多项研究已经证明了2型糖尿病(T2D)对各种人类疾病的影响;然而,其中大多数是观察性流行病学研究,这些研究存在许多潜在的偏见,包括报道的混杂和反向因果关系.在这篇文章中,我们调查了癌症和血管疾病是否会受到T2D相关性状的影响,包括空腹血糖(FPG),餐后2小时葡萄糖(2h-PG),糖化血红蛋白(HbA1c)水平,通过使用孟德尔随机化(MR)。FPG的汇总统计信息,2h-PG,和HbA1c水平是通过大规模全基因组关联研究的荟萃分析获得的,这些研究包括来自来自葡萄糖和胰岛素相关性状联盟研究的合作荟萃分析的133,010名非糖尿病个体的数据.此后,基于MR分析的统计假设,最可靠的方法,包括逆方差加权(IVW),MR-Egger,MR-Egger与模拟外推(SIMEX),加权中位数,和MR多效性残差和离群值(MR-PRESSO)方法用于鉴定受FPG影响的性状,2h-PG,和HbAlc。我们发现冠状动脉疾病受FPG的影响,根据IVW[对数比值比(logOR):0.21;P=0.012],MR-Egger(SIMEX)(逻辑:0.22;P=0.014),MR-PRESSO(对数:0.18;P=0.045),和加权中位数(logOR:0.29;P<0.001)方法,但不符合MR-Egger(logOR:0.13;P=0.426)方法。此外,低密度脂蛋白胆固醇水平受HbA1c影响,根据IVW[β(B):0.23;P=0.015),MR-Egger(B:0.45;P=0.046),MR-Egger(SIMEX)(B:0.27;P=0.007),MR-PRESSO(B;0.14;P=0.010),和加权中位数(B:0.15;P=0.012]方法。需要对相关生物学机制进行进一步研究,以验证和理解在每种性状的TD2相关因果效应中确定的疾病特异性差异。
Multiple studies have demonstrated the effects of type 2 diabetes (T2D) on various human diseases; however, most of these were observational epidemiological studies that suffered from many potential biases including reported confounding and reverse causations. In this article, we investigated whether cancer and vascular disease can be affected by T2D-related traits, including fasting plasma glucose (FPG), 2-h postprandial glucose (2h-PG), and glycated hemoglobin A1c (HbA1c) levels, by using Mendelian randomization (MR). The summary statistics for FPG, 2h-PG, and HbA1c level were obtained through meta-analyses of large-scale genome-wide association studies that included data from 133,010 nondiabetic individuals from collaborating Meta-analysis of Glucose and Insulin Related Traits Consortium studies. Thereafter, based on the statistical assumptions for MR analyses, the most reliable approaches including inverse-variance-weighted (IVW), MR-Egger, MR-Egger with a simulation extrapolation (SIMEX), weighted median, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods were applied to identify traits affected by FPG, 2h-PG, and HbAlc. We found that coronary artery disease is affected by FPG, as per the IVW [log odds ratio (logOR): 0.21; P = 0.012], MR-Egger (SIMEX) (logOR: 0.22; P = 0.014), MR-PRESSO (logOR: 0.18; P = 0.045), and weighted median (logOR: 0.29; P < 0.001) methods but not as per the MR-Egger (logOR: 0.13; P = 0.426) approach. Furthermore, low-density lipoprotein cholesterol levels are affected by HbA1c, as per the IVW [beta (B): 0.23; P = 0.015), MR-Egger (B: 0.45; P = 0.046), MR-Egger (SIMEX) (B: 0.27; P = 0.007), MR-PRESSO (B; 0.14; P = 0.010), and the weighted median (B: 0.15; P = 0.012] methods. Further studies of the associated biological mechanisms are required to validate and understand the disease-specific differences identified in the TD2-related causal effects of each trait.