Jie Zhang

The role of metabolic traits in ischemic stroke (IS) has been explored through observational studies and a few Mendelian randomization (MR) studies employing limited methods in European populations. This study aimed to investigate the causal effects of metabolic traits on IS in both East Asian and European populations utilizing multiple MR methods based on genetic insights. Two-sample and multivariable MR were performed, and MR estimates were calculated as inverse-variance weighted (IVW), weighted median, and penalized weighted median. Pleiotropy was assessed by MR–Egger and Mendelian randomization pleiotropy residual sum and outlier tests. Systolic blood pressure (SBP) was associated with an increased risk of IS by IVW in both European (OR_IVW: 1.032, 95% CI: 1.026–1.038, p < 0.001) and Japanese populations (OR_IVW: 1.870, 95% CI: 1.122–3.116, p = 0.016), which was further confirmed by other methods. Unlike the European population, the evidence for the association of diastolic blood pressure (DBP) with IS in the Japanese population was not stable. No evidence supported an association between the other traits and IS (all Ps > 0.05) in both races. A positive association was found between SBP and IS in two races, while the results of DBP were only robust in Europeans.

Background: Immunoglobulin G (IgG) N-glycosylation is considered a potential biomarker for aging and various pathological conditions. However, whether these changes in IgG N-glycosylation are a consequence or a contributor to the aging process remains unclear. This study aims to investigate the causality between IgG N-glycosylation and aging using Mendelian randomization (MR) analysis. Methods: We utilized genetic variants associated with IgG N-glycosylation traits, the frailty index (FI), and leukocyte telomere length (LTL) from a previous genome-wide association study (GWAS) on individuals of European ancestry. Two-sample and multivariable MR analyses were conducted, employing the inverse-variance weighted (IVW) method. Sensitivity analyses were performed to assess potential confounding factors. Results: Using the IVW method, we found suggestive evidence of a causal association between GP14 and FI (β 0.026, 95% CI 0.003 to 0.050, p = 0.027) and LTL (β −0.020, 95% CI −0.037 to −0.002, p = 0.029) in the two-sample MR analysis. In the multivariable MR analysis, suggestive evidence was found for GP23 and FI (β −0.119, 95% CI −0.219 to −0.019, p = 0.019) and GP2 and LTL (β 0.140, 95% CI 0.020 to 0.260, p = 0.023). Conclusions: In conclusion, our results supported a potentially causal effect of lower GP23 levels on an advanced aging state. Additional verification is required to further substantiate the causal relationship between glycosylation and aging.

Background: Although the genetic susceptibility to diabetes and ischemic heart disease (IHD) has been well demonstrated, studies aimed at exploring gene variations associated with diabetic IHD are still limited; Methods: Our study included 204 IHD cases who had been diagnosed with diabetes before the diagnosis of IHD and 882 healthy controls. Logistic regression was used to find the association of candidate SNPs and polygenic risk score (PRS) with diabetic IHD. The diagnostic accuracy was represented with AUC. Generalized multifactor dimensionality reduction (GMDR) was used to illustrate gene-gene interactions; Results: For IL6R rs4845625, the CT and TT genotypes were associated with a lower risk of diabetic IHD than the CC genotype (OR = 0.619, p = 0.033; OR = 0.542, p = 0.025, respectively). Haplotypes in the AGER gene (rs184003-rs1035798-rs2070600-rs1800624) and IL6R gene (rs7529229-rs4845625-rs4129267-rs7514452-rs4072391) were both significantly associated with diabetic IHD. PRS was associated with the disease (OR = 1.100, p = 0.005) after adjusting for covariates, and the AUC were 0.763 (p < 0.001). The GMDR analysis suggested that rs184003 and rs4845625 were the best interaction model after permutation testing (p = 0.001) with a cross-validation consistency of 10/10; Conclusions: SNPs and haplotypes in the AGER and IL6R genes and the interaction of rs184003 and rs4845625 were significantly associated with diabetic IHD.

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.

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.

Background: In observational studies, 25 hydroxyvitamin D (25OHD) concentration has been associated with an increased risk of Coronavirus disease 2019 (COVID-19). However, it remains unclear whether this association is causal. Methods: We performed a two-sample Mendelian randomization (MR) to explore the causal relationship between 25OHD concentration and COVID-19, using summary data from the genome-wide association studies (GWASs) and using 25OHD concentration-related SNPs as instrumental variables (IVs). Results: MR analysis did not show any evidence of a causal association of 25OHD concentration with COVID-19 susceptibility and severity (OR=1.168, 95% CI 0.956-1.427; OR=0.889, 95% CI 0.549-1.439). Sensitivity analyses using different instruments and statistical models yielded similar findings, suggesting the robustness of the causal association. No obvious pleiotropy bias and heterogeneity were observed. Conclusion: The MR analysis showed that there might be no linear causal relationship of 25OHD concentration with COVID-19 susceptibility and severity.

Background: In observational studies, Alzheimer’s disease (AD) has been associated with an increased risk of Coronavirus disease 2019 (COVID-19), and the prognosis of COVID-19 can affect nervous systems. However, the causality between these conditions remains to be determined. Methods: This study sought to investigate the bidirectional causal relations of AD with COVID-19 using two-sample Mendelian randomization (MR) analysis. Results: We found that genetically predicted AD was significantly associated with higher risk of severe COVID-19 (odds ratio [OR], 3.329; 95% confidence interval [CI], 1.139-9.725; P =0.028). It’s interesting that genetically predicted severe COVID-19 was also significantly associated with higher risk of AD (OR, 1.004; 95% CI, 1.001-1.007; P =0.018). In addition, the two strong genetic variants associated with severe COVID-19 was associated with higher AD risk (OR, 1.018; 95% CI, 1.003-1.034; P =0.018). There is no evidence to support that genetically predicted AD was significantly associated with COVID-19 susceptibility, and vice versa. No obvious pleiotropy bias and heterogeneity were observed. Conclusion: Overall, AD may causally affect severe COVID-19, and vice versa, performing bidirectional regulation through independent biological pathways.