls, and the adjusted ORs were 0.677, 0.738, 1.597, and 0.678 in the whole population. Furthermore, in the 1:3 rematched population, a significant association was observed, apart from GP20.Conclusions: The IgG glycosylation profile, reflecting an aging and pro‐inflammatory status, was significantly associated with DR. The variation in the IgG glycome deserves more attention in diabetic complications.

Previous studies have reported the association between multiple genetic variants in enamel formation-related genes and the risk of dental caries with inconsistent results. We performed a systematic literature search of the PubMed, Cochrane Library, HuGE and Google Scholar databases for studies published before March 21, 2020 and conducted meta-, gene-based and gene-cluster analysis on the association between genetic variants in enamel-formation-related genes and the risk of dental caries. Our systematic literature search identified 21 relevant publications including a total of 24 studies for analysis. The genetic variant rs17878486 in AMELX was significantly associated with dental caries risk (OR=1.40, 95% CI: 1.02-1.93, P =0.037). We found no significant association between the risk of dental caries with rs12640848 in ENAM (OR=1.15, 95% CI: 0.88-1.52, P =0.310), rs1784418 in MMP20 (OR=1.07, 95% CI: 0.76-1.49, P =0.702) and rs3796704 in ENAM (OR=1.06, 95% CI: 0.96-1.17, P =0.228). Gene-based analysis indicated that multiple genetic variants in AMELX showed joint association with the risk of dental caries (6 variants; P −5 ), so did genetic variants in MMP13 (3 variants; P =0.004), MMP2 (3 variants; P −5 ), MMP20 (2 variants; P −5 ) and MMP3 (2 variants; P −5 ). The gene-cluster analysis indicated a significant association between the genetic variants in this enamel-formation gene cluster and the risk of dental caries ( P −5 ). The present meta-analysis revealed that genetic variant rs17878486 in AMELX were associated with dental caries, and multiple genetic variants in enamel-formation-related genes jointly contribute to the risk of dental caries, supporting the role of genetic variants in the enamel-formation genes in the etiology of dental caries.

Objectives: COVID-19 has caused a large global pandemic. Patients with COVID-19 exhibited considerable variation in disease behavior. Pervious genome-wide association studies have identified potential genetic variants involved in the risk and prognosis of COVID-19, but the underlying biological interpretation remains largely unclear. Methods: We applied the summary data-based Mendelian randomization (SMR) method to identify genes that were pleiotropically associated with the risk and various outcomes of COVID-19, including severe respiratory confirmed COVID-19 and hospitalized COVID-19. Results: In blood, we identified 2 probes, ILMN_1765146 and ILMN_1791057 tagging IFNAR2 , that showed pleiotropic association with hospitalized COVID-19 (β [SE] = 0.42 [0.09], P = 4.75×10 ⁻⁰⁶ and β [SE] = –0.48 [0.11], P = 6.76×10 ⁻⁰⁶ , respectively). Although no other probes were significant after correction for multiple testing in both blood and lung, multiple genes as tagged by the top 5 probes were involved in inflammation or antiviral immunity, and several other tagged genes, such as PON2 and HPS5 , were involved in blood coagulation. Conclusions: We identified IFNAR2 and other potential genes that could be involved in the susceptibility or prognosis of COVID-19. These findings provide important leads to a better understanding of the mechanisms of cytokine storm and venous thromboembolism in COVID-19 and potential therapeutic targets for the effective treatment of COVID-19.

Background: Observational 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. Methods: The study aims to investigate the bidirectional causal relations of COVID-19 with AF using two-sample Mendelian randomization (MR) analysis. Results: MR 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. Conclusion: Overall, 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.

Alternative N-glycosylation has significant structural and functional consequences on immunoglobulin G (IgG) and can affect immune responses, acting as a switch between pro- and anti-inflammatory IgG functionality. Studies have demonstrated that IgG N-glycosylation is associated with ageing, body mass index, type 2 diabetes and hypertension. Herein, we have demonstrated patterns of IgG glycosylation that are associated with blood lipids in a cross-sectional study including 598 Han Chinese aged 20–68 years. The IgG glycome composition was analysed by ultra-performance liquid chromatography. Blood lipids were positively correlated with glycan peak GP6, whereas they were negatively correlated with GP18 (P < 0.05/57). The canonical correlation analysis indicated that initial N-glycan structures, including GP4, GP6, GP9-12, GP14, GP17, GP18 and GP23, were significantly correlated with blood lipids, including total cholesterol, total triglycerides (TG) and low-density lipoprotein (r = 0.390, P < 0.001). IgG glycans patterns were able to distinguish patients with dyslipidaemia from the controls, with an area under the curve of 0.692 (95% confidence interval 0.644–0.740). Our findings indicated that a possible association between blood lipids and the observed loss of galactose and sialic acid, as well as the addition of bisecting GlcNAcs, which might be related to the chronic inflammation accompanying with the development and procession of dyslipidaemia.

Glycosylation significantly affects protein structure and function and thus participates in multiple physiologic and pathologic processes. Studies demonstrated that immunoglobulin G (IgG) N-glycosylation associates with the risk factors of ischemic stroke (IS), such as aging, obesity, dyslipidemia, type 2 diabetes, and hypertension. The study aimed to investigate the association between IgG N-glycosylation and IS in a Chinese population. IgG glycome composition in patients with IS (n = 78) and cerebral arterial stenosis (CAS) (n = 75) and controls (n = 77) were analyzed by ultra-performance liquid chromatography. Eleven initial glycans and 10 derived glycans in IgG glycome representing galactosylation, sialylation, and bisecting GlcNAc significantly differed between IS patients and CAS and healthy controls after controlling for gender, age, obesity, diabetes, hypertension, and dyslipidemia. Logistic regression models incorporating IgG glycan traits were able to distinguish IS from CAS (area under receiver–operator characteristic curves (AUC), 0.802; 95% confidence interval (CI), 0.732–0.872) and controls (AUC, 0.740; 95% CI, 0.661–0.819). The canonical correlation analysis indicated that initial N-glycan structures are significantly correlated with inflammation markers (r = 0.566, p < 0.001). Our findings indicated that loss of galactose and sialic acid, as well as addition of bisecting GlcNAc, might involve in pro- or anti-inflammatory IgG functionality and further contribute to the pathogenesis of IS. IgG glycan profiles may be developed as clinical useful biomarkers for chronic disease in the future.

Background: DNA methylation in sputum has been an attractive candidate biomarker for the non-invasive screening and detection of lung cancer. Materials and Methods: Databases including PubMed, Ovid, Cochrane library, Web of Science databases, Chinese Biological Medicine (CBM), Chinese National Knowledge Infrastructure (CNKI), Wanfang, Vip Databases and Google Scholar were searched to collect the diagnostic trials on aberrant DNA methylation in the screening and detection of lung cancer published until 1 December 2016. Indirect comparison meta-analysis was used to evaluate the diagnostic value of the included candidate genes. Results: The systematic literature search yielded a total of 33 studies including a total of 4801 subjects (2238 patients with lung cancer and 2563 controls) and covering 32 genes. We identified that methylated genes in sputum samples for the early screening and auxiliary detection of lung cancer yielded an overall sensitivity of 0.46 (0.41–0.50) and specificity of 0.83 (0.80–0.86). Combined indirect comparisons identified the superior gene of SOX17 (sensitivity: 0.84, specificity: 0.88), CDO1 (sensitivity: 0.78, specificity: 0.67), ZFP42 (sensitivity: 0.87, specificity: 0.63) and TAC1 (sensitivity: 0.86, specificity: 0.75). Conclusions: The present meta-analysis demonstrates that methylated SOX17, CDO1, ZFP42, TAC1, FAM19A4, FHIT, MGMT, p16, and RASSF1A are potential superior biomarkers for the screening and auxiliary detection of lung cancer.