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Background: Previous observational studies have demonstrated a connection between the risk of Type 2 diabetes mellitus (T2DM) and gastrointestinal problems brought on by Helicobacter pylori (H. pylori) infection. However, little is understood about how these factors impact on T2DM. Method: This study used data from the GWAS database on H. pylori antibodies, gastroduodenal ulcers, chronic gastritis, gastric cancer, T2DM and information on potential mediators: obesity, glycosylated hemoglobin (HbA1c) and blood glucose levels. Using univariate Mendelian randomization (MR) and multivariate MR (MVMR) analyses to evaluate the relationship between H. pylori and associated gastrointestinal diseases with the risk of developing of T2DM and explore the presence of mediators to ascertain the probable mechanisms. Results: Genetic evidence suggests that H. pylori IgG antibody (P = 0.006, b = 0.0945, OR = 1.0995, 95% CI = 1.023–1.176), H. pylori GroEL antibody (P = 0.028, OR = 1.033, 95% CI = 1.004–1.064), gastroduodenal ulcers (P = 0.019, OR = 1.036, 95% CI = 1.006–1.068) and chronic gastritis (P = 0.005, OR = 1.042, 95% CI = 1.012–1.074) are all linked to an increased risk of T2DM, additionally, H. pylori IgG antibody is associated with obesity (P = 0.034, OR = 1.03, 95% CI = 1.002–1.055). The results of MVMR showed that the pathogenic relationship between H. pylori GroEL antibody and gastroduodenal ulcer in T2DM is mediated by blood glucose level and obesity, respectively. Conclusion: Our study found that H. pylori IgG antibody, H. pylori GroEL antibody, gastroduodenal ulcer and chronic gastritis are all related to t T2DM, and blood glucose level and obesity mediate the development of H. pylori GroEL antibody and gastroduodenal ulcer on T2DM, respectively. These findings may inform new prevention and intervention strategies for T2DM. [ABSTRACT FROM AUTHOR]

Background: Previous observational studies have demonstrated a correlation between metabolic syndrome related diseases and an elevated susceptibility to ulcers of lower limb. It has been suggested that this causal relationship may be influenced by the presence of peripheral artery disease (PAD). Nevertheless, the precise contribution of these factors as determinants of ulcers of lower limb remains largely unexplored., Method: This research incorporated information on hypertension, BMI, hyperuricemia, type 2 diabetes, PAD, and ulcers of lower limb sourced from the GWAS database. Univariate Mendelian randomization (SVMR) and multivariate Mendelian randomization (MVMR) methods were employed to assess the association between metabolic syndrome related diseases, including hypertension, obesity, hyperuricemia, and type 2 diabetes, as well as to investigate whether this association was influenced by PAD., Results: Univariate Mendelian randomization analysis showed that genetically predicted hypertension, BMI, and type 2 diabetes were associated with an increased risk of PAD and ulcers of lower limb, and PAD was associated with an increased risk of ulcers of lower limb, but there is no causal relationship between hyperuricemia and ulcers of lower limb. The results of multivariate Mendelian randomization showed that PAD mediated the causal relationship between hypertension, obesity and ulcers of lower limb, but the relationship between type 2 diabetes and ulcers of lower limb was not mediated by PAD., Conclusion: Hypertension, BMI and type 2 diabetes can increase the risk of ulcers of lower limb, and PAD can be used as a mediator of hypertension and obesity leading to ulcers of lower limb, These findings may inform prevention and intervention strategies directed toward metabolic syndrome and ulcers of lower limb., Competing Interests: 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., (Copyright © 2024 Wang, Zhang, Zou, Zhang, Jia, Zhao, Han, Sun, Zhang, Zong and Wang.)

Background: Diabetic osteoporosis exhibits heterogeneity at the molecular level. Ferroptosis, a controlled form of cell death brought on by a buildup of lipid peroxidation, contributes to the onset and development of several illnesses. The aim was to explore the molecular subtypes associated with ferroptosis in diabetic osteoporosis at the molecular level and to further elucidate the potential molecular mechanisms., Methods: Integrating the CTD, GeneCards, FerrDb databases, and the microarray data of GSE35958, we identified ferroptosis-related genes (FRGs) associated with diabetic osteoporosis. We applied unsupervised cluster analysis to divide the 42 osteoporosis samples from the GSE56814 microarray data into different subclusters based on FRGs. Subsequently, FRGs associated with two ferroptosis subclusters were obtained by combining database genes, module-related genes of WGCNA, and differentially expressed genes (DEGs). Eventually, the key genes from FRGs associated with diabetic osteoporosis were identified using the least absolute shrinkage and selection operator (LASSO), Boruta, support vector machine recursive feature elimination (SVM - RFE), and extreme gradient boosting (XGBoost) machine learning algorithms. Based on ROC curves of external datasets (GSE56815), the model's efficiency was examined., Results: We identified 15 differentially expressed FRGs associated with diabetic osteoporosis. In osteoporosis, two distinct molecular clusters related to ferroptosis were found. The expression results and GSVA analysis indicated that 15 FRGs exhibited significantly different biological functions and pathway activities in the two ferroptosis subclusters. Therefore, we further identified 17 FRGs associated with diabetic osteoporosis between the two subclusters. The results of the comprehensive analysis of 17 FRGs demonstrated that these genes were heterogeneous and had a specific interaction between the two subclusters. Ultimately, the prediction model had a strong foundation and excellent AUC values (0.84 for LASSO, 0.84 for SVM - RFE, 0.82 for Boruta, and 0.81 for XGBoost). IDH1 is a common gene to all four algorithms thus being identified as a key gene with a high AUC value (AUC = 0.698)., Conclusions: As a ferroptosis regulator, IDH1 is able to distinguish between distinct molecular subtypes of diabetic osteoporosis, which may offer fresh perspectives on the pathogenesis of the disease's clinical symptoms and prognostic heterogeneity., Competing Interests: 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., (Copyright © 2023 Wang, Meng, Zhang, Zhao, Zou, Jia, Han, Zhao, Song, Zong, Wang, Qu and Lu.)