Study participants and study design
In the present study, data were collected from a community-based cohort, cross-sectional study from Xuanwu Hospital, in Beijing (from September 2009 to September 2012 of the baseline population). Detailed study design and assessment methods were described in the previous study[13, 27]. Written informed consent was obtained from each subject at the beginning of the study, and the study has been approved by the Ethics Committee of the Capital Medical University, Beijing, China. The ethics approval was given in compliance with the Declaration of Helsinki.
The network MR study included two major components. First, we explored the casual IgG N-glycosylation for T2D and hypertension and the IgG N-glycosylation-QTLs determined IgG N-glycosylation as instrument variables (IVs) for T2D and hypertension. In our present study, the network MR exploring the causal pathway from IgG N-glycosylation to the outcome was proposed to use the IgG N-glycosylation-QTLs determined IgG N-glycosylation as IVs for the mediator (T2D or hypertension). Second, the bidirectional association between T2D and hypertension were taken forward for further analyses to better
understand the relationship between IgG N-glycosylation, T2D and hypertension. As shown in Figure 1, the framework of the network with bidirectional MR analysis consists of 3 different MR tests that are all described below (I-III). First, the causal effects of IgG
N-glycosylation-QTLs determined IgG N-glycosylation on T2D and hypertension are analyzed (I). Next, the causal effects of IgG N-glycosylation-QTLs determined T2D on hypertension is estimated (II). Finally, the causal effects of IgG N-glycosylation-QTLs determined hypertension on T2D is analyzed (III).
All participants were required to undergo physical examination that included anthropometric and biochemical measurements, as delineated in previous study. After an overnight fasting, two tubes of blood (5 mL) were collected in the morning by venipuncture. One sample was taken in vacuum negative pressure tubes not containing ethylene diamine tetraacetic acid (EDTA) to acquire serum (2 mL), which was used to detect the blood biochemistry indexes, and the other sample was taken in vacuum negative pressure tubes containing EDTA. The whole blood was centrifuged at 3000 rpm for 10 min, then the plasma (3 mL) was separated which was used to measure IgG N-glycosylation and the blood cells (2 mL) was separated which was used to detect genetic variants. All collected blood samples were processed within 8 h and stored at − 80°C until further measurement.
Demographic characteristics of participants, including age, gender, and ethnicity, were collected by a questionnaire. Anthropometric measurements (height, weight) were conducted with the participants wearing only light indoor clothing and without shoes. Body mass index (BMI) was calculated by the formula: weight (kg)/height2 (m2). Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured three times on the right arm in a day with a standard mercury sphygmomanometer and subjects were required to rest at least 5 minutes for each measurement. The participants were then classified into the hypertension group (mean SBP ≥ 140 mmHg or mean DBP ≥ 90 mmHg) or the normal blood pressure group (mean SBP < 120 mmHg and mean DBP < 80 mmHg). The fasting blood glucose (FBG) concentrations were measured by the glucose oxidase-peroxidase method (Mind Bioengineering Co. Ltd., Shanghai, China). Diagnosis of T2D was made by physicians according to the 1999 WHO Criteria (FBG greater than or equal to 7.0 mmol/L).
Genotyping and genotype imputation
The genotyping procedures were conducted with Illumina Omni Zhonghua chips (Illumina, San Diego, CA, USA). Quality control was conducted as described previously. Genotypes were imputed from the 1000 Genomes Project panel phase 3 based on East Asian population using Michigan Imputation Server. SNP with minor allele frequency (MAF) > 0.01 and imputation quality ratio > 0.3 were retained, yielding 7,108,659 imputed SNPs that were used for further IgG N-glycan-QTL mapping. Based on not facing up with the problem of population stratification, we did not correct the principal component.
The IgG N-glycan profile analysis was performed by the method of hydrophilic interaction chromatography-Ultra Performance Liquid Chromatography. The protocol of the method was reported as described in detail previously. Finally, 24 glycan peaks (GPs, GP1-GP24) were used for further IgG N-glycan-QTL mapping. The structures of glycans in each peak were reported as described in detail previously. For controlling the experimental variability, we adopted normalization methods and batch correction to process the glycan data so that all samples are comparable.
Statistical and bioinformatics analysis
The first MR analyses was aimed to evaluate the potential causal relationship IgG N-glycans of T2D and hypertension. IgG N-glycans-QTLs analysis was performed to select IVs for 24 IgG N-glycans. Briefly, linear regression was conducted to test the association between each SNP and IgG N-glycan, with each IgG N-glycan as the dependent variable of interest and the SNP as the independent variable, adjusted for age, sex and BMI. In addition, the GWAS analysis of T2D and hypertension were performed adjusting the effect of same confounders including age, sex and BMI. A relatively conservative Bonferroni correction was used (i.e., P < 0.05/1,000,000 = 5 × 10−8). Since various IgG N-glycans are highly correlated, and the mechanism regulating IgG N-glycosylation is not specific[30, 31], we have not been ruled out IgG N-glycan-QTLs overlapped between GPs. However, as many significant IgG N-glycan-QTLs are in high linkage disequilibrium, we pruned the IgG N-glycan-QTLs at LD r2<0.1. The LD proxies were defined using 1000 genomes East Asian samples. MR analysis was undertaken by inverse-variance weighted (IVW) regression with IgG N-glycan as the exposure, T2D or hypertension as the outcome, and the relevant IgG N-glycan-QTL variants as the IVs. Then these IgG N-glycan-QTLs corresponding to the casual IgG N-glycan for T2D or hypertension were as IVs for T2D or hypertension.
For forward MR, we used a conventional inverse-variance weighted (IVW) MR analysis, in which the IgG N-glycan-QTL SNPs-T2D estimate was regressed on the SNPs-hypertension estimate with the intercept term set to zero, weighted by the inverse-variance of SNPs-hypertension estimate, and vice versa for reverse MR. The heterogeneity between SNPs was estimated by Cochran Q statistic. Random-effects IVW model was used if heterogeneity existed, otherwise fixed-effects IVW model was performed. We also conducted MR-Egger and weighted median methods of MR analyses to test the robustness of the results. In addition, the MR-Egger method was used to assess the robustness of estimates to potential violations of the standard IV assumptions attributing from the directional pleiotropy. To investigate the influence of outlying or pleiotropic genetic variants, we performed a leave-one out analysis, in which 1 SNP was omitted in turn.
Data cleaning and statistical analysis was performed using R version 3.3.3 and PLINK 1.9. P < 0.05 was considered as suggestive of evidence for a potential association.