PubMed · 1467708
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J N Morris. 1992-10-31. Confounding in epidemiological studies.. https://doi.org/10.1136/bmj.305.6861.1097-a
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Neutrophil extracellular traps (NETs) -associated inflammatory traits play a significant role in type 2 diabetes mellitus (T2DM) and its complications. Notably, IL-6, a key inflammatory cytokine, is intricately linked to the formation of NETs and the pathogenesis of T2DM and its complications. This study aimed to explore the causal association between NETs-associated inflammatory traits and T2DM, as well as its complications, using a Mendelian Randomization (MR) approach. This study utilized a two-sample MR design with data from Genome-Wide Association Studies (GWAS), comprising a large European population-based meta-analysis for T2DM and its complications. The primary method of analysis was the inverse variance weighted (IVW) approach, complemented by MR-Egger regression, weighted median, and weighted mode methods. Sensitivity analyses included MR-Egger, MR-PRESSO, Cochran's Q, and leave-one-out methods to assess the robustness of the findings. The study indicated that genetically predicted levels of interleukin-6 (IL-6) were inversely associated with diabetic coronary artery disease (CAD) (OR = 0.8997, 95% CI: 0.8257-0.9803, P = 0.0158). Additionally, NETs showed significant associations with T2DM with renal complications (OR=0.97, 95% CI 0.9428-0.998, P = 0.0358) and T2DM with peripheral circulatory complications(OR = 1.0342, 95% CI 1.002-1.0673, P = 0.037). The significant IVW associations showed no evidence of heterogeneity or horizontal pleiotropy. This study suggests that genetically predicted NETs-associated inflammatory traits are associated with specific T2DM complications. Genetically predicted IL-6 was inversely associated with diabetic CAD, whereas NETs were associated with renal and peripheral circulatory complications in T2DM.
This study examined the mechanisms underlying the comorbidity between type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease (ASCVD), while identifying potential therapeutic targets. Common differentially expressed genes (C-DEGs) between T2DM and ASCVD were extracted from the GSE78721 and GSE12288 datasets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, protein-protein interaction (PPI) network construction, hub gene identification, and Drug-Gene Interaction Database (DGIdb) analysis were conducted. The association between hub C-DEGs and immune-infiltrating cells was analyzed using the CIBERSORT method. Expression levels of hub C-DEGs were quantified through qRT-PCR and Western blot analyses. A total of 32 C-DEGs were identified, comprising 20 upregulated and 12 downregulated genes. C-DEGs were predominantly enriched in key pathways, including viral myocarditis, arrhythmogenic right ventricular cardiomyopathy, hypertrophic cardiomyopathy, and dilated cardiomyopathy. PPI analysis revealed 29 nodes and 39 edges, leading to the identification of eight hub C-DEGs (HSP90B1, PLAU, SLPI, TOP3A, NCF4, PRF1, TUBA1C, and CS) across both datasets. Furthermore, hub C-DEGs (TOP3A, SLPI, NCF4, PRF1, and PLAU) demonstrated significant correlations with immune-infiltrating cell levels. Drugs specifically targeting these hub C-DEGs present promising candidates for the treatment of T2DM and ASCVD. Additionally, the expression of hub C-DEGs at both mRNA and protein levels was validated in patients with T2DM and ASCVD. An integrated bioinformatics analysis facilitated the screening of candidate therapeutic targets, mechanisms, and drugs for T2DM and ASCVD, offering new insights into molecular therapies for these conditions.
INTRODUCTION: The role of immune cells in type 2 diabetes mellitus (T2DM) development is well-studied, but their interactions with the gut microbiota and the mediating role in this process remain unclear. METHODS: We analyzed 731 immune cell phenotypes (3,757 Europeans), 473 gut microbiota traits (5,959 Finns), and T2DM data (over 400,000 Finns). Mendelian randomization (MR) was based on three assumptions: the instrumental variable (IV) is associated with exposure, IV is not influenced by confounding, and IV affects the outcome only through exposure. We selected single-nucleotide polymorphisms (SNPs) from genome-wide association studies as instrumental variables (IVs) to infer causal effects in two-sample MR analysis. RESULTS: We identified 36 immune cell phenotypes associated with T2DM, including 29 protective factors and seven risk factors, as well as 10 gut microbiota significantly linked to T2DM, with eight protective factors and two risk factors. MR revealed that five gut microbiota mediated the relationship between immune cells and T2DM. For example, the effects of CD3 on resting Treg (OR: 1.0136), CD3 on CM CD4+ (OR: 1.0180), and CD3 on naive CD4+ cells (OR: 1.0150) in T2DM were found to be partially mediated by the species Bacillus. AYThe corresponding mediation effect proportions were 8.99%, 11.8%, and 11.4%. DISCUSSION: MR analysis identified multiple gut microbiota mediators in the relationship between immune cells and T2DM, addressing previous observational evidence. Limitations included the European ancestry bias, among others. CONCLUSION: This study has highlighted the gut microbiota as a mediator between immune cells and T2DM, offering new insights for its early prevention and intervention.