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. 2023 Mar 31:14:1135726.
doi: 10.3389/fendo.2023.1135726. eCollection 2023.

Causal relationship between type 1 diabetes mellitus and six high-frequency infectious diseases: A two-sample mendelian randomization study

Xiao-Hong Chen  1 , Hong-Qiong Liu  2 , Qiong Nie  3 , Han Wang  4 , Tao Xiang  1
Affiliations

Causal relationship between type 1 diabetes mellitus and six high-frequency infectious diseases: A two-sample mendelian randomization study

Xiao-Hong Chen et al. Front Endocrinol (Lausanne). .

Abstract

Purpose: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Keywords: infections; intestinal; lower respiratory; mendelian randomization; pregnancy; sepsis; skin; urinary tract.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Three principles of the Mendelian randomization study. (I) The genetic instrumental variables (IVs) are strongly associated with T1DM; (II) The genetic IVs do not affect the outcome through the confounders; (III) The genetic IVs do not affect outcomes directly, but only via exposure. ALRIs, acute lower respiratory infections; IIs, intestinal infections; GUTIs, infections of the genitourinary tract; SSTIs, Infections of the skin and subcutaneous tissue; UTIs, urinary tract infections; T1DM, type 1 diabetes mellitus.
Figure 2
Figure 2
The funnel plot (A), scatter plot (B), Forest plot (C) and leave-one-out plot (D) of the genetic risk of T1DM on IIs.
Figure 3
Figure 3
The funnel plot (A), scatter plot (B), Forest plot (C) and leave-one-out plot (D) of the genetic risk of T1DM on sepsis.
Figure 4
Figure 4
The funnel plot (A), scatter plot (B), Forest plot (C) and leave-one-out plot (D) of the genetic risk of T1DM on ALRIs.
Figure 5
Figure 5
The funnel plot (A), scatter plot (B), Forest plot (C) and leave-one-out plot (D) of the genetic risk of T1DM on GUTIs in pregnancy.
Figure 6
Figure 6
The funnel plot (A), scatter plot (B), Forest plot (C) and leave-one-out plot (D) of the genetic risk of T1DM on SSTIs.
Figure 7
Figure 7
The funnel plot (A), scatter plot (B), Forest plot (C) and leave-one-out plot (D) of the genetic risk of T1DM on UTIs.
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