Abstract
BackgroundIn epidemiological studies, it has been proven that the occurrence of type 2 diabetes mellitus (T2DM) is related to an increased risk of infectious diseases. However, it is still unclear whether the relationship is casual.MethodsWe employed a two-sample Mendelian randomization (MR) to clarify the causal effect of T2DM on high-frequency infectious diseases: sepsis, skin and soft tissue infections (SSTIs), urinary tract infections (UTIs), pneumonia, and genito-urinary infection (GUI) in pregnancy. And then, we analyzed the genome-wide association study (GWAS) meta-analysis of European-descent individuals and conducted T2DM-related single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs) that were associated with genome-wide significance (p < 5 × 10–8). MR estimates were obtained using the inverse variance-weighted (IVW), the MR-Egger regression, the simple mode (SM), weighted median, and weighted mode.ResultsThe UK Biobank (UKB) cohort (n > 500,000) provided data for GWASs on infectious diseases. MR analysis showed little evidence of a causal relationship of T2DM with five mentioned infections’ (sepsis, SSTI, UTI, pneumonia, and GUI in pregnancy) susceptibility [odds ratio (OR) = 0.99999, p = 0.916; OR = 0.99986, p = 0.233; OR = 0.99973, p = 0.224; OR = 0.99997, p = 0.686; OR, 1.00002, p = 0.766]. Sensitivity analysis showed similar results, indicating the robustness of causality. There were no heterogeneity and pleiotropic bias.ConclusionT2DM would not be causally associated with high-frequency infectious diseases (including sepsis, SSTI, UTI, pneumonia, and GUI in pregnancy).
Highlights
Infections are responsible for more than 20% of deaths worldwide, with approximately 245,000 sepsis cases in the United Kingdom in 2017 (Rudd et al, 2020)
type 2 diabetes mellitus (T2DM) would not be causally associated with high-frequency infectious diseases
The inverse variance-weighted (IVW) method showed no obvious heterogeneity (p = 0.785) between T2DM and sepsis and that there was no association between them (OR = 0.99999; 95% CI, 0.99982–1.00016; p = 0.916)
Summary
Infections are responsible for more than 20% of deaths worldwide, with approximately 245,000 sepsis cases in the United Kingdom in 2017 (Rudd et al, 2020). Infections share risk factors with a non-communicable disease or are triggers for them, making it difficult to disentangle their underlying causes (Parks et al, 2012; Remais et al, 2013; Leung et al, 2017) One such non-communicable disease is type 2 diabetes mellitus (T2DM), a condition affecting close to 465 million people across the globe (Boulton, 2020). While undoubtedly associated with sepsis and other infections, it is not aligned in all studies (Valdez et al, 1999; Bertoni et al, 2001; Shah and Hux, 2003; Thomsen et al, 2004, 2005; Gregg et al, 2014) These findings were subject to confounding and reverse causation bias.
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