Emergency Department, The Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, Sichuan, China.
Department of Geriatrics, West China Hospital, Sichuan University, Chengdu, China.
Front Endocrinol (Lausanne). 2023 Mar 31;14:1135726. doi: 10.3389/fendo.2023.1135726. eCollection 2023.
Type 1 diabetes mellitus (T1DM) is associated with different types of infections; however, studies on the causal relationship between T1DM and infectious diseases are lacking. Therefore, our study aimed to explore the causalities between T1DM and six high-frequency infections using a Mendelian randomization (MR) approach.
Two-sample MR studies were conducted to explore the causalities between T1DM and six high-frequency infections: sepsis, acute lower respiratory infections (ALRIs), intestinal infections (IIs), infections of the genitourinary tract (GUTIs) in pregnancy, infections of the skin and subcutaneous tissues (SSTIs), and urinary tract infections (UTIs). Data on summary statistics for T1DM and infections were obtained from the European Bioinformatics Institute database, the United Kingdom Biobank, FinnGen biobank, and Medical Research Council Integrative Epidemiology Unit. All data obtained for summary statistics were from European countries. The inverse-variance weighted (IVW) method was employed as the main analysis. Considering the multiple comparisons, statistical significance was set at p< 0.008. If univariate MR analyses found a significant causal association, multivariable MR (MVMR) analyses were performed to adjust body mass index (BMI) and glycated hemoglobin (HbA1c). MVMR-IVW was performed as the primary analysis, and the least absolute shrinkage and selection operator (LASSO) regression and MVMR-Robust were performed as complementary analyses.
MR analysis showed that susceptibility to IIs increased in patients with T1DM by 6.09% using the IVW-fixed method [odds ratio (OR)=1.0609; 95% confidence interval (CI): 1.0281-1.0947, p=0.0002]. Results were still significant after multiple testing. Sensitivity analyses did not show any significant horizontal pleiotropy or heterogeneity. After adjusting for BMI and HbA1c, MVMR-IVW (OR=1.0942; 95% CI: 1.0666-1.1224, p<0.0001) showed significant outcomes that were consistent with those of LASSO regression and MVMR-Robust. However, no significant causal relationship was found between T1DM and sepsis susceptibility, ALRI susceptibility, GUTI susceptibility in pregnancy, SSTI susceptibility, and UTI susceptibility.
Our MR analysis genetically predicted increased susceptibility to IIs in T1DM. However, no causality between T1DM and sepsis, ALRIs, GUTIs in pregnancy, SSTIs, or UTIs was found. Larger epidemiological and metagenomic studies are required to further investigate the observed associations between the susceptibility of certain infectious diseases with T1DM.
1 型糖尿病(T1DM)与多种类型的感染有关;然而,关于 T1DM 与传染病之间因果关系的研究尚缺乏。因此,我们通过孟德尔随机化(MR)方法研究旨在探索 T1DM 与六种高频感染之间的因果关系。
进行两样本 MR 研究,以探索 T1DM 与六种高频感染之间的因果关系:败血症、急性下呼吸道感染(ALRI)、肠道感染(II)、妊娠时的泌尿生殖道感染(GUTI)、皮肤和皮下组织感染(SSTI)以及尿路感染(UTI)。T1DM 和感染的汇总统计数据从欧洲生物信息学研究所数据库、英国生物银行、芬兰遗传生物库和医学研究理事会综合流行病学单位获得。所有汇总统计数据均来自欧洲国家。采用逆方差加权(IVW)方法作为主要分析。考虑到多次比较,统计显著性设定为 p<0.008。如果单变量 MR 分析发现有显著的因果关联,则进行多变量 MR(MVMR)分析以调整体重指数(BMI)和糖化血红蛋白(HbA1c)。MVMR-IVW 作为主要分析,最小绝对收缩和选择算子(LASSO)回归和 MVMR-Robust 作为补充分析。
MR 分析显示,使用 IVW 固定方法,1 型糖尿病患者的 II 易感性增加了 6.09%[比值比(OR)=1.0609;95%置信区间(CI):1.0281-1.0947,p=0.0002]。经过多次测试,结果仍然显著。敏感性分析未显示任何明显的水平偏倚或异质性。在调整 BMI 和 HbA1c 后,MVMR-IVW(OR=1.0942;95%CI:1.0666-1.1224,p<0.0001)显示出与 LASSO 回归和 MVMR-Robust 一致的显著结果。然而,未发现 T1DM 与败血症易感性、ALRI 易感性、妊娠时 GUTI 易感性、SSTI 易感性和 UTI 易感性之间存在因果关系。
我们的 MR 分析从遗传学上预测了 T1DM 患者 II 易感性增加。然而,没有发现 T1DM 与败血症、ALRI、妊娠时 GUTI、SSTI 或 UTI 之间存在因果关系。需要更大规模的流行病学和宏基因组学研究来进一步探讨某些传染病与 T1DM 之间的观察到的关联。