Background: In 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.Methods: We 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.Results: The 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.Conclusion: T2DM would not be causally associated with high-frequency infectious diseases (including sepsis, SSTI, UTI, pneumonia, and GUI in pregnancy).

Background: Sepsis is defined as a life-threatening syndrome caused by an unbalanced host response to infection. The role of interleukin (IL)-36 cytokines binding to the IL-36 receptor (IL-36R) in host response during sepsis remains unknown. Methods: Serum IL-36 level was measured in 47 septic patients sampled on the day of intensive care unit (ICU) and emergency department admission, 21 non-septic ICU patient controls, and 21 healthy volunteers. In addition, the effects of IL-36R deletion on host inflammatory response in cecal ligation and puncture (CLP)-induced polymicrobial sepsis was determined. Results: On the day of ICU and emergency department admission, the patients with sepsis showed a significant increase in serum IL-36 levels compared with ICU patient controls and healthy volunteers, and the serum IL-36 levels were related to the severity of sepsis. Non-survivors of septic patients displayed significantly lower serum IL-36 levels compared with survivors. A high serum IL-36 level in ICU and emergency department admission was associated with 28-day mortality, and IL-36 was found to be an independent predictor of 28-day mortality in septic patients by logistic regression analysis. Furthermore, IL-36R deletion increased lethality in CLP-induced polymicrobial sepsis. Septic mice with IL-36R deletion had higher bacterial load and demonstrated more severe multiple organ injury (including lung, liver, and kidney) as indicated by clinical chemistry and histopathology. Mechanistically, IL-36R ligands released upon lung damage activated IL-36R⁺lung fibroblasts thereby inducing expression of the antimicrobial protein lipocalin 2. Moreover, they induced the apoptosis of lung epithelial cells. Conclusions: Septic patients had elevated serum IL-36 levels, which may correlate with disease severity and mortality. In experimental sepsis, we demonstrated a previously unrecognized role of IL-36R deletion in increasing lethality.

Background: Previous studies have observed inconsistent associations between coronavirus disease 2019 (COVID-19) and heart failure (HF), but these studies were prone to bias based on reverse causality and residual confounding factors. We aimed to investigate genetic liability between COVID-19 and heart failure using a bidirectional Mendelian randomization study. Methods: The causal relationship between COVID-19 (including COVID-19, hospitalized COVID-19 compared with the general population, and severe COVID-19) and HF are determined by using a bidirectional Mendelian randomization analysis. We drew on summary statistics from the largest HF genome-wide association study (GWAS) meta-analysis on individuals of European ancestry, which included 47,309 HF patients and 930,014 controls. The inverse variance weighted (IVW), an adaption of the Egger regression (MR-Egger), the weighted median, and weighted model were conducted for the Mendelian randomization analysis to estimate a causal effect. To confirm the stability, we performed a “leave-one-out” approach for the sensitivity analysis. Results: Genetically predicted severe COVID-19 was not significantly associated with the risk of HF [odds ratio (OR), 1.003; 95% confidence interval (CI), 0.969–1.037; p = 0.867]. The IVW demonstrated that there was no association between genetically hospitalized COVID-19 infection and HF risk [OR, 1.009; 95% CI, 0.939–1.085; p = 0.797]. There was no evidence to support the association between genetically determined COVID-19 and the risk of HF [OR, 1.066; 95% CI, 0.955–1.190; p = 0.253]. In addition, genetically predicted HF was also not causally associated with COVID-19 [OR, 1.162; 95% CI, 0.824–1.639; p = 0.393]. MR-Egger analysis indicated no evidence of directional pleiotropy. Conclusion: The current bidirectional Mendelian randomization analysis overcomes the limitations of observational studies. Our findings indicated that there is no causal association between COVID-19 and HF.

Background: Sepsis is a life-threatening syndrome caused by an imbalance in the inflammatory response to an infection that can lead to a high mortality rate. Escherichia coli is a common pathogen that causes sepsis. The role of immunoglobulin G N-glycome in estimating the mortality in patients with sepsis remains unknown. This study aims to reveal the clinical application of immunoglobulin G N-glycome as a potentially novel biomarker to predict mortality risk in Escherichia coli-induced sepsis.Methods: The serum immunoglobulin G N-glycome levels in 100 adult septic patient serum samples on the day of intensive care unit (ICU) admission, and 100 healthy volunteers were measured and analyzed. Immunoglobulin G N-glycome was compared with existing risk scores on predicting in-hospital death.Results: We identified that the fucosylation level was significantly decreased in patients. Importantly, bisecting GlcNAc, sialylation, and galactosylation have different levels between sepsis and control groups. In addition, the AUC values of the SOFA score combined with GP4, GP5, and GP9 were 0.76 (95%CI: 0.61 to 0.90), 0.58 (95%CI: 0.40 to 0.7) and 0.57 (95%CI: 0.38 to 0.76). The AUC value of the SOFA score combined with GP4 and GP7 was 0.85 (95%CI: 0.76 to 0.93) in predicting in-hospital mortality in patients with sepsis.Conclusions: Immunoglobulin G N-glycome concentrations at ICU admission are valuable for predicting the in-hospital mortality risk of patients with sepsis, suggesting that immunoglobulin G N-glycome may be a novel biomarker.

Background The phospholipid-modifying enzyme MBOAT2 plays a crucial role in iron homeostasis by inhibiting iron sequestration, thus preventing iron-induced cell death. It achieves this by remodeling the phospholipid composition of cell membranes through phospholipid metabolism. Although multiple studies have highlighted the significance of MBOAT2 in tumorigenesis, a comprehensive pan-cancer analysis has not been conducted to date. Methods In this study, we analyzed the expression levels of MBOAT2 using RNA sequencing data from the TCGA and GTEx databases. We also investigated MBOAT2 protein information using resources such as the Human Protein Atlas (HPA), GeneCards, and String databases. To assess the prognostic value of MBOAT2, we conducted survival analysis based on clinical data from TCGA. Additionally, we performed enrichment analysis using the R package “clusterProfiler” and explored the relationship between MBOAT2 expression and immune cell infiltration, as well as immune checkpoint interactions in TCGA datasets. Furthermore, we examined the correlation between MBOAT2 expression and clinical pathology through immunohistochemical analysis of breast, prostate, lung, and liver cancer tissues in the HPA database. Finally, western blotting was used to validate MBOAT2 protein expression in breast and prostate cancer cell lines. Results Our analysis revealed that MBOAT2 was highly expressed in a wide range of cancer types, with its expression correlating with improved survival outcomes in the TCGA dataset. Moreover, we found a significant association between MBOAT2 expression and immune regulation, particularly in relation to immune cell infiltration and immune checkpoint interactions. Conclusion MBOAT2 holds promise as a prognostic biomarker and may serve as a target for immunotherapy in various malignancies. Further investigation into its role in cancer immunity could offer new insights into potential therapeutic strategies.

Maternal sepsis and maternal infections (MSMI) are significant causes of maternal mortality in low- and middle-income countries (LMICs). This study, leveraging data from the Global Burden of Disease Study 2023 (GBD 2023), intended to evaluate the trends in the disease burden of MSMI in LMICs from 1990 to 2023, along with its inequality characteristics and future trends. Based on the GBD 2023 database, data on the incidence, prevalence, mortality, and disability-adjusted life years (DALYs) rates of MSMI in 129 LMICs from 1990 to 2023 were extracted. Joinpoint regression, decomposition analysis, and health inequality analysis were employed to evaluate changes in disease burden and their driving factors. An autoregressive integrated moving average (ARIMA) model was established to predict trends in disease burden from 2024 to 2035. From 1990 to 2023, the relative burden of MSMI in LMICs generally declined, and the most pronounced decrease was observed in the DALYs rate (estimated annual percentage change (estimated annual percentage change (EAPC) = -3.11, 95% confidence interval (CI): -3.26 to -2.95). However, the absolute burden showed a divergent trend. Specifically, the number of incident cases and prevalent cases increased by 24% and 33%, respectively, while the number of deaths and DALYs decreased by 37% and 39%, respectively. Stratified analysis uncovered that the burden worsened in low-income (gross national income (GNI)-L) countries (with incident cases and prevalent cases rising by 126% and 109%, respectively), whereas decreases were more significant in upper-middle-income (GNI-UM) countries (with deaths and DALYs decreasing by 83% and 81%, respectively). The increased burden in GNI-L countries was primarily driven by population growth, with relative contributions to the incidence burden and prevalence burden of 121.6% and 136.5%, respectively. In addition, widening health inequalities were observed. The concentration indexes for the DALYs rate and mortality rate decreased from -0.392 to -0.594 and from -0.395 to -0.603, respectively. ARIMA projections indicated that while the mortality rate was expected to continue to decline from 2024 to 2035 (with an average annual decrease of -6.4%), the decrease in the incidence rate was projected to be limited (with an average annual decrease of -0.82%). Over the past three decades, while the overall burden of MSMI in LMICs has decreased, the control of its absolute burden remains insufficient. GNI-L countries continue to bear a higher burden and experience widening health inequalities. Future prevention and control efforts should not only focus on continuously reducing the overall burden but also prioritize targeted resource allocation for GNI-L countries. Moreover, equity should be integrated into routine monitoring and evaluation systems.