Yang Yi, Ma Xianli, Pang Weiyi, Jiang Caina
Guangxi Engineering Research Center for Pharmaceutical Molecular Screening and Druggability Evaluation, Guilin Medical University, Guilin 541199, China.
School of Pharmacy, Guilin Medical University, Guilin 541199, China.
Toxics. 2023 Feb 13;11(2):171. doi: 10.3390/toxics11020171.
Epidemiological studies have linked particulate matter (PM2.5) to gestational diabetes mellitus (GDM). However, the causality of this association has not been established; Mendelian randomization was carried out using summary data from genome-wide association studies (GWAS). For the analysis of the causal relationship between PM2.5 and GDM, the inverse variance weighted (IVW) method was used. The exposure data came from a GWAS dataset of IEU analysis of the United Kingdom Biobank phenotypes consisting of 423,796 European participants. The FinnGen consortium provided the GDM data, which included 6033 cases and 123,000 controls. We also performed multivariate MR (MVMR), adjusting for body mass index (BMI) and smoking. As a result, we found that each standard deviation increase in PM2.5 is associated with a 73.6% increase in the risk of GDM (OR: 1.736; 95%CI: 1.226-2.457). Multivariable MR analysis showed that the effect of PM2.5 on GDM remained after accounting for BMI and smoking. Our results demonstrate a causal relationship between PM2.5 and GDM.
流行病学研究已将细颗粒物（PM2.5）与妊娠期糖尿病（GDM）联系起来。然而，这种关联的因果关系尚未确立；利用全基因组关联研究（GWAS）的汇总数据进行了孟德尔随机化分析。为了分析PM2.5与GDM之间的因果关系，采用了逆方差加权（IVW）方法。暴露数据来自对英国生物银行表型进行IEU分析的GWAS数据集，该数据集包含423796名欧洲参与者。芬兰基因联盟提供了GDM数据，其中包括6033例病例和123000例对照。我们还进行了多变量孟德尔随机化分析（MVMR），对体重指数（BMI）和吸烟情况进行了校正。结果发现，PM2.5每增加一个标准差，GDM风险就会增加73.6%（比值比：1.736；95%置信区间：1.226 - 2.457）。多变量孟德尔随机化分析表明，在考虑BMI和吸烟因素后，PM2.5对GDM的影响依然存在。我们的研究结果证明了PM2.5与GDM之间存在因果关系。
